Applying a hybrid model to support management of the endangered Topeka shiner in oxbow habitats

Abstract

IntroductionHabitat restoration aims at reinstating abiotic and biotic habitat conditions to support long-term species persistence and viability. This management practice is commonly part of recovery plans developed for species listed as threatened or endangered under the Endangered Species Act. The endangered Topeka shiner (Notropis topeka) inhabits off-channel habitats, such as oxbow lakes which are increasingly the focus of restoration, but the exact abiotic conditions conducive to its persistence in this habitat are not fully understood. In this study, a hybrid model consisting of an individual-based model of the Topeka shiner and an aquatic ecosystem model representing the oxbow habitat was applied to identify optimal environmental conditions for the persistence of Topeka shiner populations.Materials and methodsEnvironmental conditions that correlated with Topeka shiner presence were gathered from published studies and included water temperature, turbidity, oxbow depth, light intensity (as a function of riparian vegetation presence), dissolved nitrogen, and dissolved phosphorus. Selected conditions were systematically varied in simulations and results were analyzed with a partial rank correlation method that quantifies the relative influence on model output from multiple factors.ResultsConducted simulations identified water temperature, depth, and dissolved inorganic nitrogen to be the most influential for Topeka shiner population biomass and additional simulations were conducted exploring the magnitudes and directions of effects of these three factors. Water temperature had the largest positive impact on population biomass followed by oxbow depth and nitrogen reduction.DiscussionWe recommend that the three identified factors be further explored in a combination of empirical and modeling approaches to advise management for the endangered Topeka shiner. This study demonstrated how ecological models could inform recovery plans by identifying factors that enhance species persistence. Ultimately, models should support management practices that result in long-term population viability of listed species and could facilitate their timely delisting.