View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Open Archive Toulouse Archive Ouverte Open Archive TOULOUSE Archive Ouverte (OATAO) OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 10199 To link to this article : DOI:10.1007/s10980-013-9892-y URL : http://dx.doi.org/10.1007/s10980-013-9892-y To cite this version : Bernadou, Abel and Céréghino, Régis and Barcet, Hugues and Combe, Maud and Espadaler, Xavier and Fourcassié, Vincent. Physical and land-cover variables influence ant functional groups and species diversity along elevational gradients. (2013) Landscape Ecology, vol. 28 (n° 7). pp. 1387-1400. ISSN 0921-2973 Any correspondance concerning this service should be sent to the repository administrator: [email protected] Physical and land-cover variables influence ant functional groups and species diversity along elevational gradients Abel Bernadou · Régis Céréghino · Hugues Barcet · Maud Combe · Xavier Espadaler · Vincent Fourcassié Abstract Of particular importance in shaping spe­ characterize the relationship between the spatial cies assemblages is the spatial heterogeneity of the distribution of ant functional groups, species diversity, environment. The aim of our study was to investigate and the variables measured. The use of SOM allowed the influence of spatial heterogeneity and environ­ us to reduce the apparent complexity of the environ­ mental complexity on the distribution of ant functional ment to five clusters that highlighted two main groups and species diversity along altitudinal gradi­ gradients: an altitudinal gradient and a gradient of ents in a temperate ecosystem (Pyrenees Mountains). environmental closure. The composition of ant func­ During three summers, we sampled 20 sites distributed tional groups and species diversity changed along both across two Pyrenean valleys ranging in altitude from of these gradients and was differently affected by 1,009 to 2,339 rn by using pitfall traps and band environmental variables. The SOM also allowed us to collection. The environment around each sampling validate the contours of most ant functional groups by points was characterized by using both physical and highlighting the response of these groups to the land-cover variables. We then used a self-organizing environmental and land-cover variables. map algorithm (SOM, neural network) to detect and Keywords Ants · Community ecology · Elevation gradient · Landscape heterogeneity ·Neural networks · Pyrenees A. Bemadou (r:gJ) ·M. Combe · V. Fourcassié H. Barcet Centre de Recherches sur la Cognition Animale, UPS, UMR 5602 CNRS, Maison de la Recherche du Mirail, CNRS, Université de Toulouse, 118 route de Narbonne, Geode, Université Toulouse II-Le Mirail, 5 Allées 31062 Toulouse cedex 9, France A Machado, 31058 Toulouse, France e-mail: [email protected] X. Espadaler Present Address: Departament de Biologia Animal, de Biologia Vegetal A. Bemadou i d'Ecologia, Facultat de Ciències, Universitat Autônoma Evolution, Behaviour & Genetics-Biology 1, University de Barcelona, 08193 Bellaterra, Spain of Regensburg, UniversitiitsstraBe 31, 93053 Regensburg, Germany R. Céréghino EcoLab, Université Paul Sabatier, Batiment 4R1, 118 Route de Narbonne, 31062 Toulouse cedex 4, France Introduction Andersen 2003), South (Bestelmeyer and Wiens 1996) and North America (Andersen 1997a; Stephens One of the main concerns in community ecology is to and Wagner 2006), and Asia (Pfeiffer et al. 2003), this identify the environmental factors (either biotic or method has been rarely used to study the ant fauna of abiotic) that shape species assemblages (Rosenzweig Europe (but see G6mez et al. 2003). 1995). Of particular importance in this respect is the Environmental heterogeneity may act at multiple heterogeneity created by the variation of these factors. scales on animais, both spatially and temporally According to the hypothesis of habitat heterogeneity (Wiens 1989; Levin 1992). All ofthese scales however suggested by MacArthur and MacArthur (1961), may not be relevant to understand how an animal species richness should increase with increasing interacts with its environment and the choice of the structural complexity of the environment. This rela­ spatial scale at which to study environmental hetero­ tionship has indeed been found in many taxa, e.g. geneity should be consistent with its perception of the arthropods, birds, mammals, amphibians or reptiles environment. This requires the selection of appropri­ (see Tews et al. 2004 for a review). Environmental ate descriptive variables (Turner et al. 2001 ). Physical, heterogeneity can significantly influence not only chemical and biological data, however, are often species richness but also their relative distribution. difficult to analyze in an integrated way because they The distribution of ants for example is significantly are complex, noisy, and vary and covary in a non­ affected by the spatial heterogeneity generated by fire linear way (Lek and Guégan 2000). One solution is to (Parr and Andersen 2008), anthropogenic disturbances use modeling techniques, such as artificial neural (Kalif et al. 2001 ), habitat fragmentation (Vasconcelos networks, that are able to take into account the et al. 2006), or grazing (Bestelmeyer and Wiens 1996). complex structure of multi-dimensional datasets Natural gradients (e.g. altitude, latitude) are also a (Chon 2011 ). For example, the Self-Organizing Map major source of spatial heterogeneity that can influ­ algorithm (SOM, unsupervised neural network, Ko­ ence the structure of species assemblages. Mountain­ honen 2001) is a powerful and well-suited tool to ous areas in particular are characterized by rapid detect patterns in animal communities in relation to changes in climate, soil, or vegetation, over relatively environmental variables (Lek and Guégan 2000). short distances (Korner 2007). They thus offer SOMs have been used in ecology to study mostly considerable landscape heterogeneity on a condensed aquatic insect or fish communities (e.g. Compin and area and are ideal for exploring the ecological Céréghino 2007; ants: Groc et al. 2007; Delabie et al. mechanisms underlying spatial patterns in species 2009; Céréghino et al. 2010). In this study we used richness and distribution. SOM to fulfill two main objectives: (1) to describe In this study, we investigated the influence of landscape spatial patterns along altitudinal gradients spatial heterogeneity and environmental complexity and to explore whether the apparent complexity of along altitudinal gradients on the distribution of ant mountain environments can be reduced to a few functional groups and species diversity across two simple elements and (2) to address the question ofhow Pyrenean valleys: one located in Andorra, on the ant functional groups and pattern of species diversity Southern side of the Pyrenees (the Madriu-Perafita­ respond to the changes in land-cover and physical Claror valley), and another located in France, on the variables along these gradients. Northern side of the Pyrenees (the Pique valley). The categorization of organisms into functional groups has been widely used in the study of animal communities Methods (birds: Cody 1985; reptiles: Piank:a 1986). Species classification by functional groups reduces the appar­ Study area and sampling sites ent complexity of animal communities (Andersen 1997a) and thus facilitates the understanding of the Our study area was located in the Pyrenees, a general principles that govern the functioning of mountain range located in south-west Europe and that ecosystems. Although the classification in functional is shared between Spain, France and the Principality of groups has been used to study the ant fauna Andorra. Because of their orientation and geographie of Australia (Andersen 1995; Hoffmann and location, these mountains present considerable climatic contrasts. The northem and western sides of Sampling methods and species identification the Pyrenees have an oceanic climate, with rainfall throughout the year, mild winters and cool summers. At each of the 20 sites, we used a variation of the ALL The southem side in contrast has a more continental protocol (Agosti et al. 2000) to sample the ants. A climate, characterized by high solar radiation, torren­ 190 rn long line transect was traced and sampling tial rains at equinoxes, large temperature variations, points were placed on this line every 10 rn (mak:ing a and very cold winters and dry summers. total of 20 sampling points per site, yielding a total400 Two valleys were sampled in this study: the sampling points for the two valleys). The position of Madriu-Perafita-Claror, in Andorra, and the Pique the sampling points were recorded by means of a GPS valley, in France. The Madriu-Perafita-Claror valley is (Garmin® eTrex®) and subsequently loaded into a glacial valley located in the southeast part of DNA-GIS, a free geographie information system Andorra that covers an area of 4,247 ha. The valley (www .diva-gis.org). is oriented along an east-west axis and extends along Two collection methods were used to sample the an altitudinal gradient ranging from 1,055 to 2,905 m. ants at each sampling point: pitfall traps and hand The valley is well preserved: the production of timber collection. The pitfall traps consisted of plastic