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Auteur Chao, A.; Chiu, C.-H.; Villeger, S.; Sun, I.-F.; Thorn, S.; Lin, Y.-C.; Chiang, J.-M.; Sherwin, W.B.
Titre An attribute-diversity approach to functional diversity, functional beta diversity, and related (dis)similarity measures Type Article scientifique
Année 2019 Publication (down) Revue Abrégée Ecol. Monogr.
Volume 89 Numéro 2 Pages Unsp-e01343
Mots-Clés attribute diversity; biodiversity; biological diversity; consensus; conservation; differentiation measures; diversity decomposition; evenness; framework; functional (dis)similarity; functional beta diversity; functional diversity; Hill numbers; phylogenetic diversity; quadratic entropy; similarity; species diversity; species richness; species traits; trait diversity
Résumé Based on the framework of attribute diversity (a generalization of Hill numbers of order q), we develop a class of functional diversity measures sensitive not only to species abundances but also to trait-based species-pairwise functional distances. The new method refines and improves on the conventional species-equivalent approach in three areas: (1) the conventional method often gives similar values (close to unity) to assemblages with contrasting levels of functional diversity; (2) when a distance metric is unbounded, the conventional functional diversity depends on the presence/absence of other assemblages in the study; (3) in partitioning functional gamma diversity into alpha and beta components, the conventional gamma is sometimes less than alpha. To resolve these issues, we add to the attribute-diversity framework a novel concept: tau, the threshold of functional distinctiveness between any two species; here, tau can be chosen to be any positive value. Any two species with functional distance >= tau are treated as functionally equally distinct. Our functional diversity quantifies the effective number of functionally equally distinct species (or “virtual functional groups”) with all pairwise distances at least tau for different species pairs. We advocate the use of two complementary diversity profiles (tau profile and q profile), which depict functional diversity with varying levels of tau and q, respectively. Both the conventional species-equivalent method (i.e., tau is the maximum of species-pairwise distances) and classic taxonomic diversity (i.e., tau is the minimum of non-zero species-pairwise distances) are incorporated into our proposed tau profile for an assemblage. For any type of species-pairwise distance matrices, our attribute-diversity approach allows proper diversity partitioning, with the desired property gamma >= alpha and thus avoids all the restrictions that apply to the conventional diversity decomposition. Our functional alpha and gamma are interpreted as the effective numbers of functionally equally distinct species, respectively, in an assemblage and in the pooled assemblage, while beta is the effective number of equally large assemblages with no shared species and all species in the assemblages being equally distinct. The resulting beta diversity can be transformed to obtain abundance-sensitive Sorensen- and Jaccard-type functional (dis)similarity profiles. Hypothetical and real examples are used to illustrate the framework. Online software and R codes are available to facilitate computations.
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ISSN 0012-9615 ISBN Médium
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Notes WOS:000477640700001 Approuvé pas de
Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2620
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Auteur Maire, Eva; Grenouillet, G.; Brosse, S.; Villeger, S.
Titre How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces Type Article scientifique
Année 2015 Publication (down) Revue Abrégée Global Ecology and Biogeography
Volume 24 Numéro 6 Pages 728-740
Mots-Clés Diversity indices; functional dendrogram; functional dissimilarity; functional ecology; functional traits; multidimensional space
Résumé Aim Functional diversity is a key facet of biodiversity that is increasingly being measured to quantify its changes following disturbance and to understand its effects on ecosystem functioning. Assessing the functional diversity of assemblages based on species traits requires the building of a functional space (dendrogram or multidimensional space) where indices will be computed. However, there is still no consensus on the best method for measuring the quality of functional spaces. Innovation Here we propose a framework for evaluating the quality of a functional space (i.e. the extent to which it is a faithful representation of the initial functional trait values). Using simulated datasets, we analysed the influence of the number and type of functional traits used and of the number of species studied on the identity and quality of the best functional space. We also tested whether the quality of the functional space affects functional diversity patterns in local assemblages, using simulated datasets and a real study case. Main conclusions The quality of functional space strongly varied between situations. Spaces having at least four dimensions had the highest quality, while functional dendrograms and two-dimensional functional spaces always had a low quality. Importantly, we showed that using a poor-quality functional space could led to a biased assessment of functional diversity and false ecological conclusions. Therefore, we advise a pragmatic approach consisting of computing all the possible functional spaces and selecting the most parsimonious one.
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Volume de collection Numéro de collection Edition
ISSN 1466-8238 ISBN Médium
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Numéro d'Appel MARBEC @ alain.herve @ collection 1341
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Auteur Matthews, T.J.; Triantis, K.A.; Whittaker, R.J.; Guilhaumon, F.
Titre sars: an R package for fitting, evaluating and comparing species-area relationship models Type Article scientifique
Année 2019 Publication (down) Revue Abrégée Ecography
Volume 42 Numéro 8 Pages 1446-1455
Mots-Clés accumulation; curves; diversity; diversity-area relationship; island biogeography; islands; richness; species-area relationship
Résumé The species-area relationship (SAR) constitutes one of the most general ecological patterns globally. A number of different SAR models have been proposed. Recent work has shown that no single model universally provides the best fit to empirical SAR datasets: multiple models may be of practical and theoretical interest. However, there are no software packages available that a) allow users to fit the full range of published SAR models, or b) provide functions to undertake a range of additional SAR-related analyses. To address these needs, we have developed the R package 'sars' that provides a wide variety of SAR-related functionality. The package provides functions to: a) fit 20 SAR models using non-linear and linear regression, b) calculate multi-model averaged curves using various information criteria, and c) generate confidence intervals using bootstrapping. Plotting functions allow users to depict and scrutinize the fits of individual models and multi-model averaged curves. The package also provides additional SAR functionality, including functions to fit, plot and evaluate the random placement model using a species-sites abundance matrix, and to fit the general dynamic model of oceanic island biogeography. The 'sars' R package will aid future SAR research by providing a comprehensive set of simple to use tools that enable in-depth exploration of SARs and SAR-related patterns. The package has been designed to allow other researchers to add new functions and models in the future and thus the package represents a resource for future SAR work that can be built on and expanded by workers in the field.
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Langue English Langue du Résumé Titre Original
Éditeur de collection Titre de collection Titre de collection Abrégé
Volume de collection Numéro de collection Edition
ISSN 0906-7590 ISBN Médium
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Notes WOS:000477975800010 Approuvé pas de
Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2625
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Auteur Muller-Karger, F.E.; Miloslavich, P.; Bax, N.J.; Simmons, S.; Costello, M.J.; Sousa Pinto, I.; Canonico, G.; Turner, W.; Gill, M.; Montes, E.; Best, B.D.; Pearlman, J.; Halpin, P.; Dunn, D.; Benson, A.; Martin, C.S.; Weatherdon, L.V.; Appeltans, W.; Provoost, P.; Klein, E.; Kelble, C.R.; Miller, R.J.; Chavez, F.P.; Iken, K.; Chiba, S.; Obura, D.; Navarro, L.M.; Pereira, H.M.; Allain, V.; Batten, S.; Benedetti-Checchi, L.; Duffy, J.E.; Kudela, R.M.; Rebelo, L.-M.; Shin, Y.; Geller, G.
Titre Advancing Marine Biological Observations and Data Requirements of the Complementary Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) Frameworks Type Article scientifique
Année 2018 Publication (down) Revue Abrégée Front. Mar. Sci.
Volume 5 Numéro Pages
Mots-Clés Essential Biodiversity Variables (EBVs); Essential Ocean Variables (EOV); Global Ocean Observing System (GOOS); Integrated Marine Biosphere Research (IMBeR); Marine Biodiversity Observation Network (MBON); Marine Global Earth Observatory (MarineGEO); Ocean Biogeographic Information System (OBIS)
Résumé Measurements of the status and trends of key indicators for the ocean and marine life are required to inform policy and management in the context of growing human uses of marine resources, coastal development, and climate change. Two synergistic efforts identify specific priority variables for monitoring: Essential Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS), and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON). Both systems support reporting against internationally agreed conventions and treaties. GOOS, established under the auspices of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in coordinating global monitoring of the ocean and in the definition of EOVs. GEO BON is a global biodiversity observation network that coordinates observations to enhance management of the world’s biodiversity and promote both the awareness and accounting of ecosystem services. Convergence and agreement between these two efforts are required to streamline existing and new marine observation programs to advance scientific knowledge effectively and to support the sustainable use and management of ocean spaces and resources. In this context, the Marine Biodiversity Observation Network (MBON), a thematic component of GEO BON, is collaborating with GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary, representing alternative uses of a common set of scientific measurements. This work is informed by the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), an intergovernmental body of technical experts that helps international coordination on best practices for observing, data management and services, combined with capacity development expertise. Characterizing biodiversity and understanding its drivers will require incorporation of observations from traditional and molecular taxonomy, animal tagging and tracking efforts, ocean biogeochemistry, and ocean observatory initiatives including the deep ocean and seafloor. The partnership between large-scale ocean observing and product distribution initiatives (MBON, OBIS, JCOMM, and GOOS) is an expedited, effective way to support international policy-level assessments (e.g., the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services or IPBES), along with the implementation of international development goals (e.g., the United Nations Sustainable Development Goals).
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Langue English Langue du Résumé Titre Original
Éditeur de collection Titre de collection Titre de collection Abrégé
Volume de collection Numéro de collection Edition
ISSN 2296-7745 ISBN Médium
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Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2371
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Auteur Ranchou-Peyruse, M.; Auguet, J.-C.; Maziere, C.; Restrepo-Ortiz, C.X.; Guignard, M.; Dequidt, D.; Chiquet, P.; Cezac, P.; Ranchou-Peyruse, A.
Titre Geological gas-storage shapes deep life Type Article scientifique
Année 2019 Publication (down) Revue Abrégée Environ. Microbiol.
Volume Numéro Pages
Mots-Clés carbon; degradation; depth; desulfotomaculum; diversity; methanogenesis; microbial communities; spp.; sulfate-reducing bacteria; sulfite
Résumé Around the world, several dozen deep sedimentary aquifers are being used for storage of natural gas. Ad hoc studies of the microbial ecology of some of them have suggested that sulfate reducing and methanogenic microorganisms play a key role in how these aquifers' communities function. Here, we investigate the influence of gas storage on these two metabolic groups by using high-throughput sequencing and show the importance of sulfate-reducing Desulfotomaculum and a new monophyletic methanogenic group. Aquifer microbial diversity was significantly related to the geological level. The distance to the stored natural gas affects the ratio of sulfate-reducing Firmicutes to deltaproteobacteria. In only one aquifer, the methanogenic archaea dominate the sulfate-reducers. This aquifer was used to store town gas (containing at least 50% H-2) around 50 years ago. The observed decrease of sulfates in this aquifer could be related to stimulation of subsurface sulfate-reducers. These results suggest that the composition of the microbial communities is impacted by decades old transient gas storage activity. The tremendous stability of these gas-impacted deep subsurface microbial ecosystems suggests that in situ biotic methanation projects in geological reservoirs may be sustainable over time.
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Langue English Langue du Résumé Titre Original
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Volume de collection Numéro de collection Edition
ISSN 1462-2912 ISBN Médium
Région Expédition Conférence
Notes WOS:000480010600001 Approuvé pas de
Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2627
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