Climate-related naturally occurring epimutation and their roles in plant adaptation in A. thaliana.

DNA methylation has been proposed to be an important mechanism that allows plants to respond to their environments sometimes entirely uncoupled from genetic variation. To understand the genetic basis, biological functions and climatic relationships of DNA methylation at a population scale in Arabidopsis thaliana, we performed a genome-wide association analysis with high-quality single nucleotide polymorphisms (SNPs), and found that ~56% on average, especially in the CHH sequence context (71%), of the differentially methylated regions (DMRs) are not tagged by SNPs. Among them, a total of 3235 DMRs are significantly associated with gene expressions and potentially heritable. 655 of the 3235 DMRs are associated with climatic variables, and we experimentally verified one of them, HEI10 (HUMAN ENHANCER OF CELL INVASION NO.10). Such epigenetic loci could be subjected to natural selection thereby affecting plant adaptation, and would be expected to be an indicator of accessions at risk. We therefore incorporated these climate-related DMRs into a gradient forest model, and found that the natural A. thaliana accessions in Southern Europe that may be most at risk under future climate change. Our findings highlight the importance of integrating DNA methylation that is independent of genetic variations, and climatic data to predict plants' vulnerability to future climate change.

Salinity decline promotes growth and harmful blooms of a toxic alga by diverting carbon flow.

Global climate change intensifies the water cycle and makes freshest waters become fresher and vice-versa. But how this change impacts phytoplankton in coastal, particularly harmful algal blooms (HABs), remains poorly understood. Here, we monitored a coastal bay for a decade and found a significant correlation between salinity decline and the increase of Karenia mikimotoi blooms. To examine the physiological linkage between salinity decreases and K. mikimotoi blooms, we compare chemical, physiological and multi-omic profiles of this species in laboratory cultures under high (33) and low (25) salinities. Under low salinity, photosynthetic efficiency and capacity as well as growth rate and cellular protein content were significantly higher than that under high salinity. More strikingly, the omics data show that low salinity activated the glyoxylate shunt to bypass the decarboxylation reaction in the tricarboxylic acid cycle, hence redirecting carbon from CO2 release to biosynthesis. Furthermore, the enhanced glyoxylate cycle could promote hydrogen peroxide metabolism, consistent with the detected decrease in reactive oxygen species. These findings suggest that salinity declines can reprogram metabolism to enhance cell proliferation, thus promoting bloom formation in HAB species like K. mikimotoi, which has important ecological implications for future climate-driven salinity declines in the coastal ocean with respect to HAB outbreaks.

Soil N2 O emissions from specialty crop systems: A global estimation and meta-analysis.

Nitrous oxide (N2 O) exacerbates the greenhouse effect and thus global warming. Agricultural management practices, especially the use of nitrogen (N) fertilizers and irrigation, increase soil N2 O emissions. As a vital sector of global agriculture, specialty crop systems usually require intensive input and management. However, soil N2 O emissions from global specialty crop systems have not been comprehensively evaluated. Here, we synthesized 1137 observations from 114 published studies, conducted a meta-analysis to evaluate the effects of agricultural management and environmental factors on soil N2 O emissions, and estimated global soil N2 O emissions from specialty crop systems. The estimated global N2 O emission from specialty crop soils was 1.5 Tg N2 O-N year-1 , ranging from 0.5 to 4.5 Tg N2 O-N year-1 . Globally, soil N2 O emissions exponentially increased with N fertilizer rates. The effect size of N fertilizer on soil N2 O emissions generally increased with mean annual temperature, mean annual precipitation, and soil organic carbon concentration but decreased with soil pH. Global climate change will further intensify the effect of N fertilizer on soil N2 O emissions. Drip irrigation, fertigation, and reduced tillage can be used as essential strategies to reduce soil N2 O emissions and increase crop yields. Deficit irrigation and non-legume cover crop can reduce soil N2 O emissions but may also lower crop yields. Biochar may have a relatively limited effect on reducing soil N2 O emissions but be effective in increasing crop yields. Our study points toward effective management strategies that have substantial potential for reducing N2 O emissions from global agricultural soils.

Land surface conductance linked to precipitation: Co-evolution of vegetation and climate in Earth system models.

Vegetation and precipitation are known to fundamentally influence each other. However, this interdependence is not fully represented in climate models because the characteristics of land surface (canopy) conductance to water vapor and CO2 are determined independently of precipitation. Working within a coupled atmosphere and land modelling framework (CAM6/CLM5; coupled Community Atmosphere Model v6/Community Land Model v5), we have developed a new theoretical approach to characterizing land surface conductance by explicitly linking its dynamic properties to local precipitation, a robust proxy for moisture available to vegetation. This will enable regional surface conductance characteristics to shift fluidly with climate change in simulations, consistent with general principles of co-evolution of vegetation and climate. Testing within the CAM6/CLM5 framework shows that climate simulations incorporating the new theory outperform current default configurations across several error metrics for core output variables when measured against observational data. In climate simulations for the end of this century the new, adaptive stomatal conductance scheme provides a revised prognosis for average and extreme temperatures over several large regions, with increased primary productivity through central and east Asia, and higher rainfall through North Africa and the Middle East. The new projections also reveal more frequent heatwaves than originally estimated for the south-eastern US and sub-Saharan Africa but less frequent heatwaves across east Europe and northeast Asia. These developments have implications for evaluating food security and risks from extreme temperatures in areas that are vulnerable to climate change.

Microplastic pollution promotes soil respiration: A global-scale meta-analysis.

Microplastic (MP) pollution likely affects global soil carbon (C) dynamics, yet it remains uncertain how and to what extent MP influences soil respiration. Here, we report on a global meta-analysis to determine the effects of MP pollution on the soil microbiome and CO2 emission. We found that MP pollution significantly increased the contents of soil organic C (SOC) (21%) and dissolved organic C (DOC) (12%), the activity of fluorescein diacetate hydrolase (FDAse) (10%), and microbial biomass (17%), but led to a decrease in microbial diversity (3%). In particular, increases in soil C components and microbial biomass further promote CO2 emission (25%) from soil, but with a much higher effect of MPs on these emissions than on soil C components and microbial biomass. The effect could be attributed to the opposite effects of MPs on microbial biomass vs. diversity, as soil MP accumulation recruited some functionally important bacteria and provided additional C substrates for specific heterotrophic microorganisms, while inhibiting the growth of autotrophic taxa (e.g., Chloroflexi, Cyanobacteria). This study reveals that MP pollution can increase soil CO2 emission by causing shifts in the soil microbiome. These results underscore the potential importance of plastic pollution for terrestrial C fluxes, and thus climate feedbacks.

Significant accrual of soil organic carbon through long-term rice cultivation in paddy fields in China.

Paddy fields serve as significant reservoirs of soil organic carbon (SOC) and their potential for terrestrial carbon (C) sequestration is closely associated with changes in SOC pools. However, there has been a dearth of comprehensive studies quantifying changes in SOC pools following extended periods of rice cultivation across a broad geographical scale. Using 104 rice paddy sampling sites that have been in continuous cultivation since the 1980s across China, we studied the changes in topsoil (0-20 cm) labile organic C (LOC I), semi-labile organic C (LOC II), recalcitrant organic C (ROC), and total SOC. We found a substantial increase in both the content (48%) and density (39%) of total SOC within China's paddy fields between the 1980s to the 2010s. Intriguingly, the rate of increase in content and density of ROC exceeded that of LOC (I and II). Using a structural equation model, we revealed that changes in the content and density of total SOC were mainly driven by corresponding shifts in ROC, which are influenced both directly and indirectly by climatic and soil physicochemical factors; in particular temperature, precipitation, phosphorous (P) and clay content. We also showed that the δ13 CLOC were greater than δ13 CROC , independent of the rice cropping region, and that there was a significant positive correlation between δ13 CSOC and δ13 Cstraw . The δ13 CLOC and δ13 CSOC showed significantly negative correlation with soil total Si, suggesting that soil Si plays a part in the allocation of C into different SOC pools, and its turnover or stabilization. Our study underscores that the global C sequestration of the paddy fields mainly stems from the substantial increase in ROC pool.

'Out of Africa' origin of the pantropical staghorn fern genus Platycerium (Polypodiaceae) supported by plastid phylogenomics and biogeographical analysis.

BACKGROUND AND AIMS: The staghorn fern genus Platycerium is one of the most commonly grown ornamental ferns, and it evolved to occupy a typical pantropical intercontinental disjunction. However, species-level relationships in the genus have not been well resolved, and the spatiotemporal evolutionary history of the genus also needs to be explored. METHODS: Plastomes of all the 18 Platycerium species were newly sequenced. Using plastome data, we reconstructed the phylogenetic relationships among Polypodiaceae members with a focus on Platycerium species, and further conducted molecular dating and biogeographical analyses of the genus. KEY RESULTS: The present analyses yielded a robustly supported phylogenetic hypothesis of Platycerium. Molecular dating results showed that Platycerium split from its sister genus Hovenkampia ~35.2 million years ago (Ma) near the Eocene-Oligocene boundary and began to diverge ~26.3 Ma during the late Oligocene, while multiple speciation events within Platycerium occurred during the middle to late Miocene. Biogeographical analysis suggested that Platycerium originated in tropical Africa and then dispersed eastward to southeast Asia-Australasia and westward to neotropical areas. CONCLUSIONS: Our analyses using a plastid phylogenomic approach improved our understanding of the species-level relationships within Platycerium. The global climate changes of both the Late Oligocene Warming and the cooling following the mid-Miocene Climate Optimum may have promoted the speciation of Platycerium, and transoceanic long-distance dispersal is the most plausible explanation for the pantropical distribution of the genus today. Our study investigating the biogeographical history of Platycerium provides a case study not only for the formation of the pantropical intercontinental disjunction of this fern genus but also the 'out of Africa' origin of plant lineages.

Global climate change impacts on the potential distribution of typical Trachinotus fishes and early warning assessment of invasions.

Marine habitats and ecosystems are increasingly being impacted by global climate change and the global spread of captive breeding. In this study, we focused on five typical Trachinotus species (Trachinotus anak, Trachinotus blochii, Trachinotus mookalee, Trachinotus goreenisi, Trachinotus ovatus) as research subjects. We utilized species distribution models and ecological niche models to predict the present and future potential distribution of these species, as well as to assess ecological niche overlap and evaluate the early warning of invasion by Trachinotus species. T. ovatus stands out with its broad distribution range and high adaptability to different environments. It occupies 1.114% of medium-high suitable areas, spanning 100,147 km2. Our predictions also suggest that T. ovatus would undergo a significant expansion (approximately 55% of the total area) under both past and future environmental scenarios, demonstrating a higher tolerance and adaptability to changes in ambient temperatures. It can be discerned that T. ovatus exhibits strong environmental adaptability, which may potentially lead to biological invasion along the southeastern coast of China. The T. anak, on the other hand, showed a higher expansion trend under high carbon dioxide concentrations (RCP8.5), indicating a certain convergence with carbon dioxide concentration. Our models showed that under future climatic conditions, T. ovatus would become the dominant species, with increased competition with T. mookalee and decreased competition with T. goreenisi, T. mookalee, and T. anak. Based on our findings and the net-pen culture mode of T. ovatus, we identified the hotspot habitat of T. ovatus to be located in the Indo-Pacific convergence zone. However, there is a possibility of an expansion trend towards the southeast coast of China in the future. Therefore, it is crucial to provide an early warning for the potential biological invasion of T. ovatus.

A global phylogeny of turtles reveals a burst of climate-associated diversification on continental margins.

Living turtles are characterized by extraordinarily low species diversity given their age. The clade's extensive fossil record indicates that climate and biogeography may have played important roles in determining their diversity. We investigated this hypothesis by collecting a molecular dataset for 591 individual turtles that, together, represent 80% of all turtle species, including representatives of all families and 98% of genera, and used it to jointly estimate phylogeny and divergence times. We found that the turtle tree is characterized by relatively constant diversification (speciation minus extinction) punctuated by a single threefold increase. We also found that this shift is temporally and geographically associated with newly emerged continental margins that appeared during the Eocene-Oligocene transition about 30 million years before present. In apparent contrast, the fossil record from this time period contains evidence for a major, but regional, extinction event. These seemingly discordant findings appear to be driven by a common global process: global cooling and drying at the time of the Eocene-Oligocene transition. This climatic shift led to aridification that drove extinctions in important fossil-bearing areas, while simultaneously exposing new continental margin habitat that subsequently allowed for a burst of speciation associated with these newly exploitable ecological opportunities.

Warm and thermally variable incubation conditions reduce embryonic performance and carry over to influence hatchling tradeoffs.

Animals' thermal sensitivities have long been characterized by thermal performance curves (TPCs) or reaction norms, and TPCs may predict animals' responses to climate change. Typically, TPCs are parameterized by measuring performance at a range of constant temperatures. Yet, animals encounter a range of thermal environments, and temperature variability is an aspect of climate change that may affect animals more than gradual warming. Daily temperature variability is particularly important for eggs in most taxa because they are highly sensitive to temperature and cannot behaviorally avoid stressful temperatures. Thus, the legacy of thermal conditions experienced during incubation may carryover to subsequent life stages. Here, I factorially manipulated mean temperature (20, 25, or 30 °C) and daily temperature range (DTR; ±0, 5, or 10 °C) during incubation for eggs of the variable field cricket (Gryllus lineaticeps) to integrate the role of DTR into the established paradigm of TPCs. Low DTR (±5 °C) was not generally costly, and it even improved hatchling starvation resistance (sensu hormesis). However, high DTR (±10 °C) reduced and delayed hatching at a warm mean temperature (30 °C). The effects of high DTR carried over to accelerate hatchling development at an expense to hatchling starvation resistance-therefore, thermal conditions during incubation can shape tradeoffs among important traits related to life history and stress tolerance later in life. In sum, animals may exhibit complex responses to their increasingly warmer, more thermally variable environments.

Evaluating effects of climate change on the spatial distribution of an atypical cavefish Onychostoma macrolepis.

Comprehending endangered species' spatial distribution in response to global climate change (GCC) is of great importance for formulating adaptive management, conservation, and restoration plans. However, it is regrettable that previous studies mainly focused on geoclimatic species, while neglected climate-sensitive subterranean taxa to a large extent, which clearly hampered the discovery of universal principles. In view of this, taking the endemic troglophile riverine fish Onychostoma macrolepis (Bleeker, 1871) as an example, we constructed a MaxEnt (maximum-entropy) model to predict how the spatial distribution of this endangered fish would respond to future climate changes (three Global Climate Models × two Shared Socio-economic Pathways × three future time nodes) based on painstakingly collected species occurrence data and a set of bioclimatic variables, including WorldClim and ENVIREM. Model results showed that variables related to temperature rather than precipitation were more important in determining the geographic distribution of this rare and endemic fish. In addition, the suitable areas and their distribution centroids of O. macrolepis would shrink (average: 20,901.75 km2) and move toward the northeast or northwest within the study area (i.e. China). Linking our results with this species' limited dispersion potential and unique habitat requirements (i.e. karst landform is essential), we thus recommended in situ conservation to protect this relict.

Modeling the impact of sea level rise on endangered deer habitat.

Numerous unique flora and fauna inhabit the Lower Florida Keys, including the endangered Florida Key deer, found nowhere else. In this vulnerable habitat of flat islands with low elevation, accelerated sea level rise poses a threat. Predicting the impact of sea level rise on vegetation and wildlife is crucial. This study used 5 Intergovernmental Panel on Climate Change (IPCC) sea level rise scenarios to assess their effects on No Name Key, Florida. The goal was to estimate changes in the Florida Key deer population relative to sea level rise using a lidar-derived elevation data and a vegetation map. The method used 2 cases to model the sea level rise impact. In Case 1, total non-submerged area at current sea level was determined. Using 5 IPCC scenarios, a new total non-submerged land area was estimated, and deer numbers were predicted for each scenario. In Case 2, upward migration of coastal vegetation combined with the coastal squeeze process was modeled. A distinct elevation range for each vegetation type at the current sea level was determined. Vegetation ranges were redistributed based on respective elevation ranges in the sea level rise scenarios. Areas for each vegetation type were recalculated, and Key deer numbers were estimated for each sea level rise scenario. Results under the worst emission scenario showed the following: (1) for case 1, the land area was reduced to 30 % of the current land area, corresponding to having about 27 deer, and (2) for case 2, the land area was reduced to 70 % of the current land area, having about 54 deer on No Name Key. The results indicated reduced non-submerged land area and less upland vegetation, particularly hardwoods/hammocks, by the year 2100. As less land area is available, a decline in Key deer population is expected as sea levels rise. Since Key deer favor upland vegetation, habitat affected by sea level rise will likely support a smaller deer population. The findings emphasize the need for precise, timely predictions of sea level rise impacts and long-term conservation strategies. Specifically designed measures are required to protect and maintain endangered wildlife, such as the Florida Key deer, residing on these vulnerable islands.

Effect of global climate change on the sustainability of cold-water fish habitat in the alpine region: A case study on the Gymnocypris eckloni in the source region of the Yellow River.

Climate change at the global scale affects the watershed's hydrology and the river's hydrodynamic, water temperature (WT), and habitat conditions of organisms. This article proposes a quantitative assessment methodology framework for analyzing the impact of GCC on the cold-water fish habitat. This framework integrated GCC, downscaling, hydrological, hydrodynamic, water temperature, and habitat models and was applied to the source region of the Yellow River (SRYR), where there are Gymnocypris eckloni (G. eckloni) resource reduction problems. In this study, we developed a high-precision, loosely integrated hydrological, hydrodynamic, WT coupling model for SWAT-MIKE21 in the SRYR. The optimal latitude and longitude range (6° × 6°) covering the SRYR was established for downscaling, and future meteorological data under three GCC models was obtained. The main results present the discharge of spawning, and juvenile G. eckloni indicates an increasing trend from the radiation forcing low to high and from the near now to the future term. The WT increased (decreased) in April and June (May), with a maximum increase/decrease of 3.1°C (SSP370 in 2100)/1.4°C (SSP585 in 2050). The weighted useable area (WUA) demonstrated a trend of severe fluctuations in May, June, and October, and other months are equal to the base year. Total WUA (TWUA) displayed an increasing trend, with the maximum increase in spawning and juvenile period being 134.46% and 270.89%, respectively. Ultimately, the rise in confluence discharge and WT caused by GCC in the SRYR benefits spawning and juvenile G. eckloni. The results have guiding significance for the development of long-term and adaptive protection and restoration measures for G. eckloni, and provide a plan for predicting the impact of climate change on other organisms in river ecosystems in high-altitude cold regions.

Effect of Global Climate Change Concern on Environmental Sensitivity of Nursing Students.

OBJECTIVE: This study was conducted to evaluate the effect of global climate change concern on environmental sensitivity in nursing students. DESIGN: This study was descriptive, cross-sectional, and correlational. SAMPLE: The study was conducted with undergraduate nursing students (n = 350). METHOD: Descriptive Information Form, Climate Change Worry Scale, and Environmental Sensitivity Scale were used as data collection tools in the study. The relationship between global climate change concern and environmental sensitivity of nursing students was evaluated by Pearson correlation analysis, and the effect of climate change concern on environmental sensitivity of nursing students was evaluated by simple regression analysis. RESULTS: It was determined that there was a positive and moderately significant relationship between the mean total scores of the Climate Change Concern Scale and the mean total scores of the Environmental Sensitivity Scale (r = 0.388, p < 0.001). CONCLUSIONS: As a result of this study, it was found that as nursing students' concern about global climate change increased, their sensitivity toward the environment also increased.

Ecological, environmental risks and sources of arsenic and other elements in soils of Tuotuo River region, Qinghai-Tibet Plateau.

Against the backdrop of global warming, the pollutants that were once "temporarily stored" in the permafrost are gradually being released, posing significant impacts on the environment. This has become an internationally focused hot topic. In this study, the contents of 11 elements such as As, Ti, Cd, Cr, Co, Mn, Cu, Pb, Ni, Zn and V in soil samples from 128 sampling points in the freeze-thaw area of the Tuotuo River in the source region of the Yangtze River on the Qinghai-Tibet Plateau were determined to evaluate the possible sources, contamination status and ecological, environmental and health risks of these elements. The mean values of As, Cd, Pb and Zn were higher than the corresponding Tibet soil background values. Among fourteen PTEs, As, Cd and Pb had the highest average values of enrichment factor and pollution index, indicating that freeze-thaw area soils showed moderate enrichment and pollution with As, Cd and Pb. Mean ecological risk factor (ER) of Cd was 109 and other PTEs mean ER values < 40, whereas ecological risk index (RI) values of all PTEs ranged from 59.5 to 880 and mean RI values was 152, indicating moderate ecological risk in study area. Explanatory power q value of total S (TS) content was 0.217 by GeogDetector, indicating TS was the most significant contributing factor to RI. Correlation analysis and PCA analysis showed that Cr, Cu, Ni, Co, Mn, Ti, V were mainly originated from natural sources, Cd, Pb and Zn from traffic activity, As from long-distance migration-freeze-thaw.

A novel statistical framework of drought projection by improving ensemble future climate model simulations under various climate change scenarios.

Unlike other natural disasters, drought is one of the most severe threats to all living beings globally. Due to global climate change, the frequency and duration of droughts have increased in many parts of the world. Therefore, accurate prediction and forecasting of droughts are essential for effective mitigation policies and sustainable research. In recent research, the use of ensemble global climate models (GCMs) for simulating precipitation data is common. The objective of this research is to enhance the multi-model ensemble (MME) for improving future drought characterizations. In this research, we propose the use of relative importance metric (RIM) to address collinearity effects and point-wise discrepancy weights (PWDW) in GCMs. Consequently, this paper introduces a new statistical framework for weighted ensembles called the discrepancy-enhanced beta weighting ensemble (DEBWE). DEBWE enhances the weighted ensemble data of precipitation simulated by multiple GCMs. In DEBWE, we addressed uncertainties in GCMs arising from collinearity and outliers. To evaluate the effectiveness of the proposed weighting framework, we compared its performance with the simple average multi-model ensemble (SAMME), Taylor skill score ensemble (TSSE), and mutual information ensemble (MIE). Based on the Kling-Gupta efficiency (KGE) metric, DEBWE outperforms all competitors across all evaluation criteria. These inferences are based on the analysis of historical simulated data from 22 GCMs in the CMIP6 project. The quantitative performance indicators strongly support the superiority of DEBWE. The median and mean KGE values for DEBWE are 0.2650 and 0.2429, compared to SAMME (0.1000, 0.0991), TSSE (0.2600, 0.2397), and MIE (0.1550, 0.1511). For drought assessment, we computed the adaptive standardized precipitation index (SPI) for three future scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The steady-state probabilities suggest that normal drought (ND) is the most frequent condition, with extreme events (dry or wet) being less probable.

Genomic signals of local adaptation in Picea crassifolia.

BACKGROUND: Global climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce species, given their pivotal role as key constituents of the montane, boreal, and sub-alpine forests in the Northern Hemisphere. RESULTS: Here, we used transcriptomes, species occurrence records, and environmental data to investigate the spatial genetic distribution of and the climate-associated genetic variation in Picea crassifolia. Our comprehensive analysis employing ADMIXTURE, principal component analysis (PCA) and phylogenetic methodologies showed that the species has a complex population structure with obvious differentiation among populations in different regions. Concurrently, our investigations into isolation by distance (IBD), isolation by environment (IBE), and niche differentiation among populations collectively suggests that local adaptations are driven by environmental heterogeneity. By integrating population genomics and environmental data using redundancy analysis (RDA), we identified a set of climate-associated single-nucleotide polymorphisms (SNPs) and showed that environmental isolation had a more significant impact than geographic isolation in promoting genetic differentiation. We also found that the candidate genes associated with altitude, temperature seasonality (Bio4) and precipitation in the wettest month (Bio13) may be useful for forest tree breeding. CONCLUSIONS: Our findings deepen our understanding of how species respond to climate change and highlight the importance of integrating genomic and environmental data in untangling local adaptations.

Geographic distribution and impacts of climate change on the suitable habitats of Rhamnus utilis Decne in China.

BACKGROUND: Rhamnus utilis Decne (Rhamnaceae) is an ecologically and economically important tree species. The growing market demands and recent anthropogenic impacts to R. utilis forests has negatively impacted its populations severely. However, little is known about the potential distribution of this species and environmental factors that affect habitat suitability for this species. By using 219 occurrence records along with 51 environmental factors, present and future suitable habitats were estimated for R. utilis using Maxent modeling; the important environmental factors affecting its distribution were analyzed. RESULTS: January water vapor pressure, normalized difference vegetation index, mean diurnal range, and precipitation of the warmest quarter represented the critical factors explaining the environmental requirements of R. utilis. The potential habitat of R. utilis included most provinces from central to southeast China. Under the climate change scenario SSP 245, Maxent predicted a cumulative loss of ca. 0.73 × 105 km2 in suitable habitat for R. utilis during 2041-2060 while an increase of ca. 0.65 × 105 km2 occurred during 2081-2100. Furthermore, under this climate change scenario, the suitable habitat will geographically expand to higher elevations. CONCLUSIONS: The findings of our study provide a foundation for targeted conservation efforts and inform future research on R. utilis. By considering the identified environmental factors and anticipating the potential impacts of climate change, conservation strategies can be developed to preserve and restore suitable habitats for R. utilis. Protecting this species is not only crucial for maintaining biodiversity but also for sustaining the economic benefits associated with its ecological services.

Tracing the future of epidemics: Coincident niche distribution of host animals and disease incidence revealed climate-correlated risk shifts of main zoonotic diseases in China.

Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large-scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change.

C:N:P stoichiometry of plants, soils, and microorganisms: Response to altered precipitation.

Precipitation changes modify C, N, and P cycles, which regulate the functions and structure of terrestrial ecosystems. Although altered precipitation affects above- and belowground C:N:P stoichiometry, considerable uncertainties remain regarding plant-microbial nutrient allocation strategies under increased (IPPT) and decreased (DPPT) precipitation. We meta-analyzed 827 observations from 235 field studies to investigate the effects of IPPT and DPPT on the C:N:P stoichiometry of plants, soils, and microorganisms. DPPT reduced leaf C:N ratio, but increased the leaf and root N:P ratios reflecting stronger decrease of P compared with N mobility in soil under drought. IPPT increased microbial biomass C (+13%), N (+15%), P (26%), and the C:N ratio, whereas DPPT decreased microbial biomass N (-12%) and the N:P ratio. The C:N and N:P ratios of plant leaves were more sensitive to medium DPPT than to IPPT because drought increased plant N content, particularly in humid areas. The responses of plant and soil C:N:P stoichiometry to altered precipitation did not fit the double asymmetry model with a positive asymmetry under IPPT and a negative asymmetry under extreme DPPT. Soil microorganisms were more sensitive to IPPT than to DPPT, but they were more sensitive to extreme DPPT than extreme IPPT, consistent with the double asymmetry model. Soil microorganisms maintained stoichiometric homeostasis, whereas N:P ratios of plants follow that of the soils under altered precipitation. In conclusion, specific N allocation strategies of plants and microbial communities as well as N and P availability in soil critically mediate C:N:P stoichiometry by altered precipitation that need to be considered by prediction of ecosystem functions and C cycling under future climate change scenarios.