Literature DB >> 26290621

Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps.

Diego Nieto-Lugilde1, Jonathan Lenoir2, Sylvain Abdulhak3, David Aeschimann4, Stefan Dullinger5, Jean-Claude Gégout6, Antoine Guisan7, Harald Pauli8, Julien Renaud9, Jean-Paul Theurillat10, Wilfried Thuiller9, Jérémie Van Es3, Pascal Vittoz7, Wolfgang Willner11, Thomas Wohlgemuth12, Niklaus E Zimmermann12, Jens-Christian Svenning13.   

Abstract

The role of competition for light among plants has long been recognised at local scales, but its importance for plant species distributions at larger spatial scales has generally been ignored. Tree cover modifies the local abiotic conditions below the canopy, notably by reducing light availability, and thus, also the performance of species that are not adapted to low-light conditions. However, this local effect may propagate to coarser spatial grains, by affecting colonisation probabilities and local extinction risks of herbs and shrubs. To assess the effect of tree cover at both the plot- and landscape-grain sizes (approximately 10-m and 1-km), we fit Generalised Linear Models (GLMs) for the plot-level distributions of 960 species of herbs and shrubs using 6,935 vegetation plots across the European Alps. We ran four models with different combinations of variables (climate, soil and tree cover) at both spatial grains for each species. We used partial regressions to evaluate the independent effects of plot- and landscape-grain tree cover on plot-level plant communities. Finally, the effects on species-specific elevational range limits were assessed by simulating a removal experiment comparing the species distributions under high and low tree cover. Accounting for tree cover improved the model performance, with the probability of the presence of shade-tolerant species increasing with increasing tree cover, whereas shade-intolerant species showed the opposite pattern. The tree cover effect occurred consistently at both the plot and landscape spatial grains, albeit most strongly at the former. Importantly, tree cover at the two grain sizes had partially independent effects on plot-level plant communities. With high tree cover, shade-intolerant species exhibited narrower elevational ranges than with low tree cover whereas shade-tolerant species showed wider elevational ranges at both limits. These findings suggest that forecasts of climate-related range shifts for herb and shrub species may be modified by tree cover dynamics.

Entities:  

Keywords:  biotic interactions; biotic modifiers; facilitation; light competition; plant-plant interactions; shade tolerance; spatial grain; species distribution models

Year:  2015        PMID: 26290621      PMCID: PMC4538783          DOI: 10.1111/ecog.00954

Source DB:  PubMed          Journal:  Ecography        ISSN: 0906-7590            Impact factor:   5.992


  21 in total

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4.  Modeling species co-occurrence by multivariate logistic regression generates new hypotheses on fungal interactions.

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Journal:  Ecology       Date:  2010-09       Impact factor: 5.499

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6.  A significant upward shift in plant species optimum elevation during the 20th century.

Authors:  J Lenoir; J C Gégout; P A Marquet; P de Ruffray; H Brisse
Journal:  Science       Date:  2008-06-27       Impact factor: 47.728

7.  A working guide to boosted regression trees.

Authors:  J Elith; J R Leathwick; T Hastie
Journal:  J Anim Ecol       Date:  2008-04-08       Impact factor: 5.091

8.  Niches and distributional areas: concepts, methods, and assumptions.

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Journal:  Proc Natl Acad Sci U S A       Date:  2009-09-23       Impact factor: 11.205

9.  Macroecological signals of species interactions in the Danish avifauna.

Authors:  Nicholas J Gotelli; Gary R Graves; Carsten Rahbek
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-01       Impact factor: 11.205

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Authors:  M D Bertness; R Callaway
Journal:  Trends Ecol Evol       Date:  2003-11-07       Impact factor: 17.712

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Journal:  J Biogeogr       Date:  2016-03-22       Impact factor: 4.324

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