Invasive plants as drivers of regime shifts: identifying high-priority invaders that alter feedback relationships
A major challenge for invasion ecology is to identify high-impact invaders to guide prioritization of management interventions. We argue that species with the potential to cause regime shifts (altered states of ecosystem structure and function that are difficult or impossible to reverse) should be prioritized. These are species that modify ecosystems in ways that enhance their own persistence and suppress that of native species through reinforcing feedback processes.
Using both systems analysis and meta-analysis approaches, we synthesized changes to ecosystems caused by 173 invasive plant species. For the systems analysis, we examined published studies of impacts of invasive plants to determine which presented evidence consistent with a reinforcement of feedback processes. For the meta-analysis, we calculated the effect size ratio between standardized changes in recipient ecosystem and in the status of introduced species as an indication of a reinforcing feedback in particular species-environment combinations. The systems analysis approach allowed us to conceptualize regime shifts in invader-dominated landscapes and to estimate the likelihood of such changes occurring. The meta-analysis allowed us to quantitatively verify the conceptual model and the key invader-context feedbacks and to detect the strength and direction of feedbacks.
Most reinforcing feedbacks involve impacts on soil-nutrient cycling by shrub and tree invaders in forests and herbaceous invaders in wetlands. Feedbacks resulting in regime shifts were most likely related to processes associated with seed banks, fire and nutrient cycling. Results were used to derive a key for identifying high-impact invaders.
Identifying combinations of plant life-forms and ecosystems most likely to result in regime shifts is a robust approach for predicting high-impact invasions and therefore for prioritizing management interventions. The meta-analysis revealed the need for more quantitative studies, including manipulative experiments, on ecosystem feedbacks.