The value of information is context dependent: A demonstration of decision tools to address multispecies river temperature management under uncertainty
Trade-offs among objectives in natural resource management can be exacerbated in altered ecosystems and when there is uncertainty in predicted management outcomes. Multi-criteria decision analysis and value of information (VOI) are underutilized decision tools that can assist fisheries managers in handling trade-offs and evaluating the importance of uncertainty. We demonstrate the use of these tools using a case study in the Sacramento River, California, USA, where two imperiled species with different temperature requirements, winter-run Chinook Salmon Oncorhynchus tshawytscha and Green Sturgeon Acipenser medirostris , spawn and rear in the artificially cold Shasta Dam tailwater. A temperature-control device installed on Shasta Dam maintains cool water for Chinook Salmon; however, uncertainties exist related to the effects of temperatures on the spawning and rearing of both species. We consider four alternative hypotheses in models of early life-stage dynamics to evaluate the effects of alternative temperature management strategies on Chinook Salmon and Green Sturgeon management objectives. We used VOI to quantify the increase in management performance that can be expected by resolving hypothesis-based uncertainties as a function of the weight assigned to species-specific objectives. We found the decision was hindered by uncertainty; the best performing alternative depends on which hypothesis is true, with warmer or cooler alternative management strategies recommended when weights favor Green Sturgeon or Chinook Salmon objectives, respectively. The value of reducing uncertainty was highest when Green Sturgeon was slightly favored, highlighting the interaction between scientific uncertainty and decision makers' values. Our demonstration features multi-criteria decision analysis and VOI as transparent, deliberative tools that can assist fisheries managers in confronting value conflicts, prioritizing resolution of uncertainty, and optimally managing aquatic ecosystems.