Abstract

Urbanization-driven landscape changes are harmful to many species. Negative effects can be mitigated through habitat preservation and restoration, but it is often difficult to prioritize these conservation actions. This is due, in part, to the scarcity of species response data, which limit the predictive accuracy of modeling to estimate critical thresholds for biological decline and recovery. To address these challenges, we quantify effort required for restoration, in combination with a clear conservation objective and associated metric (e.g., habitat for focal organisms). We develop and apply this framework to coho salmon (Oncorhynchus kisutch), a highly migratory and culturally iconic species in western North America that is particularly sensitive to urbanization. We examine how uncertainty in biological parameters may alter locations prioritized for conservation action and compare this to the effect of shifting to a different conservation metric (e.g., a different focal salmon species). Our approach prioritized suburban areas (those with intermediate urbanization effects) for preservation and restoration action to benefit coho. We found that prioritization was most sensitive to the selected metric, rather than the level of uncertainty or critical threshold values. Our analyses highlight the importance of identifying metrics that are well-aligned with intended outcomes.

Highlights

  • IntroductionNegative effects can be mitigated through habitat preservation and restoration, but it is often difficult to prioritize these conservation actions

  • Urbanization-driven landscape changes are harmful to many species

  • We address two conservation objectives (1) habitat for coho salmon, which are highly sensitive to toxic urban runoff and frequently exhibit high mortality among adults returning to spawn in urban streams, and (2) habitat for Chinook salmon (O. tshawytscha), which are protected under the U.S Endangered Species Act

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Summary

Introduction

Negative effects can be mitigated through habitat preservation and restoration, but it is often difficult to prioritize these conservation actions This is due, in part, to the scarcity of species response data, which limit the predictive accuracy of modeling to estimate critical thresholds for biological decline and recovery. To address these challenges, we quantify effort required for restoration, in combination with a clear conservation objective and associated metric (e.g., habitat for focal organisms). One transformative change in land-use associated with urbanization is expanding imperviousness from pavement, roofs, and other hard s­ urfaces[18,19] Among other things, this change alters the quality, quantity, and routing of surface water runoff as it moves across the landscape during and after rain events. Implementing green stormwater infrastructure is costly and Scientific Reports | (2021) 11:818

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