Bioclimatic envelope modeling is a process of spatially predicting species distributions, based on interpolations of data in space. Bioclimatic envelope models use associations between different aspects of climate and observed occurrences of species to define conditions under which species are most likely to maintain viable populations. These models, also known as species-climate envelope models, are correlated with ecological niche, habitat suitability, and species distribution models, but differ in certain ways, as only climate variables are taken into account, and not, for example, resources for species use.
Bioclimatic envelope modeling allows for the mapping of species distributions, which is assumed to be impractical to map directly. As species distributions can be predicted from environmental indicators, and more detailed projections of these environmental variables are available, one can predict the current or future distribution of a species much easier than by direct monitoring.
Spatial predictions such as envelope modeling can be used to better understand distributions of species, and predict the present or future occurrence of a species, to help conservation planning, assessing the status of a species or invasive species, projecting the effects of climate change, and more.
This toolbox entry has been labelled with the following tags:
| Sector: | biodiversity and ecosystems | |
| Spatial scale: | independent | |
| Temporal focus: | future | |
| Onset: | slow | |
| Role in decision process: | diagnostic | |
| Level of skills required: | modest | |
| Data requirements: | modest | |
| Adaptation tasks: | Potential impact projection; Residual impact projection |
The model approach can be used to a number of novel questions, some of which are highlighted below:
The modeling approach discussed here, while being seen as an easier method of predicting species habitats besides direct survey of their locations, is still demanding in terms of data and skills required to perform an accurate assessment. A range of environmental data is required; importantly, the links between climate and species distribution needs to be well understood by researchers, in order to accurately model projected distribution. Input data, such as future climate estimates, must be spatially organized. Further, use of this method requires knowledge of GIS software, and knowledge of the modeling methods involved (e.g. generalized linear models, generalized additive models, classification trees, random forests).
GIS software, such as ESRI's suite of tools, requires a significant purchase and/or use of a license. Open-source GIS tools exist, but without the support and usability of more mainstream programs.
Franklin, J. 2009. Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cam- bridge, UK.
Williams, P. H., L. Hannah, S. Andelman, G. F. Midgley, M. B. Arau ? jo, G. Hughes, L. L. Manne, E. Martinez-Meyer, and R. G. Pearson. 2005. Planning for climate change: identifying minimum-dispersal corridors for the Cape Pro- teaceae. Conservation Biology 19:1063-1074.
Raxworthy, C. J., E. Mart? ?nez-Meyer, N. Horning, R. A. Nussbaum, G. E. Schneider, M. A. Ortega-Huerta, and A. T. Peterson. 2003. Predicting distributions of known and unknown reptile species in Madagascar. Nature 426:837-841.
Peterson, A. T., R. R. Lash, D. S. Carrol, and K. M. Johnson. 2006. Geographic potential for outbreaks of Marburg hemorrhagic fever. American Journal of Tropical Medicine and Hygiene 75:9-15
Araújo, M.B. & Peterson, A.T. 2012. Uses and misuses of bioclimatic envelope modelling. Ecology. 93:1527-1539.
The case study pool contains the following steps that were performed applying the described entry:
weADAPT case studies identified for this toolbox entry:
|
Adaption of grassland butterflies to climate change
Given the long-term decline trend in semi-natural grasslands due to agricultural intensification and abandonment of marginal areas in Finland (as in other parts of Europe), several grassland species are likely to face difficulties in migrating across fragmented landscapes to new climatically suitable areas... |
