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Density-independent and density-dependent variables both affect the spatial distributions of species. However, their effects are often separately addressed using different analytical techniques. We apply a spatially explicit regression framework that incorporates localized, interactive and threshold...
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ftoregonstate:ir.library.oregonstate.edu:4m90f188w 2024-09-15T17:59:35+00:00 fig2_tmp3.tif Ciannelli, Lorenzo Bartolino, Valerio Chan, Kung-Sik https://ir.library.oregonstate.edu/concern/defaults/4m90f188w unknown https://ir.library.oregonstate.edu/concern/defaults/4m90f188w Copyright Not Evaluated ftoregonstate 2024-07-22T18:06:04Z Density-independent and density-dependent variables both affect the spatial distributions of species. However, their effects are often separately addressed using different analytical techniques. We apply a spatially explicit regression framework that incorporates localized, interactive and threshold effects of both density-independent (water temperature) and density-dependent (population abundance) variables, to study the spatial distribution of a well-monitored flatfish population in the eastern Bering Sea. Results indicate that when population biomass was beyond a threshold a further increase in biomass promoted habitat expansion in a non-additive fashion with water temperature. In contrast, during years of low population size, habitat occupancy was only affected positively by water temperature. These results reveal the spatial signature of intraspecific abundance distribution relationships and the nonadditive and nonstationary responses of species spatial dynamics. Furthermore, these results underscore the importance of implementing analytical techniques that can simultaneously account for density-dependent and density-independent sources of variability when studying geographical distribution patterns. Other/Unknown Material Bering Sea ScholarsArchive@OSU (Oregon State University) |
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ScholarsArchive@OSU (Oregon State University) |
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ftoregonstate |
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Density-independent and density-dependent variables both affect the spatial distributions of species. However, their effects are often separately addressed using different analytical techniques. We apply a spatially explicit regression framework that incorporates localized, interactive and threshold effects of both density-independent (water temperature) and density-dependent (population abundance) variables, to study the spatial distribution of a well-monitored flatfish population in the eastern Bering Sea. Results indicate that when population biomass was beyond a threshold a further increase in biomass promoted habitat expansion in a non-additive fashion with water temperature. In contrast, during years of low population size, habitat occupancy was only affected positively by water temperature. These results reveal the spatial signature of intraspecific abundance distribution relationships and the nonadditive and nonstationary responses of species spatial dynamics. Furthermore, these results underscore the importance of implementing analytical techniques that can simultaneously account for density-dependent and density-independent sources of variability when studying geographical distribution patterns. |
author |
Ciannelli, Lorenzo Bartolino, Valerio Chan, Kung-Sik |
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Ciannelli, Lorenzo Bartolino, Valerio Chan, Kung-Sik fig2_tmp3.tif |
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Ciannelli, Lorenzo Bartolino, Valerio Chan, Kung-Sik |
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Ciannelli, Lorenzo |
title |
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https://ir.library.oregonstate.edu/concern/defaults/4m90f188w |
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Bering Sea |
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Bering Sea |
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https://ir.library.oregonstate.edu/concern/defaults/4m90f188w |
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Copyright Not Evaluated |
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1810436688262987776 |