University of Virginia Charlottesville, VA, United States
Background/Question/Methods As coastal foundation species have declined worldwide, restoration promises to reclaim these lost habitats and their associated ecosystem functions. However, evaluating restoration outcomes is often limited by a lack of monitoring data collected over sustained durations, particularly for both restored sites and appropriately paired reference locations. Partnerships between non-profit organizations, government agencies and academics have supported the collection of long-term data ( > 15 years) for restored populations of coastal foundation species, offering new opportunities to assess the success of coastal restoration projects.
Results/Conclusions Long-term data allowed us to clarify recovery timelines for coastal foundation species and evaluate how long is needed for restored populations to match the ecological functions of natural reference populations. For example, in coastal Virginia, we found that abundances of oysters and a key crab mesopredator on restored reefs equaled reference reefs in approximately six years, indicating that restoration can initiate rapid, sustained recovery of foundation species and associated consumers. Long-term data also supported calculation of other measures of restoration success, such as temporal population stability. For example, as oyster reefs matured and accrued biomass, they became more temporally stable, suggesting that restoration can increase resilience and may stabilize ecosystem processes that scale with foundation species biomass. These results can then inform the design of restoration and monitoring programs, helping to target when managers can reliably measure restoration progress, plan fundraising efforts, or implement adaptive management. Long-term data can also be used to validate existing habitat suitability models that inform site selection for restoration projects. Collecting long-term data about coastal restoration projects is challenging, but worthwhile; analysis of long-term data can improve how we design and monitor future restoration projects.
