Showing papers by "Ian D. Jonsen published in 2011"

Tracking apex marine predator movements in a dynamic ocean

Abstract: Pelagic marine predators face unprecedented challenges and uncertain futures. Overexploitation and climate variability impact the abundance and distribution of top predators in ocean ecosystems. Improved understanding of ecological patterns, evolutionary constraints and ecosystem function is critical for preventing extinctions, loss of biodiversity and disruption of ecosystem services. Recent advances in electronic tagging techniques have provided the capacity to observe the movements and long-distance migrations of animals in relation to ocean processes across a range of ecological scales. Tagging of Pacific Predators, a field programme of the Census of Marine Life, deployed 4,306 tags on 23 species in the North Pacific Ocean, resulting in a tracking data set of unprecedented scale and species diversity that covers 265,386 tracking days from 2000 to 2009. Here we report migration pathways, link ocean features to multispecies hotspots and illustrate niche partitioning within and among congener guilds. Our results indicate that the California Current large marine ecosystem and the North Pacific transition zone attract and retain a diverse assemblage of marine vertebrates. Within the California Current large marine ecosystem, several predator guilds seasonally undertake north-south migrations that may be driven by oceanic processes, species-specific thermal tolerances and shifts in prey distributions. We identify critical habitats across multinational boundaries and show that top predators exploit their environment in predictable ways, providing the foundation for spatial management of large marine ecosystems.

Identifying nonproportionality of fishery- independent survey data to estimate population trends and assess recovery potential for cusk (Brosme brosme)

Abstract: Cusk (Brosme brosme) was designated as ''threatened'' by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) in 2003, based on an estimated 93% decline between 1970 and 2001 from the Fisheries and Oceans Canada (DFO) Scotian Shelf summer bottom trawl survey index. We combined this index with a fishery-dependent longline index in a Bayesian surplus production state-space model to estimate population trends and the recovery potential of western Scotian Shelf cusk. We tested for index nonproportionality using a power curve function in the observation model and identified potential hyperdepletion for cusk in the trawl survey index. We estimate a 59% decline in cusk bio- mass between 1970 and 2001, and a 64% decline from 1970 to 2007. Although population projections indicate the current landing limit should lead to population recovery, robustness tests suggest the biomass projections and recovery time lines are overly optimistic. Simulations showed that incorporating multiple indices increases power to recapture model parame- ters and failure to account for index nonproportionality results in biased parameter estimates. We suggest that nonpropor- tionality of fishery-independent indices must be considered when determining the population status of data-poor species. Resume´ : Le brosme (Brosme brosme )aetedesigneespece menacee par le Comitesur la situation des especes en peril

Mining non-taxonomic concept pairs from unstructured text: a concept correlation search framework

Abstract: Ontology consists of concepts, taxonomic relations and non-taxonomic relations. The majority of the ontology learning tools focus on discovering concepts and taxonomic relations. Very little effort has been put on discovering non-taxonomic relations. In this paper, we present a concept correlation search framework to discover non-taxonomic concept pairs from unstructured text. Our framework features the (a) extraction of correlated concepts beyond ordinary search window size of a single sentence; (b) use of lift as interestingness measure for association rule mining; (c) harness of 2itemsets association rules from nitemsets association rules where n>2; and (d) identification of non-taxonomic concept pairs based on existing domain ontology. The proposed framework has been tested with the Fisheries Oceanography journals, and the results demonstrate significant improvements over traditional association rule approach in search of non-taxonomic concept pairs.