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...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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ELSEVIER SCIENCE LONDON
2020
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| Subjects: | |
| Online Access: | http://purl.org/au-research/grants/arc/DE180100635 http://hdl.handle.net/20.500.11937/90762 |
| _version_ | 1848765420409978880 |
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| author | 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. |
| author_facet | 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. |
| author_sort | Isaac, N.J.B. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:34:58Z |
| format | Journal Article |
| id | curtin-20.500.11937-90762 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:34:58Z |
| publishDate | 2020 |
| publisher | ELSEVIER SCIENCE LONDON |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-907622023-04-14T07:48:14Z Data Integration for Large-Scale Models of Species Distributions 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. 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 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. 2020 Journal Article http://hdl.handle.net/20.500.11937/90762 10.1016/j.tree.2019.08.006 English http://purl.org/au-research/grants/arc/DE180100635 http://creativecommons.org/licenses/by/4.0/ ELSEVIER SCIENCE LONDON fulltext |
| spellingShingle | 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 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. Data Integration for Large-Scale Models of Species Distributions |
| title | Data Integration for Large-Scale Models of Species Distributions |
| title_full | Data Integration for Large-Scale Models of Species Distributions |
| title_fullStr | Data Integration for Large-Scale Models of Species Distributions |
| title_full_unstemmed | Data Integration for Large-Scale Models of Species Distributions |
| title_short | Data Integration for Large-Scale Models of Species Distributions |
| title_sort | data integration for large-scale models of species distributions |
| topic | 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 |
| url | http://purl.org/au-research/grants/arc/DE180100635 http://hdl.handle.net/20.500.11937/90762 |