LAUSR

Abstract Effective conservation requires prioritizing areas that are vulnerable to large, irreversible changes. Unfortunately, rigorously documenting these changes with experiments and long-term monitoring is not only costly, but may provide evidence that is too late to facilitate proactive decisions. We use a simple model to illustrate that commonly available short-term spatial, “snapshot”, data from a given ecosystem along an environmental gradient can be used to identify environmental conditions under which different ecosystem states (e.g. different species compositions) co-occur in space. These environmental conditions are those under which future perturbations have the potential for discontinuous large, sometimes irreversible, effects; and can be mapped in space to predict potential spatial hotspots of ecosystem fragility. We apply these insights to ecologically important high-elevation subalpine meadows of the Sierra Nevada (California). Our analysis reveals specific areas within meadows that may be more vulnerable than others because their plant communities have the potential to shift to a different state. These shifts can be mechanistically explained by interactions between the vegetation and the local water regimes and/or the upper soil conditions. Our study provides a simple workflow using commonly available data to help prioritize conservation areas based on their potential sensitivity to upcoming perturbations. Such an approach could be very valuable to make most efficient use of conservation and management resources in the context of ongoing global changes.