30 research outputs found
Bioclimatic variables.
<p>Bioclimatic variables used for <i>Pristionchus pacificus s</i>pecies distribution models in the programs DIVA-GIS and MAXENT. Variables (sourced from: Worldclim ver. 1.3, October 2004; <a href="http://www.worldclim.org/" target="_blank">http://www.worldclim.org/</a>) are derived from tmean, tmin, tmax and prec (average monthly mean, minimum and maximum temperature, and average monthly precipitation, respectively).</p
Clustering analyses by environment for <i>Pristionchus pacificus</i>.
<p>Results from INSTRUCT re-coloured according to genetic cluster (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-g003" target="_blank">Fig. 3a</a>) to determine the relationship between cluster and environmental factors in <i>P. pacificus</i> on La Réunion Island. In the graphic, each vertical bar represents a <i>P. pacificus</i> strain and the coloured segments of each bar represent the proportion of that strains’ genetic membership to a particular cluster. Results are presented based on: (a) geography (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-g001" target="_blank">Fig. 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> for location codes); (b) ecozone (‘eco’ = ecozone); (c) altitude (‘alt’ = altitude); and (d) beetle host (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> for beetle codes).</p
SDMs of <i>Pristionchus pacificus</i> and its beetle hosts using DIVA-GIS.
<p>(a) Species distribution models for: (i) <i>P. pacificus,</i> and (ii-v) its beetle hosts: (ii) <i>Adoretus</i> sp., (iii) <i>Hoplochelus marginalis,</i> (iv) <i>Hoplia retusa,</i> and (v) <i>Oryctes borbonicus,</i> on La Réunion Island, draped over a topographical surface at 2.5 arc minute resolution, using the program DIVA-GIS and all bioclimatic variables (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t001" target="_blank">Table 1</a>). Panel (a) demonstrates the geographic distribution of theoretical suitable habitat, with the legend indicating presence probabilities for <i>P. pacificus</i> over five levels in a linear series; level 1 represents the minimum probability value of <i>P. pacificus</i> presence and level 5, the maximum probability presence value, according to a ‘percentile envelope’ based on the various climate variables in the model (for example, category 1 =  low (0–2.5 percentile) indicates a low presence probability of <i>P. pacificus</i>, where dark green areas on the map are those corresponding to climate envelope outliers (in the <2.5 and >97.5 percentile). Species distribution points are indicated with black circles in each case, and Panel (a)(i) shows location codes for all maps. (b) Climatic patterns for La Réunion Island draped over a topographical surface at 2.5 arc minute resolution using the program DIVA-GIS, illustrating the hottest (maximum temperature of warmest month >25°C) and driest (precipitation of driest quarter <150 mm) areas (in red). Panels show individual species distributions (coloured circles) for: (i) <i>P. pacificus,</i> and (ii-v) its beetle hosts: (ii) <i>Adoretus</i> sp., (iii) <i>H. marginalis,</i> (iv) <i>H. retusa,</i> and (v) <i>O. borbonicus</i>. Panel (a)(i) shows the location codes for all maps.</p
PCA analyses by environment for <i>Pristionchus pacificus</i>.
<p>Principal Component Analysis (PCA) performed using the adegenet package in R to seek a summary of the genetic diversity, and its relationship to environmental factors, in <i>P. pacificus</i> on La Réunion Island. Results represented based on: (a) geography (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-g001" target="_blank">Fig. 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> for location codes); (b) ecozone (‘eco’ = ecozone); (c) altitude (‘alt’ = altitude); and (d) beetle host (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> for beetle codes). In each case, axes 1 and 2 did not show clear differentiation among populations, hence PCAs of axes 1 and 3 are shown.</p
Analysis of molecular variance.
<p>ANOVA results for the partitioning of genetic diversity among <i>Pristionchus pacificus</i> La Réunion populations over four separate tests, where populations are defined by beetle, altitude, geographic location or ecozone.Df – degrees of freedom; SS – sum of squares; Var – variance component among populations; % - percentage of variation among populations (NB: the percentage of variation within populations = 1-%); all results are statistically significant (<i>P</i><0.001).</p
Pair-wise Rst.
<p>Pair-wise Rst values among <i>Pristionchus pacificus</i> populations for STR datasets: (a) ecozone; (b) geography; (c) altitude; (d) beetle host; and (e) genetic cluster. Significant values are shown in <i>italics</i>; underlined diagonal is average significant differentiation of each population to all other populations (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> for population codes).</p
Sampling sites and statistics of genetic variation.
<p>Sampling sites and statistics of genetic variation for <i>Pristionchus pacificus</i> populations on La Réunion Island at 19 microsatellite loci for STR datasets: (a) ecozone; (b) geography; (c) altitude; (d) beetle host; and (e) genetic cluster. In all cases, n – sample size; He – expected heterozygosity; T<sub>H</sub> – Theta H; An – number of alleles; As – allelic size range; s.d. - standard deviation. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> for population codes.</p
<i>Pristionchus pacificus</i> diversity and beetle hosts.
<p>(a) Map of La Réunion Island showing the approximate geographic locations (black circles), ecozones (solid lines) and altitudes (visual topography) which were used to examine the effects of environmental variables on genetic structure in <i>P. pacificus</i> (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087317#pone-0087317-t002" target="_blank">Table 2</a> and text for further details); (b) Selected photographs of the beetle hosts of <i>P. pacificus</i> (from left to right, top row: <i>Adoretus</i> sp., <i>Hoplia retusa, Oryctes borbonicus</i>; bottom row: <i>Amneides godefroyi, Maladera affinis, Hoplochelus marginalis</i>), photographs, taken by Mark Leaver, are not to scale; (c) Neighbour-joining tree created in Phylip ver. 3.69 using 19 microsatellite markers and 370 <i>P. pacificus</i> strains, main clusters are colour-coded according to the four described genetic lineages.</p
GESTE results.
<p>Results of seven regression analyses performed in GESTE to examine how much of the variation in genetic structure among <i>Pristionchus pacificus</i> populations on La Réunion Island is explained by variation in environmental factors. The first column shows the environmental factor(s) tested in a given analysis. The second and third columns correspond to the model which best explains the data (where the constant term corresponds to bias that is not accounted for by the terms in the model), and its probability (P), respectively. The remaining four columns give the probability of each individual factor in the highest probability model, with the factor in the far left column corresponding (from left to right) with labels G1, G2 and/or G3 in subsequent columns, and G1*G2 referring to the interaction between factors G1 and G2. Thus, in the first three tests, the probability of the individual factors (environmental variables) in the model is less than that of the a model including only random (constant) effects, whereas in the subsequent two-factor tests, the highest probability models were those that included both factors and their interaction (see Results for further information).</p
RDA analyses for <i>Pristionchus pacificus</i>.
<p>Redundancy analysis (RDA) performed using the vegan package in R to determine the relative contribution of environmental and spatial components driving genetic structure in <i>P. pacificus</i>. The biplot depicts the eigenvalues and lengths of eigenvectors for the RDA conditioned on geography (latitude and longitude); tmin = annual minimum temperature, prec = annual precipitation, temp_s = temperature seasonality. See Results for more information.</p