Riparian restoration offsets predicted population consequences of climate warming in a threatened headwater fish

Freshwater ecosystems and their associated biota are under increasing threats from multiple stressors including climate and land‐use change. The conservation of these ecosystems must be based on an integration of data including species physiological tolerances, the biotic and abiotic drivers of the distribution of populations, and demographic processes, to provide the comprehensive ecological information necessary for management. This study used a Bayesian belief network (BBN) to synthesize research on northern river blackfish, a threatened species in the upper Condamine River, Australia, into a probabilistic framework capable of predicting the complex relationships that exist between environmental conditions and population success. This study tested how predicted air temperature scenarios for the years 2050 and 2080, and catchment restoration scenarios, would be expected to affect three indices of population success: adult abundance, juvenile abundance, and juvenile recruitment. Compared with current climatic conditions, climate warming scenarios reduced the probability of future population success by between 0.4% and 1.6%. These shifts were almost completely offset, and even improved, when riparian zones were restored at the catchment scale, where changes ranged from an overall decrease of 0.2% to an increase of 1%. To achieve the highest probability of population success, the impacts of warming stream temperatures and the degradation of riparian zones must be mitigated. However, the model showed that there is still a possibility of complete population failure under a wide range of conditions, even when conditions appear to be suitable. To maximize the future population success of river blackfish we recommend targeting the restoration of hydrologically active catchment areas where grazing strongly influences stream biota. The use of a BBN allowed the combination of multiple sources of information to solve complex ecological problems, including how multiple stressors may affect threatened freshwater species.