HANPP and Species Richness

Until very recently, only two studies existed that used the species—energy hypothesis to evaluate the possible significance of HANPP for species endangerment. The first studied estimates of species numbers on a continental scale (Wright 1987); the second studied extinctions on a global scale since the year 1600 (Wright 1990). Although the patterns found in these two studies were consistent with the species—energy hypothesis, their usefulness was limited by the extremely coarse spatial resolution.

In an attempt to present more convincing evidence, we summarize results of two recent correlation analyses aiming to test the utility of HANPP as a pressure indicator for species loss. A direct assessment proved to be impossible: According to the species—energy hypothesis, a reduction in NPPt should result in a decline in species numbers. To test whether HANPP is a valid pressure indicator for biodiversity loss, we should have tested the ability of HANPP to predict species loss (AS), not its relationship to actual species richness (S ). Because there is no information on potential species richness (SQ), there are no data on the change in species richness (AS) as compared with the potential state. Moreover, there is no linear relationship between HANPP and NPPt, the factor that should influence the pattern of S . NPPt can be low because of high HANPP but also because of low NPPQ. Without data on AS it is not possible to test HANPP directly. Indirect tests of HANPP assume that if Sact is correlated to NPPt, this would be evidence that a reduction in NPPt should also lower species richness. This is exactly what we found.

The first study (Haberl et al. 2004a) was based on a transect of 38 squares sized 600 X 600 m in east Austria. Species numbers of seven taxonomic groups (vascular plants, bryophytes, orthopterans, gastropods, spiders, ants, and ground beetles) were determined (Sauberer et al. 2004) and correlated with HANPP and its components. Both a linear and a quadratic polynomial function were fitted to the data; the choice of model was based on the Akaike Information Criterion (AIC). The study found a highly significant correlation between NPPt and species richness (.13 < r2 < .76, depending on taxon). The AIC confirmed that the relationship between NPPt and species richness was

Figure 17.2. Correlation analyses between log(NPPt) and the logarithm of species numbers of various groups. (a) NPPt and all heterotrophs (5 taxonomic groups) on 38 east Austrian plots sized 600 x 600 m (Haberl et al. 2004a and additional unpublished data). (b) NPPt (NPP remaining in ecosystems) and bird species number on 328 plots sized 1 x 1 km randomly selected from Austria's total area of about 83,000 km2 (Haberl et al. 2005).

Figure 17.2. Correlation analyses between log(NPPt) and the logarithm of species numbers of various groups. (a) NPPt and all heterotrophs (5 taxonomic groups) on 38 east Austrian plots sized 600 x 600 m (Haberl et al. 2004a and additional unpublished data). (b) NPPt (NPP remaining in ecosystems) and bird species number on 328 plots sized 1 x 1 km randomly selected from Austria's total area of about 83,000 km2 (Haberl et al. 2005).

linear. Figure 17.2a displays the regression between NPPt and an index of the species numbers of all five heterotroph groups analyzed in this study. The scatter diagrams looked similar for all seven groups.

In Figure 17.2b we present findings of a recent study (Haberl et al. 2005) on the relationships between HANPP and bird species richness in Austria. Bird species numbers for Austria's total area were extrapolated from Austria's bird inventory (Dvorak et al. 1993) on a 250 X 250 m grid (N = 1.3 million. grid cells) using an expert system (C. Plutzar and M. Pollheimer, personal communication); HANPP data were recalculated from Haberl et al. (2001). Some simple measures of land cover heterogeneity and landscape heterogeneity were also assessed based on a land cover classification and a landscape type classification. Four different plot sizes were considered: 0.25 X 0.25 km, 1 X 1 km, 4 X 4 km, and 16 X 16 km. A nested representative sample of N = 328 squares of each size was randomly chosen. As in the previous study, both linear and quadratic polynomials were tested, and the AIC was used to decide between the two models.

The results suggest that NPP variables generally do a much better job of explaining bird species richness than all available landscape heterogeneity indicators. Consistent with the species-energy hypothesis, we found highly significant and almost always monotonous (but not linear) positive correlations between NPPt and bird species numbers (e.g., see the correlation found at the 1 X 1 km scale, Figure 17.2b).

Although direct tests of the ability of HANPP to predict species loss (AS) would be desirable, this indirect evidence supports the line of reasoning outlined in this chapter. We cannot exclude additional effects of other factors influencing biodiversity, such as possible effects of disturbance frequency or intensity (Wrbka et al. 2004).

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