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      Effects of Late-Cenozoic Glaciation on Habitat Availability in Antarctic Benthic Shrimps (Crustacea: Decapoda: Caridea)

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          Abstract

          Marine invertebrates inhabiting the high Antarctic continental shelves are challenged by disturbance of the seafloor by grounded ice, low but stable water temperatures and variable food availability in response to seasonal sea-ice cover. Though a high diversity of life has successfully adapted to such conditions, it is generally agreed that during the Last Glacial Maximum (LGM) the large-scale cover of the Southern Ocean by multi-annual sea ice and the advance of the continental ice sheets across the shelf faced life with conditions, exceeding those seen today by an order of magnitude. Conditions prevailing at the LGM may have therefore acted as a bottleneck event to both the ecology as well as genetic diversity of today's fauna. Here, we use for the first time specific Species Distribution Models (SDMs) for marine arthropods of the Southern Ocean to assess effects of habitat contraction during the LGM on the three most common benthic caridean shrimp species that exhibit a strong depth zonation on the Antarctic continental shelf. While the shallow-water species Chorismus antarcticus and Notocrangon antarcticus were limited to a drastically reduced habitat during the LGM, the deep-water shrimp Nematocarcinus lanceopes found refuge in the Southern Ocean deep sea. The modeling results are in accordance with genetic diversity patterns available for C. antarcticus and N. lanceopes and support the hypothesis that habitat contraction at the LGM resulted in a loss of genetic diversity in shallow water benthos.

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          Measuring the accuracy of diagnostic systems.

          J Swets (1988)
          Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.
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            The salinity, temperature, and delta18O of the glacial deep ocean.

            J Adkins (2002)
            We use pore fluid measurements of the chloride concentration and the oxygen isotopic composition from Ocean Drilling Program cores to reconstruct salinity and temperature of the deep ocean during the Last Glacial Maximum (LGM). Our data show that the temperatures of the deep Pacific, Southern, and Atlantic oceans during the LGM were relatively homogeneous and within error of the freezing point of seawater at the ocean's surface. Our chloride data show that the glacial stratification was dominated by salinity variations, in contrast with the modern ocean, for which temperature plays a primary role. During the LGM the Southern Ocean contained the saltiest water in the deep ocean. This reversal of the modern salinity contrast between the North and South Atlantic implies that the freshwater budget at the poles must have been quite different. A strict conversion of mean salinity at the LGM to equivalent sea-level change yields a value in excess of 140 meters. However, the storage of fresh water in ice shelves and/or groundwater reserves implies that glacial salinity is a poor predictor of mean sea level.
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              Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data.

              Most methods for modeling species distributions from occurrence records require additional data representing the range of environmental conditions in the modeled region. These data, called background or pseudo-absence data, are usually drawn at random from the entire region, whereas occurrence collection is often spatially biased toward easily accessed areas. Since the spatial bias generally results in environmental bias, the difference between occurrence collection and background sampling may lead to inaccurate models. To correct the estimation, we propose choosing background data with the same bias as occurrence data. We investigate theoretical and practical implications of this approach. Accurate information about spatial bias is usually lacking, so explicit biased sampling of background sites may not be possible. However, it is likely that an entire target group of species observed by similar methods will share similar bias. We therefore explore the use of all occurrences within a target group as biased background data. We compare model performance using target-group background and randomly sampled background on a comprehensive collection of data for 226 species from diverse regions of the world. We find that target-group background improves average performance for all the modeling methods we consider, with the choice of background data having as large an effect on predictive performance as the choice of modeling method. The performance improvement due to target-group background is greatest when there is strong bias in the target-group presence records. Our approach applies to regression-based modeling methods that have been adapted for use with occurrence data, such as generalized linear or additive models and boosted regression trees, and to Maxent, a probability density estimation method. We argue that increased awareness of the implications of spatial bias in surveys, and possible modeling remedies, will substantially improve predictions of species distributions.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                27 September 2012
                : 7
                : 9
                : e46283
                Affiliations
                [1 ]Zoologisches Forschungsmuseum Alexander Koenig, Bonn, Germany
                [2 ]Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton, United Kingdom
                [3 ]Leigh Marine Laboratory, University of Auckland, Auckland, New Zealand
                [4 ]Deutsches Zentrum für Marine Biodiversitätsforschung, Senckenberg am Meer, Wilhelmshaven, Germany
                The Australian National University, Australia
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JD. Performed the experiments: JD DR. Analyzed the data: JD ST MJR. Contributed reagents/materials/analysis tools: JD DR ST ZB MJR. Wrote the paper: JD DR ST ZB MJR.

                Article
                PONE-D-12-17267
                10.1371/journal.pone.0046283
                3459913
                23029463
                513268d9-48e4-4a0d-87f1-ad2cf156dd82
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 June 2012
                : 29 August 2012
                Page count
                Pages: 9
                Funding
                This study was funded by the German Research Foundation (DFG, RA-1688-2). The Ross Sea specimens data collected by the cruise TAN0802 (IPY-CAML Voyage), made available through the New Zealand International Polar Year-Census of Antarctic Marine Life Project (Phase 1: So001IPY; Phase 2: IPY2007-01) was funded by the New Zealand Government. The authors gratefully acknowledge project governance by the Ministry of Fisheries Science Team and the Ocean Survey 20/20 CAML Advisory Group. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Ecology
                Ecosystems
                Ecosystem Modeling
                Biodiversity
                Biogeography
                Global Change Ecology
                Marine Ecology
                Paleoecology
                Marine Biology
                Population Biology
                Population Genetics
                Haplotypes
                Earth Sciences
                Glaciology
                Ice Shelf
                Polynyas
                Marine and Aquatic Sciences

                Uncategorized
                Uncategorized

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