开发横跨美国的河流鱼类物种分布模型——管理和保护的框架

Hao Yu, None Arthur R. Cooper, Jared Ross, Alexa McKerrow, Daniel J. Wieferich, Dana M. Infante
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欲了解更多信息,请联系:美国科学分析与综合项目主任。地质SurveyP.O。邮政站302Denver, CO 80225本报告解释了用于预测美国相邻地区河流鱼类在其原生范围内发生的步骤和具体方法。在本研究中,利用鱼类存在/缺失与22个自然和人为景观变量之间的关系,增强回归树模型预测了271种生态重要河流鱼类的分布。为该范围的淡水部分开发的模型涵盖了28科的物种。本研究建模的物种最多的科是鲤科(271种中有87种),其次是棘科(34种)和蠓科(17种)。模型的预测性能使用四个指标进行评估:受试者工作特征曲线下的面积、灵敏度、特异性和真实技能统计,这些指标均来自十倍交叉验证结果。在增强回归树模型中,预测变量的相对重要性被计算并为每个物种排序。鱼类分布的3个最强自然预测因子是流域网络面积、流域年平均气温和流域最高海拔,而3个最强人为预测因子是下游干坝密度、到下游干坝的距离和流域网络边界内牧草/干草土地利用面积百分比。研究结果表明,61种鱼类对气候变量敏感,40种鱼类对人为压力敏感。本研究中建立的模型可用于获得关于栖息地保护优先事项、人为威胁和气候变化对栖息地适宜性的潜在影响的关键信息,有助于现在和未来保护河流鱼类的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation
First posted November 13, 2023 For additional information, contact: Director, Science Analytics and Synthesis ProgramU.S. Geological SurveyP.O. Box 25046, Mail Stop 302Denver, CO 80225 This report explains the steps and specific methods used to predict fluvial fish occurrences in their native ranges for the conterminous United States. In this study, boosted regression tree models predict distributions of 271 ecologically important fluvial fish species using relations between fish presence/absence and 22 natural and anthropogenic landscape variables. Models developed for the freshwater portions of the ranges for species represented 28 families. Cyprinidae was the family with the most species (87 of 271) modeled for this study, followed by Percidae (34) and Ictaluridae (17). Model predictive performance was evaluated using four metrics: area under the receiver operating characteristic curve, sensitivity, specificity, and True Skill Statistic, which are all from tenfold cross-validation results. The relative importance of the predictor variables in the boosted regression tree models was calculated and ranked for each species. The three strongest natural predictors of fish distributions were network catchment area, the mean annual air temperature of the local catchment, and the maximum elevation of the local catchment, while the three strongest anthropogenic predictors were downstream main stem dam density, distance to downstream main stem dam, and the percentage of pasture/hay land use area within network catchment boundaries. Study results showed 61 fish species were sensitive to climate variables, and 40 fish species were sensitive to anthropogenic stressors. The models developed in this study can be used to derive critical information regarding habitat protection priorities, anthropogenic threats, and potential effects of climate change on habitat suitability, aiding in efforts to conserve fluvial fishes now and into the future.
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