Estimating the population size of an endangered shorebird, the Madagascar plover, using a habitat suitability model

The Madagascar plover Charadrius thoracicus is a shorebird endemic to western Madagascar, currently classified as globally vulnerable. It is restricted to specialized wetland habitats that are increasingly threatened by humans. To inform future conservation measures for this poorly known species, we develop a predictive habitat suitability map and use this map to estimate the size of the Madagascar plover population. We integrate spatially referenced presence-only observations of Madagascar plovers with Landsat data, elevation data and measures of distance to settlements and the coast to produce a habitat suitability model using ecological niche factor analysis. Validation of this model using a receiver operating characteristic plot suggests that it is at least 84% accurate in predicting suitable sites. We then use our estimate of total area of suitable habitat above a critical suitability threshold and data on Madagascar plover density in suitable sites to estimate the total population size to derive a total population estimate of 3100±396 standard error individuals. Finally, we explore the conservation applications of our model.     

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.     

基于生境适宜性指数模型的俚岛海黍子生境层级分布

为了深入了解海黍子生境,利用模型对山东俚岛海黍子生境进行适宜性分析,分别选取温度、盐度、水深、浊度、底质、无机氮浓度、磷酸盐浓度和距海藻床距离8种环境因子,通过层次分析法赋值因子权重,结合空间分析方法建立了海黍子HSI模型.利用该模型对山东俚岛近岸海域2018年春、秋两季的环境因子调查结果进行了海黍子生境分析.结果 表...     

印度野牛在中国的分布及其栖息地适宜性分析

印度野牛(Bos gaurus)在中国分布在云南省南部和西藏藏南地区。2016年2-3月和2016年11-12月, 我们在西双版纳州、普洱市及高黎贡山区域开展印度野牛调查, 并对藏南地区进行文献调研, 共获得47处印度野牛有效出现位点数据。目前云南地区印度野牛种群数量约180-210头, 面临着严重的生存危机; 在高黎贡山未发现印度野牛。利用印度野牛分布位点数据, 选取地形、土地覆被类型、人类足迹指数、距水源和道路距离以及气候共5类14种因子作为自变量建立MaxEnt生态位模型, 通过模拟云南和西藏印度野牛的适宜分布区, 分析各环境因子对该物种分布的影响。结果表明: 模型预测精度较高, 平均AUC (area under the curve)值为0.994。印度野牛潜在适宜栖息地可划分为高适宜、次适宜、低适宜和不适宜4个等级。高适宜栖息地主要分布在云南省西双版纳和藏南地区, 其中西双版纳部分镶嵌有次适宜和低适宜栖息地斑块, 面积为4,987 km²; 藏南部分高适宜栖息地面积为13,995 km²。次适宜栖息地主要分布于云南省南部、高黎贡山区域以及藏南高适宜栖息地区的边缘, 总面积为32,778 km²。低适宜和不适宜栖息地区连接成片, 位于云南省中部、北部地区和藏南地区北部。Jackknife检验结果显示, 季节温度变化和等温线对印度野牛潜在分布区的影响较大, 而地形因子和降水变化的影响较弱。遥感地物分类结果表明: 橡胶林等人工经济林的种植占据了西双版纳野牛的适宜栖息地, 降低了景观连接度。建议管理部门加大对天然林的保护力度, 控制橡胶林等人工林在野牛适宜栖息地的扩张, 提高景观连接度, 以促进该物种种群的恢复。     

Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change

Testing climatic niche divergence and modeling habitat suitability under conditions of climate change are important for developing strategies to limit the introduction and expansion of alien invasive weeds (AIWs) and providing important ecological and evolutionary insights. We assessed climatic niches in both native and invasive ranges as well as habitat suitability under climate change for eight representative Chinese AIWs from the American continent. We used climatic variables associated with occurrence records and developed ecological niche models with Maxent. Interestingly, the climatic niches of all eight AIWs diverged significantly between the native and invasive ranges (the American continent and China). Furthermore, the AIWs showed larger climatic niche breadths in the invasive ranges than in the native ranges. Our results suggest that climatic niche shifts between native and invasive ranges occurred. Thus, the occurrence records of both native and invasive regions must be considered when modeling and predicting the spatial distributions of AIWs under current and future climate scenarios. Owing to high habitat suitability, AIWs were more likely to expand into regions of low latitude, and future climate change was predicted to result in a shift in the AIWs in Qinghai and Tibet (regions of higher altitude) as well as Heilongjiang, Jilin, Liaoning, Inner Mongolia, and Gansu (regions of higher latitude). Our results suggest that we need measures to prevent and control AIW expansion at the country‐wide level.     

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。     

Global habitat suitability of cold‐water octocorals

Aim Three‐quarters of Octocorallia species are found in deep waters. These cold‐water octocoral colonies can form a major constituent of structurally complex habitats. The global distribution and the habitat requirements of deep‐sea octocorals are poorly understood given the expense and difficulties of sampling at depth. Habitat suitability models are useful tools to extrapolate distributions and provide an understanding of ecological requirements. Here, we present global habitat suitability models and distribution maps for seven suborders of Octocorallia: Alcyoniina, Calcaxonia, Holaxonia, Scleraxonia, Sessiliflorae, Stolonifera and Subselliflorae. Location Global. Methods We use maximum entropy modelling to predict octocoral distribution using a database of 12,508 geolocated octocoral specimens and 32 environmental grids resampled to 30 arc‐second (approximately 1 km²) resolution. Additionally, a meta‐analysis determined habitat preferences and niche overlap between the different suborders of octocorals. Results Suborder Sessiliflorae had the widest potential habitat range, but all records for all suborders implied a habitat preference for continental shelves and margins, particularly the North and West Atlantic and Western Pacific Rim. Temperature, salinity, broad scale slope, productivity, oxygen and calcite saturation state were identified as important factors for determining habitat suitability. Less than 3% of octocoral records were found in waters undersaturated for calcite, but this result is affected by a shallow‐water sampling bias. Main conclusions The logistical difficulties, expense and vast areas associated with deep‐sea sampling leads to a gap in the knowledge of faunal distributions that is difficult to fill without predictive modelling. Global distribution estimates are presented, highlighting many suitable areas which have yet to be studied. We suggest that approximately 17% of oceans are suitable for at least one suborder but 3.5% may be suitable for all seven. This is the first global habitat suitability modelling study on the distribution of octocorals and forms a useful resource for researchers, managers and conservationists.     

On the edge: habitat restoration priorities for three critically endangered bird species on Sangihe,Indonesia

Remnant forests on the small Wallacean island of Sangihe north of Sulawesi hold the entire ranges of more critically endangered (CR) bird species than any other comparable area on earth. We develop habitat association models for three of these CR species to identify critical habitat features as well as areas where habitat falls slightly short of suitability, and to determine whether another area of forest away from the largest block might be suitable as an insurance site for a translocated population. Hopes for all three species appear almost totally pinned to forest within a 13 km² area of the Sahendaruman crater, with virtually no near-suitable habitat away from this site. There is, however, little overlap in habitats between one CR species and the other two: cerulean flycatcher Eutrichomyias rowleyi is associated with mature streamside forest with full canopy cover, lianas, and mid-level growth, while Sangihe whistler Coracornis sanghirensis and Sangihe golden bulbul Hypsipetes platenae are restricted to ridgetop forest with full canopy cover and large trees. We pinpoint small areas (around 5 km²) of forest in the crater that are already suitable or can be made so with habitat management, and these are absolute priorities for conservation action. We show how habitat characteristics identified within models might be enhanced, and how features, especially certain tree species, can be used as indicators of future habitat improvement.     

Ecological principles of species distribution models: the habitat matching rule

Most species distribution models (SDMs) assume that habitats are closed, stable and without competition. In that environmental context, it is ecologically correct to assume that members of a species will be distributed in direct relation to the suitability of the habitat, that is, according to the so‐called habitat matching rule. This paper examines whether it is possible to maintain the assumption of the habitat matching rule in the following circumstances: (1) when habitats are connected and organisms can move between them, (2) when there are disturbances and seasonal cycles that generate instability, and (3) when there is inter‐specific and intra‐specific competition. Here I argue that it is possible as long as the following aspects are taken into account. In open habitats at equilibrium, in which habitat selection and competition operate, the habitat matching rule can be applied in some conditions, while competition tends to homogenize the species distribution in other environmental contexts. In the latter case, two methods can be used to incorporate these effects into SDMs: new parameters can be incorporated into the response functions, or the occurrence of proportions of categories of individuals (adult/young, male/female, or dominant/subordinate species in guilds) can be used instead of the occurrence of organisms. The habitat matching rule is not fulfilled in non‐equilibrium environments. The solution to this problem lies in the design of SDMs with two strategies that depend on scale. Locally, the disequilibrium can be encapsulated using average environmental conditions, with sufficiently large cells (in the case of metapopulations) and/or long enough sampling periods (in the case of seasonal cycles). At coarse scales, the use of presence‐only models can in some cases avoid the destabilizing effect of catastrophic historical processes. The matching law is a strong assumption of SDMs because it is based on population ecology theory and the principle of evolution by natural selection.     

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence‐only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km²) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.     

Environmental change,shifting distributions,and habitat conservation plans: A case study of the California gnatcatcher

Many species have already experienced distributional shifts due to changing environmental conditions, and analyzing past shifts can help us to understand the influence of environmental stressors on a species as well as to analyze the effectiveness of conservation strategies. We aimed to (1) quantify regional habitat associations of the California gnatcatcher (Polioptila californica ); (2) describe changes in environmental variables and gnatcatcher distributions through time; (3) identify environmental drivers associated with habitat suitability changes; and (4) relate habitat suitability changes through time to habitat conservation plans. Southern California's Western Riverside County (WRC ), an approximately 4,675 km² conservation planning area. We assessed environmental correlates of distributional shifts of the federally threatened California gnatcatcher (hereafter, gnatcatcher) using partitioned Mahalanobis D ² niche modeling for three time periods: 1980–1997, 1998–2003, and 2004–2012, corresponding to distinct periods in habitat conservation planning. Highly suitable gnatcatcher habitat was consistently warmer and drier and occurred at a lower elevation than less suitable habitat and consistently had more CSS , less agriculture, and less chaparral. However, its relationship to development changed among periods, mainly due to the rapid change in this variable. Likewise, other aspects of highly suitable habitat changed among time periods, which became cooler and higher in elevation. The gnatcatcher lost 11.7% and 40.6% of highly suitable habitat within WRC between 1980–1997 to 1998–2003, and 1998–2003 to 2004–2012, respectively. Unprotected landscapes lost relatively more suitable habitat (?64.3%) than protected landscapes (30.5%). Over the past four decades, suitable habitat loss within WRC , especially between the second and third time periods, was associated with temperature‐related factors coupled with landscape development across coastal sage scrub habitat; however, development appears to be driving change more rapidly than climate change. Our study demonstrates the importance of providing protected lands for potential suitable habitat in future scenarios.     

基于生态位模型的艾比湖国家级自然保护区马鹿生境评价

生境评价和预测是对濒危物种进行有效保护的基础。通过2013年9月和2014年10月对新疆艾比湖国家级自然保护区开展2次秋季野外调查共收集了92处马鹿(Cervuselaphus)出现数据,利用马鹿出现数据作为分布点数据,选取地形、植被类型和气候因子3类23种因子作为生境变量,利用MAXENT生态位模型分析了新疆艾比湖国家级自然保护区马鹿秋季生境适宜性分布特征和主要生境因子对马鹿分布的影响。结果表明:模型预测结果较高,平均AUC(area under the curve,受试工作者曲线下面值)值为0.976;Jackknife检验结果显示:最热月最高温度对马鹿生境分布的影响较大。植被类型和坡度对马鹿生境分布的影响不大。海拔、年降雨量、气温日较差和最热季平均温度是影响马鹿生境分布的主要生境因子。马鹿秋季生境划分为高适宜、次适宜、低适宜和不适宜4个等级,马鹿的高适宜生境区主要分布在研究区域的北部,次适宜及低适宜生境区则分布于高适宜生境区的边缘,而不适宜生境区主要集中在西部和东部地区。研究不仅提供了马鹿在艾比湖的实际分布状况,也为马鹿生境和生境因子的关系方面提供了一个重要的科学依据。     

美国大陆外来入侵物种斑马纹贻贝(Dreissena polymorpha)潜在生境预测模型

防止外来生物入侵造成危害的重要手段是阻止可能造成入侵的物种进入适合其生存的地区.论文以1864个美国外来入侵物种斑马纹贻贝定点发生数据和开放式基础地理信息数据库Daymet的34个环境变量为主要信息源,采用逻辑斯蒂回归(LR)、分类与回归树模型(CART)、基于规则的遗传算法(GARP)、最大熵法(Maxent)4种途径,建立美国大陆部分潜在生境预测模型,从接受者运行特征曲线下面积(AUC)、Pearson相关系数、Kappa值3个方面来检验模型预测精度,在此基础上分析斑马纹贻贝的空间分布规律及其环境影响因素.研究结果表明:在3个评价指标中,4个生态位模型预测精度均达到优良水平,其中Maxent在物种现实生境模拟、主要生态环境因子筛选、环境因子对物种生境影响的定量描述方面都表现出了优越的性能;距水源距离、海拔高度、降水频率、太阳辐射是影响物种空间分布的主要环境因子.论文提出的研究方法对中国外来入侵物种生境预测具有较强的借鉴意义,研究结果对中国海洋外来入侵物种沙筛贝的预测与防治,具有一定的指导作用.     

Visualizing uncertainty in habitat suitability models with the hyper‐envelope modeling interface,version 2

Habitat suitability models (HSMs) are popular and used for a wide variety of applications but most do not include analysis of the uncertainty of the model outputs. Additionally, some overfit the data and few allow the ability to fill data gaps with expert opinion. HEMI 1 addressed issues with overfitting data and allowed models to incorporate both occurrence data and expert opinion. HEMI 2 improves on HEMI 1 with a simplified interface and the ability to inject random noise into occurrence locations and environmental variable values to generate uncertainty maps. HEMI 2 uses Monte Carlo methods to perform uncertainty, validation, and sensitivity testing and generates mean and standard deviation habitat suitability maps.     

Global habitat suitability models of terrestrial mammals

Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.     

Widespread occurrence of Batrachochytrium dendrobatidis in Ontario,Canada, and predicted habitat suitability for the emerging Batrachochytrium salamandrivorans

Chytridiomycosis, caused by the fungi Batrachochytrium dendrobatidis and Batrachochytrium salamandrivorans, is associated with massive amphibian mortality events worldwide and with some species’ extinctions. Previous ecological niche models suggest that B. dendrobatidis is not well‐suited to northern, temperate climates, but these predictions have often relied on datasets in which northern latitudes are underrepresented. Recent northern detections of B. dendrobatidis suggest that these models may have underestimated the suitability of higher latitudes for this fungus. We used qPCR to test for B. dendrobatidis in 1,041 non‐invasive epithelial swab samples from 18 species of amphibians collected across 735,345 km² in Ontario and Akimiski Island (Nunavut), Canada. We detected the pathogen in 113 samples (10.9%) from 11 species. Only one specimen exhibited potential clinical signs of disease. We used these data to produce six Species Distribution Models of B. dendrobatidis, which classified half of the study area as potential habitat for the fungus. We also tested each sample for B. salamandrivorans, an emerging pathogen that is causing alarming declines in European salamanders, but is not yet detected in North America. We did not detect B. salamandrivorans in any of the samples, providing a baseline for future surveillance. We assessed the potential risk of future introduction by comparing salamander richness to temperature‐dependent mortality, predicted by a previous exposure study. Areas with the highest species diversity and predicted mortality risk extended 60,530 km² across southern Ontario, highlighting the potential threat B. salamandrivorans poses to northern Nearctic amphibians. Preventing initial introduction will require coordinated, transboundary regulation of trade in amphibians (including frogs that can carry and disperse B. salamandrivorans), and surveillance of the pathways of introduction (e.g., water and wildlife). Our results can inform surveillance for both pathogens and efforts to mitigate the spread of chytridiomycosis through wild populations.     

Future climate change will severely reduce habitat suitability of the Critically Endangered Chinese giant salamander

1. Being the largest extant amphibian in the world, the IUCN Critically Endangered Chinese giant salamander Andrias davidianus is a charismatic species with great international public interest. While threats such as commercial overexploitation and habitat degradation have been extensively documented to affect natural populations of A. davidianus, still no information is available about the species sensitivity to climate change.
2. Here, we develop an ensemble of species distribution models (SDMs) for A. davidianus and projected its habitat suitability under present-day and future climate change scenarios. We based our SDMs on bioclimatic and topographic predictors, and recent (2012–2018) field-collected occurrence data across the whole distribution range of the species.
3. The ensemble SDMs exhibited good predictive capacity and suggested that slope, maximum temperature of warmest month, precipitation of driest month, and isothermality are the most influential predictors in determining distribution patterns in this species. The projections of our models point to a pronounced impact of climate changes over A. davidianus, with more than two-thirds of its suitable range expected to be lost in all scenarios of future climates tested.
4. In concert with the numerous other threats that are affecting this species, climate change poses a serious hindrance to the long-term survival of A. davidianus. We emphasise the urgent need of undertaking strict measures to manage this species and safeguard the few remaining available suitable habitats. We suggest that adaptive management strategies including designation of new reserves should be considered to mitigate the impacts of climate change on A. davidianus.