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Predicting Avian Abundance Within and Across Tidal Marshes Using Fine-Scale Vegetation and Geomorphic Metrics

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Abstract

Tidal marsh monitoring and restoration can benefit from the union of fine-scale remote sensing products and field-based survey data via spatial predictive models. As part of an interdisciplinary wetland monitoring project in San Francisco Bay, we developed a suite of 1-m pixel-level spatial metrics describing patterns in marsh vegetation and geomorphology for six sites across a large salinity gradient. These metrics, based on multi-spectral aerial imagery and derived vegetation maps, provided a basis for fine-scale spatial modeling of avian habitat potential. Using common yellowthroat (Geothlypis trichas), song sparrow (Melospiza melodia), and black rail (Laterallus jamaicensis) abundance data, we developed statistical models with relatively high explanatory power. In each case, models were improved by including vegetation-map variables, but variables directly extracted from aerial imagery were more reliable indicators of avian abundance. Although results varied by species, our models achieved reasonable within-site predictive success. When predicting to sites not used in the training set, however, validation results were inconsistent and often poor, suggesting that these models should be used with caution outside of the original study sites. As remotely sensed data become more readily available, our methods may be applied to a diverse range of sites, resulting in improved model generality and applicability.

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Acknowledgments

This manuscript is dedicated to the memory of Douglas Allen. We are grateful to the CALFED Bay-Delta Program for providing funding for this project (contract # P0685516), to the California Department of Fish and Game and Marin Audubon Society for administering portions of those funds, and to Stuart Siegel for coordinating the IRWM project. Several skilled field biologists—Leonard Liu, Parvaneh Abbaspour, April Robinson, Jules Evens, and Hildie Spautz—collected the avian data that made this analysis possible. Lisa Schile, Tom Parker, John Callaway, and Mike Vasey conducted invaluable vegetation surveys used to ground-truth vegetation maps. Jake Schweitzer was instrumental in processing and georectifying aerial imagery from HJW GeoSpatial, Inc., and created preliminary channel layers. Stuart Siegel and Douglas Allen provided valuable input on spatial geomorphic metrics. Samuel Valdez and Dennis Jongsomjit helped create spatial metric layers and attribute data for analysis. Julian Wood provided valuable input, and Jill Talmage helped administer contracts. This is PRBO publication #1704.

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  1. Karin A. Tuxen

    Present address: Google, 1600 Amphitheatre Parkway, Mountain View, CA, 94043, USA

Authors and Affiliations

  1. PRBO Conservation Science, 3820 Cypress Dr. #11, Petaluma, CA, 94954, USA

    Diana Stralberg & Nadav Nur

  2. U.S. Geological Survey, Western Ecological Research Center, Davis Field Station, One Shields Ave., UC Davis, Davis, CA, 95616, USA

    Mark P. Herzog

  3. Department of Environmental Science, Policy & Management, UC Berkeley, Berkeley, CA, 94720, USA

    Karin A. Tuxen & Maggi Kelly

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  1. Diana Stralberg
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Correspondence to Diana Stralberg.

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Stralberg, D., Herzog, M.P., Nur, N. et al. Predicting Avian Abundance Within and Across Tidal Marshes Using Fine-Scale Vegetation and Geomorphic Metrics. Wetlands 30, 475–487 (2010). https://doi.org/10.1007/s13157-010-0052-8

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