Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles-猫眼课题宝

DOI：

10.1111/csp2.349

发表时间：

2021-01

期刊：

Conservation Science and Practice

影响因子：

3.1

通讯作者：

中科院分区：

环境科学与生态学3区

文献类型：

作者：

Jennie Hannah Degenford;D. Liang;H. Bailey;A. Hoover;P. Zarate;J. Azócar;Daniel Devia;J. Alfaro‐Shigueto;J. Mangel;Nelly de Paz;Javier Quinones Davila;David Sarmiento Barturen;Juan M. Rguez‐Baron;A. Williard;C. Fahy;Nicole Barbour;G. Shillinger

东太平洋棱皮龟（Dermochelys coriacea）的数量近年来急剧下降。主要原因之一是沿海和远洋渔业的兼捕。渔业观测数据往往未得到充分利用，尽管这些数据很有可能影响政策。在这项研究中，我们创建了一个时空物种分布模型，综合渔业观测与遥感环境数据。该模型将发展成为东太平洋棱皮龟种群的动态管理工具。我们从东南太平洋（2001-2018）的多个渔场获得了棱皮龟观测数据。应用动态泊松点过程模型预测棱皮龟强度（单位面积观测值）作为动态环境协变量的函数。该模型可作为管理人员和利益相关者减少棱皮龟副渔获物的应用工具，并为分析其他脆弱种群和物种的渔业观察提供了一个建模框架。

The Eastern Pacific leatherback turtle population (Dermochelys coriacea) has declined precipitously in recent years. One of the major causes is bycatch from coastal and pelagic fisheries. Fisheries observations are often underutilized, despite strong potential for this data to affect policy. In this study, we created a spatiotemporal species distribution model that synthesizes fisheries observations with remotely sensed environmental data. The model will be developed into a dynamic management tool for the Eastern Pacific leatherback population. We obtained leatherback observation data from multiple fisheries that have operated in the Southeast Pacific (2001–2018). A dynamic Poisson point process model was applied to predict leatherback intensity (observation per unit area) as a function of dynamic environmental covariates. This model serves as a tool for application by managers and stakeholders toward the reduction of leatherback turtle bycatch and provides a modeling framework for analyzing fisheries observations from other vulnerable populations and species.

Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles

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