5 resultados para Management strategies

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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Abrupt and rapid ecosystem shifts (where major reorganizations of food-web and community structures occur), commonly termed regime shifts, are changes between contrasting and persisting states of ecosystem structure and function. These shifts have been increasingly reported for exploited marine ecosystems around the world from the North Pacific to the North Atlantic. Understanding the drivers and mechanisms leading to marine ecosystem shifts is crucial in developing adaptive management strategies to achieve sustainable exploitation of marine ecosystems. An international workshop on a comparative approach to analysing these marine ecosystem shifts was held at Hamburg University, Institute for Hydrobiology and Fisheries Science, Germany on 1-3 November 2010. Twenty-seven scientists from 14 countries attended the meeting, representing specialists from seven marine regions, including the Baltic Sea, the North Sea, the Barents Sea, the Black Sea, the Mediterranean Sea, the Bay of Biscay and the Scotian Shelf off the Canadian East coast. The goal of the workshop was to conduct the first large-scale comparison of marine ecosystem regime shifts across multiple regional areas, in order to support the development of ecosystem-based management strategies.

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The rapid increase in the number of tidal stream turbine arrays will create novel and unprecedented levels of anthropogenic activity within habitats characterized by horizontal current speeds exceeding 2 ms−1. However, the potential impacts on pursuit‐diving seabirds exploiting these tidal stream environments remain largely unknown. Identifying similarities between the fine‐scale physical features (100s of metres) suitable for array installations, and those associated with foraging pursuit‐diving seabirds, could identify which species are most vulnerable to either collisions with moving components, or displacement from these installations. A combination of vessel‐based observational surveys, Finite Volume Community Ocean Model outputs and hydroacoustic seabed surveys provided concurrent measures of foraging distributions and physical characteristics at a fine temporal (15 min) and spatial (500 m) resolution across a tidal stream environment suitable for array installations, during both breeding and non‐breeding seasons. These data sets were then used to test for associations between foraging pursuit‐diving seabirds (Atlantic puffins Fratercula arctica, black guillemots Cepphus grylle, common guillemots Uria aalge, European shags Phalacrocorax aristotelis) and physical features. These species were associated with areas of fast horizontal currents, slow horizontal currents, high turbulence, downward vertical currents and also hard–rough seabeds. The identity and strength of associations differed among species, and also within species between seasons, indicative of interspecific and intraspecific variations in habitat use. However, Atlantic puffins were associated particularly strongly with areas of fast horizontal currents during breeding seasons, and European shags with areas of rough–hard seabeds and downward vertical currents during non‐breeding seasons. Synthesis and applications. Atlantic puffins’ strong association with fast horizontal current speeds indicates that they are particularly likely to interact with installations during breeding seasons. Any post‐installation monitoring and mitigation measures should therefore focus on this species and season. The multi‐species associations with high turbulence and downward vertical currents, which often coincide with fast horizontal current speeds, also highlight useful pre‐installation mitigation measures via the omission of devices from these areas, reducing the overall likelihood of interactions. Environmental impact assessments (EIA) generally involve once‐a‐month surveys across 2‐year periods. However, the approaches used in this study show that more focussed surveys can greatly benefit management strategies aiming to reduce the likelihood of negative impacts by facilitating the development of targeted mitigation measures. It is therefore recommended that these approaches contribute towards EIA within development sites.

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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.