Comparison of the mean accuracy (AUC) of SDM models over 1000 simulated taxa.

<p>Sample clumping is caused by either biological or random processes. Panels show the predictive accuracy of data subsets binned into either high or low clumping and high or low coverage of the simulated true range. Points represent mean AUC scores from 1000 validation points per taxa and whiskers 95% confidence intervals around each mean, where scores less than 0.5 represent no accuracy gain over random chance. Spatial INLA—Bayesian SDM inferred using Integrated Nested Laplace Approximation with a spatial autocorrelation term, Non-spatial INLA—Bayesian SDM inferred using INLA without a spatial autocorrelation term, BRT—boosted regression trees based SDM, MAXENT—maximum entropy based SDM.</p

Comparison of mean accuracy (AUC) of spatially-explicit INLA SDM models on 1000 simulated taxa when varying the complexity of the underlying spatial mesh.

<p>Colours show the predictive accuracy of data subsets binned into either high or low clumping and high or low coverage of the simulated true range. Points represent mean AUC scores across 1000 taxa and whiskers 95% confidence intervals around each mean, where scores less than 0.5 represent no accuracy gain over random chance.</p

Comparison of the mean accuracy (AUC) of SDM models over 1000 simulated taxa when altering the pseudo-absence (background) point configurations and the effects of spatial thinning of presence points, on four SDM methods and across 4 types of dataset with different clumping and spatial bias.

<p>Panels show the predictive accuracy of data subsets binned into either high or low clumping and high or low coverage of the simulated true range. Where R represents random absence points, ST—spatial thinning, SW—spatially weighted absence points, B—both weighting and thinning (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0187602#pone.0187602.s009" target="_blank">S1 Table</a>) and Spatial INLA—Bayesian INLA model with spatial random effect, Non-spatial INLA—Bayesian INLA model without spatial autocorrelation term, BRT—boosted regression trees, and MAXENT—Maximum entropy based model. Points represent mean AUC scores from 1000 validation points per taxa and whiskers 95% confidence intervals around each mean, where scores less than 0.5 represent no accuracy gain over random chance.</p

Patterns of incidence illustrating some of the possible outcomes of the proposed analytical framework.

<p>A) emergence, b) receding, c) re-emergence, d) receding after emergence, e) emergence and further emergence, f) receding, emergence, stability. Segments in red show significantly positive slopes for that time period, segments in green show significantly negative slopes, and segments in yellow indicate a non-significant trend (p>0.05).</p

Data for each of the 4 classifiers

There are 4 sheets in the excel file. Each sheet contains the data used for each one of the 4 classifiers. Classifier 1 - Species-level without a hierarchy. Classifier 2 - Species-level within a family hierarchy. Classifier 3 - Species-level within a genus hierarchy. Classifier 4 - Species-level within a guild hierarchy. The species acronyms can be found in the supplementary material of the paper. The column ‘Fold’ indicates to which one of the 5 folds each call was assigned for the 5-folds cross-validation procedure used to estimate the accuracy of each classifier

The total number of species introduced at a country level (i.e., species x country introductions) during the period 1500–2000 AD.

<p>The vertical dotted lines show the approximate locations of the divisions between the four quartiles of introduction; one quarter of all dated introductions in the period 1500–2000 lie to the left of the left-most dotted line, and one quarter lie to the right of the right-most dotted line.</p

Locations of origin and introduction for bird species with introduced populations.

<p><b>(A)</b> The overlap in distribution of native ranges (i.e., richness) of the alien bird species introduced in the first quartile of population introductions ordered by date (1500–1903 AD). <b>(B)</b> Locations of first introduction records for alien bird populations (i.e., state or country-level colonisation pressure) in the first quartile. <b>(C)</b> The overlap in distribution of native ranges of the alien bird species introduced in the fourth quartile of introductions ordered by date (1983–2000 AD). <b>(D)</b> Locations of first introduction records for alien bird populations (i.e., state or country-level colonisation pressure) in the fourth quartile. In <b>(A)</b> and <b>(C)</b>, cold colours represent lower native richness of bird species that were introduced in the period, warm colours represent higher richness, and grey areas are those not covered by the native ranges of any introduced species. In <b>(B)</b> and <b>(D)</b>, cold colours represent countries with low numbers of alien bird population introductions, warm colours represent countries with higher numbers, and grey countries are those without any record of alien bird populations having been introduced during this period. Numbers associated with circles record the number of alien bird species introductions to specific islands that would otherwise not be clearly visible on these maps.</p

Global map of alien bird species richness.

<p>The figure is based on the 362 bird species with established alien distributions recorded with sufficient detail to map (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2000942#sec006" target="_blank">Methods</a>). Colder colours indicate lower bird species richness, while warmer colours represent higher richness. Grey areas are those where there are no established bird populations.</p

Data Paper. Data Paper

<h2>File List</h2><blockquote> <p>Data files are in ASCII format, tab delimited. No compression schemes were used. Data set consists of 5732 records, not including header row.</p> <p><a href="MOMv3.3.txt">MOMv3.3.txt</a></p> </blockquote><h2>Description</h2><blockquote> <p>The purpose of this data set was to compile body mass information for all mammals on Earth so that we could investigate the patterns of body mass seen across geographic and taxonomic space and evolutionary time.  We were interested in the heritability of body size across taxonomic groups (How conserved is body mass within a genus, family, and order?), in the overall pattern of body mass across continents (Do the moments and other descriptive statistics remain the same across geographic space?), and over evolutionary time (How quickly did body mass patterns iterate on the patterns seen today?  Were the Pleistocene extinctions size specific on each continent, and did these events coincide with the arrival of man?).  These data are also part of a larger project that seeks to integrate body mass patterns across very diverse taxa (NCEAS Working Group on Body size in ecology and paleoecology:  linking pattern and process across space, time and taxonomic scales).  We began with the updated version of Wilson and Reeder’s (1993) taxonomic list of all known Recent mammals of the world (<i>N</i> = 4629 species) to which we added status, distribution, and body mass estimates compiled from the primary and secondary literature. Whenever possible, we used an average of male and female body mass, which was in turn averaged over multiple localities to arrive at our species body mass values.  The sources are line referenced in the main data set, with the actual references appearing in a table within the metadata.  Mammals have individual records for each continent they occur on.  Please note that our data set is more than an amalgamation of smaller compilations.  Although we relied heavily a data set for Chiroptera by K. E. Jones (<i>N</i> = 905), the CRC handbook of Mammalian Body Mass (<i>N</i> = 688), and a data set compiled for South America by P. Marquet (<i>N</i> = 505), these total less than half the records in the current database.  The remainder are derived from more than 150 other sources (see reference table).  Furthermore, we include a comprehensive late Pleistocene species assemblage for Africa, North and South America, and Australia (an additional 230 species). “Late Pleistocene” is defined as approximately 11 ka for Africa, North and South America, and as 50 ka for Australia, because these times predate anthropogenic impacts on mammalian fauna. Estimates contained within this data set represent a generalized species value, averaged across gender and geographic space.  Consequently, these data are not appropriate for asking population-level questions where the integration of body mass with specific environmental conditions is important.  All extant orders of mammals are included, as well as several archaic groups (<i>N</i> = 4859 species).  Because some species are found on more than one continent (particularly Chiroptera), there are 5731 entries.  We have body masses for the following:  Artiodactyla (280 records), Bibymalagasia (2 records), Carnivora (393 records), Cetacea (75 records), Chiroptera (1071 records), Dasyuromorphia (67 records), Dermoptera (3 records), Didelphimorphia (68 records), Diprotodontia (127 records), Hydracoidea (5 records), Insectivora (234 records), Lagomorpha (53 records), Litopterna (2 records), Macroscelidea (14 records), Microbiotheria (1 record), Monotremata (7 records), Notoryctemorphia (1 record), Notoungulata (5 records), Paucituberculata (5 records), Peramelemorphia (24 records), Perissodactyla (47 records), Pholidota (8 records), Primates (276 records), Proboscidea (14 records), Rodentia (1425 records), Scandentia (15 records), Sirenia (6 records), Tubulidentata (1 record), and Xenarthra (75 records).  </p> <p>   <i>Key words</i>: <i>body mass; extinct mammals; late Quaternary; macroecology; taxonomy.</i></p> </blockquote