Continental scale variability in ecosystem processes: Models, data, and the role of disturbance

Management of ecosystems at large regional or continental scales and determination of the vulnerability of ecosystems to large-scale changes in climate or atmospheric chemistry require understanding how ecosystem processes are governed at large spatial scales. A collaborative project, the Vegetation and Ecosystem Modeling and Analysis Project (VEMAP), addressed modeling of multiple resource limitation at the scale of the conterminous United States, and the responses of ecosystems to environmental change. In this paper, we evaluate the model-generated patterns of spatial variability within and between ecosystems using Century, TEM, and Biome-BGC, and the relationships between modeled water balance, nutrients, and carbon dynamics. We present evaluations of models against mapped and site-specific data. In this analysis, we compare model-generated patterns of variability in net primary productivity (NPP) and soil organic carbon (SOC) to, respectively, a satellite proxy and mapped SOC from the VEMAP soils database (derived from USDA-NRCS [Natural Resources Conservation Service] information) and also compare modeled results to site-specific data from forests and grasslands. The VEMAP models simulated spatial variability in ecosystem processes in substantially different ways, reflecting the models’ differing implementations of multiple resource limitation of NPP. The models had substantially higher correlations across vegetation types compared to within vegetation types. All three models showed correlation among water use, nitrogen availability, and primary production, indicating that water and nutrient limitations of NPP were equilibrated with each other at steady state. This model result may explain a number of seemingly contradictory observations and provides a series of testable predictions. The VEMAP ecosystem models were implicitly or explicitly sensitive to disturbance in their simulation of NPP and carbon storage. Knowledge of the effects of disturbance (human and natural) and spatial data describing disturbance regimes are needed for spatial modeling of ecosystems. Improved consideration of disturbance is a key ‘‘next step’’ for spatial ecosystem models

A diagnostic study of temperature controls on global terrestrial carbon exchange

The observed interannual variability of atmospheric CO2 reflects short-term variability in sources and sinks of CO2 . Analyses using 13CO2 and O2 suggest that much of the observed interannual variability is due to changes in terrestrial CO2 exchange. First principles, empirical correlations and process models suggest a link between climate variation and net ecosystem exchange, but the scaling of ecological process studies to the globe is notoriously difficult. We sought to identify a component of global CO2 exchange that varied coherently with land temperature anomalies using an inverse modeling approach. We developed a family of simplified spatially aggregated ecosystem models (designated K-model versions) consisting of five compartments: atmospheric CO2 , live vegetation, litter, and two soil pools that differ in turnover times. The pools represent cumulative differences from mean C storage due to temperature variability and can thus have positive or negative values. Uptake and respiration of CO2 are assumed to be linearly dependent on temperature. One model version includes a simple representation of the nitrogen cycle in which changes in the litter and soil carbon pools result in stoichiometric release of plant-available nitrogen, the other omits the nitrogen feedback. The model parameters were estimated by inversion of the model against global temperature and CO2 anomaly data using the variational method. We found that the temperature sensitivity of carbon uptake (NPP) was less than that of respiration in all model versions. Analyses of model and data also showed that temperature anomalies trigger ecosystem changes on multiple, lagged time-scales. Other recent studies have suggested a more active land biosphere at Northern latitudes in response to warming and longer growing seasons. Our results indicate that warming should increase NPP, consistent with this theory, but that respiration should increase more than NPP, leading to decreased or negative NEP. A warming trend could, therefore increase NEP if the indirect feedbacks through nutrients were larger than the direct effects of temperature on NPP and respiration, a conjecture which can be tested experimentally. The fraction of the growth rate not predicted by the K-model represents model and data errors, and variability in anthropogenic release, ocean uptake, and other processes not explicitly represented in the model. These large positive and negative residuals from the K-model may be associated with the Southern Oscillation Index

Equilibration of the terrestrial water, nitrogen, and carbon cycles

Recent advances in biologically based ecosystem models of the coupled terrestrial, hydrological, carbon, and nutrient cycles have provided new perspectives on the terrestrial biosphere’s behavior globally, over a range of time scales. We used the terrestrial ecosystem model Century to examine relationships between carbon, nitrogen, and water dynamics. The model, run to a quasi-steady-state, shows strong correlations between carbon, water, and nitrogen fluxes that lead to equilibration of wateryenergy and nitrogen limitation of net primary productivity. This occurs because as the water flux increases, the potentials for carbon uptake (photosynthesis), and inputs and losses of nitrogen, all increase. As the flux of carbon increases, the amount of nitrogen that can be captured into organic matter and then recycled also increases. Because most plant-available nitrogen is derived from internal recycling, this latter process is critical to sustaining high productivity in environments where water and energy are plentiful. At steady-state, wateryenergy and nitrogen limitation ‘‘equilibrate,’’ but because the water, carbon, and nitrogen cycles have different response times, inclusion of nitrogen cycling into ecosystem models adds behavior at longer time scales than in purely biophysical models. The tight correlations among nitrogen fluxes with evapotranspiration implies that either climate change or changes to nitrogen inputs (from fertilization or air pollution) will have large and long-lived effects on both productivity and nitrogen losses through hydrological and trace gas pathways. Comprehensive analyses of the role of ecosystems in the carbon cycle must consider mechanisms that arise from the interaction of the hydrological, carbon, and nutrient cycles in ecosystems

Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle

Analyzing the Hypervolume of Plant Functional Traits in the Sierra Nevada Mountain Range

Studying Earth’s biodiversity is important in understanding how ecosystems are changing in response to environmental stressors. Particularly, monitoring Earth via remote sensing can give us high-resolution data of plant functional traits, such as canopy height, leaf mass per area (LMA), and leaf nitrogen content, which provide insight into ecosystem changes. We mapped out remote sensing airborne data from the Sierra Nevada Mountain Range in California and used R to create a hypervolume of the vegetated area. Hypervolumes are useful in creating a three-dimensional visualization of data to understand the relationships among different traits. We computed the three-dimensional space of the intersection of various functional traits by logarithmically transforming the values from the data. Additionally, we conducted fieldwork in the Angeles National Forest to validate remote sensing data of plant functional traits in the area. We can use hypervolume analyses and in-situ data to better understand how functional traits contribute to the changes we observe in the biodiversity of ecosystems

Continental Scale Variability in Ecosystem Process: Models, Data, and the Role of Disturbance

Management of ecosystems at large regional or continental scales and determination of the vulnerability of ecosystems to large-scale changes in climate or atmospheric chemistry require understanding how ecosystem processes are governed at large spatial scales. A collaborative project, the Vegetation and Ecosystem Modeling and Analysis Project (VEMAP), addressed modeling of multiple resource limitation at the scale of the conterminous United States, and the responses of ecosystems to environmental change. In this paper, we evaluate the model-generated patterns of spatial variability within and between ecosystems using Century, TEM, and Biome-BGC, and the relationships between modeled water balance, nutrients, and carbon dynamics. We present evaluations of models against mapped and site-specific data. In this analysis, we compare model-generated patterns of variability in net primary productivity (NPP) and soil organic carbon (SOC) to, respectively, a satellite proxy and mapped SOC from the VEMAP soils database (derived from USDA-NRCS [Natural Resources Conservation Service] information) and also compare modeled results to site-specific data from forests and grasslands. The VEMAP models simulated spatial variability in ecosystem processes in substantially different ways, reflecting the models’ differing implementations of multiple resource limitation of NPP. The models had substantially higher correlations across vegetation types compared to within vegetation types. All three models showed correlation among water use, nitrogen availability, and primary production, indicating that water and nutrient limitations of NPP were equilibrated with each other at steady state. This model result may explain a number of seemingly contradictory observations and provides a series of testable predictions. The VEMAP ecosystem models were implicitly or explicitly sensitive to disturbance in their simulation of NPP and carbon storage. Knowledge of the effects of disturbance (human and natural) and spatial data describing disturbance regimes are needed for spatial modeling of ecosystems. Improved consideration of disturbance is a key ‘‘next step’’ for spatial ecosystem models

Carbon source/sink information provided by column CO2 measurements from the Orbiting Carbon Observatory

© The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Atmospheric Chemistry and Physics 10 (2010): 4145-4165, doi:10.5194/acp-10-4145-2010.We quantify how well column-integrated CO2 measurements from the Orbiting Carbon Observatory (OCO) should be able to constrain surface CO2 fluxes, given the presence of various error sources. We use variational data assimilation to optimize weekly fluxes at a 2°×5° resolution (lat/lon) using simulated data averaged across each model grid box overflight (typically every ~33 s). Grid-scale simulations of this sort have been carried out before for OCO using simplified assumptions for the measurement error. Here, we more accurately describe the OCO measurements in two ways. First, we use new estimates of the single-sounding retrieval uncertainty and averaging kernel, both computed as a function of surface type, solar zenith angle, aerosol optical depth, and pointing mode (nadir vs. glint). Second, we collapse the information content of all valid retrievals from each grid box crossing into an equivalent multi-sounding measurement uncertainty, factoring in both time/space error correlations and data rejection due to clouds and thick aerosols. Finally, we examine the impact of three types of systematic errors: measurement biases due to aerosols, transport errors, and mistuning errors caused by assuming incorrect statistics. When only random measurement errors are considered, both nadir- and glint-mode data give error reductions over the land of ~45% for the weekly fluxes, and ~65% for seasonal fluxes. Systematic errors reduce both the magnitude and spatial extent of these improvements by about a factor of two, however. Improvements nearly as large are achieved over the ocean using glint-mode data, but are degraded even more by the systematic errors. Our ability to identify and remove systematic errors in both the column retrievals and atmospheric assimilations will thus be critical for maximizing the usefulness of the OCO data.SD and DB acknowledge support from NASA grant NNG06G127G. DB also acknowledges initial support from NOAA Grant NA16GP2935

Climatic, edaphic, and biotic controls over storage and turnover of carbon in soils

Soil carbon, a major component of the global carbon inventory, has significant potential for change with changing climate and human land use. We applied the Century ecosystem model to a series of forest and grassland sites distributed globally to examine large-scale controls over soil carbon. Key site-specific parameters influencing soil carbon dynamics are soil texture and foliar lignin content; accordingly, we perturbed these variables at each site to establish a range of carbon concentrations and turnover times. We examined the simulated soil carbon stores, turnover times, and C:N ratios for correlations with patterns of independent variables. Results showed that soil carbon is related linearly to soil texture, increasing as clay content increases, that soil carbon stores and turnover time are related to mean annual temperature by negative exponential functions, and that heterotrophic respiration originates from recent detritus (∼50%), microbial turnover (∼30%), and soil organic matter (∼20%) with modest variations between forest and grassland ecosystems. The effect of changing temperature on soil organic carbon (SOC) estimated by Century is dSOC/dT= 183e−0.034T. Global extrapolation of this relationship leads to an estimated sensitivity of soil C storage to a temperature of −11.1 Pg° C−1, excluding extreme arid and organic soils. In Century, net primary production (NPP) and soil carbon are closely coupled through the N cycle, so that as temperatures increase, accelerated N release first results in fertilization responses, increasing C inputs. The Century-predicted effect of temperature on carbon storage is modified by as much as 100% by the N cycle feedback. Century-estimated soil C sensitivity (−11.1 Pg° C−1) is similar to losses predicted with a simple data-based calculation (−14.1 Pg° C−1). Inclusion of the N cycle is important for even first-order predictions of terrestrial carbon balance. If the NPP-SOC feedback is disrupted by land use or other disturbances, then SOC sensitivity can greatly exceed that estimated in our simulations. Century results further suggest that if climate change results in drying of organic soils (peats), soil carbon loss rates can be high

Methane production and consumption in grassland and boreal ecosystems

The objectives of the this project were to develop a mechanistic understanding of methane production and oxidation suitable for incorporation into spatially explicit models for spatial extrapolation. Field studies were undertaken in Minnesota, Canada, and Colorado to explore the process controls over the two microbial mediated methane transformations in a range of environments. Field measurements were done in conjunction with ongoing studies in Canada (the Canadian Northern Wetlands Projects: NOWES) and in Colorado (The Shortgrass Steppe Long Term Ecological Research Project: LTER). One of the central hypotheses of the proposal was that methane production should be substrate limited, as well as being controlled by physical variables influencing microbial activity (temperature, oxidation status, and pH). Laboratory studies of peats from Canada and Minnesota (Northern and Southern Boreal) were conducted with amendments of a methanogenic substrate at multiple temperatures and at multiple pHs (the latter by titrating samples). The studies showed control by substrate, pH, and temperature in order in anaerobic samples. Field and laboratory manipulations of natural plant litter, rather than an acetogenic substrate, showed similarly large effects. The studies concluded that substrate is an important control over methanogenesis, that substrate availability in the field is closely coupled to the chemistry of the dominant vegetation influencing its decomposition rate, that most methane is produced from recent plant litter, and that landscape changes in pH are an important control, highly correlated with vegetation