As climate change intensifies, there is increasing interest in developing models that reduce uncertainties in projections of global climate and refine these projections to finer spatial scales. Forecasts of climate impacts on ecosystems are far more challenging and their uncertainties even larger because of a limited understanding of physical controls on biological systems. Management and conservation plans that explicitly account for changing climate are rare and even those generally rely on retrospective analyses rather than future scenarios of climatic conditions and associated responses of specific ecosystems. Using past biophysical relationships as a guide to predicting the impacts of future climate change assumes that the observed relationships will remain constant. However, this assumption involves a long chain of uncertainty about future greenhouse gas emissions, climate sensitivity to changes in greenhouse gases, and the ecological consequences of climate change. These uncertainties in forecasting biological responses to changing climate highlight the need for resource management and conservation policies that are robust to unknowns and responsive to change. We suggest how policy might develop despite substantial uncertainties about the future state of salmon ecosystems.
We censused juvenile salmonids and stream habitat over two consecutive summers to test the ability of habitat models to explain the distribution of juvenile Coho Salmon Oncorhynchus kisutch, young‐of‐the‐year (age‐0) steelhead O. mykiss, and steelhead parr (age ≥1) within a network consisting of several different‐sized streams. Our network‐scale habitat models explained 27, 11, and 19% of the variation in density of juvenile Coho Salmon, age‐0 steelhead, and steelhead parr, respectively, but strong levels of spatial autocorrelation were typically present in the residuals. Explanatory power of base habitat models increased and spatial autocorrelation decreased with the sequential inclusion of variables accounting for the effects of stream size, year, stream, reach location, and a tertiary interaction term. Stream‐scale models were highly variable. Fish–habitat associations were rarely linear and ranged from negative to positive; the variable accounting for location of the habitat within a stream was often more important than the habitat variables. The limited success of our network‐scale models was apparently related to variation in the strength and shape of fish–habitat associations across and within streams and years. These results indicate that there are several potential limitations to extrapolating models to broader areas based only on spatially limited surveys.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.