Climatic Drivers Research Articles

Vegetation Greening and Climate Warming Increased the Propagation Risk From Meteorological Drought to Soil Drought at Subseasonal Timescales

AbstractSubseasonal droughts including flash droughts have occurred frequently in recent years, which are accompanied by heatwaves or wildfires that raise a wide concern on environmental risk. However, the changing characteristics of subseasonal drought propagation, and the possible climate and environmental drivers remain unknown. This study quantifies the propagation characteristics from meteorological drought to soil drought using a Copula‐based Bayesian framework, and shows that higher propagation risks mainly occur in more humid regions with denser vegetation cover. Trends in drought propagation risk vary regionally, with a global increase of 2%/decade (p < 0.01) during 1980–2022. Vegetation greening and climate warming are the key drivers over >71% of the global vegetated lands, with mean contribution rates of 39.5% and 36.5% respectively. Other climatic factors including vapor pressure deficit and precipitation also paly critical roles, which closely correlate with temperature and vegetation. These findings highlight the importance of vegetation greening on subseasonal drought propagation dynamics.

Geographic variation in projected US forest aboveground carbon responses to climate change and atmospheric deposition

Forest composition and ecosystem services are sensitive to anthropogenic pressures like climate change and atmospheric deposition of nitrogen (N) and sulfur (S). Here we extend recent forest projections for the current cohort of trees in the contiguous US, characterizing potential changes in aboveground tree carbon at the county level in response to varying mean annual temperature, precipitation, and N and S deposition. We found that relative to a scenario with N and S deposition reduction and no climate change, greater climate change led generally to decreasing aboveground carbon (mean −7.5% under RCP4.5, −16% under RCP8.5). Keeping climate constant, reduced N deposition tended to lessen aboveground carbon (mean −7%), whereas reduced S deposition tended to increase aboveground carbon (+3%) by 2100. Through mid-century (2050), deposition was more important for predicting carbon responses except under the extreme climate scenarios (RCP8.5); but, by 2100, climate drivers generally outweighed deposition. While more than 70% of counties showed reductions in aboveground carbon relative to the reference scenario, these were not evenly distributed across the US. Counties in the Northwest and Northern Great Plains, and the northern parts of New England and the Midwest, primarily showed positive responses, while counties in the Southeast showed negative responses. Counties with greater initial biomass showed less negative responses to climate change while those which exhibited the greatest change in composition (>15%) had a 95% chance of losing carbon relative to a no-climate change scenario. This analysis highlights that declines in forest growth and survival due to increases in mean temperature and reductions in atmospheric N deposition are likely to outweigh positive impacts of reduced S deposition and potential increases in precipitation. These effects vary at the regional and county level, however, so forest managers must consider local rather than national dynamics to maximize forest carbon sinks in the future.

Unveiling the role of climate in spatially synchronized locust outbreak risks.

Desert locusts threaten crop production and food security. Spatially synchronized locust outbreaks further exacerbate these crises. Continental-scale understanding of such compound locust risks and underlying climatic drivers is crucial to designing coordinated and predictive control strategies but remains elusive. Here, we develop a data-driven framework to assess the compound risk of locust outbreaks in the Middle East and North Africa (MENA) and elucidate the role of climate in locust dynamics. We find that more than one-fifth of high-risk country pairs faced spatially synchronized locust risks from 1985 to 2020, dominated by concurrent winds or inundations. Individual locusts are more prone to infest arid areas punched by extreme rainfall. The spatial prevalence of locusts is strongly modulated by climate variability such as El Niño-Southern Oscillation. A warming climate will lead to widespread increases in locust outbreaks with emerging hotspots in west central Asia, posing additional challenges to the global coordination of locust control.

Distinct latitudinal patterns and drivers of topsoil nitrogen and phosphorus across urban forests in eastern China.

Nitrogen (N) and phosphorus (P) are the two most important macronutrients supporting forest growth. Unprecedented urbanization has created growing areas of urban forests that provide key ecosystem services for city dwellers. However, the large-scale patterns of soil N and P content remain poorly understood in urban forests. Based on a systematic soil survey in urban forests from nine large cities across eastern China, we examined the spatial patterns and key drivers of topsoil (0-20 cm) total N content, total P content, and N:P ratio. Topsoil total N content was found to change significantly with latitude in the form of an inverted parabolic curve, while total P content showed an opposite latitudinal pattern. Variance partition analysis indicated that regional-scale patterns of topsoil total N and P contents were dominated by climatic drivers and partially regulated by time and pedogenic drivers. Conditional regression analyses showed a significant increase in topsoil total N content with lower mean annual temperature (MAT) and higher mean annual precipitation (MAP), while topsoil total P content decreased significantly with higher MAP. Topsoil total N content also increased significantly with the age of urban park and varied with pre-urban soil type, while no such effects were found for topsoil total P content. Moreover, topsoil N:P ratio showed a latitudinal pattern similar to that of topsoil total N content and also increased significantly with lower MAT and higher MAP. Our findings demonstrate distinct latitudinal trends of topsoil N and P contents and highlight a dominant role of climatic drivers in shaping the large-scale patterns of topsoil nutrients in urban forests.

Climate change causes spatial shifts in the productivity of agricultural long-term field experiments

Long-term field experiments (LTE) are highly valuable infrastructures in agricultural- and soil sciences for understanding the long-term impacts of climate and management practices. While they are designed to run under constant conditions, climate change is expected to affect site conditions considerably. This needs to be quantified when interpreting experimental results and when redesigning the experimental setup. One way to achieve this is by utilizing vegetation growth and carbon dynamics, specifically the Net Primary Productivity (NPP), as a spatially explicit indicator. NPP facilitates the assessment and interpretation of yield performance in LTEs under future climatic conditions. Our study estimated the changes in NPP for 271 LTE sites in Germany, comparing a baseline (2000–2020) with two scenarios (2081–2100) that were based on the Shared Socioeconomic Pathways (SSPs) (SSP245) and SSP585) by the Intergovernmental Panel on Climate Change (IPCC). We used the NASA-CASA biogeochemical model to calculate NPP in baseline and IPCC scenarios using Germany as a test case. LTEs were grouped by land use (crop types) and soil information (soil type, texture), drawing on the geodata infrastructure “BonaRes Repository”. The total annual terrestrial NPP for the baseline was calculated as 202.4 Mt C (sum of forests, grasslands, and arable lands) in Germany, while total NPP was up to 56.0 Mt C for different land use types. For both scenarios, NPP was projected to increase in LTEs located in southern Germany, indicating increased crop productivity, while a decrease was projected for the central Germany. The decrease in NPP of numerous LTEs in central Germany was estimated to extend to the LTEs in the eastern part corresponding to the worst-case scenario SSP585. Explicitly, the use of the multi-model ensemble mean as the climate driver in modelling may overestimate projected NPP by reducing inter-annual variability, highlighting the importance of methodological choices for accurate future projections. Besides, the results indicated that poor soils are projected to experience a further decline in productivity, primarily attributed to escalating water scarcity. Conversely, soils with high quality are likely to witness enhanced productivity, largely driven by the extension of the growing seasons. The outcomes of this study provide a basis for considering the future conditions of German LTEs and facilitate distinguishing between the effects of climate change and the impact of agricultural management on productivity at the regional level. These outputs enable planning and developing research strategies for selecting future LTE sites and redesigning existing or newly planned experiments. Moreover, the integrated modelling framework presented here highlights the potential of LTE data for large-scale modelling studies of ecosystem functions.

Breeding birds of high-elevation mixed-conifer forests have declined in national parks of the southwestern U.S. while lower-elevation species have increased, with responses to drought varying by habitat

Abstract Climate change is considered a major driver of recent avian population declines, particularly in the drought-stricken southwestern United States. Predicting how bird populations will respond requires understanding the climatic drivers influencing population density across the region’s diverse habitats. We modelled breeding-season densities of 50 bird species in relation to spring and summer drought and the timing of North American monsoon rainfall over a 12-year period (2007–2018) and across 4 habitats comprising an approximately 1,500 m elevational gradient. We estimated annual breeding-season population density in relation to climate in the previous year by fitting a Bayesian hierarchical N-mixture model to point-count data from each of 6 national parks on the Colorado Plateau. Specifically, we asked whether (1) population trends were stable, increasing, or decreasing in the focal parks; (2) breeding densities were affected by drought or the timing of monsoon rains; and (3) climatic effects differed across habitat types and among species that molt on the breeding grounds, the nonbreeding grounds, or stopover to molt in the monsoon region of northwestern Mexico (molt migrants). Population trends varied with habitat. Species of high-elevation mixed-conifer forest declined over the study period, matching regional Breeding Bird Survey trends, likely in response to climate-related habitat loss and disturbance. By contrast, lower-elevation pinyon-juniper and grassland-shrubland species density generally increased. Effects of drought varied by habitat with elevation: mixed-conifer species responded positively to drought in the previous year, likely due to earlier snowmelt and breeding phenology, whereas pinyon-juniper species were unaffected, and grassland-shrubland species responded negatively, perhaps due to reduced nest survival. Later arrival of monsoon rains, a common prediction of climate models, had a positive effect on grassland bird densities, but a negative effect on molt-migrant densities. Late monsoon rains may result in a phenological mismatch between migration timing and the pulse of resources required to molt.

Late Pleistocene glaciations on the sub-Antarctic Kerguelen Archipelago: new evidence from 36Cl CRE dating and comparison with other southern mid-latitude glacier records

Previous paleo-glacial studies on Kerguelen showed a singular pattern of Holocene glacier evolution on this archipelago in comparison with other southern mid-latitude glacier records. In this study, we aim to test this singularity on a longer timescale, based on 26 new in situ-produced 36Cl ages from pre-Holocene glacio-geomorphic features. Samples from moraine boulders and glacially polished bedrock were extracted at six different sites, located near the Port-aux-Français scientific station (PAF site), on Longue Island, Australia Island, on the Port-Jeanne d’Arc Peninsula (PJDA site), on the Gallieni Peninsula at Baie Larose (BLR site) and the McMurdo Island. The moraine ages indicate that glacier culminations occurred during Marine Isotopic Stage 3 (MIS 3) at 42.2 ± 4.9 ka on the PAF site, and during the global Last Glacial Maximum (gLGM) at 21.5 ± 3.2 ka on the PJDA site and at 21.4 ± 3.7 ka and 19.4 ± 2.6 on Baie Larose site. This is the first time that Late Pleistocene glacier culminations are evidenced on Kerguelen by direct moraine dating, thus allowing comparison with other moraine records from the southern mid-latitudes. While it remains speculative whether or not the MIS 3 glacial maximum at ⁓42.2 ka is in phase with other glaciers at this latitude (due to high age uncertainties), the gLGM glacial maximum is synchronous with that in other southern mid-latitude regions. 36Cl CRE ages of glacially polished bedrock surfaces sampled in different locations of the archipelago vary from ⁓39 ka to ⁓19 ka. We interpret these results as reflecting periods of deglaciation that occurred in between the two glacier culminations and right after the gLGM on Kerguelen. These ages also suggest that some places of the archipelago were free of ice at least since ⁓ 39 ka. The presence of a MIS 3 moraine at PAF site that has not been obliterated by a gLGM advance suggests that the ⁓ 42.2 ka glacier extent was at least as large as gLGM glacial maxima on the archipelago. The glacier culmination during MIS 3 being larger than that during the gLGM on the Kerguelen Archipelago matches observations in other southern mid-latitude regions. Late Pleistocene glacier culminations on Kerguelen may have been in phase with cold temperatures recorded in SST records, which suggest a cooling around Kerguelen. However, climate drivers responsible for the larger MIS 3 glacier culmination on Kerguelen still remain unclear even if we hypothesize that changes in precipitation may have superimposed on temperature changes.

Drivers of heterogeneity in tundra vegetation productivity on the Yamal Peninsula, Siberia, Russia

The direction and magnitude of tundra vegetation productivity trends inferred from the normalized difference vegetation index (NDVI) have exhibited spatiotemporal heterogeneity over recent decades. This study examined the spatial and temporal drivers of Moderate Resolution Imaging Spectroradiometer Max NDVI (a proxy for peak growing season aboveground biomass) and time-integrated (TI)-NDVI (a proxy for total growing season productivity) on the Yamal Peninsula, Siberia, Russia between 2001 and 2018. A suite of remotely-sensed environmental drivers and machine learning methods were employed to analyze this region with varying climatological conditions, landscapes, and vegetation communities to provide insight into the heterogeneity observed across the Arctic. Summer warmth index, the timing of snowmelt, and physiognomic vegetation unit best explained the spatial distribution of Max and TI-NDVI on the Yamal Peninsula, with the highest mean Max and TI-NDVI occurring where summer temperatures were higher, snowmelt occurred earlier, and erect shrub and wetland vegetation communities were dominant. Max and TI-NDVI temporal trends were positive across the majority of the Peninsula (57.4% [5.0% significant] and 97.6% [13.9% significant], respectively) between 2001 and 2018. Max and TI-NDVI trends had variable relationships with environmental drivers and were primarily influenced by coastal-inland gradients in summer warmth and soil moisture. Both Max and TI-NDVI were negatively impacted by human modification, highlighting how human disturbances are becoming an increasingly important driver of Arctic vegetation dynamics. These findings provide insight into the potential future of Arctic regions experiencing warming, moisture regime shifts, and human modification, and demonstrate the usefulness of considering multiple NDVI metrics to disentangle the effects of individual drivers across heterogeneous landscapes. Further, the spatial heterogeneity in the direction and magnitude of interannual covariation between Max NDVI, TI-NDVI, and climatic drivers highlights the difficulty in generalizing the effects of individual drivers on Arctic vegetation productivity across large regions.

The impacts of rising vapour pressure deficit in natural and managed ecosystems.

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growthand survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resourcesand crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigationand management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Anzali Wetland Crisis: Unraveling the Decline of Iran's Ecological Gem

AbstractThe wetland loss rate in Iran is faster than the global average. Comprehending the shrinkage rate in Iranian wetlands and identifying the underlying drivers of these changes is essential for safeguarding their ecosystems' health and services. This study proposes a novel gray‐box modeling framework to quantify the effects of climate change and anthropogenic activities on the wetlands, by combining process‐based and machine learning models. The developed model is utilized to project the Anzali coastal wetland shrinkage by simulating the complex interaction between the meteorological, hydrological, anthropogenic and sea water level characteristics, and the changes in wetland water surface area. Our framework aggregates Soil and Water Assessment Tool model, the 12 General Circulation Models of the Coupled Model Intercomparison Project Phase 6, Landsat imagery, and the Long Short‐Term Memory model to project the shrinkage of the wetland till 2100. A comprehensive range of climate and Land Use/Cover change scenarios are analyzed. The results show that wetland will seasonally desiccate in 2058, mainly due to increasing air temperature, reduction in precipitation and inflow, excessive sediment loading to the wetland, and decline in the Caspian Sea level. For optimistic scenarios, where no changes in the Caspian Sea level is considered, the wetland will gradually diminish and become a seasonal waterbody by 2100. The outcomes of this study highlight that the Anzali wetland desiccation has profound implications for the regional‐scale ecological balance, ecosystem health and function, public health, and local economy. Robust environmental interventions and sustainable development strategies are urgently needed to mitigate the detrimental impacts of climate and anthropogenic drivers on the wetland.

Identifying and Predicting the Responses of Multi-Altitude Vegetation to Climate Change in the Alpine Zone

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region.

Climate Driver Influences on Prediction of the Australian Fire Behaviour Index

Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this study evaluates the skill with which episodes of extreme fire danger in Australia can be predicted from the activity of large-scale climate driver patterns. An extremal dependence index for extreme events is used to depict the historical predictive skill of the Australian Bureau of Meteorology’s subseasonal climate prediction system in replicating known relationships between the probability of top-decile fire danger and climate driver states at a lead time of 2–3 weeks. Results demonstrate that the El Niño Southern Oscillation, Southern Annular Mode, persistent modes of atmospheric blocking, Indian Ocean Dipole and Madden-Julian Oscillation are all key for contributing to predictability of fire danger forecasts in different regions during critical fire danger periods. Northwest Australia is found to be particularly predictable, with the highest mean index differences (>0.50) when certain climate drivers are active, compared with the climatological index mean. This integrated approach offers a valuable resource for decision-making in fire-prone regions, providing greater confidence to users relying on fire danger outlooks for key management decisions, such as those involved in the sectors of national park and forest estate management, agriculture, emergency services, health and energy. Furthermore, the results highlight strengths and weaknesses in both the Australian Fire Danger Rating System and the operational climate model, contributing additional information for improving and refining future iterations of these systems.

Disentangling late quaternary fluvial and climatic drivers of palaeohydrological change in the Najaf Sea basin, Western Iraq

AbstractThe water resource provided by lake basins in the western desert of Iraq is important for human occupation of areas outside the Tigris‐Euphrates floodplain, both in the past and into the future. This paper presents the first geomorphological and geochronological study of the date of formation of the Najaf Sea and the only such study of any lake basin to the west of Mesopotamia. Geomorphological shoreline features and a palaeochannel linking to the Euphrates were studied and dated using optically stimulated luminescence (OSL) and radiocarbon dating. Provenance was determined using heavy mineral analysis. Past environments in the Najaf Sea were reconstructed by molluscan analysis. The earliest OSL ages date from c. 30 000 and 22 000 years ago and seem to predate lake formation. Younger OSL ages date the highest lake level at c. 19 m asl to between 1620–1760 AD (base) to 1906–1974 AD (near surface). The radiocarbon ages are affected by a freshwater reservoir effect, but the maximum ages recorded for either of the c. 15 m and c. 17 m asl shorelines are c. 800 cal. BC. This predates the first archaeological sites in the Najaf basin and is similar to maximum ages of c. 850 and c. 1100 cal. BC from the associated palaeochannel. This timing does not seem to be linked to a humid climate event. We therefore conclude that the establishment of the Najaf Sea in the Najaf basin occurred as a result of an avulsion event within the Euphrates system that diverted flow to the basin. The trigger for this avulsion event likely related to rapid sediment accumulation and may have been either autogenic or driven by human activity. This study therefore suggests that Najaf Sea formation facilitated human expansion beyond the Tigris‐ Euphrates floodplain and occurred due to avulsion of the Euphrates.

Multi-scale habitat modeling framework for predicting the potential distribution of sheep gastrointestinal nematodes across Iran’s three distinct climatic zones: a MaxEnt machine-learning algorithm

Ecological niche models (ENMs) serve as valuable tools in assessing the potential species distribution, identifying crucial habitat components for species associations, and facilitating conservation efforts. The current study aimed to investigate the gastrointestinal nematodes (GINs) infection in sheep, predict and analyze their ecological niches and ranges, and identify the key bioclimatic variables influencing their distribution across three distinct climatic regions in Iran. In a cross-sectional study, a total of 2140 fecal samples were collected from semi-arid (n = 800), arid (n = 500), and humid-subtropical (n = 840) climates in East Azerbaijan, Kerman, and Guilan provinces, respectively. The flotation method was employed to assess stool samples, whereby the fecal egg count (the number of parasite eggs per gram [EPG]) was ascertained for each individual specimen. Employing a presence-only approach, the multi-scale maximum entropy (MaxEnt) method was used to model GINs' habitat suitability using 93 selected points/locations. The findings revealed that Guilan (34.2%) and East Azerbaijan (19.62%) exhibited the utmost proportion of Strongyle-type eggs. East Azerbaijan province also displayed the highest proportion of Marshallagia and Nematodirus, respectively (approximately 40% and 27%), followed by Guilan and Kerman provinces, while Kerman province had the highest proportion of Trichuris (approximately 15%). Ecological niche modeling revealed that the precipitation of the driest quarter (Bio17) exerted the most significant influence on Marshallagia, Nematodirus, Trichuris, and ُSُُُtrongyle-type eggs' presence in East Azerbaijan and Kerman provinces. For Guilan province, the most influential factor defining habitat suitability for Strongyle-type eggs, Marshallagia, and Nematodirus was increasing slope. Additionally, the distribution of Trichuris was most affected by the variable Bio2 in Guilan province. The study highlights the response of GINs to climate drivers in highly suitable regions, providing insights into ecologically favorable areas for GINs. In conclusion, this study provides a better understanding of GINs and the environmental factors influencing their transmission dynamics.

GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers

Abstract. Snow modelling is often hampered by the availability of input and calibration data, which can affect the choice of models, their complexity, and transferability. To address the trade-off between model parsimony and transferability, we present the Generalizable Empirical Model of Snow Accumulation and Melt (GEMS), a machine-learning-based model, which requires only daily precipitation, temperature or its daily diurnal cycle, and basic topographic features to simulate snow water equivalent (SWE). The model embeds a support vector regression pretrained on a large dataset of daily observations from a diverse set of the SNOwpack TELemetry Network (SNOTEL) stations in the United States. GEMS does not require any user calibration, except for the option to adjust the temperature threshold for rain–snow partitioning, though the model achieves robust simulation results with the default value. We validated the model with long-term daily observations from numerous independent SNOTEL stations not included in the training and with data from reference stations of the Earth System Model–Snow Model Intercomparison Project. We demonstrate how the model advances large-scale SWE modelling in regions with complex terrain that lack in situ snow mass observations for calibration, such as the Pamir and Andes mountains, by assessing the model's ability to reproduce daily snow cover dynamics. Future model improvements should consider the effects of vegetation, improve simulation accuracy for shallow snow in warm locations at lower elevations, and possibly address wind-induced snow redistribution. Overall, GEMS provides a new approach for snow modelling that can be useful for hydroclimatic research and operational monitoring in regions where in situ snow observations are scarce.

Climatic Drivers of Ice Slabs and Firn Aquifers in Greenland

AbstractRecent observations revealed the existence of ice slabs and aquifers on the Greenland ice sheet (GrIS). Both affect the ice sheet's hydrology: ice slabs facilitate runoff and aquifers modulate drainage to the bed. However, their climatic drivers and history remain unclear, as most observations cover only two decades. Here, we present a model simulation of the evolution of GrIS ice slabs and aquifers (1980–2020), evaluated using radar measurements. The results show that accumulation, melt and rain rates are good predictors for the spatial distribution of ice slabs and aquifers. Both features were already present in the late 1980s, and their extent remained relatively constant until the beginning of this century, after which increased melt led to their expansion. We show that almost any transect from the coast to the ice‐sheet interior will cross either an ice slab region, or an aquifer, or both.

Distribution, trends and drivers of precipitation use efficiency in the loess plateau

AbstractAgainst the background of climate change, the global carbon and water cycle has undergone significant changes, and it is of great significance to explore the interrelationships of the carbon and water cycles in different regions to cope with future climate change. In this study, based on gross primary productivity (GPP) and precipitation (PRE) data, the precipitation use efficiency (PUE) of the Loess Plateau (LP) was calculated, and the Sen trend analysis and Mann‐Kendall test were used to analyse the temporal and spatial variation characteristics of PUE, as well as the first‐order difference method was used to derive the relative contributions to quantify the impact of vegetation growth and meteorological factors on PUE. The results show that (1) from 2001 to 2018, the spatial distribution pattern of vegetation PUE exhibited an increasing trend from northwest to southeast. On the time scale, the multi‐year average value of PUE was 1.17 gC m−2 mm−1, showing an overall upward trend. Among the different land cover types, paddy fields had the highest PUE level, and sparse grassland had the lowest; (2) LAI had the highest relative contribution to vegetation PUE, followed by temperature (Temp), net radiation of the ground surface (RN), specific humidity (Shum), and wind speed (WS). LAI contributes positively to 88.9% of the area. RN positively influences high‐altitude areas, while Shum had a larger area with a negative contribution. The contribution of Temp increases from northwest to southeast, and WS has balanced positive and negative contributions; (3) LAI is the dominant factor for the spatial and temporal variation of PUE in the LP, and the size of the areas where different meteorological factors dominate the changes of PUE are as follows: WS > Shum>RN > Temp. At high altitudes, the dominant meteorological driver is WS, while at low altitudes, the dominant climate driver is Shum. This study is of guiding significance for the ecological restoration and management of the LP, and it can also provide a scientific basis for the improvement of ecosystems and the sustainable management of water resources in the context of global climate change.

Helminth ecological requirements shape the impact of climate change on the hazard of infection.

Outbreaks and spread of infectious diseases are often associated with seasonality and environmental changes, including global warming. Free-living stages of soil-transmitted helminths are highly susceptible to climatic drivers; however, how multiple climatic variables affect helminth species, and the long-term consequences of these interactions, is poorly understood. We used experiments on nine trichostrongylid species of herbivores to develop a temperature- and humidity-dependent model of infection hazard, which was then implemented at the European scale under climate change scenarios. Intestinal and stomach helminths exhibited contrasting climatic responses, with the former group strongly affected by temperature while the latter primarily impacted by humidity. Among the demographic traits, larval survival heavily modulated the infection hazard. According to the specific climatic responses of the two groups, climate change is expected to generate differences in the seasonal and spatial shifts of the infection hazard and group co-circulation. In the future, an intensification of these trends could create new opportunities for species range expansion and co-occurrence at European central-northern latitudes.

Sparse modeling for climate variable selection across trophic levels.

Understanding how populations respond to climate is fundamentally important to many questions in ecology, evolution, and conservation biology. Climate is complex and multifaceted, with aspects affecting populations in different and sometimes unexpected ways. Thus, when measuring the changing climate it is important to consider the complexity of the phenomenon and the number of ways it can be characterized through different metrics. We used a Bayesian sparse modeling approach to select among 80 metrics of climate and applied the approach to 19 datasets of bird, insect, and plant population responses to abiotic conditions as case studies of how the method can be applied for climate variable selection in a time series context. For phenological datasets, mean spring temperature was frequently selected as an important climate driver, while selected predictors were more diverse for population metrics such as abundance or reproductive success. The climate variable selection approach presented here can help to identify potential climate metrics when there is limited physiological or mechanistic information to make an a priori variable selection, and is broadly applicable across studies on population responses to climate.

Effects of climate, land use, and human population change on human–elephant conflict risk in Africa and Asia

Human-wildlife conflict is an important factor in the modern biodiversity crisis and has negative effects on both humans and wildlife (such as property destruction, injury, or death) that can impede conservation efforts for threatened species. Effectively addressing conflict requires an understanding of where it is likely to occur, particularly as climate change shifts wildlife ranges and human activities globally. Here, we examine how projected shifts in cropland density, human population density, and climatic suitability-three key drivers of human-elephant conflict-will shift conflict pressures for endangered Asian and African elephants to inform conflict management in a changing climate. We find that conflict risk (cropland density and/or human population density moving into the 90th percentile based on current-day values) increases in 2050, with a larger increase under the high-emissions "regional rivalry" SSP3 - RCP 7.0 scenario than the low-emissions "sustainability" SSP1 - RCP 2.6 scenario. We also find a net decrease in climatic suitability for both species along their extended range boundaries, with decreasing suitability most often overlapping increasing conflict risk when both suitability and conflict risk are changing. Our findings suggest that as climate changes, the risk of conflict with Asian and African elephants may shift and increase and managers should proactively mitigate that conflict to preserve these charismatic animals.