Know Your Limits - The Need for Better Data on Species Responses to Soil Variables. Diekmann, M.; Michaelis, J.; and Pannek, A. 16(7):563–572.
Know Your Limits - The Need for Better Data on Species Responses to Soil Variables [link]Paper  doi  abstract   bibtex   
Species distribution modelling has largely focused on larger spatial scales and the significance of climatic variables for future species ranges. In this study, we argue that more attention should be paid to local processes and the responses of species along soil gradients, as habitat destruction and change in terms of an altered edaphic environment are the main factors behind the decline of many plant species in Central Europe. Examples from deciduous forests and calcareous dry grasslands show that response optima and especially response limits relative to soil pH and phosphorus availability are more closely related to the range sizes and threat levels of species than the traditionally applied Ellenberg indicator values, and that species assumed to have similar preferences show considerable, ecologically relevant differences in their thresholds. There is an urgent need for collecting more and better soil data and for analyzing the relationships between the spatial distribution of plant species and edaphic variables on regional and local scales, in order to identify optimal and marginal habitats of species as a pre-requisite for their successful conservation. [Excerpt] [...] [\n] A main problem for modelling species responses along soil gradients is lack of data. Many climatic variables can easily be extracted from climate data portals such as WorldClim (e.g., Hijmans, Cameron, Parra, Jones, & Jarvis 2005; http://www.worldclim.org). Although soil data are increasingly made available in spatial grids and databases (for example, http://soilgrids.org/ or http://eusoils.jrc.ec.europa.eu/ESDB_Archive/ESDB/Index.htm), soil variables vary on much smaller spatial scales so that grid-based information is not always representative of the site in which a plant grows. In addition, soil sampling involves time-consuming field work and often expensive laboratory measurements. The few available soil data have often been obtained using different methods with regard to, for example, sampling depth or chemical analysis, which further complicates comparability and interpretation. Therefore, measurements of important environmental drivers in terms of soil variables have in most cases been replaced by an indirect assessment of habitat quality by means of indicator values. [...] [Discussion] [...] [\n] Being aware that the extent of this study is limited and that the results must be regarded as preliminary, we nonetheless conclude the following: [::(1)] At least in regional vegetation studies, species optima derived from measurements of soil variables show a higher explanatory power than indicator values. They also have the advantage to represent true values that can be compared between regions, ecosystems and species without the need for transformation. Studies on niche characteristics (such as niche breadth and position) of plants have often been based on indirect assessments of species' behaviour and turnover along gradients (e.g., Fridley et al., 2007 and Wasof et al., 2013), which often involves analytical problems and a lack of transferability to field conditions. A measurement-based approach might contribute to make studies on ecological niches more realistic. [::(2)] When aiming to predict the potential or future distribution of plant species on a regional scale, measured response optima and especially limits need to be considered. The importance of edaphic variables for predicting plant distributions has already been emphasized by Thuiller (2013) and put in practice by, for example, Dubuis et al. (2013) and Beauregard and de Blois (2014). Rare species were shown to have narrower habitat preferences in terms of soil parameters than common species (Wamelink, Goedhart, Frissel, & 2014). As already noted, a practical problem is the shortage of available environmental data. Another drawback is the high spatial heterogeneity of most soil variables that makes it difficult to integrate these variables in SDM on a coarse spatial resolution (Thuiller 2013). The problem can partly be rectified by using units on a much smaller spatial scale such as classical sample plots. Another possible solution was offered by Bertrand et al. (2012) who used an indirect estimation of soil pH for 1 km2 grid cells based on the species composition and the modelled response of species to pH. Response optima and limits assessed on a regional scale are invaluable for a refinement of large-scale SDM. For example, the general prediction of a climate change-induced shift of highly base-demanding species towards the north in Scandinavia can be modified by taking into account the relative scarcity of high-pH soils in northern Europe and the relatively high lower pH limits of many species in Central Europe (Ewald 2003). [\n] For predictions of plant distributions in climatically relatively homogeneous regions, information on species responses to finer-grained (edaphic) variables is crucial (see Beck et al. 2012), as shown by Kelly, Leach, Cameron, Maggs, and Reid (2014) in a study on invasive plants. Our results suggest that response optima and Ellenberg values both perform reasonably well, but do not succeed to differentiate between species with highly similar preferences but diverging limits [...] [::(3)] Knowing that edaphic species thresholds matter and that at the same time edaphic limits are not yet quantified for most species and variables is alarming, because the conservation of species will depend on a thorough understanding of the ecological niches of species and where these are met, now and in future. Given the long tradition of vegetation science in Central Europe and in other parts of the world, with hundreds of thousands of plots being available, we still know little about the species' niches and especially their limits. [...]
@article{diekmannKnowYourLimits2015,
  title = {Know Your Limits - {{The}} Need for Better Data on Species Responses to Soil Variables},
  author = {Diekmann, Martin and Michaelis, Jana and Pannek, Angela},
  date = {2015-11},
  journaltitle = {Basic and Applied Ecology},
  volume = {16},
  pages = {563--572},
  issn = {1439-1791},
  doi = {10.1016/j.baae.2015.08.010},
  url = {https://doi.org/10.1016/j.baae.2015.08.010},
  abstract = {Species distribution modelling has largely focused on larger spatial scales and the significance of climatic variables for future species ranges. In this study, we argue that more attention should be paid to local processes and the responses of species along soil gradients, as habitat destruction and change in terms of an altered edaphic environment are the main factors behind the decline of many plant species in Central Europe. Examples from deciduous forests and calcareous dry grasslands show that response optima and especially response limits relative to soil pH and phosphorus availability are more closely related to the range sizes and threat levels of species than the traditionally applied Ellenberg indicator values, and that species assumed to have similar preferences show considerable, ecologically relevant differences in their thresholds. There is an urgent need for collecting more and better soil data and for analyzing the relationships between the spatial distribution of plant species and edaphic variables on regional and local scales, in order to identify optimal and marginal habitats of species as a pre-requisite for their successful conservation. 

[Excerpt]

[...]

[\textbackslash n] A main problem for modelling species responses along soil gradients is lack of data. Many climatic variables can easily be extracted from climate data portals such as WorldClim (e.g., Hijmans, Cameron, Parra, Jones, \& Jarvis 2005; http://www.worldclim.org). Although soil data are increasingly made available in spatial grids and databases (for example, http://soilgrids.org/ or http://eusoils.jrc.ec.europa.eu/ESDB\_Archive/ESDB/Index.htm), soil variables vary on much smaller spatial scales so that grid-based information is not always representative of the site in which a plant grows. In addition, soil sampling involves time-consuming field work and often expensive laboratory measurements. The few available soil data have often been obtained using different methods with regard to, for example, sampling depth or chemical analysis, which further complicates comparability and interpretation. Therefore, measurements of important environmental drivers in terms of soil variables have in most cases been replaced by an indirect assessment of habitat quality by means of indicator values. [...]

[Discussion]

[...]

[\textbackslash n] Being aware that the extent of this study is limited and that the results must be regarded as preliminary, we nonetheless conclude the following:

[::(1)] At least in regional vegetation studies, species optima derived from measurements of soil variables show a higher explanatory power than indicator values. They also have the advantage to represent true values that can be compared between regions, ecosystems and species without the need for transformation. Studies on niche characteristics (such as niche breadth and position) of plants have often been based on indirect assessments of species' behaviour and turnover along gradients (e.g., Fridley et al., 2007 and Wasof et al., 2013), which often involves analytical problems and a lack of transferability to field conditions. A measurement-based approach might contribute to make studies on ecological niches more realistic.

[::(2)] When aiming to predict the potential or future distribution of plant species on a regional scale, measured response optima and especially limits need to be considered. The importance of edaphic variables for predicting plant distributions has already been emphasized by Thuiller (2013) and put in practice by, for example, Dubuis et al. (2013) and Beauregard and de Blois (2014). Rare species were shown to have narrower habitat preferences in terms of soil parameters than common species (Wamelink, Goedhart, Frissel, \& 2014). As already noted, a practical problem is the shortage of available environmental data. Another drawback is the high spatial heterogeneity of most soil variables that makes it difficult to integrate these variables in SDM on a coarse spatial resolution (Thuiller 2013). The problem can partly be rectified by using units on a much smaller spatial scale such as classical sample plots. Another possible solution was offered by Bertrand et al. (2012) who used an indirect estimation of soil pH for 1 km2 grid cells based on the species composition and the modelled response of species to pH. Response optima and limits assessed on a regional scale are invaluable for a refinement of large-scale SDM. For example, the general prediction of a climate change-induced shift of highly base-demanding species towards the north in Scandinavia can be modified by taking into account the relative scarcity of high-pH soils in northern Europe and the relatively high lower pH limits of many species in Central Europe (Ewald 2003).

[\textbackslash n] For predictions of plant distributions in climatically relatively homogeneous regions, information on species responses to finer-grained (edaphic) variables is crucial (see Beck et al. 2012), as shown by Kelly, Leach, Cameron, Maggs, and Reid (2014) in a study on invasive plants. Our results suggest that response optima and Ellenberg values both perform reasonably well, but do not succeed to differentiate between species with highly similar preferences but diverging limits [...]

[::(3)] Knowing that edaphic species thresholds matter and that at the same time edaphic limits are not yet quantified for most species and variables is alarming, because the conservation of species will depend on a thorough understanding of the ecological niches of species and where these are met, now and in future. Given the long tradition of vegetation science in Central Europe and in other parts of the world, with hundreds of thousands of plots being available, we still know little about the species' niches and especially their limits. [...]},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13841261,forest-resources,habitat-suitability,limiting-factor,niche-modelling,soil-resources,uncertainty},
  number = {7}
}
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