Evaluating models to assess the distribution of Buxus balearica in southern Spain

Question: Which is the best model to predict the habitat distribution of Buxus balearica Lam. in southern Spain? Location: Málaga and Granada, Spain, across an area of 38 180 km². Methods: Prediction models based on 17 environmental variables were tested. Six methods were compared: multivariate adaptive regression spline (MARS), maximum entropy approach to modelling species' distributions (Maxent), two generic algorithms based on environmental metrics dissimilarity (BIOCLIM and DOMAIN), Genetic Algorithm for Rule‐set Prediction (GARP), and supervised learning methods based on generalized linear classifiers (support vector machines, SVMs). To test the predictive power of the models we used the Kappa index. Results: Maxent most accurately predicted the habitat distribution of B. balearica, followed by MARS models. The other models tested yielded lower accuracy values. A comparison of the predictive power of the models revealed that climate variables made the highest contributions among the environmental variables studied. The variables that made the lowest contributions were the insolation models. To examine the sensitivity of the models to a reduction in the number of variables, a test showed that accuracy of over 0.90 was maintained by applying just three climatic variables (spring rainfall, mean temperature of the warmest month, and mean temperature of the coldest month). Maps derived from the algorithms of all models tested coincided well with the known distribution of the species. Conclusions: Model habitat prediction is a preliminary step towards highlighting areas of high habitat suitability of B. balearica. These data support the results of previous research, which show that MaxEnt is the best technique for modelling species distributions with small sample sizes.     

气候变化背景下紫楠在中国的适宜分布区模拟

为了解气候对紫楠(Phoebe sheareri)分布的影响,应用Maxent和GARP模型模拟了紫楠在当前气候下的中国适宜分布区,分析了影响其分布的主要环境因子,并预测了未来气候情境下其分布区的变化。结果表明,紫楠适宜分布在长江中下游及以南的各省区。影响紫楠分布的主要环境因子有年降雨量、最干季均温、降雨的季节性、相对湿度和6-8月的日照时数,这5个因子的累积贡献率达84.3%。在未来气候情境下,广东、云南、广西和海南等地区的适生区面积会显著锐减,而陕西中部、河南南部、安徽东部和江苏北部适生区面积会大幅度增加。因此,在未来气候变化背景下,紫楠的适宜分布区有向北扩张的趋势。     

Weather, not climate, defines distributions of vagile bird species

Background

Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species.

Methodology

We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed “weather” models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950–2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables.

Conclusions

Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species'' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions.     

Predicting the in-between: Present and future habitat suitability of an intertidal euryhaline fish

New World mangrove trees are foundation species, and their range is predicted to expand northward with climate change. Foundation species are commonly prioritized for conservation, with the goal of preserving the entire community that depends on them. However, no studies have explicitly investigated whether mangrove-dependent species' ranges will track the northward expansion of New World mangrove forests. We use the mangrove rivulus fish, Kryptolebias marmoratus, to investigate shifts in habitat suitability in response to various climate change scenarios (Representative Concentration Pathways 2.6, 4.5, 6.0, and 8.5). Niche models for coastal species focus on traditional climatic variables (e.g., precipitation, temperature) even though coastal habitats also are directly influenced by marine variables (e.g., sea surface salinity). We employ a novel data integration method that combines marine and climatic variables, and that accounts for model selection uncertainty using model averaging to provide robust estimates of habitat suitability. Contrary to expectation, suitability of rivulus habitat is predicted to increase in the south and decrease or remain unchanged in the north across all climate change scenarios. Thus, rivulus might experience range contraction, not expansion. Habitat became more suitable with increased salinity of the saltiest month and precipitation of the driest quarter. In laboratory settings, rivulus have higher survival, reproductive success, and growth rates in low salinities. This discrepancy suggests that some combination of the responses of rivulus and its competitors to environmental change will restrict rivulus to habitats that laboratory experiments consider suboptimal. Our models suggest that focusing conservation decisions on foundation species could overestimate habitat availability and resilience of affiliated communities while simultaneously underestimating species declines and extinction risks.     

Predicting potential distribution of chestnut phylloxerid (Hemiptera: Phylloxeridae) based on GARP and Maxent ecological niche models

The chestnut phylloxerid, Moritziella castaneivora, has been recently recorded as a forest pest in China. It heavily damaged chestnut trees and has caused serious economic losses in some main chestnut production areas. In order to effectively monitor and manage this pest, it is necessary to investigate its potential geographical distribution worldwide. In this study, we used two ecological niche models, Genetic Algorithm for Rule‐set Production (GARP) and Maximum Entropy (Maxent), along with the geographical distribution of the host plants, Japanese chestnut (Castanea crenata) and Chinese chestnut (Castanea mollissima), to predict the potential geographical distribution of M. castaneivora. The results suggested that the suitable distribution areas based on GARP were general consistent with those based on Maxent, but GARP predicted distribution areas that extended more in size than did Maxent. The results also indicated that the suitable areas for chestnut phylloxerid infestations were mainly restricted to Northeast China (northern Liaoning), East China (southern Shandong, northern Jiangsu and western Anhui), North China (southern Hebei, Beijing and Tianjin), Central China (eastern Hubei and southern Henan), Japan (Kinki, Shikoku and Tohoku) and most parts of the Korean Peninsula. In addition, some provinces of central and western China were predicted to have low suitability or unsuitable areas (e.g. Xinjiang, Qinghai and Tibet). A jackknife test in Maxent showed that the average precipitation in July was the most important environmental variable affecting the distribution of this pest species. Consequently, the study suggests several reasonable regulations and management strategies for avoiding the introduction or invasion of this high‐risk chestnut pest to these potentially suitable areas.     

Potential distribution of vulnerable Entandrophragma angolense (Welw.) C. DC. (Meliaceae) in East Africa

The various human‐induced threats imposed on nature have recently triggered the study of species' distributions. We developed potential suitability models using two algorithms for a threatened African mahogany, Entandrophragma angolense, in three East African countries; Kenya, Tanzania and Uganda. The effect of features selection and modelling algorithm selection on potential suitability predictions was explored. Occurrence records and high‐resolution environmental data were used. The two species distribution modelling techniques were genetic algorithm rule for prediction; and maximum entropy modelling. With Maxent, the area under the receiver characteristic operating curve (AUC) for potential distribution models tested on independent data ranged from 0.942 to 0.972 when using automatic features and from 0.974 to 0.666 with target or specific features. With GARP, AUC for potential distribution models ranged from 0.591 to 0.736 with all rule types and from 0.388 to 0.805 for specific rule types (Tables  1  and 2 ). The area under the E. angolense potential suitability was best predicted by soil, rainfall and aspect using GARP. Potential suitability increased with increasing aspect and decreased with increasing slope. Low rainfall and elevation increased potential suitability, while high levels of either variable decreased potential suitability. Potential suitability maps for vulnerable species require using a multi‐algorithm, fine scale data approach and incorporation of environmental variables like soil, slope, land use and elevation. Species distribution models can offer insight on the distribution requirements of vulnerable species and help guide the development of management plans. Results of this study suggest that E. angolense management plans should promote the protection of terrestrial forests surrounding water bodies including Mabira forest in Uganda.     

Habitat suitability of Gymnocladus assamicus - A critically endangered plant of Arunachal Pradesh,India using machine learning and statistical modeling

The present study sought to identify the potential distribution range of critically endangered Gymnocladus assamicus in Arunachal Pradesh based on published data and field collection. We used the Maxent model to estimate the range of distribution and the result was then compared with three other models, i.e., the Generalized Linear Model (GLM), the Bioclim and the Random Forest model to assess the species' habitat suitability. A total of 23 different environmental variables were used, including bioclimatic ones, monthly minimum and maximum temperature, monthly precipitation and elevation data. The Maxent output listed 12 variables explaining 99.9% variation in the model. In comparison, Maxent showed the maximum region under habitat suitability criteria (1884.48 km²), followed by Random Forest (70.73 km²) and Bioclim (11.62 km²) model. Except for the Maxent model, suitable habitats predicted by other models are highly restricted within and across the study species' current distribution range. The average model prediction shows an expanded distribution range for the species up to Tawang which is the closest district of currently known distribution of the species in the state. Thus, the present study recognizes the importance of the geographic range of G. assamicus, a critically endangered species with very limited spatial distribution range and also provides some specific details to explore possible habitats for the species in new areas of potential occurrence in Arunachal Pradesh, India.     

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range‐wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back‐cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long‐term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long‐term demographic decline and range contraction for a species of high‐conservation concern. Range‐wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal‐limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management.     

气候变化对祁连山蒙古扁桃潜在适生区的影响

气候变化将改变物种的生存环境，影响其分布范围，甚至威胁到某些物种的生存。本文通过ArcGIS软件和最大熵(MaxEnt)模型模拟蒙古扁桃(Amygdalus mongolica)在祁连山当前(1970—2000年)和未来(2081—2100年)2个气候时期背景下的地理分布格局，并分析其主要的环境影响因素。结果表明：(1)在当前气候条件下，蒙古扁桃在祁连山的东南部有较好的适生性；(2)未来4种气候情景下(SSP126,SSP245,SSP245和SSP585),蒙古扁桃在祁连山南部及东南部的适生区有消失的风险，扩张区主要集中在祁连山中北部的国家公园附近；(3)蒙古扁桃的分布格局主要向祁连山北部和高纬度地区迁移；(4)最湿月降水量(Bio13)、坡度(Slope)、最冷季度均温(Bio11)和最热月最高温(Bio5)的累计贡献率达到了80%以上，是影响蒙古扁桃适生分布的主要因子。本研究模拟、分析、预测了当前和未来不同情景下蒙古扁桃在祁连山的潜在分布及其变化，为祁连山生态及物种多样性的保护提供科学依据。     

A MaxEnt modelling approach to understand the climate change effects on the distributional range of White-bellied Sholakili Sholicola albiventris (Blanford, 1868) in the Western Ghats,India

Each species is uniquely influenced by anthropogenic climate change. Change in temperature and precipitation due to climate change may lead to species adaptation or extinction, or in some cases, a range shift. To know the influence of climate change on a restricted and endemic bird species of the Western Ghats (WG), White-bellied Sholakili (WBS) Sholicola albiventris (Blanford, 1868), we conducted a study by using species distribution modelling. We considered 73 spatial bias-corrected occurrence points of WBS along with environmental variables like the mean temperature of coldest quarter (Bio 11), precipitation of driest month (Bio 14) and mean precipitation of warmest quarter (Bio 18). We used the MaxEnt application with ENM evaluate tool in R statistical package for developing a climate model for WBS. Bio 11 was observed to be the most crucial climate variable shaping the habitat of WBS. The current study predicts that only 2823km² in WG is suitable for WBS. One-third of this area falls under the protected area network, of which 52% is becoming unsuitable to this narrow endemic due to climate warming. The model also predicts 26% to 45% habitat loss under different climate change scenarios by the 2050s.     

Environmental suitability of new reported localities of the funnelweb spider Macrothele calpeiana: an assessment using potential distribution modelling with presence‐only techniques

Aim The funnelweb spider Macrothele calpeiana is endemic to the southern half of the Iberian Peninsula, but recent occurrence records from localities in Spain, North Africa and other regions of Europe, which are distant from its native populations, suggest human‐mediated dispersal, probably associated with the commercial export of olive trees. The main goal of this study was to assess the environmental suitability of these new records and to discuss the spider’s potential to become an invasive species, mainly in new regions across Central Europe and the Mediterranean Basin. Location Central Europe, Mediterranean Basin. Methods Using presence points from the Iberian native populations of M. calpeiana and a set of climatic variables, four presence‐only algorithms (BIOCLIM, DOMAIN, GARP and Maxent) were applied to model the potential distribution of the spider. The models were transferred to Central Europe and the Mediterranean Basin, and the locations of the new records in both the occupied and potential environmental spaces were screened. Results The four models were generally congruent in predicting the existence of a suitable climate for the species across the Mediterranean Basin, although BIOCLIM and DOMAIN yielded more constrained predictions than GARP and Maxent. Whereas the new records from Central Europe were located far from the occupied and potential climatic spaces, those from the Iberian Peninsula were not. Main conclusions Climatic suitability together with propagule pressure owing to human activities will certainly enhance the opportunities for M. calpeiana to colonize new areas across the Mediterranean Basin. The species has invaded areas beyond its native range, and those new locations located in the Iberian Peninsula and North Africa show environmental suitability for the spider and deserve long‐term monitoring. Although the new locations in Central Europe were not predicted by the climate models and the persistence of the species seems improbable, the possibility of rapid evolution or phenotypic plasticity processes raises the need for caution over the possibility of a future spread of M. calpeiana across Europe. Stronger controls over the transport of trees must be applied, and further studies on the ecology of the spider are imperative to assess the possible impact on the invaded ecosystems.     

Using ecological niche modelling to evaluate niche stability in deep time

Aim To investigate relative niche stability in species responses to various types of environmental pressure (biotic and abiotic) on geological time‐scales using the fossil record. Location The case study focuses on Late Ordovician articulate brachiopods of the Cincinnati Arch in eastern North America. Methods Species niches were modelled for a suite of fossil brachiopod species based on five environmental variables inferred from sedimentary parameters using GARP and Maxent . Niche stability was assessed by comparison of (1) the degree of overlap of species distribution models developed for a time‐slice and those generated by projecting niche models of the previous time‐slice onto environmental layers of a second time‐slice using GARP and Maxent , (2) Schoener’s D statistic, and (3) the similarity of the contribution of each environmental parameter within Maxent niche models between adjacent time‐slices. Results Late Ordovician brachiopod species conserved their niches with high fidelity during intervals of gradual environmental change but responded to inter‐basinal species invasions through niche evolution. Both native and invasive species exhibited similar levels of niche evolution in the invasion and post‐invasion intervals. Niche evolution was related mostly to decreased variance within the former ecological niche parameters rather than to shifts to new ecospace. Main conclusions Although the species examined exhibited morphological stasis during the study interval, high levels of niche conservatism were observed only during intervals of gradual environmental change. Rapid environmental change, notably inter‐basinal species invasions, resulted in high levels of niche evolution among the focal taxa. Both native and invasive species responded with similar levels of niche evolution during the invasion interval and subsequent environmental reorganization. The assumption of complete niche conservatism frequently employed in ecological niche modelling (ENM) analyses to forecast or hindcast species geographical distributions is more likely to be accurate for climate change studies than for invasive species analyses over geological time‐scales.     

Modeling impacts of climate change on the geographic distribution of medicinal plant Fritillaria cirrhosa D. Don

Fritillaria cirrhosa D. Don is a renowned traditional Chinese medicine plant that is mainly distributed in the southeastern margin of the Qinghai–Tibet Plateau. The overexploitation in the recent years has led to a sharp decline of this undomesticated resource. Analyzing the impact of climate change on the geographic distribution of F. cirrhosa is meaningful for its conservation and domestication. In this study, the maximum entropy model (Maxent) was used to simulate the distribution of F. cirrhosa in relation to the current and future climatic conditions. The maximum temperature of the warmest month (Bio 5) and the precipitation of the warmest quarter (Bio 18) were the two most important bioclimatic variables determining the distribution of F. cirrhosa. Based on the predicted level of climatic warming, a further reduction of the geographic distribution of F. cirrhosa is to be expected. This study demonstrated the necessity and urgency of establishing more effective ways to protect the natural F. cirrhosa resources and developing artificial cultivation methodology.     

Macro‐ and microclimatic interactions can drive variation in species' habitat associations

Many species are more restricted in their habitat associations at the leading edges of their range margins, but some species have broadened their habitat associations in these regions during recent climate change. We examine the effects of multiple, interacting climatic variables on spatial and temporal patterns of species' habitat associations, using the speckled wood butterfly, Pararge aegeria, in Britain, as our model taxon. Our analyses reveal that this species, traditionally regarded as a woodland‐dependent insect, is less restricted to woodland in regions with warmer winters and warmer and wetter summers. In addition, over the past 40 years of climate change, the species has become less restricted to woodland in locations where temperature and summer rainfall have increased most. We show that these patterns arise mechanistically because larval growth rates are slower in open (i.e. nonwoodland) habitats associated with colder microclimates in winter and greater host plant desiccation in summer. We conclude that macro‐ and microclimatic interactions drive variation in species' habitat associations, which for our study species resulted predominantly in a widening of habitat associations under climate change. However, species vary in their climatic and nonclimatic requirements, and so complex spatial and temporal patterns of changes in habitat associations are likely to be observed in future as the climate changes.     

全球气候变化下贵州省青冈林的潜在生境动态

为了解贵州省青冈林在全球气候变化下的潜在分布特征,基于现状分布数据,结合当前气候数据和未来气候变化情景(RCP8.5情景,2070-2099年)构建Maxent潜在分布模型,预测贵州省青冈林的潜在分布变化。结果表明,最冷季均温(bio11)、最冷月最低温度(bio6)和年均降水量(bio12)为控制贵州省青冈林潜在生境的主导气候因子;RCP8.5情景下贵州省青冈林的潜在分布面积相较当前气候条件增加,中度适宜生境增加19 419 km2,高度适宜生境增加9 944 km2;中度适宜生境平均海拔较当前气候条件上升126 m,高度适宜生境平均上升85 m。总的来说,贵州省青冈林对全球气候变化的响应不十分敏感。     

Projecting marine species range shifts from only temperature can mask climate vulnerability

Climate change is causing range shifts in many marine species, with implications for biodiversity and fisheries. Previous research has mainly focused on how species' ranges will respond to changing ocean temperatures, without accounting for other environmental covariates that could affect future distribution patterns. Here, we integrate habitat suitability modeling approaches, a high‐resolution global climate model projection, and detailed fishery‐independent and ‐dependent faunal datasets from one of the most extensively monitored marine ecosystems—the U.S. Northeast Shelf. We project the responses of 125 species in this region to climate‐driven changes in multiple oceanographic factors (e.g., ocean temperature, salinity, sea surface height) and seabed characteristics (i.e., rugosity and depth). Comparing model outputs based on ocean temperature and seabed characteristics to those that also incorporated salinity and sea surface height (proxies for primary productivity and ocean circulation features), we explored how an emphasis on ocean temperature in projecting species' range shifts can impact assessments of species' climate vulnerability. We found that multifactor habitat suitability models performed better in explaining and predicting species historical distribution patterns than temperature‐based models. We also found that multifactor models provided more concerning assessments of species' future distribution patterns than temperature‐based models, projecting that species' ranges will largely shift northward and become more contracted and fragmented over time. Our results suggest that using ocean temperature as a primary determinant of range shifts can significantly alter projections, masking species' climate vulnerability, and potentially forestalling proactive management.     

气候变化下栓皮栎潜在地理分布格局及其主导气候因子

栓皮栎(Quercus variabilis)是东亚天然分布最广泛的树种之一。利用最大熵(Maxent)模型对现实气候条件下栓皮栎在东亚地区的潜在分布及其分布的主导气候因子进行分析,同时结合全新世中期(6000年前)和未来气候(2050年)来模拟和预测气候变化背景下栓皮栎潜在分布格局的变化。结果表明:现实气候条件下东亚栓皮栎适生区(适宜生境和低适宜生境)面积占总研究区面积的21.88%,主要集中在东亚南部区域,在我国北起陕西中部、山西和河北南部边缘、山东,西起甘肃东部边缘、四川中东部、云南、西藏东部边缘,一直到东部沿海区域,同时在朝鲜半岛南部和日本中南部也有分布,其中适宜生境面积占研究区总面积的5.69%,主要集中在秦岭山脉、大巴山脉、伏牛山、云南的云贵高原、罗霄山脉、南岭山脉、武夷山和台湾岛;气候变化情景下,栓皮栎的适生区分布面积变化较小,但其适宜生境的分布范围却发生了较大的变化,随着全球气候的波动性变化,适宜生境分布范围逐渐向西部秦岭山脉、大巴山脉、四川、重庆和云贵高原等区域集中,并使该分布中心的适宜生境面积逐渐扩大;影响栓皮栎分布的主要气候因子为最冷月的最低气温(Bio6)、最冷季平均气温(Bio11)和年降水量(Bio12),三者的贡献率分别为48.6%、21.4%和14.2%。     

基于生态位模型的艾比湖鹅喉羚生境评价

明确物种生境空间分布格局及其与环境因素的关系,对了解该物种的生境需求和适宜生境空间分布至关重要。生境评价和预测是对物种进行有效保护的基础。以鹅喉羚(Gazella subgutturosa)为研究对象,以其重要栖息地新疆博州艾比湖国家级湿地自然保护区为研究区域,选取115个鹅喉羚分布点数据和23个环境变量因子,应用MAXENT模型分析其生境空间分布及主要影响因子,划分了鹅喉羚在研究区域的适宜生境,并对它的栖息地特征进行了分析。探讨了鹅猴羚生境选择与环境因子的关系。结果表明:气温日较差是影响鹅喉羚生境分布的主要环境因子。植被类型,坡度和最干月降水量对艾比湖鹅喉羚的生境选择影响不大。除了温度和降水在内的19项生物气候变量是鹅猴羚选择生境的重要因素之外,海拔和坡向等地形特征也影响鹅猴羚的生境选择性。鹅喉羚的高度适宜生境区主要分布在研究区域的北部和东部,中度及低度适宜生境区则分布于高度适宜生境区的边缘,而非适宜生境区主要集中在西部地区。研究不仅提供了鹅喉羚在艾比湖的实际分布状况及其栖息地特征,也为鹅喉羚在栖息地方面的研究,即鹅猴羚的栖息地选择和环境因子的关系方面提供了一个重要的依据。     

Species Distribution Modelling predicts habitat suitability and reduction of suitable habitat under future climatic scenario for Sclerophrys perreti: A critically endangered Nigerian endemic toad

Sclerophrys perreti is a critically endangered Nigerian native frog currently imperilled by human activities. A better understanding of its potential distribution and habitat suitability will aid in conservation; however, such knowledge is limited for S. perreti. Herein, we used a species distribution model (SDM) approach with all known occurrence data (n = 22) from our field surveys and primary literature, and environmental variable predictors (19 bioclimatic variables, elevation and land cover) to elucidate habitat suitability and impact of climate change on this species. The SDM showed that temperature and precipitation were the predictors of habitat suitability for S. perreti with precipitation seasonality as the strongest predictor of habitat suitability. The following variable also had a significant effect on habitat suitability: temperature seasonality, temperature annual range, precipitation of driest month, mean temperature of wettest quarter and isothermality. The model predicted current suitable habitat for S. perreti covering an area of 1,115 km². However, this habitat is predicted to experience 60% reduction by 2050 owing to changes in temperature and precipitation. SDM also showed that suitable habitat exists in south-eastern range of the inselberg with predicted low impact of climate change compared to other ranges. Therefore, this study recommends improved conservation measures through collaborations and stakeholder's meeting with local farmers for the management and protection of S. perreti.     

气候变化对黄土高原及邻近地区稀有种枯蝉分布的潜在影响(英文)

【目的】未来数十年的气候变化预计会是造成很多物种生境丧失的一个重要因素。对适应能力相对脆弱的地方性物种,预测气候变化对其生境的影响将对生物多样性保护具有重要意义。【方法】本文基于最大熵模型,对珍稀蝉科中国特有种枯蝉Subpsaltria yangi在当前和未来气候条件下的生境适宜度进行了评估。【结果】结果表明,枯蝉主要局限分布于黄土高原及邻近地区。预计至2050年,即使在温和的气候变化情景下,枯蝉的生境面积也会明显减少。影响枯蝉栖息地分布的关键因素为年平均气温、最冷月的最低气温、最冷季的平均气温和最潮湿月份的降水量。枯蝉现存种群栖息地应当受到保护,甘肃天水和陕西延安地区应作为枯蝉分布的核心区予以保护,以应对气候变化对其生境带来的影响。【结论】本研究获得的枯蝉适宜生境分布图可以为该稀有物种的新种群发现、现生种群分布地土地规划管理以及有效的自然保护区设立提供重要信息。