A spatially explicit population model of simulated fisheries impact on loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic Ocean

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Abstract

Incidental mortality from commercial fishing operations can alter the demography and distribution of affected species. Population assessments for long-lived, wide-ranging species such as sea turtles may need to include a spatial component and a consideration of the affected life stages. We used a spatial matrix population projection model to examine the impact of federally authorized incidental fishing mortality on a simulated Northwest Atlantic loggerhead sea turtle population. We projected the population for 100 years, simulating fisheries bycatch mortality through removals from the population that were directed toward specific spatial units or life stages. We kept removals constant across years for most simulations. We incorporated demographic information in the removals by using reproductive values to estimate adult-equivalent turtles, which we compared with removing individual turtles. Removals made in terms of adult equivalents had identical population impacts for all removal schemes (80% population decline after 40 years). Removals made in terms of individuals had the greatest impact if weighted toward the adult life stage (89% population decline after 40 years) and the least impact if weighted toward the youngest life stage (78% population decline after 40 years). Differences in impact between spatially directed removals were attributed to unequal stage distributions between regions. Because the population impact of loggerhead mortality depends on the affected life stage, the monitoring of population-level impacts is more reliable if authorized incidental take is specified and monitored by life stage or by adult equivalents.

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Warden, M. L., Haas, H. L., Rose, K. A., & Richards, P. M. (2015). A spatially explicit population model of simulated fisheries impact on loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic Ocean. Ecological Modelling, 299, 23–39. https://doi.org/10.1016/j.ecolmodel.2014.11.025

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