羌塘高原藏羚羊栖息地分布及影响因素

藏羚羊作为羌塘高原草食性野生动物的典型代表,明确其栖息地的准确分布将有利于识别藏羚羊种群保护关键区域,协调羌塘高原人与野生动物冲突。采用野外调查与物种分布模型相结合的办法,以藏羚羊栖息地选择偏好和迁徙规律为基础,利用Maxent模型模拟其在繁殖季节和非繁殖季节的栖息地分布,并通过栖息地质量模型辅以GIS空间分析方法,识别受人类干扰的栖息地范围。结果表明：藏羚羊在非繁殖季节主要分布在羌塘高原东南部,围绕在色林错等水系周围,其越冬区面积约为26万km²。倾向选择海拔4800m以上、气候温暖、靠近水源且食物资源丰富的区域。藏羚羊在繁殖季节栖息地明显呈现由南向北扩散的趋势,多在水系周围呈小片状分布于羌塘东北、中北、昆仑山南麓部分区域,产羔区面积约为30万km²。选择产羔地时则注重坡度、水源、海拔、气温日较差等,对植被资源的选择倾向较非繁殖季弱,重视迁徙通道连贯性和产羔区域安全性。羌塘高原人类活动整体较弱,北部羌塘国家级自然保护区是藏羚羊理想栖息地,但南部地区社会经济较发达,尤其是那曲地区南部和阿里西南部,居民地、道路和牧业等人类活动对栖息地干扰较大,受干扰面积分别占藏羚羊越冬区的39.7%,产羔区的34.9%。     

Spatial sampling bias and model complexity in stream‐based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin,USA

Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream‐segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large‐river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC_C‐selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC_C‐selected models were more inclusive of westward‐situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.     

Environmental Suitability and Distribution of the Caucasian Rock Agama, Paralaudakia caucasia （Sauria： Agamidae） in Western and Central Asia

Predictive potential distribution modeling is crucial in outlining habitat usage and establishing conservation management priorities. In this paper we provide detailed data on the distribution of the Caucasian rock agama Para- laudakia caucasia, and use species distribution models （MAXENT） to evaluate environmental suitability and potential distribution at a broad spatial scale. Locality data on the distribution of P. caucasia have been gathered over nearly its entire range by various authors from field surveys. The distribution model ofP caucasia showed good performance （AUC = 0.887）, and predicted high suitability in regions mainly located in Tajikistan, north Pakistan, Afghanistan, southeast Turkmenistan, northeast Iran along the Elburz mountains, Transcaueasus （Azerbajan, Armenia, Georgia）, northeastern Turkey and northward along the Caspian Sea coast in Daghestan, Russia. The identification of suitable areas for this species will help to assess conservation status of the species, and to set up management programs.     

Using maximum entropy to predict the potential distribution of an invasive freshwater snail

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A habitat quality indicator for common birds in Europe based on species distribution models

The EU 2020 Biodiversity Strategy requires the gathering of information on biodiversity to aid in monitoring progress towards its main targets. Common species are good proxies for the diversity and integrity of ecosystems, since they are key elements of the biomass, structure, functioning of ecosystems, and therefore of the supply of ecosystem services. In this sense, we aimed to develop a spatially-explicit indicator of habitat quality (HQI) at European level based on the species included in the European Common Bird Index, also grouped into their major habitat types (farmland and forest). Using species occurrences from the European Breeding Birds Atlas (at 50 km × 50 km) and the maximum entropy algorithm, we derived species distribution maps using refined occurrence data based on species ecology. This allowed us to cope with the limitations arising from modelling common and widespread species, obtaining habitat suitability maps for each species at finer spatial resolution (10 km × 10 km grid), which provided higher model accuracy. Analysis of the spatial patterns of local and relative species richness (defined as the ratio between species richness in a given location and the average richness in the regional context) for the common birds analysed demonstrated that the development of a HQI based on species richness needs to account for the regional species pool in order to make objective comparisons between regions. In this way, we proved that relative species richness compensated for the bias caused by the inherent heterogeneous patterns of the species distributions that was yielding larger local species richness in areas where most of the target species have the core of their distribution range. The method presented in this study provides a robust and innovative indicator of habitat quality which can be used to make comparisons between regions at the European scale, and therefore potentially applied to measure progress towards the EU Biodiversity Strategy targets. Finally, since species distribution models are based on breeding birds, the HQI can be also interpreted as a measure of the capacity of ecosystems to provide and maintain nursery/reproductive habitats for terrestrial species, a key maintenance and regulation ecosystem service.     

入侵害虫菊方翅网蝽在中国的潜在分布预测

菊方翅网蝽Corythucha marmorata(Uhler,1878)是我国新近发现的外来入侵害虫,研究明确菊方翅网蝽在我国的潜在分布范围对其监测预警及科学防控具有重要意义。本研究根据菊方翅网蝽的地理分布数据及相关环境变量,运用Maxent生态位模型与ArcGIS预测了菊方翅网蝽在中国的潜在地理分布范围。预测结果表明:菊方翅网蝽在我国的适生区主要分布于100°～125°E,20°～40°N的亚热带、暖温带区域,其中高适生区主要集中在长江中下游地区,包括浙江、江苏、湖南、上海大部分地区、安徽南部、湖北南部、江西西部及南部、贵州东部、福建东部、广西北部、山东中部、河南南部以及重庆、台湾局部;此外,极端气温、平均气温、最干月份降雨量对菊方翅网蝽的潜在分布影响较大。菊方翅网蝽已在我国成功入侵并迅速蔓延成灾,应在疫区边缘地带加强监测,并采取措施防止其进一步扩散。     

Invasion of the gall mite Aceria genistae (Acari: Eriophyidae), a natural enemy of the invasive weed Cytisus scoparius,into California,U.S.A. and predictions for climate suitability in other regions using ecological niche modelling

Scotch broom (Cytisus scoparius (L.) Link) is a European shrub that has naturalised in several countries worldwide and is recognised as an invasive weed in much of western North America. The mite Aceria genistae (Nalepa) is a coevolved, gall-inducing herbivore associated with Scotch broom in its native range and has been intentionally introduced as a classical weed biological control agent of C. scoparius in Australia and New Zealand. An adventive, never intentionally introduced, population of A. genistae was discovered in Washington and Oregon, U.S.A. in 2005. Surveys for A. genistae in California resulted in the discovery of the gall mite in 11 counties, with a widely scattered distribution. Molecular and morphological assessments confirm the mites collected from galls in California are A. genistae. Whether natural or anthropogenic, the estimated rate of long range dispersal for A. genistae from Washington or Oregon to California ranges from 39 to 62?km/yr. Niche model predictions indicate that A. genistae will continue to expand its distribution throughout much of the Scotch broom-invaded lands of California but areas supporting the weed in the Eastern U.S.A. appear less suitable. Modelling evidence also indicates that portions of Chile and Argentina are suitable for colonisation by A. genistae, also suggesting that expansion of the mite is possible in areas of Tasmania, southeastern Australia, and New Zealand where the mite was released. The environmental safety of A. genistae in relation to non-target plants and the influence of herbivory on Scotch broom fitness are discussed.     

Current and future potential distributions of three Dracaena Vand. ex L. species under two contrasting climate change scenarios in Africa

Forest undergrowth plants are tightly connected with the shady and humid conditions that occur under the canopy of tropical forests. However, projected climatic changes, such as decreasing precipitation and increasing temperature, negatively affect understory environments by promoting light‐demanding and drought‐tolerant species. Therefore, we aimed to quantify the influence of climate change on the spatial distribution of three selected forest undergrowth plants, Dracaena Vand. ex L. species, D. afromontana Mildbr., D. camerooniana Baker, and D. surculosa Lindl., simultaneously creating the most comprehensive location database for these species to date. A total of 1,223 herbarium records originating from tropical Africa and derived from 93 herbarium collections worldwide have been gathered, validated, and entered into a database. Species‐specific Maxent species distribution models (SDMs) based on 11 bioclimatic variables from the WorldClim database were developed for the species. HadGEM2‐ES projections of bioclimatic variables in two contrasting representative concentration pathways (RCPs), RCP2.6 and RCP8.5, were used to quantify the changes in future potential species distribution. D. afromontana is mostly sensitive to temperature in the wettest month, and its potential geographical range is predicted to decrease (up to ?63.7% at RCP8.5). Optimum conditions for D. camerooniana are low diurnal temperature range (6–8°C) and precipitation in the wettest season exceeding 750 mm. The extent of this species will also decrease, but not as drastically as that of D. afromontana. D. surculosa prefers high precipitation in the coldest months. Its potential habitat area is predicted to increase in the future and to expand toward the east. This study developed SDMs and estimated current and future (year 2050) potential distributions of the forest undergrowth Dracaena species. D. afromontana, naturally associated with mountainous plant communities, was the most sensitive to predicted climate warming. In contrast, D. surculosa was predicted to extend its geographical range, regardless of the climate change scenario.