ALBERT

Description: ABSTRACT Atmospheric models such as the Weather Research and Forecasting (WRF) model provide a tool to evaluate the behavior of regional hydrological cycle components, including precipitation, evapotranspiration, soil water storage and runoff. Recent model developments have focused on coupled atmospheric‐hydrological modeling systems, such as WRF‐Hydro, in order to account for subsurface, overland, and river flow and potentially improve the representation of land‐atmosphere interactions. The aim of this study is to investigate the contribution of lateral terrestrial water flow to the regional hydrological cycle, with the help of a joint soil‐vegetation‐atmospheric water tagging (SVA‐TAG) procedure newly developed in the so‐called WRF‐tag and WRF‐Hydro‐tag models. An application of both models for the high precipitation event on 15 August 2008 in the German and Austrian parts of the upper Danube river basin (94,100 km2) is presented. The precipitation that fell in the basin during this event is considered as a water source, is tagged and subsequently tracked for a 40 month‐period until December 2011. At the end of the study period, in both simulations, approximately 57% of the tagged water has run off, while 41% has evaporated back to the atmosphere, including 2% that has recycled in the upper Danube river basin as precipitation. In WRF‐Hydro‐tag, the surface evaporation of tagged water is slightly enhanced by surface flow infiltration, and slightly reduced by subsurface lateral water flow in areas with low topography gradients. This affects the source precipitation recycling only in a negligible amount.

Description: Abstract Snow acts as a vital source of water especially in areas where streamflow relies on snowmelt. The spatio‐temporal pattern of snow cover has tremendous value for snowmelt modeling. Instantaneous snow extent can be observed by remote sensing. Cloud cover often interferes. Many complex methods exist to resolve this, but often have requirements which delay the availability of the data and prohibit its use for real‐time modeling. In this research, we propose a new method for spatially modeling snow cover throughout the melting season. The method ingests multiple years of MODIS snow cover data and combines it using principal component analysis (PCA) to produce a spatial melt‐pattern model. Development and application of this model relies on the inter‐annual recurrence of the seasonal melting pattern. This recurrence has long been accepted as fact, but to our knowledge has not been utilized in remote sensing of snow. We develop and test the model in a large watershed in Wyoming using 17 years of remotely sensed snow cover images. When applied to images from two years that were not used in its development, the model represents snow covered area with accuracy of 84.9‐97.5% at varied snow covered areas. The model also effectively removes cloud cover if any portion of the interface between land and snow is visible in a cloudy image. This new PCA method for modeling the inter‐annually recurring spatial melt pattern exclusively from remotely sensed images possesses its own intrinsic merit, in addition to those associated with its applications.

Description: Abstract The development of the unconventional gas and CO2 sequestration is moving to deep formations. Because of the small flow pathways in the matrix, the Knudsen number might be high even though the gas is dense. In fact, due to the relatively high pressure at in situ conditions, gas flow in microfractures usually manifests a strong slip and nonideal gas effects. Therefore, understanding the coupling mechanism of these two on gas flow in rough‐walled microfractures is required to accurately model subsurface flow behavior. In this study, pressure‐driven gas flow in rough‐walled microfracture is analyzed in depth. Starting from the local governing equations for gas flow, a local flow model that includes gas slip and nonideal gas effects is derived by solving the Stokes equation with a first‐order slip boundary condition. Focusing at the representative elementary volume scale, the upscaled solutions to gas flow in a fracture with sinusoidal surface are derived to obtain the apparent permeability. The impact of nonideal gas effects, fracture roughness and aperture, and the tangential momentum accommodation coefficient on CH4 and CO2 flow is analyzed. The results show that fracture roughness introduces a high degree of heterogeneity in gas flow. At in situ conditions effects of gas slip, fracture roughness and tangential momentum accommodation coefficient on gas flow are reduced. The ideal gas law is capable of estimating CH4 flow to some extent. However, it fails to estimate CO2 flow in microfractures.

Description: Abstract In recent years, climatology, variability, hydrological impact, and climatic drivers of atmospheric rivers (ARs) are widely explored based on various AR identification algorithms. Different algorithms, varying in their tracing variables, thresholds, and geometric metrics criteria, will introduce uncertainty in further study of AR. Herein, a novel AR identification algorithm is proposed to address some current limitations. A coupled quantile and Gaussian kernel smoothing technique is proposed to make a balance in capturing the spatiotemporal variation of integrated water vapor transport climatology and avoiding largely biased estimation. In spite of variety of AR shape, orientation, and curvature, more reliable AR metrics (e.g., length and width) can be calculated based on the generated smooth AR trajectory, which is realized by modifying and integrating the concepts of local regression and K‐nearest neighbors. An unprecedented and novel metric (i.e., turning angle series) is delivered to quantify AR curvature, serves as the key to distinguish tropical cyclone‐like features, which often indicate occurrences of tropical cyclones. It also bridges ARs to their associated atmospheric circulation patterns. A pilot application of the algorithm is presented to identify persistent AR events related to flood triggering extreme precipitation sequences in the Yangtze River Basin (YRB). A dominating AR route, which connects Arabian Sea, Bay of Bengal, South China Sea, to Southeast China and YRB, terminates in the North Pacific, is found principal to the flood triggering extreme precipitation sequences in the YRB. In addition, this algorithm is extensible to other regions, even global domain.

Description: Abstract High‐intensity precipitation represents a threat for several regions of the world because of the related risk of natural disasters (e.g., floods and landslides). This work focuses on low‐level precipitation enhancement that occurs in the cloud warm layer and has been observed in relation to collision‐coalescence (CC) leading to flash floods and extreme rainfall events in tropical and temperate latitudes. Specifically, signatures of precipitation enhancement (referred to as CC‐dominant precipitation) are investigated in the observations from the Global Precipitation Measurement (GPM) core mission Dual‐frequency Precipitation Radar (DPR) over the central/eastern Contiguous United States (CONUS) during June 2014 – May 2018. A classification scheme for CC‐dominant precipitation, developed for dual‐polarization S‐band radar measurements and applied in a previous work to X‐band radar observations in complex terrain, is used as a benchmark. The scheme is here applied to the GPM ground validation dataset that matches ground‐based radar observations across CONUS to space‐borne DPR retrievals. The occurrence of CC‐dominant precipitation is documented and the corresponding signatures of CC‐dominant precipitation at Ku‐ and Ka‐band are studied. CC‐dominant profiles show distinguishing features when compared to profiles not dominated by CC, e.g., characteristic vertical slopes of reflectivity at Ku‐ and Ka‐band in the liquid layer, lower freezing level height, and shallower ice layer, which are linked to environmental conditions driving the peculiar CC microphysics. This work aims at improving satellite quantitative precipitation estimation, particularly GPM retrievals, by targeting CC development in precipitation columns. This article is protected by copyright. All rights reserved.

Description: Abstract A storage‐discharge relation tells us how discharge will change when new water enters a hydrologic system, but not which water is released. Does an incremental increase in discharge come from faster turnover of older water already in storage? Or are the recent inputs rapidly delivered to the outlet, ‘short‐circuiting’ the bulk of the system? Here I demonstrate that the concepts of storage‐discharge relationships and transit time distributions can be unified into a single relationship that can usefully address these questions: the age‐ranked storage‐discharge relation. This relationship captures how changes in total discharge arise from changes in the turn‐over rate of younger and older water in storage, and provides a window into both the celerity and velocity of water in a catchment. This leads naturally to a distinction between cases where an increase in total discharge is accompanied by an increase (old water acceleration), no change (old water steadiness), or a decrease in the rate of discharge of older water in storage (old water suppression). The simple theoretical case of a power‐law age‐ranked storage‐discharge relations is explored to illustrate these cases. Example applications to data suggest that the apparent presence of old water acceleration or suppression is sensitive to the functional form chosen to fit to the data, making it difficult to draw decisive conclusions. This suggests new methods are needed that do not require a functional form to be chosen, and provide age‐dependent uncertainty bounds.

Description: Abstract Aims As global temperatures rise, the survival of many species may hinge on whether they can shift their climatic niches quickly enough to avoid extinction. Previous analyses among species and populations suggest that species’ niches change far slower than rates of projected climate change. However, it is unclear how quickly niches can change over the timeframe most relevant to global warming (decades instead of thousands or millions of years). Here, we use data from introduced species to assess how quickly climatic niches can change over decadal timescales. Location Global. Methods We analyse climatic data from 76 reptile and amphibian species introduced into the USA. We test for a relationship between species climatic‐niche values in their native and introduced ranges. We also quantify niche shifts in introduced populations relative to their native ranges and the rate of change associated with these shifts. We then compare these rate estimates to those estimated among species and to projected rates of future climate change. Results Remarkably, niche shifts in introduced species are roughly a million times faster than niche shifts among species in their native ranges and roughly 10 times faster than rates of projected climate change. Main conclusions Our results demonstrate that dramatic and rapid niche shifts are possible, although these may be limited in species’ native ranges by biotic interactions and other factors.

Description: Abstract Hydrogeological field studies rely often on a single conceptual representation of the subsurface. This is problematic since the impact of a poorly chosen conceptual model on predictions might be significantly larger than the one caused by parameter uncertainty. Furthermore, conceptual models often need to incorporate geological concepts and patterns in order to provide meaningful uncertainty quantification and predictions. Consequently, several geologically‐realistic conceptual models should ideally be considered and evaluated in terms of their relative merits. Here, we propose a full Bayesian methodology based on Markov chain Monte Carlo (MCMC) to enable model selection among 2D conceptual models that are sampled using training images and concepts from multiple‐point statistics (MPS). More precisely, power posteriors for the different conceptual subsurface models are sampled using sequential geostatistical resampling and Graph Cuts. To demonstrate the methodology, we compare and rank five alternative conceptual geological models that have been proposed in the literature to describe aquifer heterogeneity at the MAcroDispersion Experiment (MADE) site in Mississippi, USA. We consider a small‐scale tracer test (MADE‐5) for which the spatial distribution of hydraulic conductivity impacts multilevel solute concentration data observed along a 2D transect. The thermodynamic integration and the stepping‐stone sampling methods were used to compute the evidence and associated Bayes factors using the computed power posteriors. We find that both methods are compatible with MPS‐based inversions and provide a consistent ranking of the competing conceptual models considered.

Description: Abstract Laboratory experiments examined the impact of model vegetation on wave‐driven resuspension. Model canopies were constructed from cylinders with three diameters (d = 0.32, 0.64, and 1.26 cm) and 12 densities (cylinders/m2) up to a solid volume fraction (ϕ) of 10%. The sediment bed consisted of spherical grains with d50 = 85 μm. For each experiment, the wave velocity was gradually adjusted by increasing the amplitude of 2‐s waves in a stepwise fashion. A Nortek Vectrino sampled the velocity at z = 1.3 cm above the bed. The critical wave orbital velocity for resuspension was inferred from records of suspended sediment concentration (measured with optical backscatter) as a function of wave velocity. The critical wave velocity decreased with increasing solid volume fraction. The reduction in critical wave velocity was linked to stem‐generated turbulence, which, for the same wave velocity, increased with increasing solid volume fraction. The measured turbulence was consistent with a wave‐modified version of a stem‐turbulence model. The measurements suggested that a critical value of turbulent kinetic energy was needed to initiate resuspension, and this was used to define the critical wave velocity as a function of solid volume fraction. The model predicted the measured critical wave velocity for stem diameters d = 0.64 to 2 cm. Combining the critical wave velocity with an existing model for wave damping defined the meadow size for which wave damping would be sufficient to suppress wave‐induced sediment suspension within the interior of the meadow.

Description: Evergreen broadleaf forests (EBFs) illustrated higher temporal stability and resistance of EVI than other biomes. Preserving EBFs is beneficial for global vegetation productivity stability and climate mitigation. Abstract Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non‐evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long‐term Standardized Precipitation and Evaporation Index (SPEI) data and satellite‐derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre‐drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: −0.08 to −1.80), area (areal fraction range: 2%–19%), and duration (month range: 7.9–9.1) in the EBF biome over 2000–2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more‐intense climate extremes in the future.

Description: Projected changes in coastal metacommunities driven by ocean warming and acidification based on the elements of the metacommunity structure framework of Leibold and Mikkelson (Oikos 97:237, 2002) and Presley, Higgins, and Willig (Oikos 119:908, 2010). Under present‐day conditions (a) metacommunity is structured by habitat environmental filtering. Under future climate conditions (b) metacommunity is randomly structured. Abstract Predictions of the effects of global change on ecological communities are largely based on single habitats. Yet in nature, habitats are interconnected through the exchange of energy and organisms, and the responses of local communities may not extend to emerging community networks (i.e., metacommunities). Using large mesocosms and meiofauna communities as a model system, we investigated the interactive effects of ocean warming and acidification on the structure of marine metacommunities from three shallow‐water habitats: sandy soft‐bottoms, marine vegetation, and rocky reef substrates. Primary producers and detritus—key food sources for meiofauna—increased in biomass under the combined effect of temperature and acidification. The enhanced bottom‐up forcing boosted nematode densities but impoverished the functional and trophic diversity of nematode metacommunities. The combined climate stressors further homogenized meiofauna communities across habitats. Under present‐day conditions metacommunities were structured by habitat type, but under future conditions they showed an unstructured random pattern with fast‐growing generalist species dominating the communities of all habitats. Homogenization was likely driven by local species extinctions, reducing interspecific competition that otherwise could have prevented single species from dominating multiple niches. Our findings reveal that climate change may simplify metacommunity structure and prompt biodiversity loss, which may affect the biological organization and resilience of marine communities.

Description: Explaining interspecific variation in autumn bird migration phenology trends has been challenging. We performed a spatially explicit time window analysis of weather effects on mean autumn passage of four trans‐Saharan and six intra‐European passerines at the island of Heligoland (Germany) over a 55‐year period (1960–2014). Weather variables at the breeding and stopover grounds explained up to 80% of the species‐specific interannual variability in autumn passage. Overall, wind conditions were most important, but the climatic contributions to the temporal trend in autumn migration phenology consisted of a potpourri of wind, precipitation and temperature effects. Abstract Climate change has caused a clear and univocal trend towards advancement in spring phenology. Changes in autumn phenology are much more diverse, with advancement, delays, and ‘no change' all occurring frequently. For migratory birds, patterns in autumn migration phenology trends have been identified based on ecological and life‐history traits. Explaining interspecific variation has nevertheless been challenging, and the underlying mechanisms have remained elusive. Radar studies on non‐species‐specific autumn migration intensity have repeatedly suggested that there are strong links with weather. In long‐term species‐specific studies, the variance in autumn migration phenology explained by weather has, nevertheless, been rather low, or a relationship was even lacking entirely. We performed a spatially explicit time window analysis of weather effects on mean autumn passage of four trans‐Saharan and six intra‐European passerines to gain insights into this apparent contradiction. We analysed data from standardized daily captures at the Heligoland island constant‐effort site (Germany), in combination with gridded daily temperature, precipitation and wind data over a 55‐year period (1960–2014), across northern Europe. Weather variables at the breeding and stopover grounds explained up to 80% of the species‐specific interannual variability in autumn passage. Overall, wind conditions were most important. For intra‐European migrants, wind was even twice as important as either temperature or precipitation, and the pattern also held in terms of relative contributions of each climate variable to the temporal trends in autumn phenology. For the trans‐Saharan migrants, however, the pattern of relative trend contributions was completely reversed. Temperature and precipitation had strong trend contributions, while wind conditions had only a minor impact because they did not show any strong temporal trends. As such, understanding species‐specific effects of climate on autumn phenology not only provides unique insights into each species' ecology but also how these effects shape the observed interspecific heterogeneity in autumn phenological trends.

Description: A climatology of the boundary‐layer wind‐turning angle over land is presented based on radiosonde observations from 800 stations in the Integrated Global Radiosonde Archive (IGRA). The dependence of the wind turning on a suite of parameters is analyzed. Results from previous studies indicating the importance of the planetary boundary layer (PBL) stratification for the angle of wind turning are confirmed here. A clear increase in the wind‐turning angle with wind speed, particularly for stratified conditions, is also evident. According to Rossby number similarity theory, the cross‐isobaric angle for a neutral and barotropic boundary layer decreases with the surface Rossby number, Ro. The IGRA observations indicate that this dependence on Ro might partly be linked to the dependence of the stratification on the wind speed, a dependence that seems to prevail even for the high wind speeds, a criteria that traditionally is used to approximate a neutral PBL. The vertical distribution of the turning of the wind is analyzed using the high resolution Stratospheric Processes And their Role in Climate (SPARC) data. For unstable cases, there is a maximum in the directional wind shear around the PBL top, whereas for the most stable class of cases there is a maximum near the surface. The wind‐turning angles from observations are also compared with values obtained from ERA‐Interim reanalysis fields, also presented over ocean. ERA‐Interim underestimates the magnitude of the wind‐turning angles as well as the range. Furtheremore, the midlatitude cross‐isobaric mass transport is estimated using the IGRA data. This transport is generally underestimated by ERA‐Interim, likely related to the too small wind‐turning angles. This article is protected by copyright. All rights reserved.

Description: We analyzed the effect of forest age on the climate sensitivity of carbon storage, timber growth rate, and species richness using a unique dataset of 18,507 plots in boreal–temperate forests of eastern North America. Old forests exhibited the highest combined performance and strongest association of the investigated indicators both under baseline and changed climatic conditions. Regions east and southeast of the Great Lakes were particularly vulnerable to climate change. Our findings suggest that strategies aimed at enhancing the representation of older forest conditions in the region will help sustain ecosystem services and biodiversity in a changing world. Abstract Climate change threatens the provisioning of forest ecosystem services and biodiversity (ESB). The climate sensitivity of ESB may vary with forest development from young to old‐growth conditions as structure and composition shift over time and space. This study addresses knowledge gaps hindering implementation of adaptive forest management strategies to sustain ESB. We focused on a number of ESB indicators to (a) analyze associations among carbon storage, timber growth rate, and species richness along a forest development gradient; (b) test the sensitivity of these associations to climatic changes; and (c) identify hotspots of climate sensitivity across the boreal–temperate forests of eastern North America. From pre‐existing databases and literature, we compiled a unique dataset of 18,507 forest plots. We used a full Bayesian framework to quantify responses of nine ESB indicators. The Bayesian models were used to assess the sensitivity of these indicators and their associations to projected increases in temperature and precipitation. We found the strongest association among the investigated ESB indicators in old forests (〉170 years). These forests simultaneously support high levels of carbon storage, timber growth, and species richness. Older forests also exhibit low climate sensitivity of associations among ESB indicators as compared to younger forests. While regions with a currently low combined ESB performance benefitted from climate change, regions with a high ESB performance were particularly vulnerable to climate change. In particular, climate sensitivity was highest east and southeast of the Great Lakes, signaling potential priority areas for adaptive management. Our findings suggest that strategies aimed at enhancing the representation of older forest conditions at landscape scales will help sustain ESB in a changing world.

Description: Temperate plants are at risk of being exposed to late spring freezes—called false springs—which are a major factor determining range limits, can impose high ecological and economic damage, and may be increasing with climate change. Currently, many false spring studies simplify the myriad complexities involved in assessing false spring risks and damage. Here, we review major areas that could improve predictions: understanding how species have evolved to avoid or tolerate false springs (e.g., through shortening how long they are at risk), identifying the cues that underlie spring phenology, and studying how local climate impacts false spring risk. Abstract Temperate plants are at risk of being exposed to late spring freezes. These freeze events—often called false springs—are one of the strongest factors determining temperate plants species range limits and can impose high ecological and economic damage. As climate change may alter the prevalence and severity of false springs, our ability to forecast such events has become more critical, and it has led to a growing body of research. Many false spring studies largely simplify the myriad complexities involved in assessing false spring risks and damage. While these studies have helped advance the field and may provide useful estimates at large scales, studies at the individual to community levels must integrate more complexity for accurate predictions of plant damage from late spring freezes. Here, we review current metrics of false spring, and how, when, and where plants are most at risk of freeze damage. We highlight how life stage, functional group, species differences in morphology and phenology, and regional climatic differences contribute to the damage potential of false springs. More studies aimed at understanding relationships among species tolerance and avoidance strategies, climatic regimes, and the environmental cues that underlie spring phenology would improve predictions at all biological levels. An integrated approach to assessing past and future spring freeze damage would provide novel insights into fundamental plant biology and offer more robust predictions as climate change progresses, which are essential for mitigating the adverse ecological and economic effects of false springs.

Description: As ocean warming and El Niño events increase in intensity, coral reefs, the rainforests of the marine realm, are at the forefront of their associated impacts. The frequency, intensity and spatial extent of coral bleaching are projected to increase in tandem, yet many reefs are located in poorly monitored tropical regions. By tuning marine heatwaves (MHWs) to coral bleaching conditions, we created an atlas of MHWs over the data‐poor Red Sea region, revealing hotspots of reef zones susceptible to bleaching. As this methodology may be applied to any environment, it could help optimize management plans under global environmental change. Abstract As the Earth's temperature continues to rise, coral bleaching events become more frequent. Some of the most affected reef ecosystems are located in poorly monitored waters, and thus, the extent of the damage is unknown. We propose the use of marine heatwaves (MHWs) as a new approach for detecting coral reef zones susceptible to bleaching, using the Red Sea as a model system. Red Sea corals are exceptionally heat‐resistant, yet bleaching events have increased in frequency. By applying a strict definition of MHWs on 〉30 year satellite‐derived sea surface temperature observations (1985–2015), we provide an atlas of MHW hotspots over the Red Sea coral reef zones, which includes all MHWs that caused major coral bleaching. We found that: (a) if tuned to a specific set of conditions, MHWs identify all areas where coral bleaching has previously been reported; (b) those conditions extended farther and occurred more often than bleaching was reported; and (c) an emergent pattern of extreme warming events is evident in the northern Red Sea (since 1998), a region until now thought to be a thermal refuge for corals. We argue that bleaching in the Red Sea may be vastly underrepresented. Additionally, although northern Red Sea corals exhibit remarkably high thermal resistance, the rapidly rising incidence of MHWs of high intensity indicates this region may not remain a thermal refuge much longer. As our regionally tuned MHW algorithm was capable of isolating all extreme warming events that have led to documented coral bleaching in the Red Sea, we propose that this approach could be used to reveal bleaching‐prone regions in other data‐limited tropical regions. It may thus prove a highly valuable tool for policymakers to optimize the sustainable management of coastal economic zones.

Description: Global warming is rapidly advancing the timing of spring leaf‐out in temperate deciduous tree species; however, the interactive effects of temperature and daylength underlying this warming response remain unclear. Based on data from six tree species across 2,377 European phenology observation sites, we found that, in addition to and independent of the known effect of chilling, daylength correlates negatively with the heat requirement for leaf‐out in all studied species. These results provide the first large‐scale empirical evidence of a widespread daylength effect on the temperature sensitivity of leaf‐out phenology in temperate deciduous trees. Abstract Global warming has led to substantially earlier spring leaf‐out in temperate‐zone deciduous trees. The interactive effects of temperature and daylength underlying this warming response remain unclear. However, they need to be accurately represented by earth system models to improve projections of the carbon and energy balances of temperate forests and the associated feedbacks to the Earth's climate system. We studied the control of leaf‐out by daylength and temperature using data from six tree species across 2,377 European phenological network (www.pep725.eu), each with at least 30 years of observations. We found that, in addition to and independent of the known effect of chilling, daylength correlates negatively with the heat requirement for leaf‐out in all studied species. In warm springs when leaf‐out is early, days are short and the heat requirement is higher than in an average spring, which mitigates the warming‐induced advancement of leaf‐out and protects the tree against precocious leaf‐out and the associated risks of late frosts. In contrast, longer‐than‐average daylength (in cold springs when leaf‐out is late) reduces the heat requirement for leaf‐out, ensuring that trees do not leaf‐out too late and miss out on large amounts of solar energy. These results provide the first large‐scale empirical evidence of a widespread daylength effect on the temperature sensitivity of leaf‐out phenology in temperate deciduous trees.

Description: We review the causes of variations in observed and modelled historical trends in water‐use efficiency of plants and ecosystems. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. We provide recommendations for improving observation‐based estimates of water‐use efficiency, which will better inform the representation of the exchange of carbon and water in the vegetation–atmosphere continuum in vegetation models. Abstract Plant water‐use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO2 concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO2. Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long‐term observation‐based estimates of WUE that will better inform the representation of WUE in vegetation models.

Description: We used satellite‐derived leaf chlorophyll content (Chlleaf) to infer leaf photosynthetic capacity () that varies temporally and spatially. The new Chlleaf‐based data set was then incorporated into an established terrestrial biosphere model (i.e. BEPS) to estimate global photosynthesis. Our results show that Chlleaf‐based and its seasonally average values (Chlavg‐based ) can both effectively improve the estimates of photosynthesis when validated against observations at 124 sites of different plant functional types across the globe. This study highlights that Chlleaf is a valuable leaf physiological trait to add in future models to better simulate the terrestrial carbon cycle. Abstract The terrestrial biosphere plays a critical role in mitigating climate change by absorbing anthropogenic CO2 emissions through photosynthesis. The rate of photosynthesis is determined jointly by environmental variables and the intrinsic photosynthetic capacity of plants (i.e. maximum carboxylation rate; ). A lack of an effective means to derive spatially and temporally explicit has long hampered efforts towards estimating global photosynthesis accurately. Recent work suggests that leaf chlorophyll content (Chlleaf) is strongly related to , since Chlleaf and are both correlated with photosynthetic nitrogen content. We used medium resolution satellite images to derive spatially and temporally explicit Chlleaf, which we then used to parameterize within a terrestrial biosphere model. Modelled photosynthesis estimates were evaluated against measured photosynthesis at 124 eddy covariance sites. The inclusion of Chlleaf in a terrestrial biosphere model improved the spatial and temporal variability of photosynthesis estimates, reducing biases at eddy covariance sites by 8% on average, with the largest improvements occurring for croplands (21% bias reduction) and deciduous forests (15% bias reduction). At the global scale, the inclusion of Chlleaf reduced terrestrial photosynthesis estimates by 9 PgC/year and improved the correlations with a reconstructed solar‐induced fluorescence product and a gridded photosynthesis product upscaled from tower measurements. We found positive impacts of Chlleaf on modelled photosynthesis for deciduous forests, croplands, grasslands, savannas and wetlands, but mixed impacts for shrublands and evergreen broadleaf forests and negative impacts for evergreen needleleaf forests and mixed forests. Our results highlight the potential of Chlleaf to reduce the uncertainty of global photosynthesis but identify challenges for incorporating Chlleaf in future terrestrial biosphere models.

Description: Early warning metrics from satellites of drought‐induced tree mortality could be incredibly valuable. We test several metrics in an aspen mortality event and find that these metrics can explain both tree physiological stress during the drought and subsequent mortality after the drought. Abstract Climate change‐driven drought stress has triggered numerous large‐scale tree mortality events in recent decades. Advances in mechanistic understanding and prediction are greatly limited by an inability to detect in situ where trees are likely to die in order to take timely measurements and actions. Thus, algorithms of early warning and detection of drought‐induced tree stress and mortality could have major scientific and societal benefits. Here, we leverage two consecutive droughts in the southwestern United States to develop and test a set of early warning metrics. Using Landsat satellite data, we constructed early warning metrics from the first drought event. We then tested these metrics' ability to predict spatial patterns in tree physiological stress and mortality from the second drought. To test the broader applicability of these metrics, we also examined a separate drought in the Amazon rainforest. The early warning metrics successfully explained subsequent tree mortality in the second drought in the southwestern US, as well as mortality in the independent drought in tropical forests. The metrics also strongly correlated with spatial patterns in tree hydraulic stress underlying mortality, which provides a strong link between tree physiological stress and remote sensing during the severe drought and indicates that the loss of hydraulic function during drought likely mediated subsequent mortality. Thus, early warning metrics provide a critical foundation for elucidating the physiological mechanisms underpinning tree mortality in mature forests and guiding management responses to these climate‐induced disturbances.

Description: Most studies analyzing influences of climatic warming on crop yield have ignored that yield response to temperature is stage dependent. Here we integrate field census data, satellite‐derived data, statistical regressions and mechanistic models to investigate how heat stress nonlinearly influences maize yield and its components (biomass accumulation, phenological development and grain formation). Our analysis through integrating data and crop models suggests that future adaptation strategies should be targeted at the heat stress during grain formation and changes in agricultural management need to be better accounted for to adequately estimate the heat stress effects. Abstract Evidence suggests that global maize yield declines with a warming climate, particularly with extreme heat events. However, the degree to which important maize processes such as biomass growth rate, growing season length (GSL) and grain formation are impacted by an increase in temperature is uncertain. Such knowledge is necessary to understand yield responses and develop crop adaptation strategies under warmer climate. Here crop models, satellite observations, survey, and field data were integrated to investigate how high temperature stress influences maize yield in the U.S. Midwest. We showed that both observational evidence and crop model ensemble mean (MEM) suggests the nonlinear sensitivity in yield was driven by the intensified sensitivity of harvest index (HI), but MEM underestimated the warming effects through HI and overstated the effects through GSL. Further analysis showed that the intensified sensitivity in HI mainly results from a greater sensitivity of yield to high temperature stress during the grain filling period, which explained more than half of the yield reduction. When warming effects were decomposed into direct heat stress and indirect water stress (WS), observational data suggest that yield is more reduced by direct heat stress (−4.6 ± 1.0%/°C) than by WS (−1.7 ± 0.65%/°C), whereas MEM gives opposite results. This discrepancy implies that yield reduction by heat stress is underestimated, whereas the yield benefit of increasing atmospheric CO2 might be overestimated in crop models, because elevated CO2 brings yield benefit through water conservation effect but produces limited benefit over heat stress. Our analysis through integrating data and crop models suggests that future adaptation strategies should be targeted at the heat stress during grain formation and changes in agricultural management need to be better accounted for to adequately estimate the effects of heat stress.

Description: Are there non‐native marine species in Antarctica? With over 500 visits from more than 180 vessels annually and rapidly changing environmental conditions, Antarctica appears to be increasingly vulnerable to impacts from non‐native marine species. We explore factors that influence the likelihood of non‐native marine species establishing in the Antarctic region, present new estimates for human activity, and make recommendations to researchers, environmental managers and policy makers. Abstract Antarctica is experiencing significant ecological and environmental change, which may facilitate the establishment of non‐native marine species. Non‐native marine species will interact with other anthropogenic stressors affecting Antarctic ecosystems, such as climate change (warming, ocean acidification) and pollution, with irreversible ramifications for biodiversity and ecosystem services. We review current knowledge of non‐native marine species in the Antarctic region, the physical and physiological factors that resist establishment of non‐native marine species, changes to resistance under climate change, the role of legislation in limiting marine introductions, and the effect of increasing human activity on vectors and pathways of introduction. Evidence of non‐native marine species is limited: just four marine non‐native and one cryptogenic species that were likely introduced anthropogenically have been reported freely living in Antarctic or sub‐Antarctic waters, but no established populations have been reported; an additional six species have been observed in pathways to Antarctica that are potentially at risk of becoming invasive. We present estimates of the intensity of ship activity across fishing, tourism and research sectors: there may be approximately 180 vessels and 500+ voyages in Antarctic waters annually. However, these estimates are necessarily speculative because relevant data are scarce. To facilitate well‐informed policy and management, we make recommendations for future research into the likelihood of marine biological invasions in the Antarctic region.

Description: Global Change Biology, Volume 25, Issue 7, Page e5-e5, July 2019.

Description: The effect of legumes on soil nitrogen (N) cycling was much greater than that of N enrichment in this N‐limited grassland either across (a, c) or within (b, d) the experimental year. Legume effects were also greater than those of N enrichment in alleviating potential negative effects of species richness on mineralization (a). Abstract Legumes are an important component of plant diversity that modulate nitrogen (N) cycling in many terrestrial ecosystems. Limited knowledge of legume effects on soil N cycling and its response to global change factors and plant diversity hinders a general understanding of whether and how legumes broadly regulate the response of soil N availability to those factors. In a 17‐year study of perennial grassland species grown under ambient and elevated (+180 ppm) CO2 and ambient and enriched (+4 g N m−2 year−1) N environments, we compared pure legume plots with plots dominated by or including other herbaceous functional groups (and containing one or four species) to assess the effect of legumes on N cycling (net N mineralization rate and inorganic N pools). We also examined the effects of numbers of legume species (from zero to four) in four‐species mixed plots on soil N cycling. We hypothesized that legumes would increase N mineralization rates most in those treatments with the greatest diversity and the greatest relative limitation by and competition for N. Results partially supported these hypotheses. Plots with greater dominance by legumes had greater soil nitrate concentrations and mineralization rates. Higher species richness significantly increased the impact of legumes on soil N metrics, with 349% and 505% higher mineralization rates and nitrate concentrations in four‐species plots containing legumes compared to legume‐free four‐species plots, in contrast to 185% and 129% greater values, respectively, in pure legume than nonlegume monoculture plots. N‐fertilized plots had greater legume effects on soil nitrate, but lower legume effects on net N mineralization. In contrast, neither elevated CO2 nor its interaction with legumes affected net N mineralization. These results indicate that legumes markedly influence the response of soil N cycling to some, but not all, global change drivers.

Description: Ecosystems can be characterized as complex systems that traverse a variety of functional and structural states in response to changing bioclimatic forcings. An ecosystem's functional state can be empirically described using Process Networks that use timeseries observations to determine the strength of process‐level functional couplings between ecosystem components by using the LaThuile FLUXNET synthesis dataset. The resulted elasticity maps provide theoretically novel resource to anticipate ecological state transitions in response to climate change and to validate process‐based models of ecological change. Tropical forests, hot deserts, savannas, and high elevations are most elastic to climate change. Abstract Ecosystems can be characterized as complex systems that traverse a variety of functional and structural states in response to changing bioclimatic forcings. A central challenge of global change biology is the robust empirical description of these states and state transitions. An ecosystem's functional state can be empirically described using Process Networks (PN) that use timeseries observations to determine the strength of process‐level functional couplings between ecosystem components. A globally extensive source of in‐situ observations of terrestrial ecosystem dynamics is the FLUXNET eddy‐covariance network that provides standardized observations of micrometeorology and carbon, water, and energy flux dynamics. We employ the LaThuile FLUXNET synthesis dataset to delineate each month's functional state for 204 sites, yielding the LaThuile PN version 1.0 database that describes the strength of an ecosystem's functional couplings from air temperature and precipitation to carbon fluxes during each site‐month. Then we calculate the elasticity of these couplings to seasonal scale forcings: air temperature, precipitation, solar radiation, and phenophase. Finally, we train artificial neural networks to extrapolate these elasticities from 204 sites to the globe, yielding maps of the estimated functional elasticity of every terrestrial ecosystem's functional states to changing seasonal bioclimatic forcings. These maps provide theoretically novel resource that can be used to anticipate ecological state transitions in response to climate change and to validate process‐based models of ecological change. These elasticity maps show that each ecosystem can be expected to respond uniquely to changing forcings. Tropical forests, hot deserts, savannas, and high elevations are most elastic to climate change, and elasticity of ecosystems to seasonal air temperature is on average an order of magnitude higher than elasticity to other bioclimatic forcings. We also observed a reasonable amount of moderate relationships between functional elasticity and structural state change across different ecosystems.

Description: Global Change Biology, Volume 25, Issue 7, Page e3-e4, July 2019.

Description: Plant stress resulting from soil freezing is expected to increase in northern temperate regions over the next century due to reductions in snow cover caused by climate change. Soil spatial heterogeneity can buffer the effects of plant freezing stress by increasing the availability of soil microsites that function as microrefugia. While the deliberate creation of soil microsites in ecological restoration projects could increase the frequency of microrefugia that mitigate plant community responses to increased freezing stress, the design of these microsites must be optimized, given that soil heterogeneity also has the potential to exacerbate freezing stress responses. Abstract Plant stress resulting from soil freezing is expected to increase in northern temperate regions over the next century due to reductions in snow cover caused by climate change. Within plant communities, soil spatial heterogeneity can potentially buffer the effects of plant freezing stress by increasing the availability of soil microsites that function as microrefugia. Moreover, increased species richness resulting from soil heterogeneity can increase the likelihood of stress‐tolerant species being present in a community. We used a field experiment to examine interactions between soil heterogeneity and increased freezing intensity (achieved via snow removal) on plant abundance and diversity in a grassland. Patches of topsoil were mixed with either sand or woodchips to create heterogeneous and homogeneous treatments, and plant community responses to snow removal were assessed over three growing seasons. Soil heterogeneity interacted significantly with snow removal, but it either buffered or exacerbated the snow removal response depending on the specific substrate (sand vs. woodchips) and plant functional group. In turn, snow removal influenced plant responses to soil heterogeneity; for example, adventive forb cover responded to increased heterogeneity under ambient snow cover, but this effect diminished with snow removal. Our results reveal that soil heterogeneity can play an important role in determining plant responses to changes in soil freezing stress resulting from global climate change. While the deliberate creation of soil microsites in ecological restoration projects as a land management practice could increase the frequency of microrefugia that mitigate plant community responses to increased freezing stress, the design of these microsites must be optimized, given that soil heterogeneity also has the potential to exacerbate freezing stress responses.

Description: Abstract The impacts of aquatic vegetation on bed load transport rate and bedform characteristics were quantified using flume measurements with model emergent vegetation. First, a model for predicting the turbulent kinetic energy, kt, in vegetated channels from channel average velocity U and vegetation volume fraction ϕ was validated for mobile sediment beds. Second, using data from several studies, the predicted kt was shown to be a good predictor of bed load transport rate, Qs, allowing Qs to be predicted from U and ϕ for vegetated channels. The control of Qs by kt was explained by statistics of individual grain motion recorded by a camera, which showed that the number of sediment grains in motion per bed area was correlated with kt. Third, ripples were observed and characterized in channels with and without model vegetation. For low vegetation solid volume fraction (ϕ ≤ 0.012), the ripple wavelength was constrained by stem spacing. However, at higher vegetation solid volume fraction (ϕ=0.025), distinct ripples were not observed, suggesting a transition to sheet flow, which is sediment transport over a plane bed without the formation of bedforms. The fraction of the bed load flux carried by migrating ripples decreased with increasing ϕ, again suggesting that vegetation facilitated the formation of sheet flow.

Description: Abstract Aim Understanding biodiversity–ecosystem function (BEF) relationships in forest systems is crucial for effective forest management and restoration, yet testing these relationships is often limited by biased diversity patterns in forestry plantings (biased towards commercially valuable species) and uncontrollable diversity in mature natural forests. Multispecies reforestation plantings present a valuable opportunity to investigate BEF relationships in woody systems, especially across large environmental gradients. Location Reforestation plantings across the arable region of Australia. Time period 1951–2012. Major taxa studied Three hundred and sixty‐four woody plant species. Methods We examined relationships between productivity and diversity using inventory data from 977 plots in 386 multispecies reforestation plantings. Diversity was estimated using observed species richness and three functional diversity indices calculated from four functional traits: specific leaf area, wood density, seed mass and maximum attainable height. We modelled how plot‐level biomass accumulation (a productivity proxy) correlated with these diversity indices, as well as age since planting, plant density and three environmental variables: solar radiation, moisture availability and soil sand content. These models were fitted across Australia and, separately, within eight groups of plantings with similar environmental conditions. Results We found no correlation between diversity and productivity, regardless of the diversity metric or spatial scale used (continent‐wide or within environment groups). Instead, productivity was best explained by local environmental conditions and plant density. Main conclusions A positive relationship between diversity and productivity was not evident in planted forests across a wide range of Australian woodland and forest systems, at least in the first few decades of growth. Our findings suggest that the positive relationship between diversity and productivity commonly reported in experimental settings should not be assumed for all systems and conditions.

Description: Pinus sylvestris growth reversed its response to temperature between the non‐warming period (1958–1986) and the warming period (1987–2014). The shifting of the growing season to April during rapid warming, the presence of snow cover during early growing season, and a consequent alleviation of water‐limitation during the early growing season contribute to the reversed correlation between temperature and growth for April and May since 1987. Abstract Boreal forests are facing profound changes in their growth environment, including warming‐induced water deficits, extended growing seasons, accelerated snowmelt, and permafrost thaw. The influence of warming on trees varies regionally, but in most boreal forests studied to date, tree growth has been found to be negatively affected by increasing temperatures. Here, we used a network of Pinus sylvestris tree‐ring collections spanning a wide climate gradient the southern end of the boreal forest in Asia to assess their response to climate change for the period 1958–2014. Contrary to findings in other boreal regions, we found that previously negative effects of temperature on tree growth turned positive in the northern portion of the study network after the onset of rapid warming. Trees in the drier portion did not show this reversal in their climatic response during the period of rapid warming. Abundant water availability during the growing season, particularly in the early to mid‐growing season (May–July), is key to the reversal of tree sensitivity to climate. Advancement in the onset of growth appears to allow trees to take advantage of snowmelt water, such that tree growth increases with increasing temperatures during the rapidly warming period. The region's monsoonal climate delivers limited precipitation during the early growing season, and thus snowmelt likely covers the water deficit so trees are less stressed from the onset of earlier growth. Our results indicate that the growth response of P. sylvestris to increasing temperatures strongly related to increased early season water availability. Hence, boreal forests with sufficient water available during crucial parts of the growing season might be more able to withstand or even increase growth during periods of rising temperatures. We suspect that other regions of the boreal forest may be affected by similar dynamics.

Description: We conducted a global meta‐analysis to examine changes in soil organic carbon sequestration induced by three common climate‐smart agriculture (CSA) management practices (i.e., conservation tillage, cover crops, and biochar) and associated environmental controlling factors. Our results demonstrate that croplands could serve as an improved carbon sink and provide climate benefits by adopting these CSA practices. However, climate and soil conditions, as well as the combined effects of multiple management practices, should be proactively considered in scaling up these CSA practices to local and regional levels for achieving climate mitigation and adaptation while ensuring crop security and soil health. Abstract Climate‐smart agriculture (CSA) management practices (e.g., conservation tillage, cover crops, and biochar applications) have been widely adopted to enhance soil organic carbon (SOC) sequestration and to reduce greenhouse gas emissions while ensuring crop productivity. However, current measurements regarding the influences of CSA management practices on SOC sequestration diverge widely, making it difficult to derive conclusions about individual and combined CSA management effects and bringing large uncertainties in quantifying the potential of the agricultural sector to mitigate climate change. We conducted a meta‐analysis of 3,049 paired measurements from 417 peer‐reviewed articles to examine the effects of three common CSA management practices on SOC sequestration as well as the environmental controlling factors. We found that, on average, biochar applications represented the most effective approach for increasing SOC content (39%), followed by cover crops (6%) and conservation tillage (5%). Further analysis suggested that the effects of CSA management practices were more pronounced in areas with relatively warmer climates or lower nitrogen fertilizer inputs. Our meta‐analysis demonstrated that, through adopting CSA practices, cropland could be an improved carbon sink. We also highlight the importance of considering local environmental factors (e.g., climate and soil conditions and their combination with other management practices) in identifying appropriate CSA practices for mitigating greenhouse gas emissions while ensuring crop productivity.

Description: We demonstrate that foliar water uptake (FU) occurs in six common Amazonian tree genera. Using meteorological and canopy wetness data, coupled with empirically derived estimates of leaf conductance to FU, we estimate the contribution by FU to annual transpiration at this site has a median value of 8% (103 mm/year) and an interquartile range of 3%–15%. Our results indicate that FU is likely to be a common strategy in Amazonian rainforest and may have significant implications for the Amazon carbon budget and potentially also influence the drought tolerance of individual Amazonian trees and tree species. Abstract The absorption of atmospheric water directly into leaves enables plants to alleviate the water stress caused by low soil moisture, hydraulic resistance in the xylem and the effect of gravity on the water column, while enabling plants to scavenge small inputs of water from leaf‐wetting events. By increasing the availability of water, and supplying it from the top of the canopy (in a direction facilitated by gravity), foliar uptake (FU) may be a significant process in determining how forests interact with climate, and could alter our interpretation of current metrics for hydraulic stress and sensitivity. FU has not been reported for lowland tropical rainforests; we test whether FU occurs in six common Amazonian tree genera in lowland Amazônia, and make a first estimation of its contribution to canopy–atmosphere water exchange. We demonstrate that FU occurs in all six genera and that dew‐derived water may therefore be used to “pay” for some morning transpiration in the dry season. Using meteorological and canopy wetness data, coupled with empirically derived estimates of leaf conductance to FU (kfu), we estimate that the contribution by FU to annual transpiration at this site has a median value of 8.2% (103 mm/year) and an interquartile range of 3.4%–15.3%, with the biggest sources of uncertainty being kfu and the proportion of time the canopy is wet. Our results indicate that FU is likely to be a common strategy and may have significant implications for the Amazon carbon budget. The process of foliar water uptake may also have a profound impact on the drought tolerance of individual Amazonian trees and tree species, and on the cycling of water and carbon, regionally and globally.

Description: Increasing environmental temperatures have resulted in more frequent and more severe outbreaks of ranavirus disease in UK frogs. Future climate change could threaten larval recruitment and lead to greater impacts but the results of this study point to possible mitigation steps. Abstract The global trend of increasing environmental temperatures is often predicted to result in more severe disease epidemics. However, unambiguous evidence that temperature is a driver of epidemics is largely lacking, because it is demanding to demonstrate its role among the complex interactions between hosts, pathogens, and their shared environment. Here, we apply a three‐pronged approach to understand the effects of temperature on ranavirus epidemics in UK common frogs, combining in vitro, in vivo, and field studies. Each approach suggests that higher temperatures drive increasing severity of epidemics. In wild populations, ranavirosis incidents were more frequent and more severe at higher temperatures, and their frequency increased through a period of historic warming in the 1990s. Laboratory experiments using cell culture and whole animal models showed that higher temperature increased ranavirus propagation, disease incidence, and mortality rate. These results, combined with climate projections, predict severe ranavirosis outbreaks will occur over wider areas and an extended season, possibly affecting larval recruitment. Since ranaviruses affect a variety of ectothermic hosts (amphibians, reptiles, and fish), wider ecological damage could occur. Our three complementary lines of evidence present a clear case for direct environmental modulation of these epidemics and suggest management options to protect species from disease.

Description: We measured the response of three phytoplankton communities to multifactorial combinations of temperature, nutrient and grazing treatments. Nutrients elevated net growth rates and reduced carbon:nutrient and nitrogen:phosphorus ratios of all communities. Warming effects on growth and stoichiometry depended on lake productivity: warming enhanced growth in the most productive community and caused strongest stoichiometric responses in the least productive community. Grazing reduced C:P and N:P ratios in the least productive community, suggesting consumer‐driven nutrient recycling. Our experiments indicate that stoichiometric responses to warming, and interactions with nutrient supply and grazing, depend on lake productivity and cell size distribution. Abstract Global change involves shifts in multiple environmental factors that act in concert to shape ecological systems in ways that depend on local biotic and abiotic conditions. Little is known about the effects of combined global change stressors on phytoplankton communities, and particularly how these are mediated by distinct community properties such as productivity, grazing pressure and size distribution. Here, we tested for the effects of warming and eutrophication on phytoplankton net growth rate and C:N:P stoichiometry in two phytoplankton cell size fractions (〈30 µm and 〉30 µm) in the presence and absence of grazing in microcosm experiments. Because effects may also depend on lake productivity, we used phytoplankton communities from three Dutch lakes spanning a trophic gradient. We measured the response of each community to multifactorial combinations of temperature, nutrient, and grazing treatments and found that nutrients elevated net growth rates and reduced carbon:nutrient ratios of all three phytoplankton communities. Warming effects on growth and stoichiometry depended on nutrient supply and lake productivity, with enhanced growth in the most productive community dominated by cyanobacteria, and strongest stoichiometric responses in the most oligotrophic community at ambient nutrient levels. Grazing effects were also most evident in the most oligotrophic community, with reduced net growth rates and phytoplankton C:P stoichiometry that suggests consumer‐driven nutrient recycling. Our experiments indicate that stoichiometric responses to warming and interactions with nutrient addition and grazing are not universal but depend on lake productivity and cell size distribution.

Description: In Europe, we explored latitudinal community shifts for nematodes—abundant soil organisms that include root herbivores—in the rhizospheres of climate change‐driven range‐expanding plant species. We sampled nematode communities of several range‐expanding plant species along their expansion trajectory and compared these nematode communities with those of related plant species that are native along the entire expansion gradient. We show that nematode communities change with latitude, but that the strength of nematode community shifts strongly depends on range‐expanding plant species. Abstract Current climate change has led to latitudinal and altitudinal range expansions of numerous species. During such range expansions, plant species are expected to experience changes in interactions with other organisms, especially with belowground biota that have a limited dispersal capacity. Nematodes form a key component of the belowground food web as they include bacterivores, fungivores, omnivores and root herbivores. However, their community composition under climate change‐driven intracontinental range‐expanding plants has been studied almost exclusively under controlled conditions, whereas little is known about actual patterns in the field. Here, we use novel molecular sequencing techniques combined with morphological quantification in order to examine nematode communities in the rhizospheres of four range‐expanding and four congeneric native species along a 2,000 km latitudinal transect from South‐Eastern to North‐Western Europe. We tested the hypotheses that latitudinal shifts in nematode community composition are stronger in range‐expanding plant species than in congeneric natives and that in their new range, range‐expanding plant species accumulate fewest root‐feeding nematodes. Our results show latitudinal variation in nematode community composition of both range expanders and native plant species, while operational taxonomic unit richness remained the same across ranges. Therefore, range‐expanding plant species face different nematode communities at higher latitudes, but this is also the case for widespread native plant species. Only one of the four range‐expanding plant species showed a stronger shift in nematode community composition than its congeneric native and accumulated fewer root‐feeding nematodes in its new range. We conclude that variation in nematode community composition with increasing latitude occurs for both range‐expanding and native plant species and that some range‐expanding plant species may become released from root‐feeding nematodes in the new range.

Description: Large‐diameter, tall‐stature and big‐crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence, play an important role in climate change mitigation strategies. We show that the “big‐sized trees effect” overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big‐sized trees may be more susceptible to atmospheric drought. We argue that the effects of big‐sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning. Abstract Large‐diameter, tall‐stature, and big‐crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence play an important role in climate change mitigation strategies. Here, we hypothesized that the effects of large‐diameter, tall‐stature, and big‐crown trees overrule the effects of species richness and remaining trees attributes on aboveground biomass in tropical forests (i.e., we term the “big‐sized trees hypothesis”). Specifically, we assessed the importance of: (a) the “top 1% big‐sized trees effect” relative to species richness; (b) the “99% remaining trees effect” relative to species richness; and (c) the “top 1% big‐sized trees effect” relative to the “99% remaining trees effect” and species richness on aboveground biomass. Using environmental factor and forest inventory datasets from 712 tropical forest plots in Hainan Island of southern China, we tested several structural equation models for disentangling the relative effects of big‐sized trees, remaining trees attributes, and species richness on aboveground biomass, while considering for the full (indirect effects only) and partial (direct and indirect effects) mediation effects of climatic and soil conditions, as well as interactions between species richness and trees attributes. We found that top 1% big‐sized trees attributes strongly increased aboveground biomass (i.e., explained 55%–70% of the accounted variation) compared to species richness (2%–18%) and 99% remaining trees attributes (6%–10%). In addition, species richness increased aboveground biomass indirectly via increasing big‐sized trees but via decreasing remaining trees. Hence, we show that the “big‐sized trees effect” overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big‐sized trees may be more susceptible to atmospheric drought. We argue that the effects of big‐sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning.

Description: Global Change Biology, Volume 25, Issue 8, Page i-ii, August 2019.

Description: Soil fauna is a key component of terrestrial ecosystems, although its response to climate change and its consequences to ecosystem functioning deserve more attention. In a climate manipulation experiment replicated across Europe, we found that the abundance and the taxonomic, phylogenetic, and functional richness of springtails decreased within 4 years of drought. This richness decline led to phylogenetically more clustered communities sharing evolutionary conserved traits. Additionally, despite the climatic differences among our study sites, we found that taxonomic, phylogenetic, and functional richness of springtail communities were able to explain up to 30% of the variation in annual litter decomposition rates. Abstract Soil fauna play a fundamental role on key ecosystem functions like organic matter decomposition, although how local assemblages are responding to climate change and whether these changes may have consequences to ecosystem functioning is less clear. Previous studies have revealed that a continued environmental stress may result in poorer communities by filtering out the most sensitive species. However, these experiments have rarely been applied to climate change factors combining multiyear and multisite standardized field treatments across climatically contrasting regions, which has limited drawing general conclusions. Moreover, other facets of biodiversity, such as functional and phylogenetic diversity, potentially more closely linked to ecosystem functioning, have been largely neglected. Here, we report that the abundance, species richness, phylogenetic diversity, and functional richness of springtails (Subclass Collembola), a major group of fungivores and detritivores, decreased within 4 years of experimental drought across six European shrublands. The loss of phylogenetic and functional richness was higher than expected by the loss of species richness, leading to communities of phylogenetically similar species sharing evolutionary conserved traits. Additionally, despite the great climatic differences among study sites, we found that taxonomic, phylogenetic, and functional richness of springtail communities alone were able to explain up to 30% of the variation in annual decomposition rates. Altogether, our results suggest that the forecasted reductions in precipitation associated with climate change may erode springtail communities and likely other drought‐sensitive soil invertebrates, thereby retarding litter decomposition and nutrient cycling in ecosystems.

Description: Worldwide, China is home to the fourth largest combined area of natural wetlands. A recent study provided a synthesis of its carbon budget. However, based on our experience of observing and simulating CH4 emissions from natural wetlands, as well as evidence in the literature, we suggest the results to be an overestimation of the CH4 release from China's marshlands, and here are the two reasons why: an overestimation of the extent of China's marshlands and an overestimation of the CH4 emission rates from the Tibetan Plateau

Description: The figure displays the effects (red = negative; blue = positive) of explanatory variables on tree sensitivity to climate, and the resulting 1970–2005 growth trends. Old‐growth boreal black spruce stands exhibited a more negative response to previous summer temperature, identified as the primary climatic driver of growth trajectories for this species. This finding suggests an exacerbated effect of heat‐induced stresses, which resulted in more negative long‐term growth trends for old‐growth stands, especially when combined with late‐frost damage. Other explanatory variables, such as regional climate, competition, and soil conditions, modified tree sensitivity to climate. Abstract Currently, there is no consensus regarding the way that changes in climate will affect boreal forest growth, where warming is occurring faster than in other biomes. Some studies suggest negative effects due to drought‐induced stresses, while others provide evidence of increased growth rates due to a longer growing season. Studies focusing on the effects of environmental conditions on growth–climate relationships are usually limited to small sampling areas that do not encompass the full range of environmental conditions; therefore, they only provide a limited understanding of the processes at play. Here, we studied how environmental conditions and ontogeny modulated growth trends and growth–climate relationships of black spruce (Picea mariana) and jack pine (Pinus banksiana) using an extensive dataset from a forest inventory network. We quantified the long‐term growth trends at the stand scale, based on analysis of the absolutely dated ring‐width measurements of 2,266 trees. We assessed the relationship between annual growth rates and seasonal climate variables and evaluated the effects of various explanatory variables on long‐term growth trends and growth–climate relationships. Both growth trends and growth–climate relationships were species‐specific and spatially heterogeneous. While the growth of jack pine barely increased during the study period, we observed a growth decline for black spruce which was more pronounced for older stands. This decline was likely due to a negative balance between direct growth gains induced by improved photosynthesis during hotter‐than‐average growing conditions in early summers and the loss of growth occurring the following year due to the indirect effects of late‐summer heat waves on accumulation of carbon reserves. For stands at the high end of our elevational gradient, frost damage during milder‐than‐average springs could act as an additional growth stressor. Competition and soil conditions also modified climate sensitivity, which suggests that effects of climate change will be highly heterogeneous across the boreal biome.

Description: Invasive species threaten global biodiversity, agriculture, food security and ecosystem function. Pest risk analysis is key to biosecurity efforts, but is hampered by incomplete knowledge of invasive species distributions. We use statistical species distribution models to estimate presence probabilities for 1,739 crop pests and pathogens globally, and test model predictions for unobserved occurrences in China against observations abstracted from the Chinese literature. We show that large numbers of currently unobserved invasive species of agriculture are probably already present around the world, particularly in China, India and the former USSR. Abstract Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75–0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability 〉0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

Description: Abstract Aim Understanding how spatial scale of study affects observed dispersal patterns can provide insights to spatiotemporal population dynamics, particularly in systems with significant long‐distance dispersal (LDD). We aimed to investigate the dispersal gradients of two rusts of wheat with spores of similar size, mass and shape, over multiple spatial scales. We hypothesized that a single dispersal kernel could fit the dispersal from all spatial scales well, and that it would be possible to obtain similar results in spatiotemporal increase of disease when modelling based on differing scales. Location Central Oregon and St. Croix Island. Taxa Puccinia striiformis f. sp. tritici, Puccinia graminis f. sp. tritici, Triticum aestivum. Methods We compared empirically derived primary disease gradients of cereal rust across three spatial scales: local (inoculum source and sampling unit = 0.0254 m, spatial extent = 1.52 m) field‐wide (inoculum source = 1.52 m, sampling unit = 0.305 m and spatial extent = 91.4 m) and regional (inoculum source and sampling unit = 152 m, spatial extent = 10.5 km). We then examined whether disease spread in spatially explicit simulations depended upon the scale at which data were collected by constructing a compartmental time‐step model. Results The three data sets could be fit well by a single power law dispersal kernel. Simulating epidemic spread at different spatial resolutions resulted in similar patterns of spatiotemporal spread. Dispersal kernel data obtained at one spatial scale can be used to represent spatiotemporal disease spread at a larger spatial scale. Main Conclusions Organisms spread by aerially dispersed small propagules that exhibit LDD may follow similar dispersal patterns over a several hundred‐ or thousand‐fold expanse of spatial scale. Given that the primary mechanisms driving aerial dispersal remains constant, it may be possible to extrapolate across scales when empirical data are unavailable at a scale of interest.

Description: The response of coral‐reef communities to a major coral‐bleaching event depended on whether reefs were adjacent to islands with seabirds versus islands that lacked seabirds due to the presence of invasive rats. There was a post‐bleaching shift in benthic communities only around islands with seabirds, characterized by an increase in Halimeda and crustose coralline algae (CCA) (a). Overall fish community structure around both island types shifted following the bleaching event, characterized by a loss of planktivores and corallivores (b). However, biomass of key feeding groups, namely herbivores and piscivores, remained higher around islands with seabirds compared to islands with rats. Abstract Cross‐ecosystem nutrient subsidies play a key role in the structure and dynamics of recipient communities, but human activities are disrupting these links. Because nutrient subsidies may also enhance community stability, the effects of losing these inputs may be exacerbated in the face of increasing climate‐related disturbances. Nutrients from seabirds nesting on oceanic islands enhance the productivity and functioning of adjacent coral reefs, but it is unknown whether these subsidies affect the response of coral reefs to mass bleaching events or whether the benefits of these nutrients persist following bleaching. To answer these questions, we surveyed benthic organisms and fishes around islands with seabirds and nearby islands without seabirds due to the presence of invasive rats. Surveys were conducted in the Chagos Archipelago, Indian Ocean, immediately before the 2015–2016 mass bleaching event and, in 2018, two years following the bleaching event. Regardless of the presence of seabirds, relative coral cover declined by 32%. However, there was a post‐bleaching shift in benthic community structure around islands with seabirds, which did not occur around islands with invasive rats, characterized by increases in two types of calcareous algae (crustose coralline algae [CCA] and Halimeda spp.). All feeding groups of fishes were positively affected by seabirds, but only herbivores and piscivores were unaffected by the bleaching event and sustained the greatest difference in biomass between islands with seabirds versus those with invasive rats. By contrast, corallivores and planktivores, both of which are coral‐dependent, experienced the greatest losses following bleaching. Even though seabird nutrients did not enhance community‐wide resistance to bleaching, they may still promote recovery of these reefs through their positive influence on CCA and herbivorous fishes. More broadly, the maintenance of nutrient subsidies, via strategies including eradication of invasive predators, may be important in shaping the response of ecological communities to global climate change.

Description: Irrigated agriculture alters near‐surface temperature and humidity, which may mask global climate change at the regional scale. This is the first study to quantify irrigation‐induced climate change in the Midwest United States using a 60 km transect consisting of 28 meteorological sensors across the Wisconsin Central Sands region. Irrigated agriculture decreased the diurnal temperature range and vapor pressure deficit compared to rainfed agriculture and forests. These regional climate impacts must be considered together with increased greenhouse gas emissions, groundwater quality concerns, and surface water degradation when evaluating irrigation expansion in the Midwest United States. Abstract Irrigated agriculture alters near‐surface temperature and humidity, which may mask global climate change at the regional scale. However, observational studies of irrigation‐induced climate change are lacking in temperate, humid regions throughout North America and Europe. Despite unknown climate impacts, irrigated agriculture is expanding in the Midwest United States, where unconfined aquifers provide groundwater to support crop production on coarse soils. This is the first study in the Midwest United States to observe and quantify differences in regional climate associated with irrigated agricultural conversion from forests and rainfed agriculture. To this end, we established a 60 km transect consisting of 28 stations across varying land uses and monitored surface air temperature and relative humidity for 31 months in the Wisconsin Central Sands region. We used a novel approach to quantify irrigated land use in both space and time with a database containing monthly groundwater withdrawal estimates by parcel for the state of Wisconsin. Irrigated agriculture decreased maximum temperatures and increased minimum temperatures, thus shrinking the diurnal temperature range (DTR) by an average of 3°C. Irrigated agriculture also decreased the vapor pressure deficit (VPD) by an average of 0.10 kPa. Irrigated agriculture significantly decreased evaporative demand for 25% and 66% of study days compared to rainfed agriculture and forest, respectively. Differences in VPD across the land‐use gradient were highest (0.21 kPa) during the peak of the growing season, while differences in DTR were comparable year‐round. Interannual variability in temperature had greater impacts on differences in DTR and VPD across the land‐use gradient than interannual variability in precipitation. These regional climate changes must be considered together with increased greenhouse gas emissions, changes to groundwater quality, and surface water degradation when evaluating the costs and benefits of groundwater‐sourced irrigation expansion in the Midwest United States and similar regions around the world.

Description: We combined the use of a unique whole‐ecosystem warming approach coupled with microbial community analyses and functional assessments through two growth seasons. We found microbial diversity and nitrogen fixation decreased with warming treatment. Abstract Sphagnum‐dominated peatlands comprise a globally important pool of soil carbon (C) and are vulnerable to climate change. While peat mosses of the genus Sphagnum are known to harbor diverse microbial communities that mediate C and nitrogen (N) cycling in peatlands, the effects of climate change on Sphagnum microbiome composition and functioning are largely unknown. We investigated the impacts of experimental whole‐ecosystem warming on the Sphagnum moss microbiome, focusing on N2 fixing microorganisms (diazotrophs). To characterize the microbiome response to warming, we performed next‐generation sequencing of small subunit (SSU) rRNA and nitrogenase (nifH) gene amplicons and quantified rates of N2 fixation activity in Sphagnum fallax individuals sampled from experimental enclosures over 2 years in a northern Minnesota, USA bog. The taxonomic diversity of overall microbial communities and diazotroph communities, as well as N2 fixation rates, decreased with warming (p 〈 0.05). Following warming, diazotrophs shifted from a mixed community of Nostocales (Cyanobacteria) and Rhizobiales (Alphaproteobacteria) to predominance of Nostocales. Microbiome community composition differed between years, with some diazotroph populations persisting while others declined in relative abundance in warmed plots in the second year. Our results demonstrate that warming substantially alters the community composition, diversity, and N2 fixation activity of peat moss microbiomes, which may ultimately impact host fitness, ecosystem productivity, and C storage potential in peatlands.

Description: Six freshly isolated strains of the Arctic diatom Thalassiosira hyalina were incubated as mono‐ and multistrain cultures under different temperature and CO2 conditions. Although strains originated from the same water sample, monocultures showed large physiological diversity. When tested all together in multistrain cultures, selection dynamics as well as bulk physiology within these artificial populations differed fundamentally between the two treatments and diverged strongly from predictions based on monoculture traits. This suggests that cells change their phenotype depending on their biological surroundings and that such intraspecific interactions need to be better understood to predict future phytoplankton ecology from experimental data. Abstract Arctic phytoplankton and their response to future conditions shape one of the most rapidly changing ecosystems on the planet. We tested how much the phenotypic responses of strains from the same Arctic diatom population diverge and whether the physiology and intraspecific composition of multistrain populations differs from expectations based on single strain traits. To this end, we conducted incubation experiments with the diatom Thalassiosira hyalina under present‐day and future temperature and pCO2 treatments. Six fresh isolates from the same Svalbard population were incubated as mono‐ and multistrain cultures. For the first time, we were able to closely follow intraspecific selection within an artificial population using microsatellites and allele‐specific quantitative PCR. Our results showed not only that there is substantial variation in how strains of the same species cope with the tested environments but also that changes in genotype composition, production rates, and cellular quotas in the multistrain cultures are not predictable from monoculture performance. Nevertheless, the physiological responses as well as strain composition of the artificial populations were highly reproducible within each environment. Interestingly, we only detected significant strain sorting in those populations exposed to the future treatment. This study illustrates that the genetic composition of populations can change on very short timescales through selection from the intraspecific standing stock, indicating the potential for rapid population level adaptation to climate change. We further show that individuals adjust their phenotype not only in response to their physicochemical but also to their biological surroundings. Such intraspecific interactions need to be understood in order to realistically predict ecosystem responses to global change.

Description: We present a fine‐resolution assessment of the persistence of global plant biodiversity under land‐use and climate change scenarios, using generalized dissimilarity modelling and the species–area relationship. We estimate the number of species committed to extinction has increased by 60% globally during the 20th century; this value is projected to decrease slightly by 2050 under a sustainable land‐use scenario and to greatly increase under more intensive land‐use change scenarios. Alarmingly, the additional impact from climate change might largely surpass that of land use; sustainable land‐use planning might not be sufficient to prevent biodiversity loss, without a stabilization of climate to pre‐industrial times.  Abstract Nations have committed to ambitious conservation targets in response to accelerating rates of global biodiversity loss. Anticipating future impacts is essential to inform policy decisions for achieving these targets, but predictions need to be of sufficiently high spatial resolution to forecast the local effects of global change. As part of the intercomparison of biodiversity and ecosystem services models of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services, we present a fine‐resolution assessment of trends in the persistence of global plant biodiversity. We coupled generalized dissimilarity models, fitted to 〉52 million records of 〉254 thousand plant species, with the species–area relationship, to estimate the effect of land‐use and climate change on global biodiversity persistence. We estimated that the number of plant species committed to extinction over the long term has increased by 60% globally between 1900 and 2015 (from ~10,000 to ~16,000). This number is projected to decrease slightly by 2050 under the most optimistic scenario of land‐use change and to substantially increase (to ~18,000) under the most pessimistic scenario. This means that, in the absence of climate change, scenarios of sustainable socio‐economic development can potentially bring extinction risk back to pre‐2000 levels. Alarmingly, under all scenarios, the additional impact from climate change might largely surpass that of land‐use change. In this case, the estimated number of species committed to extinction increases by 3.7–4.5 times compared to land‐use‐only projections. African regions (especially central and southern) are expected to suffer some of the highest impacts into the future, while biodiversity decline in Southeast Asia (which has previously been among the highest globally) is projected to slow down. Our results suggest that environmentally sustainable land‐use planning alone might not be sufficient to prevent potentially dramatic biodiversity loss, unless a stabilization of climate to pre‐industrial times is observed.

Description: We study how climate change may affect an important Neotropical ecosystem: the aquatic food webs inside bromeliad plants. To explore potential mechanisms, we combine common garden experiments and food web manipulations with space‐for‐time community transplants along an elevational gradient. Our study experimentally disentangles the multiple mechanisms by which climate change impacts ecosystems, and demonstrates how a single species can act as a biotic multiplier for climate change, drastically affecting the food web response. Abstract Predicting the biological effects of climate change presents major challenges due to the interplay of potential biotic and abiotic mechanisms. Climate change can create unexpected outcomes by altering species interactions, and uncertainty over the ability of species to develop in situ tolerance or track environmental change further hampers meaningful predictions. As multiple climatic variables shift in concert, their potential interactions further complicate ecosystem responses. Despite awareness of these complexities, we still lack controlled experiments that manipulate multiple climatic stressors, species interactions, and prior exposure of species to future climatic conditions. Particularly studies that address how changes in water availability interact with other climatic stressors to affect aquatic ecosystems are still rare. Using aquatic insect communities of Neotropical tank bromeliads, we combined controlled manipulations of drought length and species interactions with a space‐for‐time transplant (lower elevations represent future climate) and a common garden approach. Manipulating drought length and experiment elevation revealed that adverse effects of drought were amplified at the warmer location, highlighting the potential of climatic stressors to synergistically affect communities. Manipulating the presence of omnivorous tipulid larvae showed that negative interactions from tipulids, presumably from predation, arose under drought, and were stronger at the warmer location, stressing the importance of species interactions in mediating community responses to climate change. The common garden treatments revealed that prior community exposure to potential future climatic conditions did not affect the outcome. In this powerful experiment, we demonstrated how complexities arise from the interplay of biotic and abiotic mechanisms of climate change. We stress that single species can steer ecological outcomes, and suggest that focusing on such disproportionately influential species may improve attempts at making meaningful predictions of climate change impacts on food webs.

Description: Since 1990, the IPCC has produced five Assessment Reports (ARs) including agriculture. Using a database of the ca. 2,100 cited experiments and simulations in the five ARs, our conclusions are that crop yields decline but with large statistical variation. Livestock effects have almost been quantitatively absent. Mitigation assessments need better to link emissions and their mitigation with food production and security; agriculture has been dealt with inconsistently between the IPCC five ARs. IPCC needs to examine interactions between crop resource use efficiencies and include production and nonproduction aspects of food security. Abstract Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom‐up and top‐down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.

Description: We provide a description of regime shifts of forest carbon sinks in Mediterranean forests (Pinus halepensis Mill.) over 1950–2012. We demonstrate that non‐stationary effects of ocean surface temperature determine the onset of regime shifts of forest carbon uptake. ENSO effects regulated by ocean multidecadal variability (AMO–AMOC) are key in the emergence of multidecadal changes in forest carbon sink activity. The reported negative effects of ocean surface temperature (SST) trends on forest carbon uptake for the last decades are unprecedented over the last 150 years. Abstract The mechanisms translating global circulation changes into rapid abrupt shifts in forest carbon capture in semi‐arid biomes remain poorly understood. Here, we report unprecedented multidecadal shifts in forest carbon uptake in semi‐arid Mediterranean pine forests in Spain over 1950–2012. The averaged carbon sink reduction varies between 31% and 37%, and reaches values in the range of 50% in the most affected forest stands. Regime shifts in forest carbon uptake are associated with climatic early warning signals, decreased forest regional synchrony and reduced long‐term carbon sink resilience. We identify the mechanisms linked to ocean multidecadal variability that shape regime shifts in carbon capture. First, we show that low‐frequency variations of the surface temperature of the Atlantic Ocean induce shifts in the non‐stationary effects of El Niño Southern Oscillation (ENSO) on regional forest carbon capture. Modelling evidence supports that the non‐stationary effects of ENSO can be propagated from tropical areas to semi‐arid Mediterranean biomes through atmospheric wave trains. Second, decadal changes in the Atlantic Multidecadal Oscillation (AMO) significantly alter sea–air heat exchanges, modifying in turn ocean vapour transport over land and land surface temperatures, and promoting sustained drought conditions in spring and summer that reduce forest carbon uptake. Third, we show that lagged effects of AMO on the winter North Atlantic Oscillation also contribute to the maintenance of long‐term droughts. Finally, we show that the reported strong, negative effects of ocean surface temperature (AMO) on forest carbon uptake in the last decades are unprecedented over the last 150 years. Our results provide new, unreported explanations for carbon uptake shifts in these drought‐prone forests and review the expected impacts of global warming on the profiled mechanisms.

Description: Coral bleaching and mortality following marine heatwaves are transforming coral reefs, but the long‐term effects of habitat turnover for coral reef fishes remain unclear. Using a 23‐year time series spanning a severe marine heatwave, we show that reef fish communities persisted in altered compositions 〉15 years after mass coral mortality. After bleaching, herbivore dominance was typical of all reefs, and new macroalgal habitats were most dissimilar to their historic compositions. Frequent and severe bleaching events caused by ocean warming will prevent reef fish communities from recovering to their prebleaching state. Abstract Ecological communities are reorganizing in response to warming temperatures. For continuous ocean habitats this reorganization is characterized by large‐scale species redistribution, but for tropical discontinuous habitats such as coral reefs, spatial isolation coupled with strong habitat dependence of fish species imply that turnover and local extinctions are more significant mechanisms. In these systems, transient marine heatwaves are causing coral bleaching and profoundly altering habitat structure, yet despite severe bleaching events becoming more frequent and projections indicating annual severe bleaching by the 2050s at most reefs, long‐term effects on the diversity and structure of fish assemblages remain unclear. Using a 23‐year time series spanning a thermal stress event, we describe and model structural changes and recovery trajectories of fish communities after mass bleaching. Communities changed fundamentally, with the new emergent communities dominated by herbivores and persisting for 〉15 years, a period exceeding realized and projected intervals between thermal stress events on coral reefs. Reefs which shifted to macroalgal states had the lowest species richness and highest compositional dissimilarity, whereas reefs where live coral recovered exceeded prebleaching fish richness, but remained dissimilar to prebleaching compositions. Given realized and projected frequencies of bleaching events, our results show that fish communities historically associated with coral reefs will not re‐establish, requiring substantial adaptation by managers and resource users.

Description: Many populations face large changes in seasonal climate, yet the demographic mechanisms that mediate the impact of these changes on population dynamics remain largely unknown. We demonstrate a widely applicable method to facilitate better understanding of the mechanisms through which climatic variables drive population responses. In a well‐studied mammal population we found that a single axis accounts for most of the (co)variation in survival and reproduction and when we attribute seasonal impacts of climatic variables to this axis we find that the direction and magnitude of their effects changes over the course of a year. Abstract Predicting how species will be affected by future climatic change requires the underlying environmental drivers to be identified. As vital rates vary over the lifecycle, structured population models derived from statistical environment–demography relationships are often used to inform such predictions. Environmental drivers are typically identified independently for different vital rates and demographic classes. However, these rates often exhibit positive temporal covariance, suggesting that vital rates respond to common environmental drivers. Additionally, models often only incorporate average weather conditions during a single, a priori chosen time window (e.g. monthly means). Mismatches between these windows and the period when the vital rates are sensitive to variation in climate decrease the predictive performance of such approaches. We used a demographic structural equation model (SEM) to demonstrate that a single axis of environmental variation drives the majority of the (co)variation in survival, reproduction, and twinning across six age–sex classes in a Soay sheep population. This axis provides a simple target for the complex task of identifying the drivers of vital rate variation. We used functional linear models (FLMs) to determine the critical windows of three local climatic drivers, allowing the magnitude and direction of the climate effects to differ over time. Previously unidentified lagged climatic effects were detected in this well‐studied population. The FLMs had a better predictive performance than selecting a critical window a priori, but not than a large‐scale climate index. Positive covariance amongst vital rates and temporal variation in the effects of environmental drivers are common, suggesting our SEM–FLM approach is a widely applicable tool for exploring the joint responses of vital rates to environmental change.

Description: Elevated pCO2 and warming may promote algal growth and toxin production, and thereby possibly support the proliferation and toxicity of HABs. Using a meta‐analytic approach we found that elevated pCO2 increased growth rates of dinoflagellate HAB species, while this was not the case for non‐HAB phytoplankton species. Warming also led to higher growth rates, but mainly for species isolated at higher latitudes. These results warn for a greater potential of dinoflagellate HAB development in future coastal waters, particularly in temperate regions. Abstract Elevated pCO2 and warming may promote algal growth and toxin production, and thereby possibly support the proliferation and toxicity of harmful algal blooms (HABs). Here, we tested whether empirical data support this hypothesis using a meta‐analytic approach and investigated the responses of growth rate and toxin content or toxicity of numerous marine and estuarine HAB species to elevated pCO2 and warming. Most of the available data on HAB responses towards the two tested climate change variables concern dinoflagellates, as many members of this phytoplankton group are known to cause HAB outbreaks. Toxin content and toxicity did not reveal a consistent response towards both tested climate change variables, while growth rate increased consistently with elevated pCO2. Warming also led to higher growth rates, but only for species isolated at higher latitudes. The observed gradient in temperature growth responses shows the potential for enhanced development of HABs at higher latitudes. Increases in growth rates with more CO2 may present an additional competitive advantage for HAB species, particularly as CO2 was not shown to enhance growth rate of other non‐HAB phytoplankton species. However, this may also be related to the difference in representation of dinoflagellate and diatom species in the respective HAB and non‐HAB phytoplankton groups. Since the proliferation of HAB species may strongly depend on their growth rates, our results warn for a greater potential of dinoflagellate HAB development in future coastal waters, particularly in temperate regions.

Description: This study addresses how nutrient addition regulates biological nitrogen (N) fixation (BNF) in terrestrial ecosystems and uncovers the latitude patterns and drivers of BNF in response to nutrient enrichment. We found a negative effect of N addition, a positive effect of Micro addition, and an inconsistent effect of P addition on terrestrial BNF and also observed a less sensitivity of BNF to nutrient addition in low‐latitude biomes than in mid‐/high‐latitude biomes. Our findings indicate that certain types of global change (warming, elevated precipitation and N deposition) may reduce the nutrient constraints of BNF in mid‐/high‐latitude biomes. Abstract Biological nitrogen (N) fixation (BNF), an important source of N in terrestrial ecosystems, plays a critical role in terrestrial nutrient cycling and net primary productivity. Currently, large uncertainty exists regarding how nutrient availability regulates terrestrial BNF and the drivers responsible for this process. We conducted a global meta‐analysis of terrestrial BNF in response to N, phosphorus (P), and micronutrient (Micro) addition across different biomes (i.e, tropical/subtropical forest, savanna, temperate forest, grassland, boreal forest, and tundra) and explored whether the BNF responses were affected by fertilization regimes (nutrient‐addition rates, duration, and total load) and environmental factors (mean annual temperature [MAT], mean annual precipitation [MAP], and N deposition). The results showed that N addition inhibited terrestrial BNF (by 19.0% (95% confidence interval [CI]: 17.7%‒20.3%); hereafter), Micro addition stimulated terrestrial BNF (30.4% [25.7%‒35.3%]), and P addition had an inconsistent effect on terrestrial BNF, i.e., inhibiting free‐living N fixation (7.5% [4.4%‒10.6%]) and stimulating symbiotic N fixation (85.5% [25.8%‒158.7%]). Furthermore, the response ratios (i.e., effect sizes) of BNF to nutrient addition were smaller in low‐latitude (〈30°) biomes (8.5%‒36.9%) than in mid‐/high‐latitude (≥30°) biomes (32.9%‒61.3%), and the sensitivity (defined as the absolute value of response ratios) of BNF to nutrients in mid‐/high‐latitude biomes decreased with decreasing latitude (p ≤ 0.009; linear/logarithmic regression models). Fertilization regimes did not affect this phenomenon (p 〉 0.05), but environmental factors did affect it (p 〈 0.001) because MAT, MAP, and N deposition accounted for 5%‒14%, 10%‒32%, and 7%‒18% of the variance in the BNF response ratios in cold (MAT 〈 15°C), low‐rainfall (MAP 〈 2,500 mm), and low‐N‐deposition (〈7 kg ha−1 year−1) biomes, respectively. Overall, our meta‐analysis depicts a global pattern of nutrient impacts on terrestrial BNF and indicates that certain types of global change (i.e., warming, elevated precipitation and N deposition) may reduce the sensitivity of BNF in response to nutrient enrichment in mid‐/high‐latitude biomes.

Description: Exposure of a temperate heath/grassland to elevated CO2 (eCO2), warming, and drought, in all combinations for 8 years resulted in a progressive increase in soil carbon stocks under eCO2. The response to eCO2 was not affected by simultaneous exposure to warming and drought. The robust increase in soil C under eCO2 suggests that there is continued and strong potential for enhanced soil carbon sequestration in some ecosystems to mitigate increasing atmospheric CO2 concentrations under future climate conditions Abstract Elevated atmospheric CO2 concentration and climate change may substantially alter soil carbon (C) dynamics, which in turn may impact future climate through feedback cycles. However, only very few field experiments worldwide have combined elevated CO2 (eCO2) with both warming and changes in precipitation in order to study the potential combined effects of changes in these fundamental drivers of C cycling in ecosystems. We exposed a temperate heath/grassland to eCO2, warming, and drought, in all combinations for 8 years. At the end of the study, soil C stocks were on average 0.927 kg C/m2 higher across all treatment combinations with eCO2 compared to ambient CO2 treatments (equal to an increase of 0.120 ± 0.043 kg C m−2 year−1), and showed no sign of slowed accumulation over time. However, if observed pretreatment differences in soil C are taken into account, the annual rate of increase caused by eCO2 may be as high as 0.177 ± 0.070 kg C m−2 year−1. Furthermore, the response to eCO2 was not affected by simultaneous exposure to warming and drought. The robust increase in soil C under eCO2 observed here, even when combined with other climate change factors, suggests that there is continued and strong potential for enhanced soil carbon sequestration in some ecosystems to mitigate increasing atmospheric CO2 concentrations under future climate conditions. The feedback between land C and climate remains one of the largest sources of uncertainty in future climate projections, yet experimental data under simulated future climate, and especially including combined changes, are still scarce. Globally coordinated and distributed experiments with long‐term measurements of changes in soil C in response to the three major climate change‐related global changes, eCO2, warming, and changes in precipitation patterns, are, therefore, urgently needed.

Description: In this study, we analysed the relationship between changes in mean precipitation, precipitation variability, farming practices and grazing cattle using a system dynamics approach for a semi‐arid Australian rangeland system. Forage production and animal stocking rates were significantly affected by drought events as well as by long‐term climate trends. Decreases in the annual precipitation means or increases in the interannual (year‐to‐year) and intra‐annual (month‐to‐month) precipitation variability, all reduced herd sizes. Climate contributed the most to the variance in stocking rates, followed by forage productivity levels and feeding supplementation practices (with or without urea and molasses). While intensification strategies and favourable climates increased long‐term herd sizes, they also resulted in larger reductions in animal numbers during droughts and raised total enteric methane emissions. Abstract Grazing livestock are an important source of food and income for millions of people worldwide. Changes in mean climate and increasing climate variability are affecting grasslands' carrying capacity, thus threatening the livelihood of millions of people as well as the health of grassland ecosystems. Compared with cropping systems, relatively little is known about the impact of such climatic changes on grasslands and livestock productivity and the adaptation responses available to farmers. In this study, we analysed the relationship between changes in mean precipitation, precipitation variability, farming practices and grazing cattle using a system dynamics approach for a semi‐arid Australian rangeland system. We found that forage production and animal stocking rates were significantly affected by drought intensities and durations as well as by long‐term climate trends. After a drought event, herd size recovery times ranged from years to decades in the absence of proactive restocking through animal purchases. Decreases in the annual precipitation means or increases in the interannual (year‐to‐year) and intra‐annual (month‐to‐month) precipitation variability, all reduced herd sizes. The contribution of farming practices versus climate effect on herd dynamics varied depending on the herd characteristics considered. Climate contributed the most to the variance in stocking rates, followed by forage productivity levels and feeding supplementation practices (with or without urea and molasses). While intensification strategies and favourable climates increased long‐term herd sizes, they also resulted in larger reductions in animal numbers during droughts and raised total enteric methane emissions. In the face of future climate trends, the grazing sector will need to increase its adaptability. Understanding which farming strategies can be beneficial, where, and when, as well as the enabling mechanisms required to implement them, will be critical for effectively improving rangelands and the livelihoods of pastoralists worldwide.

Description: Cover crops significantly (p 〈 0.001) decreased N leaching and significantly (p 〈 0.001) increased soil organic carbon sequestration without having significant (p 〉 0.05) effects on direct N2O emissions. Cover crops could mitigate net greenhouse gas balance by 2.06 ± 2.10 Mg CO2‐eq ha−1 year−1. One of the potential disadvantages of the cover crops identified was the reduction in grain yield of the primary crop by ≈4%, compared to the control treatment. This drawback could be avoided by selecting legume–non‐legume mixed cover crops. However, cover crop management need to be adapted to specific soil, management and regional climatic conditions. Abstract Cover crops play an increasingly important role in improving soil quality, reducing agricultural inputs and improving environmental sustainability. The main objectives of this critical global review and systematic analysis were to assess cover crop practices in the context of their impacts on nitrogen leaching, net greenhouse gas balances (NGHGB) and crop productivity. Only studies that investigated the impacts of cover crops and measured one or a combination of nitrogen leaching, soil organic carbon (SOC), nitrous oxide (N2O), grain yield and nitrogen in grain of primary crop, and had a control treatment were included in the analysis. Long‐term studies were uncommon, with most data coming from studies lasting 2–3 years. The literature search resulted in 106 studies carried out at 372 sites and covering different countries, climatic zones and management. Our analysis demonstrates that cover crops significantly (p 〈 0.001) decreased N leaching and significantly (p 〈 0.001) increased SOC sequestration without having significant (p 〉 0.05) effects on direct N2O emissions. Cover crops could mitigate the NGHGB by 2.06 ± 2.10 Mg CO2‐eq ha−1 year−1. One of the potential disadvantages of cover crops identified was the reduction in grain yield of the primary crop by ≈4%, compared to the control treatment. This drawback could be avoided by selecting mixed cover crops with a range of legumes and non‐legumes, which increased the yield by ≈13%. These advantages of cover crops justify their widespread adoption. However, management practices in relation to cover crops will need to be adapted to specific soil, management and regional climatic conditions.

Description: We manipulated the rate and frequency of nitrogen inputs for six consecutive years in a temperate grassland in northern China and measured aboveground net primary productivity (ANPP) and belowground net primary productivity (BNPP) from 2012 to 2014. We found that in the low range of N addition rates, BNPP showed the greatest negative response and ANPP showed the greatest positive responses with increases in N addition. As N addition increased beyond 10 g N m−2 year−1, increases in ANPP dampened and decreases in BNPP ceased altogether. Abstract Nitrogen (N) enrichment often increases aboveground net primary productivity (ANPP) of the ecosystem, but it is unclear if belowground net primary productivity (BNPP) track responses of ANPP. Moreover, the frequency of N inputs may affect primary productivity but is rarely studied. To assess the response patterns of above‐ and belowground productivity to rates of N addition under different addition frequencies, we manipulated the rate (0–50 g N m−2 year−1) and frequency (twice vs. monthly additions per year) of NH4NO3 inputs for six consecutive years in a temperate grassland in northern China and measured ANPP and BNPP from 2012 to 2014. In the low range of N addition rates, BNPP showed the greatest negative response and ANPP showed the greatest positive responses with increases in N addition (〈10 g N m−2 year−1). As N addition increased beyond 10 g N m−2 year−1, increases in ANPP dampened and decreases in BNPP ceased altogether. The response pattern of net primary productivity (combined above‐ and belowground; NPP) corresponded more closely to ANPP than to BNPP. The N effects on BNPP and BNPP/NPP (fBNPP) were not dependent on N addition frequency in the range of N additions typically associated with N deposition. BNPP was more sensitive to N addition frequency than ANPP, especially at low rates of N addition. Our findings provide new insights into how plants regulate carbon allocation to different organs with increasing N rates and changing addition frequencies. These root response patterns, if incorporated into Earth system models, may improve the predictive power of C dynamics in dryland ecosystems in the face of global atmospheric N deposition.

Description: Abstract Aim To identify the effect of multiple, temporally close, forcing events (i.e. climate‐driven habitat fragmentations/homogenizations) in shaping current patterns of biodiversity in alpine areas. Given their spatial configuration, alpine areas have been traditionally seen as islands surrounded by an “ocean” of unsuitable lands. A quantitative assessment of the effects of Holocene climate fluctuations on islands area and inter‐island connectivity is crucial to finely reconstruct past biodiversity dynamics and forecast species responses to future changes. Location Italy. Taxa Carabidae (Ground beetles), Chrysomelidae (Leaf beetles), Elateridae (Click beetles), Orthoptera (Grasshoppers and Crickets) and Papilionoidea (Butterflies and Skippers). Methods A total of 1,077 species for 128,093 records were analysed and a classification based on their functional traits allowed identifying groups of good and poor dispersers within each taxon. A dynamic discrete model of ecosystem evolution provided the spatio‐temporal context to test two competing (transient equilibria vs. nonequilibrium) dynamics based on different colonization capabilities. In the transient equilibria dynamic the species are able to respond to island evolution through successful dispersal and colonization events, whereas in the nonequilibrium dynamic ineffective immigration constrains the current species richness to that generated by the strongest island contraction. Results With the exception of Elateridae, good dispersers (Chrysomelidae and Papilionoidea) responded to environmental changes by establishing a series of transient equilibria. In contrast, the nonequilibrium dynamic better described patterns of species richness in poor dispersers (Carabidae and Orthoptera). Main conclusions Our approach could be used as the basis for the development of spatially and temporally explicit models of island evolution and could be a valuable tool for quantifying the sensitivity of single taxa to climate‐driven habitat changes. It also represents a further step towards the forecasting of future responses to climate change and the accompanying development of conservation strategies that more effectively respond to the detrimental impacts of climate change on biodiversity.

Description: A schematic illustration of the assimilation windows employed by the ECMWF Long Window Data Assimilation (LWDA) system. Black dots represent observations distributed quasi‐randomly in time throughout the window. This study quantifies the extent to which the ECMWF 4D‐Var displays differential (heightened) sensitivity to observations located near the end of the 12‐hr assimilation time window compared to observations located near the start of the window. Using dedicated satellite data denial experiments, it is shown that the lattermost 3 hr of observations are significantly more influential on the quality of the assimilation and forecasting system than the first 3 hr of data. Furthermore, it is found that the last 3 hr of data even outperforms the 6 hr of data (i.e. twice the number of observations) located in the first half of the window. The heightened importance of late window data is discussed in terms of these measurements being our most up‐to‐date information on the atmosphere, but also their ability to provide additional dynamical information to the assimilation system via feature advection wind tracing. The implications of this sensitivity are discussed. Firstly, it leads to the existence of influential (late window) satellite orbits, the location of which can have a strong bearing on the impact of observations from different satellites in different regions. Secondly, this sensitivity reinforces the need for data providers to minimize dissemination delays to ensure that crucial late window data reach users in time to be assimilated. Finally, numerical weather prediction (NWP) centres (who run 4D systems) must ensure that these lattermost observations are being captured and used effectively. Some suggestions for this are proposed.

Description: The Netherlands is characterized by highly variable land use within a small area, and a strong influence of the North Sea on national climate. Devoid of significant topography, it is an excellent location for assessing the relative influence of various factors on fog occurrence in the absence of terrain effects. Using observations from a dense network of weather stations throughout the country, the climatology of fog in the Netherlands is assessed over a period of 45 years. On a national scale, inter‐annual variability is linked to changes in synoptic pressure‐gradient forcing. Within the country, a comprehensive in‐depth analysis of regional differences between fog occurrence is made, together with an assessment of local physical factors that could bias fog formation in one location over another. Regional variability is shown to be strongly related to the mesoscale influences of urbanization and the North Sea. In fact, some locations experience over twice as much fog as others. From this finding, a simple index is presented, which combines the water and urban fraction surrounding a station. This “Regionally Weighted Index” (RWI) is able to accurately sort the stations according to their relative fogginess. Its practical use is encouraged for assessing a given site's climatological favourability, even when in situ meteorological observations are unavailable. This article is protected by copyright. All rights reserved.

Description: Abstract Reliable estimation of the volume and timing of snowmelt runoff is vital for water supply and flood forecasting in snow‐dominated regions. Snowmelt is often simulated using temperature‐index (TI) models due to their applicability in data‐sparse environments. Previous research has shown that a modified‐TI model, which uses a radiation‐derived proxy temperature instead of air temperature as its surrogate for available energy, can produce more accurate snow covered area (SCA) maps than a traditional TI model. However, it is unclear whether the improved SCA maps are associated with improved snow water equivalent (SWE) estimation across the watershed or improved snowmelt‐derived streamflow simulation. This paper evaluates whether a modified‐TI model produces better streamflow estimates than a TI model when they are used within a fully‐distributed hydrologic model. It further evaluates the performance of the two models when they are calibrated using either point SWE measurements or SCA maps. The Senator Beck Basin in Colorado is used as the study site because its surface is largely bedrock, which reduces the role of infiltration and emphasizes the role of the SWE pattern on streamflow generation. Streamflow is simulated using both models for six years. The modified‐TI model produces more accurate streamflow estimates (including flow volume and peak flow rate) than the TI model, likely because the modified‐TI model better reproduces the SWE pattern across the watershed. Both models also produce better performance when calibrated with SCA maps instead of point SWE data, likely because the SCA maps better constrain the space‐time pattern of SWE.

Description: Abstract The development of glacier karst at the margins of melting ice sheets produces complex glaciofluvial sediment‐landform assemblages that provide information on ice sheet downwasting processes. We present the first combined geomorphological, sedimentological and geophysical investigation of the Brampton Kame Belt, an important glaciofluvial depositional zone at the centre of the last British‐Irish Ice Sheet. Ground‐penetrating radar (GPR) data allow the broad scale internal architecture of ridges (eskers) and flat‐topped hills (ice‐walled lake plains) to be determined at four sites. In combination with sediment exposures, these provide information on lateral and vertical variations in accretion styles, depositional boundaries, and grain size changes. Building on existing work on the subject, we propose a refined model for the formation of ice‐walled lake plains resulting from the evolution and collapse of major drainage axes into lakes as stable glacier karst develops during deglaciation. The internal structure of esker ridges demonstrates variations in sedimentation that can be linked to differences in ridge morphologies across the kame belt. This includes low energy flow conditions and multiple accretion phases identified within large S‐N oriented esker ridges; and fluctuating water pressures, hyperconcentrated flows, and significant deformation within a fragmented SW‐NE oriented esker ridge. In combination with updated geomorphological mapping, this work allows us to identify two main styles of drainage within the kame belt: (1) major drainage axes aligned broadly S‐N that extend through the entire kame belt and collapsed into a chain of ice‐walled lakes; and (2) a series of smaller, fragmented SW‐NE aligned esker ridges that represent ice‐marginal drainage as the ice sheet receded south‐eastwards up the Vale of Eden. Our study demonstrates the importance of integrated geomorphological, sedimentological and geophysical investigations in order to understand complex and polyphase glaciofluvial sediment‐landform assemblages.

Description: Abstract Aims Phylogenetic endemism describes the extent to which unique phylogenetic lineages are constrained to restricted geographic areas. Previous studies indicate that species endemism is related to both past and modern climate, but studies of phylogenetic endemism are relatively rare and mainly focused on smaller regions. Here, we provide the first assessment of the patterns of species and phylogenetic endemism in angiosperm trees across the Northern Hemisphere as well as the relative importance of modern climate and glacial–interglacial climate change as drivers of these patterns. Location Northern Hemisphere. Major taxa Angiosperm trees. Methods Using tree assemblages at the scale of 100 km × 100 km grid cells and simultaneous autoregressive (SAR) models, we assessed the relationships between species endemism, phylogenetic endemism and modern climate variables, Last Glacial Maximum (LGM) to present temperature velocity. Results Species and phylogenetic endemism were associated with both modern climate and glacial–interglacial climate change, with higher values in areas with stable historical climate and warmer and wetter modern conditions. Notably, the multivariate SAR analyses showed that the combinations of variables with highest Akaike’s information criterion (AIC) weight always included both LGM–present climate instability and modern climate, that is, modern precipitation and temperature. Main conclusions Our results show that high phylogenetic endemism is partially dependent on long‐term climate stability, highlighting the threat posed by future climate changes to the preservation of rare, phylogenetically distinct lineages of trees.

Description: Abstract Oxygen deficient zones (ODZs) in the tropical ocean exert a profound influence on global biogeochemical cycles, but the factors that regulate their long‐term structure and sensitivity to oceanic change remain poorly understood. We analyzed hydrographic observations and a high‐resolution physical/biogeochemical model to diagnose the primary pathways that ventilate the tropical Pacific ODZs. Historical and recent autonomous observations reveal pronounced and widespread O2 peaks, termed secondary oxygen maxima (SOMs), within the depths of the broader O2 minimum layer, especially at the equatorward edge of both northern and southern ODZs. In the northern ODZ, Lagrangian particle tracking in an eddy‐permitting numerical model simulation attributes these features to intrusions of the Northern Subsurface Countercurrent along the equatorial edge of the ODZ. Zonal subsurface jets also ventilate the poleward edge of the northern ODZ but induce a smaller O2 flux and do not yield detectable SOMs. Along the ODZ's eastern boundary, oxygenation is achieved by the seasonal cycle of upwelling of low‐O2 water onto the continental shelf, followed by downwelling of O2‐replenished near‐surface waters back into the ODZ. Waters entering the northern Pacific ODZ originate from the extratropics in both hemispheres, but two thirds are from the Southern Hemisphere and arrive later and with a wider range of transit times. These results suggest that predicting future changes in the large Pacific ODZs will require a better understanding of the climate sensitivity of the narrow zonal jets and seasonal dynamics of coastal upwelling that supply their O2.

Description: Severe winter windstorms have become an increasingly common occurrence over recent decades in northwestern Europe. Although there exists considerable uncertainty, storminess is projected to increase in the future. On centennial to millennial time scales in particular, the mechanisms forcing storminess remain unsettled. We contribute to available palaeostorm records by reconstructing changes over the last 6670 years using a coastal peat sequence retrieved from the ombrotrophic Laphroaig bog on Islay, southwestern Scotland. We use a combination of ash content, grain size and elemental chemistry to identify periods of greater storminess, which are dated to 6605, 6290–6225, 5315–5085, 4505, 3900–3635, 3310–3130, 2920–2380, 2275–2190, 2005–1860, 1305–1090, 805–435 and 275 cal. a BP. Storm signals in the first half of the record up to ~3000 cal. a BP are mainly apparent in the grain‐size changes. Samples from this time period also have a different elemental signature than those later in the record. We speculate that this is due to receding sea levels and the consequent establishment of a new sand source in the form of dunes, which are still present today. The most significant events and strongest winds are found during the Iron Ages Cold Epoch (2645 cal. a BP), the transition into, and in the middle of, the Roman Ages Warm Period (2235 and 1965 cal. a BP) and early in the Little Ice Age (545 cal. a BP). The Laphroaig record generally agrees with regionally relevant peat palaeostorm records from Wales and the Outer Hebrides, although the relative importance of the different storm periods is not the same. In general, stormier periods are coeval with cold periods in the region as evidenced by parallels with increased ice‐rafted debris in the North Atlantic, highlighting that sea‐ice conditions could impact future storminess and storm track position.

Description: Abstract This study aims at proposing novel approaches for integrating qualitative flow observations in a lumped hydrologic routing model and assessing their usefulness for improving flood estimation. Routing is based on a three‐parameter Muskingum model used to propagate streamflow in five different rivers in the United States. Qualitative flow observations, synthetically generated from observed flow, are converted into fuzzy observations using flow characteristic for defining fuzzy classes. A model states updating method and a model output correction technique are implemented. An innovative application of Interacting Multiple Models, which use was previously demonstrated on tracking in ballistic missile applications, is proposed as state updating method, together with the traditional Kalman filter. The output corrector approach is based on the fuzzy error corrector, which was previously used for robots navigation. This study demonstrates the usefulness of integrating qualitative flow observations for improving flood estimation. In particular, state updating methods outperform the output correction approach in terms of average improvement of model performances, while the latter is found to be less sensitive to biased observations and to the definition of fuzzy sets used to represent qualitative observations.

Description: Abstract The Sustainable Development Goals (SDGs) of the United Nations Agenda 2030 represent an ambitious blueprint to reduce inequalities globally and achieve a sustainable future for all mankind. Meeting the SDGs for water requires an integrated approach to managing and allocating water resources, by involving all actors and stakeholders, and considering how water resources link different sectors of society. To date, water management practice is dominated by technocratic, scenario‐based approaches that may work well in the short‐term, but can result in unintended consequences in the long‐term due to limited accounting of dynamic feedbacks between the natural, technical and social dimensions of human‐water systems. The discipline of socio‐hydrology has an important role to play in informing policy by developing a generalizable understanding of phenomena that arise from interactions between water and human systems. To explain these phenomena, socio‐hydrology must address several scientific challenges to strengthen the field and broaden its scope. These include engagement with social scientists to accommodate social heterogeneity, power relations, trust, cultural beliefs, and cognitive biases, which strongly influence the way in which people alter, and adapt to, changing hydrological regimes. It also requires development of new methods to formulate and test alternative hypotheses for the explanation of emergent phenomena generated by feedbacks between water and society. Advancing socio‐hydrology in these ways therefore represents a major contribution towards meeting the targets set by the SDGs, the societal grand challenge of our time.

Description: Abstract Field data of topography, water levels, and peat hydraulic conductivity collected over a 28‐year period have revealed the impacts of marginal drainage on uncut raised bog ecohydrology and its peat properties. Drainage of the regional groundwater body has induced changes in the hydraulic properties of deep peat, with peat compression decreasing hydraulic conductivity and storativity while simultaneously introducing localized secondary porosity and effective storage. Where peat has increased in hydraulic conductivity, there is a corresponding decline in vertical hydraulic gradients and significant localized increases in recharge to the underlying substrate. Repeated topographic surveys show intense localized areas of peat consolidation (〉5%) where it is underlain by highly permeable (〉10 m/day) glacial till deposits. More widely, continued subsidence (4–6 mm/year) of the bog surface has been measured over 900 m from the bog margin, resulting in the progressive loss of approximately 40% of actively growing raised bog since 1991. This loss has thus been shown to be attributable to changes in the underlying groundwater head due to deep‐cut drainage, rather than near‐surface peatland drainage. However, although reinstating regional hydrostatic pressures in order to restore this ombrotrophic peatland may control the rapid drainage through preferential flow pathways, this may not eliminate the ecological impacts resulting from changed surface morphology arising from subsidence. Hence, this longitudinal study provides new insights into the role that aquifer systems and groundwater bodies play in maintaining hydrogeological processes in ombrotrophic peatland systems, while highlighting the difficulty in ecological restoration where regional groundwater dependencies are significant.

Description: Atmospheric angular momentum (AAM) is a quantity related to the global distributions of surface pressure and zonal wind. We found that the AAM has increased in the 20th century, mainly due its zonal wind component. However, the AAM budget in the ERA‐20C reanalysis is not well‐closed, which can be largely attributed to the analysis increments. It is well known that global warming in the 20th century has influenced the global circulation of the atmosphere. Atmospheric angular momentum (AAM), a measure of the rotation of the atmosphere around the Earth's axis, is a useful quantity to investigate changes in the global atmospheric circulation. In this study, 20th century trends in the AAM budget are determined using the ERA‐20C reanalysis data of the European Centre for Medium‐Range Weather Forecasts (ECMWF). In addition, the closure of the AAM budget is determined to assess the ability of ERA‐20C to conserve angular momentum. The total AAM has increased in the 20th century, associated mainly with an increasing relative (zonal wind) AAM in most of the stratosphere and the tropical upper troposphere, and a poleward redistribution in the midlatitudes. These trends can be related to the warming in the troposphere and cooling in the lower stratosphere found in this study, likely caused by increasing atmospheric CO2 concentrations. The Ω‐AAM, representing the rotation of the atmosphere along with the Earth, shows no clear trend, but a spurious peak around 1920. This peak is caused by a global increase in surface pressure and is considered an artefact of changes in the amount of assimilated observations. It is also found that the AAM budget is not well closed in ERA‐20C, which is mainly the result of the assimilation of observations during production of the reanalysis. The trends in the AAM budget in ERA‐20C are likely affected by changes in the number of assimilated observations and should be validated with other reanalyses in further research.

Description: (a) Radar at [0800 UTC‐1100 UTC] on 30 October, (b) neighbourhood ensemble probability (NEP) of accumulated rainfall 0800‐1100 UTC on 30 October to exceed rain amounts of 6 mm over the 3 h for EC‐SINGV, and (c) UM‐SINGV. The simulations are initialized at 1500 UTC 29 October. A convective‐scale ensemble system was developed to predict the occurrence of heavy convective rainfall around Singapore with a focus on the prediction of high‐impact events. The new ensemble SINGV‐EPS has been nested within two global ensembles, MOGREPS‐G (UK Met Office) and EC‐ENS (ECMWF). Predicting the occurrence of convective rainfall in an area such as Singapore is challenging and this article discusses the use of the convection‐permitting ensemble to characterize the uncertainties in the prediction of such localized heavy rainfall. First, verification of wind, temperature, and precipitation is performed for a month‐long period to assess the relative performance of each ensemble. This reveals differences, but no robust signal to say one is better than the other. The results are not statistically significant and not all variables are consistently better with one ensemble or the other. Secondly, the precipitation characteristics of SINGV‐EPS are analysed from probabilities of precipitation and variability among the ensemble members. SINGV‐EPS is sensitive to the choice of the global ensemble providing the initial conditions and boundaries. The results suggest there is benefit, in some cases, from combining the two ensembles. Thirdly, the spread of the ensemble precipitation is analysed using the dispersion Fractions Skill Score (dFSS). We compare the impact of the initial perturbations and the perturbations in lateral boundary conditions in both nesting options. The initial perturbations dominate in the beginning of the forecasts, with influence up to T+24 h, and are associated with an upscale growth of the uncertainties. The impact of the parent ensemble and lateral boundary conditions dominate at the end of the forecast and tend to influence larger scales more.

Description: This study describes different processes leading to heat waves in Europe. Employing backward trajectories, three clusters with coherent thermodynamic characteristics and vertical motions are identified. In two of the three clusters, subsidence is of first‐order importance for high near‐surface temperatures, whereas the third cluster is primarily heated diabatically due to surface sensible heat fluxes. Western Russia, in particular, is largely affected by remote surface fluxes, whereas the British Isles are largely affected by subsidence and adiabatic warming. This study presents a comprehensive analysis of processes determining heat waves across different climates in Europe for the period 1979–2016. Heat waves are defined using a percentile‐based index and the main processes quantified along trajectories are adiabatic compression by subsidence and local and remote diabatic processes in the upper and lower troposphere. This Lagrangian analysis is complemented by an Eulerian calculation of horizontal temperature advection. During typical summers in Europe, one or two heat waves occur, with an average duration of five days. Whereas high near‐surface temperatures over Scandinavia are accompanied by omega‐like blocking structures at 500 hPa, heat waves over the Mediterranean are connected to comparably flat ridges. Tracing air masses backwards from the heat waves, we identify three trajectory clusters with coherent thermodynamic characteristics, vertical motions, and geographic origins. In all regions, horizontal temperature advection is almost negligible. In two of the three clusters, subsidence in the free atmosphere is very important in establishing high temperatures near the surface, while the air masses in the third cluster are warmed primarily due to diabatic heating near the surface. Large interregional differences occur between the British Isles and western Russia. Over the latter region, near‐surface transport and diabatic heating appear to be very important in determining the intensity of the heat waves, whereas subsidence and adiabatic warming are of first‐order importance for the British Isles. Although the large‐scale pattern is quasistationary during heat wave days, new air masses are entrained steadily into the lower troposphere during the life cycle of a heat wave. Overall, the results of the present study provide a guideline as to which processes and diagnostics weather and climate studies should focus on to understand the severity of heat waves.

Description: We investigate persistent low‐frequency variability of the stratospheric winter polar vortex in a rotating spherical shallow‐water model under the action of topographic wave‐forcing and radiative cooling to a simple time‐varying equilibrium state representative of the seasonal cycle in solar heating. A range of modes of variability is obtained, dependent on wave forcing amplitude and characterized by the distribution of quiescent and disturbed winters, defined as winters in which the vortex is either close to radiative equilibrium, with low planetary wave amplitude, or else strongly disturbed from equilibrium by the wave forcing. At low forcing amplitude the vortex is typically quiescent every year, while at higher amplitude it is typically disturbed; in both cases there is little year‐to‐year variation of the vortex state. For a range of intermediate forcing amplitudes, however, the vortex transitions between quiescent and disturbed states from one winter to the next with a persistent and well‐defined pattern of variability. To investigate the extent to which the low‐frequency variability found here may be explained in terms of a low‐latitude flywheel mechanism, we conduct additional experiments varying a linear drag on the zonal mean flow in the tropics and find that sufficiently strong drag can completely suppress the variability. The robustness of the variability is demonstrated by further experiments using a modified radiative equilibrium profile, associated with a tropical westerly flow: similar variability is obtained but the modified profile is less effective at constraining the tropical flow from a persistent easterly acceleration. This article is protected by copyright. All rights reserved.

Description: Two areas – one over the eastern part of the North Atlantic (a) and one over the Baltic Sea (b) – were identified as locations where blocking influences the occurrence of thunderstorms in parts of western and central Europe. Shown is the relative frequency of cases investigated in the study quantifying how often (a) blocking suppresses and (b) blocking supports thunderstorm days in Europe. A statistically significant link is presented between atmospheric blocking located over the eastern North Atlantic and northern Europe and warm‐season thunderstorm activity over western and central Europe. Lightning data from 2001 to 2014 were used to identify thunderstorm days and blocking events were extracted from the ERA‐Interim reanalysis using an objective identification algorithm. The statistical link between the two phenomena is established through odds ratio analysis. Two areas – one over the eastern part of the North Atlantic and one over the Baltic Sea – were identified as locations where blocking influences the occurrence of deep moist convection in parts of western and central Europe. Based on the mean ambient conditions on days with blocking in these two areas, well‐known dynamic and thermodynamic mechanisms supporting or suppressing the development of thunderstorms were confirmed. The anticyclonic circulation of a block over the eastern part of the North Atlantic leads to a northerly to northwesterly advection of dry and stable air masses into Europe on the eastern flank of the block. In addition, these environmental conditions are on average associated with large‐scale subsidence of air masses (convection‐inhibiting conditions). In contrast, the southerly to southwesterly advection of warm, moist and unstable air masses on the western flank of a block over the Baltic Sea results in convection‐favouring conditions over western and central Europe. Both blocking situations are on average associated with weak wind speeds at mid‐tropospheric levels and with weak wind shear. As a consequence, thunderstorms related to atmospheric blocking over the Baltic Sea tend to be on average less organised.

Description: Tropical convective systems are major sources of atmospheric gravity waves (GWs). These waves are a key driver of the global atmospheric circulation, especially in the middle and upper atmosphere. Tropical cyclones (TCs) such as hurricanes and typhoons are particularly dramatic examples of such systems, and are therefore potentially significant individual sources of GWs. To investigate this effect, I produce and analyse GW observations from three satellite limb‐sounders in the vicinity of TCs. By statistically combining 15 years of GW observations from 1 379 individual TCs represented in the International Best Track Archive for Climate Stewardship, I show that TCs are associated with a 15% increase over background GW amplitudes, and a 25% increase in measured momentum fluxes (MFs), primarily during the period immediately before the TC. I further show that this additional contribution is small relative to other GW‐generating processes, and thus that individual TCs do not have a large quantitative effect on the dynamics of the middle and upper atmosphere as a whole. Thus, I conclude that accurate modelling of TC‐generated short‐vertical‐wavelength GWs need not be a development priority for the next generation of weather and climate models. My results also demonstrate that stronger GW activity is associated with TCs which will later develop into hurricane‐intensity storms than those that will not, and thus that better space‐based monitoring of stratospheric GW activity could be a useful tool to help better forecast strong hurricane events in the presence of obscuring tropospheric cloud. Gravity waves, tropical cyclones, satellites, remote sensing, stratosphere, mesosphere This article is protected by copyright. All rights reserved.

Description: Abstract The mismatch between water demand and water availability in many megacities poses vexing water management challenges. Managers are forced to take remedial efforts to address these challenges, often with a heavy focus on infrastructure solutions such as building reservoirs or interbasin transfers to meet demand, which may in fact exacerbate the problem through unintended consequences that arise from neglect of social, economic, and environmental factors. Such a situation awaits Beijing, China, which faces major water management challenges in spite of the addition of a large interbasin transfer to meet increasing demand. In this study, a sociohydrologic model is developed for investigating Beijing's future water sustainability from a holistic and dynamic perspective. Using the model, we first explore the sociohydrologic mechanisms that contributed to Beijing's worsening water situation during 1988–2014. We then use the model to assess possible future impacts of the South to North Water Diversion Project on Beijing's water supply prospects for the 2015–2035 period. Alternative futures are explored by combining three different sustainable management strategies. The model results show that the source of Beijing's dominant water pressure experienced a transformation from productive to domestic water use over the last 30 years. They also indicate that the transfer water via South to North Water Diversion Project cannot fundamentally reverse Beijing's water shortage in the long term and that demand‐oriented management measures will be required for alleviating the city's water stress. These findings provide guidance not only for Beijing's water management but also for other less developed cities around the world.

Description: Abstract Nitrification is susceptible to changes in light and pH and, thus, could be influenced by recent sea ice reductions and acidification in the Arctic Ocean. We investigated the sensitivity of nitrification to light, pH, and substrate availability in a natural nitrifier community of the Arctic Ocean. Nitrification was active near the bottom of the shelf region (〈60 m) and in the halocline layer (50–200 m) of the Arctic basin, where ammonium was abundant, but was low in the ammonium‐depleted Atlantic layer (〉250 m). In pH control experiments, nitrification rates significantly declined when the pH was manipulated to be 0.22 lower than the controls. However, nitrification was relatively insensitive to changes in pH compared to changes in light. Light control experiments showed that nitrification was inhibited by a light intensity above 0.11 mol photons m−2 day−1, which was presumably the light threshold. A light intensity greater than the light threshold extended to the shelf bottom and upper halocline layer, limiting nitrification in these waters. Satellite data analyses indicated that the area where light levels inhibit nitrification has increased throughout the Arctic Ocean due to the recent sea ice reduction, which may lead to a declining trend in nitrification. Our results suggest that stronger light levels in the future Arctic Ocean could further suppress nitrification and alter the composition of inorganic nitrogen, with implications for the structure of ecosystems.

Description: Abstract The stable longitudinal dunes in the northern Simpson Desert, Australia, were observed in satellite imagery to become more active after vegetation cover was reduced by fire and drought. Subsequent rainfall events also resulted in significant vegetation regrowth and dune stabilisation. These switches between more active and stable conditions have not been previously described in the largely vegetated dune fields of central Australia. The observations, made on 12 dune sites, relied on high spatial resolution satellite imagery to observe dune crest activity, and seasonal Landsat fractional cover imagery to observe vegetation cover changes. The non‐photosynthetic vegetation (NPV) component of the fractional vegetation cover images revealed significant changes in hummock grass cover on the dunes between 1988‐2018, with a positive relationship with the 3‐year cumulative rainfall, disrupted by two periods of patchy burning. Only those sites that had burnt became active, and only after vegetation cover had remained low (NPV 〈 16%) during the ‘Millennium Drought’. There is no threshold in vegetation cover, below which dune crests become active, but active dune features require 4‐years of low NPV cover (〈16%) to develop. The large rainfall event that ended the drought increased NPV cover, stabilising the dunes. Similar hummock grass covered dunes are present across large areas of the arid zone, and are likely to respond in similar ways, given that fire and drought are common occurrences in Australia.

Description: Abstract The data assimilation scheme used in the Met Office's OSTIA (Operational Sea Surface Temperature and Ice Analysis) system has been updated from an OI‐type scheme to a variational assimilation scheme, NEMOVAR. The updated system includes a dual length scale background error correlation operator, and a flow‐dependent component to adjust the length scale combination in favour of the short scale in regions of high sea surface temperature (SST) variability. The NEMOVAR assimilation scheme improves both the analysis performance and the representation of SST features in the OSTIA analysis compared to the OI scheme of the original system. The results of spectral analysis, assessment of horizontal SST gradients and the response of an atmospheric model to the OSTIA SST analysis as a boundary condition indicate that the flow‐dependent formulation successfully contributes to improvements in the feature resolution capability of the analysis. Overall, using a short length scale of 15 km and including a flow‐dependent adjustment component produces the best results compared to using either 40 km or the first Rossby radius of deformation as the short length scale. The new system successfully captures realistic ocean variability without introducing noise into the analysis, allowing the feature resolution capability of the new system to out‐perform that of other comparable SST analysis products. This article is protected by copyright. All rights reserved.

Description: Abstract Thermal regime and thickness of the active layer respond rapidly to climate variations, and thus they are important measures of cryosphere changes in polar environments. We monitored air temperature and ground temperature at a depth of 5 cm and modeled active‐layer thickness using the Stefan and Kudryavtsev models at the Abernethy Flats site, James Ross Island, Eastern Antarctic Peninsula, in the period March 2006 to February 2016. The decadal average of air and ground temperature was −7.3 and −6.1°C, respectively, and the average modeled active‐layer thickness reached 60 cm. Mean annual air temperature increased by 0.10°C y−1 over the study period, while mean annual ground temperature showed the opposite tendency of −0.05°C y−1. The cooling took place mainly in summer and caused thawing season shortening and active‐layer thinning of 1.6 cm y−1. However, these trends need to be taken carefully because all were non‐significant at p 〈 0.05. The Stefan and Kudryavtsev models reproduced the active‐layer thickness with mean absolute errors of 2.6 cm (5.0%) and 3.4 cm (5.9%), respectively, which is better than in most previous studies, making them promising tools for active‐layer modeling over Antarctica.

Description: Front cover: The cover image is based on the Original Article The herbivorous fish family Kyphosidae (Teleostei: Perciformes) represents a recent radiation from higher latitudes by Steen Knudsen et al., https://doi.org/10.1111/jbi.13634.

Description: Abstract Aim The geographic range and ecological niche of species are widely used concepts in ecology, evolution and conservation and many modelling approaches have been developed to quantify each. Niche and distribution modelling methods require a litany of design choices; differences among subdisciplines have created communication barriers that increase isolation of scientific advances. As a result, understanding and reproducing the work of others is difficult, if not impossible. It is often challenging to evaluate whether a model has been built appropriately for its intended application or subsequent reuse. Here, we propose a standardized model metadata framework that enables researchers to understand and evaluate modelling decisions while making models fully citable and reproducible. Such reproducibility is critical for both scientific and policy reports, while international standardization enables better comparison between different scenarios and research groups. Innovation Range modelling metadata (RMMS) address three challenges: they (a) are designed for convenience to encourage use, (b) accommodate a wide variety of applications, and (c) are extensible to allow the research community to steer them as needed. RMMS are based on a metadata dictionary that specifies a hierarchical structure to catalogue different aspects of the range modelling process. The dictionary balances a constrained, minimalist vocabulary to improve standardization with flexibility for users to modify and extend. To facilitate use, we have developed an R package, rangeModelMetaData, to build templates, automatically fill values from common modelling objects, check for inconsistencies with standards, and suggest values. Main conclusions Range Modelling Metadata tools foster cross‐disciplinary advances in biogeography, conservation and allied disciplines by improving evaluation, model sharing, model searching, comparisons and reproducibility among studies. Our initially proposed standards here are designed to be modified and extended to evolve with research trends and needs.

Description: Abstract Aim To test two prominent, alternate hypotheses that provide explanations for the great accumulation of endemic species in the Kimberley bioregion in north‐western Australia, using an extensively sampled, region wide phylogeny of northern Australia's most species‐rich freshwater fish family, Terapontidae. Specifically, we test whether the Kimberley may act as (1) a “museum” accumulating taxa and endemic species over time or (2) a “cradle” of more recent diversification and neoendemism. Location The Australian monsoonal tropics. Taxon Grunters (Terapontidae). Methods We obtained a robust and well‐supported Bayesian phylogeny for the family using DNA sequences from mtDNA and nuclear gene regions. We performed molecular phylogenetic analyses using species tree methods including molecular dating analysis, ancestral range reconstruction and diversification analysis. Results Based on our phylogeny, the combined molecular clock estimates and likelihood‐based historical‐biogeographic reconstructions suggest that terapontids recently transitioned into the Kimberley from the east during the late‐Miocene. We found that 80% of Kimberley terapontids diversified within the Kimberley in the last 3 Ma. Furthermore, diversification analyses identified a single significant shift in diversification rates ~1.4 Ma that corresponds with a change in global climate midway through the Pleistocene that was predominantly driven by speciation in the Kimberley. Main conclusions The weight of evidence suggests that the Kimberley has been a “cradle” of evolution for Terapontidae, rather than a “museum”. Our analysis provides strong evidence for a geologically recent transition of terapontids into the Kimberley from regions to the east during the late‐Miocene followed by a significant increase in speciation rates during the Pleistocene, driven by speciation in the Kimberley. The results provide important insight into the evolutionary and biogeographical processes that have shaped the regions unique biota, which will inform land managers working to protect and conserve both species and the processes responsible for generating and sustaining them.

Description: Abstract Aim Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used. Location Global land, excluding Antarctica. Taxon Amphibians, birds and mammals. Methods We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning. Results Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type. Main conclusions Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.

Description: The Arctic is a hotspot for climate change, which is affecting populations in complex ways since it impacts the entire Arctic food web. In this Arctic goose population, rapid climate change benefits early stages of reproduction through advanced snow melt and vegetation green‐up, but this is counteracted by changes at other trophic levels, also caused by climate change. Processes at non‐breeding sites affect goose reproduction and survival directly and via carryover effects. This highlights the importance of holistic approaches, studying all migratory stages, when predicting climate change effects. These counteracting effects contributed to stabilizing population growth at the Arctic breeding grounds. Abstract Climate change is most rapid in the Arctic, posing both benefits and challenges for migratory herbivores. However, population‐dynamic responses to climate change are generally difficult to predict, due to concurrent changes in other trophic levels. Migratory species are also exposed to contrasting climate trends and density regimes over the annual cycle. Thus, determining how climate change impacts their population dynamics requires an understanding of how weather directly or indirectly (through trophic interactions and carryover effects) affects reproduction and survival across migratory stages, while accounting for density dependence. Here, we analyse the overall implications of climate change for a local non‐hunted population of high‐arctic Svalbard barnacle geese, Branta leucopsis, using 28 years of individual‐based data. By identifying the main drivers of reproductive stages (egg production, hatching and fledging) and age‐specific survival rates, we quantify their impact on population growth. Recent climate change in Svalbard enhanced egg production and hatching success through positive effects of advanced spring onset (snow melt) and warmer summers (i.e. earlier vegetation green‐up) respectively. Contrastingly, there was a strong temporal decline in fledging probability due to increased local abundance of the Arctic fox, the main predator. While weather during the non‐breeding season influenced geese through a positive effect of temperature (UK wintering grounds) on adult survival and a positive carryover effect of rainfall (spring stopover site in Norway) on egg production, these covariates showed no temporal trends. However, density‐dependent effects occurred throughout the annual cycle, and the steadily increasing total flyway population size caused negative trends in overwinter survival and carryover effects on egg production. The combination of density‐dependent processes and direct and indirect climate change effects across life history stages appeared to stabilize local population size. Our study emphasizes the need for holistic approaches when studying population‐dynamic responses to global change in migratory species.

Description: Abstract The dynamic system response curve (DSRC) method has been shown to effectively use error feedback correction to obtain updated areal estimates of mean rainfall and thereby improve the accuracy of real‐time flood forecasts. In this study, we address two main shortcomings of the existing method. First, ridge estimation is used to deal with ill‐conditioning of the normal equation coefficient matrix when the method is applied to small basins, or when the length of updating rainfall series is short. Second, the effects of spatial heterogeneity of rainfall on rainfall error estimates are accounted for using a simple index. The improved performance of the method is demonstrated using both synthetic and real data studies. For smaller basins with relatively homogeneous spatial distributions of rainfall, the use of ridge regression provides more accurate and robust results. For larger‐scale basins with significant spatial heterogeneity of rainfall, spatial rainfall error updating provides significant improvements. Overall, combining the two strategies results in the best performance for all cases, with the effects of ridge estimation and spatially distributed updating complementing each other.

Description: Abstract Understanding how spatial variability in stream discharge and water chemistry decrease with increasing catchment area is required to improve our ability to predict hydrological and biogeochemical processes in ungauged basins. We investigated differences in this decrease of variability with increasing catchment area among catchments, and among specific discharge (Qs) and water chemistry parameters. We defined the slope of the decrease in the variability with increasing catchment area as the rate of decrease in the standard deviation and coefficient of variation (δSD and δCV, respectively), both of which are −0.5 for the simple mixing of random variables (random mixing). All δSD and δCV values of Qs were less than −0.5, while those of most water chemistry values were greater than −0.5, indicating that with increased catchment area the spatial variability of Qs decreased more steeply than for random mixing, while for water chemistry they decreased less steeply. δSD and δCV had linear relationships with both the spatial dissimilarity index and relative changes in parameters’ mean values with increasing catchment area. It suggested that differences in δSD or δCV for Qs and water chemistry can be explained by the different spatial structures, where dissimilar values of Qs and similar values of water chemistry, respectively, are located close together in space. Differences in δSD and δCV according to Qs and water chemistry should significantly affect the determination of representative elementary area (REA), and therefore need to be considered when predicting REA from spatial variability of low‐order streams.

Description: Abstract The Ensemble Kalman Filter (EnKF) has been proved as a useful algorithm to merge coarse resolution Gravity Recovery and Climate Experiment (GRACE) data with hydrologic model results. However, in order for the EnKF to perform optimally a correct forecast error covariance is needed. The EnKF estimates this error covariance through an ensemble of model simulations with perturbed forcing data. Consequently a correct specification of perturbation magnitude is essential for the EnKF to work optimally. To this end, an Adaptive EnKF (AEnKF), a variant of the EnKF with an additional component that dynamically detects and corrects error misspecifications during the filtering process, has been applied. Due to the low spatial and temporal resolution of GRACE data, the efficiency of this method could be different than for other hydrologic applications. Therefore, instead of spatially or temporally averaging the internal diagnostic (normalized innovations) to detect the misspecifications, spatiotemporal averaging was used. First, sensitivity of the estimation accuracy to the degree of error in forcing perturbations was investigated. Second, efficiency of the AEnKF for GRACE assimilation was explored using two synthetic and one real data experiment. Results show that there is considerable benefit in using this method to estimate the forcing error magnitude, and that the AEnKF can efficiently estimate this magnitude.

Description: Abstract The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water storage (TWS) product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM simulated groundwater correlates strongly with 12‐month precipitation anomalies in low and mid‐latitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional‐scale drought indicators, with discrepancies mainly in their estimated drought severity.

Description: Abstract Plant functional traits provide a link in process‐based vegetation models between plant‐level physiology and ecosystem‐level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large‐scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re‐evaluation of trait‐based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type‐specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.

Description: Abstract Groundwater transit time is an essential hydrologic metric for groundwater resources management. However, especially in tropical environments studies on the transit time distribution (TTD) of groundwater infiltration and its corresponding mean transit time (mTT) have been extremely limited due to data sparsity. In this study, we primarily use stable isotopes to examine the TTDs and their mTTs of both vertical and horizontal infiltration at a riverbank infiltration area in the Vietnamese Mekong Delta (VMD), representative of the tropical climate in Asian Monsoon regions. Precipitation, river water, groundwater, and local ponding surface water were sampled for three to nine years and analyzed for stable isotopes (δ18O and δ2H), providing a unique data set of stable isotope records for a tropical region. We quantified the contribution that the two sources contributed to the local shallow groundwater by a novel concept of two‐component lumped parameter models (LPMs) that are solved using δ18O records. The study illustrates that two‐component LPMs, in conjunction with hydrological and isotopic measurements, are able to identify subsurface flow conditions and water mixing at riverbank infiltration systems. However, the predictive skill and the reliability of the models decrease for locations farther from the river, where recharge by precipitation dominates, and a low‐permeable aquitard layer above the highly permeable aquifer is present. This specific setting impairs the identifiability of model parameters. For river infiltration short mTTs (〈40 weeks) were determined for sites closer to the river (〈200 m), whereas for the precipitation infiltration the mTTs were longer (〉80 weeks) and independent of the distance to the river. The results not only enhance the understanding of the groundwater recharge dynamics in the VMD but also suggest that the highly complex mechanisms of surface‐groundwater interaction can be conceptualized by exploiting two‐component LPMs in general. The model concept could thus be a powerful tool for better understanding both the hydrological functioning of mixing processes and the movement of different water components in riverbank infiltration systems.

Description: Abstract Physically‐based models are useful frameworks for testing intervention strategies designed to reduce elevated sediment loads in agricultural catchments. Evaluating the success of these strategies depends on model accuracy, generally established by a calibration and evaluation process. In this contribution, the physically‐based SHETRAN model was assessed in two similar UK agricultural catchments. The model was calibrated on the Blackwater catchment (18 km2) and evaluated in the adjacent Kit Brook catchment (22 km2) using 4‐years of 15‐minute discharge and suspended sediment flux data. Model sensitivity to changes in single and multiple combinations of parameters as well as sensitivity to changes in Digital Elevation Model (DEM) resolution were assessed. Model flow performance was reasonably accurate; with a Nash‐Sutcliffe efficiency coefficient (NSE) of 0.78 in Blackwater and 0.60 in Kit Brook. In terms of event prediction, the mean of the absolute percentage of difference (μAbsdiff) between measured and simulated flow volume (Qv), peak discharge (Qp), sediment yield (Sy) and peak sediment flux (Sp) showed larger values in Kit Brook (48% [Qv], 66% [Qp], 298% [Sy], 438% [Sp]) compared to the Blackwater catchment (30% [Qv], 41% [Qp], 106% [Sy], 86% [Sp]). Results indicate that SHETRAN can produce reasonable flow prediction but performs less well in estimation of sediment flux, despite reasonably similar hydro‐sedimentary behaviour between catchments. The sensitivity index showed flow volume sensitive to saturated hydraulic conductivity and peak discharge to the Strickler coefficient; sediment yield was sensitive to the overland flow erodibility coefficient and peak sediment flux to raindrop/leaf soil erodibility coefficient. The multi‐parameter sensitivity analysis showed that different combinations of parameters produced similar model responses. Model sensitivity to grid resolution presented similar flow volumes for different DEM resolutions, whereas event peak and duration (for both flow and sediment flux) were highly sensitive to changes in grid size.

Description: Abstract Warming permafrost on a global scale is projected to have significant impacts on engineering, hydrology and environmental quality. Greater warming trends are predicted on the Qinghai–Tibetan Plateau (QTP), but most models for mountain permafrost have not considered the effects of water phase change and the state of deep permafrost due to a lack of detailed information. To better understand historical and future permafrost change based on in situ monitoring and field investigations, a numerical heat conduction permafrost model was introduced which differentiated the frozen and thawed state of soil, and considered unfrozen water content in frozen soil, distribution of ground ice and geothermal heat flow. Simulations were conducted at two sites with validation by long‐term monitoring of ground temperature data. After forcing with reconstructed historical ground surface temperature series starting from 1966, the model predicted permafrost changes until 2100 under different RCP scenarios. The results indicate a slow thermal response of permafrost to climate warming at the two investigated sites. Even under the most radical warming scenario (RCP8.5), deepening of the permafrost table is not obvious before 2040. At both sites, the model indicates that shallow permafrost may disappear but deep permafrost may persist by 2100. Moreover, the simulation shows that the degradation modes may differ between zones of discontinuous and continuous permafrost. The main degradation mode of the site in the discontinuous zone appears to be upward thawing from the permafrost base, while that of the site in the continuous zone is downward thawing at the permafrost table with little change at the permafrost base.

Description: Abstract High‐frequency stable isotope data are useful for validating atmospheric moisture circulation models and provide improved understanding of the mechanisms controlling isotopic compositions in tropical rainfall. Here we present a near‐continuous 6‐month record of O‐ and H‐isotope compositions in both water vapour and daily rainfall from Northeast Australia measured by laser spectroscopy. The data set spans both Wet and Dry Seasons to help address a significant data and knowledge gap in the southern hemisphere tropics. We interpret the isotopic records for water vapour and rainfall in the context of contemporaneous meteorological observations. Surface air moisture provided near‐continuous tracking of the links between isotopic variations and meteorological events on local to regional spatial scales. Power spectrum analysis of the isotopic variation showed a range of significant periodicities, from hourly to monthly scales and cross‐wavelet analysis identified significant regions of common power for hourly‐averaged water vapour isotopic composition and relative humidity, wind direction and solar radiation. Relative humidity had the greatest sub‐diurnal influence on isotopic composition. On longer timescales (weeks to months) isotope variability was strongly correlated with both wind direction and relative humidity. The high‐frequency records showed diurnal isotopic variations in O‐ and H‐isotope compositions due to local dew formation and, for deuterium excess, as a result of evapotranspiration. Several significant negative isotope anomalies on a daily scale were associated with the activity of regional mesoscale convective systems and the occurrence of two tropical cyclones. Calculated air parcel back‐trajectories identified the predominant moisture transport paths from the Southwest Pacific Ocean while moisture transport from northerly directions occurred mainly during the Wet Season monsoonal air flow. Water vapour isotope compositions reflected the same meteorological events as recorded in rainfall isotopes but provided much more detailed and continuous information on atmospheric moisture cycling than the intermittent isotopic record provided by rainfall. Improved global coverage of stable isotope data for atmospheric water vapour is likely to improve simulations of future changes to climate drivers of the hydrological cycle.

Description: Journal of Biogeography, Volume 46, Issue 9, Page ii-iv, September 2019.

Description: Abstract Aim Major efforts have been devoted to understanding the geographic pattern of sexual size dimorphism (SSD). Rensch's rule posits that SSD increases with body size in male‐biased SSD species and decreases with body size in female‐biased SSD species. This pattern, and its inverse, have been mainly explored at the interspecific level, whereas research at the intraspecific level has been largely neglected. Here, we test whether the allometric pattern of SSD in an urodele amphibian conforms to Rensch's rule and evaluate the relative role of four potential mechanisms: sexual selection, fecundity selection, density‐dependent resource availability and differential plasticity. Location Iberian Peninsula. Taxon Lissotriton boscai (Amphibia: Caudata: Salamandridae). Methods We used original (field‐based) and published data on body size, courtship behaviour and fecundity parameters and a suite of climatic, ecological and genetic (mitochondrial and nuclear markers) predictors to assess these hypotheses. Results The results showed that SSD increased with increasing female mean body size, supporting the inverse Rensch's rule pattern. Primary productivity‐related variables and female density were among the most relevant ecological predictors of SSD after accounting for genetic structure and capture date. Main conclusions This study reveals that the interplay between the density‐dependent resource availability hypothesis and the differential plasticity hypothesis explains the inverse Rensch's rule. We discuss how combining biogeographical and experimental approaches can provide alternative interpretations to the classical sexual and fecundity selection hypotheses on the interpopulation variation in SSD.

Description: Abstract A multitude of disturbance agents, such as wildfires, land use, and climate‐driven expansion of woody shrubs, are transforming the distribution of plant functional types across Arctic‐Boreal ecosystems, which has significant implications for interactions and feedbacks between terrestrial ecosystems and climate in the northern high‐latitudes. However, because the spatial resolution of existing land cover data sets is too coarse, large‐scale land cover changes in the Arctic‐Boreal region (ABR) have been poorly characterized. Here we use 31 years (1984‐2014) of moderate spatial resolution (30 m) satellite imagery over a region spanning 4.7 x 106 km2 in Alaska and northwestern Canada to characterize regional‐scale ABR land cover changes. We find that 13.6 ± 1.3 % of the domain has changed, primarily via two major modes of transformation: (1) simultaneous disturbance‐driven decreases in Evergreen Forest area (‐14.7 ± 3.0 % relative to 1984) and increases in Deciduous Forest area (+14.8 ± 5.2 %) in the Boreal biome; and (2) climate‐driven expansion of Herbaceous and Shrub vegetation (+7.4 ± 2.0 %) in the Arctic biome. By using time series of 30 m imagery, we characterize dynamics in forest and shrub cover occurring at relatively short spatial scales (hundreds of m) due to fires, harvest, and climate‐induced growth that are not observable in coarse spatial resolution (e.g. 500 m or greater pixel size) imagery. Wildfires caused most of Evergreen Forest Loss and Evergreen Forest Gain and substantial areas of Deciduous Forest Gain. Extensive shifts in the distribution of plant functional types at multiple spatial scales are consistent with observations of increased atmospheric CO2 seasonality and ecosystem productivity at northern high latitudes and signal continental‐scale shifts in the structure and function of high northern‐latitude ecosystems in response to climate change.

Description: Abstract Nutrient availability influences virtually every aspect of an ecosystem, and is a critical modifier of ecosystem responses to global change. Although this crucial role of nutrient availability in regulating ecosystem structure and functioning has been widely acknowledged, nutrients are still often neglected in observational and experimental synthesis studies due to difficulties in comparing the nutrient status across sites. In the current study, we explain different nutrient‐related concepts and discuss the potential of soil‐, plant‐ and remote sensing‐based metrics to compare the nutrient status across space. Based on our review and additional analyses on a dataset of European, managed temperate and boreal forests (ICP Forests dataset), we conclude that the use of plant‐ and remote sensing‐based metrics that rely on tissue stoichiometry is limited due to their strong dependence on species identity. The potential use of other plant‐based metrics such as Ellenberg indicator values and plant‐functional traits is also discussed. We conclude from our analyses and review that soil‐based metrics have the highest potential for successful inter‐site comparison of the nutrient status. As an example, we used and adjusted a soil‐based metric, previously developed for conifer forests across Sweden, against the same ICP Forests data. We suggest that this adjusted and further adaptable metric, which included the organic carbon concentration (SOC) in the upper 20 cm of the soil (including the organic fermentation‐humus (FH) layer), the C:N ratio and pHCaCl2 of the FH layer, can be used as a complementary tool along with other indicators of nutrient availability, to compare the background nutrient status across temperate and boreal forests dominated by spruce, pine or beech. Future collection and provision of harmonized soil data from observational and experimental sites is crucial for further testing and adjusting the metric.

Description: Abstract The role of wave forcing on the main hydro‐morphological dynamics evolving in the shallow waters of the nearshore and at river mouths is analyzed. Focus is mainly on the cross‐shore dynamics that evolve over mildly sloping barred, dissipative sandy beaches from the storm up to the yearly time scale, at most. Local and nonlocal mechanisms as well as connections across three main inter‐related subsystems of the nearshore ‐ the region of generation and evolution of nearshore bars, river mouths and the swash zone ‐ are analyzed. The beach slope is a major controlling parameter for all nearshore dynamics. A local mechanism that must be properly described for a suitable representation of wave‐forced dynamics of all such three subsystems is the proper correlation between orbital velocity and sediment concentration in the bottom boundary layer; while specific dynamics are the wave‐current interaction and bar generation at river mouths and the sediment presuspension at the swash zone. Fundamental nonlocal mechanisms are both Infragravity (IG) waves and large‐scale horizontal vortices (i.e. with vertical axes), both influencing the hydrodynamics, the sediment transport and the seabed morphology across the whole nearshore. Major connections across the three subsystems are the upriver propagation of IG waves generated by breaking sea waves and swash‐swash interactions, the interplay between the swash zone and along‐river‐flank sediment transport and the evolution of nearshore sand bars.