Mean Annual Temperature Research Articles

Humid, Warm and Treed Ecosystems Show Longer Time‐Lag of Vegetation Response to Climate

AbstractClimate‐vegetation interaction assessments often focus on vegetation response to concurrent climatic perturbations, seldom on the time‐lag effect of climate. Here we employ global satellite observations, climate data records and CO2 flux measurements to calculate the time‐lag of vegetation response to climate. We analyze the time‐lags of various climate variables under distinct environmental conditions to gain insight into how the long‐term climatic regimes and tree cover influence the time‐lag effects. Our findings reveal that terrestrial ecosystems characterized by arid and cold climates show more concurrent climate‐vegetation interactions than other ecosystems. Whereas areas with higher tree cover and humid ecosystems with both high mean annual temperature and precipitation show substantial time‐lag response of vegetation to climate by up to 6 months. Since the global climate‐vegetation interaction is dominated by time‐lag effects, incorporating these effects is paramount to improve our understanding of vegetation dynamics under a changing climate.

Morphological evolution and niche conservatism across a continental radiation of Australian blindsnakes.

Understanding how continental radiations are assembled across space and time is a major question in macroevolutionary biology. Here, we use a phylogenomic-scale phylogeny, a comprehensive morphological dataset and environmental niche models to evaluate the relationship between trait and environment, and assess the role of geography and niche conservatism in the continental radiation of Australian blindsnakes. This fossorial snake group comprises 47 described species and is widespread across various biomes on continental Australia. Although we expected blindsnakes to be morphologically conserved, we found considerable interspecific variation in all morphological traits we measured. Absolute body length is negatively correlated with mean annual temperature and body shape ratios are negatively correlated with soil compactness. We found that morphologically similar species are likely not a result of ecological convergence. Age-overlap correlation tests revealed niche similarity decreased with relative age of speciation events. We also found low geographical overlap across the phylogeny suggesting speciation is largely allopatric with low rates of secondary range overlap. Our study offers insights into the eco-morphological evolution of blindsnakes, and the potential for phylogenetic niche conservatism to influence continental scale radiations.

Sparse Trend Estimation

Abstract The low-frequency movements of economic variables play a prominent role in policy analysis and decision-making. We develop a robust estimation approach for these slow-moving trend processes which is guided by a judicious choice of priors and is characterized by sparsity. We present novel stylized facts from longer-run survey expectations that inform the structure of the estimation procedure. The general version of the proposed Bayesian estimator with a spike-and-slab prior accounts explicitly for cyclical dynamics. We show that it performs well in simulations against relevant benchmarks and report empirical estimates of trend growth for U.S. output and annual mean temperature.

Summer heat wave in 2022 led to rapid warming of permafrost in the central Qinghai-Tibet Plateau

Extreme events with increasing frequency and intensity are significantly affecting the permafrost environment. Analysis using the ERA5-Land reanalysis data revealed that the permafrost region of the central Qinghai-Tibet Plateau (QTP) experienced the summer heat wave in 2022. Four active layer sites experienced maximum active layer thicknesses (ALT) in 2022 (mean: 207.7 cm), which was 20% higher than the mean ALT during 2000–2021 (mean: 175.9 cm). The mean annual ground temperature (MAGT) observed in 2022 was also the highest, exceeding the average of the previous years by 10%. The contribution fraction of heat wave to the seasonal thaw depth of active layer was quantified using Stefan model with ranging from 6.6% to 13.6%, and the maximum contribution fraction occurs in 2022. These findings are helpful to better understand the impact processes of extreme events on the active layer and permafrost.

Spatial heterogeneity in the potential distribution of Aedes mosquitoes in India under current and future climatic scenarios

Aedes is the most globally distributed mosquito genus in the 21st century and transmits various arboviral diseases. The rapid expansion of Ae. Aegypti and Ae. albopictus breeding habitats is a significant threat to global public health, driven by temperature and precipitation changes. In this study, bioclimatic variables were employed to predict the spatial distribution of Ae. aegypti and Ae. albopictus in India. The reference coordinate points of (n = 583) Aedes occurrences at a scale of ∼1 km and nineteen bioclimatic factors were retrieved to train SDM (Species Distribution Models) for both species. Maximum entropy modelling was used to predict the species’ fundamental climatic niche distributions. Future projections were made using global climate models for 2021–2040 and 2081–2100 separately. The models performed reasonably well (AUC > 0.77). Both species thrived in reduced diurnal temperature and higher annual mean temperatures, with suitability increasing alongside precipitation. Ae. aegypti’s projected present and future distribution was broader than that of Ae. Albopictus. The expansion of Aedes suitability varied under different future climatic scenarios. Suitability for Ae. aegypti could expand from between 17.6 and 41.1 % in 2100 under SSP (shared socioeconomic pathways) scenarios 1 and 3, respectively, whereas for Ae. albopictus suitability increased from between 10.2 and 25 % under SSP scenarios 1 and 3 respectively. Preparing for future epidemics and outbreaks requires robust vector distribution models to identify high-risk areas, allocate resources for surveillance and control, and implement prevention strategies.

Increased global warming potential during freeze-thaw cycle is primarily due to the contribution of N2O rather than CO2

While freeze-thaw cycle (FTC) can influence greenhouse gas emissions, the specific greenhouse gas that responds most strongly to FTC, as well as the underlying mechanisms, remain unclear. Here, we conducted a meta-analysis to explore the responses of global warming potential (GWP) and the fluxes of CO2 and N2O to FTC. Our results showed that FTC treatment significantly increased GWP, N2O flux, cumulative GWP, and cumulative N2O emissions by 23.1 %, 53.2 %, 14.5 %, and 164.6 %, respectively, but did not affect CO2 flux, indicating that the enhanced GWP during the FTC period may be primarily due to the contribution of N2O flux rather than CO2 flux. The responses of GWP (+68.6 %), CO2 (+21.0 %), and N2O fluxes (+136.3 %) in croplands was higher than those in other ecosystems, exhibiting a strong dependence on ecosystem types. The effect size of FTC treatment on greenhouse gas emissions escalated with decreasing freezing temperature and diminished with increasing FTC frequency. Moreover, mean annual temperature (MAT) and FTC patterns were key factors influencing GWP during the FTC period. These findings provide critical insights into the variations in greenhouse gas emissions due to FTC and its influencing factors, allowing for more accurate predictions of the future impact of global climate change on GWP.

Biogeographical Variation in Termite Distributions Alters Global Deadwood Decay

ABSTRACTAimTermites are a crucial group of macroinvertebrates regulating rates of deadwood decomposition across tropical and subtropical regions. When examining global patterns of deadwood decay, termites are treated as a homogenous group. There exist key biogeographical differences in termite distribution. One such clear distinction is the distribution of fungus‐growing termites (FGT, subfamily Macrotermitinae). Considering that climate will have shaped termite distribution and ecosystem processes, we evaluate the roles of termite distribution (presence of FGT) and climate (aridity) on global patterns in deadwood decay.LocationBetween 46° N‐43° S and 175° E‐85° W.Time PeriodPresent (between 2016 and 2021).Major Taxa StudiedTermites (Blattodea: Termitoidae).MethodsWe add salient data to an existing global dataset on deadwood decomposition, including new data from five existing sites and seven additional African sites. We analyse a dataset spanning six continents, 16 countries and 102 experimental sites. Firstly, we evaluate climatic differences (mean annual temperature, mean annual precipitation and mean annual aridity) between sites with and without FGT. Secondly, using aridity as a single comparative climate metric between sites that accounts for temperature and precipitation differences, we examine the interaction between FGT and aridity on global patterns of termite deadwood discovery and decay through multivariate logistic and linear regressions.ResultsTermite‐driven decay and wood discovery increased with aridity; however, responses differed between FGT and NFGT sites. Wood discovery increased with aridity in FGT sites only, suggesting a greater role of FGT to deadwood decay in arid environments. On average, both termite discovery and decay of deadwood were approximately four times greater in regions with FGT compared with regions without FGT.Main ConclusionsTermite discovery and decay of deadwood is climate dependent, and higher decay may be through greater discovery of deadwood in FGT sites. Inclusion of biogeographical differences in termite distribution could potentially alter current and future global estimates of deadwood turnover.

Modeling habitat suitability to predict the potential distribution of the Sri Lankan Green Pit Viper

Snake distribution and habitat modeling serve multiple valuable purposes, one of which involves establishing a systematic approach for collecting and assessing data related to the presence and influence of diverse factors on snake distribution patterns. The main objective of this study is to explore the habitat association of the Sri Lankan Green Pit Viper (Peltopelor trigonocephalus) and develop models to assess the suitability of different habitats within the island Sri Lanka. We modeled the suitable habitat for this species using the maximum entropy algorithm, combining presence data collected over two years (from April 2021 to April 2023) with a set of seven environmental variables (annual precipitation, annual mean temperature, precipitation of coldest quarter, elevation, land use, isothermality, Euclidean distance to water). We assessed the importance of different environmental variables through jackknife tests. We evaluated the predictive ability of the models using the area under the receiver operating characteristic curve. We discovered that the primary explanatory variables influencing the distribution of the species were annual mean temperature, annual precipitation, and elevation, contributing significantly at 35%, 31.6%, and 20%, respectively. The Sri Lankan Green pit viper inhabited riparian, forest, and open habitats, with the highest number of individuals recorded in riparian areas. We presented the first habitat suitability models for the Sri Lankan Green Pit Viper, offering valuable insights for conservation biologists and land managers involved in preserving this species.

Green Manure Mediated Improvement in Saline Soils in China: A Meta-Analysis

The application of green manure is a traditional and valuable practice to improve the fertility of saline soil. However, the impact of environmental factors, green manure types and returning methods on the changes in soil fertility and soil salinity remain poorly quantified at a large scale. In the present study, we conducted a meta-analysis to generate a comprehensive evaluation of the effects of green manure on soil organic carbon (SOC), soil salt content, and soil nutrients compared to bare soil in China. The results showed that compared with bare soil, green manure planting could significantly increase the SOC content of saline soil, reduce salt content, and improve the soil total nitrogen (N), soil available phosphorus (P) and soil available potassium (K) contents. On average, green manure significantly enhanced SOC by 34.82% (percentage change), soil total N by 32.23%, soil available P by 34.34% and soil available K by 17.43%, while reducing soil salt content by 47.75%, compared to bare soil. In areas with a mean annual temperature (MAT) of <10 °C or a mean annual precipitation (MAP) of 200–400 mm, green manure had the largest increase in SOC, soil total N, soil available P, and soil available K. The smallest increases were observed in areas with an MAT above 15 °C and MAP greater than 800 mm. Green manure types influenced the improvement effect of green manure on saline soil. Green manure mixtures were more conducive to increases in SOC, while the increases in soil total N resulting from mixed green manure were lower in comparison to those from both legumes and non-legumes. In addition, the initial salt content, experimental years, and returning method influenced the improvement effect of green manure on saline soil. Therefore, this meta-analysis identified green manure as a promising practice for significantly improved saline soil in China.

Alterations in Suitable Cultivation Area for Scutellaria baicalensis under Future Climatic Scenarios in China: Geodetector-Based Prediction

The dried roots of Scutellaria baicalensis (S. baicalensis) have been widely used as a traditional medicine. Recently, climate change and human activities have caused the degeneration of its wildlife habitat. However, there is rare knowledge on the effect and interactive effect of different variables on the spatial heterogeneity of S. baicalensis and how the pattern of suitable cultivation area in China would shift in response to climate change. Based on the Geodetector and Habitat Suitability Index (HSI) method, we proposed an assessment model to identify the critical environmental variable(s) affecting the distribution of suitable cultivation area for S. baicalensis in China and to project its shift under climate change. The results showed that soil and mean annual temperature are two determining variables in its spatial heterogeneity in China. Compared to 1981–2010, future climate change may result in a decrease in its suitable area, and yet may result in an increase in the extremely suitable area (about 1.00–1.35 million km2). S. baicalensis in the southern and northwestern part of its current distribution and the southwestern part and small area of northern China may experience expansion during the 21st century, while S. baicalensis in southern China, the Huang-Huai-Hai plain, and the midwest of northwestern China may experience contractions. Meanwhile, climate warming is expected to shift its distribution northwest through an expansion at the northern (at least 84 km) and western (at least 62 km) boundary and contraction at the southern (at least 529 km) boundary, respectively. These results could provide valuable information to policy-makers for the conservation and scientific introduction of S. baicalensis.

Identifying temperature refuges in Utah using temperature, biota, and habitat data

AbstractUnderstanding where on landscapes to make investments, such as designating protected areas, is a critical component of biodiversity management. Locations for management actions should achieve current management objectives while also having the best chance of continued success in the future. Climate change has the potential to undermine biodiversity management, as it may lead to substantial changes in environmental conditions that are outside local managers' control. Following changes in environmental conditions, areas on the landscape may become unsuitable for the species or habitats that the initial actions were intended to benefit. The potential for local actions to be undermined by global‐scale threats makes it essential to account for and minimize exposure to temperature change. We present a series of analyses identifying priority areas for wildlife and habitat management. We conducted our analyses using a systematic landscape planning approach that identifies areas within species' ranges or current distributions of key habitats that are predicted to be less affected by future temperature change. We used the ranges of 142 animal and 149 plant species identified as species of greatest conservation need (SGCN) together with the distributions of 14 terrestrial and 19 aquatic key habitats in Utah, USA. We measured temperature change in 2 ways: as changes in mean annual temperature between 2020 and the year 2100 (temperature difference) and by quantifying how far a species range or habitat would have to shift to maintain its current temperature envelope (climate velocity). We identified the sub‐watersheds with hydrologic unit code 12 (HUC 12) that collectively encompassed the ranges of our SGCNs and key habitats while minimizing overall exposure to temperature change. These high priority HUC 12s represented areas that were not only hotspots for SGCNs and key habitats but also acted as temperature refugia, where management actions are likely to be robust to temperature change. We hope that our identification of high‐priority HUC 12s will help inform and guide future management actions to improve their long‐term outcomes.

Enhanced enrichment of rare earth elements during pedogenesis under subtropical climate

Rare earth elements (REE) are crucial strategic resources, and weathering-crust rare earth deposits are one of the primary sources. To systematically understand the geochemical behavior (e.g., enrichment and leaching) of REE in soils (or weathering crusts) formed from diverse parent rocks under varying climatic conditions, 171 soil profiles (weathering crusts) developed from three main types of parent rocks (granite, basalt, and carbonate rock) worldwide were studied. Granite shows the highest concentration of rare earth elements at 264 (interquartile range (IQR): 278) ppm, 171 (IQR: 151) ppm and 11.9 (IQR: 36.4) ppm in basalt and carbonate rock, respectively (median test: p < 0.05). The median REE values within the soil profiles were significantly different (median test: p < 0.05), with the concentration of 318 (IQR: 441) ppm, 267 (IQR: 217) ppm and 207 (IQR: 417) ppm in soils derived from granite, carbonate rock, and basalt, respectively. Principal component analysis (PCA) and Linear mixed-effects models (LME) revealed that soils developed from granite and basalt inherit the mineral characteristics of their parent rocks, with REE concentrations primarily influenced by the REE content of the parent rock and climate. In contrast, the REE concentrations in soils developed from carbonate rocks are predominantly controlled by climate. LME and correlation analysis indicates that the enrichment of REE (Q REE ) shows a trend of initially increasing and then decreasing with rising temperature and precipitation, due to variations host clay minerals. The greatest enrichment occurs in the subtropical region (mean annual temperature (MAT) = 15 ̶ 23 °C; mean annual precipitation (MAP) = 1000 ̶ 2000 mm); weathering-crust type REE deposits are primarily found in the subtropics.

Analysis of the Influence of Driving Factors on Vegetation Changes Based on the Optimal-Parameter-Based Geographical Detector Model in the Yima Mining Area

The growth of vegetation directly maintains the ecological security of coal mining areas. It is of great significance to monitor the dynamic changes in vegetation in mining areas and study the driving factors of vegetation spatial division. This study focuses on the Yima mining area in Henan Province. Utilizing MODIS and multi-dimensional explanatory variable data, the Theil–Sen Median + Mann–Kendall trend analysis, variation index, Hurst index, and optimal-parameter-based geographical detector model (OPGD) are employed to analyze the spatiotemporal changes and future trends in the EVI (enhanced vegetation index) from 2000 to 2020. This study further investigates the underlying factors that contribute to the spatial variation in vegetation. The results indicate the following: (1) During the period studied, the Yima mining area was primarily characterized by a moderate-to-low vegetation cover. The area exhibited significant spatial variation, with a notable pattern of “western improvement and eastern degradation”. This pattern indicated that the areas that experienced improvement greatly outnumbered the areas that underwent degradation. Moreover, there was an inclination towards a deterioration in vegetation in the future. (2) Based on the optimal parameter geographic detector, it was found that 2 km was the optimal spatial scale for the analysis of the driving factors of vegetation change in this area. The optimal parameter combination was determined by employing five spatial data discretization methods and selecting an interval classification range of 5–10. This approach effectively addresses the subjective bias in spatial scales and data discretization, leading to enhanced accuracy in vegetation change analysis and the identification of its driving factors. (3) The spatial heterogeneity of vegetation is influenced by various factors, such as topography, socio-economic conditions, climate, etc. Among these factors, population density and mean annual temperature were the primary driving forces in the study area, with Q > 0.29 and elevation being the strongest explanatory factor (Q = 0.326). The interaction between temperature and night light was the most powerful explanation (Q = 0.541), and the average Q value of the interaction between the average annual temperature and other driving factors was 0.478, which was the strongest cofactor among the interactions. The interactions between any two factors enhanced their impact on the vegetation’s spatial changes, and each driving factor had its suitable range for affecting vegetative growth within this region. This research provides scientific support for conserving vegetation and restoring the ecological system.

Climate Warming Has Contributed to the Rise of Timberlines on the Eastern Tibetan Plateau but Slowed in Recent Years

The alpine timberline is a component of terrestrial ecosystems and is highly susceptible to climate change. Since 2000, the Tibetan Plateau’s high-altitude zone has been experiencing a persistent warming, clarifying that the response of the alpine timberline to climate warming is important for mitigating the negative impacts of global warming. However, it is difficult for traditional field surveys to clarify changes in the alpine timberline over a wide range of historical periods. Therefore, alpine timberline sites were extracted from 2000–2021, based on remote sensing data sources (LANDSAT, MODIS), to quantify the timberline vegetation growth in the Gexigou National Nature Reserve and to explore the impacts of climate change on timberline vegetation growth. The results show that the mean temperature increased significantly from 2000 to 2021 (R2 = 0.35, p = 0.0036) at a rate of +0.03 °C/year. The alpine timberline continued to shift upwards, but at a slower rate, by +22.87 m, +23.23 m, and +2.73 m in 2000–2007, 2007–2014, and 2014–2021, respectively. The sample plots of the timberline showing an upward shift experienced a decreasing trend. The timberline NDVI increased significantly from 2000 to 2021 (R2 = 0.2678, p = 0.0136) with an improvement in its vegetation. The timberline NDVI is positively correlated with the annual mean temperature (p < 0.05), February mean temperature (p < 0.05), June minimum temperature (p < 0.05), February maximum temperature (p < 0.01), June maximum temperature (p < 0.01), and June mean temperature (p < 0.01). It was also found to be negatively correlated with annual precipitation (p < 0.01). The study showcases the practicality of using remote sensing techniques to investigate the alpine timberline shifts and timberline vegetation. The findings are valuable in developing approaches to the sustainable management of timberline ecosystems.

From crisis to opportunity: climate change benefits livestock production in Somalia

Abstract While livelihoods of Somalian livestock smallholders rely heavily on seasonal climate conditions, little is known of long-term implications of the changing climate for this nation. Here, we quantify implications of the changing climate on the productivity and profitability of livestock smallholders across a rainfall gradient in northwestern Somalia. Using the Sustainable Grazing Systems (SGS) model, we explore 80 future climate realisations, with global climate model projections including low- and high-impact socio-economic pathways (SSP245 and SSP585), two climate horizons (2040 and 2080) and four case study farm regions. In general, future seasonal and annual rainfall and temperature relative to the baseline period (1981–2020) increased for most regions. Mean annual temperatures increased by 9%–14%, while cumulative annual precipitation increased by 37%–57% from mid to late century, respectively. Grassland production increased with later climate horizons, as higher average annual rainfall together with elevated atmospheric carbon dioxide drove up growth rates in spring and autumn. Under the low emissions scenario (SSP245), changes in farm profit were modest or positive, ranging from negative 4% in Berbera–20% plus in Sheikh. Under the higher emissions scenario (SSP585), farm profits were higher, ranging from 23% to 42% above baseline profits, largely due to greater pasture production and lower requirements for supplementary feed. We conclude that future climates will benefit the productivity and profitability of smallholder farmers in Somalia, although more agile farm management will be required to cope with increased seasonal climate variability.

Distinct features of topsoil carbon fractions across urban forests in eastern China

AbstractRapid urbanization has increased the areas of urban forests that store considerable soil carbon (C). Different soil C fractions may show distinctive contents and spatial patterns in view of their contrasting sensitivities to various drivers. However, current studies on soil C fractions are mostly limited to natural ecosystems and little is known about the large‐scale patterns and drivers of soil C fractions in urban forests. Based on a field survey of urban forests across a north–south transect in eastern China, we analysed the spatial variations and main drivers of topsoil (surface layer, 0–10 cm; subsurface layer, 10–20 cm) C fractions (i.e., soil organic C, SOC; soil inorganic C, SIC; particulate organic C, POC; mineral‐associated organic C, MAOC). Our results showed that topsoil contents of POC, MAOC and SOC changed non‐linearly with latitude, with lowest values occurring in the cities in the warm temperate region. In contrast, SIC content showed the highest values in the warm temperate region. POC instead of MAOC was found to be a major fraction of SOC in urban forests. The spatial variation in topsoil POC content was mainly explained by mean annual temperature, soil clay and silt content, and park age. The spatial variation in MAOC content was mainly explained by soil clay and silt content, mean annual precipitation, mean annual temperature and park age. In contrast, the spatial variation in SIC content was mainly explained by mean annual precipitation and soil pH. These findings demonstrate distinct features of different soil C fractions in urban forests and provide useful implications for urban soil carbon management.

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×108 people, providing important ecosystem services for human survival and development. However, dryland ecosystems are extremely fragile and sensitive to external environmental changes. Land use and land cover (LULC) changes significantly impact soil structure and function, thus affecting the soil multifunctionality (SMF). However, the effect of LULC changes on the SMF in the drylands of China has rarely been reported. In this study, we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center. We explored the drivers of the SMF changes under different LULC types (including forest, grassland, shrubland, and desert) and used structural equation modeling to explore the main driver of the SMF changes. The results showed that the SMF under the four LULC types decreased in the following descending order: forest, grassland, shrubland, and desert. The main driver of the SMF changes under different LULC types was mean annual temperature (MAT). In addition to MAT, pH in forest, soil moisture (SM) and soil biodiversity index in grassland, SM in shrubland, and aridity index in desert are crucial factors for the SMF changes. Therefore, the SMF in the drylands of China is regulated mainly by MAT and pH, and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes. The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

Between-year weather differences and long-term environmental trends both contribute to observed vegetation changes in a plot resurvey study.

Repeated surveys of vegetation plots offer a viable tool to detect fine-scale responses of vegetation to environmental changes. In this study, our aim was to explore how the species composition and species richness of dry grasslands changed over a period of 17 years, how these changes relate to environmental changes and how the presence of spring ephemerals, which may react to short-term weather fluctuations rather than long-term climatic trends, may influence the results. A total of 95 plots was surveyed in 2005 and resurveyed in 2022 in dry grasslands of the Kiskunság Sand Ridge (Hungary, Eastern Central Europe), where there has been a significant increase in mean annual temperature during the last decades, while no trends in precipitation can be identified. Db-RDA was performed to reveal compositional changes. The changes in environmental conditions and naturalness state were assessed using ecological and naturalness indicator values. We also compared per-plot richness of all species, native species and non-native species of the old and the new relevés. All analyses were repeated after removing all spring ephemerals. We found clear temporal changes in species composition. Mean temperature indicator values increased, while mean soil moisture indicator values decreased during the 17 years. Also, decreasing per-plot richness was detected both for all species and for native species, while mean naturalness increased. After the removal of spring ephemerals, the compositional changes were less obvious although still significant. The increase in the temperature indicator values remained significant even without the spring ephemerals. However, the decrease in the moisture indicator values, the decrease in the number of all species and native species, as well as the increase in naturalness indicator values disappeared when spring ephemerals were excluded from the analyses. Our study demonstrates that between-year weather differences and long-term environmental trends both contribute to observed vegetation changes.

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District, Ghana

Smallholder farmers in Ahafo Ano North District, Ghana, face multiple climatic and non-climatic issues. This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions (FGDs) with 10 respondents. The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022. The relative importance index (RII) value was used to rank the climatic and non-climatic factors perceived by respondents. The socioeconomic characteristics affecting smallholder farmers’ perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model. Results showed that mean annual rainfall decreased (P>0.05) but mean annual temperature significantly increased (P<0.05) from 2002 to 2022 in the district. The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature (RII=0.498), erratic rainfall (RII=0.485), and increased windstorms (RII=0.475). The critical non-climatic factors were high cost of farm inputs (RII=0.485), high cost of healthcare (RII=0.435), and poor condition of roads to farms (RII=0.415). Smallholder farmers’ perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics (P<0.05). This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors. Therefore, to enhance the resilience of smallholder farmers to climate change, it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

"Two zones and three centers" distribution and suitable areas shift of an evergreen oak in subtropical China under climate scenarios.

Understanding the impact of climate change on the geographical distribution of species is a fundamental requirement for biodiversity conservation and resource management. Quercus oxyphylla, an evergreen oak endemic to China, plays a crucial role in maintaining the ecological stability in subtropical regions and high economic value attributed to its dark and high-density heartwood, but the existing resources are close to endangered. Currently, limited knowledge exists regarding its distribution and potential influences of climate change on suitable areas. This study utilized 63 occurrence records and Biomod2 platform, to predict changes in suitable areas for Q. oxyphylla under future climate change. The results revealed that (1) Q. oxyphylla showed a pattern of three disjunctive geographical centers in the eastern subregion of subtropical evergreen broad-leaved forest region (IVA): Qinling-Daba Mountains, Nanling Mountains and Wuyi Mountains center. Currently, the highly suitable areas concentrated in two zones divided by the Yangtze River, that is, the northern subtropical evergreen and deciduous broad-leaved forest zone (IVAii) and the mid-subtropical evergreen broad-leaved forest zone (IVAi). (2) The temperature-related variables, such as annual temperature range (Bio7), the mean diurnal range (Bio2), and annual mean temperature (Bio1), were identified as the key determinants of the distribution pattern. Because of its considerable climatic variations in temperature and water conditions, Q. oxyphylla's habitat displayed a wider climate niche and strong physiological tolerance to climate change. (3) Under future climate scenarios, the suitable area of the species was expected to overall expand with significant regional differences. The suitable area in IVAi was expected to expand significantly northward while that in IVAii was expected to gradually shrink. To address the impact of climate change, it is necessary to develop conservation plans focused around the three distribution centers, implement localized and regional conservation policies, and conduct educational outreach among local people.