Habitat productivity is a poor predictor of body size in rodents

Abstract

The "resource availability hypothesis" predicts occurrence of larger rodents in more productive habitats. This prediction was tested in a dataset of 1,301 rodent species. We used adult body mass as a measure of body size and normalized difference vegetation index (NDVI) as a measure of habitat productivity. We utilized a cross-species approach to investigate the association between these variables. This was done at both the order level (Rodentia) and at narrower taxonomic scales. We applied phylogenetic generalized least squares (PGLS) to correct for phylogenetic relationships. The relationship between body mas and NDVI was also investigated across rodent assemblages. We controlled for spatial autocorrelation using generalized least squares (GLS) analysis. The cross-species approach found extremely low support for the resource availability hypothesis. This was reflected by a weak positive association between body mass and NDVI at the order level. We find a positive association in only a minority of rodent subtaxa. The best fit GLS model detected no significant association between body mass and NDVI across assemblages. Thus, our results do not support the view that resource availability plays a major role in explaining geographic variation in rodent body size.

Keywords: Bergmann’s rule; body size (body mass); habitat productivity; heat conservation hypothesis; normalized difference vegetation index (NDVI); resource availability hypothesis.

Figure 1.

Scatterplot of species-level NDVI values (unitless) versus species-level body mass values (grams) for order Rodentia (A). The red dashed line is the line of best fit based on the PGLS regression of the observed data (the points shown on the plot). The shaded blue area is the region occupied by the lines of best fit for each one of the 1,000 vectors of randomized log body mass values (the points are not shown on the plot). In (B), from top to bottom, a histogram showing the frequency distribution of the adjusted R² values of each randomized PGLS analysis, followed by a frequency distribution of the λ values estimated from the residuals of the regression model (using maximum likelihood), and the P-values for each randomized PGLS. The red vertical line indicates P = 0.05. Results of the empirical PGLS analysis are shown in Table 1 and those of the randomized PGLS analyses are found in Supplementary Table S5.

Figure 2.

Map of the assemblage-level NDVI values. This map and the associated color scale depict the values of the actual 1.5-degree grid cells used in the cross-assemblage analysis (those in Supplementary Table S4). Negative NDVI values (close to zero) represent permanently snow-covered terrestrial habitats with no discernable vegetation. The white regions of the map denote missing data. The latitude and the longitude are indicated in the Y- and X-axes, respectively.

Figure 3.

Map of the assemblage-level body mass values (logged). This map and the associated color scale depict the values of the actual 1.5-degree grid cells used in the cross-assemblage analysis (those in Supplementary Table S4). The white regions of the map denote regions where none of the 1,301 species are present. The latitude and the longitude are indicated in the Y- and X-axes, respectively.

Figure 4.

Scatterplot of assemblage-level NDVI values (unitless) versus assemblage-level body mass values (in grams). The red dashed line corresponds to the regression line of best fit. Each point corresponds to one of the 7,602 grids cells used in the regression models.