The population level is often the biological endpoint addressed in ecological risk assessments (ERAs). However, ERAs tend to ignore the metapopulation structure, which precludes an understanding of how population viability is affected by multiple stressors (e.g., toxicants and environmental conditions) at large spatial scales. Here we integrate metapopulation model simulations into a regional‐scale, multiple stressors risk assessment (Bayesian network relative risk model [BN‐RRM]) of organophosphate (OP) exposure, water temperature, and DO impacts on Chinook salmon (Oncorhynchus tshawytscha). A matrix metapopulation model was developed for spring Chinook salmon in the Yakima River Basin (YRB), Washington, USA, including 3 locally adapted subpopulations and hatchery fish that interact with those subpopulations. Three metapopulation models (an exponential model, a ceiling density‐dependent model, and an exponential model without dispersal) were integrated into the BN‐RRM to evaluate the effects of population model assumptions on risk calculations. Risk was defined as the percent probability that the abundance of a subpopulation would decline from their initial abundance (500 000). This definition of risk reflects the Puget Sound Partnership's management goal of achieving “no net loss” of Chinook abundance. The BN‐RRM model results for projection year 20 showed that risk (in % probability) from OPs and environmental stressors was higher for the wild subpopulations—the American River (50.9%–97.7%) and Naches (39.8%–84.4%) spring Chinook—than for the hatchery population (CESRF 18.5%–46.5%) and the Upper Yakima subpopulation (21.5%–68.7%). Metapopulation risk was higher in summer (58.1%–68.7%) than in winter (33.6%–53.2%), and this seasonal risk pattern was conserved at the subpopulation level. To reach the management goal in the American River spring Chinook subpopulation, the water temperature conditions in the Lower Yakima River would need to decrease. We demonstrate that 1) relative risk can vary across a metapopulation's spatial range, 2) dispersal among patches impacts subpopulation abundance and risk, and 3) local adaptation within a salmon metapopulation can profoundly impact subpopulation responses to equivalent stressors. Integr Environ Assess Manag 2021;17:95–109. © 2020 SETAC

中文翻译：

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将种群动态集成到贝叶斯网络相对风险模型中：在生态环境中评估农药对奇努克鲑鱼（Oncorhynchus tshawytscha）的风险

人口水平通常是生态风险评估（ERA）中涉及的生物学终点。但是，ERAs往往忽略了种群的结构，这使得人们无法理解在较大的空间尺度上人口生存力如何受到多种压力源（例如，毒物和环境条件）的影响。在这里，我们将有机种群（OP）暴露，水温和DO对奇努克鲑鱼（Oncorhynchus tshawytscha）的有机磷（OP）暴露，水温和DO影响的区域集成的，多应激源风险评估（贝叶斯网络相对风险模型[BN-RRM]）集成到了人口种群模型模拟中。）。针对美国华盛顿州亚基马河盆地（YRB）的春季奇努克鲑鱼建立了一个矩阵种群模型，包括3个局部适应的亚种群和与这些亚种群相互作用的孵化场鱼类。BN-RRM中集成了三种综合人口模型（指数模型，依赖于密度的上限模型和没有扩散的指数模型），以评估人口模型假设对风险计算的影响。风险定义为亚人群的丰度从其最初的丰度（500 000）下降的百分比概率。风险的定义反映了Puget Sound Partnership的管理目标，即实现Chinook丰度“不净损失”。BN-RRM模型对第20年预测的结果表明，野生亚种群（美国河（50.9％–97.7％）和纳奇（39.8％–84.4％）春季）来自OP和环境胁迫的风险（以概率％）较高。契努克族比孵化场人口（CESRF 18.5％–46.5％）和上亚基马亚群（21.5％–68.7％）高。夏季（58.1％–68.7％）的种群迁移风险高于冬季（33.6％–53.2％）的种群风险，这种季节性风险模式在亚种群水平上得以保留。为了达到美国河春努努克族群的管理目标，需要降低下亚基马河的水温条件。我们证明1）相对风险可以在整个种群的空间范围内变化，2）斑块之间的分散会影响亚种群的数量和风险，Integr环境评估管理2021; 17：95–109。©2020 SETAC