Edward B. Rastetter

Potential Net Primary Productivity in South America: Application of a Global Model

We use a mechanistically based ecosystem simulation model to describe and analyze the spatial and temporal patterns of terrestrial net primary productivity (NPP) in South America. The Terrestrial Ecosystem Model (TEM) is designed to predict major carbon and nitrogen fluxes and pool sizes in terrestrial ecosystems at continental to global scales. Information from intensively studies field sites is used in combination with continental-scale information on climate, soils, and vegetation to estimate NPP in each of 5888 non-wetland, 0.5° latitude °0.5° longitude grid cells in South America, at monthly time steps. Preliminary analyses are presented for the scenario of natural vegetation throughout the continent, as a prelude to evaluating human impacts on terrestrial NPP. The potential annual NPP of South America is estimated to be 12.5 Pg/yr of carbon (26.3 Pg/yr of organic matter) in a non-wetland area of 17.0 ° 106 km2 . More than 50% of this production occurs in the tropical and subtropical evergreen forest region. Six independent model runs, each based on an independently derived set of model parameters, generated mean annual NPP estimates for the tropical evergreen forest region ranging from 900 to 1510 g°m-2 °yr-1 of carbon, with an overall mean of 1170 g°m-2 °yr-1 . Coefficients of variation in estimated annual NPP averaged 20% for any specific location in the evergreen forests, which is probably within the confidence limits of extant NPP measurements. Predicted rates of mean annual NPP in other types of vegetation ranged from 95 g°m-2 °yr-1 in arid shrublands to 930 g°m@ ?yr-1 in savannas, and were within the ranges measured in empirical studies. The spatial distribution of predicted NPP was directly compared with estimates made using the Miami mode of Lieth (1975). Overall, TEM predictions were °10% lower than those of the Miami model, but the two models agreed closely on the spatial patterns of NPP in south America. Unlike previous models, however, TEM estimates NPP monthly, allowing for the evaluation of seasonal phenomena. This is an important step toward integration of ecosystem models with remotely sensed information, global climate models, and atmospheric transport models, all of which are evaluated at comparable spatial and temporal scales. Seasonal patterns of NPP in South America are correlated with moisture availability in most vegetation types, but are strongly influenced by seasonal differences in cloudiness in the tropical evergreen forests. On an annual basis, moisture availability was the factor that was correlated most strongly with annual NPP in South America, but differences were again observed among vegetation types. These results allow for the investigation and analysis of climatic controls over NPP at continental scales, within and among vegetation types, and within years. Further model validation is needed. Nevertheless, the ability to investigate NPP-environment interactions with a high spatial and temporal resolution at continental scales should prove useful if not essential for rigorous analysis of the potential effects of global climate changes on terrestrial ecosystems.

CONTROLS ON NITROGEN CYCLING IN TERRESTRIAL ECOSYSTEMS: A SYNTHETIC ANALYSIS OF LITERATURE DATA

Isotope pool dilution studies are increasingly reported in the soils and ecology literature as a means of measuring gross rates of nitrogen (N) mineralization, nitrification, and inorganic N assimilation in soils. We assembled data on soil characteristics and gross rates from 100 studies conducted in forest, shrubland, grassland, and agricultural systems to answer the following questions: What factors appear to be the major drivers for production and consumption of inorganic N as measured by isotope dilution studies? Do rates or the relationships between drivers and rates differ among ecosystem types? Across a wide range of ecosystems, gross N mineralization is positively correlated with microbial biomass and soil C and N concentrations, while soil C:N ratio exerts a negative effect on N mineralization only after adjusting for differences in soil C. Nitrification is a log-linear function of N mineralization, increasing rapidly at low mineralization rates but changing only slightly at high mineralization rates. In contrast, NH 4 1 assimilation by soil microbes increases nearly linearly over the full range of mineralization rates. As a result, nitrification is proportionately more important as a fate for NH4 1 at low mineralization rates than at high mineralization rates. Gross nitrification rates show no relationship to soil pH, with some of the fastest nitrification rates occurring below pH 5 in soils with high N mineralization rates. Differences in soil organic matter (SOM) composition and concentration among ecosystem types in- fluence the production and fate of mineralized N. Soil organic matter from grasslands appears to be inherently more productive of ammonium than SOM from wooded sites, and SOM from deciduous forests is more so than SOM in coniferous forests, but differences appear to result primarily from differing C:N ratios of organic matter. Because of the central importance of SOM characteristics and concentrations in regulating rates, soil organic matter depletion in agricultural systems appears to be an important determinant of gross process rates and the proportion of NH4 1 that is nitrified. Addition of 15 N appears to stimulate NH4 1 consumption more than NO3 2 consumption processes; however, the magnitude of the stim- ulation may provide useful information regarding the factors limiting microbial N trans- formations.

Reconciling carbon-cycle concepts, terminology, and methods

Recent projections of climatic change have focused a great deal of scientific and public attention on patterns of carbon (C) cycling as well as its controls, particularly the factors that determine whether an ecosystem is a net source or sink of atmospheric carbon dioxide (CO2). Net ecosystem production (NEP), a central concept in C-cycling research, has been used by scientists to represent two different concepts. We propose that NEP be restricted to just one of its two original definitions—the imbalance between gross primary production (GPP) and ecosystem respiration (ER). We further propose that a new term—net ecosystem carbon balance (NECB)—be applied to the net rate of C accumulation in (or loss from [negative sign]) ecosystems. Net ecosystem carbon balance differs from NEP when C fluxes other than C fixation and respiration occur, or when inorganic C enters or leaves in dissolved form. These fluxes include the leaching loss or lateral transfer of C from the ecosystem; the emission of volatile organic C, methane, and carbon monoxide; and the release of soot and CO2 from fire. Carbon fluxes in addition to NEP are particularly important determinants of NECB over long time scales. However, even over short time scales, they are important in ecosystems such as streams, estuaries, wetlands, and cities. Recent technological advances have led to a diversity of approaches to the measurement of C fluxes at different temporal and spatial scales. These approaches frequently capture different components of NEP or NECB and can therefore be compared across scales only by carefully specifying the fluxes included in the measurements. By explicitly identifying the fluxes that comprise NECB and other components of the C cycle, such as net ecosystem exchange (NEE) and net biome production (NBP), we can provide a less ambiguous framework for understanding and communicating recent changes in the global C cycle.

Towards an ecological understanding of biological nitrogen fixation

N limitation to primary production and other ecosystem processes is widespread. To understand the causes and distribution of N limitation, we must understand the controls of biological N fixation. The physiology of this process is reasonably well characterized, but our understanding of ecological controls is sparse, except in a few cultivated ecosystems. We review information on the ecological controls of N fixation in free-living cyanobacteria, vascular plant symbioses, and heterotrophic bacteria, with a view toward developing improved conceptual and simulation models of ecological controls of biological N fixation.A model (Howarth et al. 1999) of cyanobacterial fixation in lakes (where N fixation generally increases substantially when N:P ratios are low) versus estuaries (where planktonic N fixation is rare regardless of N:P ratios) concludes that an interaction of trace-element limitation and zooplankton grazing could constrain cyanobacteria in estuaries and so sustain N limitation. Similarly. a model of symbiotic N fixation on land (Vitousek & Field 1999) suggests that shade intolerance, P limitation, and grazing on N-rich plant tissues could suppress symbiotic N fixers in late-successional forest ecosystems. This congruence of results raises the question – why do late-successional tropical forests often contain many potentially N-fixing canopy legumes, while N fixers are absent from most late-successional temperate and boreal forests? We suggest that relatively high N availability in lowland tropical forests permits legumes to maintain an N-demanding lifestyle (McKey 1994) without always being required to pay the costs of fixing N.Overall, both the few simulation models and the more-numerous conceptual models of ecological controls of biological N fixation suggest that there are substantial common features across N-fixing organisms and ecosystems. Despite the many groups of organisms capable of fixing N, and the very different ecosystems in which the process is important, we suggest that these common controls provide a foundation for the development of regional and global models that incorporate ecological controls of biological N fixation.

Aggregating Fine‐Scale Ecological Knowledge to Model Coarser‐Scale Attributes of Ecosystems

As regional and global scales become more important to ecologists, methods must be developed for the application of existing fine-scale knowledge to predict coarser-scale ecosystem properties. This generally involves some form of model in which fine-scale components are aggregated. This aggregation is necessary to avoid the cumulative error associated with the estimation of a large number of parameters. However, aggregation can itself produce errors that arise because of the variation among the aggregated components. The statistical expectation operator can be used as a rigorous method for translating fine-scale relationships to coarser scales without aggregation errors. Unfortunately this method is too cumbersome to be applied in most cases, and alternative methods must be used. These alternative methods are typically partial corrections for the variation in only a few of the fine-scale attributes. Therefore, for these methods to be effective, the attributes that are the most severe sources of error must be identified a priori. We present a procedure for making these identifications based on a Monte Carlo sampling of the fine-scale attributes. We then present four methods of translating fine-scale knowledge so it can be applied at coarser scales: (1) partial transformations using the expectation operator, (2) moment expansions, (3) partitioning, and (4) calibration. These methods should make it possible to apply the vast store of fine-scale ecological knowledge to model coarser-scale attributes of ecosystems.

BIOMASS AND CO2 FLUX IN WET SEDGE TUNDRAS: RESPONSES TO NUTRIENTS, TEMPERATURE, AND LIGHT

The aim of this research was to analyze the effects of increased N or P availability, increased air temperature, and decreased light intensity on wet sedge tundra in northern Alaska. Nutrient availability was increased for 6–9 growing seasons, using N and P fertilizers in factorial experiments at three separate field sites. Air temperature was increased for six growing seasons, using plastic greenhouses at two sites, both with and without N + P fertilizer. Light intensity (photosynthetically active photon flux) was reduced by 50% for six growing seasons at the same two sites, using optically neutral shade cloth. Responses of wet sedge tundra to these treatments were documented as changes in vegetation biomass, N mass, and P mass, changes in whole-system CO2 fluxes, and changes in species composition and leaf-level photosynthesis. Biomass, N mass, and P mass accumulation were all strongly P limited, and biomass and N mass accumulation also responded significantly to N addition with a small N × P interaction. Greenhouse warming alone had no significant effect on biomass, N mass, or P mass, although there was a consistent trend toward increased mass in the greenhouse treatments. There was a significant negative interaction between the greenhouse treatment and the N + P fertilizer treatment, i.e., the effect of the two treatments combined was to reduce biomass and N mass significantly below that of the fertilizer treatment only. Six years of shading had no significant effect on biomass, N mass, or P mass. Ecosystem CO2 fluxes included net ecosystem production (NEP; net CO2 flux), ecosystem respiration (RE, including both plant and soil respiration), and gross ecosystem production (GEP; gross ecosystem photosynthesis). All three fluxes responded to the fertilizer treatments in a pattern similar to the responses of biomass, N mass, and P mass, i.e., with a strong P response and a small, but significant, N response and N × P interaction. The greenhouse treatment also increased all three fluxes, but the greenhouse plus N + P treatment caused a significant decrease in NEP because RE increased more than GEP in this treatment. The shade treatment increased both GEP and RE, but had no effect on NEP. Most of the changes in CO2 fluxes per unit area of ground were due to changes in plant biomass, although there were additional, smaller treatment effects on CO2 fluxes per unit biomass, per unit N mass, and per unit P mass. The vegetation was composed mainly of rhizomatous sedges and rushes, but changes in species composition may have contributed to the changes in vegetation nutrient content and ecosystem-level CO2 fluxes. Carex cordorrhiza, the species with the highest nutrient concentrations in its tissues in control plots, was also the species with the greatest increase in abundance in the fertilized plots. In comparison with Eriophorum angustifolium, another species that was abundant in control plots, C. cordorrhiza had higher photosynthetic rates per unit leaf mass. Leaf photosynthesis and respiration of C. cordorrhiza also increased with fertilizer treatment, whereas they decreased or remained constant in E. angustifolium. The responses of these wet sedge tundras were similar to those of a nearby moist tussock tundra site that received an identical series of experiments. The main difference was the dominant P limitation in wet sedge tundra vs. N limitation in moist tussock tundra. Both tundras were relatively unresponsive to the increased air temperatures in the greenhouses but showed a strong negative interaction between the greenhouse and fertilizer treatments. New data from this study suggest that the negative interaction may be driven by a large increase in respiration in warmed fertilized plots, perhaps in relation to large increases in P concentration.

RESPONSES OF N-LIMITED ECOSYSTEMS TO INCREASED CO2: A BALANCED-NUTRITION, COUPLED-ELEMENT-CYCLES MODEL

Ecosystem responses to increased CO2 are often constrained by nutrient limitation. We present a model of multiple-element limitation (MEL) and use it to analyze constraints imposed by N on the responses to an instantaneous doubling of CO2 concen- tration in a 350-yr-old eastern deciduous forest. We examine the effects of different exchange rates of inorganic N with sources and sinks external to the ecosystem (e.g., through de- position and leaching) and different initial ratios of net: gross N mineralization. Both of these factors influence the availability of N to vegetation and, therefore, have important effects on ecosystem responses to increased CO2. We conclude that reliable assessments of ecosystem responses to CO2 will require a better understanding of both these factors. The responses to increased CO2 appear on at least four characteristic time scales. (1) There is an instantaneous increase in net primary production, which results in an increase in the vegetation C:N ratio. (2) On a time scale of a few years, the vegetation responds by increasing uptake effort for available N (e.g., through increased allocation of biomass, energy, and enzymes to fine roots). (3) On a time scale of decades, there is a net movement of N from soil organic matter to vegetation, which enables vegetation biomass to accumulate. (4) On the time scale of centuries, ecosystem responses are dominated by increases in total ecosystem N, which enable organic matter to accumulate in both vegetation and soils. In general, short-term responses are markedly different from long-term responses.

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.

Validating models of ecosystem response to global change

Models are an essential component of any assessment of ecosystem response to changes in global climate and elevated atmospheric carbon dioxide concentration. The problem with these models is that their long-term predictions are impossible to test unambiguously except by allowing enough time for the full ecosystem response to develop. Unfortunately, when one must assess potentially devastating changes in the global environment, time becomes a luxury. Therefore, confidence in these models has to be built through the accumulation of fairly weak corrobatin evidence rather than through a few crucial and unambiguous tests. The criteria employed to judge the value of these models are thus likely to differ greatly from those used to judge finer scale models, which are more amenable to the scientific tradition of hypothesis formulation and testing. This article looks at four categories of tests which could potentially be used to evaluate ERCC (ecosystem response to climate and carbon dioxide concentration) models and illustrates why they cannot be considered crucial tests. The the synthesis role of ERCC models are is discussed and why they are vital to any assessment of long-term responses of ecosystems to changes in global climate and carbon dioxide concentration. 49 refs., 2 figs.

PREDICTING GROSS PRIMARY PRODUCTIVITY IN TERRESTRIAL ECOSYSTEMS

Our goal was to construct a simple, highly aggregated model, driven by easily available data sets, that accurately predicted terrestrial gross primary productivity (GPP; carboxylation plus oxygenation) in diverse environments and ecosystems. Our starting point was a fine-scale, multilayer model of half-hourly canopy processes that has been parametrized for Harvard Forest, Massachusetts. Over varied growing season conditions, this fine-scale model predicted hourly carbon and latent energy fluxes that were in good agreement with data from eddy covariance studies. Using an heuristic process, we derived a simple aggregated set of equations operating on cumulative or average values of the most sensitive driving variables (leaf area index, mean foliar N concentration, canopy height, average daily temperature and temperature range, atmospheric transmittance, latitude, day of year, atmospheric CO2 concentration, and an index of soil moisture). We calibrated the aggregated model to provide estimates of GPP similar to those of the fine-scale model across a wide range of these driving variables. Our calibration across this broad range of conditions captured 96% of fine-scale model behavior, but was computationally many orders of magnitude faster. We then tested the assumptions we had made in generating the aggregated model by applying it in different ecosystems. Using the same parameter values derived for Harvard Forest, the aggregated model made sound predictions of GPP for wet-sedge tundra in the Arctic under a variety of experimental manipulations, and also for a range of forest types across the OTTER (Oregon Transect Ecosystem Research) transect in Oregon, running from coastal Sitka spruce to high-plateau mountain juniper.