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Capture-recapture meets big data: integrating statistical classification with ecological models of species abundance and occurrence Advances in new technologies such as remote cameras, noninvasive genetics and bioacoustics provide massive quantities of electronic data. Much work has been done on automated (“machine learning”) methods of classification which produce “sample class designations” (e.g., identification of species or individuals) that are regarded as observed data in ecological models. However, these “data” are actually derived quantities (or synthetic data) and subject to various important sources of bias and error. If the derived quantities are used to make ecological determinations without consideration of these biases, those inferences which inform monitoring, conservation, and management will be flawed. We propose to develop... Categories: Project; Tags: Active, All Working Groups, Classification, Core Science Systems, Ecological Modelling, All tags... Ecological Modelling, Ecosystems, Ecosystems, Machine learning, ecosystem ecology, synthesis, Fewer tags