Projects per year
Abstract
Bioregions are important tools for understanding and managing natural resources. Bioregions should describe locations of relatively homogenous assemblages of species occur, enabling managers to better regulate activities that might affect these assemblages. Many existing bioregionalization approaches, which rely on expert-derived, Delphic comparisons or environmental surrogates, do not explicitly include observed biological data in such analyses. We highlight that, for bioregionalizations to be useful and reliable for systems scientists and managers, the bioregionalizations need to be based on biological data; to include an easily understood assessment of uncertainty, preferably in a spatial format matching the bioregions; and to be scientifically transparent and reproducible. Statistical models provide a scientifically robust, transparent, and interpretable approach for ensuring that bioregions are formed on the basis of observed biological and physical data. Using statistically derived bioregions provides a repeatable framework for the spatial representation of biodiversity at multiple spatial scales. This results in better-informed management decisions and biodiversity conservation outcomes.
Original language | English |
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Journal | BioScience |
Volume | 70 |
Issue number | 1 |
Pages (from-to) | 48-59 |
Number of pages | 12 |
ISSN | 0006-3568 |
DOIs | |
Publication status | Published - Jan 2020 |
MoE publication type | A1 Journal article-refereed |
Fields of Science
- 1172 Environmental sciences
- 112 Statistics and probability
- biogeography
- community ecology
- statistics
- marine biology
- GENERALIZED LINEAR-MODELS
- POINT PROCESS MODELS
- SPECIES DISTRIBUTION
- BIAS CORRECTION
- BIODIVERSITY
- IMPLEMENTATION
- PREDICTIONS
- ECOREGIONS
- FRAMEWORK
- REGIONS
Projects
- 2 Finished
-
Multivariate Gaussian processes for hierarchical modelling of species distributions
Vanhatalo, J., Kaurila, K. & Numminen, S.
Suomen Akatemia Projektilaskutus
01/09/2018 → 31/08/2022
Project: Research project
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Applying species distribution modeling in marine spatial planning and fisheries management
Vanhatalo, J., Hartmann, M., Liu, J. & Kaurila, K.
01/10/2016 → 30/09/2018
Project: Research project