This analysis identifies essential metrics to quantify resistance and recovery in ecosystems, highlighting the significance of boundedness and symmetry.
Various indices have been developed to experimentally quantify resistance and recovery (two components of engineering resilience) in response to anthropogenic and natural disturbances. This diversity complicates the selection of appropriate metrics for comparing resilience across ecosystems and studies. The presence of both positive and negative disturbances further aggravates this challenge. We propose that a suitable index for quantifying resistance and recovery in experiments should satisfy four key criteria: symmetry, monotonicity, boundedness and standardization. They are inspired by methodological parallels between resilience and plant interaction quantification. Particularly, we highlight the importance of symmetry for fairly comparing the effects of disturbances with differing directional impacts. We review and compare six metrics commonly used for resilience quantification and find that none satisfies all four criteria. Specifically, the popular index of log‐transformed response ratio violates both boundedness and symmetry, making it sensitive to outliers and inappropriate for comparing increases vs. decreases induced by disturbances. By further evaluating six metrics developed for plant interaction quantification, we identify one metric (NInt A )—commonly used in that field but not in resilience research—that meets all four criteria. Synthesis and applications . We propose these four criteria as guidelines for developing and selecting appropriate metrics to quantify and compare resistance and recovery in experiments. We recommend the identified standardized index of resistance and recovery (NInt A ), as it enables fair and generalizable comparisons of the effects of both positive and negative disturbances across studies and ecosystems. Furthermore, this metric can support more robust predictions of tipping point's risks and restoration outcomes.
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Rubén Díaz‐Sierra (2025) studied this question.
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