Global biodiversity, stoichiometry and ecosystem function responses to human-induced C-N-P imbalances

Abstract

Global change analyses usually consider biodiversity as a global asset that needs to be preserved. Biodiversity is frequently analysed mainly as a response variable affected by diverse environmental drivers. However, recent studies highlight that gradients of biodiversity are associated with gradual changes in the distribution of key dominant functional groups characterized by distinctive traits and stoichiometry, which in turn often define the rates of ecosystem processes and nutrient cycling. Moreover, pervasive links have been reported between biodiversity, food web structure, ecosystem function and species stoichiometry. Here we review current global stoichiometric gradients and how future distributional shifts in key functional groups may in turn influence basic ecosystem functions (production, nutrient cycling, decomposition) and therefore could exert a feedback effect on stoichiometric gradients. The C-N-P stoichiometry of most primary producers (phytoplankton, algae, plants) has been linked to functional trait continua (i.e. to major axes of phenotypic variation observed in inter-specific analyses of multiple traits). In contrast, the C-N-P stoichiometry of higher-level consumers remains less precisely quantified in many taxonomic groups. We show that significant links are observed between trait continua across trophic levels. In spite of recent advances, the future reciprocal feedbacks between key functional groups, biodiversity and ecosystem functions remain largely uncertain. The reported evidence, however, highlights the key role of stoichiometric traits and suggests the need of a progressive shift towards an ecosystemic and stoichiometric perspective in global biodiversity analyses.

Keywords: Biodiversity; Ecosystem function; Species richness; Stoichiometry.

Figure 1

The adaptive trait continuum in Mediterranean butterflies. This functional trait continuum is described by the scores along the PCA axis 1 of 169 butterfly species (see Table 2, Carnicer et al 2013a and supplementary methods for further details). A) Observed distribution of major functional groups along an altitudinal gradient (modified from Stefanescu et al 2011). S: total butterfly species richness, Disp4: species richness of highly dispersive species; Disp3: species richness of high-medium dispersive species; Disp2: species richness of medium-low dispersive species; Disp1: species richness of low dispersive species. B) Observed relationship of the adaptive trait continuum (PCA) with genetic variability (F_ST). C) Observed relationship of the adaptive trait continuum (PCA) with regional population trends. Population trends were estimated as the slope of log-linear regression of abundances from the period 1994-2008 using TRIM software and were available for 78 species.

Figure 2

Observed relationships between the adaptive trait continuum of Mediterranean butterflies (PCA) and A) leaf P content; B) Leaf N content of the host plants. See supplementary methods for further details.