ALBERT

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: Progress in Human Geography, Ahead of Print. 〈br/〉This paper argues that retail spaces, such as marketplaces, are increasingly becoming sites of urban contestation. The globalisation of retail, online shopping and the redevelopment of cities has pushed marketplaces to the margins, but they still serve millions of people, particularly the urban poor. Concurrently, marketplaces are branded as authentic consumption experiences for tourists and residents. Building on these contradictions, I propose a novel framework with three analytical lenses to reposition marketplaces as marginal city spaces that serve as productive sites for studying urban transformation processes across the Global North and South.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

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

Beschreibung: 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.

Beschreibung: 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.

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

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.

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

Beschreibung: 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.

Beschreibung: 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

Beschreibung: 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.

Beschreibung: 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.

Beschreibung: 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.