Tue, Aug 16, 2022: 3:30 PM-3:45 PM
520C
Background/Question/MethodsClassifications of vegetation provide a baseline understanding of plant-environment interactions necessary for management. Classifications were local until more recent efforts emerged to develop large-scale (e.g., US, Europe, Australia) classifications that reached across political borders. The development of these larger scale classifications utilized the available records scattered throughout the geographic area (albeit not evenly) and from a century of research, resulting in some classified units not currently present on the landscape (e.g., American Chestnut forest). Because of the variety of factors that can drive vegetation dynamics, the United States Vegetation Classification (USNVC) was developed to be dynamic and incorporate new units or changes to units over time. However, it is unknown how well classification assignments hold up over time and how much effort will be required to keep up with vegetation changes and novel communities. Here, we examine USNVC longevity with resampled data sets by asking: 1) how much change has occurred within plots that suggests a shift of that plot to another concept, and 2) how many plots no longer fit a concept (are novel) within the USNVC? We examined expert classification changes among sampling periods, and then examined resampled plots using a supervised classification.
Results/ConclusionsWe examined a data set from the Duke Forest in Piedmont North Carolina originally sampled in 1977 and resampled in 2009 (32-year span). Based on the expert classifications from each sampling year, 56% of plots changed their association type. However based on a supervised classification (of the original 1977 classification), 80% of plots changed associations, and 27% of those plots were not classified to any association types in the original classification. In other words, they were novel to the classification, likely due to increased levels of deer and lack of fire in a landscape once greatly influenced by fire. Our results suggest that the USNVC is a robust classification that will last for decades for most of the concepts currently described, but an accelerated ability is needed to capture novel communities that are rapidly developing, especially given changing climate and disturbance regimes.
Results/ConclusionsWe examined a data set from the Duke Forest in Piedmont North Carolina originally sampled in 1977 and resampled in 2009 (32-year span). Based on the expert classifications from each sampling year, 56% of plots changed their association type. However based on a supervised classification (of the original 1977 classification), 80% of plots changed associations, and 27% of those plots were not classified to any association types in the original classification. In other words, they were novel to the classification, likely due to increased levels of deer and lack of fire in a landscape once greatly influenced by fire. Our results suggest that the USNVC is a robust classification that will last for decades for most of the concepts currently described, but an accelerated ability is needed to capture novel communities that are rapidly developing, especially given changing climate and disturbance regimes.