Climate Change and Spatiotemporal Distributions of Vector-Borne Diseases in Nepal – A Systematic Synthesis of Literature

Background

Despite its largely mountainous terrain for which this Himalayan country is a popular tourist destination, Nepal is now endemic for five major vector-borne diseases (VBDs), namely malaria, lymphatic filariasis, Japanese encephalitis, visceral leishmaniasis and dengue fever. There is increasing evidence about the impacts of climate change on VBDs especially in tropical highlands and temperate regions. Our aim is to explore whether the observed spatiotemporal distributions of VBDs in Nepal can be related to climate change.

Methodology

A systematic literature search was performed and summarized information on climate change and the spatiotemporal distribution of VBDs in Nepal from the published literature until December2014 following providing items for systematic review and meta-analysis (PRISMA) guidelines.

Principal Findings

We found 12 studies that analysed the trend of climatic data and are relevant for the study of VBDs, 38 studies that dealt with the spatial and temporal distribution of disease vectors and disease transmission. Among 38 studies, only eight studies assessed the association of VBDs with climatic variables. Our review highlights a pronounced warming in the mountains and an expansion of autochthonous cases of VBDs to non-endemic areas including mountain regions (i.e., at least 2,000 m above sea level). Furthermore, significant relationships between climatic variables and VBDs and their vectors are found in short-term studies.

Conclusion

Taking into account the weak health care systems and difficult geographic terrain of Nepal, increasing trade and movements of people, a lack of vector control interventions, observed relationships between climatic variables and VBDs and their vectors and the establishment of relevant disease vectors already at least 2,000 m above sea level, we conclude that climate change can intensify the risk of VBD epidemics in the mountain regions of Nepal if other non-climatic drivers of VBDs remain constant.     

Bumblebees moving up: shifts in elevation ranges in the Pyrenees over 115 years

In a warming climate, species are expected to shift their geographical ranges to higher elevations and latitudes, and if interacting species shift at different rates, networks may be disrupted. To quantify the effects of ongoing climate change, repeating historical biodiversity surveys is necessary. In this study, we compare the distribution of a plant–pollinator community between two surveys 115 years apart (1889 and 2005–06), reporting distribution patterns and changes observed for bumblebee species and bumblebee-visited plants in the Gavarnie-Gèdre commune in the Pyrenees, located in southwest Europe at the French–Spanish border. The region has warmed significantly over this period, alongside shifts in agricultural land use and forest. The composition of the bumblebee community shows relative stability, but we observed clear shifts to higher elevations for bumblebees (averaging 129 m) and plants (229 m) and provide preliminary evidence that some bumblebee species shift with the plants they visit. We also observe that some species have been able to occupy the same climate range in both periods by shifting elevation range. The results suggest the need for long-term monitoring to determine the role and impact of the different drivers of global change, especially in montane habitats where the impacts of climate changes are anticipated to be more extreme.     

Present and future projections of habitat suitability of the Asian tiger mosquito,a vector of viral pathogens,from global climate simulation

Climate change can influence the transmission of vector-borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian tiger mosquito (Aedes albopictus), which can transmit pathogens that cause chikungunya, dengue fever, yellow fever and various encephalitides. Using a general circulation model at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the twenty-first century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that approximately 2.4 billion individuals in a land area of nearly 20 million km² will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.     

Variable precipitation leads to dynamic range limits of forest songbirds at a forest‐grassland ecotone

Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest‐grassland ecotone in the southcentral United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad‐scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest‐breeding passerines from 30‐year average climate conditions from 1980 to 2010. During this time, the southern Great Plains experienced an unprecedented wet period without periodic multi‐year droughts that characterized the region''s long‐term climate from the early 1900s. Species’ climatic niche models were then projected onto two historical drought periods: 1952–1958 and 1966–1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest‐grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980–2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966–1972 range limit projections. Periods of lower precipitation in the forest‐grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years.     

Niche dynamics of Memecylon in Sri Lanka: Distribution patterns,climate change effects,and conservation priorities

Recent climate projections have shown that the distribution of organisms in island biotas is highly affected by climate change. Here, we present the result of the analysis of niche dynamics of a plant group, Memecylon, in Sri Lanka, an island, using species occurrences and climate data. We aim to determine which climate variables explain current distribution, model how climate change impacts the availability of suitable habitat for Memecylon, and determine conservation priority areas for Sri Lankan Memecylon. We used georeferenced occurrence data of Sri Lankan Memecylon to develop ecological niche models and assess both current and future potential distributions under six climate change scenarios in 2041–2060 and 2061–2080. We also overlaid land cover and protected area maps and performed a gap analysis to understand the impacts of land‐cover changes on Memecylon distributions and propose new areas for conservation. Differences among suitable habitats of Memecylon were found to be related to patterns of endemism. Under varying future climate scenarios, endemic groups were predicted to experience habitat shifts, gains, or losses. The narrow endemic Memecylon restricted to the montane zone were predicted to be the most impacted by climate change. Projections also indicated that changes in species’ habitats can be expected as early as 2041–2060. Gap analysis showed that while narrow endemic categories are considerably protected as demonstrated by their overlap with protected areas, more conservation efforts in Sri Lankan forests containing wide endemic and nonendemic Memecylon are needed. This research helped clarify general patterns of responses of Sri Lankan Memecylon to global climate change. Data from this study are useful for designing measures aimed at filling the gaps in forest conservation on this island.     

The Effects of Climate Change and Globalization on Mosquito Vectors: Evidence from Jeju Island,South Korea on the Potential for Asian Tiger Mosquito (Aedes albopictus) Influxes and Survival from Vietnam Rather Than Japan

Background

Climate change affects the survival and transmission of arthropod vectors as well as the development rates of vector-borne pathogens. Increased international travel is also an important factor in the spread of vector-borne diseases (VBDs) such as dengue, West Nile, yellow fever, chikungunya, and malaria. Dengue is the most important vector-borne viral disease. An estimated 2.5 billion people are at risk of infection in the world and there are approximately 50 million dengue infections and an estimated 500,000 individuals are hospitalized with dengue haemorrhagic fever annually. The Asian tiger mosquito (Aedes albopictus) is one of the vectors of dengue virus, and populations already exist on Jeju Island, South Korea. Currently, colder winter temperatures kill off Asian tiger mosquito populations and there is no evidence of the mosquitos being vectors for the dengue virus in this location. However, dengue virus-bearing mosquito vectors can inflow to Jeju Island from endemic area such as Vietnam by increased international travel, and this mosquito vector''s survival during colder winter months will likely occur due to the effects of climate change.

Methods and Results

In this section, we show the geographical distribution of medically important mosquito vectors such as Ae. albopictus, a vector of both dengue and chikungunya viruses; Culex pipiens, a vector of West Nile virus; and Anopheles sinensis, a vector of Plasmodium vivax, within Jeju Island, South Korea. We found a significant association between the mean temperature, amount of precipitation, and density of mosquitoes. The phylogenetic analyses show that an Ae. albopictus, collected in southern area of Jeju Island, was identical to specimens found in Ho Chi Minh, Vietnam, and not Nagasaki, Japan.

Conclusion

Our results suggest that mosquito vectors or virus-bearing vectors can transmit from epidemic regions of Southeast Asia to Jeju Island and can survive during colder winter months. Therefore, Jeju Island is no longer safe from vector borne diseases (VBDs) due to the effects of globalization and climate change, and we should immediately monitor regional climate change to identify newly emerging VBDs.     

The fate of Meconopsis species in the Tibeto‐Himalayan region under future climate change

High‐mountain areas such as the Tibeto‐Himalayan region (THR) host cold‐adapted biota expected to be sensitive to anthropogenic climate change. Meconopsis is a representative endangered genus confined to alpine meadow or subnival habitats in the THR. We used climate‐niche factor analysis to study the vulnerability of ten Meconopsis species to climate change, comparing current climate (representative of 1960–1990) to future climate scenarios (2070: average 2061–2080). For these ten Meconopsis species, we then identified potential future climate refugia and determined optimal routes for each species to disperse to the proposed refugia. Our results indicate that for the ten Meconopsis species, the regions with low vulnerability to climate change in the THR are the central Qinghai‐Tibet Plateau, the Hengduan Mountains (HDM), the eastern Himalayas, and the West Qinling Mountain (WQL), and can be considered potential future climate refugia. Under future climate change, we found for the ten Meconopsis species potential dispersal routes to three of the four identified refugia: the HDM, the eastern Himalayas, and the WQL. Our results suggest that past refugia on the THR will also be the future climate refugia for the ten Meconopsis species, and these species may potentially persist in multiple future climate refugia, likely reducing risks from climate change. Furthermore, climate change may affect the threat ranking of Red Listed Species for Meconopsis species, as Least Concern species were estimated to become more vulnerable to climate change than the only Near Threatened species.     

Climate influences on the cost-effectiveness of vector-based interventions against malaria in elimination scenarios

Despite the dependence of mosquito population dynamics on environmental conditions, the associated impact of climate and climate change on present and future malaria remains an area of ongoing debate and uncertainty. Here, we develop a novel integration of mosquito, transmission and economic modelling to assess whether the cost-effectiveness of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) against Plasmodium falciparum transmission by Anopheles gambiae s.s. mosquitoes depends on climatic conditions in low endemicity scenarios. We find that although temperature and rainfall affect the cost-effectiveness of IRS and/or LLIN scale-up, whether this is sufficient to influence policy depends on local endemicity, existing interventions, host immune response to infection and the emergence rate of insecticide resistance. For the scenarios considered, IRS is found to be more cost-effective than LLINs for the same level of scale-up, and both are more cost-effective at lower mean precipitation and higher variability in precipitation and temperature. We also find that the dependence of peak transmission on mean temperature translates into optimal temperatures for vector-based intervention cost-effectiveness. Further cost-effectiveness analysis that accounts for country-specific epidemiological and environmental heterogeneities is required to assess optimal intervention scale-up for elimination and better understand future transmission trends under climate change.     

Range‐wide persistence of the endangered arroyo toad (Anaxyrus californicus) for 20+ years following a prolonged drought

Prolonged drought due to climate change has negatively impacted amphibians in southern California, U.S.A. Due to the severity and length of the current drought, agencies and researchers had growing concern for the persistence of the arroyo toad (Anaxyrus californicus), an endangered endemic amphibian in this region. Range‐wide surveys for this species had not been conducted for at least 20 years. In 2017–2020, we conducted collaborative surveys for arroyo toads at historical locations. We surveyed 88 of the 115 total sites having historical records and confirmed that the arroyo toad is currently extant in at least 61 of 88 sites and 20 of 25 historically occupied watersheds. We did not detect toads at almost a third of the surveyed sites but did detect toads at 18 of 19 specific sites delineated in the 1999 Recovery Plan to meet one of four downlisting criteria. Arroyo toads are estimated to live 7–8 years, making populations susceptible to prolonged drought. Drought is estimated to increase in frequency and duration with climate change. Mitigation strategies for drought impacts, invasive aquatic species, altered flow regimes, and other anthropogenic effects could be the most beneficial strategies for toad conservation and may also provide simultaneous benefits to several other native species that share the same habitat.     

植物物候与气候研究进展

植物物候及其变化是多个环境因子综合影响的结果,其中气候是最重要、最活跃的环境因子。主要从气候环境角度分析了植物物候与气候以及气候变化间的相互关系,概述了国内外有关植物物候及物候模拟等方面的研究进展。表明,温度是影响物候变化最重要的因子;同时,水分成为胁迫因子时对物候的影响也十分重要。近50a左右,世界范围内的植物物候呈现出了春季物候提前,秋季物候推迟或略有推迟的特征,从而导致了多数植物生长季节的延长,并成为全球物候变化的趋势。全球气候变暖改变了植物开始和结束生长的日期,其中冬季、春季气温的升高使植物的春季物候提前是植物生长季延长的主要原因。目前对物候学的研究方向主要集中在探讨物候与气候变化之间的关系,而模型模拟是定量研究气候变化与植物物候之间关系的重要方式,国内外已经开发出多种物候模型来分析气候驱动与物候响应之间的因果关系。另外遥感资料的应用也为物候模型研究提供了新的方向。物候机理研究、物候与气候关系以及物候模型研究将是研究的重点。     

Large‐scale PVA modeling of insects in cultivated grasslands: The role of dispersal in mitigating the effects of management schedules under climate change

In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60‐year periods (2020–2079) on a fine temporal (daily) and high spatial (250 × 250 m²) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.     

Impacts of predator-mediated interactions along a climatic gradient on the population dynamics of an alpine bird

According to classic theory, species'' population dynamics and distributions are less influenced by species interactions under harsh climatic conditions compared to under more benign climatic conditions. In alpine and boreal ecosystems in Fennoscandia, the cyclic dynamics of rodents strongly affect many other species, including ground-nesting birds such as ptarmigan. According to the ‘alternative prey hypothesis’ (APH), the densities of ground-nesting birds and rodents are positively associated due to predator–prey dynamics and prey-switching. However, it remains unclear how the strength of these predator-mediated interactions change along a climatic harshness gradient in comparison with the effects of climatic variation. We built a hierarchical Bayesian model to estimate the sensitivity of ptarmigan populations to interannual variation in climate and rodent occurrence across Norway during 2007–2017. Ptarmigan abundance was positively linked with rodent occurrence, consistent with the APH. Moreover, we found that the link between ptarmigan abundance and rodent dynamics was strongest in colder regions. Our study highlights how species interactions play an important role in population dynamics of species at high latitudes and suggests that they can become even more important in the most climatically harsh regions.     

A 250-year index of first flowering dates and its response to temperature changes

Widespread concerns about global biodiversity loss have led to a growing demand for indices of biodiversity status. Today, climate change is among the most serious threats to global biodiversity. Although many studies have revealed phenological responses to climate change, no long-term community-level indices have been developed. We derived a 250-year index of first flowering dates for 405 plant species in the UK for assessing the impact of climate change on plant communities. The estimated community-level index in the most recent 25 years was 2.2–12.7 days earlier than any other consecutive 25-year period since 1760. The index was closely correlated with February–April mean Central England Temperature, with flowering 5.0 days earlier for every 1°C increase in temperature. The index was relatively sensitive to the number of species, not records per species, included in the model. Our results demonstrate how multi-species, multiple-site phenological events can be integrated to obtain indices showing trends for each species and across species. This index should play an important role in monitoring the impact of climate change on biodiversity. Furthermore, this approach can be extended to incorporate data from other taxa and countries for evaluating cross-taxa and cross-country phenological responses to climate change.     

Predicting the potential global distribution of Ageratina adenophora under current and future climate change scenarios

AimInvasive alien species (IAS) threaten ecosystems and humans worldwide, and future climate change may accelerate the expansion of IAS. Predicting the suitable areas of IAS can prevent their further expansion. Ageratina adenophora is an invasive weed over 30 countries in tropical and subtropical regions. However, the potential suitable areas of A. adenophora remain unclear along with its response to climate change. This study explored and mapped the current and future potential suitable areas of Ageratina adenophora.LocationGlobal.TaxaAsteraceae A. adenophora (Spreng.) R.M.King & H.Rob. Commonly known as Crofton weed.MethodsBased on A. adenophora occurrence data and climate data, we predicted its suitable areas of this weed under current and future (four RCPs in 2050 and 2070) by MaxEnt model. We used ArcGIS 10.4 to explore the potential suitable area distribution characteristics of this weed and the “ecospat” package in R to analyze its altitudinal distribution changes.ResultsThe area under the curve (AUC) value (>0.9) and true skill statistics (TSS) value (>0.8) indicated excelled model performance. Among environment factors, mean temperature of coldest quarter contributed most to the model. Globally, the suitable areas for A. adenophora invasion decreased under climate change scenarios, although regional increases were observed, including in six biodiversity hotspot regions. The potential suitable areas of A. adenophora under climate change would expand in regions with higher elevation (3,000–3,500 m).Main conclusionsMean temperature of coldest quarter was the most important variable influencing the potential suitable area of A. Adenophora. Under the background of a warming climate, the potential suitable area of A. adenophora will shrink globally but increase in six biodiversity hotspot regions. The potential suitable area of A. adenophora would expand at higher elevation (3,000–3,500 m) under climate change. Mountain ecosystems are of special concern as they are rich in biodiversity and sensitive to climate change, and increasing human activities provide more opportunities for IAS invasion.     

西南地区生态系统服务供需历史变化与SSP-RCP情景预测

生态系统服务的供需平衡对实现可持续发展至关重要。为了更好地了解过去气候变化和社会经济发展对生态系统服务的影响,并对未来不同气候和社会经济发展情景做出正确响应,有必要对生态系统服务的供需变化进行系统的评估和预测。研究对我国西南地区2000、2010、2015年的水源涵养、食物生产和固碳3项生态系统服务的供给和需求进行了定量的空间评估,然后基于IPCC(Intergovernmental Panel on Climate Change)提出的社会经济发展和气候变化联合情景框架,即SSP-RCP情景(Shared Socio-economic Pathways-Representative Concentration Pathways),对此3项生态系统服务在未来2035年和2050年的供给和需求进行了SSP1-RCP2.6、SSP2-RCP4.5、SSP4-RCP6.0和SSP5-RCP8.5 4个情景下的预测。结果显示,西南地区水源涵养和固碳服务的供给和需求具有显著的空间不匹配特征,且其需求从2000—2015年分别增长了11.49%和252.41%。根据SSP-RCP情景预测结果,水源...     

Integrating plant–soil interactions into global carbon cycle models

1.  Plant–soil interactions play a central role in the biogeochemical carbon (C), nitrogen (N) and hydrological cycles. In the context of global environmental change, they are important both in modulating the impact of climate change and in regulating the feedback of greenhouse gas emissions (CO₂, CH₄ and N₂O) to the climate system.
2.  Dynamic global vegetation models (DGVMs) represent the most advanced tools available to predict the impacts of global change on terrestrial ecosystem functions and to examine their feedbacks to climate change. The accurate representation of plant–soil interactions in these models is crucial to improving predictions of the effects of climate change on a global scale.
3.  In this paper, we describe the general structure of DGVMs that use plant functional types (PFTs) classifications as a means to integrate plant–soil interactions and illustrate how models have been developed to improve the simulation of: (a) soil carbon dynamics, (b) nitrogen cycling, (c) drought impacts and (d) vegetation dynamics. For each of these, we discuss some recent advances and identify knowledge gaps.
4.  We identify three ongoing challenges, requiring collaboration between the global modelling community and process ecologists. First, the need for a critical evaluation of the representation of plant–soil processes in global models; second, the need to supply and integrate knowledge into global models; third, the testing of global model simulations against large-scale multifactor experiments and data from observatory gradients.
5.   Synthesis . This paper reviews how plant–soil interactions are represented in DGVMs that use PFTs and illustrates some model developments. We also identify areas of ecological understanding and experimentation needed to reduce uncertainty in future carbon coupled climate change predictions.     

Climate alters the movement ecology of a non‐migratory bird

Global climate change is causing increased climate extremes threatening biodiversity and altering ecosystems. Climate is comprised of many variables including air temperature, barometric pressure, solar radiation, wind, relative humidity, and precipitation that interact with each other. As movement connects various aspects of an animal''s life, understanding how climate influences movement at a fine‐temporal scale will be critical to the long‐term conservation of species impacted by climate change. The sedentary nature of non‐migratory species could increase some species risk of extirpation caused by climate change. We used Northern Bobwhite (Colinus virginianus; hereafter bobwhite) as a model to better understand the relationship between climate and the movement ecology of a non‐migratory species at a fine‐temporal scale. We collected movement data on bobwhite from across western Oklahoma during 2019–2020 and paired these data with meteorological data. We analyzed movement in three different ways (probability of movement, hourly distance moved, and sinuosity) using two calculated movement metrics: hourly movement (displacement between two consecutive fixes an hour apart) and sinuosity (a form of tortuosity that determines the amount of curvature of a random search path). We used generalized linear‐mixed models to analyze probability of movement and hourly distance moved, and used linear‐mixed models to analyze sinuosity. The interaction between air temperature and solar radiation affected probability of movement and hourly distance moved. Bobwhite movement increased as air temperature increased beyond 10°C during low solar radiation. During medium and high solar radiation, bobwhite moved farther as air temperature increased until 25–30°C when hourly distance moved plateaued. Bobwhite sinuosity increased as solar radiation increased. Our results show that specific climate variables alter the fine‐scale movement of a non‐migratory species. Understanding the link between climate and movement is important to determining how climate change may impact a species’ space use and fitness now and in the future.     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.     

Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016

The Arctic Ocean is undergoing rapid transformation toward a seasonally ice‐free ecosystem. As ice‐adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food‐web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska''s SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite‐telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming.     

The future of the Amazon: new perspectives from climate, ecosystem and social sciences

The potential loss or large-scale degradation of the tropical rainforests has become one of the iconic images of the impacts of twenty-first century environmental change and may be one of our century's most profound legacies. In the Amazon region, the direct threat of deforestation and degradation is now strongly intertwined with an indirect challenge we are just beginning to understand: the possibility of substantial regional drought driven by global climate change. The Amazon region hosts more than half of the world's remaining tropical forests, and some parts have among the greatest concentrations of biodiversity found anywhere on Earth. Overall, the region is estimated to host about a quarter of all global biodiversity. It acts as one of the major 'flywheels' of global climate, transpiring water and generating clouds, affecting atmospheric circulation across continents and hemispheres, and storing substantial reserves of biomass and soil carbon. Hence, the ongoing degradation of Amazonia is a threat to local climate stability and a contributor to the global atmospheric climate change crisis. Conversely, the stabilization of Amazonian deforestation and degradation would be an opportunity for local adaptation to climate change, as well as a potential global contributor towards mitigation of climate change. However, addressing deforestation in the Amazon raises substantial challenges in policy, governance, sustainability and economic science. This paper introduces a theme issue dedicated to a multidisciplinary analysis of these challenges.