Compensatory dynamics stabilize aggregate community properties in response to multiple types of perturbations

Abstract

Compensatory dynamics are an important suite of mechanisms that can stabilize community and ecosystem attributes in systems subject to environmental fluctuations. However, few experimental investigations of compensatory dynamics have addressed these mechanisms in systems of real-world complexity, and existing evidence relies heavily on correlative analyses, retrospective examination, and experiments in simple systems. We investigated the potential for compensatory dynamics to stabilize plankton communities in plankton mesocosm systems of real-world complexity. We employed four types of perturbations including two types of nutrient pulses, shading, and acidification. To quantify how communities responded to these perturbations, we used a measure of community-wide synchrony combined with spectral analysis that allowed us to assess timescale-specific community dynamics, for example, whether dynamics were synchronous at some timescales but compensatory at others. The 150-d experiment produced 32-point time series of all zooplankton taxa in the mesocosms. We then used those time series to evaluate total zooplankton biomass as an aggregate property and to evaluate community dynamics. For three of our four perturbation types, total zooplankton biomass was significantly less variable in systems with environmental variation than in constant environments. For the same three perturbation types, community-wide synchrony was much lower in fluctuating environments than in the constant environment, particularly at longer timescales (periods ≈ 60 d). Additionally, there were strong negative correlations between population temporal variances and the level of community-wide synchrony. Taken together, these results strongly imply that compensatory interactions between species stabilized total biomass in response to perturbations. Diversity did not differ significantly across either treatments or perturbation types, thus ruling out several classes of mechanisms driven by changes in diversity. We also used several pieces of secondary evidence to evaluate the particular mechanism behind compensatory responses since a wide variety of mechanisms are hypothesized to produce compensatory dynamics. We concluded that fluctuation dependent endogenous cycles that occur as a consequence of consumer-resource interactions in competitive communities were the most likely explanation for the compensatory dynamics observed in our experiment. As with our previous work, scale-dependent dynamics were also a key to understanding compensatory dynamics in these experimental communities.

Reduced competition enhances community temporal stability under conditions of increasing environmental stress

“…, Brown et al. ). Community stability is defined as the inverse of temporal variability in aggregate community properties such as in total biomass or functionality over time (Pimm ).…”

“…, Brown et al. ). Species niche differences increase community temporal stability due to desynchronized population dynamic among species under conditions of a fluctuating resource supply, which changes the biomass of each species over time but retains the total biomass of the community.…”

System-level optimal yield: increased value, less risk, improved stability, and better fisheries

“…Thus, fisheries portfolios need to be constructed with recognition of the constraints placed on multiple stock maximization that is set by ecosystem productivity. The proposal by Fogarty (2014) to embody these constraints as "ceilings and floors" in a fishery portfolio is certainly feasible, can help define the portfolio frontier, has been explored in a fisheries portfolio context (Edwards et al 2004;Sanchirico et al 2008;Rȃ dulescu et al 2010;Schindler et al 2010;Yang 2011;DuFour et al 2015;Jin et al 2016), has been proposed for ecological portfolios addressing biodiversity (Tilman et al 1998;Thibault and Connolly 2013;Schindler et al 2015;Brown et al 2016), and has actually been routinely adopted in financial portfolio approaches (Markowitz 1952;Brigham and Gapenski 1988;Gruber 1977, 1995;Choueifaty and Coignard 2008;Fabozzi and Markowitz 2011;Marston 2011). This portfolio cap constraint, coupled with the overfishing risk constraints, provides the useful trade space that is needed in many fisheries negotiations, helping to focus the debate on wise and equitable allocations among the stocks.…”

“…This is done cognizant of the level of risk facing the portfolio; in a fisheries context that would be primarily to not have any stock overfished. The dynamics of this aggregate level are almost always much less variable than that of the individual components (Simon and Ando 1961;Booth and Fama 1992;Brown et al 2016). It is well known in financial contexts that more diversified portfolios are less volatile (e.g., Markowitz 1952; Brigham and Gapenski 1988;Gruber 1977, 1995;Choueifaty and Coignard 2008;Fabozzi and Markowitz 2011;Marston 2011).…”

“…The dynamics of many ecological and biological systems are also almost always less variable than the individual components they are composed of, similarly exhibiting portfolio effects. This concept is well represented in the ecological literature (e.g., Waltho and Kolasa 1994;Tilman et al 1998;Thibault and Connolly 2013;Schindler et al 2015;Brown et al 2016), particularly related to biodiversity. The concept has had some attention in the fisheries literature (Edwards et al 2004;Rȃ dulescu et al 2010;Schindler et al 2010;Yang 2011;DuFour et al 2015;Jin et al 2016), but the application has not been widely implemented.…”