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Variation partition analysis explaining the percentage of variation explained by abiotic (environmental distance) and spatial variables (geographical distance) of forest community and rubber monoculture community based on 18SrRNA gene sequences; see Materials & Methods section.
However, spatial genetic turnover (allele frequency variation across space) is influenced by geographical and environmental distance, suggesting that genetic connectivity, and by extension landscape connectivity, is impacted by gaps in the PA network.
The relationship between community similarity and environmental distance is a result of comparing tropical/subtropical waters with highly productive systems characteristic of the sub-Antarctic region.
To quantify the importance of environmental conditions on community structure, we calculated the 'site-to-site' environmental distance using five different nutritional variables: nitrate plus nitrite, phosphate and silicate concentration in seawater, the depth of the nutricline and the nutristad (the gradient of nitrate in the nutricline).
Across the sub-Antarctic front community similarity was correlated with environmental distance in AMT 3 4, and with geographic distance in AMT 2. Community similarity was correlated with both environmental and geographic distance in AMT 1, but the relationship was not significant when holding matrices constant (Table 2).
QST was associated with environmental distance, suggesting ecological selection for phenotypic divergence.
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El, Arad, SOM, pH and LP were used to estimate the environmental distances between SUs.
For each of the two regions, we accounted for environmental distances between plots by first fitting the best model of the floristic similarity matrix (simjk) against the six Ellenberg's distance matrices and the plot size distance matrix.
For each of the two regions, multiple linear regressions on distance matrices (MRM) [57], [58] were then used to analyse the dependency of plot-to-plot β-diversity on geographical distances between plots, after accounting for environmental distances.
In analyses using all sites, no statistically significant correlations were detected between genetic distance (FST) and environmental distances (spawning temperature and salinity, April temperature and salinity).
We used Mantel and partial Mantel tests implemented in R to test for correlations between genetic distance (as measured by FST) for the three different datasets and environmental distances.
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