Institution
National Marine Fisheries Service
Government•Silver Spring, Maryland, United States•
About: National Marine Fisheries Service is a government organization based out in Silver Spring, Maryland, United States. It is known for research contribution in the topics: Population & Fisheries management. The organization has 3949 authors who have published 7053 publications receiving 305073 citations. The organization is also known as: NOAA Fisheries & NOAA National Marine Fisheries Service.
Topics: Population, Fisheries management, Oncorhynchus, Fishing, Bycatch
Papers published on a yearly basis
Papers
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TL;DR: The steps of model selection are outlined and several ways that it is now being implemented are highlighted, so that researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.
Abstract: Recently, researchers in several areas of ecology and evolution have begun to change the way in which they analyze data and make biological inferences. Rather than the traditional null hypothesis testing approach, they have adopted an approach called model selection, in which several competing hypotheses are simultaneously confronted with data. Model selection can be used to identify a single best model, thus lending support to one particular hypothesis, or it can be used to make inferences based on weighted support from a complete set of competing models. Model selection is widely accepted and well developed in certain fields, most notably in molecular systematics and mark-recapture analysis. However, it is now gaining support in several other areas, from molecular evolution to landscape ecology. Here, we outline the steps of model selection and highlight several ways that it is now being implemented. By adopting this approach, researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.
3,489 citations
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University of Miami1, Wildlife Conservation Society2, Marine Sciences Research Center3, Scripps Institution of Oceanography4, University of Washington5, University of Maryland Center for Environmental Science6, National Marine Fisheries Service7, University of California, Santa Cruz8, Royal School of Mines9, National Research Council10, Commonwealth Scientific and Industrial Research Organisation11
TL;DR: Pikitch et al. as discussed by the authors describe the potential benefits of implementation of ecosystem-based fishery management that, in their view, far outweigh the difficulties of making the transition from a management system based on maximizing individual species.
Abstract: Ecosystem-based fishery management (EBFM) is a new direction for fishery management, essentially reversing the order of management priorities so that management starts with the ecosystem rather than a target species. EBFM aims to sustain healthy marine ecosystems and the fisheries they support.
Pikitch
et al .
describe the potential benefits of implementation of EBFM that, in their view, far outweigh the difficulties of making the transition from a management system based on maximizing individual species.
2,011 citations
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TL;DR: Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys, the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software.
Abstract: Summary
1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance.
2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use.
3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated.
4. A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance.
5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap.
6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software.
7.Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of-the-art software that implements these methods is described that makes the methods accessible to practising ecologists.
1,878 citations
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TL;DR: NeEstimator v2 includes three single‐sample estimators (updated versions of the linkage disequilibrium and heterozygote‐excess methods, and a new method based on molecular coancestry), as well as the two‐sample (moment‐based temporal) method.
Abstract: NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.
1,515 citations
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Commonwealth Scientific and Industrial Research Organisation1, University of Queensland2, Museum für Naturkunde3, University of Erlangen-Nuremberg4, Nelson Mandela Metropolitan University5, University of the Sunshine Coast6, Edith Cowan University7, Aberystwyth University8, Technical University of Denmark9, University of North Carolina at Chapel Hill10, Spanish National Research Council11, University of Western Australia12, University of California, Santa Barbara13, University of British Columbia14, University of Texas at Austin15, University of Plymouth16, National Marine Fisheries Service17
TL;DR: This article synthesized all available studies of the consistency of marine ecological observations with expectations under climate change This yielded a meta-database of 1,735 marine biological responses for which either regional or global climate change was considered as a driver.
Abstract: Research that combines all available studies of biological responses to regional and global climate change shows that 81–83% of all observations were consistent with the expected impacts of climate change These findings were replicated across taxa and oceanic basins Past meta-analyses of the response of marine organisms to climate change have examined a limited range of locations1,2, taxonomic groups2,3,4 and/or biological responses5,6 This has precluded a robust overview of the effect of climate change in the global ocean Here, we synthesized all available studies of the consistency of marine ecological observations with expectations under climate change This yielded a meta-database of 1,735 marine biological responses for which either regional or global climate change was considered as a driver Included were instances of marine taxa responding as expected, in a manner inconsistent with expectations, and taxa demonstrating no response From this database, 81–83% of all observations for distribution, phenology, community composition, abundance, demography and calcification across taxa and ocean basins were consistent with the expected impacts of climate change Of the species responding to climate change, rates of distribution shifts were, on average, consistent with those required to track ocean surface temperature changes Conversely, we did not find a relationship between regional shifts in spring phenology and the seasonality of temperature Rates of observed shifts in species’ distributions and phenology are comparable to, or greater, than those for terrestrial systems
1,504 citations
Authors
Showing all 3963 results
Name | H-index | Papers | Citations |
---|---|---|---|
Thomas N. Williams | 132 | 1145 | 95109 |
Thomas P. Quinn | 96 | 455 | 33939 |
Michael P. Carey | 90 | 463 | 27005 |
Rebecca Fisher | 86 | 255 | 50260 |
Peter Kareiva | 84 | 260 | 33352 |
Daniel E. Schindler | 69 | 222 | 18359 |
Robin S. Waples | 69 | 195 | 22752 |
Ronald W. Hardy | 64 | 202 | 14145 |
Kenneth E. Sherman | 64 | 348 | 15934 |
André E. Punt | 63 | 400 | 16532 |
Jason S. Link | 60 | 217 | 12799 |
William G. Sunda | 57 | 103 | 13933 |
Steven J. Bograd | 57 | 220 | 12511 |
Walton W. Dickhoff | 56 | 130 | 8507 |
Jay Barlow | 55 | 241 | 9939 |