Taxonomic and regional uncertainty in species-area relationships and the identification of richness hotspots

Laboratoire Ecosystèmes Lagunaires, Unité Mixte de Recherche 5119, Centre National de la Recherche Scientifique-IFREMER-UM2, Université Montpellier 2, cc 093, Place Eugène Bataillon, 34095 Montpellier Cedex 5, France.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 11/2008; 105(40):15458-63. DOI: 10.1073/pnas.0803610105
Source: PubMed


Species-area relationships (SARs) are fundamental to the study of key and high-profile issues in conservation biology and are particularly widely used in establishing the broad patterns of biodiversity that underpin approaches to determining priority areas for biological conservation. Classically, the SAR has been argued in general to conform to a power-law relationship, and this form has been widely assumed in most applications in the field of conservation biology. Here, using nonlinear regressions within an information theoretical model selection framework, we included uncertainty regarding both model selection and parameter estimation in SAR modeling and conducted a global-scale analysis of the form of SARs for vascular plants and major vertebrate groups across 792 terrestrial ecoregions representing almost 97% of Earth's inhabited land. The results revealed a high level of uncertainty in model selection across biomes and taxa, and that the power-law model is clearly the most appropriate in only a minority of cases. Incorporating this uncertainty into a hotspots analysis using multimodel SARs led to the identification of a dramatically different set of global richness hotspots than when the power-law SAR was assumed. Our findings suggest that the results of analyses that assume a power-law model may be at severe odds with real ecological patterns, raising significant concerns for conservation priority-setting schemes and biogeographical studies.

Download full-text


Available from: David Mouillot, Feb 15, 2014
50 Reads
  • Source
    • "Essentially, larger sampled areas support higher number of individuals and therefore increase the probability of encountering additional species, as well as increased chances of finding environmental heterogeneity and species that differ in their niches (Pihl et al. 2002; Scheiner 2003; Guilhaumon et al. 2008, 2012). We consider the possibility that species richness in estuaries can increase with habitat area (Horn & Allen 1976; Monaco, Lowery & Emmett 1992; Nicolas et al. 2010). "
    [Show abstract] [Hide abstract]
    ABSTRACT: 1.Knowledge on global patterns of biodiversity and regulating variables is indispensable to develop predictive models. 2.The present study used predictive modelling approaches to investigate hypotheses that explain the variation in fish species richness between estuaries over a worldwide spatial extent. Ultimately, such models will allow assessment of future changes in ecosystem structure and function as a result of environmental changes. 3.A comprehensive worldwide database was compiled on the fish assemblage composition and environmental characteristics of estuaries. Generalized Linear Models were used to quantify how variation in species richness among estuaries is related to historical events, energy dynamics, and ecosystem characteristics, whilst controlling for sampling effect. 4.At the global extent, species richness differed among marine biogeographic realms and continents, and increased with mean sea surface temperature, terrestrial net primary productivity, and the stability of connectivity with marine ecosystem (open versus temporarily open estuaries). At a smaller extent (within marine biogeographic realm or continent) other characteristics were also important in predicting variation in species richness, with species richness increasing with estuary area and continental shelf width. 5.The results suggest that species richness in an estuary is defined by predictors that are spatially hierarchical. Over the largest spatial extents species richness is influenced by the broader distributions and habitat use patterns of marine and freshwater species that can colonize estuaries, which are in turn governed by history contingency, energy dynamics and productivity variables. Species richness is also influenced by more regional and local parameters that can further affect the process of community colonization in an estuary including the connectivity of the estuarine with the adjacent marine habitat, and, over smaller spatial extents, the size of these habitats. In summary, patterns of species richness in estuaries across large spatial extents seem to reflect from global to local processes acting on community colonization. The importance of considering spatial extent, sampling effects and of combining history and contemporary environmental characteristics when exploring biodiversity is highlighted.
    Journal of Animal Ecology 03/2015; 84(5). DOI:10.1111/1365-2656.12372 · 4.50 Impact Factor
  • Source
    • "Our results demonstrate that SARs in land plants are shaped by extrinsic and intrinsic factors, challenging purely neutral models such as the mathematical expression of MacArthur & Wilson's (1967) theory. This highlights the importance of applying integrative frameworks that take both geological histories and taxonomic idiosyncrasies into account in SAR studies, which has critical consequences for the use of the SAR in conservation biology (Guilhaumon et al., 2008; Sólymos & Lele, 2012 "
    [Show abstract] [Hide abstract]
    ABSTRACT: AimAlthough the increase in species richness with increasing area is considered one of the few laws in ecology, the role of environmental and taxon-specific features in shaping species–area relationships (SARs) remains controversial. Using 421 land-plant floras covering continents, continental islands and oceanic islands, we investigate whether variations in SAR parameters can be interpreted in terms of differences among lineages in speciation mode and dispersal capacities (TAXON), or of geological history and geographical isolation between continents and islands (GEO).LocationGlobal.Methods Linear mixed-effects models describing variation in SARs, depending on the factors GEO and TAXON and controlling for differences between realms (REALM) and biomes (BIOME).ResultsThe best random-effect structure included both random slopes and random intercepts for GEO, TAXON, REALM and BIOME. This accounted for 77% of the total variation in species richness, substantially more than the 27% statistically explained by the model with fixed effects only (i.e. the simple SAR). The slopes of the SARs were higher for oceanic islands than for continental islands and continents, and higher in spermatophytes than in pteridophytes and bryophytes. The intercepts largely exhibited the reverse trend. TAXON was included in best-fit models restricted to oceanic and continental islands, but not continents. Analysing each plant lineage separately, the intercept of GEO was only included in the random structure of spermatophytes.Main conclusionsSAR parameters varied considerably depending on geological history and taxon-specific traits. Such differences in SARs among land plants challenge the neutral theory that the accumulation of species richness on islands is controlled exclusively by extrinsic factors. Taxon-specific differences in SARs were, however, confounded by interactions with geological history and geographical isolation. This highlights the importance of applying integrative frameworks that take both environmental context and taxonomic idiosyncrasies into account in SAR analyses.
    Global Ecology and Biogeography 11/2014; 23(11):1275-1283. DOI:10.1111/geb.12230 · 6.53 Impact Factor
  • Source
    • "In classic island biogeography, richness should increase with area because of the parallel influences of patch area (larger patches support more individuals) and habitat heterogeneity (Rosenzweig, 1995; Ricklefs & Lovette, 1999). Studies deriving empirical SARs typically have done so from sets of islands or island-like patches that vary in size (Stiles & Scheiner, 2007; Guilhaumon et al., 2008; Williams et al., 2009; Honkanen et al., 2010). In contrast, in the typical conservation situation, area remains unchanged. "
    Dataset: geb2011
Show more