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

Anthropogenic land-use legacies underpin climate change-related risks to forest ecosystems

Forest ecosystems with long-lasting human imprints can emerge worldwide as outcomes of land-use cessation. However, the interaction of these anthropogenic legacies with climate change impacts on forests is not well understood. Here, we set out how anthropogenic land-use legacies that persist in forest properties, following alterations in forest distribution, structure, and composition, can interact with climate change stressors. We propose a risk-based framework to identify anthropogenic legacies of land uses in forest ecosystems and quantify the impact of their interaction with climate-related stress on forest responses. Considering anthropogenic land-use legacies alongside environmental drivers of forest ecosystem dynamics will improve our predictive capacity of climate-related risks to forests and our ability to promote ecosystem resilience to climate change.

Climate-Driven Plant Response and Resilience on the Tibetan Plateau in Space and Time: A Review

Climate change variation on a small scale may alter the underlying processes determining a pattern operating at large scale and vice versa. Plant response to climate change on individual plant levels on a fine scale tends to change population structure, community composition and ecosystem processes and functioning. Therefore, we reviewed the literature on plant response and resilience to climate change in space and time at different scales on the Tibetan Plateau. We report that spatiotemporal variation in temperature and precipitation dynamics drives the vegetation and ecosystem function on the Tibetan Plateau (TP), following the water-energy dynamics hypothesis. Increasing temperature with respect to time increased the net primary productivity (NPP) on most parts of the Tibetan Plateau, but the productivity dynamics on some parts were constrained by 0.3 °C decade-1 rising temperature. Moreover, we report that accelerating studies on plant community assemblage and their contribution to ecosystem functioning may help to identify the community response and resilience to climate extremes. Furthermore, records on species losses help to build the sustainable management plan for the entire Tibetan Plateau. We recommend that incorporating long-term temporal data with multiple factor analyses will be helpful to formulate the appropriate measures for a healthy ecosystem on the Tibetan Plateau.

The forests of the midwestern United States at Euro-American settlement: Spatial and physical structure based on contemporaneous survey data

We present gridded 8 km-resolution data products of the estimated stem density, basal area, and biomass of tree taxa at Euro-American settlement of the midwestern United States during the middle to late 19th century for the states of Minnesota, Wisconsin, Michigan, Illinois, and Indiana. The data come from settlement-era Public Land Survey (PLS) data (ca. 0.8-km resolution) of trees recorded by land surveyors. The surveyor notes have been transcribed, cleaned, and processed to estimate stem density, basal area, and biomass at individual points. The point-level data are aggregated within 8 km grid cells and smoothed using a generalized additive statistical model that accounts for zero-inflated continuous data and provides approximate Bayesian uncertainty estimates. The statistical modeling smooths out sharp spatial features (likely arising from statistical noise) within areas smaller than about 200 km2. Based on this modeling, presettlement Midwestern landscapes supported multiple dominant species, vegetation types, forest types, and ecological formations. The prairies, oak savannas, and forests each had distinctive structures and spatial distributions across the domain. Forest structure varied from savanna (averaging 27 Mg/ha biomass) to northern hardwood (104 Mg/ha) and mesic southern forests (211 Mg/ha). The presettlement forests were neither unbroken and massively-statured nor dominated by young forests constantly structured by broad-scale disturbances such as fire, drought, insect outbreaks, or hurricanes. Most forests were structurally between modern second growth and old growth. We expect the data product to be useful as a baseline for investigating how forest ecosystems have changed in response to the last several centuries of climate change and intensive Euro-American land use and as a calibration dataset for paleoecological proxy-based reconstructions of forest composition and structure for earlier time periods. The data products (including raw and smoothed estimates at the 8-km scale) are available at the LTER Network Data Portal as version 1.0.

Forest Disturbance Types and Current Analogs for Historical Disturbance-Independent Forests

Forest classifications by disturbance permit designation of multiple types of both old growth forests and shorter-lived forests, which auto-replace under severe disturbance, and also identification of loss of the disturbance type and associated forest. Historically, fire and flooding disturbance regimes, or conversely, infrequent disturbance, produced unique forests such as disturbance-independent forests of American beech (Fagus grandifolia), eastern hemlock (Tsuga canadensis), and sugar maple (Acer saccharum) in the Eastern United States. However, disturbance has changed to primarily frequent mechanical overstory disturbance, resulting in novel forests. To demonstrate the transition to no-analog forests after disturbance change, I compared historical tree surveys (ca. 1837 to 1857) to current surveys in the Northern Lower Peninsula of Michigan. To establish widespread disturbance change effects, I also located where beech and hemlock are currently most abundant throughout the Eastern US compared to historical distribution of beech–hemlock forests. In the Northern Lower Peninsula of Michigan, beech and hemlock historically were about 30% of all trees, but currently, beech and hemlock are 2% of all trees. Red maple (Acer rubrum) increased from 1% to 11% of all trees and aspen (Populus) increased from 2% to 13% of all trees. The squared-chord difference between historical and current surveys was 0.40, or dissimilar forests. Areas with ≥20% beech and hemlock or ≥15% of either species decreased from about 52 million to 6 million hectares, with current distribution restricted to the Northeastern US. Current forests are dissimilar to historical forests, and this transition appears to be driven by disturbance regimes without historical analogs. Disturbance change may provide perspective in forest management for climate change.

Land-use and climatic causes of environmental novelty in Wisconsin since 1890

Multiple global change drivers are increasing the present and future novelty of environments and ecological communities. However, most assessments of environmental novelty have focused only on future climate and were conducted at scales too broad to be useful for land management or conservation. Here, using historical county-level data sets of agricultural land use, forest composition, and climate, we conduct a regional-scale assessment of environmental novelty for Wisconsin landscapes from ca. 1890 to 2012. Agricultural land-use data include six cropland types, livestock densities for four livestock species, and human populations. Forestry data comprise biomass-weighted relative abundances for 15 tree genera. Climate data comprise seasonal means for temperature and precipitation. We found that forestry and land use are the strongest cause of environmental novelty (Novelty_Forest  = 3.66, Novelty_Ag  = 2.83, Novelty_Climate  = 1.60, with Wisconsin's forests transformed by early 20th-century logging and its legacies and multiple waves of agricultural innovation and obsolescence. Climate change is the smallest contributor to contemporary novelty, with precipitation signals stronger than temperature. Magnitudes and causes of environmental novelty are strongly spatially patterned, with novelty in southern Wisconsin roughly twice that in northern Wisconsin. Forestry is the most important cause of novelty in the north, land use and climate change are jointly important in the southwestern Wisconsin, and land use and forest composition are most important in central and eastern Wisconsin. Areas of high regional novelty tend also to be areas of high local change, but local change has not pushed all counties beyond regional baselines. Seven counties serve as the best historical analogues for over one-half of contemporary Wisconsin counties (40/72), and so can offer useful historical counterparts for contemporary systems and help managers coordinate to tackle similar environmental challenges. Multi-dimensional environmental novelty analyses, like those presented here, can help identify the best historical analogues for contemporary ecosystems, places where new management rules and practices may be needed because novelty is already high, and the main causes of novelty. Separating regional novelty clearly from local change and measuring both across many dimensions and at multiple scales thus helps advance ecology and sustainability science alike.

Refining predictions of population decline at species' rear edges

According to broad-scale application of biogeographical theory, widespread retractions of species' rear edges should be seen in response to ongoing climate change. This prediction rests on the assumption that rear edge populations are "marginal" since they occur at the limit of the species' ecological tolerance and are expected to decline in performance as climate warming pushes them to extirpation. However, conflicts between observations and predictions are increasingly accumulating and little progress has been made in explaining this disparity. We argue that a revision of the concept of marginality is necessary, together with explicit testing of population decline, which is increasingly possible as data availability improves. Such action should be based on taking the population perspective across a species' rear edge, encompassing the ecological, geographical and genetic dimensions of marginality. Refining our understanding of rear edge populations is essential to advance our ability to monitor, predict and plan for the impacts of environmental change on species range dynamics.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information.

Which climate change path are we following? Bad news from Scots pine

Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated.