Robert B. McKane

15N natural abundances and N use by tundra plants

Plant species collected from tundra ecosystems located along a north-south transect from central Alaska to the north coast of Alaska showed large and consistent differences in 15N natural abundances. Foliar δ15N values varied by about 10% among species within each of two moist tussock tundra sites. Differences in 15N contents among species or plant groups were consistent across moist tussock tundra at several other sites and across five other tundra types at a single site. Ericaceous species had the lowest δ15N values, ranging between about −8 to −6‰. Foliar 15N contents increased progressively in birch, willows and sedges to maximum δ15N values of about +2‰ in sedges. Soil 15N contents in tundra ecosystems at our two most intensively studied sites increased with depth and δ15N values were usually higher for soils than for plants. Isotopic fractionations during soil N transformations and possibly during plant N uptake could lead to observed differences in 15N contents among plant species and between plants and soils. Patterns of variation in 15N content among species indicate that tundra plants acquire nitrogen in extremely nutrient-poor environments by competitive partitioning of the overall N pool. Differences in plant N sources, rooting depth, mycorrhizal associations, forms of N taken up, and other factors controlling plant N uptake are possible causes of variations in δ15N values of tundra plant species.

CLIMATIC EFFECTS ON TUNDRA CARBON STORAGE INFERRED FROM EXPERIMENTAL DATA AND A MODEL

We used a process-based model of ecosystem carbon (C) and nitrogen (N) dynamics, MBL-GEM (Marine Biological Laboratory General Ecosystem Model), to integrate and analyze the results of several experiments that examined the response of arctic tussock tundra to manipulations of CO2, temperature, light, and soil nutrients. The experiments manipulated these variables over 3- to 9-yr periods and were intended to simulate anticipated changes in the arctic environment. Our objective was to use the model to extend the analysis of the experimental data so that unmeasured changes in ecosystem C storage and the underlying mechanisms controlling those changes could be estimated and compared. Using an inverse calibration method, we derived a single parameter set for the model that closely simulated the measured responses of tussock tundra to all of the experimental treatments. This parameterization allowed us to infer confidence limits for ecosystem components and processes that were not directly measured in the experiments. Thus, we used the model to estimate changes in ecosystem C storage by inferring key soil processes within the constraints imposed by measured components of the ecosystem C budget. Because tussock tundra is strongly N limited, we hypothesized that changes in ecosystem C storage in response to the experimental treatments would be constrained by several key aspects of C–N interactions: (1) changes in the amount of N in the ecosystem, (2) changes in the C:N ratios of vegetation and soil, and (3) redistribution of N between soil (with a low C:N ratio) and vegetation (with a high C:N ratio). The model results reveal widely differing patterns of change in C–N interactions and constraints on change in ecosystem C storage among treatments. For example, after 9 yr the elevated CO2 (2 × ambient) treatment and the N fertilized (10 g N·m−2·yr−1) treatment increased ecosystem C stocks by 1.4 and 2.9%, respectively. Whereas the increase in the CO2 treatment was due solely to an increase in the C:N ratios of vegetation and soil, the increase in the fertilized treatment was due to increased ecosystem N content and a shift of N from soil to vegetation. In contrast, the greenhouse (3.5°C above ambient) and shade (one-half ambient light) treatments decreased ecosystem C stocks by 1.9 and 2.7%, respectively. The primary reason for the net C losses in these treatments was an increase in respiration relative to photosynthesis, with a consequent decrease in the ecosystem C:N ratio. However, when we simulated the elevated temperatures in the greenhouse treatment without the confounding effects of decreased light intensity (an artifact of the greenhouse structures), there was a long-term increase in ecosystem C stocks because of increased photosynthetic response to the temperature-induced shift of N from soil to vegetation. If our simulated changes in ecosystem C storage are extrapolated for the ≈43 Pg C contained in arctic tundras globally, the maximum net gain or loss (≈0.3% per yr) from tundra would be equivalent to 0.13 Pg C/yr. Although fluxes of this magnitude would have a relatively minor impact on current changes in atmospheric CO2, the long-term impact on tundra C stores could be significant. The synthesis and insights provided by the model should make it possible to extrapolate into the future with a better understanding of the processes governing long-term changes in tundra C storage.

Effects of global change on carbon storage in tropical forests of South America

We used a process-based model of ecosystem biogeochemistry (MBL-GEM) to evaluate the effects of global change on carbon (C) storage in mature tropical forest ecosystems in the Amazon Basin of Brazil. We first derived a single parameterization of the model that was consistent with all the C stock and turnover data from three intensively studied sites within the Amazon Basin that differed in temperature, rainfall, and cloudiness. The range in temperature, soil moisture, and photosynthetically active radiation (PAR) among these sites is about as large as the anticipated changes in these variables in the tropics under CO2-induced climate change. We then tested the parameterized model by predicting C stocks along a 2400-km transect in the Amazon Basin. Comparison of predicted and measured vegetation and soil C stocks along this transect suggests that the model provides a reasonable approximation of how climatic and hydrologic factors regulate present-day C stocks within the Amazon Basin. Finally, we used the model to predict and analyze changes in ecosystem C stocks under projected changes in atmospheric CO2 and climate. The central hypothesis of this exercise is that changes in ecosystem C storage in response to climate and CO2 will interact strongly with changes in other element cycles, particularly the nitrogen (N) and phosphorus (P) cycles. We conclude that C storage will increase in Amazonian forests as a result of (1) redistribution of nutrients from soil (with low C:nutrient ratios) to vegetation (with high C:nutrient ratios), (2) increases in the C:nutrient ratio of vegetation and soil, and (3) increased sequestration of external nutrient inputs by the ecosystem. Our analyses suggest that C:nutrient interactions will constrain increases in C storage to a maximum of 63 Mg/ha during the next 200 years, or about 16% above present-day stocks. However, it is impossible to predict how much smaller the actual increase in C storage will be until more is known about the controls on soil P availability. On the basis of these analyses, we identify several topics for further research in the moist tropics that must be addressed to resolve these uncertainties.

Carbon cycling in the Kuparuk basin: Plant production, carbon storage, and sensitivity to future changes

The Marine Biological Laboratory General Ecosystem Model was calibrated for an arctic tussock tundra system using data from long-term observations and experiments at Toolik Lake, Alaska. These experiments include the effects of changes in temperature, light, CO 2 , and nutrients, so the model could be applied to five regions comprising the entire Kuparuk River basin. Net primary production, averaged for the entire basin, was 92 g C m -2 yr A 150 year simulation of carbon storage under a doubling of CO 2 (slow ramp-up) and a temperature increase of 3.5°C gave an estimate of +400 g C m -2 when soil moisture increased and +500 g C m -2 when soil moisture decreased. Drier soils stimulated decomposition producing an increase in nitrogen availability; the increased N led to increased net primary production. If this result is applicable to other arctic ecosystems, then it is unlikely that warming will enhance carbon loss to the atmosphere to further enhance warming.

FOREST DYNAMICS IN OREGON LANDSCAPES: EVALUATION AND APPLICATION OF AN INDIVIDUAL-BASED MODEL

The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application. The model was able to capture much of the variation in forest basal area and composition in western Oregon even though temperature and precipitation were the only inputs that were varied among simulated sites. The measured decline in total basal area from tall coastal forests eastward to interior steppe was matched by simulations. Changes in simulated forest dominants also approximated those in the actual data. Simulated abundances of a few minor species did not match actual abundances, however. Subsequent projections of climate change and harvest effects in a west Cascades landscape indicated no change in forest dominance as of 2050. Yet, climate-driven shifts in the distributions of some species were projected. The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data. Simulations with fire as an agent of partial disturbance suggested that frequent fires of low severity can alter forest composition and structure as much or more than severe fires at historic frequencies.

Belowground processes in forest-ecosystem biogeochemical simulation models

Abstract Numerical simulation models of forest ecosystems synthesize a broad array of concepts from tree physiology, community ecology, hydrology, soil physics, soil chemistry and soil microbiology. Most current models are directed toward assessing natural processes or existing conditions, nutrient losses influenced by atmospheric deposition, C and N dynamics related to climate variation, and impacts of management activities. They have been applied mostly at the stand or plot scale, but regional and global applications are expanding. Commonly included belowground processes are nutrient uptake by roots, root respiration, root growth and death, microbial respiration, microbial mineralization and immobilization of nutrients, nitrification, denitrification, water transport, solute transport, cation exchange, anion sorption, mineral weathering and solution equilibration. Models differ considerably with respect to which processes and associated chemical forms are included, and how environmental and other factors influence process rates. Recent models demonstrated substantial discrepancies between model output and observations for both model verification and validation. The normalized mean absolute error between model output and observations of soil solution solute concentrations, solid phase characteristics, and process rates ranged from 0 to >1000%. There were considerable differences among outputs from models applied to the same situation, with process rates differing by as much as a factor of 4, and changes in chemical masses differing in both direction and magnitude. These discrepancies are attributed to differences in model structure, specific equations relating process rates to environmental factors, calibration procedures, and uncertainty of observations. Substantial improvement in the capability of models to reproduce observed trends is required for models to be generally applicable in public-policy decisions. Approaches that may contribute to improvement include modularity to allow easy alteration and comparison of individual equations and process formulations; hierarchical structure to allow selection of level of detail, depending on availability of data for calibration and driving variables; enhanced documentation of all phases of model development, calibration, and evaluation; and continued coordination with experimental studies.

Analysis of CO2, Temperature, and Moisture Effects on Carbon Storage in Alaskan Arctic Tundra Using a General Ecosystem Model

Projected changes in global climate associated with accumulations of CO2 and other greenhouse gases in the atmosphere might stimulate the release of a substantial portion of the estimated 4.3 × 1016g of carbon stored in wet and moist arctic tundras (Oechel, 1989; Shaver et al., 1992). About 98% of this carbon is in soils and has accumulated over thousands of years as a result of cold, wet conditions that serve to slow decomposition. Increased temperatures will stimulate decomposition and hence release CO2 from soils to the atmosphere. However, increased CO2, increased temperature, and higher amounts of available nitrogen (as a result of faster decomposition) could stimulate rates of production in vegetation and thereby also stimulate CO2 removal from the atmosphere. The key to which of these two opposing processes dominates appears to be closely tied to the nitrogen cycle (Billings et al., 1984; Rastetter et al., 1992; Shaver et al., 1992).

A simple model for analyzing climatic effects on terrestrial carbon and nitrogen dynamics: An arctic case study

[1] We developed a simplified plant-soil model (PSM) composed of four coupled differential equations that simulate the effects of climate change on major stocks and fluxes of carbon (C) and nitrogen (N) in terrestrial ecosystems. Here we use the model to examine past, present, and future changes in C storage in arctic Alaska, a region undergoing rapid climate change. Model parameters were initialized to simulate the buildup of C and N stocks from the beginning of the current postglacial period (� 10,000 years BP) to present-day levels for tussock tundra at Toolik Lake, Alaska. For projected rates of warming during the next century, the model predicts an increase in aboveground plant biomass and a net loss of soil carbon, resulting in almost no net change in total ecosystem C. The simplified model structure serves to clarify several important issues that have not been adequately addressed in previous studies. These issues include altered residence times of C and N in soils and plants, decreased synchrony of above and belowground processes, and the relationship between a model’s initial conditions and the ecosystem’s trajectory at the point of initialization.

A STABLE ISOTOPE SIMULATOR THAT CAN BE COUPLED TO EXISTING MASS BALANCE MODELS

To facilitate the simulation of isotope dynamics in ecosystems, we developed software to model changes in the isotopic signatures of the stocks of an element using the output from any parent model that specifies the stocks and flux rates of that element based on a mass balance approach. The software alleviates the need to recode the parent model to incorporate isotopes. This parent model can be a simple mass balance spreadsheet of the system. The isotopic simulations use a linear, donor-controlled approximation of the fluxes in the parent model, which are updated for each time step. These approximations are based on the output of the parent model, so no modifications to the parent model are required. However, all fluxes provided to the simulator must be gross fluxes, and the user must provide the initial isotopic signature for all stocks, the fractionation associated with each flux, and the isotopic signature of any flux originating from outside the system. We illustrate the use of the simulator with two examples. The first is based on a model of the carbon and nitrogen mass balance in an eight-species food web. We examine the consequences of using the steady-state assumption implicit in multi-source mixing models often used to map food webs based on 13C and 15N. We also use the simulator to analyze a pulse chase 15N-labeling experiment based on a spreadsheet model of the nitrogen cycle at the Harvard Forest Long Term Ecological Research site. We examine the constraints on net vs. gross N mineralization that are necessary to match the observed changes in the isotopic signatures of the forest N stocks.

Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

Abstract The accuracy of six combined methods formed by three commonly-used soil hydraulic functions and two methods to determine soil hydraulic parameters based on a soil hydraulic parameter look-up table and soil pedotransfer functions was examined for simulating soil moisture. A novel data analysis and modelling approach was used that eliminated the effects of evapotranspiration so that specific sources of error among the six combined methods could be identified and quantified. By comparing simulated and observed soil moisture at six sites of the USDA Soil Climate Analysis Network, we identified the optimal soil hydraulic functions and parameters for predicting soil moisture. Through sensitivity tests, we also showed that adjusting only the soil saturated hydraulic conductivity, Ks , is insufficient for representing important effects of macropores on soil hydraulic conductivity. Our analysis illustrates that, in general, soil hydraulic conductivity is less sensitive to Ks than to the soil pore-size distribution parameter. Editor D. Koutsoyiannis; Associate editor D. Hughes Citation Pan, F., McKane, R.B. and Stieglitz, M., 2012. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture. Hydrological Sciences Journal, 57 (4), 723–737.