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: Butterfly numbers have dropped by one third in the US over 20 years because of climate change and habitat destruction – and other insects may be declining too

Description: Chlamydia may be able to spread through the gut after oral sex and go on to cause rectal infections, according to a study of heterosexual men

Description: David Attenborough says the UK must take radical action to meet its climate change targets, but politicians must make efforts to keep the public on side too

Description: Instagram will ask users to think again if they are about to post something that could be considered offensive and early tests suggest it could work, says the firm

Description: Virgin Galactic is to become the first publicly traded company for human space travel after it announced a merger with a major investment group

Description: A therapy that uses RNA interference to treat the rare condition hereditary transthyretin-mediated amyloidosis has been approved for NHS use in England

Description: Ashley Spindler's machine-learning code is slowly teaching itself to simulate and identify distant galaxies – giving her time for hobbies like making chain-mail armour

Description: A computer program called the Ramanujan Machine is generating mathematical conjectures for constants like π and e, just like the legendary Indian mathematician

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: Air pollution from human activities in China has decreased the potential output of solar panels by 13 per cent between 1960 and 2015, resulting in loss electricity generation and revenue

Description: Some male infertility may be down to the damage sperm experiences as it matures and enters semen – so taking immature sperm directly from the testes could help

Description: Science fiction books like ZED and This Is How You Lose the Time War use exhilarating writing to create worlds that seem eerily similar to ours, says Helen Marshall in her monthly sci-fi column

Description: Jodrell Bank Observatory, a world-leading centre for radio astronomy in the UK, has been added to the UNESCO World Heritage List

Description: A hack that accessed the personal data of around half a million British Airways customers has earned the firm a record £183 million fine

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: Sight Machine, an AI project at the Barbican, shows how the algorithms used in techniques like facial detection capture the performance of a string quartet

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: Abstract Tectonic extension of continental lithosphere creates accommodation space in which sediments are deposited. Climate‐driven processes provide the mechanism by which mass is detached from hillslopes and sediments are transported into this accommodation space. These two forcings, climate and tectonics, act together to create either endorheic (internally drained) or exorheic (externally drained) rift basins. Here we use a large‐scale dynamic landscape evolution‐tectonics model to understand the contribution of tectonic processes in endorheic‐exorheic transitions. In the model, extension results in opening of an asymmetric half‐graben along a listric normal fault. Rift opening occurs in the models in wet, temperate, or semi‐arid climates where runoff and evapotranspiration are varied. Our numerical experiments show that slow rift‐opening rates, a slowing‐down of rift opening, or increase of headwater topography (e.g., upstream epeirogenic uplift), are tectonic situations that can cause a transition from an endorheic to an exorheic drainage state in a rift basin. Our results also show that wet climate conditions lead to a permanent exorheism that persists regardless of rift opening rates. In semi‐arid climates, endorheic conditions are favored, and may last for the duration of rifting except for when rift opening is very slow. These results form an interpretive framework to study endorheic and exorheic drainage systems in natural continental rifts. In the slow‐opening Rio Grande rift, the endorheic‐exorheic transition may have occurred without dramatic climate changes. Lake‐level variations in East African rift basins are predicted by our models to result from variations in climate.

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: People with quadriplegia can feed themselves and brush their teeth thanks to nerve surgery – and doctors say it’s time to make the surgery more widely available

Description: Early weather stations only covered 20 per cent of the globe, causing them to underestimate how much our greenhouse gas emissions have warmed the climate

Description: A wildlife survey in Finland has found that by felling trees and building dams, beavers increase the diversity and abundance of woodland mammals

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.