Using a vegetation index to assess wetland condition in the Prairie Pothole Region of North America

Abstract

Wetlands deliver a suite of ecosystem services to society. Anthropogenic activities, such as wetland drainage, have resulted in considerable wetland loss and degradation, diminishing the intrinsic value of wetland ecosystems worldwide. Protecting remaining wetlands and restoring degraded wetlands are common management practices to preserve and reclaim wetland benefits to society. Accordingly, methods for monitoring and assessing wetlands are required to evaluate their ecologic condition and outcomes of restoration activities. We used an established methodology for conducting vegetation-based assessments and describe a case study consisting of a wetland condition assessment in the Prairie Pothole Region of the North American Great Plains. We provide an overview of an existing method for selecting wetlands to sample across broad geographic distributions using a spatially balanced statistical design. We also describe site assessment protocols, including vegetation survey methods, and how field data were applied to a vegetation index that categorized wetlands according to ecologic condition. Results of the case study indicated that vegetation communities in nearly 50% of the surveyed wetlands were in very poor or poor condition, while only about 25% were considered good or very good. Approximately 70% of wetlands in native grasslands were categorized as good or very good compared to only 12% of those in reseeded grasslands (formerly cropland). In terms of informing restoration and management activities, results indicated that improved restoration practices could include a greater focus on establishing natural vegetation communities, and both restored and native prairie wetlands would benefit from enhanced management of invasive species.

Farm management and landscape context shape plant diversity at wetland edges in the Prairie Pothole Region of Canada

“…Our study builds on the extensive knowledge base of prairie pothole wetland edge vegetation elsewhere in North America (Galatowitsch et al, 2000; Jones et al, 2023; Stewart & Kantrud, 1971), and uniquely from a Canadian perspective. Most studies involve the emergent marsh zone and many have focused on invasive species and restoration (Aronson & Galatowitsch, 2008; Galatowitsch & Van der Valk, 1996; Paradeis et al, 2010), wetland floristic indices (DeKeyser et al, 2003; Tangen et al, 2022), land management (Galatowitsch et al, 2000; Murphy & Grant, 2005) or temporal change (Hargiss et al, 2023). Ours focused on the wet meadow zone around Canadian prairie potholes and included the consideration of plant groups that could provide both ecosystem services and disservices (bee‐pollinated and introduced species, respectively).…”

Analisis Model Spasial Kondisi Lahan Daerah Aliran Sungai (DAS): Mendukung Pengambilan Keputusan Berkelanjutan di DAS Paguyaman, Indonesia

“…Campbell et al, (2022) menggarisbawahi pentingnya kerangka terstruktur untuk mengukur dan mengevaluasi respons vegetasi lahan basah terhadap pengelolaan air, yang mempertimbangkan data ekologi dan nilai-nilai sosial. Tangen et al, (2022) menggunakan indeks vegetasi untuk menilai kondisi lahan basah di Kawasan Prairie Pothole, yang menunjukkan prioritas restorasi seperti berfokus pada komunitas vegetasi alami. (Camarretta et al, 2019) meneliti penggunaan penginderaan jarak jauh untuk memantau restorasi hutan, menekankan kemampuannya dalam menangkap kompleksitas struktural dan memperkirakan efektivitas restorasi.…”

Response of Vegetation Coverage to Climate Drivers in the Min-Jiang River Basin along the Eastern Margin of the Tibetan Plat-Eau, 2000–2022

“…For example, while traditional methods for vegetation coverage research, such as spatio-temporal analysis and geostatistical methods, have been widely adopted, they also have certain limitations. The implementation of these methods is limited by topography and other natural conditions, resulting in difficult data acquisition, high time cost, and low efficiency [25][26][27]. In recent years, there have been fast advancements in remote sensing technology, and the Google Earth Engine platform (GEE) has given researchers a strong tool for quickly accessing, processing, and analyzing data on vegetation coverage worldwide.…”