Species aggregation models resolve essential foraging habitat: Implications for conservation and management

Species aggregations are a culmination of behavioral events arising from an array of biophysical interactions, dynamically shifting in space and time. Prediction of species' aggregation dynamics remains a challenge in studies of their distribution patterns. Species distribution models (SDMs) are statistical tools for understanding spatial patterns of marine biodiversity, ranging from essential species habitat, assessing fisheries bycatch, and projecting future distribution changes. SDMs involving pelagic species abundance generally do not typically resolve aggregation patterns. We use a 20-year observation record of seabird species aggregations, with seabirds being the most easily quantified "pelagic" species, to develop SDMs and a regional ocean modeling system to identify physical drivers and changes in aggregation location and intensity over time. We apply a conceptual ecosystem model to organize environmental covariates according to habitat production within coastal upwelling systems. The SDM used a 2-step modeling approach: a presence/absence model and a binary aggregation model. Thus, we aim to predict factors that characterize baseline ocean habitat for a species (presence/absence) and that aggregate large numbers of the species. Prediction of seabird aggregation results in realistic spatial distribution patterns that reflect known species habitat associations. Temporally, aggregation indices indicate mixed responses both within and between resident and migrant species, reflecting interannual effects of warm/cool ocean years and mesoscale structure supporting enhanced or decreased productive foraging habitat. The most abundant species were more likely to form aggregations during warmer years, indicating a response to a decrease in productive foraging habitat. The occurrence of species aggregations in spring is predictable by examining ocean-climate conditions in the preceding winter, thus providing a potential early warning system of anticipated ecosystem shifts. We contend that the aggregation occurrence model may improve the realism of pelagic SDMs and their utility for assessing spatial and temporal variability of trophic interactions. We discuss the utility of species aggregation models for quantifying the variability in critical pelagic habitats, the ecology and response of seabird species as indicators, advancement of ecosystem modeling and monitoring, and conservation applications (e.g., bycatch, wind energy, and oil spills).

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Publication Details

Journal
Ecological Applications
Published
2025-07-01
DOI
https://doi.org/10.1002/eap.70068
Citations
1
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
1.84

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Species aggregation models resolve essential foraging habitat: Implications for conservation and management

Jarrod A. Santora, Isaac D. Schroeder, Elliott L. Hazen, Brian K. Wells et al.
1 citations
Ecological Applications
Species Distribution and Climate Change
1.84
article

Species aggregation models resolve essential foraging habitat: Implications for conservation and management

Jarrod A. Santora, Isaac D. Schroeder, Elliott L. Hazen, Brian K. Wells, John C. Field, Megan A. Cimino, Steven J. Bograd, Justin J. Suca
article en
1 citations

Abstract

Species aggregations are a culmination of behavioral events arising from an array of biophysical interactions, dynamically shifting in space and time. Prediction of species' aggregation dynamics remains a challenge in studies of their distribution patterns. Species distribution models (SDMs) are statistical tools for understanding spatial patterns of marine biodiversity, ranging from essential species habitat, assessing fisheries bycatch, and projecting future distribution changes. SDMs involving pelagic species abundance generally do not typically resolve aggregation patterns. We use a 20-year observation record of seabird species aggregations, with seabirds being the most easily quantified "pelagic" species, to develop SDMs and a regional ocean modeling system to identify physical drivers and changes in aggregation location and intensity over time. We apply a conceptual ecosystem model to organize environmental covariates according to habitat production within coastal upwelling systems. The SDM used a 2-step modeling approach: a presence/absence model and a binary aggregation model. Thus, we aim to predict factors that characterize baseline ocean habitat for a species (presence/absence) and that aggregate large numbers of the species. Prediction of seabird aggregation results in realistic spatial distribution patterns that reflect known species habitat associations. Temporally, aggregation indices indicate mixed responses both within and between resident and migrant species, reflecting interannual effects of warm/cool ocean years and mesoscale structure supporting enhanced or decreased productive foraging habitat. The most abundant species were more likely to form aggregations during warmer years, indicating a response to a decrease in productive foraging habitat. The occurrence of species aggregations in spring is predictable by examining ocean-climate conditions in the preceding winter, thus providing a potential early warning system of anticipated ecosystem shifts. We contend that the aggregation occurrence model may improve the realism of pelagic SDMs and their utility for assessing spatial and temporal variability of trophic interactions. We discuss the utility of species aggregation models for quantifying the variability in critical pelagic habitats, the ecology and response of seabird species as indicators, advancement of ecosystem modeling and monitoring, and conservation applications (e.g., bycatch, wind energy, and oil spills).

Ecological ApplicationsVol. 35(5)
NOAA National Marine Fisheries Service (US), University of Hawaiʻi at Mānoa (US), National Oceanic and Atmospheric Administration (US), University of California, Santa Cruz (US), NOAA National Marine Fisheries Service Southwest Fisheries Science Center (US)
Biological and Physical Sciences Division
Life below water
Openalex Percentile: Top 14%
Species Distribution and Climate Change
1.84
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