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

Boreal forest CO2 exchange and evapotranspiration predicted by nine ecosystem process models: Intermodel comparisons and relationships to field measurements

Nine ecosystem process models were used to predict CO2 and water vapor exchanges by a 150-year-old black spruce forest in central Canada during 1994–1996 to evaluate and improve the models. Three models had hourly time steps, five had daily time steps, and one had monthly time steps. Model input included site ecosystem characteristics and meteorology. Model predictions were compared to eddy covariance (EC) measurements of whole-ecosystem CO2exchange and evapotranspiration, to chamber measurements of nighttime moss-surface CO2release, and to ground-based estimates of annual gross primary production, net primary production, net ecosystem production (NEP), plant respiration, and decomposition. Model-model differences were apparent for all variables. Model-measurement agreement was good in some cases but poor in others. Modeled annual NEP ranged from −11 g C m−2 (weak CO2source) to 85 g C m−2 (moderate CO2 sink). The models generally predicted greater annual CO2sink activity than measured by EC, a discrepancy consistent with the fact that model parameterizations represented the more productive fraction of the EC tower “footprint.” At hourly to monthly timescales, predictions bracketed EC measurements so median predictions were similar to measurements, but there were quantitatively important model-measurement discrepancies found for all models at subannual timescales. For these models and input data, hourly time steps (and greater complexity) compared to daily time steps tended to improve model-measurement agreement for daily scale CO2 exchange and evapotranspiration (as judged by root-mean-squared error). Model time step and complexity played only small roles in monthly to annual predictions

Comparison of boreal ecosystem model sensitivity to variability in climate and forest site parameters

Ecosystem models are useful tools for evaluating environmental controls on carbon and water cycles under past or future conditions. In this paper we compare annual carbon and water fluxes from nine boreal spruce forest ecosystem models in a series of sensitivity simulations. For each comparison, a single climate driver or forest site parameter was altered in a separate sensitivity run. Driver and parameter changes were prescribed principally to be large enough to identify and isolate any major differences in model responses, while also remaining within the range of variability that the boreal forest biome may be exposed to over a time period of several decades. The models simulated plant production, autotrophic and heterotrophic respiration, and evapotranspiration (ET) for a black spruce site in the boreal forest of central Canada (56°N). Results revealed that there were common model responses in gross primary production, plant respiration, and ET fluxes to prescribed changes in air temperature or surface irradiance and to decreased precipitation amounts. The models were also similar in their responses to variations in canopy leaf area, leaf nitrogen content, and surface organic layer thickness. The models had different sensitivities to certain parameters, namely the net primary production response to increased CO2 levels, and the response of soil microbial respiration to precipitation inputs and soil wetness. These differences can be explained by the type (or absence) of photosynthesis-CO2 response curves in the models and by response algorithms of litter and humus decomposition to drying effects in organic soils of the boreal spruce ecosystem. Differences in the couplings of photosynthesis and soil respiration to nitrogen availability may also explain divergent model responses. Sensitivity comparisons imply that past conditions of the ecosystem represented in the models\u27 initial standing wood and soil carbon pools, including historical climate patterns and the time since the last major disturbance, can be as important as potential climatic changes to prediction of the annual ecosystem carbon balance in this boreal spruce forest

Population–reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population–reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population–reaction model. We also show that population–reaction models can be applied to various ecological concepts, such as predator–prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Effects of processes at the population and community level on carbon dynamics of an ecosystem model

Ecological processes at the population and community level are often ignored in biogeochemical models, however, the effects of excluding these processes at the ecosystem level is uncertain. In this study we analyzed the set of behaviors that emerge after introducing population and community processes into an ecosystem carbon model. We used STANDCARB, a hybrid model that incorporates population, community, and ecosystem processes to predict carbon dynamics over time. Our simulations showed that at the population level, colonization and mortality rates can limit the maximum biomass achieved during a successional sequence. Specifically, colonization rates control temporal lags in the initiation of carbon accumulation, and mortality rates can have important effects on annual variation in live biomass. At the community level, differences in species traits and changes in species composition over time introduced significant changes in carbon dynamics. Species with different set of parameters, such as growth and mortality rates, introduce patterns of carbon accumulation that could not be reproduced using a single species with the average of parameters of multiple species or by simulating the most abundant species (strategies commonly employed in terrestrial biogeochemical models). We conclude that omitting population and community processes from biogeochemical models introduces an important source of uncertainty that can impose important limitations for predictions of future carbon balances

Asymmetric warming significantly affects net primary production, but not ecosystem carbon balances of forest and grassland ecosystems in northern China

We combine the process-based ecosystem model (Biome-BGC) with climate change-scenarios based on both RegCM3 model outputs and historic observed trends to quantify differential effects of symmetric and asymmetric warming on ecosystem net primary productivity (NPP), heterotrophic respiration (Rh) and net ecosystem productivity (NEP) of six ecosystem types representing different climatic zones of northern China. Analysis of covariance shows that NPP is significant greater at most ecosystems under the various environmental change scenarios once temperature asymmetries are taken into consideration. However, these differences do not lead to significant differences in NEP, which indicates that asymmetry in climate change does not result in significant alterations of the overall carbon balance in the dominating forest or grassland ecosystems. Overall, NPP, Rh and NEP are regulated by highly interrelated effects of increases in temperature and atmospheric CO2 concentrations and precipitation changes, while the magnitude of these effects strongly varies across the six sites. Further studies underpinned by suitable experiments are nonetheless required to further improve the performance of ecosystem models and confirm the validity of these model predictions. This is crucial for a sound understanding of the mechanisms controlling the variability in asymmetric warming effects on ecosystem structure and functioning