Using long-term monitoring data to measure restoration outcomes: a prairie case study

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Charlotte Reemts , Brandon Belcher

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Restoration is rarely accomplished with a single management intervention. Instead, most sites require years or decades of ongoing work to achieve or maintain restoration goals. Here we share a case study of how long-term monitoring data were used to assess restoration outcomes and address issues to consider when collecting and maintaining long-term data. Tallgrass prairies in the Great Plains of the United States are one of the most highly converted systems in the world. While individual management interventions in tallgrass prairies are relatively well-studied, the cumulative effect of long-term management is rarely documented. Using a 22-year monitoring dataset, we show that overall diversity increased in an unplowed prairie remnant; the number of prairie specialist species trended higher as well. Frequent prescribed fire in multiple seasons likely contributed to increasing diversity by favoring different species over time. Because of the long-term data available from this site, we can document important changes in a high-quality site. Maintaining long-term monitoring data requires detailed documentation of sampling methods to account for staffing changes over time. Permanent markers for monitoring locations facilitates relocation of sample sites and consistency of data collection. Monitoring that is done annually is more likely to continue because it becomes part of an annual routine. To reduce the staff and time burden of annual monitoring, sample sites can be sampled on a rotating basis.

Resource Type:
Conference Presentation, SER2021

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