人为干扰对神农架川金丝猴连通性及遗传多样性的影响

川金丝猴湖北种群是川金丝猴分布的最东缘,现主要分布于神农架国家公园和巴东自然保护区,其作为单独的管理单元,相对较低的遗传多样性、孤立的遗传状态和较小的种群数量,使得该种群面对环境变化脆弱性高。以神农架为研究区域,首先基于物种分布模型获得川金丝猴移动的阻力图层,利用电路理论分析适宜生境连接度;其次,设置道路和旅游两个人为干扰情景,运用最小费用距离模型与电路理论模型,分析道路和旅游活动对川金丝猴移动路径以及对不同亚群内和亚群间连通性的影响;最后,利用CDPOP软件模拟道路对川金丝猴遗传多样性的影响。结果表明:(1)神农架川金丝猴适宜生境分布较集中,生境斑块间存在多个潜在扩散区域;(2)道路改变了川金丝猴往来于南北生境间的最优路径,旅游干扰对川金丝猴移动路径无明显影响,其干扰主要在于川金丝猴对其具有回避性,回避距离为100 m;(3)道路显著降低金猴岭亚群内的连通性,并显著增加了所有亚群间的移动阻力,旅游活动对亚群内和亚群间的连通性无显著影响;(4)川金丝猴种群在150年内的遗传多样性呈下降趋势,道路的影响将加剧遗传多样性下降的程度。基于以上结果本文提出了针对性的保护建议,对于该物种的保护和其他濒危物种的类似研究具有较强的参考价值和借鉴意义。     

矿区土地利用生态风险的时空异质性

以微山县煤矿较集中、地面塌陷较严重的11个乡镇作为研究区,以遥感影像和土地利用现状数据为数据源,获取4期土地利用类型分布图,根据景观生态学理论构建景观意义上的土地利用生态风险指数,结合空间统计学及地统计学理论,探究2000—2016年研究区适宜尺度下土地利用生态风险的时空变化情况及空间异质性。结果表明:1 km×1 km规则网格是最佳研究尺度,在该尺度下研究区土地利用生态风险的空间分布呈集聚模式,且具有很强的空间正相关性;2000—2005年土地利用生态风险指数在小尺度上的随机变异逐渐被较大尺度上的空间结构性变异所取代,2005年生态风险总的空间变异程度较高,2005—2016年随机因素引起的空间变异程度增强;2000—2016年土地利用生态风险呈现由中高、高生态风险向中、中低生态风险转变的特征;生态风险恶化区和明显恶化区主要分布在东部矿区周边、道路沿线、地面塌陷较严重的区域,研究区西南部微山湖沿岸东西两侧,耕地的生态风险恶化程度2010—2016年较高;17年间微山湖湖区的生态风险稳定区和改善区大幅增加,生态风险明显下降。     

基于生态安全格局与多尺度景观连通性的城市生态源地识别

高度城市化区域面临着严峻的生态环境问题,生态安全格局构建是保障城市生态安全的重要途径。生态源地的科学识别一直是生态安全格局构建的技术难点。以高度城市化的深圳市为例,从社会-经济-自然三方面要素构建DPSIR模型评估区域生态安全,并基于景观连通性的多尺度分析识别生态源地。研究表明:(1)深圳市生态安全格局呈现东南部、东北部优良,中部、西部区域警告的空间特征,其中安全区、较安全区、基本安全区、预警、中警分别占比30.34%、13.49%、9.85%、9.15%和37.17%;(2)通过连接度、聚合度、内聚力和分离度4个景观连通性测度指标的主成分分析,可知400 m是深圳市生态源地景观连通性最优的识别尺度,斑块最小识别阈值面积为0.8 km~2;(3)深圳市生态源地面积为753.78 km~2,占全市总面积的37.74%,主要为深圳市东南部与西部区域的林地和水域用地,其中包含了86.87%的法定保护区,且91.92%的区域落入生态控制线范围内;(4)基于生态安全格局与多尺度景观连通性的生态源地识别方法可为城市生态源地的识别提供新思路,从而有效指导城市规划。     

oSCR: a spatial capture–recapture R package for inference about spatial ecological processes

Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture–recapture methods related to heterogeneity in detectabililty, and the emergence of new technologies (e.g. camera traps, non‐invasive genetics) that have vastly improved our ability to collection spatially explicit observation data on individuals. However, the utility of SCR methods reaches far beyond simply convenience and data availability. SCR presents a formal statistical framework that can be used to test explicit hypotheses about core elements of population and landscape ecology, and has profound implications for how we study animal populations. In this software note, we describe the technical basis and analytical workflow of oSCR, an R package for analyzing spatial encounter history data using a multi‐session sex‐structured likelihood. The impetus for developing oSCR was to create an accessible and transparent analysis tool that allows users to conveniently and intuitively formulate statistical models that map directly to fundamental processes of interest in spatial population ecology (e.g. space use, resource selection, density and connectivity). We have placed an emphasis on creating a transparent and accessible code base that is coupled with a logical workflow that we hope stimulates active participation in further technical developments.     

Trophic rewilding establishes a landscape of fear: Tasmanian devil introduction increases risk‐sensitive foraging in a key prey species

Global declines of large carnivores have reduced the ‘landscape of fear’ that constrains the behaviour of other species. In recent years, active and passive trophic rewilding have potentially begun restoring these lost top–down controls. The Tasmanian devil Sarcophilus harrisii has declined severely due to a novel transmissible cancer. In response to extinction fears, devils were introduced to the devil‐free Maria Island, where their abundance rapidly increased. We tested how this introduction influenced risk‐sensitive foraging in the common brushtail possum Trichosurus vulpecula, a major prey species for devils, using giving‐up densities (GUDs). Before the introduction of devils, possum GUDs on Maria Island were indistinguishable from the long‐diseased region of Tasmania, where devils have been rare since ~2000. Three years after devil introduction, GUDs were 64% higher on Maria Island than the control region, demonstrating that after an initial period of high mortality, possums quickly adopted risk‐sensitive foraging behaviours. Devil activity across Maria Island was variable, leading to a heterogeneous landscape of fear and highlighting that top predators must be at functional densities to elicit behavioural responses from prey. Our study provides strong evidence that top predators modify the behaviour of prey by instilling fear, causing rapid ecological change following recoveries.     

广东省中山市五桂山土沉香空间遗传结构

为了解五桂山的土沉香(Aquilaria sinensis)种群空间遗传结构,利用18个微卫星位点对143株胸高直径大于5 cm的土沉香个体基因型进行了检测。结果表明,五桂山土沉香种群的观测杂合度和期望杂合度均为0.534;近交系数为0.000 1,说明五桂山土沉香遗传多样性并不低,且种群处于随机交配状况。空间遗传结构分析结果表明,五桂山土沉香缺乏空间遗传结构,不同遗传背景的个体相互混杂,导致相邻个体遗传差异较大。这可能是五桂山土沉香种群发育过程中自疏所致,也可能是这一地区土沉香为人工种植,而非自然发育形成而造成的。     

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the “eucalypts”) are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole‐genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome‐wide, interspecific differentiation (F_ST = 0.15) and intraspecific differentiation between localities (F_ST ≈ 0.01–0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments.     

Urbanization reduces genetic connectivity in bobcats (Lynx rufus) at both intra– and interpopulation spatial scales

Urbanization is a major factor driving habitat fragmentation and connectivity loss in wildlife. However, the impacts of urbanization on connectivity can vary among species and even populations due to differences in local landscape characteristics, and our ability to detect these relationships may depend on the spatial scale at which they are measured. Bobcats (Lynx rufus) are relatively sensitive to urbanization and the status of bobcat populations is an important indicator of connectivity in urban coastal southern California. We genotyped 271 bobcats at 13,520 SNP loci to conduct a replicated landscape resistance analysis in five genetically distinct populations. We tested urban and natural factors potentially influencing individual connectivity in each population separately, as well as study–wide. Overall, landscape genomic effects were most frequently detected at the study–wide spatial scale, with urban land cover (measured as impervious surface) having negative effects and topographic roughness having positive effects on gene flow. The negative effect of urban land cover on connectivity was also evident when populations were analyzed separately despite varying substantially in spatial area and the proportion of urban development, confirming a pervasive impact of urbanization largely independent of spatial scale. The effect of urban development was strongest in one population where stream habitat had been lost to development, suggesting that riparian corridors may help mitigate reduced connectivity in urbanizing areas. Our results demonstrate the importance of replicating landscape genetic analyses across populations and considering how landscape genetic effects may vary with spatial scale and local landscape structure.     

Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

Taxonomy has traditionally relied on morphological and ecological traits to interpret and classify biological diversity. Over the last decade, technological advances and conceptual developments in the field of molecular ecology and systematics have eased the generation of genomic data and changed the paradigm of biodiversity analysis. Here we illustrate how traditional taxonomy has led to species designations that are supported neither by high throughput sequencing data nor by the quantitative integration of genomic information with other sources of evidence. Specifically, we focus on Omocestus antigai and Omocestus navasi, two montane grasshoppers from the Pyrenean region that were originally described based on quantitative phenotypic differences and distinct habitat associations (alpine vs. Mediterranean‐montane habitats). To validate current taxonomic designations, test species boundaries, and understand the factors that have contributed to genetic divergence, we obtained phenotypic (geometric morphometrics) and genome‐wide SNP data (ddRADSeq) from populations covering the entire known distribution of the two taxa. Coalescent‐based phylogenetic reconstructions, integrative Bayesian model‐based species delimitation, and landscape genetic analyses revealed that populations assigned to the two taxa show a spatial distribution of genetic variation that do not match with current taxonomic designations and is incompatible with ecological/environmental speciation. Our results support little phenotypic variation among populations and a marked genetic structure that is mostly explained by geographic distances and limited population connectivity across the abrupt landscapes characterizing the study region. Overall, this study highlights the importance of integrative approaches to identify taxonomic units and elucidate the evolutionary history of species.     

近25年长江中游地区土地利用时空变化格局与驱动因素

长江中游地区(湖北省、湖南省和江西省)位于长江经济带中心,是我国"中三角城市群"所在地,也是国家"两屏三带"生态安全战略的重点区域,其土地利用变化受地理环境制约和社会经济发展的影响,也与未来区域可持续发展密切相关。根据1990、2000、2010和2015年Landsat TM遥感影像数据,采用景观格局分析、梯度分析及相关性分析方法,揭示近25年土地利用时空变化格局及其与社会经济因素的关系。研究表明:(1)研究区耕地与林地为主体景观,分别占30%、50%,建设用地占比3%,具有重要生态功能的土地利用类型(林地、灌木、水体、草地、果园)占比达67%。(2)沿中心城区-边缘区梯度,各土地利用类型表现出明显的空间特征,建设用地和耕地面积占比显著减小,破碎化程度增加,而林地呈整体化趋势。(3)近25年来,该区耕地、林地分别减少1.06%、0.49%,建设用地增加1.08%,整体景观破碎化程度加重、景观多样性升高;除林地外,其它地类变化均与社会经济因素(人口、农业人口、非农业人口、GDP、人均GDP、城市化水平、三大产业产值)显著相关。这些结果表明,与沿海地区相比,近25年长江中游地区土地利用变化较小,还有着较好的基于提供生态系统服务的土地利用基础;但生态保护任务仍然艰巨,需划定生态保护红线,保护优质耕地,控制城市扩展规模,加强生态廊道、节点的建设,增强区域景观生态功能,以便满足未来长江经济带可持续发展的需要。