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      Bias and information in biological records : Bias and information in biological records

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      Biological Journal of the Linnean Society
      Wiley-Blackwell

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          ESTIMATING ABUNDANCE FROM REPEATED PRESENCE–ABSENCE DATA OR POINT COUNTS

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            Comparative losses of British butterflies, birds, and plants and the global extinction crisis.

            There is growing concern about increased population, regional, and global extinctions of species. A key question is whether extinction rates for one group of organisms are representative of other taxa. We present a comparison at the national scale of population and regional extinctions of birds, butterflies, and vascular plants from Britain in recent decades. Butterflies experienced the greatest net losses, disappearing on average from 13% of their previously occupied 10-kilometer squares. If insects elsewhere in the world are similarly sensitive, the known global extinction rates of vertebrate and plant species have an unrecorded parallel among the invertebrates, strengthening the hypothesis that the natural world is experiencing the sixth major extinction event in its history.
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              Unified maximum likelihood estimates for closed capture-recapture models using mixtures.

              S Pledger (2000)
              Agresti (1994, Biometrics 50, 494-500) and Norris and Pollock (1996a, Biometrics 52, 639-649) suggested using methods of finite mixtures to partition the animals in a closed capture-recapture experiment into two or more groups with relatively homogeneous capture probabilities. This enabled them to fit the models Mh, Mbh (Norris and Pollock), and Mth (Agresti) of Otis et al. (1978, Wildlife Monographs 62, 1-135). In this article, finite mixture partitions of animals and/or samples are used to give a unified linear-logistic framework for fitting all eight models of Otis et al. by maximum likelihood. Likelihood ratio tests are available for model comparisons. For many data sets, a simple dichotomy of animals is enough to substantially correct for heterogeneity-induced bias in the estimation of population size, although there is the option of fitting more than two groups if the data warrant it.
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                Author and article information

                Journal
                Biological Journal of the Linnean Society
                Biol J Linn Soc Lond
                Wiley-Blackwell
                00244066
                July 2015
                July 2015
                : 115
                : 3
                : 522-531
                Article
                10.1111/bij.12532
                e3bf555c-3716-452c-9f6d-9318cbf1f4c3
                © 2015

                http://doi.wiley.com/10.1002/tdm_license_1

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