Modeling and spatial prediction of pre-settlement patterns of forest distribution using witness tree data

Abstract

At the time of European settlement, land surveys were conducted progressively westward throughout the United States. Outside of the original 13 colonies, surveys generally followed the Public Land Survey system in which trees, called witness trees, were regularly recorded at 1 mi by 1 mi grid intersections. This unintentional sampling provides insight into the composition and structure of pre-European settlement forests, which is used as baseline data to assess forest change following settlement. In this paper, a model for the Public Land Surveys of east central Alabama is developed. Assuming that the locations of trees of each species are realized from independent Poisson processes whose respective log intensities are linear functions of environmental covariates (i.e., elevation, landform, and physiographic province), the species observed at the survey grid intersections are independently sampled from a generalized logistic regression model. If all 68 species found in the survey were included, the model would be highly over-parameterized, so only the distribution of the most common taxon, pines, will be considered at this time. To assess the impact of environmental factors not included in the model, a hidden Gaussian random field shall be added as a random effect. A Markov Chain Monte Carlo algorithm is developed for Bayesian inference on model parameters, and for Bayes posterior prediction of the spatial distribution of pines in east central Alabama.

Spatial Distribution of Trees and Landscapes of the Past: A Mixed Spatially Correlated Multinomial Logit Model Approach for the Analysis of the Public Land Survey Data

“…As noted in previous studies (Hooten, Larsen, and Wikle ; Rathbun and Black ; He et al. ; Wang ; Yoo and Trgovac ), the local abundance of a tree species is characterized by spatial clusters.…”

“…As evidenced in earlier studies (Rathbun and Black ; He et al. ; Fagin and Hoagland ), environmental conditions to which tree species respond play an important role when reconstructing the spatial distribution of forest vegetation in a landscape.…”

“…; Manies and Mladenoff ; Friedman, Reich, and Frelich ; Wu ; Wang and Larsen ; Yoo and Trgovac ). However, spatial autocorrelation alone may not be sufficient to reconstruct fine‐scale interaction between environmental conditions and tree species occurrences (Manies and Mladenoff ; Rathbun and Black ).…”

Spatially constrained forest cover dynamics using Markovian random processes

“…Markov Chain Monte Carlo simulation models of land-use and/or land-cover change can offer an understanding and analysis of any linkage or interaction between impacts and natural resource management strategies (Baker, 1989;Brown et al, 2000;Eastman et al, 2005;Turner and Meyer, 1991). Markov chains have been widely used to model land use changes including both urban and nonurban areas (Acevedo et al, 1995;Hill and Curran, 2001;Hill et al, 2004;Johnson, et al, 1991;Johnson, et al, 1991;Kaya and Buongiorno, 1987;Lembersky and Johnson, 1975;Lin and Buongiorno, 1998;Logofet and Lesnaya, 2000;Ogden, 1983;Orloci and Orloci, 1988;Rathbun and Black, 2006;Rollin et al, 2005;Waggoner and Stephens, 1970;Yemshanov and Perera, 2002). Brown et al (2000) represented forest-cover change using two transition probabilities that were calculated from Landsat imagery and that, taken together; describe a Markov transition matrix between forest and non-forest over a 10-year period.…”

Considerations for ecological reconstruction of historic vegetation: Analysis of the spatial uncertainties in the California Vegetation Type Map dataset

“…Wang (2005) and Mladenoff et al (2002) provide good reviews of the data. These witness tree point data have been used in interpolations and statistical clustering routines to reconstruct pre-European settlement forest species composition and structure across the Midwest, the Southeast and Eastern US, including Wisconsin (He, Mladenoff et al 2000;Radeloff et al 2000;Schulte et al 2002;Bollinger et al 2004); in Alabama (Black et al 2002;Rathbun and Black 2006); Minnesota (Friedman and Reich 2005); Michigan (Leahy and Pregitzer 2003); Pennsylvania (Black and Abrams 2001); West Virginia (Abrams and McCay 1996), and Southern Illinois (Anderson et al 2006). Other researchers have used the PLS data with archeological sites to examine Native American influence on pre-European settlement vegetation patterns (Black et al 2002;Foster et al 2004).…”