Modelling spatial distribution of critically endangered Asian elephant and Hoolock gibbon in Bangladesh forest ecosystems under a changing climate

The Asian elephant (Elephas maximus) and Hoolock gibbon (Hoolock hoolock) are two globally endangered wildlife species limited to only tropical Asian forests. In Bangladesh both species are critically endangered and distributed mainly in the northeast and southeast hilly regions bordering neighboring India and Myanmar. Using existing distribution data, land-use/land cover, elevation and bio-climatic variables, we modeled the likely distribution of Asian elephant and Hoolock gibbon in Bangladesh for 2050 and 2070. We used the IPCC's Representative Concentration Pathways (RCPs) – RCP6.0 and RCP8.5 and Maximum Entropy algorithm for our modelling. Our study indicated that the Asian elephant will be more resilient to climate change compared with the Hoolock gibbon. Habitat loss for the Asian elephant is also expected to remain constant (i.e. 38%) throughout the period, whilst Hoolock gibbon habitat will be more sensitive to climatic variations, with the species predicted to be extirpated from the country by 2070. Being highly exposed to climate change with ever increasing land use pressures, we believe our study in Bangladesh can be used to enhance our understanding of future vulnerabilities of wildlife in a rapidly changing climate. A trans-boundary conservation program with greater attention to the species that are less resilient to climate change is also essential.     

气候变化下基于物种与植物耦联机制的小白额雁(Anser erythropus)潜在生境及适宜性研究--以长江流域中下游为例

气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。     

不同气候变化情景下亚洲北山羊（Capra sibirica）的响应（英文）

目前很少见到关于气候变化影响亚洲北山羊物种栖息地的研究。通过调查气候变化对塔吉克斯坦东部亚洲北山羊(Capra sibirica)分布的影响,并采用生态位建模比较了亚洲北山羊的适宜栖息地的当前与未来分布情况。预计到2070年,现有适宜栖息地的18%(2689 km^2)将变得不适宜亚洲北山羊的生存,损失的区域主要位于研究区域的东南部和西北部地区。新的适宜栖息地可能会扩展到当前亚洲北山羊范围之外:到2070年将扩展30%(4595 km^2)的范围,这些区域与亚洲北山羊现有的分布有很强的相关性。东南部的损失与该地区当前大多数的亚洲北山羊栖息地重叠,主要出现在比研究区域海拔低得多的区域(3500–4000 m)。当同时考虑损失和收益时,亚洲北山羊可能会净扩展到新的适宜栖息地。到2070年,亚洲北山羊的平均栖息地增加量约为30%(1379 km^2),表明适宜栖息地已向北部低温栖息地转移。研究结果有助于规划气候变化情景下塔吉克斯坦东部山区对生物多样性保护的潜在影响。应该特别注意东南地区的高地山羊种群,那里的栖息地可能由于气候对山区生态系统的影响而变得不适合该物种继续生存。     

气候变化下蒙古沙拐枣(Calligonum mongolicum)适宜生境预测

蒙古沙拐枣(Calligonum mongolicum)是中国干旱、荒漠地区主要的防风固沙植物,预测该气候变化对其地理分布范围的影响,对中国荒漠化防治工作具有指导意义。采用获得的蒙古沙拐枣108个种群分布数据和22个气候环境因子数据,利用最大熵(MaxEnt)模型软件预测蒙古沙拐枣在当前、2041-2060年及2061-2080年在中国干旱区的潜在地理分布,探究气候变化对该物种分布的可能影响。结果表明:(1)影响蒙古沙拐枣分布的主要气候环境因子为年降水量、年平均气温、气温年较差、最干季降雨量以及海拔;(2)目前,蒙古沙拐枣的适宜生境面积约为5.4×10^5 km^2,高适宜生境为7×10^4 km^2,主要分布在新疆塔里木盆地、准噶尔盆地边缘地带、甘肃河西走廊及其周边、腾格里沙漠;(3)在未来气候变化的情景下,蒙古沙拐枣的适宜生境范围大幅增加,适宜生境向高纬度地区移动,高适宜生境集中分布于甘肃河西走廊以及腾格里沙漠地区,且呈带状分布。     

Potential vulnerability of Namaqualand plant diversity to anthropogenic climate change

We provide a position paper, using a brief literature review and some new modelling results for a subset of succulent plant species, which explores why Namaqualand plant diversity might be particularly vulnerable to anthropogenic climate change despite presumed species resilience under arid conditions, and therefore a globally important test-bed for adaptive conservation strategies. The Pleistocene climate-related evolutionary history of this region in particular may predispose Namaqualand (and Succulent Karoo) plant endemics to projected climate change impacts. Key Succulent Karoo plant lineages originated during cool Pleistocene times, and projected air temperatures under anthropogenic climate change are likely to exceed these significantly. Projected rainfall patterns are less certain, and projections of the future prevalence of coastal fog are lacking, but if either of these water inputs is reduced in concert with rising temperatures, this seems certain to threaten the persistence of, at least, narrow-endemic plant species. Simple modelling approaches show strong reduction in spatial extent of bioclimates typical of Namaqualand within the next five decades and that both generalist species with large geographic ranges, and narrow-range endemics may be susceptible to climate change induced loss of potential range. Persistence of endemics in micro-habitats that are buffered from extreme climate conditions cannot be discounted, though no attempts have been made to address this shortcoming of broader scale bioclimatic modelling. The few experimental data available on elevated temperature and drought tolerance suggest susceptibility of leaf succulent species, but high drought tolerance of non-succulent shrubs. Both species-level monitoring and further experimental work is essential to test and refine projections of climate change impacts on species persistence, and the implications for conservation.     

Incorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections?

Species distribution models (SDMs) are one of the most important GIScience research areas in biogeography and are the primary means by which the potential effects of climate change on species’ distributions and ranges are investigated. Dispersal is an important ecological process for species responding to changing climates, however, SDMs and their subsequent spatial products rarely reflect accessibility to any future suitable environment. Dispersal-related movement can be confounded by factors that vary across landscapes and climates, as well as within and among species, and it has therefore remained difficult to parametrise in SDMs. Here we compared 20 models that have previously been used (or have the potential to be used) to represent dispersal processes in SDM to predict future range shifts in response to climate change. We assessed the different dispersal models in terms of their accuracy at predicting future distributions, as well as the uncertainty associated with their predictions. Atlas data for 50 bird species from 1988 to 1991 in Great Britain were treated as base distributions (t₁), with the species–environment relationships extrapolated (using three commonly used statistical methods) to 2008–2011 (t₂). Dispersal (in the form of the 20 different models) was simulated from the base distribution (t₁) to 2008–2011 (t₂). The results were then combined and used to identify locations that were both abiotically suitable (obtained from the statistical methods) and accessible (obtained from the dispersal models). The accuracy of these coupled projections was assessed with the 2008–2011 atlas data (the observed t₂ distribution). There was substantial variation in the accuracy of the different dispersal models, and in general, the more restrictive dispersal models (e.g. fixed rate dispersal) resulted in lower accuracy for the metrics which reward correct prediction of presences. Ensemble models of the dispersal methods (generated by combining multiple projection outcomes) were created for each species, and a new Ensemble Agreement Index (EAI), which ranges from 0 (no agreement among models) to 1 (full agreement among models) was developed to quantify uncertainty among the projections. EAI values ranged from 0.634 (some areas of disagreement and therefore medium uncertainty among dispersal models) to 0.999 (large areas of agreement and low uncertainty among dispersal models). The results of this research highlight the importance of incorporating dispersal and also illustrate that the method with which dispersal is simulated greatly impacts the projected future distribution. This has important implications for studies aimed at predicting the effects of changing environmental conditions on species’ distributions.     

Predicting the Impact of Climate Change on Vulnerable Species in Gandaki River Basin,Central Himalayas

Gandaki River Basin (GRB) is an important part of the central Himalayan region, which provides habitat for numerous wild species. However, climatic changes are making the habitat in this basin more vulnerable. This paper aims to assess the potential impacts of climate change on the spatial distributions of habitat changes for two vulnerable species, Himalayan black bear (Ursus thibetanus laniger) and common leopard (Panthera pardus fusca), using the maximum entropy (MaxEnt) species distribution model. Species occurrence locations were used along with several bioclimatic and topographic variables (elevation, slope and aspect) to fit the model and predict the potential distributions (current and future) of the species. The results show that the highly suitable area of Himalayan black bear within the GRB currently encompasses around 1642 km² (5.01% area of the basin), which is predicted to increase by 51 km² in the future (2050). Similarly, the habitat of common leopard is estimated as 3999 km² (12.19% of the GRB area), which is likely to increase to 4806 km² in 2050. Spatially, the habitat of Himalayan black bear is predicted to increase in the eastern part (Baseri, Tatopani and north from Bhainse) and to decrease in the eastern (Somdang, Chhekampar), western (Burtibang and Bobang) and northern (Sangboche, Manang, Chhekampar) parts of the study area. Similarly, the habitat of common leopard is projected to decrease particularly in the eastern, western and southern parts of the basin, although it is estimated to be extended in the southeastern (Bhainse), western (Harichaur and northern Sandhikhark) and north-western (Sangboche) parts of the basin. To determine the habitat impact, the environmental variables such as elevation, Bio 15 (precipitation seasonality) and Bio 16 (precipitation of wettest quarter) highly contribute to habitat change of Himalayan black bear; while Bio 13 (precipitation of wettest month) and Bio 15 are the main contributors for common leopard. Overall, this study predicted that the suitable habitat areas of both species are likely to be impacted by climate change at different altitudes in the future, and these are the areas that need more attention in order to protect these species.     

北京市土地利用空间格局演化模拟及预测

土地利用空间格局的演化模拟可定量地从空间尺度揭示区域土地利用变化的驱动因素,是厘清未来时期内土地变化的重要途径。基于CLUE-S模型,以北京市为研究案例,结合1985、2000和2010年三期土地利用数据,运用Logistic逐步回归方法识别了北京市各种土地利用类型演化的驱动因素,对北京市土地利用空间格局进行模拟。在此基础上,基于北京市社会经济发展、土地利用规划、资源禀赋及生态保护等不同情景,对北京市2020年土地利用空间分布格局进行模拟及预测。结果表明：①不同的时期内,驱动因子对不同土地利用类型的影响呈现差异性,其中交通因素及社会经济因素对土地利用类型的转化率影响较显著,坡度对各个土地利用类型的影响较大。②通过对2010年北京市土地利用变化的模拟结果来看,Kappa指数为87.03%,说明预测结果与实际土地利用情况有较好的一致性。③预测结果显示,北京市的城市发展均表现为继续向外扩展,且以东南、东北为主要扩展方向,但扩张的程度存在差异。     

基于PLUS和InVEST模型的渭河流域土地利用与生境质量时空变化及预测

生境质量是关系人类福祉和实现可持续发展的重要基础,对区域生态保护和土地资源可持续利用具有重大意义。以渭河流域为研究对象,基于2000、2010年和2020年的土地利用数据,应用斑块生成土地利用变化模拟（Patch-generating land use simulation,PLUS）模型、生态系统服务和权衡的综合评估（Integrated valuation of ecosystem services and trade-offs,InVEST）模型预测并评价了土地利用与生境质量时空变化特征。结果表明：（1） 2000—2020年渭河流域建设用地和草地面积逐年增加,林地面积略微增长,耕地面积持续减少;2020—2050年土地利用变化趋势同2000—2020年基本一致但剧烈程度显著下降,建设用地扩张趋势减缓,耕地减少幅度下降,草地面积占比超过耕地跃居流域第一。（2） 2000—2020年流域内生境质量两极分化趋势明显,低生境质量和高生境质量区域面积有所增加,中等生境质量的面积减少,整体生境质量水平呈上升趋势;2020—2050年生境质量水平继续保持逐年上升趋势但增幅放缓,生境质量变化强度下降,低生境质量区域面积逐渐减少,中等生境质量面积保持稳定,高生境质量面积有所增长。研究结果可为渭河流域土地资源可持续利用和高质量发展提供相应科学依据和决策参考。     

Relative importance of climate,topography, and habitats for breeding wetland birds with different latitudinal distributions in the Czech Republic

Given species' vulnerability to climate change, land use change, and habitat loss, it is pertinent to examine how the distribution of a particular species is related to those factors. We assessed the use of climate, habitat, and topography data for modeling the distributions of 14 central European wetland birds, and compared the relative importance of these factors among bird groups with differing latitudinal distributions in Europe. We used the Third Atlas of Breeding Birds in the Czech Republic as a source of species distribution data. Variables were derived from Corine Land Cover, WorldClim, and Shuttle Radar Topography Mission (SRTM) data. Hierarchical partitioning and multiple logistic models identified climatic, topographical, and habitat predictors as important determinants of distribution for each of the species under study. However, the relative contributions of particular variables differed among the species. Climatic, topographical, and habitat factor groups also differed in their importance to latitudinal species groups. Our results indicated that wetland birds with range margins close to the Czech Republic were potentially limited by two different factors: climate conditions impact the southerly distributed species and the availability of suitable habitat affects the northerly distributed species. The accuracy of the study models varied from fair to high (the area under curve values was 0.60–0.89) and revealed negative correlations with the relative occurrence area. In this study, we propose that any difference in model performance is more attributable to data characteristics than to a species' geographical characteristics.     

Climate-induced change of environmentally defined floristic domains: A conservation based vulnerability framework

Global climate change is having marked influences on species distributions, phenology and ecosystem composition and raises questions as to the effectiveness of current conservation strategies. Conservation planning has only recently begun to adequately account for dynamic threats such as climate change. We propose a method to incorporate climate-dynamic environmental domains, identified using specific environmental correlates of floristic composition, into conservation strategies, using the province of KwaZulu-Natal, South Africa as a case study. The environmental domains offer an approach to conservation that conserves diversity under current and future climates, recognising that the species constituting diversity may change through time. We mapped current locations of domains by identifying their positions in a multi-dimensional environmental space using a non-hierarchical iterative k-means clustering algorithm. Their future locations were explored using an ensemble of future climate scenarios. The HadCM2 and GFDL2.1 models represented the extreme ranges of the models. The magnitude of change in each environmental domain was calculated using Euclidean distances to determine areas of greatest and least stability for each future climate projection. Domains occurring in the savanna biome increase at the expense of domains occurring in the grassland biome, which has significant negative consequences for the species rich grasslands. The magnitude of change maps represents areas of changed climatic conditions or edaphic disjunctions. The HadCM2 model predicted the greatest overall magnitude of change across the province. Species with specific soil requirements may not be able to track changing climatic conditions. A vulnerability framework was developed that incorporated climatic stability and habitat intactness indices. The mean magnitude of change informed the potential speed of transition of domains between the vulnerability quadrants. The framework informs appropriate conservation actions to mitigate climate change impacts on biodiversity. The study explicitly links floristic pattern and climate variability and provides useful insights to facilitate conservation planning for climate change.     

Changes in production potentials of rapeseed in the Yangtze River Basin of China under climate change: A multi-model ensemble approach

Rapeseed is one of the major oil crops in China and it is very sensitive to climate change. The Yangtze River Basin is the main rapeseed production area in China. Therefore, a better understanding of the impact of climate change on rapeseed production in the basin is of both scientific and practical importance to Chinese oil industry and food security. In this study, based on climate data from 5 General Circulation Models (GCMs) with 4 representative concentration pathways (RCPs) in 2011–2040 (2020s), 2041–2070 (2050s) and 2071–2100 (2080s), we assessed the changes in rapeseed production potential between the baseline climatology of 1981–2010 and the future climatology of the 2020s, 2050s, and 2080s, respectively. The key modelling tool – the AEZ model – was updated and validated based on the observation records of 10 representative sites in the basin. Our simulations revealed that: (1) the uncertainty of the impact of climate change on rapeseed production increases with time; (2) in the middle of this century (2050s), total rapeseed production would increase significantly; (3) the average production potential increase in the 2050s for the upper, middle and lower reaches of the Yangtze River Basin is 0.939, 1.639 and 0.339 million tons respectively; (4) areas showing most significant increases in production include southern Shaanxi, central and eastern Hubei, northern Hunan, central Anhui and eastern Jiangsu.     

Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata

Cellular automata (CA) have been widely used to simulate complex urban development processes. Previous studies indicated that vector-based cellular automata (VCA) could be applied to simulate urban land-use changes at a realistic land parcel level. Because of the complexity of VCA, these studies were conducted at small scales or did not adequately consider the highly fragmented processes of urban development. This study aims to build an effective framework called dynamic land parcel subdivision (DLPS)-VCA to accurately simulate urban land-use change processes at the land parcel level. We introduce this model in urban land-use change simulations to reasonably divide land parcels and introduce a random forest algorithm (RFA) model to explore the transition rules of urban land-use changes. Finally, we simulate the land-use changes in Shenzhen between 2009 and 2014 via the proposed DLPS-VCA model. Compared to the advanced Patch-CA and RFA-VCA models, the DLPS-VCA model achieves the highest simulation accuracy (Figure-of-Merit = 0.232), which is 32.57% and 18.97% higher respectively, and is most similar to the actual land-use scenario (similarity = 94.73%) at the pattern level. These results indicate that the DLPS-VCA model can both accurately split the land during urban land-use changes and significantly simulate urban expansion and urban land-use changes at a fine scale. Furthermore, the land-use change rules that are based on DPLS-VCA mining and the simulation results of several future urban development scenarios can act as guides for future urban planning policy formulation.     

Remotely sensed agricultural modification improves prediction of suitable habitat for a threatened lizard

The geographical distribution of a species is limited by factors such as climate, resources, disturbances and species interactions. Environmental niche models attempt to encapsulate these limits and represent them spatially but do not always incorporate disturbance factors. We constructed MaxEnt models derived from a remotely sensed vegetation classification with, and without, an agricultural modification variable. Including agricultural modification improved model performance and led to more sites with native vegetation and fewer sites with exotic or degraded native vegetation being predicted suitable for A. parapulchella. Analysis of a relatively well-surveyed sub-area indicated that including agricultural modification led to slightly higher omission rates but markedly fewer likely false positives. Expert assessment of the model based on mapped habitat also suggested that including agricultural modification improved predictions. We estimate that agricultural modification has led to the destruction or decline of approximately 30–35% of the most suitable habitat in the sub-area studied and approximately 20–25% of suitable habitat across the entire study area, located in the Australian Capital Territory, Australia. Environmental niche models for a range of species, particularly habitat specialists, are likely to benefit from incorporating agricultural modification. Our findings are therefore relevant to threatened species planning and management, particularly at finer spatial scales.     

Northward-shift of temperature zones in China’s eco-geographical study under future climate scenario

Despite the well-documented effects of global climate change on terrestrial species’ ranges, eco-geographical regions as the regional scale of ecosystems have been poorly studied especially in China with diverse climate and ecosystems. Here we analyse the shift of temperature zones in eco-geographical study over China using projected future climate scenario. Projected climate data with high resolution during 1961–2080 were simulated using regional climate model of PRECIS. The number of days with mean daily temperature above 10℃ and the mean temperature of January are usually regarded as the principal criteria to indicate temperature zones, which are sensitive to climate change. Shifts due to future climate change were calculated by comparing the latitude of grid cells for the future borderline of one temperature zone with that for baseline period (1961–1990). Results indicated that the ranges of Tropical, Subtropical, Warm Temperate and Plateau Temperate Zones would be enlarged and the ranges of Cold Temperate, Temperate and Plateau Sub-cold Zones would be reduced. Cold Temperate Zone would probably disappear at late this century. North borderlines of temperature zones would shift northward under projected future climate change, especially in East China. Farthest shifts of the north boundaries of Plateau Temperate, Subtropical and Warm Temperate Zones would be 3.1°, 5.3° and 6.6° latitude respectively. Moreover, northward shift would be more notably in northern China as future temperature increased.     

未来气候情景下中国生态地理区域系统温度带的北移(英文)

Despite the well-documented effects of global climate change on terrestrial species' ranges,eco-geographical regions as the regional scale of ecosystems have been poorly studied especially in China with diverse climate and ecosystems.Here we analyse the shift of temperature zones in eco-geographical study over China using projected future climate scenario.Projected climate data with high resolution during 1961-2080 were simulated using regional climate model of PRECIS.The number of days with mean daily temperature above 10℃ and the mean temperature of January are usually regarded as the principal criteria to indicate temperature zones,which are sensitive to climate change.Shifts due to future climate change were calculated by comparing the latitude of grid cells for the future borderline of one temperature zone with that for baseline period(1961-1990).Results indicated that the ranges of Tropical,Subtropical,Warm Temperate and Plateau Temperate Zones would be enlarged and the ranges of Cold Temperate,Temperate and Plateau Sub-cold Zones would be reduced.Cold Temperate Zone would probably disappear at late this century.North borderlines of temperature zones would shift northward under projected future climate change,especially in East China.Farthest shifts of the north boundaries of Plateau Temperate,Subtropical and Warm Temperate Zones would be 3.1°,5.3° and 6.6° latitude respectively.Moreover,northward shift would be more notably in northern China as future temperature increased.     

2000-2025年环境保护政策情景下中国陆地碳储量估算

政策总是通过对土地利用/土地覆被的强烈影响而影响陆地碳平衡。本研究旨在探讨环境保护政策（主要是退耕还林）政策对我国陆地碳平衡的影响,从而为政府部门等相关政策制定者提供环境保护和应对气候变化的决策支持。利用DLS（Dynamics Land System）模型对2000-2025年环境保护政策情景下的土地利用变化模拟结果和前人对碳密度的研究成果,运用碳密度法估算了该政策情景对中国陆地碳储量的影响。研究结果表明,在整个阶段,林地将增加23%,耕地和草地将分别减少37%和11%,由此会引起我国森林碳储量每年增加66.0 Tg C,土壤碳储量每年增加13.3 Tg C,而草地碳储量则每年减少5.7 Tg C。总体而言,在环境保护政策情景下,2000-2025年中国整个陆地生态系统的碳储量将增加1.8 Pg C,年均增加量为0.074 Pg C,而这种变化89.6%的原因源于森林碳储量的增加。     

基于FLUS-InVEST模型的中国未来土地利用变化及其对碳储量影响的模拟

基于代表性浓度路径情景（Representative Concentration Pathways, RCPs）,耦合FLUS-InVEST（Future Land Use Simulation-Integrated Valuation of Ecosystem Services and Trade-offs, FLUS-InVEST）模型,以土地利用视角模拟了中国2100年的陆地生态系统碳储量,探讨其空间分异。结果表明：1）历史土地利用变化作用下,中国生态系统碳储量减少中心由华北地区转向东北地区,增加中心由西北地区转向西南地区;碳储量的减少由林地生态系统转向草地生态系统。2）未来RCPs情景下,中国林地生态系统碳储量都将持续增加,草地生态系统碳储量持续减少。RCP 6.0情景下,中国林地面积将增加9.43%左右,草地面积减少5.42%,全国林地碳储量较2010年增加2 332.64 Tg,而草地碳储量将损失1 719.03 Tg。在RCP 8.5情景下,全国林地面积增加5.15%,草地面积将减少5.10%,林地碳储量较2010年将增加1 754.59 Tg,草地碳储量将损失2 468.80 Tg。3）RCP 6.0情景对未来碳汇贡献度较RCP 8.5情景大。在RCP 6.0情景下,植被地上碳储量和表层土壤碳储量分别净增加127.12和83.67 Tg。但在RCP 8.5情景下,植被地上碳储量和表层土壤碳储量分别净减少24.67和32.41 Tg。4）不同RCPs情景下,碳储量增长均集中在横断山-秦岭-太行山-大兴安岭和雪峰山-太行山-大兴安岭两带;减少区域主要分布于云贵高原、四川盆地和京津冀地区。     

基于DLS模型的城市土地政策生态效应研究——以深圳市为例

以快速城市化典型地区——深圳市为例,结合土地利用变化与生态质量评价模型对城市土地利用的数量控制和空间控制两类生态政策的生态效应进行了评估。结果表明：(1) 在城市化发展过程中,由于城市用地扩张,城市生境面临破碎化增加、连通性降低、生境质量下降等生态风险,生态政策的实施可以在一定程度上缓解上述生态风险。(2) 数量控制的生态政策可以提高土地利用的集约性,遏制景观破碎化和生境质量下降趋势和增强景观连通性,但可能造成城市开发强度上升,对城市用地周边生态环境产生影响。(3) 空间控制的生态政策可以维护生态用地格局,遏制景观破碎化和生境质量下降趋势,但在维护景观连通性方面作用有限。(4) 两种政策同时使用会产生协同效应,其效果优于单独使用两种政策。     

利用MaxEnt研究印度中部秃鹫栖息地适宜性及气候变化的影响

秃鹫提供了宝贵的生态系统服务,在生态系统平衡中发挥着重要作用,但印度本土秃鹫数量在过去几年有所下降。掌握秃鹫栖息地的分布现状对于管理和防止秃鹫数量继续下降至关重要。可以预见,目前的气候危机可能会进一步导致秃鹫生境适宜性的变化,并影响现存的秃鹫种群。因此,本研究利用物种分布模型,对印度中部一个秃鹫栖息地的短期和长期变化进行预测,并以统计和图形的方式呈现数据。选择MaxEnt软件进行预测,是因为它与其他模型相比具有一定的优势,如只使用现有数据,在数据不完整、样本量小、样本间隙小等情况下表现良好。采用全球气候模式集成学习算法(CCSM4、Had GEM2AO和MIROC5)以获得更好的预测结果。14个稳健模型(AUC 0.864–0.892)是利用7个秃鹫种群(长喙、白臀、红头、银灰色、埃及秃鹫、喜马拉雅和欧亚狮鹫)在两个季节共1000多个地点的数据建立的。选定的气候(温度和降水)和环境变量(NDVI、海拔和土地利用/土地覆盖)被用于预测当前栖息地,未来的预测只基于气候变量。影响秃鹫栖息地分布的最重要变量是降水量(bio 15,bio 18,bio19)和温度(bio 3,bio 5)。在目前的预测中,森林和水体是影响土地利用的主要因素。在较小尺度上,随着时间的推移,极端适宜的栖息地面积减少,高度适宜的栖息地面积增加,总适宜栖息地面积在2050年略有增加,但到2070年有所减少。在更大的尺度上考虑,2050年适宜栖息地的净损失为5%,2070年为7.17%(RCP4.5)。相似的,在RCP8.5下,2050年适宜栖息地的净损失为6%,2070年为7.3%。研究结果可用于制定秃鹫的保护规划和管理,从而保护其免受未来的气候变化等威胁。