Showing papers by "Paul J. Hanson published in 2014"

Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate Free‐Air CO2 Enrichment studies

Abstract: We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2] (eCO(2)) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)-nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO(2) and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10-yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above-ground-below-ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO(2) effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C-N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO(2), given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections. (Less)

Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites.

Abstract: Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.

Organic matter transformation in the peat column at Marcell Experimental Forest: Humification and vertical stratification

Abstract: We characterized peat decomposition at the Marcell Experimental Forest (MEF), Minnesota, USA, to a depth of 2 m to ascertain the underlying chemical changes using Fourier transform infrared (FT IR) and 13C nuclear magnetic resonance (NMR) spectroscopy) and related these changes to decomposition proxies C:N ratio, δ13C and δ15N, bulk density, and water content. FT IR determined that peat humification increased rapidly between 30 and 75 cm, indicating a highly reactive intermediate-depth zone consistent with changes in C:N ratio, δ13C and δ15N, bulk density, and water content. Peat decomposition at the MEF, especially in the intermediate-depth zone, is mainly characterized by preferential utilization of O-alkyl-C, carboxyl-C, and other oxygenated functionalities with a concomitant increase in the abundance of alkyl- and nitrogen-containing compounds. Below 75 cm, less change was observed but aromatic functionalities and lignin accumulated with depth. Significant correlations with humification indices, identified by FT IR spectroscopy, were found for C:N ratios. Incubation studies at 22°C revealed the highest methane production rates, greatest CH4:CO2 production ratios, and significant O-alkyl-C utilization within this 30 and 75 cm zone. Oxygen-containing functionalities, especially O-alkyl-C, appear to serve as excellent proxies for soil decomposition rate and should be a sensitive indicator of the response of the solid phase peat to increased temperatures caused by climate change and the field study manipulations that are planned to occur at this site. Radiocarbon signatures of microbial respiration products in deeper pore waters at the MEF resembled the signatures of more modern dissolved organic carbon rather than solid phase peat, indicating that recently photosynthesized organic matter fueled the bulk of subsurface microbial respiration. These results indicate that carbon cycling at depth at the MEF is not isolated from surface processes.

Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration

Abstract: Free-air CO2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model-data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.—the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model-data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO2 treatments. Model outputs were compared against observations using a range of goodness-of-fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness-of-fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model-data synthesis therefore goes beyond goodness-of-fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses—(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model—the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions.

Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

Abstract: As a key component of the carbon cycle, soil CO2 efflux (SCE) is being increasingly studied to improve our mechanistic understanding of this important carbon flux. Predicting ecosystem responses to climate change often depends on extrapolation of current relationships between ecosystem processes and their climatic drivers to conditions not yet experienced by the ecosystem. This raises the question of to what extent these relationships remain unaltered beyond the current climatic window for which observations are available to constrain the relationships. Here, we evaluate whether current responses of SCE to fluctuations in soil temperature and soil water content can be used to predict SCE under altered rainfall patterns. Of the 58 experiments for which we gathered SCE data, 20 were discarded because either too few data were available or inconsistencies precluded their incorporation in the analyses. The 38 remaining experiments were used to test the hypothesis that a model parameterized with data from the control plots (using soil temperature and water content as predictor variables) could adequately predict SCE measured in the manipulated treatment. Only for 7 of these 38 experiments was this hypothesis rejected. Importantly, these were the experiments with the most reliable data sets, i.e., those providing high-frequency measurements of SCE. Regression tree analysis demonstrated that our hypothesis could be rejected only for experiments with measurement intervals of less than 11 days, and was not rejected for any of the 24 experiments with larger measurement intervals. This highlights the importance of high-frequency measurements when studying effects of altered precipitation on SCE, probably because infrequent measurement schemes have insufficient capacity to detect shifts in the climate dependencies of SCE. Hence, the most justified answer to the question of whether current moisture responses of SCE can be extrapolated to predict SCE under altered precipitation regimes is "no" – as based on the most reliable data sets available. We strongly recommend that future experiments focus more strongly on establishing response functions across a broader range of precipitation regimes and soil moisture conditions. Such experiments should make accurate measurements of water availability, should conduct high-frequency SCE measurements, and should consider both instantaneous responses and the potential legacy effects of climate extremes. This is important, because with the novel approach presented here, we demonstrated that, at least for some ecosystems, current moisture responses could not be extrapolated to predict SCE under altered rainfall conditions.

Ground-dwelling Beetle Responses to Long-term Precipitation Alterations in a Hardwood Forest

Abstract: It is widely predicted that regional precipitation patterns may be altered due to climate change, and these changes may affect areas with extensive forests. Therefore, studies investigating the role of this climate driver on forest floor fauna are timely. We examined the impact of precipitation alteration over 13 years on Coleoptera (specifically Family Carabidae) communities in a temperate forest by testing the effects of dry (33% precipitation interception), ambient (control), and wet (33% precipitation addition) treatments. We collected insects in pitfall traps and quantified forest-floor physical and chemical parameters. Beetle abundance and Carabidae tribe richness were significantly reduced in dry plots. Community similarity was substantially higher between wet and ambient plots compared to dry plots due to the substantial reduction of three dominant carabid tribes. Litter mass increased overall, litter nitrogen decreased, and carbon:nitrogen ratio (C:N) and total phenolics increased in the dry-plot Oi horizon. Beetle abundance and tribe richness were positively related to soil moisture, and beetle abundance was negatively related to litter mass. Microarthropod abundance was highest in the dry treatment. This study provides evidence that shifting precipitation patterns predicted with climate change could alter important ground-fauna communities in extensive ecosystems such as temperate forests.