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Using step-selection functions to model landscape connectivity for African elephants: accounting for variability across individuals and seasons

机译:使用步进选择功能来模拟非洲大象的景观连接:占个人和季节的变异性

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Landscape connectivity is an important component of systematic conservation planning. Step-selection functions (SSFs) is a highly promising method for connectivity modeling. However, differences in movement behavior across individuals and seasons are usually not considered in current SSF-based analyses, potentially leading to imprecise connectivity models. Here, our objective was to use SSFs to build functional connectivity models for African elephants Loxodonta africana in a seasonal environment to illustrate the temporal variability of functional landscape connectivity. We provide a methodological framework for integrating detected inter-individual variability into resistance surface modeling, for assessing how landscape connectivity changes across seasons, and for evaluating how seasonal connectivity differences affect predictions of movement corridors. Using radio-tracking data from elephants in the Borderland area between Kenya and Tanzania, we applied SSFs to create seasonal landscape resistance surfaces. Based on seasonal models, we predicted movement corridors connecting major protected areas (PAs) using circuit theory and least-cost path analysis. Our findings demonstrate that individual variability and seasonality lead to substantial changes in landscape connectivity and predicted movement corridors. Specifically, we show that the models disregarding seasonal resource fluctuations underestimate connectivity for the wet and transitional seasons, and overestimate connectivity for the dry season. Based on our seasonal models, we predicted a connectivity network between large PAs and highlight seasonal and consistent patterns that are most important for effective management planning. Our findings reveal that elephant movements in the borderland between Kenya and Tanzania are essential for maintaining connectivity in the dry season, and that existing corridors do not protect these movements in full extent.
机译:景观连接是系统保护计划的重要组成部分。步进选择功能(SSFS)是一种高度有希望的连接建模方法。然而,在基于SSF的基于SSF的分析中,通常不考虑各个和季节的运动行为的差异,可能导致不精确的连接模型。在这里,我们的目标是使用SSFS在季节性环境中为非洲大象Loxodonta Africana构建功能连接模型,以说明功能景观连接的时间变化。我们提供了一种用于将检测到的各种可变性集成到电阻表面建模的方法框架,用于评估季节横跨景观的变化以及评估季节性连接差异如何影响运动走廊的预测。我们在肯尼亚和坦桑尼亚之间的边境地区的大象中使用射线跟踪数据,我们应用SSFS创建季节性景观阻力表面。基于季节性模型,我们预测了使用电路理论和最低成本路径分析连接主要保护区域(PAS)的运动走廊。我们的调查结果表明,各个变异性和季节性导致景观连接和预测运动走廊的大量变化。具体而言,我们表明模型无视季节性资源波动低估了潮湿和过渡季节的连通性,以及旱季的连通性。根据我们的季节性模型,我们预测了大型PAS之间的连接网络,并突出显示最重要的季节性和一致的模式,这些模式对于有效的管理计划最重要。我们的调查结果表明,肯尼亚和坦桑尼亚之间边境的大象运动对于维持旱季的连接至关重要,并且现有的走廊不会在全面保护这些运动。

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