Global Perspective on the Migration History and Current and Future Potential Distribution of Rattus tanezumi.

1961-2005年东北地区气温和降水变化趋势

ABSTRACTSpecies distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of Indianthus virgatus under current and future climate change scenarios (2050 and 2070) using MaxEnt (3.4.4) and Wallace Ecological Modeling (v2.1.2) tools. The study also intended to identify key environmental predictors of I. virgatus' distribution. Species occurrence data were collected from various sources, including herbarium (online and physical), field surveys, and online databases, yielding 105 unique locations in the Western Ghats (WG) of India and Sri Lanka. We used 19 bioclimatic variables and elevation data sourced from WorldClim for modeling. The MaxEnt and Wallace models showed excellent performance in predicting the distribution of I. virgatus, with area under the curve values of 0.958 (± 0.002) and 0.93, respectively. In MaxEnt modeling, Temperature Seasonality (bio4) was the most significant environmental parameter, followed by the Precipitation of the Coldest Quarter (bio19). In contrast, the Annual Mean Temperature (bio1), Temperature Seasonality (bio4), and Annual Precipitation (bio12) were among the key contributors in Wallace EcoMod. Both the models predicted relatively lesser areas in the species' distribution range as highly suitable habitats (HSH) in India and Sri Lanka. We found divergent trends in predicting I. virgatus distributions using MaxEnt and Wallace EcoMod, particularly for future projections. Nevertheless, both models predicted significant habitat loss under future climate change scenarios, especially under RCP85, with varying degrees of suitability across India and Sri Lanka. Overall, our findings on expected habitat loss under future climate change scenarios highlight the importance of conserving I. virgatus, which has already been declared critically endangered (CR) in Sri Lanka.

Mammalian faunas, ecological indices, and machine-learning regression for the purpose of paleoenvironment reconstruction in the Miocene of South America

Combined with recent historical climate data and two periods of land use data sets from remote sensing data, we test the net primary productivity (NPP) data sets in North China modelled by the satellite data-driven Global Production Efficiency Model (GLO-PEM) for detecting the widespread spatial and temporal characteristics of the impacts of climate and land use change on the regional NPP. Our results show that over the past 20 years, the mean annual temperature in the study region has remarkably increased by more than 0.064 °C, but over the same period, there has been a 1.49 mm decrease in annual precipitation and decrease in NPP by an annual rate of 6.9 TgC. The NPP changes in the study region were greatly affected by the average temperature and precipitation by ten-day periods as well as the seasonal temperature and precipitation in the study region. The correlation between seasonal NPP and seasonal precipitation and temperature is highly consistent with land cover spatially, and the correlation coefficient changes with the changes of vegetation types. The analysis reveals that the related areas in land use change only take up 5.45% of the whole studied region, so the climate changes dominate the impacts on the NPP in the whole study region (90% of the total). However, land use plays an absolute dominative role in areas with land cover changes, accounting for 97% of the total. From 1981 to 2000, the NPP in the whole study region remarkably reduced due to obvious precipitation decrease and temperature rise. Between two periods of land use (about 10 years), the changes in climate are predicted to promote a decrease in NPP by 78 (±0.6) TgC, and integrated impacts of climate changes and land use to promote a decrease in NPP by 87(±0.8) TgC.

Global climate change is significantly altering the large scale distributions of plants and animals. The Earth has warmed by 0.7°C during the last century. The consequences are already apparent in forest ecosystems as species are responding to the changing climate with shifts in their phenology and geographic distributions. The potential for large increases in global mean temperatures (e.g., 4.3 ± 0.7°C) by 2100 has significant implications for forest species and ecosystems. Under these varying climatic conditions, some species may go extinct either locally or regionally, with climate change acting synergistically with other extinction drivers. Tropical Asian forests contain several biodiversity hotspots and species-rich ecoregions. Our understanding of species’ and forest ecosystems’ vulnerability to global climate change in this region is limited. Addressing this problem is a critical task for current tropical Asian ecological research.The overall aim of this PhD thesis is to investigate the current and potential effects of climate change on the geographic distribution and composition of selected plant and mammal species in tropical Asian forests. The selected plants include Sal (Shorea robusta), Garjan (Dipterocarpus turbinatus) and Teak (Tectona grandis). These all are ecologically and economically important timber trees and are distributed widely across South and Southeast Asia. The selected mammals include Asiatic black bear (Ursus thibetanus), Asian elephant (Elephas maximus), Western hoolock gibbon (Hoolock hoolock) and Bengal tiger (Panthera tigris tigris). These threatened large mammals are of high conservation concern and are typically targeted by international conventions. I present a comprehensive review of the previous literature and new predictive models of species distributions that quantify potential climate change impacts on tropical forests. My results show that projected changes in temperature and rainfall extremes are potential threats to the diverse and species-rich forest ecoregions of tropical Asia.I used bio-climatic models and two scenarios of climate change (a moderate and an extreme Representative Concentration Pathway (RCP) scenario) to assess climate change impacts on the continental scale distributions of two threatened Dipterocarp trees Sal and Garjan, and the valuable timber species, Teak. Annual precipitation was the key bioclimatic variable for explaining the current and future distributions of Sal and Garjan. Suitable habitat conditions for Sal will decline by 24% and 34% by 2070 under the RCP4.5 and RCP8.5 scenarios, respectively. In contrast, the consequences of climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. Changes in annual precipitation, precipitation seasonality and annual mean actual evapotranspiration may result in shifts in the distributions of Teak across tropical Asia. These findings can contribute to conservation planning for the species and their management under future climates.I developed habitat suitability models for the four large threatened mammals (Asiatic black bear, Asian elephant, Western hoolock gibbon and Bengal tiger), across their entire distributions in Asia. The results suggest that changes in annual precipitation, annual mean temperature, precipitation and temperature seasonality, and land use/land cover change could reduce suitable habitat for these large mammals and therefore increase their extinction risks. It can be concluded that increasing climate stress on tropical forests could lead to greater extinction risks of these threatened large mammals.The findings of this thesis provide a fundamental basis for further studies of climate change impacts on species distribution in tropical Asia, and highlight the conservation importance of the plant and animal species in the region. The modelling outputs can be used to categorize the natural habitats of Sal, Garjan and Teak as low to high risk under changing climates to inform conservation planning and forest management. Given the conservation importance of the threatened large mammals for maintaining a healthy forest ecosystem, the findings of the models can be used to categorize the likely suitable habitats under changing climates and preparing proper guidelines to reduce their extinction risks. To ensure wider applicability to conservation planning for species vulnerable to global climate change, the methods and analyses presented here for tropical Asia could be applied to other tropical regions (i.e., in Africa and the Americas), using different species groups and forest types.

Background and aims – Climate change is driving biodiversity loss globally, including species with medicinal and aromatic properties. In this study, we assessed the potential distributions of three plants, Lippia alba, L. turbinata, and Salimenaea integrifolia, widely consumed in South America. In this study, we aimed i) to predict their current geographic distribution through SDM, ii) to estimate the importance of abiotic factors in their distribution, iii) to evaluate the potential change in future distribution under different scenarios of climate change. Material and methods – Using MaxEnt, we modelled the current and future potential distributions of these three species under three Representative Concentration Pathways (RCPs 2.6, 4.5, and 8.5) for the period 2070 (2061–2080). Key results – The distribution of L. alba is primarily influenced by precipitation seasonality and mean annual temperature, whereas L. turbinata and S. integrifolia are shaped by mean annual temperature and annual precipitation. The most favourable areas for L. alba are found in the Chacoan, Espinal, Pampean, Paranaense, Caatinga, Atlantic, and Amazonian biogeographic provinces (2,250,640 km2). Lippia turbinata thrives in the Chacoan, Espinal, Monte, Pampean, and Yungas provinces (671,851 km2), while S. integrifolia is best suited to the Monte, Chacoan, and Puna/Prepuna provinces (197,022 km2). Our results indicate heterogeneous responses to climate change in the future: L. turbinata and S. integrifolia may experience range expansion (15.12 to 19.86% and 1.48 to 3.46%, respectively), while L. alba is projected to face range contraction (-4.60 to -23.23%), particularly in the northern edge of its distribution. Conclusion – These findings emphasize the species-specific responses of medicinal and aromatic plants to climate change. Moreover, they highlight the need to develop tailored conservation strategies to safeguard vulnerable populations and preserve valuable medicinal resources.

BackgroundIn recent years, global climate change in tandem with increased human activity has resulted in habitat degradation or the migration of rare medicinal plants, potentially impacting the quality of medicinal herbs. Astragalus membranaceus var. mongholicus is a valuable bulk medicinal material in Northwest China. As the demand for this medicinal herb continues to increase in both domestic and international markets, ensuring the sustainable development of high-quality Astragali Radix is important. In this study, the maximum entropy (Maxent) model was applied, thereby incorporating 136 distribution records, along with 39 environmental factors of A. membranaceus var. mongholicus, to assess the quality zonation and potential distribution of this species in China under climate change.ResultsThe results showed that the elevation, annual mean temperature, precipitation of wettest month, solar radiation in June, and mean temperature of warmest quarter were the critical environmental factors influencing the accumulation of astragaloside IV and Astragalus polysaccharide in A. membranaceus var. mongholicus. Among the twelve main environmental variables, annual mean temperature, elevation, precipitation of the wettest month, and solar radiation in November were the four most important factors influencing the distribution of A. membranaceus var. mongholicus. In addition, ecological niche modelling revealed that highly suitable habitats were mainly located in central and western Gansu, eastern Qinghai, northern Shaanxi, southern Ningxia, central Inner Mongolia, central Shanxi, and northern Hebei. However, the future projections under climate change suggested a contraction of these suitable areas, shifting towards northeastern high-latitude and high-elevation mountains.ConclusionsThe findings provide essential insights for developing adaptive strategies for A. membranaceus var. mongholicus cultivation in response to climate change and can inform future research on this species. By considering the identified environmental factors and the potential impacts of the predicted climate changes, we can visualize the regional distribution of high-quality Radix Astragali and develop conservation strategies to protect and restore its suitable habitats.

Journal of EcologyVolume 105, Issue 2 p. 559-560 CorrigendumFree Access Corrigendum This article corrects the following: Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar Ghislain Vieilledent, Oliver Gardi, Clovis Grinand, Christian Burren, Mamitiana Andriamanjato, Christian Camara, Charlie J. Gardner, Leah Glass, Andriambolantsoa Rasolohery, Harifidy Rakoto Ratsimba, Valéry Gond, Jean-Roger Rakotoarijaona, Emily Lines, Volume 104Issue 3Journal of Ecology pages: 703-715 First Published online: February 25, 2016 First published: 24 October 2016 https://doi.org/10.1111/1365-2745.12679Citations: 1AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Vieilledent, G., Gardi, O., Grinand, C., Burren, C., Andriamanjato, M., Camara, C., Gardner, C.J., Glass, L., Rasolohery, A., Ratsimba, H.R., Gond, V. & Rakotoarijaona, J.R. (2016) Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar. Journal of Ecology, 104, 703–715. doi:10.1111/1365-2745.12548. In the paper by Vieilledent et al. (2016), the authors inadvertently inverted the captions of Figs 2 and 3. The authors and journal would like to correct this error. The results and conclusions of the article are not affected. The figures with their correct captions are below. Figure 2Open in figure viewerPowerPoint Forest carbon map in 2010 for Madagascar. We derived a national forest carbon map in 2010 for Madagascar at 250-m resolution. We fitted our model using above-ground carbon density for 1771 forest plots measured between 1996 and 2013. Our model included six explicative variables: two vegetation indexes (VCF and EVI from 2000 to 2010 MODIS satellite images at 250 m), one topographic variable (elevation from SRTM at 90 m) and three climatic variables [mean annual temperature, mean annual precipitation and temperature seasonality from WorldClim at 30 arc-seconds (~1 km)]. Our predictions are limited to the extent of the forest in 2010. Clear differences appear for the forest carbon stocks between the three ecoregions including moist, dry and spiny forest (see black lines for delimitations). Figure 3Open in figure viewerPowerPoint Relationships between explicative variables and ACD. Graphics show the marginal effect of the variable on ACD. Range of predicted ACD is reduced compared to the observed range of ACD in forest plots because variables other than the target variable are set to their mean values. Hash marks at the bottom of the plot indicate the deciles of the explicative variable. Percentage in the top-left or top-right corner of each panel is the percentage of increase in mean square error when the variable was randomly permuted, which indicates the variable relative importance in determining ACD. Reference Vieilledent, G., Gardi, O., Grinand, C., Burren, C., Andriamanjato, M., Camara, C., Gardner, C.J., Glass, L., Rasolohery, A., Ratsimba, H.R., Gond, V. & Rakotoarijaona, J.R. (2016) Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar. Journal of Ecology, 104, 703– 715. doi:10.1111/1365-2745.12548 Citing Literature Volume105, Issue2March 2017Pages 559-560 FiguresReferencesRelatedInformation

Introduction: Global warming is the most important challenge facing man in the 21st century. Warmer weather will increase evapotranspiration, which will exacerbate droughts. One of the main causes of global warming is man himself. Humans have accelerated the Earth's climate change by producing large amounts of greenhouse gases. For this reason, information about changes in the earth's temperature in the next decades has always been considered. The results of the researchers show that climate change has obvious and significant effects on temperature and rainfall in different parts of Iran in the next decades. By predicting and estimating the extent of these effects, climate change impacts can be mitigated with adequate preparedness, low cost, and greater speed.Material and methods: In this study, the effect of climate change on the mean maximum and minimum annual and seasonal temperatures in Arak under the emission scenarios of RCP2.6, RCP4.5, RCP8.5 for the 2040s was investigated. To use the output of General Circulation Models at regional and local scales is that they are using downscaling models, are downscaled. In this study, Statistical Downscaling Model (SDSM) to downscale output of General Circulation Models CanESM2 were used. This model had an acceptable ability to simulate the average maximum and minimum seasonal and annual temperatures in the study area. Results and discussion: According to the obtained results, the mean maximum temperature in winter and spring will decrease under all three scenarios RCP2.6, RCP4.5, RCP8.5, which can indicate that the daily temperature will be cooler in these seasons. However, the mean maximum temperature will increase in summer and autumn, which may indicate that the daily temperature will be warmer in these seasons. The mean minimum temperature in winter and spring under all three scenarios RCP2.6, RCP4.5, RCP8.5 will decrease and increase in summer seasons. These results show that in the 2040s, the city of Arak has colder night temperatures in winter and spring and warmer temperatures in summer and spring. Due to the fact that warmer weather increases the demand for water and electricity, and because Arak is an industrial city with a dry climate, it can face serious challenges of water and electricity shortage in the future.Conclusion: According to the results obtained in this study, in the 2040s, Arak will have colder winters and springs, and warmer summers and autumns. The highest effect of climate change on the temperature of Arak is related to the average minimum temperature in autumn, which under the scenarios of RCP2.6, RCP4.5, RCP8.5, the average minimum temperature in autumn increased by 206.88, 196.37 and 192.27 percent, respectively. The mean annual maximum and minimum temperature under all three scenarios will increase in the 2040s. The highest increase in the mean annual maximum and minimum temperature is related to RCP8.5 and RCP2.6 scenarios, respectively, which they are equal to 4.14 and 4.38.

Facing climate change: Range dynamics and chromosome diversity in Hedeoma multiflora Benth., a South American aromatic-medicinal plant at risk

Dengue, chikungunya, and Zika virus epidemics transmitted by Aedes aegypti mosquitoes have recently (re)emerged and spread throughout the Americas, Southeast Asia, the Pacific Islands, and elsewhere. Understanding how environmental conditions affect epidemic dynamics is critical for predicting and responding to the geographic and seasonal spread of disease. Specifically, we lack a mechanistic understanding of how seasonal variation in temperature affects epidemic magnitude and duration. Here, we develop a dynamic disease transmission model for dengue virus and Aedes aegypti mosquitoes that integrates mechanistic, empirically parameterized, and independently validated mosquito and virus trait thermal responses under seasonally varying temperatures. We examine the influence of seasonal temperature mean, variation, and temperature at the start of the epidemic on disease dynamics. We find that at both constant and seasonally varying temperatures, warmer temperatures at the start of epidemics promote more rapid epidemics due to faster burnout of the susceptible population. By contrast, intermediate temperatures (24–25°C) at epidemic onset produced the largest epidemics in both constant and seasonally varying temperature regimes. When seasonal temperature variation was low, 25–35°C annual average temperatures produced the largest epidemics, but this range shifted to cooler temperatures as seasonal temperature variation increased (analogous to previous results for diurnal temperature variation). Tropical and sub-tropical cities such as Rio de Janeiro, Fortaleza, and Salvador, Brazil; Cali, Cartagena, and Barranquilla, Colombia; Delhi, India; Guangzhou, China; and Manila, Philippines have mean annual temperatures and seasonal temperature ranges that produced the largest epidemics. However, more temperate cities like Shanghai, China had high epidemic suitability because large seasonal variation offset moderate annual average temperatures. By accounting for seasonal variation in temperature, the model provides a baseline for mechanistically understanding environmental suitability for virus transmission by Aedes aegypti. Overlaying the impact of human activities and socioeconomic factors onto this mechanistic temperature-dependent framework is critical for understanding likelihood and magnitude of outbreaks.

Simulation of future land surface temperature under the scenario of climate change using remote sensing & GIS techniques of northwestern Rajshahi district, Bangladesh

On the basis of the mean annual and seasonal temperatures from 30 meteorological stations in the Jinsha River Basin (JRB) from 1961 to 2008, the temperature trends are analyzed by using Mann–Kendall test and linear trend analysis. There is an increasing trend in mean annual and seasonal temperatures during this period, and the increasing trends in winter seem more significant than those in the other three seasons. The mean annual temperature has increased by 0.0158°C/year during the last 48 years. There are more than 70% of stations exhibiting increasing trends for annual and seasonal temperatures. The increasing trends in the headwater and upper reaches are more dominant than those in the middle and lower reaches. The largest increase magnitude occurred in the low temperature area, while the largest decrease magnitude occurred in the high temperature area. The decreasing trends are mainly characterized for the maximum temperature time series, and summer is the only season showing a slight and insignificant increasing trend. All the time series showed a statistically significant increasing trend at the level of α = 0.05 for the minimum temperature time series. As a whole, the increasing magnitude of the minimum temperature is significantly greater than the decreasing magnitude of the maximum temperature.

The ecological effects of species introductions can change in magnitude over time, but an understanding of how and why they do so remains incompletely understood. Clarifying this issue requires consideration of how temporal variation in invader traits affects invasion impacts (e.g., through differential effects on the diversity and composition of native species assemblages). We examine the temporal dynamics of Argentine ant invasions in northern California byresurveying 202 sites first sampled 30-40yr ago. To test how invasion impacts change over time, we estimated native ant richness and species composition at 20 riparian woodland sites that span a 30-yr invasion chronosequence. We then use these data to test how variation in two invader traits (aggression and relative abundance) is related to time since invasion and invasion impact. Native ant assemblages along the chronosequence exhibited reduced native ant richness and altered species composition (compared to uninvaded control sites), but the magnitude of these impacts was independent of time since invasion. These results are corroborated by additional temporal comparisons of native ant assemblages at riparian sites sampled 20-30yr ago. Our findings together illustrate that the impacts of invasions can persist undiminished over at least a 30-yr time frame and remain evident at regional scales. Although neither invader trait varied with time since invasion, native ant richness declined as the relative abundance of the Argentine ant increased. This latter result supports the hypothesis that factors reducing invader abundance at particular sites can decrease invasion impacts, but also that such changes may be due to site-specific factors (e.g., abiotic conditions) that affect invader abundance rather than time since invasion per se. Future studies should attempt to differentiate factors that are intrinsic to the process of invasion (e.g., changes in invader populations) from long-term environmental changes (e.g., climate change) that represent extrinsic influences on the dynamics of invasion.

To investigate the current distribution of ticks and predict the suitable habitats of ticks in the Yangtze River Delta urban agglomeration in 2017, so as to provide insights into tick control and management of tick-borne diseases in these areas. All publications pertaining to tick and pathogen distribution in the Yangtze River Delta urban agglomeration were retrieved, and the geographical location of tick distribution was extracted. The effects of 19 climatic factors on the distribution of ticks were examined using the jackknife method, including the mean temperature of the wettest quarter, precipitation of the coldest quarter, mean temperature of the driest quarter, maximum temperature of the warmest month, precipitation of the driest month, minimal temperature of the coldest month, annual precipitation, mean daily temperature range, precipitation seasonality, annual temperature range, temperature seasonality, annual mean temperature, mean temperature of the warmest quarter, precipitation of the wettest quarter, isothermality, mean temperature of the coldest quarter, precipitation of the wettest month, precipitation of the driest quarter and precipitation of the warmest quarter. The distribution of ticks was analyzed in 2020 using the maximum entropy (MaxEnt) model, and the potential suitable habitats of ticks were predicted in 2070 using the MaxEnt model based on climatic data. A total of 380 Chinese and English literatures were retrieved, and 148 tick distribution sites were extracted, with 135 sites included in the subsequent analysis. There were 7 genera (Haemaphysalis, Rhipicephalus, Ixodes, Dermacentor, Boophilus, Hyalomma and Amblyomma) and 27 species of ticks detected in the Yangtze River Delta urban agglomeration. The climatic factors affecting the distribution of ticks in the Yangtze River Delta urban agglomeration mainly included the mean temperature of the wettest quarter and the precipitation of the coldest quarter, with 26.1% and 23.6% contributions to tick distributions. The high-, medium- and low-suitable habitats of ticks were 20 337.08, 40 017.38 km2 and 74 931.43 km2 in the Yangtze River Delta urban agglomeration in 2020, respectively. The climate changes led to south expansion of the suitable habitats of ticks in the Yangtze River Delta urban agglomeration in 2070, and the total areas of suitable habitats of ticks was predicted to increase by 18 100 km2. In addition, the high-, medium- and low-suitable habitats of ticks were predicted to increase to 24 317.84, 45 283.02 km2 and 83 766.38 km2 in the Yangtze River Delta urban agglomeration in 2070, respectively. Multiple tick species are widespread in the Yangtze River Delta urban agglomeration, and the future climate changes may lead to expansion of tick distribution in these areas.