Does the scale of our observational window affect our conclusions about correlations between endangered salmon populations and their habitat

• Published in: Landscape ecology Vol. 25; no. 5; pp. 727 - 743
• Main Authors: Feist, Blake E, Steel, E. Ashley, Jensen, David W, Sather, Damon N. D
• Format: Journal Article
• Language: English
• Published: Dordrecht Dordrecht : Springer Netherlands 01.05.2010; Springer Netherlands; Springer Nature B.V
• Subjects: Animal populations; Biomedical and Life Sciences; Brackish; Catchment scale; Ecology; Endangered & extinct species; Endangered species; Environmental Management; Environmental restoration; Fish populations; Freshwater; Geographic information systems; Habitats; Land use; Landscape Ecology; Landscape/Regional and Urban Planning; Life Sciences; Marine; Nature Conservation; Oncorhynchus; Remote sensing; Research Article; River basins; Salmon; Scale models; Sustainable Development; Wildlife conservation; USA, Columbia R. basin; I, Pacific; Multiple spatial scales; Restoration; Conservation; Spatial analysis; Pacific salmon; Habitat; Spatial extent; Land use
• ISSN: 0921-2973; 1572-9761
• DOI: 10.1007/s10980-010-9458-1

Differences in the strength of species-habitat relationships across scales provide insights into the mechanisms that drive these relationships and guidance for designing in situ monitoring programs, conservation efforts and mechanistic studies. The scale of our observation can also impact the strength of perceived relationships between animals and habitat conditions. We examined the relationship between geographic information system (GIS)-based landscape data and Endangered Species Act-listed anadromous Pacific salmon (Oncorhynchus spp.) populations in three subbasins of the Columbia River basin, USA. We characterized the landscape data and ran our models at three spatial scales: local (stream reach), intermediate (6th field hydrologic units directly in contact with a given reach) and catchment (entire drainage basin). We addressed three questions about the effect of scale on relationships between salmon and GIS representations of landscape conditions: (1) at which scale does each predictor best correlate with salmon redd density, (2) at which scale is overall model fit maximized, and (3) how does a mixed-scale model compare with single scale models (mixed-scale meaning models that contain variables characterized at different spatial scales)? We developed mixed models to identify relationships between redd density and candidate explanatory variables at each of these spatial scales. Predictor variables had the strongest relationships with redd density when they were summarized over the catchment scale. Meanwhile strong models could be developed using landscape variables summarized at only the local scale. Model performance did not improve when we used suites of potential predictors summarized over multiple scales. Relationships between species abundance and land use or intrinsic habitat suitability detected at one scale cannot necessarily be extrapolated to other scales. Therefore, habitat restoration efforts should take place in the context of conditions found in the associated watershed or landscape.