Stressor fluxes alter the relationship between beta‐diversity and regional productivity

Abstract

Dispersal of organisms can influence the relationship between beta-diversity and regional productivity in heterogeneous environments. However, many ecosystems are also linked by fluxes of stressors, with an unknown influence on this relationship. In this study, we assess the relationship between beta-diversity (measured as Bray-Curtis dissimilarity) and regional productivity (measured as biovolume) under various levels of a stressor flux in meta-ecosystems that were composed of two marine micro-algae communities. We created heterogeneity by exposing one of the two communities to a herbicide and manipulated regional diversity by applying a dispersal gradient, which decreased beta-diversity. We applied four stressor flux levels, which homogenized the herbicide concentration between the communities over time. The stressor flux changed the relationship between beta-diversity and regional productivity by changing the effect of dispersal on regional productivity. In absence of the stressor flux, the relationship between beta-diversity and regional productivity was mostly not significant, but positive at the end of the experiment. This positive relationship was generated by a negative effect of dispersal on regional productivity, probably because dispersal disrupted local dynamics by removing organisms from the most-productive unstressed community. In presence of the stressor flux, the relationship between beta-diversity and regional productivity was often negative as dispersal now increased regional productivity. Dispersal increased regional productivity by increasing the productivity of the stressed community. This positive effect was stronger in the presence than in the absence of the stressor flux because the stressor flux reduced the concentration of the herbicide in the stressed community, where it facilitated recovery. Our study shows that stressor fluxes can strongly interact with the effects of dispersal on productivity and thus influence diversity-productivity relationships.

Niche-based deterministic assembly processes strengthen the effects of β-diversity on metacommunity functioning of marine bacterioplankton

“…The β diversity effects were not significant in 8 out of the 14 cruises (colored dash lines in Figure 2). Current research on the relationship between β diversity and metacommunity functions also find such similar pattern that β diversity generally has positive effects on ecosystem functions [73][74][75][76][77], but non-significant or even negative β diversity effects are not uncommon [8,9,78]. Interestingly, we found the variability of β diversity effects coincided with the variability of metacommunity assembly processes, as indicated by 𝛽𝑀𝑃𝑇𝐼 (Figure 3 and S3-1).…”

Deterministic Assembly Processes Strengthen the Effects of β-Diversity on Community Biomass of Marine Bacterioplankton

“…2 ). Current research on the relationship between β diversity and the overall functions of multiple sites has also found similar patterns, showing that β diversity generally has positive effects on ecosystem functions ( 4 , 46 – 49 ) but that nonsignificant or even negative β diversity effects are not uncommon ( 6 , 7 , 50 ). We acknowledge that variable β diversity in the literature could stem from the difference among ecosystem types, where different levels of habitat heterogeneity, dispersal limitation, and abiotic influences will alter the relationship between biodiversity and ecosystem functioning ( 1 ).…”

The effects of dispersal on spatial synchrony in metapopulations differ by timescale

“…ε = (ε 1 ,ε 2 ) T is two‐dimensional Gaussian white noise with component variances 0.01 and correlation coefficient ρ, which describes the response of population growth rate to environmental fluctuations. We calculate population variability and synchrony based on x i ( t ) to avoid the immediate influence of dispersal (de Raedt et al 2019; but see Desharnais et al 2018). Previous studies that considered both x i ( t ) and x i ′( t ) showed that these two types of models generated qualitatively similar effects of dispersal on synchrony and variability (Wang et al 2015).…”