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Incorporating behavior-based indices of connectivity into spatially explicit population models

机译:将基于行为的连通性指数纳入空间明确的人口模型

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Measuring connectivity in fragmented landscapes remains a central problem in ecology. Connectivity metrics range from descriptors of landscape structure to direct observations of a species' ability to move to and colonize a forest patch. We constructed individual-based spatially explicit population models for a guild of forest rodents in Indiana to test the ability of structural and actual, or behavioral, measures of connectivity to predict patch and landscape occupancy and abundance. Model accuracy was assessed using comparisons with data from trapping studies. Predicted abundances within patches correlated with empirical data for five out of six species, but predicted patterns of patch occupancy corresponded with observations for only one species. Discrepancies may be due to inaccurate parameter values or the absence from the models of ecological processes such as conspecific attraction and competition. Nonetheless, the models demonstrated the utility of patch immigration as a measure of connectivity in explaining population abundance in fragmented landscapes. We discuss potential methods of collecting these behavior-based data.
机译:在零散的景观中测量连通性仍然是生态学的中心问题。连通性指标的范围从景观结构的描述符到对物种迁移并定居于森林斑块的能力的直接观察。我们为印第安纳州的一个森林啮齿动物协会构建了基于个体的空间明晰的种群模型,以测试连通性的结构和实际(或行为)量度,以预测斑块和景观的占用和丰度。使用与诱捕研究的数据进行比较,评估模型的准确性。斑块中的预测丰度与六种物种中的五种的经验数据相关,但斑块占用率的预测模式仅与一种物种的观测值相对应。差异可能是由于参数值不正确或生态过程模型(例如特定吸引和竞争)的缺失所致。但是,这些模型证明了斑块移民的实用性,可以作为一种连通性手段来解释零散景观中的人口数量。我们讨论了收集这些基于行为的数据的潜在方法。

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