Annual Temperature Range Research Articles

Predicting the distribution of critically endangered tree species Karomia gigas under climate change in Tanzania

Global climate change and anthropogenic pressure are increasingly adding stress to critically endangered plant species. Unfortunately, the responses of these species are largely unknown in the African tropics to a great extent partly because of limited research. To implement sustainable conservation or adaptation strategy, it is necessary to understand the impacts of climate change on both the ecosystems and species. Here we present an assessment of the current and future habitat suitability distribution of Karomia gigas (Faden) Verdc (Lamiaceae), a critically endangered tree species by using a maximum entropy (MaxEnt) species distribution model. The future predictions of Karomi gigas were done for the years 2050 (RCP 2.6 and 8.5) and 2070 (RCP 2.6 and 8.5). Future and current predictions are made using bioclimatic variables with a spatial resolution of 30 s. This study was carried out in Litipo and Mitundumbea forest reserves found in the coastal forests of Lindi, Tanzania. The area under receiver operating curve (AUC) value confirmed a predictive accuracy based on 45 occurrence points. The Jackknife test was used to assess the contribution of environmental variables in the model. The temperature annual range (Bio7) showed the highest predictive contribution and useful information to predict the current and future potential distributions of K. gigas in the forest reserves. In conclusion, the study shows that the habitat suitability distribution for K. gigas in Tanzania will increase significantly between 2050 and 2070. Therefore, this study showed that modeling outputs using MaxEnt can be helpful for habitat conservation and species restoration in East African coastal forests.

Dynamics of the distribution of invasive alien plants (Asteraceae) in China under climate change

Climate change and biological invasions pose significant threats to the conservation of biodiversity and the provision of ecosystem services. With the rapid development of international trade and economy, China has become one of the countries most seriously affected by invasive alien plants (IAPs), especially the Asteraceae IAPs. For this end, we selected occurrence data of 31 Asteraceae IAPs and 33 predictor variables to explore the distribution pattern under current climate using MaxEnt model. Based on future climate data, the changes in distribution dynamics of Asteraceae IAPs were predicted under two time periods (2041–2060 and 2081–2100) and three climate change scenarios (SSP126, SSP245 and SSP585). The results indicated that the potential distribution of IAPs was mainly in the southeast of China under current climate. Climatic variables, including precipitation of coldest quarter (BIO19), temperature annual range (BIO07) and annual precipitation (BIO12) were the main factors affecting the potential distribution. Besides, human footprint (HFP), population (POP) and soil moisture (SM) also had a great contribution for shaping the distribution pattern. With climate change, the potential distribution of IAPs would shift to the northwest and expand. It would also accelerate the expansion of most Asteraceae IAPs in China. The results of our study can help to understand the dynamics change of distributions of Asteraceae IAPs under climate change in advance so that early strategies can be developed to reduce the risk and influence of biological invasions.

Geospatial analysis to assess distribution patterns and predictive model for endangered Lilium mackliniae Sealy: to support management decisions.

Lilium mackliniae Sealy is a species endemic to the Indo-Myanmar Biodiversity Hotspot with confined occurrence in the Shiruihills of Manipur (India). A rapid fragmentation of the species resulted in enlisting the remaining population as endangered. Tribal communities have managed this population in national parks for in situ conservation because of its sacred value. Maximum entropy-based modeling was performed with 19 bioclimatic and six geospatial variables on 65 true presence data to assess the threat on its only habitat. The accuracy of modeling was confirmed by an AUC value of 0.989. Among the variables used for habitat modeling, elevation range was a key predictor of the species distribution, followed by land use class and annual temperature range. Additionally, the model projected a similar habitat for the species in the same district. This study, therefore, provides essential information for the conservation and management of the species.

Circular Mining Wastes Management for Sustainable Production of Camellia sinensis (L.) O. Kuntze

Mining operations have a significant negative impact on the surrounding ecosystems. The operation of mines and quarries creates a large amount of waste that accumulate and are practically unrecyclable in the environment. The involvement of these wastes in economic activity is an extremely urgent task. This can make the economy more sustainable and reduce its influence on ecosystems. This work presents the attempts of using quarry wastes as a fertilizer applied for growing tea crops. The novelty of this research involves revealing the quarry wastes as a fertilizer when growing Camellia sinensis (L.) O. Kuntze and assessing changes in the productivity of this plant when applying these calcium wastes. The waste of a quarry intended for extracting crushed stone was studied in this article. The composition of the waste was analyzed. Fertilizers used for manuring the soil were prepared based on the waste. Two experimental sites were selected. One of them was a control, where Camellia sinensis (L.) O. Kuntze was grown without using fertilizers. Fertilizers obtained from the waste were applied on the second site. The experimental work proceeded for 10 years. When discussing the results, special attention was paid to climatic conditions. This was caused by the need to show that it was the use of the fertilizer that influenced the change in the yield, not the climatic conditions. As a result of using calcium fertilizers based on the waste, the productivity of Camellia sinensis (L.) O. Kuntze was increased. The application of the fertilizers based on the quarry wastes was shown to provide an increase in the yield. The possibility of using calcium fertilizers to overcome unfavorable agroclimatic conditions during the tea cultivation was also demonstrated. To assess the climatic impact of applying new fertilizers, three-dimensional modeling in the “gnuplot v.5.4” software was used. As a result, an increase in the average annual precipitation, from 1000 to 1980 mm/year, in the range of the average annual air temperature, from 14 to 16 °C, was found to lead to an increase (when using a new fertilizer) in the yield of Camellia sinensis (L.) O. Kuntze up to 4.8 times (from 20 to 95 centner/ha). The results have shown that applying fertilizers based on the quarry wastes is also possible in unfavorable climatic conditions.

Variations of air temperature differences at different temporal scales over the Tibetan Plateau since 1961 and their possible causes

AbstractThe air temperature difference is an essential indicator to measure weather and climate change. The Tibetan Plateau (TP) is a sensitive area to global climate change. The study on its temperature difference variations is of great significance for further understanding the evolution of weather and climate systems, and scientific disaster prevention and mitigation. In this study, the spatio‐temporal evolution characteristics of the temperature difference on daily, monthly, seasonal and annual scales and their possible causes are analysed based on the daily observations at 59 meteorological stations over the TP from 1961 to 2020 and the circulation indexes such as the East Asian summer monsoon, South Asian summer monsoon, midlatitude westerly and TP summer monsoon. The results indicate that the diurnal temperature range (DTR) on the TP tends to decrease from 1961 to 2020. Compared with the situation in the late 20th century, the annual average of the DTR in the eastern TP turns from a nonsignificant increasing trend into a pronounced decreasing trend, while that in the western TP maintains a decreasing trend. This phenomenon is primarily influenced by the minimum and maximum temperature, precipitation and atmospheric circulations. The standardized temperature difference at different temporal scales shows decreasing trends and is distributed in north–south and east–west distribution patterns. The annual temperature range is mainly influenced by the remarkable increase of the minimum temperature, especially in the northern and southeastern TP. Besides, the increases of maximum temperature and precipitation also affect the annual temperature range. In terms of the seasonal temperature range, it is dramatically influenced by different meteorological factors, especially in the northern TP. The monthly temperature range (Mon‐TR) is dramatically influenced by the maximum and minimum temperature in the first and second half years, respectively. Moreover, the circulation systems, such as the midlatitude westerly, South Asian summer monsoon and TP summer monsoon, are the main influencing factors of the temperature difference variations on the TP. The midlatitude westerly have a large influence on Mon‐TR in June and September, and the significantly influenced stations reaches 54.2% and 35.6%. The impact stations of the TP summer monsoon on Mon‐TR is the largest in August, and the significantly influenced stations is 39%. In July, the influenced stations of the TP summer monsoon and South Asian summer monsoon on the Mon‐TR reaches 30.5%–33.9%. The influenced area of the Mon‐TR in June is largest affected by single summer monsoon or westerly index. Previous studies have shown that the warming mechanisms and their influencing factors have changed in the TP since the 21st century. The study results might provide the foundation for a scientific understanding of climate warming on the TP.

Genotype x environment interaction and climate sensitivity in growth and wood density of European larch

European larch is an ecologically and economically important tree species planted across a wide range of environments. Understanding its response to the rapidly changing climate is essential to developing efficient gene resource management strategies in line with the assisted migration methodology. In this study, we quantified the genotype x environment interaction (GxE) of a larch provenance in a multi-environmental trial analysis using factor analytic (FA) modeling. We analyzed the mean annual height increment (MAI-H), the mean annual diameter increment (MAI-DBH), and wood density (PP). Additionally, we evaluated the effect of several environmental variables on these traits. The genetic correlations between sites varied from −0.53 to 0.99, −0.87 to 0.99, and −0.17 to 0.99 for MAI-H, MAI-DBH, and PP, respectively. This indicates the presence of low to high GxE. The growth traits showed more GxE signal than wood density. Narrow-sense heritability estimates were 0.41, 0.16, and 0.35 for MAI-H, MAI-DBH, and PP, respectively. The FA modeling of order 2 explained 77.4%, 67.9%, and 77.3% of the genetic variance for MAI-H, MAI-DBH, and PP, respectively. For MAI-H, the latent regression plots for the predicted site means indicate a significant positive correlation with the first factor loading. At the individual genotype level, the latent regression plots indicated high levels of GxE, especially for growth traits. Significant and relatively high correlations were found between several EVs and the factor loadings of the FA models, suggesting their possible influence on the genotypic performance across environments. Regarding MAI-H, elevation, averaged monthly mean temperature, precipitation seasonality, and stand age were correlated with the first factor loading. Annual temperature range with both the first and second factor loadings. For MAI-DBH, the mean diurnal range was correlated with the first factor loading. In the case of PP, we found that elevation was correlated with the second factor loading. Overall, this approach successfully modeled the GxE and identified environmental variables likely affecting it. Therefore, we conclude that this methodology is a valuable tool for selecting suitable genotypes adapted to specific environmental conditions.

Climatic adaptation explains responses to Pleistocene oscillations and diversification in European vipers

AbstractAimAllopatric speciation is the primary mode of diversification in the Mediterranean Basin. However, the contribution of climatic adaptation during this process is contradictory. In this work, we investigate the eco‐evolutionary processes that drove diversification in this region, using European vipers as a case study. We describe the climatic requirements of different lineages to compare their responses to the Pleistocene climatic oscillations and tackle the evolutionary mechanisms underlying their diversification.LocationEurasia and North Africa.TaxonEuropean vipers (genus Vipera).MethodsWe used ecological niche modelling (ENM) to identify the climatic requirements of 24 Vipera lineages and infer past range dynamics associated with their diversification during the Pleistocene. To test whether climatic niches varied across lineages, we calculated the phylogenetic signal of different climatic variables and examined the relationship with phylogenetic relatedness. To investigate climatic niche evolution and test for phylogenetic niche conservatism (PNC), we quantified pairwise niche overlap in sister phylogenetic units under a 3D hypervolume approach.ResultsENM identified temperature annual range, precipitation of wettest month and precipitation of driest quarter as the most important climatic variables related to the distribution of most lineages, validating Pelias clade as cold‐adapted, and Vipera 1 and Vipera 2 as warm‐adapted clades. Projections to past conditions varied among clades, with Pelias and Vipera 1 having more similar responses, while Vipera 2 exhibited greater variability. We found significant phylogenetic signal in one temperature‐related and two humidity‐related climatic variables and detected high complexity in ecological niche evolution across the phylogeny, both rejecting the hypothesis of PNC.Main ConclusionsClimatic adaptation played a significant role in driving diversification among European vipers. Cold‐adapted and warm‐adapted lineages presented similar climatic requirements and remarkable responses to Pleistocene stages, resulting in an intricate pattern of niche divergence along the phylogeny that favours local adaptation rather than PNC.

Shifts in the Distribution Range and Niche Dynamics of the Globally Threatened Western Tragopan (Tragopan melanocephalus) Due to Climate Change and Human Population Pressure.

The impact of a changing climate, particularly global warming, often harms the distribution of pheasants, particularly those with limited endemic ranges. To effectively create plans of action aimed at conserving species facing threats such as the Western Tragopan, (Tragopan melanocephalus; Gray, 1829; Galliformes, found in the western Himalayas), it is crucial to understand how future distributions may be affected by anticipated climate change. This study utilized MaxEnt modeling to assess how suitable the habitat of the targeted species is likely to be under different climate scenarios. While similar studies have been conducted regionally, there has been no research on this particular endemic animal species found in the western Himalayas throughout the entire distribution range. The study utilized a total of 200 occurrence points; 19 bioclimatic, four anthropogenic, three topographic, and a vegetation variable were also used. To determine the most fitting model, species distribution modeling (SDM) was employed, and the MaxEnt calibration and optimization techniques were utilized. Data for projected climate scenarios of the 2050s and 2070s were obtained from SSPs 245 and SSPs 585. Among all the variables analyzed; aspect, precipitation of coldest quarter, mean diurnal range, enhanced vegetation index, precipitation of driest month, temperature seasonality, annual precipitation, human footprint, precipitation of driest quarter, and temperature annual range were recognized as the most influential drivers, in that order. The predicted scenarios had high accuracy values (AUC-ROC > 0.9). Based on the feedback provided by the inhabitants, it was observed that the livability of the selected species could potentially rise (between 3.7 to 13%) in all projected scenarios of climate change, because this species is relocating towards the northern regions of the elevation gradient, which is farther from the residential areas, and their habitats are shrinking. The suitable habitats of the Tragopan melanocephalus in the Himalayan region will move significantly by 725 m upwards, because of predicted climate change. However, the fact that the species is considered extinct in most areas and only found in small patches suggests that further research is required to avert a further population decline and delineate the reasons leading to the regional extinction of the species. The results of this study can serve as a foundation for devising conservation strategies for Tragopan melanocephalus under the changing climate and provide a framework for subsequent surveillance efforts aimed at protecting the species.

Genetic diversity analysis and potential suitable habitat of Chuanminshen violaceum for climate change

To provide a scientific basis for the sustainable development of C. violaceum, we correctly identified the different germplasm resources and obtained excellent germplasm resources. In this study, MaxEnt was used to predict the distribution range of C. violaceum in China under current and future climate scenarios and explain the impact of environmental variables on its distribution. An SRAP (sequence-related amplified polymorphism) molecular marker was used to analyse the genetic diversity of the plant. The results showed the areas of the total, most, moderately and poorly suitable habitats of C. violaceum were 69.93 × 104 km2, 7.77 × 104 km2, 12.68 × 104 km2 and 49.49 × 104 km2, respectively. The most suitable habitat was concentrated in central and eastern Sichuan, and scattered in Chongqing and Hubei. Under SS1–2.6, SSP2–4.5 and SSP5–8.5 scenarios in 2050s and 2090s, the area of the most suitable habitat would decrease by 25.13%–34.88%. The centroid of the most suitable habitat would move to the west by 45.44 km (SSP1–2.6), 42.15 km (SSP2–4.5) and 37.72 km (SSP5–8.5) in the future. Annual precipitation (bio12), minimum temperature of the coldest month (bio6), precipitation of coldest quarter (bio19), temperature annual range (bio7), elevation (El) and mean UV-B of highest month (UV-B3) were identified as the dominant environmental variables related to the distribution of C. violaceum. A total of 374 bands were amplified by 37 primer pairs, of which 283 bands were polymorphic, and the polymorphic percentage was 75.67%. The analysis of molecular variance showed higher percentages of genetic variation within the population. All the accessions could be distinguished by SRAP markers. The cluster analysis results showed that 63 accessions were classified into 7 groups, which were correlated with the geographical distribution of the accessions to some degree. The accessions from Langzhong and Qingbaijiang had higher diversity. These results suggest that strategic transplantation of C. violaceum from particular geographic locations could help make the species more resilient to climate change and slow the contraction of the species' distribution.

Species distribution models of Brant's oak (Quercus brantii Lindl.): The impact of spatial database on predicting the impacts of climate change

Investigating the correlation between environmental variables and species distribution should be performed using data acquired from appropriate spatial scales to meet adaptive management requirements in a changing environment. This research aimed to model the influence of climate change on the spatial distribution of Brant’s oak (Quercus brantii Lindl.) via presence data acquired from local (Ilam province, western Iran), regional (Zagros ecoregion), and global (whole distribution extent of Brant’s oak) extents. To project the potential habitat of Brant's oak, general circulation models (CCSM4, HADGEM2-ES, BCC-CSM1–1 and GISS-E2-R) under the 2.6 and 8.5 representative concentration pathways (RCP) for 2050 and 2070 were used. To model the distribution of Brant’s oak, artificial neural network (ANN), random forest (RF), generalized linear model (GLM), and maximum entropy (MaxEnt) were compared. To validate the models, random-holdback cross-validation, whereby 80% of the data was randomly selected to calibrate the model and the remaining 20% was used to validate the models, was carried out. The results revealed that enhancing the modeling extent increased the accuracy of the model; hence, a model trained using the global dataset performed better than local and regional datasets. In all three geographical extents, RF and MaxEnt had the best performance in modeling the spatial distribution range of Brant’s oak. The main predictors of Brant’s oak distribution were different in local, regional, and global models. The mean temperature of driest quarter (bio9), at the local extent; precipitation of wettest month (bio13), at the regional extent; and temperature annual range (bio7), at the global extent were the most important climatic variables. The findings also indicated that the potential habitat of Brant’s oak will decline in the future under climate change scenarios (i.e., RCP 2.6 and RCP 8.5) and across all three geographical extents compared to the current habitat. Using the findings of this study, it is possible to identify the suitable habitats of Brant's oak forests with more certainty and take measures to manage and protect them.

Modeling impacts of climate change on the geographic distribution and abundances of Tamarindus indica in Tigray region, Ethiopia

Tamarindus indica is a multipurpose dry land species in sub-Saharan that is traditionally used to build resilience into the farming system. The species is highly threatened and listed on the IUCN Red List. However, information on how climatic condition locally influences its ecological distribution is limited. This study investigates the current and future suitable habitat for the species in the Tigray region, in northern Ethiopia. A total of 220 species presence points and the number of T. indica within a 50 m × 50 m plot were collected. In addition, 19 bioclimatic variables, 3 topographic variables and soil data were used to model the impact of future climate conditions under two Representative Concentration Path Ways (RCP4.5 and RCP 8.5). MaxEnt-v-3.3.3 k, Diva-GIS-7.5, and GIS10.6 were used to model the current and future distribution. SPSSv-26 was also utilized to analyze the relationship between the species’ abundance and environmental variables. Results showed that the environmental variables determining most for the distribution of T. indica were mean diurnal range (Bio2 (56.9%)); temperature seasonality (Bio4 (10.3%)) and temperature annual range (Bio7 (9.2%)). The model suggested that the current distribution of T. indica covers an area of 9209 km2 (14.04%). This would have increased to 29,363 km2 (44.78%) and 11,046 km2 (16.85%) by 2070 under RCP4.5 and RCP8.5, respectively. Compared to the high-impact areas, new gains of suitable areas (net 25,081 km2) for the future distribution of the species were predicted in 2070-RCP4.5. Altitude, rainfall, temperature, silt contents of soils and soil pH have significant contributions (P-value<0.05) to the abundance of T. indica. However, altitude has a negative relationship with the abundance of T. indica. Additional studies to understand population trends and other threats are recommended.

Where in Europe is Chrysomya albiceps? Modelling present and future potential distributions

Chrysomya albiceps (Wiedemann, 1819), a species of blowfly (Diptera, Calliphoridae), historically distributed throughout Southern Europe, has recently dispersed to cooler regions in Europe, which is an intriguing phenomenon. In this work, we used Maxent software to formulate climate suitability using a machine learning technique to investigate this fact. The bioclimatic variables that best explained the climate suitability were Annual Mean Temperature (67.7%) and Temperature Annual Range (21.4%). We found that C. albiceps is climatically suitable for several parts of Europe, except for high altitude areas like the Swiss Alps. In warmer countries such as Portugal, Spain and Italy, the entire coastal territory was the most suitable for the species. Future scenario models show that in these eastern countries and some northern areas, climate suitability has increased. This increase is reinforced when comparing the gains and losses in climate suitability between the present-day model and the future scenario models. These changes are most likely caused by changes in temperature, which is the main explanatory factor among the tested variables, for the climate suitability. As one of the most important species in forensic contexts and a potential myiasis agent, the expansion of C. albiceps to new locations cannot be neglected, and its expansion must be carefully monitored.

Projecting Podocarpaceae response to climate change: we are not out of the woods yet.

Under the changing climate, the persistence of Afrotemperate taxa may be threatened as suitable habitat availability decreases. The unique disjunct ranges of podocarps in southern Africa raise questions about the persistence of these species under climate change. Here, we identified likely environmental drivers of these distributions, characterized the current and future (2070) environmental niches, and projected distributions of four podocarp species in South Africa. Species distribution models were conducted using species locality data for Afrocarpus falcatus, Podocarpus latifolius, Pseudotropheus elongatus and Podocarpus henkelii and both historical climate data (1970-2000) and future climate scenarios (Representative Concentration Pathway [RCP] 4.5 and 8.5, 2061-2080) to estimate the current and future distributions. We also used this opportunity to identify the most important climatic variables that likely govern each species' distribution. Using niche overlap estimates, a similarity test, and indices of niche expansion, stability and unfilling, we explored how niches change under different climate scenarios. The distribution of the study species was governed by the maximum temperature of the warmest month, temperature annual range, mean temperature of the wettest quarter, and precipitation of the wettest, driest and warmest quarters. The current distribution of A. falcatus was predicted to expand to higher elevations under RCP 4.5 and RCP 8.5. Podocarpus henkelii was predicted to lose most of its suitable habitat under RCP 4.5 and expand under RCP 8.5; however, this was the opposite for P. elongatus and P. latifolius. Interestingly, P. elongatus, which had the smallest geographic distribution, showed the most vulnerability to climate change in comparison to the other podocarps. Mapping the distribution of podocarps and understanding the differences in their current and future climate niches provide insight into potential climate drivers of podocarp persistence and the potential for adaptation of these species. Overall, these results suggest that P. elongatus and P. henkelii may expand to novel environmental niches.

Prediction of the Current and Future Distribution of Tomato Leafminer in China Using the MaxEnt Model.

Tomato leafminer (Tuta absoluta), an important quarantine pest in China, was first detected in China in Yili, Xinjiang Uygur Autonomous Region, in 2017. Its damage has grown in recent years, severely harming Solanaceae plants in China and causing enormous economic losses. The study and prediction of the current and future suitable habitats for tomato leafminer in China can provide an important reference for the monitoring, early warning, and prevention and control of the pest. Here, tomato leafminer's potential distributions in China under the current climate and four future climate models (SSP1-26, SSP2-45, SSP3-70, and SSP5-85) were predicted using the maximum entropy (MaxEnt) model with ArcGIS software, and the accuracy of the prediction results was tested. The areas under the receiver operating characteristic curves of the models were all greater than 0.8, and the test omission rate of the model simulation results basically agreed with the theoretical omission rate, suggesting that the prediction results had satisfactory accuracy and reliability. Under the current climatic conditions, the highly suitable habitats for tomato leafminer in China are mainly distributed in most of North China, most of East China, most of South China, most of Central China, most of Southwest China, some parts of Northeast China, and only a few parts of Northwest China. Annual mean temperature is the main environmental factor limiting the distribution. The suitable habitats for tomato leafminer will shift under different future climate models: Under SSP1-26, the highly suitable habitats will spread to the north and northeast and to the southeast coastal areas; under SSP2-45, the size of highly suitable habitats will grow from the present to 2080 and shrink from 2081 to 2100; under SSP3-70, the highly suitable habitats will spread northeastwards, but the highly suitable habitats in southeast coastal areas will shrink from 2081 to 2100 and turn into moderately suitable habitats. Under SSP5-85, the highly suitable habitats will spread northeastwards and northwestwards, with the size of highly suitable habitats gradually decreasing and the size of moderately suitable habitats increasing. Different climates will lead to different distributions of suitable habitats for tomato leafminer, with annual mean temperature, isothermality, and mean diurnal range as the main environmental influences.

Compositional variation in grassland plant communities

AbstractHuman activities are altering ecological communities around the globe. Understanding the implications of these changes requires that we consider the composition of those communities. However, composition can be summarized by many metrics which in turn are influenced by different ecological processes. For example, incidence‐based metrics strongly reflect species gains or losses, while abundance‐based metrics are minimally affected by changes in the abundance of small or uncommon species. Furthermore, metrics might be correlated with different predictors. We used a globally distributed experiment to examine variation in species composition within 60 grasslands on six continents. Each site had an identical experimental and sampling design: 24 plots × 4 years. We expressed compositional variation within each site—not across sites—using abundance‐ and incidence‐based metrics of the magnitude of dissimilarity (Bray–Curtis and Sorensen, respectively), abundance‐ and incidence‐based measures of the relative importance of replacement (balanced variation and species turnover, respectively), and species richness at two scales (per plot‐year [alpha] and per site [gamma]). Average compositional variation among all plot‐years at a site was high and similar to spatial variation among plots in the pretreatment year, but lower among years in untreated plots. For both types of metrics, most variation was due to replacement rather than nestedness. Differences among sites in overall within‐site compositional variation were related to several predictors. Environmental heterogeneity (expressed as the CV of total aboveground plant biomass in unfertilized plots of the site) was an important predictor for most metrics. Biomass production was a predictor of species turnover and of alpha diversity but not of other metrics. Continentality (measured as annual temperature range) was a strong predictor of Sorensen dissimilarity. Metrics of compositional variation are moderately correlated: knowing the magnitude of dissimilarity at a site provides little insight into whether the variation is driven by replacement processes. Overall, our understanding of compositional variation at a site is enhanced by considering multiple metrics simultaneously. Monitoring programs that explicitly incorporate these implications, both when designing sampling strategies and analyzing data, will have a stronger ability to understand the compositional variation of systems and to quantify the impacts of human activities.

Coherence of terrestrial vertebrate species richness with external drivers across scales and taxonomic groups

AbstractAimUnderstanding connections between environment and biodiversity is crucial for conservation, identifying causes of ecosystem stress, and predicting population responses to changing environments. Explaining biodiversity requires an understanding of how species richness and environment covary across scales. Here, we identify scales and locations at which biodiversity is generated and correlates with environment.LocationFull latitudinal range per continent.Time PeriodPresent day.Major Taxa StudiedTerrestrial vertebrates: all mammals, carnivorans, bats, songbirds, hummingbirds, amphibians.MethodsWe describe the use of wavelet power spectra, cross‐power and coherence for identifying scale‐dependent trends across Earth's surface. Spectra reveal scale‐ and location‐dependent coherence between species richness and topography (E), mean annual precipitation (Pn), temperature (Tm) and annual temperature range (ΔT).Results&gt;97% of species richness of taxa studied is generated at large scales, that is, wavelengths km, with 30%–69% generated at scales km. At these scales, richness tends to be highly coherent and anti‐correlated with E and ΔT, and positively correlated with Pn and Tm. Coherence between carnivoran richness and ΔT is low across scales, implying insensitivity to seasonal temperature variations. Conversely, amphibian richness is strongly anti‐correlated with ΔT at large scales. At scales km, examined taxa, except carnivorans, show highest richness within the tropics. Terrestrial plateaux exhibit high coherence between carnivorans and E at scales km, consistent with contribution of large‐scale tectonic processes to biodiversity. Results are similar across different continents and for global latitudinal averages. Spectral admittance permits derivation of rules‐of‐thumb relating long‐wavelength environmental and species richness trends.Main ConclusionsSensitivities of mammal, bird and amphibian populations to environment are highly scale dependent. At large scales, carnivoran richness is largely independent of temperature and precipitation, whereas amphibian richness correlates strongly with precipitation and temperature, and anti‐correlates with temperature range. These results pave the way for spectral‐based calibration of models that predict biodiversity response to climate change scenarios.

Modeling the Distribution of the Chytrid Fungus Batrachochytrium dendrobatidis with Special Reference to Ukraine.

Amphibians are the most threatened group of vertebrates. While habitat loss poses the greatest threat to amphibians, a spreading fungal disease caused by Batrachochytrium dendrobatidis Longcore, Pessier & D.K. Nichols 1999 (Bd) is seriously affecting an increasing number of species. Although Bd is widely prevalent, there are identifiable heterogeneities in the pathogen's distribution that are linked to environmental parameters. Our objective was to identify conditions that affect the geographic distribution of this pathogen using species distribution models (SDMs) with a special focus on Eastern Europe. SDMs can help identify hotspots for future outbreaks of Bd but perhaps more importantly identify locations that may be environmental refuges ("coldspots") from infection. In general, climate is considered a major factor driving amphibian disease dynamics, but temperature in particular has received increased attention. Here, 42 environmental raster layers containing data on climate, soil, and human impact were used. The mean annual temperature range (or 'continentality') was found to have the strongest constraint on the geographic distribution of this pathogen. The modeling allowed to distinguish presumable locations that may be environmental refuges from infection and set up a framework to guide future search (sampling) of chytridiomycosis in Eastern Europe.

Prediction of Potential Distribution Patterns of Three Larix Species on Qinghai-Tibet Plateau under Future Climate Scenarios

How climate change affects the plants on the Qinghai-Tibet Plateau (QTP) has become a hot research topic in recent years. It was widely recognized that Larix. are sensitive to climate change, while the corresponding research of Larix. on the QTP has been rare. Using the maximum entropy (MaxEnt) model, we predicted the potential distribution patterns of Larix potaninii Batalin, Larix griffithii and Larix speciosa on the QTP in this study under different future climate scenarios. The results demonstrated that the area of suitable habitat for Larix potaninii Batalin (Larix griffithii) presented a loss (gain) trend, while that for Larix speciosa remained unchanged on the whole. The centroids of their suitable habits all migrated to the high-altitude and high-latitude areas, suggesting the three species may take the same survival strategy in response to climate change. Annual Precipitation was the most significant environmental factor influencing the distribution pattern of Larix potaninii Batalin, while Temperature Annual Range was the most significant for Larix griffithii and Larix speciosa. The overlapping potential suitable area for the three Larix species was the maximum under the 2041–2060 SSP126 future climate scenarios and decreased with the increasing emission concentration, suggesting that the niches of these species may step towards separation. This study suggested the survival strategies of the Larix species in response to climate change and the findings may provide a reliable basis for conserving the endangered Larix species under different future climate scenarios.

Not the expected poleward migration: Impact of climate change scenarios on the distribution of two endemic evergreen broad-leaved Quercus species in China

One of the key strategies for species to respond to climate change is range shift. It is commonly believed that species will migrate towards the poles and higher elevations due to climate change. However, some species may also shift in opposite directions (i.e., equatorward) to adapt to changes in other climatic variables beyond climatic isotherms. In this study, we focused on two evergreen broad-leaved Quercus species endemic to China and used ensemble species distribution models to project their potential distribution shifts and extinction risk under two shared socioeconomic pathways of six general circulation models for the years 2050 and 2070. We also investigated the relative importance of each climatic variable in explaining range shifts of these two species. Our findings indicate a sharp reduction in the habitat suitability for both species. Q. baronii and Q. dolicholepis are projected to experience severe range contractions, losing over 30 % and 100 % of their suitable habitats under SSP585 in the 2070s, respectively. Under the assumption of universal migration in future climate scenarios, Q. baronii is expected to move towards the northwest (~105 km), southwest (~73 km), and high elevation (180–270 m). The range shifts of both species are driven by temperature and precipitation variables, not only annual mean temperature. Specifically, precipitation seasonality and temperature annual range were the most crucial environmental variables, causing the contraction and expansion of Q. baronii and contraction of Q. dolicholepis, respectively. Our results highlight the importance of considering additional climatic variables beyond the annual mean temperature to explain species range shifts in multiple directions.

Climatic seasonality challenges the stability of microbial-driven deep soil carbon accumulation across China.

Microbial residues contribute to the long-term stabilization of carbon in the entire soil profile, helping to regulate the climate of the planet; however, how sensitive these residues are to climatic seasonality remains virtually unknown, especially for deep soils across environmental gradients. Here, we investigated the changes of microbial residues along soil profiles (0-100 cm) from 44 typical ecosystems with a wide range of climates (~3100 km transects across China). Our results showed that microbial residues accountfor a larger portion of soil carbon in deeper (60-100 cm) vs. shallower (0-30 and 30-60 cm) soils. Moreover, we find that climate especially challenges the accumulation of microbial residues in deep soils, while soil properties and climate share their roles in controlling the residue accumulation in surface soils. Climatic seasonality, including positive correlations with summer precipitation and maximum monthly precipitation, as well as negative correlations with temperature annual range, are important factors explaining microbial residue accumulation in deep soils across China. In particular, summer precipitation is the key regulator of microbial-driven carbon stability in deep soils, which has 37.2% of relative independent effects on deep-soil microbial residue accumulation. Our work provides novel insights into the importance of climatic seasonality in driving the stabilization of microbial residues in deep soils, challenging the idea that deep soils as long-term carbon reservoirs can buffer climate change.