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Data integration for large-scale models of species distributions

Isaac, Nick J.B. ORCID: https://orcid.org/0000-0002-4869-8052; Jarzyna, Marta A.; Keil, Petr; Dambly, Lea I.; Boersch-Supan, Philipp H.; Browning, Ella; Freeman, Stephen N.; Golding, Nick; Guillera-Arroita, Gurutzeta; Henrys, Peter A.; Jarvis, Susan; Lahoz-Monfort, José; Pagel, Jörn; Pescott, Oliver L. ORCID: https://orcid.org/0000-0002-0685-8046; Schmucki, Reto; Simmonds, Emily G.; O’Hara, Robert B.. 2020 Data integration for large-scale models of species distributions. Trends in Ecology & Evolution, 35 (1). 56-67. https://doi.org/10.1016/j.tree.2019.08.006

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Abstract/Summary

With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species’ potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1016/j.tree.2019.08.006
UKCEH and CEH Sections/Science Areas: Biodiversity (Science Area 2017-)
Soils and Land Use (Science Area 2017-)
ISSN: 0169-5347
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - full text available via Official URL link.
Additional Keywords: point process, integrated distribution model, state-space model, citizen science, occupancy model, species distribution model
NORA Subject Terms: Ecology and Environment
Data and Information
Date made live: 06 Jan 2020 11:18 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/526349

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