Data Integration for Large-Scale Models of Species Distributions
Access Status
Open access
Authors
Isaac, N.J.B.
Jarzyna, M.A.
Keil, P.
Dambly, L.I.
Boersch-Supan, P.H.
Browning, E.
Freeman, S.N.
Golding, Nick
Guillera-Arroita, G.
Henrys, P.A.
Jarvis, S.
Lahoz-Monfort, J.
Pagel, J.
Pescott, O.L.
Schmucki, R.
Simmonds, E.G.
O'Hara, R.B.
Date
2020Type
Journal Article
Metadata
Show full item recordCitation
Isaac, N.J.B. and Jarzyna, M.A. and Keil, P. and Dambly, L.I. and Boersch-Supan, P.H. and Browning, E. and Freeman, S.N. et al. 2020. Data Integration for Large-Scale Models of Species Distributions. Trends in Ecology and Evolution. 35 (1): pp. 56-67.
Source Title
Trends in Ecology and Evolution
ISSN
Faculty
Faculty of Health Sciences
School
Curtin School of Population Health
Funding and Sponsorship
Collection
Abstract
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.
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/