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Marine biodiversity of the United States (U.S.) is extensively documented, but data assembled by the United States National Committee for the Census of Marine Life demonstrate that even the most complete taxonomic inventories are based on records scattered in space and time. The best-known taxa are those of commercial importance. Body size is directly correlated with knowledge of a species, and knowledge also diminishes with distance from shore and depth. Measures of biodiversity other than species diversity, such as ecosystem and genetic diversity, are poorly documented. Threats to marine biodiversity in the U.S. are the same as those for most of the world: overexploitation of living resources; reduced water quality; coastal development; shipping; invasive species; rising temperature and concentrations of carbon dioxide in the surface ocean, and other changes that may be consequences of global change, including shifting currents; increased number and size of hypoxic or anoxic areas; and increased number and duration of harmful algal blooms. More information must be obtained through field and laboratory research and monitoring that involve innovative sampling techniques (such as genetics and acoustics), but data that already exist must be made accessible. And all data must have a temporal component so trends can be identified. As data are compiled, techniques must be developed to make certain that scales are compatible, to combine and reconcile data collected for various purposes with disparate gear, and to automate taxonomic changes. Information on biotic and abiotic elements of the environment must be interactively linked. Impediments to assembling existing data and collecting new data on marine biodiversity include logistical problems as well as shortages in finances and taxonomic expertise.
Marine biodiversity of the United States (U.S.) is extensively documented, but data assembled by the United States National Committee for the Census of Marine Life demonstrate that even the most complete taxonomic inventories are based on records scattered in space and time. The best-known taxa are those of commercial importance. Body size is directly correlated with knowledge of a species, and knowledge also diminishes with distance from shore and depth. Measures of biodiversity other than species diversity, such as ecosystem and genetic diversity, are poorly documented. Threats to marine biodiversity in the U.S. are the same as those for most of the world: overexploitation of living resources; reduced water quality; coastal development; shipping; invasive species; rising temperature and concentrations of carbon dioxide in the surface ocean, and other changes that may be consequences of global change, including shifting currents; increased number and size of hypoxic or anoxic areas; and increased number and duration of harmful algal blooms. More information must be obtained through field and laboratory research and monitoring that involve innovative sampling techniques (such as genetics and acoustics), but data that already exist must be made accessible. And all data must have a temporal component so trends can be identified. As data are compiled, techniques must be developed to make certain that scales are compatible, to combine and reconcile data collected for various purposes with disparate gear, and to automate taxonomic changes. Information on biotic and abiotic elements of the environment must be interactively linked. Impediments to assembling existing data and collecting new data on marine biodiversity include logistical problems as well as shortages in finances and taxonomic expertise.
An age- and sex-structured population dynamics model is fitted using Bayesian methods to data on the catches and abundance estimates for the Eastern North Pacific (ENP) stock of gray whales. The prior distributions used for these analyses incorporate revised estimates of abundance for ENP gray whales and account explicitly for the drop in abundance caused by the 1999–2000 mortality event. A series of analyses are conducted to evaluate the sensitivity of the results to different assumptions. The model fits the available data adequately, but, as in previous assessments, the measures of uncertainty associated with the survey-based abundance estimates are found to be negatively biased. The data support the inclusion of the 1999–2000 mortality event in the model, and accounting for this event leads to greater uncertainty regarding the current status of the resource. The baseline analysis estimates the ENP gray whale population to be above the maximum sustainable yield level (MSYL) with high probability (0.884). The posterior mean for the ratio of 2009 (1+) abundance to MSYL is 1.29 (with a posterior median of 1.37 and a 90% probability interval of 0.68–1.51). These results are consistent across all the model runs conducted. The baseline model also estimates the 2009 ENP gray whale population size (posterior mean of 20,366) to be at 85% of its carrying capacity (posterior mean of 25,808), and this is also consistent across all the model runs. The baseline model estimate of the maximum rate of increase, λmax, is 1.062 which, while high, is nevertheless within the range of estimates obtained for other baleen whales.
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