A Multidimensional Functional Trait Approach Reveals the Imprint of Environmental Stress in Mediterranean Woody Communities
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Water availability is one of the most important factors determining species distribution, plant community structure and ecosystem functioning. We explore how the functional structure of Mediterranean woody plant communities varies along a regional gradient of aridity in the Andalusian region (south Spain). We question whether communities located in more arid sites show more similarity in their functional structure when compared with communities located in wetter sites or whether, instead, there is divergence in their functional spaces. We selected five aridity zones (three sampling sites per zone) and measured 13 traits of different functional dimensions (including leaf, stem and root traits) in 74 woody plant species. We quantified functional space differences using the n-dimensional niche space approach (hypervolume). We found a larger functional space for the wetter communities compared with the more arid communities, which showed greater overlap of the trait space occupation. Our results indicate that aridity acts as a key abiotic filter affecting various metrics of the community trait structure, in accordance with the plant economics spectrum. We have also documented consistent variation in the functional space, supporting lower functional diversity under more harsh climatic conditions. The trend of functional space variation along the aridity gradient was different when considering traits from only one plant organ. Thus, the filtering process driving the functional structure of the communities studied here largely depends on the trait axis considered; for example, the root dimension showed considerable variation in wet environments, whereas the leaf dimension exhibited a larger functional space in the drier habitats.
Keywordsaridity dry shrubland functional diversity functional structure hypervolume plant traits
This study was funded by the Spanish MEC Projects DIVERBOS (CGL2011-30285-C02-01 and C02-02), ECO-MEDIT (CGL2014-53236-R), RESTECO (CGL2014-52858-R) and DECAFUN (CGL2015-70123-R), the Andalusian ANASINQUE project (PGC2010-RNM-5782), the Life + Biodehesa Project (11/BIO/ES/000726), and the European FEDER funds. CV was supported by the European Research Council (ERC) Starting Grant Project ‘Ecophysiological and biophysical constraints on domestication in crop plants’ (Grant ERC-StG-2014-639706-CONSTRAINTS). Thanks are due to Emilio Retamosa and Vicky Schwarzer from the Cabo de Gata Natural Park, for field assistance and plant classification. Isotopic analysis was carried out in the LIE (EBD-CSIC) and analysis of leaf N in the SCAI of the University of Córdoba. Dr. David Walker revised the English.
- Canfield RH. 1941. Application of the line interception method in sampling range vegetation. J For 39:388–94.Google Scholar
- de la Riva EG, Pérez-Ramos IM, Tosto A, Navarro-Fernández CM, Olmo M, Marañón T, Villar R. 2016a. Disentangling the relative importance of species occurrence, abundance and intraspecific variability in community assembly: a trait-based approach at the whole-plant level in Mediterranean forests. Oikos 125:354–63.CrossRefGoogle Scholar
- Heywood VH, Ed. 1995. Global biodiversity assessment. Cambridge: Cambridge University Press.Google Scholar
- Hutchinson GE. 1957. Cold spring harbour symposium on quantitative biology. Concluding Remarks 22:415–27.Google Scholar
- IPCC. 2013. Climate change 2013: the physical scientific basis.WMO, UNEP.Google Scholar
- Klein CH. 2007. Lecture notes for the teaching module forest inventory. Institute of Forest Management, Faculty of Forest Sciences and Forest Ecology. Georg August Universitat, DE.Google Scholar
- Laliberté E, Shipley B. 2011. Measuring functional diversity (FD) from multiple traits, and other tools for functional ecology. 1.0–11.Google Scholar
- Loranger J, Violle C, Shipley B, Lavorel S, Bonis A, Cruz P, Louault F, Loucougaray G, Mesléard F, Yavercovski N, Garnier E. 2016b. Recasting the dynamic equilibrium model through a functional lens: the interplay of trait-based community assembly and climate. J Ecol 104:781–91.CrossRefGoogle Scholar
- Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Oksanen MJ. 2013. Package ‘vegan’. Community ecology package, version, 2(9).Google Scholar
- Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team. 2015. nlme: linear and nonlinear mixed effects models. R package version 3.1-121, http://CRAN.R-project.org/package=nlme.
- Trabucco A, Zomer RJ. 2009. Global Aridity Index (Global-Aridity) and Global Potential Evapo-Transpiration (Global-PET) Geospatial Database. CGIAR Consortium for Spatial Information. Published online, available from the CGIAR-CSI GeoPortal at http://www.csi.cgiar.org.