Quantifying patterns of resilience: What matters is the intensity, not the relevance, of contributing factors

Abstract

Ecological resilience, broadly defined as the magnitude of the disturbance a system needs to shift to an alternative stable state, is becoming a critical trait in the Anthropocene era. However, we are far from having baseline resilience data to guide decision makers toward more resilient ecological systems. In the last decade, the resilience assessment framework has taken a sum of products approach to obtain a resilience indicator based on the relevance and the intensity of multiple factors. While factor intensity relies on quantitative data, estimates of factor relevance rely on ordinal data with a lesser understanding of their relative importance to resilience, which may have consequences in the value of the resilience indicator. Here, we computed three resilience indicators to test for the quantitative impact that changes in factor relevance might cause to the resilience indicator. We defined the Inclusive Resilience Indicator of a Site (IRIS) as a relevance-free indicator based exclusively on factor intensity. We also computed the Relative Resilience Potential (RRP) and an RRP with random relevance values (RRPrrv) as indicators based on both intensity and relevance. To calculate these three indicators in rocky reefs of the Alboran Sea, we quantified 17 biological, environmental, and human-related factors known to influence resilience. We used correlation analyses, Linear Mixed Models, and Generalized Additive Models to compare the three resilience indicators and to examine their spatial patterns. We found highly significant positive correlations between the RRP, RRPrrv, and IRIS indicators (r > 0.9, p < 0.001 for all comparisons). All three indicators had equivalent resilience values (p=0.440), provided non-significant differences in their predictions (p=0.097), and exposed the same resilience gradients in the Alboran Sea (p < 0.001 for all indicators). IRIS accounted for 94% and 99% of the variance associated with RRP and RRPrrv, respectively, suggesting that the intensity-based IRIS can estimate resilience without the uncertainties associated with factor relevance. The new IRIS indicator proposed in our study may facilitate the acquisition of baseline data needed to further advance in the ecological and management implications of marine resilience.