Assess ecosystem resilience: Linking response and effect traits to environmental variability

Disturbances, nature as well as human, are putting constant pressure on ecosystems. These include small scale disturbances like a falling tree, but also large scale disturbances like eutrophication and climate change. Resilience is a useful indicator to assess whether an ecosystem has the capacity to maintain functioning with environmental variability. In this study we tested whether plant functional traits can be distinguished to develop a response-and-effect framework for general predictions concerning resilience. We defined response traits to assess the system's resistance to disturbance, and effect traits to assess its recovery after disturbance. We used a dataset with 932 vegetation plots containing 104 species from a selected wetland area in The Netherlands. The environmental variability was related to response traits and the response traits to effect traits with RLQ analysis, fourth-corner analysis and Spearman's rank correlation. As a result, combinations of traits that specify effects of environmental change on ecosystem resilience were found. A strong resistance to environmental variability was shown, and consequently, a positive effect on resilience. Due to correlations between response and effect traits, combinations of traits were identified having a variable effect on the resilience of the system. In this way this study argues to further develop a response-and-effect framework to understand and assess ecosystem resilience. The selection of traits is system-specific, and therefore, one should only select those response and effect traits that differentiate between response to environmental variability and effects on ecosystem functioning.

► A response-and-effect framework for general predictions concerning resilience.
► Combinations of traits specify effects of environmental change on resilience.
► Selection of traits is system specific and subject to confounding effects.
► Appropriate trait selection supports system level understanding.