A multi-scale approach for integrating species distribution models with landscape connectivity to identify critical linkage zones for African savanna elephants (Loxodonta africana)

IF 2.6 3区 环境科学与生态学 Q2 ECOLOGY
Lei Song , Amy E. Frazier , Anna Bond Estes , Lyndon Despard Estes
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Abstract

The populations of African savanna elephants have declined by an estimated 60 % since the 1970s, which can be attributed to a mixture of poaching and habitat loss. Human activities and environmental changes have caused unprecedented loss and fragmentation of elephant natural habitats, resulting in the isolation of elephant populations. Preserving habitat connectivity is thus increasingly important to conserve remaining elephants' populations and maintain ecological functions. A major challenge in large-scale connectivity modeling is data availability constraints. To tackle this issue, we developed an integrated modeling approach that leverages multiple, publicly available occurrence datasets, which vary in format and quality, with a multi-scale SDM to estimate spatial suitability of African savanna elephants. Two SDMs, based on polygon-based observations and presence-only occurrences, were separately calibrated using the Isolation Forest algorithm and then ensembled using Bayes fusion. Particularly, we included multiple landscape metrics derived from a high-resolution (∼5 m) land cover map as environmental predictors in the SDMs to characterize the landscape structure influencing elephant movement. The resulting environmental suitability was then used to map landscape connectivity through circuit theory, implemented in Circuitscape. Using species distribution modeling (SDM) and graph-based landscape connectivity modeling, we aimed to understand population connectivity and target vital corridors across Tanzania, one of the most important elephant range states. Shapley value-based variable analysis in SDM revealed that human modifications strongly influence elephant distribution at broad scales, while habitat fragmentation and connectivity impact their activities. Connectivity results further highlighted that both long- and short-distance connectivity are currently facing significant threats from intensive human activities (e.g., agriculture) in Tanzania and identified critical linkage zones that should be targeted for connectivity conservation efforts.
基于物种分布模型和景观连通性的多尺度方法识别非洲草原象关键联系带
自20世纪70年代以来,非洲草原象的数量估计下降了60%,这可归因于偷猎和栖息地丧失。人类活动和环境变化造成了大象自然栖息地前所未有的丧失和破碎化,导致大象种群的隔离。因此,保护栖息地的连通性对于保护剩余的大象种群和维持生态功能变得越来越重要。大规模连接建模的一个主要挑战是数据可用性约束。为了解决这一问题,我们开发了一种综合建模方法,该方法利用多个公开可用的数据集,这些数据集在格式和质量上各不相同,并使用多尺度SDM来估计非洲稀树草原象的空间适宜性。使用隔离森林算法分别校准基于多边形观测和仅存在事件的两个sdm,然后使用贝叶斯融合进行集成。特别是,我们纳入了从高分辨率(~ 5米)土地覆盖图中提取的多个景观指标,作为SDMs中的环境预测因子,以表征影响大象运动的景观结构。由此产生的环境适宜性随后被用于通过电路理论绘制景观连通性,并在Circuitscape中实现。利用物种分布模型(SDM)和基于图的景观连通性模型,我们旨在了解坦桑尼亚(大象最重要的栖息地之一)的种群连通性和目标重要走廊。基于Shapley值的SDM变量分析表明,人类活动对大象分布有较大影响,而栖息地破碎化和连通性影响大象活动。连通性结果进一步强调,坦桑尼亚的长途和短距离连通性目前都面临着来自密集人类活动(如农业)的重大威胁,并确定了应以连通性保护为目标的关键连通性区域。
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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