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      The Trajectory of Dispersal Research in Conservation Biology. Systematic Review

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          Abstract

          Dispersal knowledge is essential for conservation management, and demand is growing. But are we accumulating dispersal knowledge at a pace that can meet the demand? To answer this question we tested for changes in dispersal data collection and use over time. Our systematic review of 655 conservation-related publications compared five topics: climate change, habitat restoration, population viability analysis, land planning (systematic conservation planning) and invasive species. We analysed temporal changes in the: (i) questions asked by dispersal-related research; (ii) methods used to study dispersal; (iii) the quality of dispersal data; (iv) extent that dispersal knowledge is lacking, and; (v) likely consequences of limited dispersal knowledge. Research questions have changed little over time; the same problems examined in the 1990s are still being addressed. The most common methods used to study dispersal were occupancy data, expert opinion and modelling, which often provided indirect, low quality information about dispersal. Although use of genetics for estimating dispersal has increased, new ecological and genetic methods for measuring dispersal are not yet widely adopted. Almost half of the papers identified knowledge gaps related to dispersal. Limited dispersal knowledge often made it impossible to discover ecological processes or compromised conservation outcomes. The quality of dispersal data used in climate change research has increased since the 1990s. In comparison, restoration ecology inadequately addresses large-scale process, whilst the gap between knowledge accumulation and growth in applications may be increasing in land planning. To overcome apparent stagnation in collection and use of dispersal knowledge, researchers need to: (i) improve the quality of available data using new approaches; (ii) understand the complementarities of different methods and; (iii) define the value of different kinds of dispersal information for supporting management decisions. Ambitious, multi-disciplinary research programs studying many species are critical for advancing dispersal research.

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          Most cited references55

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          Spatial patterns of seed dispersal, their determinants and consequences for recruitment.

          Growing interest in spatial ecology is promoting new approaches to the study of seed dispersal, one of the key processes determining the spatial structure of plant populations. Seed-dispersion patterns vary among plant species, populations and individuals, at different distances from parents, different microsites and different times. Recent field studies have made progress in elucidating the mechanisms behind these patterns and the implications of these patterns for recruitment success. Together with the development and refinement of mathematical models, this promises a deeper, more mechanistic understanding of dispersal processes and their consequences.
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            The genetical structure of populations.

            S. Wright (1951)
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              What can genetics tell us about population connectivity?

              Genetic data are often used to assess 'population connectivity' because it is difficult to measure dispersal directly at large spatial scales. Genetic connectivity, however, depends primarily on the absolute number of dispersers among populations, whereas demographic connectivity depends on the relative contributions to population growth rates of dispersal vs. local recruitment (i.e. survival and reproduction of residents). Although many questions are best answered with data on genetic connectivity, genetic data alone provide little information on demographic connectivity. The importance of demographic connectivity is clear when the elimination of immigration results in a shift from stable or positive population growth to negative population growth. Otherwise, the amount of dispersal required for demographic connectivity depends on the context (e.g. conservation or harvest management), and even high dispersal rates may not indicate demographic interdependence. Therefore, it is risky to infer the importance of demographic connectivity without information on local demographic rates and how those rates vary over time. Genetic methods can provide insight on demographic connectivity when combined with these local demographic rates, data on movement behaviour, or estimates of reproductive success of immigrants and residents. We also consider the strengths and limitations of genetic measures of connectivity and discuss three concepts of genetic connectivity that depend upon the evolutionary criteria of interest: inbreeding connectivity, drift connectivity, and adaptive connectivity. To conclude, we describe alternative approaches for assessing population connectivity, highlighting the value of combining genetic data with capture-mark-recapture methods or other direct measures of movement to elucidate the complex role of dispersal in natural populations.
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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
                2014
                17 April 2014
                : 9
                : 4
                : e95053
                Affiliations
                [1 ]ARC Centre of Excellence for Environmental Decisions, the NERP Environmental Decisions Hub, Fenner School of Environment and Society, The Australian National University, Canberra, Australian Capital Territory, Australia
                [2 ]School of Botany, University of Melbourne, Melbourne, Victoria, Australia
                [3 ]School of Biological Sciences, University of Wollongong, Wollongong, New South Wales, Australia
                University of Waikato (National Institute of Water and Atmospheric Research), New Zealand
                Author notes

                Competing Interests: Don Driscoll is on the editorial board of PLOS ONE. This does not alter the authors' adherence to PLOS ONE editorial policies and criteria.

                Conceived and designed the experiments: DD SB PB KI PL DL AS LB EB AE ME RG RH BH GK NM BS IS DS NS NV MW. Performed the experiments: DD SB PB KI PL DL AS LB EB AE ME RG RH BH GK NM BS IS DS NS NV MW. Analyzed the data: DD. Wrote the paper: DD SB PB KI PL DL AS LB EB AE ME RG RH BH GK NM BS IS DS NS NV MW.

                Article
                PONE-D-13-52898
                10.1371/journal.pone.0095053
                3990620
                24743447
                0b66ccbc-f855-4ace-bc72-77a503d0f182
                Copyright @ 2014

                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
                : 18 December 2013
                : 23 March 2014
                Page count
                Pages: 18
                Funding
                ARC Center of Excellence for Environmental Decisions, National Environmental Research Program Environmental Decisions 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 and Life Sciences
                Ecology
                Biodiversity
                Ecosystems
                Spatial and Landscape Ecology
                Population Biology
                Population Dynamics
                Metapopulation Dynamics
                Computer and Information Sciences
                Earth Sciences
                Atmospheric Science
                Climatology
                Climate Change
                Ecology and Environmental Sciences
                Conservation Science
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Science Policy
                Social Sciences

                Uncategorized
                Uncategorized

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