The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages
Open accessAbstract
Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realized properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate the properties of assemblages. Here, we propose to unify the two approaches in a single ‘spatially explicit species assemblage modelling’ (SESAM) framework. This framework uses relevant designations of initial species source pools for modelling, macroecological variables, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.
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F. Dormann, C., M. McPherson, J., B. Araújo, M., Bivand, R., Bolliger, J., Carl, G., G. Davies, R., Hirzel, A., Jetz, W., Daniel Kissling, W., et al. (2007) · Ecography · doi:10.1111/j.2007.0906-7590.05171.x · Cited by 3,433
Novel climates, no‐analog communities, and ecological surprises
Williams, J. W., & Jackson, S. T. (2007) · Frontiers in Ecology and the Environment · doi:10.1890/070037 · Cited by 1,736
COMPETITIVE INTERACTIONS BETWEEN TREE SPECIES IN NEW ZEALAND'S OLD-GROWTH INDIGENOUS FORESTS
Leathwick, J. R., & Austin, M. P. (2001) · Ecology · doi:10.1890/0012-9658(2001)082[2560:cibtsi]2.0.co;2 · Cited by 243
Cited by
Wisz, M. S., Pottier, J., Kissling, W. D., Pellissier, L., Lenoir, J., Damgaard, C. F., Dormann, C. F., Forchhammer, M. C., Grytnes, J., Guisan, A., et al. (2013) · Biological Reviews · doi:10.1111/j.1469-185x.2012.00235.x · Cited by 1,769
Self-citationSo Many Variables: Joint Modeling in Community Ecology
Warton, D. I., Blanchet, F. G., O’Hara, R. B., Ovaskainen, O., Taskinen, S., Walker, S. C., & Hui, F. K. C. (2015) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2015.09.007 · Cited by 854
Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling
Sillero, N., Arenas-Castro, S., Enriquez‐Urzelai, U., Vale, C. G., Sousa-Guedes, D., Martínez-Freiría, F., Real, R., & Barbosa, A. M. (2021) · Ecological Modelling · doi:10.1016/j.ecolmodel.2021.109671 · Cited by 456
Joint Species Distribution Modelling: With Applications in R
Ovaskainen, O., & Abrego, N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108591720 · Cited by 394
Identifying long-term stable refugia for relict plant species in East Asia
Tang, C. Q., Matsui, T., Ohashi, H., Dong, Y.-F., Momohara, A., Herrando-Moraira, S., Qian, S., Yang, Y., Ohsawa, M., Luu, H. T., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06837-3 · Cited by 322
Metadata
- Authors
- Guisan, A., & Rahbek, C.
- Venue
- Journal of Biogeography
- Publisher
- Wiley
- Published
- 2011-06-10
- Volume
- 38
- Issue
- 8
- Pages
- 1433-1444
- ISSN
- 0305-0270 (ISSN-L)
- OpenAlex
- W1575429187
- Cited by
- 469
- References
- 3
- FWCI
- 23.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Guisan, A., & Rahbek, C. (2011). SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages. Journal of Biogeography. https://doi.org/10.1111/j.1365-2699.2011.02550.x
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.