Changes in Forest Composition, Stem Density, and Biomass from the Settlement Era (1800s) to Present in the Upper Midwestern United States

Abstract

EuroAmerican land use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Gridded (8x8km) estimates of pre-settlement (1800s) forests from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan) using 19th Century Public Land Survey (PLS) records provide relative composition, biomass, stem density, and basal area for 26 tree genera. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection. We compare pre-settlement to modern forests using Forest Inventory and Analysis (FIA) data, with respect to structural changes and the prevalence of lost forests, pre-settlement forests with no current analogue, and novel forests, modern forests with no past analogs. Differences between PLSS and FIA forests are spatially structured as a result of differences in the underlying ecology and land use impacts in the Upper Midwestern United States. Modern biomass is higher than pre-settlement biomass in the northwest (Minnesota and north-eastern Wisconsin, including regions that were historically open savanna), and lower in the east (eastern Wisconsin and Michigan), due to shifts in species composition and, presumably, average stand age. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 29% of all FIA cells, while 25% of pre-settlement forests no longer exist in a modern context. Lost forests are centered around the forests of the Tension Zone, particularly in hemlock dominated forests of north-central Wisconsin, and in oak-elm-basswood forests along the forest-prairie boundary in south central Minnesota and eastern Wisconsin. Novel FIA forest assemblages are distributed evenly across the region, but novelty shows a strong relationship to spatial distance from remnant forests in the upper Midwest, with novelty predicted at between 20 to 60km from remnants, depending on historical forest type. The spatial relationships between remnant and novel forests, shifts in ecotone structure and the loss of historic forest types point to significant challenges to land managers if landscape restoration is a priority in the region. The spatial signals of novelty and ecological change also point to potential challenges in using modern spatial distributions of species and communities and their relationship to underlying geophysical and climatic attributes in understanding potential responses to changing climate. The signal of human settlement on modern forests is broad, spatially varying and acts to homogenize modern forests relative to their historic counterparts, with significant implications for future management.

Benchmarking historical CMIP5 plant functional types across the Upper Midwest and Northeastern United States

“…CMIP5 models varied widely in their ability to capture historical regional Euro‐American settlement patterns of evergreen and deciduous PFTs (Figure ), due to differences in modeled climate, PFT‐climate relationships, and in internal elasticities related to connections among climate, PFT distributions, and vegetation‐atmosphere flux. The ESV data set for the Northeastern United States [ Paciorek et al , ] provides a regional‐scale benchmark at a critical time period, which acts as the baseline before the start of the industrial era in the CMIP experiments, binding data from the Upper Midwest [ Goring et al ., ] through the East Coast of the United States [ Cogbill et al ., ; Thompson et al ., ] before European settlers initiated major land use changes. Local‐scale variance in the ESV is partly the result of the higher spatial resolution and resampling process and also because historical contingency plays a role in vegetation structure on the landscape [ Jackson et al ., ].…”

“…BENCHMARKING HISTORICAL CMIP5 PFTS 523 A new regional reconstruction of historical plant functional type (PFT) distributions from the Euro-American settlement-era vegetation (ESV) data covers the Upper Midwest through the Northeastern United States [Goring et al, 2015] (Figure 1) and provides the opportunity for detailed evaluation of PFT simulation accuracy in the CMIP5 preindustrial control experiment and the effects on simulated ecosystem-atmosphere feedbacks. ESV data are compiled from forest composition data collected by surveyors working for individual townships (in Journal of Geophysical Research: Biogeosciences 10.1002/2015JG003175 New England) and the U.S. General Land Office [Cogbill et al, 2003;Thompson et al, 2013;Goring et al, 2015]. The ESV data collected in this time transgressive survey reflect forest composition from the early 1700s to 1907, with the earliest records from the east, and the latest records in northwestern Minnesota.…”

“…The ESV data used in this analysis were developed from Public Land Survey (PLS) records in the Upper Midwest [Liu et al, 2011;Goring et al, 2015], and from Town Proprietor Surveys (TPSs) in New England, New York, and Pennsylvania [Cogbill et al, 2003;Thompson et al, 2013]. Original survey records consist of counts of representative trees within townships (the TPS), and a standardized data set representing the closest two trees at section and quarter-section points, aggregated to an 8 × 8 km grid (the PLS) [Goring et al, 2015].…”

“…The ESV data used in this analysis were developed from Public Land Survey (PLS) records in the Upper Midwest [Liu et al, 2011;Goring et al, 2015], and from Town Proprietor Surveys (TPSs) in New England, New York, and Pennsylvania [Cogbill et al, 2003;Thompson et al, 2013]. Original survey records consist of counts of representative trees within townships (the TPS), and a standardized data set representing the closest two trees at section and quarter-section points, aggregated to an 8 × 8 km grid (the PLS) [Goring et al, 2015]. The data sets were combined using a multinomial probit model [McCulloch and Rossi, 1994] for the counts with latent Markov random field spatial models for each taxon with neighborhood structure defined by the four nearest neighbors of each cell [Rue and Held, 2005], also known as an intrinsic conditional autoregressive model [Banerjee et al, 2004] to produce estimates on an 8 × 8 km grid across the entire Northwestern U.S. with uncertainty [Paciorek et al, 2016].…”

“…The ESV data set for the Northeastern United States [Paciorek et al, 2016] provides a regional-scale benchmark at a critical time period, which acts as the baseline before the start of the industrial era in the CMIP experiments, binding data from the Upper Midwest [Goring et al, 2015] through the East Coast of the United States [Cogbill et al, 2003;Thompson et al, 2013] before European settlers initiated major land use changes. Local-scale variance in the ESV is partly the result of the higher spatial resolution and resampling process and also because historical contingency plays a role in vegetation structure on the landscape [Jackson et al, 2009].…”