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  • 1
    Publication Date: 2016-01-14
    Description: Article Marine protected areas (MPAs) are established to conserve species, but the extent to which they also conserve evolutionary history is not clear. Here, Mouillot et al . show that for tropical corals and fish, the current global MPA network secures only 1.7 and 17.6% of phylogenetic diversity, respectively. Nature Communications doi: 10.1038/ncomms10359 Authors: D. Mouillot, V. Parravicini, D. R. Bellwood, F. Leprieur, D. Huang, P. F. Cowman, C. Albouy, T. P. Hughes, W. Thuiller, F. Guilhaumon
    Electronic ISSN: 2041-1723
    Topics: Biology , Chemistry and Pharmacology , Natural Sciences in General , Physics
    Published by Springer Nature
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  • 2
    Publication Date: 2016-02-05
    Description: Article Knowing which species traits may confer resilience to human-mediated stressors will help predict future impacts on biodiversity. Here, Mellin et al . show that large bodied fish with small geographic ranges are disproportionately affected by the negative impacts of human disturbance and climate variability. Nature Communications doi: 10.1038/ncomms10491 Authors: C. Mellin, D. Mouillot, M. Kulbicki, T. R. McClanahan, L. Vigliola, C. J. A. Bradshaw, R. E. Brainard, P. Chabanet, G. J. Edgar, D. A. Fordham, A. M. Friedlander, V. Parravicini, A. M. M. Sequeira, R. D. Stuart-Smith, L. Wantiez, M. J. Caley
    Electronic ISSN: 2041-1723
    Topics: Biology , Chemistry and Pharmacology , Natural Sciences in General , Physics
    Published by Springer Nature
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  • 3
    Publication Date: 2015-01-22
    Description: Climate-induced coral bleaching is among the greatest current threats to coral reefs, causing widespread loss of live coral cover. Conditions under which reefs bounce back from bleaching events or shift from coral to algal dominance are unknown, making it difficult to predict and plan for differing reef responses under climate change. Here we document and predict long-term reef responses to a major climate-induced coral bleaching event that caused unprecedented region-wide mortality of Indo-Pacific corals. Following loss of 〉90% live coral cover, 12 of 21 reefs recovered towards pre-disturbance live coral states, while nine reefs underwent regime shifts to fleshy macroalgae. Functional diversity of associated reef fish communities shifted substantially following bleaching, returning towards pre-disturbance structure on recovering reefs, while becoming progressively altered on regime shifting reefs. We identified threshold values for a range of factors that accurately predicted ecosystem response to the bleaching event. Recovery was favoured when reefs were structurally complex and in deeper water, when density of juvenile corals and herbivorous fishes was relatively high and when nutrient loads were low. Whether reefs were inside no-take marine reserves had no bearing on ecosystem trajectory. Although conditions governing regime shift or recovery dynamics were diverse, pre-disturbance quantification of simple factors such as structural complexity and water depth accurately predicted ecosystem trajectories. These findings foreshadow the likely divergent but predictable outcomes for reef ecosystems in response to climate change, thus guiding improved management and adaptation.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Graham, Nicholas A J -- Jennings, Simon -- MacNeil, M Aaron -- Mouillot, David -- Wilson, Shaun K -- England -- Nature. 2015 Feb 5;518(7537):94-7. doi: 10.1038/nature14140. Epub 2015 Jan 14.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland 4811 Australia. ; 1] Centre for Environment, Fisheries and Aquaculture Science, Pakefield Road, Lowestoft NR33 OHT, UK [2] School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK. ; 1] Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland 4811 Australia [2] Australian Institute of Marine Science, PMB 3 Townsville MC, Townsville, Queensland 4810, Australia. ; 1] Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland 4811 Australia [2] ECOSYM, UMR CNRS-UM2 5119, Universite Montpellier 2, 34095 Montpellier Cedex, France. ; 1] Department of Parks and Wildlife, Kensington, Perth, Western Australia 6151, Australia [2] School of Plant Biology, Oceans Institute, University of Western Australia, Crawley, Western Australia 6009, Australia.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25607371" target="_blank"〉PubMed〈/a〉
    Keywords: Acclimatization ; Animals ; Anthozoa/*growth & development/*physiology ; Biodiversity ; *Climate Change ; *Coral Reefs ; *Ecosystem ; Fishes/physiology ; Indian Ocean ; Pacific Ocean ; Population Dynamics ; Seawater/analysis ; Seaweed/physiology ; Seychelles ; Symbiosis ; Tropical Climate
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 4
    Publication Date: 2014-05-31
    Description: The most prominent pattern in global marine biogeography is the biodiversity peak in the Indo-Australian Archipelago. Yet the processes that underpin this pattern are still actively debated. By reconstructing global marine paleoenvironments over the past 3 million years on the basis of sediment cores, we assessed the extent to which Quaternary climate fluctuations can explain global variation in current reef fish richness. Comparing global historical coral reef habitat availability with the present-day distribution of 6316 reef fish species, we find that distance from stable coral reef habitats during historical periods of habitat loss explains 62% of the variation in fish richness, outweighing present-day environmental factors. Our results highlight the importance of habitat persistence during periods of climate change for preserving marine biodiversity.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Pellissier, Loic -- Leprieur, Fabien -- Parravicini, Valeriano -- Cowman, Peter F -- Kulbicki, Michel -- Litsios, Glenn -- Olsen, Steffen M -- Wisz, Mary S -- Bellwood, David R -- Mouillot, David -- New York, N.Y. -- Science. 2014 May 30;344(6187):1016-9. doi: 10.1126/science.1249853.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉University of Fribourg, Department of Biology, Chemin du Musee 10, CH-1700 Fribourg, Switzerland. Department of Bioscience, Aarhus University, 8000 C Aarhus, Denmark. ; Laboratoire Ecologie des Systemes Marins Cotiers UMR 5119, CNRS, Institut de Recherche pour le Developpement (IRD), Institut Francais de Recherche pour l'Exploitation de la Mer, UM2, UM1, cc 093, Place E. Bataillon, FR-34095 Montpellier Cedex 5, France. ; IRD, UR 227 CoReUs, LABEX (Laboratoire d'Excellence) Corail, Laboratoire Arago, Boite Postale 44, FR-66651 Banyuls/mer, France. CESAB (Centre de Synthese et d'Analyse sur la Biodiversite)-FRB (Fondation pour la Recherche sur la Biodiversite), Immeuble Henri Poincare, Domaine du Petit Arbois, FR-13857 Aix-en-Provence cedex 3, France. ; Centre for Macroevolution and Macroecology, Research School of Biology, Australian National University, Canberra, ACT 0200, Australia. ; IRD, UR 227 CoReUs, LABEX (Laboratoire d'Excellence) Corail, Laboratoire Arago, Boite Postale 44, FR-66651 Banyuls/mer, France. ; Department of Ecology and Evolution, Biophore Building, University of Lausanne, 1015 Lausanne, Switzerland. Swiss Institute of Bioinformatics, Quartier Sorge, 1015 Lausanne, Switzerland. ; Center for Ocean and Ice, Danish Meteorological Institute, Lyngbyvej 100, 2100 Copenhagen, Denmark. ; Department of Bioscience, Aarhus University, 8000 C Aarhus, Denmark. Department of Ecology and Environment, DHI Water and Environment, 2970 Horsholm, Denmark. ; Australian Research Council Centre of Excellence for Coral Reef Studies, and School of Marine and Tropical Biology, James Cook University, Townsville, QLD 4811, Australia. ; Laboratoire Ecologie des Systemes Marins Cotiers UMR 5119, CNRS, Institut de Recherche pour le Developpement (IRD), Institut Francais de Recherche pour l'Exploitation de la Mer, UM2, UM1, cc 093, Place E. Bataillon, FR-34095 Montpellier Cedex 5, France. Australian Research Council Centre of Excellence for Coral Reef Studies, and School of Marine and Tropical Biology, James Cook University, Townsville, QLD 4811, Australia. david.mouillot@univ-montp2.fr.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24876495" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Australia ; *Biodiversity ; *Climate Change ; *Conservation of Natural Resources ; *Coral Reefs ; *Fishes
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 5
    Electronic Resource
    Electronic Resource
    Oxford, UK; Malden, USA : Blackwell Publishing Ltd/Inc.
    Journal of fish biology 64 (2004), S. 0 
    ISSN: 1095-8649
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology
    Notes: Ten functional traits of fish species were related to habitat, diet or food acquisition, to propose a classification of 21 lagoon fishes into 10 functional groups. The selection of traits was based on their functional interest and the ease of measurement. Some groups were taxonomically related containing species belonging to the same genus, e.g. Syngnathus, Atherina or Pomatochistus. Species with a flat body shape constituted another group and three species (Anguilla anguilla, Gambusia affinis and Callionymus pusillus) formed individual groups. These results could be used to constitute functional units and to simplify such complex ecosystems and their interactions.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Population ecology 41 (1999), S. 203-215 
    ISSN: 1437-5613
    Keywords: Key words: Diversity indices ; Estimator performances ; Simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Although having been much criticized, diversity indices are still widely used in animal and plant ecology to evaluate, survey, and conserve ecosystems. It is possible to quantify biodiversity by using estimators for which statistical characteristics and performance are, as yet, poorly defined. In the present study, four of the most frequently used diversity indices were compared: the Shannon index, the Simpson index, the Camargo eveness index, and the Pielou regularity index. Comparisons were performed by simulating the Zipf–Mandelbrot parametric model and estimating three statistics of these indices, i.e., the relative bias, the coefficient of variation, and the relative root-mean-squared error. Analysis of variance was used to determine which of the factors contributed most to the observed variation in the four diversity estimators: abundance distribution model or sample size. The results have revealed that the Camargo eveness index tends to demonstrate a high bias and a large relative root-mean-squared error whereas the Simpson index is least biased and the Shannon index shows a smaller relative root-mean-squared error, regardless of the abundance distribution model used and even when sample size is small. Shannon and Pielou estimators are sensitive to changes in species abundance pattern and present a nonnegligible bias for small sample sizes (〈1000 individuals).
    Type of Medium: Electronic Resource
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  • 7
    ISSN: 1437-5613
    Keywords: Key words Heterogeneity ; Scale ; Parsimonious model Trap size ; Diptera
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract The heterogeneity associated with the spatial distribution of organisms is an awkward problem in ecology because this heterogeneity directly depends on the sampling scale. To specify the scope of the influence of sampling scale on the level of species aggregation, we need data sets that entail excessive sampling costs in situ. To find a solution for this problem, we can use models to simulate patterns of organisms. These models are often very complex models that take into account heterogeneity of habitats and displacement or longevity of studied species. In this article, we introduce a new stochastic model to simulate patterns for one taxon and we want this model to be parsimonious, i.e., with few parameters and able to simulate observed patterns. This model is based on an aggregation–repulsion rule. This aggregation–repulsion rule is defined by two parameters. On a large scale, the number of aggregates present on the pattern is the first parameter. On a smaller scale, the level of aggregation–repulsion among individuals is determined by a probability distribution. These two parameters are estimated from field data set in a robust way so that the simulated patterns reflect the observed heterogeneity. We apply this model to entomological data: four Diptera families, namely the Sciaridae, Phoridae, Cecidomyiidae, and Empididae. The field data for the Phoridae family are used to simulate sampling using different trap sizes. We record changes in the coefficient of variation (C) as a function of the sampling scale, and we can suggest to ecologists emergence traps of 0.6 m2, in other words a square 77 × 77 cm trap, to obtain a C value under 20%.
    Type of Medium: Electronic Resource
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  • 8
  • 9
    Publication Date: 1999-08-01
    Print ISSN: 1438-3896
    Electronic ISSN: 1438-390X
    Topics: Biology
    Published by Springer
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  • 10
    Publication Date: 2000-12-20
    Print ISSN: 1438-3896
    Electronic ISSN: 1438-390X
    Topics: Biology
    Published by Springer
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