On the functional relationship between biodiversity and economic value

Abstract

Biodiversity's contribution to human welfare has become a key argument for maintaining and enhancing biodiversity in managed ecosystems. The functional relationship between biodiversity (b) and economic value (V) is, however, insufficiently understood, despite the premise of a positive-concave bV relationship that dominates scientific and political arenas. Here, we review how individual links between biodiversity, ecosystem functions (F), and services affect resulting bV relationships. Our findings show that bV relationships are more variable, also taking negative-concave/convex or strictly concave and convex forms. This functional form is driven not only by the underlying bF relationship but also by the number and type of ecosystem services and their potential trade-offs considered, the effects of inputs, and the type of utility function used to represent human preferences. Explicitly accounting for these aspects will enhance the substance and coverage of future valuation studies and allow more nuanced conclusions, particularly for managed ecosystems.

Fig. 1. Underlying cascade and types of values for linking biodiversity with economic value.

Taken from Potschin and Haines-Young (6) with small alterations and extensions. Blue boxes follow the indirect valuation pathway (solid lines), and yellow boxes include direct valuation (dashed lines) or combinations of both. For definition of terms, see Table 1. Abbreviations used in blue boxes are also used for mathematical representations in the text, Table 2, and Supplementary Methods.

Fig. 2. Plausible biodiversity–economic value (bV) relationships derived from theoretical considerations and empirical examples reviewed here.

See Table 2 and Supplementary Methods for detailed description and assumptions of example relationships depicted here. (A to D) Economic value is given in monetary units, and biodiversity is given in number of species (see Supplementary Methods for numerical examples). For A.3, the x axis has to be multiplied by a factor of 100.

Fig. 3. Empiric examples for bV relationships.

(A) Services related to biomass production or carbon sequestration are considered. All values have been normalized between zero (minimum economic value/species richness) and 100% (maximum economic value/species richness). Yellow: Costanza et al. (73) estimate a biodiversity (reflected by the number of vascular plants) NPP relationship for certain ecoregions in the United States and couple this function with a function to estimate aggregated economic value published earlier (78). Magenta: Annual economic value of carbon sequestration in grasslands (74) based on a medium scenario for social costs of carbon, when progressively adding grass species to a grassland monoculture [data were adopted from Hungate et al. (74)]. The authors report net present values of differences in ecosystem carbon content with an increasing number of grass species over a 50-year period (marginal values) based on social costs of carbon (112) discounted with a constant 4% discount rate. Green: Commercial forest value when species richness (per plot) varies (75). An assumed reduction by one tree species forms high and low economic values close to 100%, while a reduction to only one tree species forms the minimum (zero achievement level). Blue: Utility of commercial value of biomass yields in grasslands depending on Shannon diversity index (65). (B) Marginal and cumulative values of species for pharmaceutical bioprospecting [data are from Simpson et al. (80)]. A probability for a commercial discovery, P, of 0.000012 or 0.000020 for each single species and other coefficients according to Simpson et al. (80) was assumed to compute upper bounds for marginal species net economic value according to equation 10 of Simpson et al. (80). The number n of species available for pharmaceutical testing was varied from 5000 to 250,000. The mathematical products of the respective marginal net economic value and the number of additional species were summed to express the functional relationship between the number of species and the cumulative net economic value in percent. (C) Insurance value of admixing natural tree species into nonnatural forests based on data taken from (85). With nonnatural forest, we refer to a forest plantation made up by a single nonnative tree species. Admixing these stands, poor in species diversity and forest structure, with native tree species [e.g., those suggested by the concept of potential natural vegetation; see, e.g., (83)] would increase naturalness. The insurance value is quantified as the decrease in risk premium (Table 1; see eqs. S7 to S13). Here, we assigned logarithmic utility to each uncertain economic return, which was subsequently averaged. If the economic risk is high (i.e., we have volatile economic return), a high risk premium and a high expected economic return are required. For example, the high risk premium required for a nonnatural forest (Norway spruce) is reduced by about €450 per hectare by integrating 7% natural tree species (European beech) [data: (85); valuation approach: (65)].

Fig. 4. “Roadmap” of studies presented as examples for bV relationships.

Figure orders the example studies (each study being represented by one line; see lower box for sources) by the identified drivers of functional bV relationships (boxes with gray borders) across the three-step cascade (blue boxes from top down; see Fig. 1 for abbreviations) and gives the resulting relationship (lower gray boxes). Solid lines show empirical studies, which largely follow the three-step cascade. Dashed lines reflect own considerations based on empirical and theoretical evidence (see lower box for a more detailed description). Figure is intended to show which conditions are most frequently considered or still missing in the studies reviewed here and how this may affect the resulting bV relationship.