Data Integration for Large-Scale Models of Species Distributions

Data Integration for Large-Scale Models of Species Distributions

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...

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Bibliographic Details
Main 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.
Format: Journal Article
Language:English
Published: ELSEVIER SCIENCE LONDON 2020
Subjects:
Science & Technology
Life Sciences & Biomedicine
Ecology
Evolutionary Biology
Genetics & Heredity
Environmental Sciences & Ecology
POINT PROCESS MODELS
CITIZEN SCIENCE DATA
BIG DATA
BIAS
ECOLOGY
FUTURE
INFORMATION
CHALLENGES
FRAMEWORK
ABUNDANCE
Online Access:http://purl.org/au-research/grants/arc/DE180100635
http://hdl.handle.net/20.500.11937/90762
Description
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.

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