Boada J et al. (2017), Immanent conditions determine imminent collapse...

ECB-ART-45370

Proc Biol Sci 2017 Mar 29;2841851:. doi: 10.1098/rspb.2016.2814.

Show Gene links Show Anatomy links

Immanent conditions determine imminent collapses: nutrient regimes define the resilience of macroalgal communities.

Boada J , Arthur R , Alonso D , Pagès JF , Pessarrodona A , Oliva S , Ceccherelli G , Piazzi L , Romero J , Alcoverro T .

???displayArticle.abstract???
Predicting where state-changing thresholds lie can be inherently complex in ecosystems characterized by nonlinear dynamics. Unpacking the mechanisms underlying these transitions can help considerably reduce this unpredictability. We used empirical observations, field and laboratory experiments, and mathematical models to examine how differences in nutrient regimes mediate the capacity of macrophyte communities to sustain sea urchin grazing. In relatively nutrient-rich conditions, macrophyte systems were more resilient to grazing, shifting to barrens beyond 1 800 g m-2 (urchin biomass), more than twice the threshold of nutrient-poor conditions. The mechanisms driving these differences are linked to how nutrients mediate urchin foraging and algal growth: controlled experiments showed that low-nutrient regimes trigger compensatory feeding and reduce plant growth, mechanisms supported by our consumer-resource model. These mechanisms act together to halve macrophyte community resilience. Our study demonstrates that by mediating the underlying drivers, inherent conditions can strongly influence the buffer capacity of nonlinear systems.

???displayArticle.pubmedLink??? 28330920
???displayArticle.pmcLink??? PMC5378086
???displayArticle.link??? Proc Biol Sci

Genes referenced: LOC100887844 LOC100893907 LOC115925415 LOC583082 LOC590297 ncaph

???attribute.lit??? ???displayArticles.show???

	Figure 1. A macroalgal community grows up to a carrying capacity N following the solid blue line in the absence of herbivores. A population of herbivores consumes this macroalgae community at a rate represented by the solid green line (intermediate pressure, May 1977). Under this consumption curve, two stable states exist; a barren state (red point) and a well-structured macroalgal state (blue point). One unstable state exists (orange point) in which situations on the left precipitate barren formation (consumption > growth) and situations on the right enhance the macroalgal community stability (consumption < growth). The distance between the unstable point and red points represents the barren precipitation state and the distance between the unstable point and the carrying capacity N represents the macroalgal state resilience.
	Figure 2. Bubble plots of the percentage of algal cover for different sea urchin biomass for the two regions sampled: (a) Catalan coast (n = 237) and (b) Sardinia Island (n = 185). Bubble size is proportional to the number of times a specific combination of urchin biomass and macroalgal cover was recorded. Dashed red lines indicate the position of thresholds. Photos are representative of typical barren areas in each region. Change point analysis results for high- (c) and low- (d) nutrient regions. Black dots show the mean algal cover at different levels of the stressor (urchin biomass in grams per square metre of wet weight). Red horizontal lines represent the mean algal cover before and after the threshold. Grey areas represent the confidence intervals (95%) around change points detected. The F statistic (Chow test) obtained for the forward threshold is presented for both high- (e) and low-nutrient regions (f). F statistic peaks around the area where the change point has been detected.
	Figure 3. Conceptual diagram describing the two mechanisms evaluated; the compensatory feeding and nutrient-mediated growth of the macroalgal community and sea urchin population described in figure 1a. Under low-nutrient regimes sea urchins compensate feeding (i.e. increased consumption rates) (b) mean consumption rate on fertilized C. mediterranea F = 0.53 + 0.04 g day−1 (n = 15) and on non-fertilized C. mediterranea NF = 0.71 + 0.03 g day−1 (n = 15) in laboratory experiments after 6 days. At the same time under low-nutrient regimes, the macroalgal community presents retarded growth rates, (c) mean percentage cover of erect and turf algae in the high-nutrient region HN = 100% + 0% and low nutrient region LN = 29.3% + 7.42% after one month of herbivore exclusion.
	Figure 4. Under ‘rapid searching regime’, the area of the parameter space where regime shifts are prone to occur is relative large. The range of urchin densities that allows for coexistence of two stable stationary states increases as handling time increases. Parameter values are given above and have been chosen to satisfy the ‘rapid searching condition’ , and match the range of sea urchin densities found in the field (see electronic supplementary material, appendix A). A gradient of sea urchin pressure (from A to B) takes the system from a macroalgae-dominated state (a) to a barren state (b).
	Figure 5. Buffer capacity of macroalgal community and barrens in each nutrient regime. The bubble graph shows macroalgal percentage cover related to sea urchin biomass in gram per metre square (wet weight) in the two regions. The dashed red line represents the threshold after a tipping point F2 is reached. F1 represents the tipping point from which the recovery of the macroalgal state is possible. Both F1 and F2 are set in the position determined by the consumer–resource mathematical model (see electronic supplementary material, appendix A). The schematic drawing below shows the resilience of each stable state in both nutrient regimes. The valleys represent the alternative stable states and the depth of the valley represents the resilience of that particular state.

References [+] :

Andersen, Ecological thresholds and regime shifts: approaches to identification. 2009, Pubmed