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<datestamp>2018-01-11</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Progressive-Change BACIPS: a flexible approach forenvironmental impact assessment</title>
<creator>Thiault, Lauric</creator>
<creator>Kernaleguen, Laëtitia</creator>
<creator>Osenberg, Craig W</creator>
<creator>Claudet, Joachim</creator>
<contributor>Patrimoines Locaux et Gouvernance (PALOC) ; Institut de Recherche pour le Développement (IRD) - Muséum National d'Histoire Naturelle (MNHN)</contributor>
<contributor>Centro de conservacion marina and CeBiB ; Pontificia Universidad Católica de Chile</contributor>
<contributor>Laboratoire d'Excellence CORAIL (LabEX CORAIL) ; Institut de Recherche pour le Développement (IRD) - Université des Antilles et de la Guyane (UAG) - École des hautes études en sciences sociales (EHESS) - École pratique des hautes études (EPHE) - Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER) - Université de la Réunion (UR) - Université de la Polynésie Française (UPF) - Université de Nouvelle Calédonie - Institut d'écologie et environnement</contributor>
<contributor>Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO) ; Université Pierre et Marie Curie - Paris 6 (UPMC) - Institut de la francophonie pour l'informatique - Université Cheikh Anta Diop (UCAD) - Université Gaston Bergé (Saint-Louis, Sénégal) - Universtié Yaoundé 1 (Cameroun) - University Cadi Ayyad (UCA)</contributor>
<contributor>Centre de recherches insulaires et observatoire de l'environnement (CRIOBE) ; Université de Perpignan Via Domitia (UPVD) - École pratique des hautes études (EPHE) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Deakin University [Burwood] </contributor>
<contributor>Odum School of Ecology</contributor>
<description>International audience</description>
<source>ISSN: 2041-210X</source>
<source>EISSN: 2041-210X</source>
<source>Methods in Ecology and Evolution</source>
<publisher>Wiley</publisher>
<identifier>hal-01416668</identifier>
<identifier>https://hal-univ-perp.archives-ouvertes.fr/hal-01416668</identifier>
<source>https://hal-univ-perp.archives-ouvertes.fr/hal-01416668</source>
<source>Methods in Ecology and Evolution, Wiley, 2016, 〈10.1111/2041-210X.12655〉</source>
<identifier>DOI : 10.1111/2041-210X.12655</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1111/2041-210X.12655</relation>
<language>en</language>
<subject lang=en>assessment design</subject>
<subject lang=en> Before-After Control-Impact Paired Series</subject>
<subject lang=en> data analysis</subject>
<subject lang=en> effect size</subject>
<subject lang=en> impact assessment</subject>
<subject lang=en> multi-model inference</subject>
<subject lang=en> resources management</subject>
<subject lang=en> simulations</subject>
<subject lang=en> statistical models Introduction Human activities</subject>
<subject>[SDE.IE] Environmental Sciences/Environmental Engineering</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>1. The Before-After Control-Impact Paired Series (BACIPS) design distinguishes natural spatial and temporalvariability from variation induced by an environmental impact (or intervention) of interest. BACIPS is a powerfultool to derive inferences about interventions when classic experimental approaches (e.g. which rely on spatialreplicates and random assignment of treatments) are not feasible or desirable. Previously applied BACIPSdesigns generally assume that effects are sudden, constant and long-lived: that is, that systems exhibit ‘stepchanges’in response to interventions. However, complex ecological interactions or gradual interventions maycreate delayed and/or progressive responses, potentially impeding the reliability of classic (step-change) analyses.2. We propose a novel approach, the Progressive-Change BACIPS, which generalizes and expands the scope ofBACIPS analyses.We evaluate the relative performance of this approach using both simulated and real data thatexhibit step-change, linear, asymptotic and sigmoid responses following an intervention.We quantify the statisticalpower and accuracy of the Progressive-Change BACIPS under varying initial population densities, intensityof spatial sampling, effect sizes and number of sampling dates After the intervention.3. We show that Progressive-Change BACIPS identified the correct model among the set of candidate modelsunder most conditions and led to accurate estimates of the parameters that were used to generate the simulateddata. When data were sparse, and the dynamics complex, simpler (more parsimonious) models were favouredover the more complex models that actually generated the simulated data. Application of the Progressive-Change BACIPS to existing data sets from the literature led to strong support for specific models (over alternatives)and led to more specific inferences than possible under the classic BACIPS approach.4. The Progressive-Change BACIPS proposed here is more flexible than the original BACIPS formulationbecause the data are used to inform the form of the final model, rather than having the form of the modelimposed on the data. This leads to better estimates of the effects of environmental impacts and the time-scalesover which they operate. As a result, the Progressive-Change BACIPS should be applicable to a wide range ofstudies and should help improve investigation of time-dependent effects. R code to perform Progressive-ChangeBACIPS analysis is provided.</description>
<date>2016</date>
</dc>
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