Assessing species climatic requirements beyond the realized niche: some lessons mainly from tree species distribution modelling

Trevor H. Booth ()
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Trevor H. Booth: CSIRO Land and Water

Climatic Change, 2017, vol. 145, issue 3, No 1, 259-271

Abstract: Abstract Almost all climate change studies of plants and animals adopt an ‘equilibrium assumption’ that analyses of natural distributions provide reliable estimates of species climatic requirements. Yet commercial forestry trials around the world have shown that many tree species can grow successfully under climatic conditions somewhat different from those of their natural distributions. Under climate change it is reasonable to assume that a long-lived tree species, already well-established at particular sites, may be able to display some of the climatic adaptability shown in trials outside its natural distribution. The purpose of this paper is to outline how some species distribution modelling (SDM) and ecological niche modelling (ENM) studies have estimated species climatic requirements beyond those shown by conventional analyses of just their natural distributions, and to show how recent developments are facilitating these analyses. Some of the earliest SDM studies of trees demonstrated the desirability of assessing species climatic requirements using data from outside, as well as within, their natural distributions. In recent years, with the advent of large biodiversity databases and some revised SDM analysis methods, there has been a revival of interest in measuring species climatic requirements using data from beyond their realized niches. It is recommended that at least for tree species, natural distribution data, and where possible results from plantings beyond natural distributions, should be analysed in climate change studies. When this is not possible, some alternative methods of estimating species climatic requirements are identified and some of their advantages and disadvantages are considered.

Keywords: climate change; fundamental niche; species extinction; species vulnerability; forest; species distribution model (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10584-017-2107-9

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