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Data from: Current climate, but also long-term climate changes and human impacts, determine the geographic distribution of European mammal diversity


Coelho dos Santos, Ana Margarida et al. (2021), Data from: Current climate, but also long-term climate changes and human impacts, determine the geographic distribution of European mammal diversity, Dryad, Dataset,


Aim. Historical climate variations, current climate and human impacts are known to influence current species richness, but their effects on phylogenetic and trait diversity have been seldom studied. We investigated the relationship of these three factors with the independent variations of species, phylogenetic and trait diversity of European mammals. Considering the position of the 0ºC isotherm in the Last Glacial Maximum as a tipping point, we tested the following hypotheses: northern European assemblages host less species than southern European ones; northern areas harbour trait and phylogenetically clustered assemblages, while the more stable southern areas host random or overdispersed assemblages; and, species richness increases with human influence, while phylogenetic and trait diversity show clustered patterns in areas with stronger human influence.

Location. Western Palearctic.

Time period. Current and Late-Pleistocene effects on present-day diversity.

Major taxa studied. Terrestrial mammals.

Methods. We used a novel analytical approach based on distance matrices to separate the independent variations of species, phylogenetic and trait diversity, and assessed their relationships with current climate, climate stability and human influence through structural equation models.

Results. The species-poor assemblages from northern Europe show higher phylogenetic and trait clustering than the more stable richer southern areas. However, no assemblage presented trait nor phylogenetic overdispersion. Current climate is the primary driver of phylogenetic and trait diversity, while species richness is affected similarly by both current and past climates. Higher human influence correlates positively with species richness and trait diversity, both directly and by mediating indirect effects of present climate.

Main conclusions. Current climate, climate stability and human influence affect the studied aspects of diversity, although the form and magnitude of their effects varies through space. Importantly, higher levels of human disturbances correlate with more speciose and trait diverse assemblages, an apparently counterintuitive result that deserves further study.


Data on the distribution of native terrestrial (both volant and non-volant) mammal species were obtained from IUCN (2016), using a 100 km equal-area grid (i.e. with 10,000 km2 cells) encompassing the whole Western Palearctic, i.e. both Europe and the Mediterranean region (European grid, based on the ETRS89 Lambert Azimuthal Equal-Area projection; it also includes the Mediterranean Islands and Northern Africa). This region hosts 357 mammal species, which constitute the regional pool of species that can potentially colonise any grid cell, and therefore were used as the source pool for all community assembly analyses described below. The extent of the analyses was limited to mainland Europe (comprising Great Britain and Russia up to the Ural Mountains), the Anatolian Peninsula, Syria and Israel. In total, these territories host 354 mammal species. We excluded cells that had less than 95% of land surface.

Species richness (S_R) was calculated as the number of species recorded in each grid cell.

We used a dated mammalian ‘supertree’ (Bininda-Emonds et al., 2007, updated by Fritz et al., 2009), modifying it according to the IUCN Red List taxonomic nomenclature (IUCN, 2016). For each assemblage (i.e. each grid cell), we calculated phylogenetic diversity (PD) using Faith’s (1992) index, corresponding to the total branch length of a phylogenetic tree that connects all species within an assemblage. Afterwards, we calculated net phylogenetic diversity (nPD; herein called phylogenetic diversity for simplicity), i.e. the PD that is independent of species richness. To do this, we first created 1000 random assemblages from the species pool with the same species richness of each real assemblage, by shuffling species labels across the tips of the phylogeny. Second, we calculated nPD as the difference between the observed PD and the mean PD of the randomisations, divided by the standard deviation of the randomised PD values; therefore, nPD corresponds to the standardised effect size of each assemblage (Gotelli & Rohde, 2002). Negative nPD values correspond to assemblages with species that are phylogenetically clustered (i.e. evolutionarily closer than expected by chance), whereas positive values indicate phylogenetically overdispersed assemblages (i.e. more distant than expected by chance).

Trait (functional) diversity was calculated using Petchey & Gaston’s (2002) FD (herein named FD). Trait data were obtained from PanTheria database (Jones et al., 2009) and updated using additional sources (as in Hidasi-Neto et al., 2015; Safi et al., 2011). The selected traits include: (i) body mass (in grams), (ii) diet (i.e. vertebrates, invertebrates, foliage, stems and bark, grass, fruits, seeds, flowers, nectar and pollen, roots and tuber); (iii) habitat (aquatic, fossorial, ground-dwelling, aboveground dwelling, aerial) and activity period (cathemeral, crepuscular, diurnal, nocturnal). When trait data were missing for a given species, median values for the genus were used. To calculate FD we started by producing a distance matrix from a trait matrix (using a modified version of Gower’s distance; Pavoine et al., 2009), converting it into a dendrogram (using UPGMA), and calculating the sum of branch lengths across it. In this case, the dendrogram was built using trait information of all mammal species present in the species pool. We also calculated net trait diversity (nFD), i.e. the FD that is independent of species richness, in the same way as nPD. Finally, we calculated phylogenetically-independent trait diversity from the residuals of the regression between the trait and phylogenetic distance matrices (using absolute distance values). These residuals were then used to construct a new dendrogram, which in turn was used to calculate the net phylogenetically-independent trait diversity (npiFD), following the same steps as for nPD and nFD. As in the case of nPD, negative values of npiFD indicate assemblages with species that are functionally clustered (i.e. species with trait values more similar than expected by chance), whereas positive values indicate trait overdispersed assemblages (i.e. more different than expected by chance)

Current and historical climate data were gathered from the ECHAM3 paleoclimatic model (Braconnot et al., 2007; processed as in Calatayud et al., 2016; Hortal et al., 2011), and included current temperature (TEMP_0K) and precipitation (PCIP_0K), and temperature and precipitation stability since the LGM (TSTAB_0-21k; PSTAB_0-21k, respectively). Comparability between these variables was attained by extracting all information from the same Atmosphere-Ocean General circulation model, i.e. using a downscaled version of the ECHAM3 paleoclimatic model (Braconnot et al., 2007). The impact of human activities (i.e. anthropogenic effects) was measured with the Human Influence Index (HII; Sanderson et al., 2002).


Bininda-Emonds, O. R. P., Cardillo, M., Jones, K. E., MacPhee, R. D. E., Beck, R. M. D., Grenyer, R., … Purvis, A. (2007). The delayed rise of present-day mammals. Nature, 446, 507-512. Corrigendum (2008) Nature, 456, 274.

Braconnot, P., Otto-Bliesner, B., Harrison, S., Joussaume, S., Peterchmitt, J. Y., Abe-Ouchi, A., ... Zaho, Y. (2007). Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum -  Part 1: experiments and large-scale features. Climate of the Past, 3, 261-277.

Calatayud, J., Hortal, J., Medina, N. G., Turin, H., Bernard, R., Casale, A. … Rodríguez, M. A. (2016). Glaciations, deciduous forests, water availability and current geographical patterns in the diversity of European Carabus species. Journal of Biogeography, 43, 2343-2353.

Faith, D. P. (1992). Systematics and conservation: on predicting the feature diversity of subsets of taxa. Cladistics, 8, 361-373.

Fritz, S. A., Bininda-Emonds, O. R. P., & Purvis, A. (2009). Geographical variation in predictors of mammalian extinction risk: big is bad, but only in the tropics. Ecology Letters, 12, 538–549.

Gotelli, N. J., & Rohde, K. (2002). Co-occurrence of ectoparasites of marine fishes: a null model analysis. Ecology Letters, 5, 86-94.

Hidasi-Neto, J., Loyola, R., & Cianciaruso, M. V. (2015). Global and local evolutionary and ecological distinctiveness of terrestrial mammals: identifying priorities across scales. Diversity & Distributions, 21, 548-559.

Hortal, J., Diniz-Filho, J. A. F., Bini, L. M., Rodríguez, M. Á., Baselga, A., Nogués-Bravo, D., ... Lobo, J. M. (2011). Ice age climate, evolutionary constraints and diversity patterns of European dung beetles. Ecology Letters, 14, 741-748.

IUCN (2016). The IUCN Red List of Threatened Species. Version 2016-3. <>.

Jones, K. E., Bielby, J., Cardillo, M., Fritz, S. A., O'Dell, J., Orme, C. D. L., … Michener, W. K. (2009). PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology, 90, 2648-2648.

Pavoine, S., Vallet, J., Dufour, A.-B., Gachet, S., & Daniel, H. (2009). On the challenge of treating various types of variables: application for improving the measurement of functional diversity. Oikos, 118, 391-402.

Petchey, O. L., & Gaston, K. J. (2002). Functional diversity (FD), species richness and community composition. Ecology Letters, 5, 402-411.

Safi, K., Cianciaruso, M. V., Loyola, R. D., Brito, D., Armour-Marshall, K., & Diniz-Filho, J. A. F. (2011). Understanding global patterns of mammalian functional and phylogenetic diversity. Philosophical Transactions of the Royal Society B, 366, 2536-2544.

Sanderson, E. W., Jaiteh, M., Levy, M. A., Redford, K. H., Wannebo, A. V., & Woolmer, G. (2002). The human footprint and the last of the wild. Bioscience, 52, 891-904.

Usage Notes

Table Headers:

ET_ID: Grid Cell Identifier

X: Longitude of the centroid in UTM coordinates

Y: Latitude of the centroid in UTM coordinates

S_R: Species Richness

PD: Phylogenetic Diversity (sensu Faith, 1992)

nPD: Net Phylogenetic Diversity

FD: Functional Diversity (sensu Petchey & Gaston, 2002)

nFD: Net Functional Diversity

npiFD: Net phylogenetically-independent functional diversity

TEMP_0K: Current temperature

PCIP_0K: Current precipitation

TSTAB_0-21k: Temperature stability since the Last Glacial Maximum

PSTAB_0-21k: Precipitation stability since the Last Glacial Maximum

HII: Human Influence Index

N_S: Cell placed North or South of the 0ºC isotherm of the Last Glacial Maximum (categorical)


CSIC & CNPq, Award: P2011BR0071

Conselho Nacional de Desenvolvimento Científico e Tecnológico, Award: PVE 314523/2014-6

FP7 People: Marie-Curie Actions, Award: IEF 331623 ‘COMMSTRUCT’

Ministerio de Ciencia, Innovación y Universidades, Award: IJCI-2014-19502

Universidad de Alcalá, Award: Ayudas de movilidad de personal docente y personal investigador

Fundação para a Ciência e a Tecnologia, Award: CEEIND/03425/2017

Conselho Nacional de Desenvolvimento Científico e Tecnológico, Award: 306694/2018-2

MCTIC/CNPq/FAPEG , Award: 465610/2014-5

CSIC & CNPq, Award: P2011BR0071

MCTIC/CNPq/FAPEG, Award: 465610/2014-5