Understanding and predicting the impacts of multiple, compounding threats on communities and ecosystem resilience is critical for effective management of US military lands, thereby minimizing encroachment by threatened/endangered species and maximizing flexibility for military training. The overarching objective of this project is to develop a theoretical framework and use empirical data to understand and predict how threats or disturbances to ecological communities influence ecosystem resilience. The specific technical objectives are to 1) Develop a theoretical and predictive framework of the mechanisms influencing ecosystem resilience in mutualistic networks, 2) experimentally test how seed dispersal networks (SDNs) change in response to removal of a key invasive plant and validate ecosystem resilience models, and 3) develop a framework to be used by managers to identify strategies for increasing resilience to threats.

 

The project team plans to use network science to examine the effects of species loss on ecosystem resilience by creating a theoretical framework of a mutualistic network and using field-based empirical validation. For objective 1 (above), the project team will use empirically-informed simulations of species loss within seed dispersal networks to evaluate how species-level traits, community-level traits, and pairwise metrics impact rewiring, and ultimately affect robustness and resilience. Species loss will be modeled based on vulnerability to single and multiple threats known to influence ecosystem processes, including climate change, wildfire, and invasive species. For objective 2, the project team will experimentally test if and how SDNs respond to removal of a key non-native, invasive plant and if the results match the estimated responses to species loss developed in their theoretical framework. To accomplish this, the project team will conduct a before-after-control-impact study design in which they remove Clidemia hirta from experimental plots. The project team will then calculate robustness and resilience based on a suite of field collected metrics (e.g. frugivore abundance and diversity, fruit removal rates) and compare these to the predictions derived from the theoretical framework. Finally, for objective 3, the project team will construct a framework that land managers can deploy to quantify and predict community level response to species loss and, thereby, identify approaches for improving ecosystem resilience to individual and compound threats.

The decline or regional extirpation of threatened and endangered species (TES), even for reasons outside the control of military land managers, can lead to restrictions on military training. Predicting ecological responses to threats, however, is hampered by a paucity of information on how these threats impact critical mutualistic interactions. The project team plans to use the development of a framework, validated empirically, that military land managers can use to understand, predict, and thus potentially mitigate, the effects of species loss on ecosystem resilience. This project would be the first to empirically test the impacts of species removal on seed dispersal networks and the first to incorporate rewiring into an ecosystem resilience framework. Thus, the research has the potential to substantially enhance the ability to understand and predict ecological response to disturbance. Although this work is focused on ecological systems, the theoretical framework could be transitioned to any network-based system where an end-user could evaluate the impacts of node removal and rewiring potential on system resilience.