The impact of predation by marine mammals on Patagonian toothfish longline fisheries

Predatory interaction of marine mammals with longline fisheries is observed globally, leading to partial or complete loss of the catch and in some parts of the world to considerable financial loss. Depredation can also create additional unrecorded fishing mortality of a stock and has the potential to introduce bias to stock assessments. Here we aim to characterise depredation in the Patagonian toothfish (Dissostichus eleginoides) fishery around South Georgia focusing on the spatio-temporal component of these interactions. Antarctic fur seals (Arctocephalus gazella), sperm whales (Physeter macrocephalus), and orcas (Orcinus orca) frequently feed on fish hooked on longlines around South Georgia. A third of longlines encounter sperm whales, but loss of catch due to sperm whales is insignificant when compared to that due to orcas, which interact with only 5% of longlines but can take more than half of the catch in some cases. Orca depredation around South Georgia is spatially limited and focused in areas of putative migration routes, and the impact is compounded as a result of the fishery also concentrating in those areas at those times. Understanding the seasonal behaviour of orcas and the spatial and temporal distribution of “depredation hot spots” can reduce marine mammal interactions, will improve assessment and management of the stock and contribute to increased operational efficiency of the fishery. Such information is valuable in the effort to resolve the human-mammal conflict for resources

Experimental Beetle Metapopulations Respond Positively to Dynamic Landscapes and Reduced Connectivity

Interactive effects of multiple environmental factors on metapopulation dynamics have received scant attention. We designed a laboratory study to test hypotheses regarding interactive effects of factors affecting the metapopulation dynamics of red flour beetle, Tribolium castaneum. Within a four-patch landscape we modified resource level (constant and diminishing), patch connectivity (high and low) and patch configuration (static and dynamic) to conduct a 23 factorial experiment, consisting of 8 metapopulations, each with 3 replicates. For comparison, two control populations consisting of isolated and static subpopulations were provided with resources at constant or diminishing levels. Longitudinal data from 22 tri-weekly counts of beetle abundance were analyzed using Bayesian Poisson generalized linear mixed models to estimate additive and interactive effects of factors affecting abundance. Constant resource levels, low connectivity and dynamic patches yielded greater levels of adult beetle abundance. For a given resource level, frequency of colonization exceeded extinction in landscapes with dynamic patches when connectivity was low, thereby promoting greater patch occupancy. Negative density dependence of pupae on adults occurred and was stronger in landscapes with low connectivity and constant resources; these metapopulations also demonstrated greatest stability. Metapopulations in control landscapes went extinct quickly, denoting lower persistence than comparable landscapes with low connectivity. When landscape carrying capacity was constant, habitat destruction coupled with low connectivity created asynchronous local dynamics and refugia within which cannibalism of pupae was reduced. Increasing connectivity may be counter-productive and habitat destruction/recreation may be beneficial to species in some contexts

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

Draft U.S. Pacific Marine Mammal Stock Assessments: 2009

Under the 1994 amendments to the Marine Mammal Protection Act (MMPA), the National Marine Fisheries Service (NMFS) and the U.S. Fish and Wildlife Service (USFWS) are required to publish Stock Assessment Reports for all stocks of marine mammals within U.S. waters, to review new information every year for strategic stocks and every three years for non-strategic stocks, and to update the stock assessment reports when significant new information becomes available. This report presents stock assessments for 13 Pacific marine mammal stocks under NMFS jurisdiction, including 8 “strategic” stocks and 5 “non-strategic” stocks (see summary table). A new stock assessment for humpback whales in American Samoa waters is included in the Pacific reports for the first time. New or revised abundance estimates are available for 9 stocks, including Eastern North Pacific blue whales, American Samoa humpback whales, five U.S. west coast harbor porpoise stocks, the Hawaiian monk seal, and southern resident killer whales. A change in the abundance estimate of Eastern North Pacific blue whales reflects a recommendation from the Pacific Scientific Review Group to utilize mark-recapture estimates for this population, which provide a better estimate of total population size than the average of recent line-transect and mark-recapture estimates. The ‘Northern Oregon/Washington Coast Stock’ harbor porpoise stock assessment includes a name change (‘Oregon’ is appended to ‘Northern Oregon’) to reflect recent stock boundary changes. Changes in abundance estimates for the two stocks of harbor porpoise that occur in Oregon waters are the result of these boundary changes, and do not reflect biological changes in the populations. Updated information on the three stocks of false killer whales in Hawaiian waters is also included in these reports. Information on the remaining 50 Pacific region stocks will be reprinted without revision in the final 2009 reports and currently appears in the 2008 reports (Carretta et al. 2009). Stock Assessments for Alaskan marine mammals are published by the National Marine Mammal Laboratory (NMML) in a separate report. Pacific region stock assessments include those studied by the Southwest Fisheries Science Center (SWFSC, La Jolla, California), the Pacific Islands Fisheries Science Center (PIFSC, Honolulu, Hawaii), the National Marine Mammal Laboratory (NMML, Seattle, Washington), and the Northwest Fisheries Science Center (NWFSC, Seattle, WA). Northwest Fisheries Science Center staff prepared the report on the Eastern North Pacific Southern Resident killer whale. National Marine Mammal Laboratory staff prepared the Northern Oregon/Washington coast harbor porpoise stock assessment. Pacific Islands Fisheries Science Center staff prepared the report on the Hawaiian monk seal. Southwest Fisheries Science Center staff prepared stock assessments for 9 stocks. The stock assessment for the American Samoa humpback whale was prepared by staff from the Center for Coastal Studies, Hawaiian Islands Humpback National Marine Sanctuary, the Smithsonian Institution, and the Southwest Fisheries Science Center. Draft versions of the stock assessment reports were reviewed by the Pacific Scientific Review Group at the November 2008, Maui meeting. The authors also wish to thank those who provided unpublished data, especially Robin Baird and Joseph Mobley, who provided valuable information on Hawaiian cetaceans. Any omissions or errors are the sole responsibility of the authors. This is a working document and individual stock assessment reports will be updated as new information on marine mammal stocks and fisheries becomes available. Background information and guidelines for preparing stock assessment reports are reviewed in Wade and Angliss (1997). The authors solicit any new information or comments which would improve future stock assessment reports. These Stock Assessment Reports summarize information from a wide range of sources and an extensive bibliography of all sources is given in each report. We strongly urge users of this document to refer to and cite original literature sources rather than citing this report or previous Stock Assessment Reports. If the original sources are not accessible, the citation should follow the format: [Original source], as cited in [this Stock Assessment Report citation]