R. Quinn Thomas

Clustered disturbances lead to bias in large‐scale estimates based on forest sample plots

Assessments from field plots steer much of our current understanding of global change impacts on forest ecosystem structure and function. Recent widespread observations of net carbon accumulation in field plots have suggested that terrestrial ecosystems may be a carbon sink, possibly resulting from climate change and/or CO(2) fertilization. We hypothesize that field plots may inadequately sample inherently rare mortality events, leading to bias when plot level measurements are scaled up to larger domains. In this study, we constructed a simple computer simulation model of forest dynamics to investigate the effects of disturbance patterns on landscape-scale carbon balance estimates. The model was constructed to be a balanced biosphere at the landscape-scale with a uniform spatial pattern of forest growth rates. Disturbance gap-size distributions across the landscape were modelled with a power-law distribution. Small and frequent disturbances result in a well-mixed heterogeneous forest where even small sample plots represented domain-wide behaviour. However, with disturbances dominated by large and rare events, sample plots as large as 50 ha displayed significant bias towards growth. We suggest that the accuracy of domain level estimates of carbon balance from sample plots are highly sensitive to the distribution of disturbance events across the landscape, and to the number, size and distribution of field plots that comprise the estimate. Assumptions that small clusters of field plots may be representative of domain-wide conditions should only be made very cautiously, and warrant further investigation for verification.

Nitrogen limitation on land: how can it occur in Earth system models?

The representation of the nitrogen (N) cycle in Earth system models (ESMs) is strongly motivated by the constraint N poses on the sequestration of anthropogenic carbon (C). Models typically implement a stoichiometric relationship between C and N in which external supply and assimilation by organisms are adjusted to maintain their internal stoichiometry. N limitation of primary productivity thus occurs if the N supply from uptake and fixation cannot keep up with the construction of tissues allowed by C assimilation. This basic approach, however, presents considerable challenges in how to faithfully represent N limitation. Here, we review how N limitation is currently implemented and evaluated in ESMs and highlight challenges and opportunities in their future development. At or near steady state, N limitation is governed by the magnitude of losses from the plant-unavailable pool vs. N fixation and there are considerable differences in how models treat both processes. In nonsteady-state systems, the accumulation of N in pools with slow turnover rates reduces N available for plant uptake and can be challenging to represent when initializing ESM simulations. Transactional N limitation occurs when N is incorporated into various vegetation and soil pools and becomes available to plants only after it is mineralized, the dynamics of which depends on how ESMs represent decomposition processes in soils. Other challenges for ESMs emerge when considering seasonal to interannual climatic oscillations as they create asynchronies between C and N demand, leading to transient alternations between N surplus and deficit. Proper evaluation of N dynamics in ESMs requires conceptual understanding of the main levers that trigger N limitation, and we highlight key measurements and observations that can help constrain these levers. Two of the biggest challenges are the mechanistic representation of plant controls on N availability and turnover, including N fixation and organic matter decomposition processes.

Global patterns and substrate-based mechanisms of the terrestrial nitrogen cycle

Nitrogen (N) deposition is impacting the services that ecosystems provide to humanity. However, the mechanisms determining impacts on the N cycle are not fully understood. To explore the mechanistic underpinnings of N impacts on N cycle processes, we reviewed and synthesised recent progress in ecosystem N research through empirical studies, conceptual analysis and model simulations. Experimental and observational studies have revealed that the stimulation of plant N uptake and soil retention generally diminishes as N loading increases, while dissolved and gaseous losses of N occur at low N availability but increase exponentially and become the dominant fate of N at high loading rates. The original N saturation hypothesis emphasises sequential N saturation from plant uptake to soil retention before N losses occur. However, biogeochemical models that simulate simultaneous competition for soil N substrates by multiple processes match the observed patterns of N losses better than models based on sequential competition. To enable better prediction of terrestrial N cycle responses to N loading, we recommend that future research identifies the response functions of different N processes to substrate availability using manipulative experiments, and incorporates the measured N saturation response functions into conceptual, theoretical and quantitative analyses.

Frequency, not relative abundance, of temperate tree species varies along climate gradients in eastern North America

There have been many attempts to model the impacts of climate change on the distributions of temperate tree species, but empirical analyses of the effects of climate on the distribution and abundance of tree species have lagged far behind the models. Here, we used forest inventory data to characterize variation in adult tree abundance along climate gradients for the 24 most common tree species in the northeastern United States. The two components of our measure of species abundance--local frequency vs. relative abundance--showed dramatically different patterns of variation along gradients of mean annual temperature and precipitation. Local frequency (i.e., the percentage of plots in a given climate in which a species occurred) varied strongly for all 24 species, particularly as a function of temperature. Relative abundance when present in a plot, on the other hand, was effectively constant for most species right up to their estimated climatic range limits. Although the range limits for both temperature and precipitation were quite broad for all of the species, the range of climates within which a species was common (i.e., high frequency) was much narrower. Because frequency in sites within a given climate shows a strong sensitivity to temperature, at least, this suggests that the processes determining canopy tree recruitment on new sites also vary strongly with climate.

Using lidar data and a height-structured ecosystem model to estimate forest carbon stocks and fluxes over mountainous terrain

Accurately predicting forest dynamics and associated carbon fluxes requires both knowledge of the current state of the ecosystem and an understanding of the underlying processes and environmental conditions that influence the ecosystem processes. Here, we apply a combination of light detection and ranging (lidar) remote sensing (LVIS), an individual-based height-structured ecosystem model (ED), and detailed topographic and climate data to address these requirements to predict carbon dynamics at the Hubbard Brook Experimental Forest (HBEF) in the White Mountains of New Hampshire. Lidar data provided substantial constraints on model estimates of carbon stocks and annual net ecosystem production (ANEP). Lidar-initialized model estimates of carbon stocks (10.77 kg C m−2) were within 5% of the field estimates over the domain and accounted for the 44% decrease in carbon stocks observed between minimum and maximum elevation at HBEF. Lidar-initialized model estimates of ANEP (0.023 kg C m−2 year−1) also compared favorably with recent field estimates. Model estimates of ANEP strongly depended on fine-scale (1 ha) lidar data on vegetation structure, environmental gradients, and the dynamics of disturbance events. Substituting fine-scale (1 ha) data on vegetation structure and climate with domain-wide inputs increased model estimates of ANEP by 84%. Substituting fine-scale climate data with domain-wide inputs but initializing with fine-scale data on vegetation structure increased estimates of ANEP by 40%. Model simulations initialized with spatial heterogeneity in environmental conditions but that lacked corresponding spatial heterogeneity in vegetation structure were the most problematic because this configuration had serious inconsistencies in areas where the domain mean canopy height exceeded the local potential for vegetation (e.g., at high elevations). Lastly, failing to account for increased natural disturbance rates with elevation increased model estimates of ANEP by 43%. This research demonstrates that the combination of lidar data and a height-structured ecosystem model can be a powerful tool for estimating forest carbon stocks and fluxes, even in complex mountainous environments. To be most useful for constraining model predictions, lidar data need to be at the scale of the underlying environmental heterogeneity that determines plant vital rates.

Terrestrial and marine perspectives on modeling organic matter degradation pathways

Organic matter (OM) plays a major role in both terrestrial and oceanic biogeochemical cycles. The amount of carbon stored in these systems is far greater than that of carbon dioxide (CO2 ) in the atmosphere, and annual fluxes of CO2 from these pools to the atmosphere exceed those from fossil fuel combustion. Understanding the processes that determine the fate of detrital material is important for predicting the effects that climate change will have on feedbacks to the global carbon cycle. However, Earth System Models (ESMs) typically utilize very simple formulations of processes affecting the mineralization and storage of detrital OM. Recent changes in our view of the nature of this material and the factors controlling its transformation have yet to find their way into models. In this review, we highlight the current understanding of the role and cycling of detrital OM in terrestrial and marine systems and examine how this pool of material is represented in ESMs. We include a discussion of the different mineralization pathways available as organic matter moves from soils, through inland waters to coastal systems and ultimately into open ocean environments. We argue that there is strong commonality between aspects of OM transformation in both terrestrial and marine systems and that our respective scientific communities would benefit from closer collaboration.

Local-Scale Carbon Budgets and Mitigation Opportunities for the Northeastern United States

Economic and political realities present challenges for implementing an aggressive climate change abatement program in the United States. A high-efficiency approach will be essential. In this synthesis, we compare carbon budgets and evaluate the carbon-mitigation potential for nine counties in the northeastern United States that represent a range of biophysical, demographic, and socioeconomic conditions. Most counties are net sources of carbon dioxide (CO2) to the atmosphere, with the exception of rural forested counties, in which sequestration in vegetation and soils exceed emissions. Protecting forests will ensure that the regions largest CO2 sink does not become a source of emissions. For rural counties, afforestation, sustainable fuelwood harvest for bioenergy, and utility-scale wind power could provide the largest and most cost-effective mitigation opportunities among those evaluated. For urban and suburban counties, energy-efficiency measures and energy-saving technologies would be most cost effective. Through the implementation of locally tailored management and technology options, large reductions in CO2 emissions could be achieved at relatively low costs.

Examining Uncertainties in Representations of the Carbon Cycle in Earth System Models

Terrestrial and ocean scientists gathered to pursue intellectual fertilization across the traditional land-ocean disciplinary split in carbon cycle science. The goal was to examine the processes driving uncertainties in representations of the carbon cycle in Earth System Models (ESMs). Ecosystem processes with land and ocean parallels were explored through talks, posters, and breakout sessions on four themes: disturbance, remineralization/decomposition, individual organisms/trophic interactions, and nutrient limitation. Data-model synthesis and observational constraints on ESM behavior were a common thread among themes. Key data resources were summarized, and many of these have now been posted at https://climatedataguide.ucar.edu.

A mid‐century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity

Ecological forecasting of forest productivity involves integrating observations into a process-based model and propagating the dominant components of uncertainty to generate probability distributions for future states and fluxes. Here, we develop a forecast for the biomass change in loblolly pine (Pinus taeda) forests of the southeastern United States and evaluate the relative contribution of different forms of uncertainty to the total forecast uncertainty. Specifically, we assimilated observations of carbon and flux stocks and fluxes from sites across the region, including global change experiments, into a forest ecosystem model to calibrate the parameter distributions and estimate the process uncertainty (i.e., model structure uncertainty revealed in the residuals of the calibration). Using this calibration, we forecasted the change in biomass within each 12-digit Hydrologic (H12) unit across the native range of loblolly pine between 2010 and 2055 under the Representative Concentration Pathway 8.5 scenario. Averaged across the region, productivity is predicted to increase by a mean of 31% between 2010 and 2055 with an average forecast 95% quantile interval of ±15 percentage units. The largest increases were predicted in cooler locations, corresponding to the largest projected changes in temperature. The forecasted mean change varied considerably among the H12 units (3-80% productivity increase), but only units in the warmest and driest extents of the loblolly pine range had forecast distributions with probabilities of a decline in productivity that exceeded 5%. By isolating the individual components of the forecast uncertainty, we found that ecosystem model process uncertainty made the largest individual contribution. Ecosystem model parameter and climate model uncertainty had similar contributions to the overall forecast uncertainty, but with differing spatial patterns across the study region. The probabilistic framework developed here could be modified to include additional sources of uncertainty, including changes due to fire, insects, and pests: processes that would result in lower productivity changes than forecasted here. Overall, this study presents an ecological forecast at the ecosystem management scale so that land managers can explicitly account for uncertainty in decision analysis. Furthermore, it highlights that future work should focus on quantifying, propagating, and reducing ecosystem model process uncertainty.

NCAR’s Summer Colloquium: Capacity Building in Cross-Disciplinary Research of Earth System Carbon–Climate Connections

AFFILIATIONS: bracco—School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia; long—Climate and Global Dynamics Laboratory, NCAR,* Boulder, Colorado; levine—Department of Biological Sciences, University of Southern California, Los Angeles, California; thoMas—Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia; Deutsch—School of Oceanography, University of Washington, Seattle, Washington; McKinley— Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, Wisconsin