Novel and Lost Forests in the Upper Midwestern United States, from New Estimates of Settlement-Era Composition, Stem Density, and Biomass

Abstract

BackgroundEuroAmerican 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. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection.Changes in Forest StructureWe compare pre-settlement to modern forests using US Forest Service Forest Inventory and Analysis (FIA) data to show the prevalence of lost forests (pre-settlement forests with no current analog), and novel forests (modern forests with no past analogs). Differences between pre-settlement and modern forests are spatially structured owing to differences in land-use impacts and accompanying ecological responses. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 28% of all FIA cells, and 28% of pre-settlement forests no longer exist in a modern context. Lost forests include tamarack forests in northeastern Minnesota, hemlock and cedar dominated forests in north-central Wisconsin and along the Upper Peninsula of Michigan, and elm, oak, basswood and ironwood 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 for land managers if landscape restoration is a priority. 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.

Understanding ecological change across large spatial, temporal and taxonomic scales: integrating data and methods in light of theory

“…For example, re-surveys and other approaches in ecology have been successful at linking historical with contemporary communities (Tingley and Beissinger 2009, Rapacciuolo et al 2014a, Goring et al 2016) but fewer approaches exist to align the recent paleo record with historical and contemporary records (Seddon et al 2014, Jackson andBlois 2015; but see Terry 2010, Tomašových andKidwell 2017). First, many researchers are making substantial contributions within their core sub-discipline, yet progress towards integrating data and methods across space and time requires focusing on the spatiotemporal boundaries between sub-disciplines.…”

“…Grinnell Resurvey Project; ) and museum collections (e.g. Key advances are being made by the PalEON project (<http://sites.nd.edu/paleonproject/>) in this regard (Dawson et al 2016, Goring et al 2016. the Soaproot Saddle and San Joaquin Experimental Range sites) and repeated ecological monitoring as part of individual studies (Kelt et al 2013).…”

Effect of historical land‐use and climate change on tree‐climate relationships in the upper Midwestern United States

“…; Goring et al . ), outbreaks of exotic pathogens (Barnes ), climate changes accompanying the Little Ice Age (Hotchkiss et al . ) and current anthropogenic warming (WICCI ).…”

“…We use gridded historical and contemporary climate observations (PRISM‐LT) and estimates of pre‐settlement and modern forest vegetation (Goring et al . ) to map the geographical and climatic distributions for 15 major tree taxa in the upper Midwest. We construct four observed and hypothetical sets of tree‐climate relationships, using a 2 × 2 factorial of pre‐settlement and modern vegetation and climates.…”

Estimating historical forest density from land‐survey data: a response to Baker and Williams (2018)

“…These surveys were conducted throughout the United States and represent a systematic, historical sample of trees across a broad geographic area. The Cottam, Pollard, and Morisita are count-based plotless density estimators (PDE) and have a history of being applied to GLO data (e.g., Kronenfeld and Wang 2007, Rhemtulla et al 2009, Hanberry et al 2012, Maxwell et al 2014, Goring et al 2016. Levine et al (2017) tested the accuracy and precision of four plotless density estimators that can be applied to GLO survey sample data, including the Cottam (Cottam and Curtis 1956), Pollard (Pollard 1971), Morisita (Morisita 1957), and mean harmonic Voronoi density (MHVD; Williams and Baker 2011) estimators.…”