Abstract
Population declines of early successional forest-associated wildlife species have been linked to declines in habitat abundance. Forest Inventory and Analysis (FIA) data can be used to estimate composition and change in 'young' forest, but such information typically lacks spatial specificity for determining landscape patterns that also affect habitat suitability. We developed a satellite remote sensing approach for making spatially explicit maps of young forest, using Landsat time series stacks and a vegetation change tracker (VCT) algorithm to identify forest disturbances occurring since 1985, and corresponding estimates of stand age based on year of disturbance. Wisconsin statewide estimates of young forest (1-20 years), from VCT and FIA, respectively, were 923,000 and 836,000 ha. Compared to FIA-based estimates, VCT-based estimates were statistically significantly higher for forest age classes of 1-5, 6-10, and 11-15 years, and significantly lower for the 16-20 year age class. Ongoing studies are examining causes and potential corrections for discrepancies between VCT- and FIA-based estimates of young forest in Wisconsin.
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