Critical slowing down as early warning for the onset of collapse in mutualistic communities

Abstract

Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.

Keywords: critical transition; ecological networks; mutualism; pollinator decline; resilience.

Fig. 1.

Detection of the abrupt onset of collapse using critical slowing-down (CSD) indicators in mutualistic communities. (A) A plant–pollinator community from Cordon del Cepo, Chile. The black boxes represent mutualistic links between plants and animals. We used the structure of 79 empirical mutualistic networks to simulate their dynamics and potential collapse under gradual environmental change. (B) Decreasing mutualistic strength γ stresses species biomasses until unexpectedly an abrupt transition is induced. This first transition marks the onset of a sequence of extinctions until the collapse of the complete community. (C and D) Identifying critical slowing down at the species and community level. Close to the onset of community collapse, variance and correlation tend to increase. This increase is evident measured both from species biomasses and from the aggregated total community biomass.

Fig. 2.

Performance of critical slowing-down (CSD) indicators measured at the species (n = 11,195) and community (n = 79) level in 79 mutualistic communities. Performance was estimated as the natural logarithmic ratio of autocorrelation at lag 1 ($\mathrm{AR}1$) and coefficient of variation ($\mathrm{CV}$) close and far from the onset of community collapse. The multivariate index of variability was estimated on the community biomass variance–covariance matrix. Positive values indicate an increase in the indicators before the onset collapse. The boxplots include the median, box edges represent the 5th and 95th percentiles, and box whiskers indicate the minimum and maximum values.

Fig. 3.

Structural traits and critical slowing-down (CSD) indicators. Spearman rank correlations between species traits (degree and contribution to nestedness) and species indicators performance. Boxplots include the median, box edges represent the 25th and 75th percentiles, and box whiskers indicate the 5th and 95th percentiles.

Fig. 4.

Mapping species resilience based on critical slowing-down (CSD) indicators. Each node represents a species in the plant–pollinator community from Fig. 1. Species are ranked according to their order of extinction (from Left to Right), their size corresponds to the number of their interactions (degree), and are colored according to their changes in $\mathrm{CV}$ before the onset of community collapse. Black colors indicate strong increases in $\mathrm{CV}$. We used color boxes to group species that went coextinct. We found a positive correlation between the magnitude of the $\mathrm{CV}$ change and the order of species extinctions. Similar patterns were confirmed in all 79 communities (Fig. S4). This information can be used to rank species risk to extinction.

Fig. 5.

The effect of trade-offs in mutualistic strengths on CSD indicators. (A) In the presence of a trade-off, mutualistic strengths are inversely proportional to the number of species interactions (δ = 1). All species suffer similar losses to the decreasing mutualistic strength and the onset of community collapse usually occurs abruptly. (B) In the absence of a mutualistic trade-off (δ = 0, all of the rest of the parameters are the same as in A), mutualistic strengths are the same across all species. As a result, mutualistic benefits are proportional to the number of their interactions and the onset of community collapse is gradual. (C and E) Community level $\mathrm{CV}$ and $\mathrm{AR}1$ indicators clearly increase up to the onset of collapse in the presence of the trade-off (δ = 1). (D and F) Indicators at species level have mostly positive trends but perform poorer in the absence of the mutualistic trade-off (δ = 0).