One outcome of the 2022 Society of Environmental Toxicology and Chemistry Pellston Workshop on incorporating climate change predictions into ecological risk assessments was the key question of how to integrate ecological risk assessments that focus on contaminants with the environmental alterations from climate projections. This article summarizes the results of integrating selected direct and indirect effects of climate change into an existing Bayesian network previously used for ecological risk assessment. The existing Bayesian Network Relative Risk Model integrated the effects of two organophosphate pesticides (malathion and diazinon), water temperature, and dissolved oxygen levels on the Chinook salmon population in the Yakima River Basin (YRB), Washington, USA. The endpoint was defined as the entity, Yakima River metapopulation, and the attribute was defined as no decline to a subpopulation or the overall metapopulation. In this manner, we addressed the management objective of no net loss of Chinook salmon, an iconic and protected species. Climate change-induced changes in water quality parameters (temperature and dissolved oxygen levels) used models based on projected climatic conditions in the 2050s and 2080s by the use of a probabilistic model. Pesticide concentrations in the original model were modified assuming different scenarios of pest control strategies in the future, because climate change may alter pest numbers and species. Our results predict that future direct and indirect changes to the YRB will result in a greater probability that the salmon population will continue to fail to meet the management objective of no net loss. As indicated by the sensitivity analysis, the key driver in salmon population risk was found to be current and future changes in temperature and dissolved oxygen, with pesticide concentrations being not as important.