Compilation and discussion of driver,pressure, and state indicators for the Grand Bank ecosystem,Northwest Atlantic |
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| Affiliation: | 1. Department of Biology, Dalhousie University, 1355 Oxford Street, PO Box 15000, Halifax, NS B3H 4R2, Canada;2. Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, USA;3. BirdLife International, Wellbrook Court, Cambridge CB30NA, UK;4. Centre for Biodiversity & Environment Research, Department of Genetics, Evolution & Environment, University College London, WC1E 6BT, UK;5. Earth to Ocean Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada;6. Conservation Biology Division, NOAA Fisheries, Northwest Fisheries Science Center, 2725 Montlake Blvd. E. Seattle, WA, USA;7. Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, PO Box 1066 Blindern, NO-0316 Oslo, Norway;8. Wyoming Natural Diversity Database, University of Wyoming, 1000 E. University Ave., Dept. 3381, Laramie, WY, USA;9. USDA Forest Service, Rocky Mountain Research Station, 800 E. Beckwith Avenue, Missoula, MT, USA;10. NOAA Fisheries, Northwest Fisheries Science Center, 2725 Montlake Blvd. E. Seattle, WA, USA |
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| Abstract: | There are global calls for new ecosystem-based fisheries management (EBFM) approaches. Scientific support for EBFM includes assessing ecosystem indicators of biological communities, environmental conditions, and human activities. As part of a broader research project we have synthesized a suite of traditional and new indicators for the Grand Bank in Atlantic Canada, which we share here. This is an ideal ecosystem for indicator analysis because it experienced dramatic changes over the past three decades, including a collapse in fish biomass that had profound socio-economic consequences. We exploit the wealth of data for this ecosystem to investigate how individual indicators reflect observed changes in the ecosystem, and then illustrate two applications of this indicator suite. Correlations were used to show that relationships among the fish functional groups changed after the collapse, and that a subset of indicators is sufficient to characterize each ecosystem category. Lagged correlations highlighted how changes in the drivers and pressures are often not immediately manifest in the fish community structure. We also organized indicators into the DPSIR (driver-pressure-state-impact-response) management framework. This exercise illustrated that indicator categorization is contextual and not straightforward, and we advocate for use of simpler categories that clearly show what is actionable. Additional future analyses that can be performed with our newly published suite of indicators are recommended. |
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| Keywords: | DPSIR Ecosystem-based fisheries management Ecosystem indicators Fishing pressure Environmental change Lag correlations |
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