Institution
Wildfowl & Wetlands Trust
Nonprofit•
About: Wildfowl & Wetlands Trust is a based out in . It is known for research contribution in the topics: Population & Waterfowl. The organization has 159 authors who have published 297 publications receiving 10436 citations.
Topics: Population, Waterfowl, Threatened species, Branta, Branta leucopsis
Papers published on a yearly basis
Papers
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Michael R. Hoffmann1, Craig Hilton-Taylor2, Ariadne Angulo2, Monika Böhm3 +170 more•Institutions (81)
TL;DR: Though the threat of extinction is increasing, overall declines would have been worse in the absence of conservation, and current conservation efforts remain insufficient to offset the main drivers of biodiversity loss in these groups.
Abstract: Using data for 25,780 species categorized on the International Union for Conservation of Nature Red List, we present an assessment of the status of the world's vertebrates. One-fifth of species are classified as Threatened, and we show that this figure is increasing: On average, 52 species of mammals, birds, and amphibians move one category closer to extinction each year. However, this overall pattern conceals the impact of conservation successes, and we show that the rate of deterioration would have been at least one-fifth again as much in the absence of these. Nonetheless, current conservation efforts remain insufficient to offset the main drivers of biodiversity loss in these groups: agricultural expansion, logging, overexploitation, and invasive alien species.
1,333 citations
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TL;DR: This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.
Abstract: The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.
1,210 citations
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TL;DR: It is suggested that ecological barriers and particularly human disturbance likely constrain the capacity of herbivorous waterfowl to track the green wave in some regions, highlighting key challenges in conserving migratory birds.
Abstract: Tracking seasonally changing resources is regarded as a widespread proximate mechanism underpinning animal migration. Migrating herbivores, for example, are hypothesized to track seasonal foliage dynamics over large spatial scales. Previous investigations of this green wave hypothesis involved few species and limited geographical extent, and used conventional correlation that cannot disentangle alternative correlated effects. Here, we introduce stochastic simulations to test this hypothesis using 222 individual spring migration episodes of 14 populations of ten species of geese, swans and dabbling ducks throughout Europe, East Asia, and North America. We find that the green wave cannot be considered a ubiquitous driver of herbivorous waterfowl spring migration, as it explains observed migration patterns of only a few grazing populations in specific regions. We suggest that ecological barriers and particularly human disturbance likely constrain the capacity of herbivorous waterfowl to track the green wave in some regions, highlighting key challenges in conserving migratory birds.
654 citations
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Conservation International1, Griffith University2, Carleton University3, International Union for Conservation of Nature and Natural Resources4, International Institute of Minnesota5, United States Geological Survey6, UNESCO-IHE Institute for Water Education7, University of Washington8, Cardiff University9, Wildfowl & Wetlands Trust10, Free University of Berlin11
TL;DR: In this paper, the authors present an emergency recovery plan to bend the curve of freshwater biodiversity loss, which includes accelerating implementation of environmental flows; improving water quality; protecting and restoring critical habitats; managing the exploitation of freshwater ecosystem resources, especially species and riverine aggregates; preventing and controlling nonnative species invasions; and safeguarding and restoring river connectivity.
Abstract: Despite their limited spatial extent, freshwater ecosystems host remarkable biodiversity, including one-third of all vertebrate species. This biodiversity is declining dramatically: Globally, wetlands are vanishing three times faster than forests, and freshwater vertebrate populations have fallen more than twice as steeply as terrestrial or marine populations. Threats to freshwater biodiversity are well documented but coordinated action to reverse the decline is lacking. We present an Emergency Recovery Plan to bend the curve of freshwater biodiversity loss. Priority actions include accelerating implementation of environmental flows; improving water quality; protecting and restoring critical habitats; managing the exploitation of freshwater ecosystem resources, especially species and riverine aggregates; preventing and controlling nonnative species invasions; and safeguarding and restoring river connectivity. We recommend adjustments to targets and indicators for the Convention on Biological Diversity and the Sustainable Development Goals and roles for national and international state and nonstate actors.
420 citations
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University of Salford1, University of Queensland2, University of Western Australia3, Queensland University of Technology4, University of Lausanne5, Wildfowl & Wetlands Trust6, Canadian Parks and Wilderness Society7, University of Évora8, University of Freiburg9, University of Melbourne10, University of Plymouth11, Mississippi State University12, Australian Institute of Marine Science13, Griffith University14, Zurich University of Applied Sciences/ZHAW15, University of British Columbia16, Duke University17, Finnish Environment Institute18, University of Adelaide19, King Fahd University of Petroleum and Minerals20, IFREMER21, University of California, Davis22, Technical University of Madrid23, National Institute of Water and Atmospheric Research24, Memorial University of Newfoundland25, Royal Society for the Protection of Birds26, University of Kansas27, University of California, Merced28, University of the Sunshine Coast29, Nelson Mandela Metropolitan University30, Swedish University of Agricultural Sciences31, University of Grenoble32, Oregon State University33, University of Toronto34, Gulf of Maine Research Institute35, University of Georgia36, Newcastle University37, Parks Canada38, Humboldt University of Berlin39
TL;DR: Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.
Abstract: Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world However, limited understanding of the accuracy and precision of models transferred to novel conditions (their ‘transferability’) undermines confidence in their predictions Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions
358 citations
Authors
Showing all 159 results
Name | H-index | Papers | Citations |
---|---|---|---|
James A. Robinson | 84 | 362 | 76056 |
John L. Quinn | 78 | 450 | 20877 |
Andy J. Green | 55 | 288 | 13152 |
Stephen C. Votier | 48 | 126 | 7106 |
Deborah J. Pain | 46 | 99 | 6717 |
Chris Carbone | 43 | 109 | 9322 |
Nick C. Davidson | 33 | 80 | 10426 |
Geoff M. Hilton | 32 | 88 | 3323 |
Myrfyn Owen | 31 | 50 | 2900 |
Jeffrey M. Black | 28 | 96 | 3409 |
Mark Everard | 28 | 167 | 3054 |
Andre S. Gilburn | 21 | 46 | 1258 |
Eileen C. Rees | 17 | 65 | 955 |
Kevin A. Wood | 17 | 57 | 961 |
Kendrew Colhoun | 16 | 25 | 1259 |