Niche models for British plants and lichens obtained using an ensemble approach. (September 2015)

• Record Type: Journal Article
• Authors: Henrys, P. A.; Smart, S. M.; Rowe, E. C.; Jarvis, S. G.; Fang, Z.; Evans, C. D.; Emmett, B. A.; Butler, A.
• Is Part Of: New journal of botany. Volume 5:Number 2(2015)
• Page Start: 89
• Page End: 100
• Publication Date: 2015-09
• Subjects: biodiversity, -- climate change, -- envelope, -- niche occupancy, -- pollution, -- R package; Botany -- Europe, Western -- Periodicals; Botany -- British Isles -- Periodicals; Plants -- Europe, Western -- Periodicals; Plants -- British Isles -- Periodicals; 580.94
• DOI: 10.1179/2042349715Y.0000000010
• Languages: English
• ISSNs: 2042-3489

Abstract

Abstract : Site-occupancy models that predict habitat suitability for plant species in relation to measurable environmental factors can be useful for conservation planning. Such models can be derived from large-scale presence–absence datasets on the basis of environmental observations or, where only floristic data are available, using plant trait values averaged across a plot. However, the estimated modelled relationship between species presence and environmental variables depends on the type of statistical model adopted and hence can introduce additional uncertainty. Authors used an ensemble-modelling approach to constrain and quantify the uncertainty because of the choice of statistical model, applying generalised linear models (GLM), generalised additive models (GAM), and multivariate adaptive regression splines (MARS). Niche models were derived for over 1000 species of vascular plants, bryophytes and lichens, representing a large proportion of the British flora and many species occurring in continental Europe. Each model predicts habitat suitability for a species in response to climate variables and trait-based scores (evaluated excluding the species being modelled) for soil pH, fertility, wetness and canopy height. An R package containing the fitted models for each species is presented which allows the user to predict the habitat suitability of a given set of conditions for a particular species. Further functions within the package are included so that these habitat suitability scores can be plotted in relation to individual explanatory variables. A simple case study shows how the R package (MultiMOVE) can be used quickly and efficiently to answer questions of scientific interest, specifically whether climate change will counteract any benefits of sheep-grazing for a particular plant community. The package itself is freely available viahttp://doi.org/10.5285/94ae1a5a-2a28-4315-8d4b-35ae964fc3b9 .