Oceans and Coasts Program

Arlington, VA, United States

Oceans and Coasts Program

Arlington, VA, United States
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Brannstrom A.,Umeå University | Brannstrom A.,International Institute For Applied Systems Analysis | Johansson J.,International Institute For Applied Systems Analysis | Johansson J.,Lund University | And 6 more authors.
Evolutionary Ecology Research | Year: 2012

Background: The complexity and dynamical nature of community interactions make modelling a useful tool for understanding how communities develop over time and how they respond to external perturbations. Large community-evolution models (LCEMs) are particularly promising, since they can address both ecological and evolutionary questions, and can give rise to richly structured and diverse model communities. Questions: Which types of models have been used to study community structure and what are their key features and limitations? How do adaptations and/or invasions affect community formation? Which mechanisms promote diverse and stable communities? What are the implications of LCEMs for management and conservation? What are the key challenges for future research? Models considered: Static models of community structure, demographic community models, and small and large community-evolution models. Conclusions: Large community-evolution models encompass a variety of modelled traits and interactions, demographic dynamics, and evolutionary dynamics. They are able to reproduce empirical community structures. They have already generated new insights, such as the dual role of competition, which limits diversity through competitive exclusion yet facilitates diversity through speciation. Other critical factors determining eventual community structure are the shape of trade-off functions, inclusion of adaptive foraging, and energy availability. A particularly interesting feature of LCEMs is that these models not only help to contrast outcomes of community formation via species assembly with those of community formation via gradual evolution and speciation, but that they can furthermore unify the underlying invasion processes and evolutionary processes into a single framework. © 2012 Åke Brännström.


Grizzle R.E.,University of New Hampshire | Ward L.G.,University of New Hampshire | Fredriksson D.W.,U.S. Naval Academy | Irish J.D.,University of New Hampshire | And 6 more authors.
Marine Pollution Bulletin | Year: 2014

The seafloor at an open ocean finfish aquaculture facility in the western Gulf of Maine, USA was monitored from 1999 to 2008 by sampling sites inside a predicted impact area modeled by oceanographic conditions and fecal and food settling characteristics, and nearby reference sites. Univariate and multivariate analyses of benthic community measures from box core samples indicated minimal or no significant differences between impact and reference areas. These findings resulted in development of an adaptive monitoring protocol involving initial low-cost methods that required more intensive and costly efforts only when negative impacts were initially indicated. The continued growth of marine aquaculture is dependent on further development of farming methods that minimize negative environmental impacts, as well as effective monitoring protocols. Adaptive monitoring protocols, such as the one described herein, coupled with mathematical modeling approaches, have the potential to provide effective protection of the environment while minimize monitoring effort and costs. © 2014 Elsevier Ltd.


PubMed | MER Corporation, U.S. Naval Academy, University of New Hampshire, Oceans and Coasts Program and University of Florida
Type: Journal Article | Journal: Marine pollution bulletin | Year: 2014

The seafloor at an open ocean finfish aquaculture facility in the western Gulf of Maine, USA was monitored from 1999 to 2008 by sampling sites inside a predicted impact area modeled by oceanographic conditions and fecal and food settling characteristics, and nearby reference sites. Univariate and multivariate analyses of benthic community measures from box core samples indicated minimal or no significant differences between impact and reference areas. These findings resulted in development of an adaptive monitoring protocol involving initial low-cost methods that required more intensive and costly efforts only when negative impacts were initially indicated. The continued growth of marine aquaculture is dependent on further development of farming methods that minimize negative environmental impacts, as well as effective monitoring protocols. Adaptive monitoring protocols, such as the one described herein, coupled with mathematical modeling approaches, have the potential to provide effective protection of the environment while minimize monitoring effort and costs.

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