Strengthening global-change science by integrating aeDNA with paleoecoinformatics

Ancient environmental DNA (aeDNA) data are close to enabling insights into past global-scale biodiversity dynamics at unprecedented taxonomic extent and resolution. However, achieving this potential requires solutions that bridge bioinformatics and paleoecoinformatics. Essential needs include support for dynamic taxonomic inferences, dynamic age inferences, and precise stratigraphic depth. Moreover, aeDNA data are complex and heterogeneous, generated by dispersed researcher networks, with methods advancing rapidly. Hence, expert community governance and curation are essential to building high-value data resources. Immediate recommendations include uploading metabarcoding-based taxonomic inventories into paleoecoinformatic resources, building linkages among open bioinformatic and paleoecoinformatic data resources, harmonizing aeDNA processing workflows, and expanding community data governance. These advances will enable transformative insights into global-scale biodiversity dynamics during large environmental and anthropogenic changes.

Bayesian ages for pollen records since the last glaciation in North America

Terrestrial pollen records are abundant and widely distributed, making them an excellent proxy for past vegetation dynamics. Age-depth models relate pollen samples from sediment cores to a depositional age based on the relationship between sample depth and available chronological controls. Large-scale synthesis of pollen data benefit from consistent treatment of age uncertainties. Generating new age models helps to reduce potential artifacts from legacy age models that used outdated techniques. Traditional age-depth models, often applied for comparative purposes, infer ages by fitting a curve between dated samples. Bacon, based on Bayesian theory, simulates the sediment deposition process, accounting for both variable deposition rates and temporal/spatial autocorrelation of deposition from one sample to another within the core. Bacon provides robust uncertainty estimation across cores with different depositional processes. We use Bacon to estimate pollen sample ages from 554 North American sediment cores. This dataset standardizes age-depth estimations, supporting future large spatial-temporal studies and removes a challenging, computationally-intensive step for scientists interested in questions that integrate across multiple cores.

Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States

Forest ecosystems in eastern North America have been in flux for the last several thousand years, well before Euro‐American land clearance and the 20th‐century onset of anthropogenic climate change. However, the magnitude and uncertainty of prehistoric vegetation change have been difficult to quantify because of the multiple ecological, dispersal, and sedimentary processes that govern the relationship between forest composition and fossil pollen assemblages. Here we extend STEPPS, a Bayesian hierarchical spatiotemporal pollen–vegetation model, to estimate changes in forest composition in the upper Midwestern United States from about 2,100 to 300 yr ago. Using this approach, we find evidence for large changes in the relative abundance of some species, and significant changes in community composition. However, these changes took place against a regional background of changes that were small in magnitude or not statistically significant, suggesting complexity in the spatiotemporal patterns of forest dynamics. The single largest change is the infilling of Tsuga canadensis in northern Wisconsin over the past 2,000 yr. Despite range infilling, the range limit of T. canadensis was largely stable, with modest expansion westward. The regional ecotone between temperate hardwood forests and northern mixed hardwood/conifer forests shifted southwestward by 15–20 km in Minnesota and northwestern Wisconsin. Fraxinus, Ulmus, and other mesic hardwoods expanded in the Big Woods region of southern Minnesota. The increasing density of paleoecological data networks and advances in statistical modeling approaches now enables the confident detection of subtle but significant changes in forest composition over the last 2,000 yr.

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

Contemporary forest inventory data are widely used to understand environmental controls on tree species distributions and to construct models to project forest responses to climate change, but the stability and representativeness of contemporary tree-climate relationships are poorly understood. We show that tree-climate relationships for 15 tree genera in the upper Midwestern US have significantly altered over the last two centuries due to historical land-use and climate change. Realised niches have shifted towards higher minimum temperatures and higher rainfall. A new attribution method implicates both historical climate change and land-use in these shifts, with the relative importance varying among genera and climate variables. Most climate/land-use interactions are compounding, in which historical land-use reinforces shifts in species-climate relationships toward wetter distributions, or confounding, in which land-use complicates shifts towards warmer distributions. Compounding interactions imply that contemporary-based models of species distributions may underestimate species resilience to climate change.

Correction: Statistically-Estimated Tree Composition for the Northeastern United States at Euro-American Settlement

[This corrects the article DOI: 10.1371/journal.pone.0150087.].

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

Background

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. 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 Structure

We 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.

Statistically-Estimated Tree Composition for the Northeastern United States at Euro-American Settlement

We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statistical methodology used to produce the product from trees recorded by land surveyors. Composition is defined as the proportion of stems larger than approximately 20 cm diameter at breast height for 22 tree taxa, generally at the genus level. The data come from settlement-era public survey records that are transcribed and then aggregated spatially, giving count data. The domain is divided into two regions, eastern (Maine to Ohio) and midwestern (Indiana to Minnesota). Public Land Survey point data in the midwestern region (ca. 0.8-km resolution) are aggregated to a regular 8 km grid, while data in the eastern region, from Town Proprietor Surveys, are aggregated at the township level in irregularly-shaped local administrative units. The product is based on a Bayesian statistical model fit to the count data that estimates composition on the 8 km grid across the entire domain. The statistical model is designed to handle data from both the regular grid and the irregularly-shaped townships and allows us to estimate composition at locations with no data and to smooth over noise caused by limited counts in locations with data. Critically, the model also allows us to quantify uncertainty in our composition estimates, making the product suitable for applications employing data assimilation. We expect this data product to be useful for understanding the state of vegetation in the northeastern United States prior to large-scale Euro-American settlement. In addition to specific regional questions, the data product can also serve as a baseline against which to investigate how forests and ecosystems change after intensive settlement. The data product is being made available at the NIS data portal as version 1.0.

Using a down-scaled bioclimate envelope model to determine long-term temporal connectivity of Garry oak (Quercus garryana) habitat in western North America: implications for protected area planning

Under the Canadian Species at Risk Act (SARA), Garry oak (Quercus garryana) ecosystems are listed as "at-risk" and act as an umbrella for over one hundred species that are endangered to some degree. Understanding Garry oak responses to future climate scenarios at scales relevant to protected area managers is essential to effectively manage existing protected area networks and to guide the selection of temporally connected migration corridors, additional protected areas, and to maintain Garry oak populations over the next century. We present Garry oak distribution scenarios using two random forest models calibrated with down-scaled bioclimatic data for British Columbia, Washington, and Oregon based on 1961-1990 climate normals. The suitability models are calibrated using either both precipitation and temperature variables or using only temperature variables. We compare suitability predictions from four General Circulation Models (GCMs) and present CGCM2 model results under two emissions scenarios. For each GCM and emissions scenario we apply the two Garry oak suitability models and use the suitability models to determine the extent and temporal connectivity of climatically suitable Garry oak habitat within protected areas from 2010 to 2099. The suitability models indicate that while 164 km(2) of the total protected area network in the region (47,990 km(2)) contains recorded Garry oak presence, 1635 and 1680 km(2) of climatically suitable Garry oak habitat is currently under some form of protection. Of this suitable protected area, only between 6.6 and 7.3% will be "temporally connected" between 2010 and 2099 based on the CGCM2 model. These results highlight the need for public and private protected area organizations to work cooperatively in the development of corridors to maintain temporal connectivity in climatically suitable areas for the future of Garry oak ecosystems.