Dynamic management approaches protect endangered bycatch species but with much greater efficiency than existing static closures.
Climate change is causing range shifts in many marine species, with implications for biodiversity and fisheries. Previous research has mainly focused on how species' ranges will respond to changing ocean temperatures, without accounting for other environmental covariates that could affect future distribution patterns. Here, we integrate habitat suitability modeling approaches, a high-resolution global climate model projection, and detailed fishery-independent and -dependent faunal datasets from one of the most extensively monitored marine ecosystems-the U.S. Northeast Shelf.We project the responses of 125 species in this region to climate-driven changes in multiple oceanographic factors (e.g., ocean temperature, salinity, sea surface height) and seabed characteristics (i.e., rugosity and depth). Comparing model outputs based on ocean temperature and seabed characteristics to those that also incorporated salinity and sea surface height (proxies for primary productivity and ocean circulation features), we explored how an emphasis on ocean temperature in projecting species' range shifts can impact assessments of species' climate vulnerability. We found that multifactor habitat suitability models performed better in explaining and predicting species historical distribution patterns than temperature-based models.We also found that multifactor models provided more concerning assessments of species' future distribution patterns than temperature-based models, projecting that species' ranges will largely shift northward and become more contracted and fragmented over time. Our results suggest that using ocean temperature as a primary determinant of range shifts can significantly alter projections, masking species' climate vulnerability, and potentially forestalling proactive management. K E Y W O R D Sclimate change, habitat suitability models, marine species, range shifts, species vulnerability | 4209 MCHENRY Et al.
Aim Advances in ecological and environmental modelling offer new opportunities for estimating dynamic habitat suitability for highly mobile species and supporting management strategies at relevant spatiotemporal scales. We used an ensemble modelling approach to predict daily, year‐round habitat suitability for a migratory species, the blue whale (Balaenoptera musculus), and demonstrate an application for evaluating the spatiotemporal dynamics of their exposure to ship strike risk. Location The California Current Ecosystem (CCE) and the Southern California Bight (SCB), USA. Methods We integrated a long‐term (1994–2008) satellite tracking dataset on 104 blue whales with data‐assimilative ocean model output to assess year‐round habitat suitability. We evaluated the relative utility of ensembling multiple model types compared to using single models, and selected and validated candidate models using multiple cross‐validation metrics and independent observer data. We quantified the spatial and temporal distribution of exposure to ship strike risk within shipping lanes in the SCB. Results Multi‐model ensembles outperformed single‐model approaches. The final ensemble model had high predictive skill (AUC = 0.95), resulting in daily, year‐round predictions of blue whale habitat suitability in the CCE that accurately captured migratory behaviour. Risk exposure in shipping lanes was highly variable within and among years as a function of environmental conditions (e.g., marine heatwave). Main conclusions Daily information on three‐dimensional oceanic habitats was used to model the daily distribution of a highly migratory species with high predictive power and indicated that management strategies could benefit by incorporating dynamic environmental information. This approach is readily transferable to other species. Dynamic, high‐resolution species distribution models are valuable tools for assessing risk exposure and targeting management needs.
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