Bibliography - K. Kearney

1. Cheung, W., V. Lam, Jorge Sarmiento, K. Kearney, R. Watson, D. Zeller, and D. Pauly, 2009: Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Global Change Biology, doi:10.1111/j.1365-2486.2009.01995.x
   [ Abstract ]

   Previous projection of climate change impacts on global food supply focuses solely on production from terrestrial biomes, ignoring the large contribution of animal protein from marine capture fisheries. Here, we project changes in global catch potential for 1,066 species of exploited marine fish and invertebrates from 2005 to 2055 under climate change scenarios. We show that climate change may lead to large scale re-distribution of global catch potential, with an average of 30 - 70% increase in high latitude regions and a drop of up to 40% in the tropics. Moreover, maximum catch potential declines considerably in the southward margins of semi-enclosed seas while it increases in poleward tips of continental shelf margins. Such changes are most apparent in the Pacific Ocean. Among the 20 most important fishing Exclusive Economic Zone (EEZ) regions in terms of their total landings, EEZ regions with the highest increase in catch potential by 2055 include Norway, Greenland, US (Alaska) and Russia (Asia). On the contrary, EEZ regions with the biggest loss in maximum catch potential include Indonesia, USA (excluding Alaska and Hawaii), Chile, and China. Many highly impacted regions, particularly those in the tropics, are socio-economically vulnerable to these changes. 36 Thus, our results indicate the need to develop adaptation policy that could minimize climate change impacts through fisheries. The study also provides information which may be useful to evaluate fisheries management options under climate change.

2. Cheung, W., V. Lam, Jorge Sarmiento, K. Kearney, R. Watson, and D. Pauly, 2009: Projecting global marine biodiversity impacts under climate change scenarios. Fish and Fisheries, doi:10.1111/j.1467-2979.2008.00315.x
   [ Abstract ]

   Climate change can impact the pattern of marine biodiversity through changes in species’ distributions. However, global studies on climate change impacts on ocean biodiversity have not been performed so far. Our paper aims to investigate the global patterns of such impacts by projecting the distributional ranges of a sample of 1066 exploited marine fish and invertebrates for 2050 using a newly developed dynamic bioclimate envelope model. Our projections show that climate change may lead to numerous local extinction in the sub-polar regions, the tropics and semi-enclosed seas. Simultaneously, species invasion is projected to be most intense in the Arctic and the Southern Ocean. Together, they result in dramatic species turnovers of over 60% of the present biodiversity, implying ecological disturbances that potentially disrupt ecosystem services. Our projections can be viewed as a set of hypothesis for future analytical and empirical studies.

3. Christensen, Villy, Carl J. Walters, Robert Ahrens, Jacqueline Alder, K. Kearney, and Jorge Sarmiento, 2009: Database-driven models of the world's Large Marine Ecosystems. Ecological Modelling, 220, doi:10.1016/j.ecolmodel.2009.04.041 1984-1996
   [ Abstract ]

   We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.

Direct link to page: http://cmi.princeton.edu/bibliography/results.php?author=3580