Simon Goring

Holocene seasonality changes in the central Mediterranean region reconstructed from the pollen sequences of Lake Accesa (Italy) and Tenaghi Philippon (Greece)

This study presents pollen-based climate reconstructions of Holocene temperature and precipitation seasonality for two high-resolution pollen sequences from the central (Lake Accesa, central Italy) and eastern Mediterranean (Tenaghi Philippon, Greece) regions. The quantitative climate reconstruction uses multiple methods to provide an improved assessment of the uncertainties involved in palaeoclimate reconstructions. The multimethod approach comprises Partial Least Squares regression, Weighted Average Partial Least Squares regression, the Modern Analogues Technique, and the Non-Metric-Multidimensional Scaling/Generalized Additive Model method. We find two distinct climate intervals during the Holocene. The first is a moist period from 9500 to 7800 cal. BP characterised by wet winters and dry summers, resulting in a strongly seasonal hydrological contrast (stronger than today) that is interrupted by a short-lived event around 8200 cal. BP. This event is characterised by wet winters and summers at Accesa whereas at Tenaghi Philippon the signal is stronger, reversing the established seasonal pattern, with dry winters and wet summers. The second interval represents a later aridification phase, with a reduced seasonal contrast and lower overall precipitation, lasting from 7800 to 5000 cal. BP. Present-day Mediterranean conditions were established between 2500 and 2000 cal. BP. Many studies show the Holocene to have a complex pattern of climatic change across the Mediterranean regions. Our results confirm the traditional understanding of an evolution from wetter (early Holocene) to drier climatic conditions (late Holocene), but highlight the role of changing seasonality during this time. Our data yield new insights into the aspect of seasonality changes, and explain the apparent discrepancies between the previously available climate information based on pollen, lake-levels and isotopes by invoking changes in precipitation seasonality.

Macrosystems ecology: understanding ecological patterns and processes at continental scales

Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisci- plines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents.

Creating and maintaining high‐performing collaborative research teams: the importance of diversity and interpersonal skills

Collaborative research teams are a necessary and desirable component of most scientific endeavors. Effective collaborative teams exhibit important research outcomes, far beyond what could be accomplished by individuals working independently. These teams are made up of researchers who are committed to a common purpose, approach, and performance goals for which they hold themselves mutually accountable. We call such collaborations “high-performing collaborative research teams”. Here, we share lessons learned from our collective experience working with a wide range of collaborative teams and structure those lessons within a framework developed from literature in business, education, and a relatively new discipline, “science of team science”. We propose that high-performing collaborative research teams are created and maintained when team diversity (broadly defined) is effectively fostered and interpersonal skills are taught and practiced. Finally, we provide some strategies to foster team functioning and make recommendations for improving the collaborative culture in ecology.

Improving the culture of interdisciplinary collaboration in ecology by expanding measures of success

Interdisciplinary collaboration is essential to understand ecological systems at scales critical to human decision making. Current reward structures are problematic for scientists engaged in interdisciplinary research, particularly early career researchers, because academic culture tends to value only some research outputs, such as primary-authored publications. Here, we present a framework for the costs and benefits of collaboration, with a focus on early career stages, and show how the implementation of novel measures of success can help defray the costs of collaboration. Success measures at team and individual levels include research outputs other than publications, including educational outcomes, dataset creation, outreach products (eg blogs or social media), and the application of scientific results to policy or management activities. Promotion and adoption of new measures of success will require concerted effort by both collaborators and their institutions. Expanded measures should better reflect an...

A Regional Perspective on Holocene Fire–Climate–Human Interactions in the Pacific Northwest of North America

Wildfire plays an important role in ecosystems of the Pacific Northwest, but past relationships among fire, climate, and human actions remain unclear. A multiscale analysis of thirty-four macroscopic charcoal records from a variety of biophysical settings was conducted to reconstruct fire activity for the Pacific Northwest (PNW) during the past 12,000 years. Trends in biomass burning and fire frequency are compared to paleoenvironmental and population data at a variety of temporal and spatial scales to better understand fire regime variability on centennial- to millennial-length time scales. PNW fire activity in the early Holocene is linked to climatic and vegetation changes; however, increased fire activity in the middle to late Holocene is inconsistent with long-term trends in temperature and precipitation. Two hypotheses are explored to explain the rise in fire activity after ca. 5,500 calendar years before present, including greater climate variability and increased human use of fire. Climatic changes such as increased El Niño/Southern Oscillation event frequency during the past approximately 6,000 years could have led to hydrologic shifts conducive to more frequent fire events, despite overall trends toward cooler and moister conditions. Alternatively, increasing human populations and their associated uses of fire might have increased biomass burning. Centennial-scale changes in fire activity, such as during the Medieval Climate Anomaly and the Little Ice Age, closely match widespread shifts in both climate and population, suggesting that one or both influenced the late-Holocene fire history of the PNW.

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

Centennial-scale climate-ecosystem feedbacks are a major source of predictive uncertainty for land-atmosphere fluxes of energy, carbon, and water. Accurate representations of plant functional type (PFT) distributions through time and space are required for modeling centennial-scale feedbacks within Earth system models (ESMs). We tested the ability of ESMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to capture historical PFT distributions at the time of Euro-American settlement in the Northeastern United States against a new subcontinental-scale data set of historical tree abundances derived from forest composition surveys. To identify and diagnose errors in ESM-simulated PFT distributions and quantify impacts on modeled albedo, net primary productivity, and transpiration, we analyzed actual and modeled PFT distributions with respect to historical mean annual climate and modeled elasticity among PFTs, climate, and vegetation-atmosphere fluxes. Historical PFT distributions were poorly matched between ESMs and the settlement-era data, often due to inaccurate PFT-climate relationships within ESMs, particularly for evergreen trees. Some models exhibited large local, but regionally compensating, errors in simulated albedo, net primary productivity, and transpiration due to inaccurate PFT distributions, while others had systematic regional biases in vegetation-atmosphere fluxes. Internal variable elasticity varied among ESMs, and these differences closely corresponded to model skill in predicting PFT distributions. New historical benchmarks like the settlement-era vegetation data provide opportunities to confront ESMs, parse sources of error, and improve simulations of historical and future vegetation-atmosphere feedbacks.

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

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 (8×8km) 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 northeastern 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.

The Neotoma Paleoecology Database: A Research Outreach Nexus

Paleoecological data from the Quaternary Period (2.6 million years ago to present) provides an opportunity for educational outreach for the earth and biological sciences. Paleoecology data repositories serve as technical hubs and focal points within their disciplinary communities and so are uniquely situated to help produce teaching modules and engagement resources. The Neotoma Paleoecology Database provides support to educators from primary schools to graduate students. In collaboration with pedagogical experts, the Neotoma Paleoecology Database team has developed teaching modules and model workflows. Early education is centered on discovery; higher-level educational tools focus on illustrating best practices for technical tasks. Collaborations among pedagogic experts, technical experts and data stewards, centered around data resources such as Neotoma, provide an important role within research communities, and an important service to society, supporting best practices, translating current research advances to interested audiences, and communicating the importance of individual research disciplines.

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.