Year: 2019
Type: review
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.
Source: Trends in Ecology & Evolution
Authors: Nick J.B. Isaac, Marta A. Jarzyna, Petr Keil, Lea I. Dambly, Philipp H. Boersch-Supan, Ella Browning, Stephen N. Freeman, Nick Golding, Gurutzeta Guillera-Arroita, Peter A. Henrys, Susan Jarvis, José Lahoz-Monfort, Jörn Pagel, Oliver L. Pescott, Reto Schmucki, Emily G. Simmonds, Robert B. O’Hara
Institutions: UK Centre for Ecology & Hydrology, University College London, The Ohio State University, German Centre for Integrative Biodiversity Research, Martin Luther University Halle-Wittenberg, University of Florida, British Trust for Ornithology, Zoological Society of London, The University of Melbourne, University of Hohenheim, Norwegian University of Science and Technology
Language: English
Subfield: Ecological Modeling
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: hybrid
Estimated APC paid: $4,000
Awards: UK Status, Change and Projections of the Environment (UK-SCaPE), G2664551268, Modelling the drivers of population change in bats, Demographic distribution models for ecology, conservation & public health, Connections between imperfect detection and ecological inference, Data integration for large scale ecological models, G8601092817
OpenAlex ID: W2982619951