Multi-Scale Inteactions within Natural Systems: A Conceptual Framework

Eugene S. Takle* and David T. Kao**

*Department of Geological and Atmospheric Science and Department of Agronomy
**Department of Civil and Construction Engineering
Iowa State University, Ames, IA 50011 USA
e-mail: gstakle@iastate.edu*, dtk@iastate.edu
**KEYWORDS: environmental science, natural resources, interactive systems, microclimate model

ABSTRACT
We present a conceptual framework for evaluating the interaction of biological systems with the environment over scales as small as plant components to scales as large as the global atmosphere. The economic and ecological performance of plants and its relation to human influences can be evaluated systematically within this framework. Results of a model that couples plants, soil, and microclimate demonstrate how one component species of a plant community alters the microclimate and soil characteristics for neighboring plants.

INTRODUCTION
The urgent need for societal (economic, cultural, etc.) growth that is sustainable in both industrialized and developing nations calls for methods of assessing interactions of widely disperse components of natural systems and their individual and collective responses to human intervention. Specialized areas of research have produced advanced numerical and conceptual models of components of natural systems (e.g., global climate models, forest succession models, soil heat-transfer models). Having been developed more or less independently for the purposes of studying internal processes, these models usually do not consider linkage to other components of natural systems. Time and space scales usually are dictated by internal considerations and not for interfacing to a spectrum of external influences. And such models generally evolve toward more detail and complexity at the expense of being able to interface smoothly to other components of the natural world.

We have developed a framework for modeling natural systems called plant-soil-climate-system science (psc-system science) that spans space scales from global to scales of insects. This framework puts plants at the central focus and includes plants of different types growing close enough to one another so as to induce mutual interactions. The environment of these plants consists of (1) a spatially fixed component (soil of a particular type, slope of surface, latitude and longitude), (2) fluids of the atmosphere and soil, (3) living organisms (insects, pathogens, soil microbes, etc.), and (4) human influences. This paper offers a conceptual picture of how these influences can be organized to create a systems approach to the study of plant performance in natural or managed ecosystems. It further offers an opportunity for research results developed deep within a particular discipline to become part of a larger bank of knowledge and general modeling framework for understanding and predicting plant performance.

CONCEPTUAL FRAMEWORK
We have developed a framework for modeling the interaction of natural systems that allows events on the scale of global climate processes to be linked in a physically consistent way through a hierarchy of first-principles models to processes on scales of insects. The central role of plants in providing photosynthetic processes that transform carbon dioxide and solar energy into feedstock for other life on the planet suggests that plants be put at the center of this framework. For considerations of stability of the global climate system, plants provide important feedbacks that tend to keep the climate from drifting very far from its presently observed state (Lovelock, 1982), although the result may not be a steady state (Zeng et al. 1990).

Global and regional scale models of plant interactions with their environment aggregate plant communities at scales corresponding to the finest resolution of the model. For 1-dimensional global models, all vegetation is lumped together without any plant-plant interaction within the biosphere. Even 3-dimensional global climate models and regional climate models do not allow such interactions. However, at scales of plant communities, interactions between different plants are central to the functioning of the unit and must be included.

Therefore, a pivotal consideration in the progression of scales from global to microscale in environmental models is the scale at which the presence of one plant modifies the environment of another plant. For example, simulation of the ecosystem dynamics of a small stream with wooded banks (a richly diverse ecosystem in a prairie landscape) requires detailed information about interaction of vegetation with the atmosphere that is not captured by parameterizations in global or regional climate models. It is noteworthy that microclimate modifications introduced by vegetation can be much larger than modifications introduced by doubling greenhouse gas concentrations. Human control of surface vegetation, with even small attendant changes in microclimates, can have deliberate or inadvertent cumulative influence on ambient temperature, moisture, and radiation which are key environmental factors for most plant processes, soil processes, crop production, changes in insect populations, plant disease characteristics, and small animal habitat.

From these considerations, it can be concluded that the physical scale at which plants interact is on the order of the physical size of the largest component of the plant community. Understanding these microscale interactions is key to understanding human impact on natural systems at all scales.

Figure 1 gives a schematic representation of the scope of the systems approach envisioned in the natural-systems framework. Central to this figure are two plants of different types. These could be agricultural plants or other agro-ecosystem plants (e.g., trees, shrubs, wetland plants). Models of physiological development of plants are evolving, and models of some plants, such as those used as agricultural crops, have shown promise for yield prediction. Many plant processes are yet to be incorporated directly into physiological models, but information on these processes may exist as databases or qualitative narrative resulting from specific research projects. The conceptual framework brings these disparate information sources together in a plant information bank under the organization of an expert system that is able to accept a request for information about incremental plant growth or response to external influences.

Plants interact with their micro-environment of soil and atmosphere and create changes in this micro-environment (e.g., extract moisture and nutrients from the soil, add moisture to the air, create turbulence, provide shade). These modified conditions comprise part of the micro-environment of the neighboring plant. In this way, fluid flow in soil and atmosphere become connecting agents leading to plant interactions. Recent progress in describing fluid flow processes in such heterogeneous conditions offer opportunities to advance the rigor with which these interactions can be described. We will return to this in the following section.

Models and databases of insect and pathogen behavior organized and interrogated by computer-based expert systems provide information on the flourishing or demise of these predators under specific micro-environments of atmospheric and soil conditions. Populations of these pests as determined by environmental factors provided by microclimate databases or models are used by plant models, along with other micro-environment conditions, to determine the dynamic response of the plant and its resulting modification of the micro-environment for its neighboring plant.

Crop growth models use plant physiological processes to describe evolution of a crop over the entire growing season and estimate crop yield. While still somewhat crude, these crop models recently have become much more sophisticated, and continued improvement in validity of such models is expected. The envisioned psc-system science goes much further to include simulation of atmospheric turbulent flow and three-dimensional transport of heat, moisture, CO2, oxygen, and trace chemicals in both soil and atmosphere. Present crop models are limited to uniform field conditions. Psc-system science addresses heterogeneous soil and microclimate conditions and simulates interactions among different plant species growing in multi-cropped, sheltered, or naturally heterogeneous environments.

Human factors that may influence the plant environment through either deliberate actions (e.g., cropping strategies, management practices, and applied chemicals and fertilizers) or inadvertent actions (e.g., surface water contamination, long range transport of pollutants, soil erosion) can be quantified and evaluated within the systems approach. Psc-system science offers a conceptual framework for issues such as sustainable agriculture and precision farming.

MICROCLIMATE INTERACTIONS
Simulation of the microclimate impact of an agricultural shelterbelt is an example of the physical linkage of different components of the plant-soil-climate system. In this example, the key question is how does the presence of an agricultural shelterbelt (in this case an infinitely long line of trees in an agricultural landscape) influence evapotranspiration from an agricultural crop growing downwind of the shelter. Observational studies have been somewhat inconclusive on this issue, with some showing up to 40% reduction in evapotranspiration immediately behind the shelter, but others showing slight increases.

We address this issue by use of a turbulent, atmospheric flow model based on fundamentals of flow through a porous medium (Wang and Takle, 1995a, b), in this case being living vegetation represented by trees. To this basic aerodynamic model we add equations governing conservation of heat and moisture (Wang and Takle, 1996). Figure 2 gives plots of the latent heat (evapotranspiration in Fig. 2a) and sensible heat (Fig. 2b) from a surface that initially is saturated with water on the leeward side of a shelter of medium density and height H as a function of time of day (vertical axis) and distance from the shelter in units of H (horizontal axis).

The results show that the shelter reduces wind speed and breaks down large turbulent length scales, reduces vertical transport of water vapor and therefore reduces evaporation from the surface in the near lee. Decreased evaporation leads to a build-up of heat and hence an increase in sensible heat flux in the near lee as shown in Figure 2a and 2b. As shown in Figure 2a, the latent heat flux is decreased by from 20% to 50% between 11 AM and 4 PM LST in the region of 4 to 8 H behind the shelter. Because this time of the day normally has high surface evaporation, the shelter substantially reduces loss of soil moisture. The reduction in evaporation is balanced through the surface energy budget by an increase in sensible heat loss by the surface, as shown in Figure 2b. Sensible heat flux is increased by a factor of 4 during midday in the region of 4 to 8 H. This build-up of heat in the lee may be beneficial during the cool season but detrimental during the warm season, depending on the type of crop and other conditions.

We extended the model to evaluate the impact of the shelter on evapotranspiration as a function of time since the last precipitation event. For each experiment, the soil was considered saturated at day zero after which no precipitation occurs. Results shown in Fig 3a reveal that the daily average latent heat is reduced by the shelter in the region out to 20 H for the first 30 days, with maximum reduction being in the region of 4-8 H. After 30 days, evapotranspiration increases (in comparison with an unsheltered region) in the lee, with maximum increase around day 40. The sensible heat flux, shown in Fig 3b, has opposite sign.

We also investigated the evolution of soil moisture at two locations downwind of the shelter after a precipitation event (Wang et al. 1977). Figure 4 shows the changes of soil moisture at 2.5 H (Fig. 4a) and 45 H (Fig. 4b) downwind at depths of 0.02 m (indicated by curve labeled W1), 1.0 m (W2), and 2.0 m (W3). It is noteworthy that soil moisture is significantly higher (20% higher) at 5 H than at 45 H at about 20 days, but after 60 days (1440 hours) they become nearly equal. Deep soil moisture remains slightly higher near the shelter. It also is notable that the diurnal variation is considerably reduced nearer the shelter.

From these results we can conclude that the trees have significant impact on reducing evapotranspiration for the first 3-4 weeks after a rain event, but their value in maintaining soil moisture diminishes after that time.
This example shows how the micro-environment of a heterogeneous plant ecosystem can be simulated by a numerical model of soil, plants, and atmosphere built on fundamental principles of conservation of energy and mass and theory of aerodynamic flow through porous obstacles. We presently are using output of this model to produce microclimate environments for agricultural crops (corn and soybeans) grown in the interaction region.
Domains of microclimate model use meteorological conditions of larger scale flow as lateral and top boundary conditions. These could be supplied from observations or output of regional climate models, which in turn can be imbedded in global models (Gutowski et al. 1996). This hierarchy of models allows impacts of global-scale phenomena, such as El Nino or warming induced by greenhouse gases, to be linked in a physically consistent way through a hierarchy of scales to individual components of a heterogeneous ecosystem. Plant response to these or other such remote influences as location in the watershed, proximity to major water bodies, vector-borne pathogens of distant origin, or distant sources of pollution can be evaluated without having to rely solely on hypothetical scenarios and sensitivity studies.

A key consideration in the coupling of models of different scales is the conservation of fundamental properties such as momentum, energy, and mass of major gases, trace gases, and water substance across the different space and time scales considered by different models. Development of systematic methods to accurately characterize fluxes of such quantities from one model to another is a major challenge for such a modeling framework (Bryan et al. 1996).

ANALYZING ECONOMIC AND ECOLOGICAL ASPECTS OF PLANT PERFORMANCE
The largest uncertainty in agricultural economic models is weather. Current research attention to seasonal and interannual climate variability and climate impacts of El Nino, increased concentration s of greenhouse gases and aerosols suggests opportunities for closer linkage of climate, crop, and economic models.

Psc-system simulations allow searches for the best return and least risk (economic or environmental) resulting from alternative actions. Typical simulations might include evaluating response of different plants (crops) to ensembles of environmental (atmospheric and soil) conditions, determining comprehensive environmental effects of agricultural chemicals (fertilizers, pesticides) under realistic environmental conditions, evaluating effects of alternative tillage practices, and maximizing plant performance under alternative strip-cropping strategies.
Problems to be addressed with the psc-system approach include many that presently are studied only through isolated field tests. The modeling component is intended to give larger context to field studies by providing a conceptual framework of interconnections for broader use of results of such studies. Simulations involving chemicals or genetically altered materials could be conducted without necessary precautions required for field tests.
Modeling studies offer an inexpensive method of simulating alternative field conditions and other geographic locations as a guide for evaluating hypotheses and defining further field and laboratory experiments.

AN EXTENDED VIEW OF THE FRAMEWORK
We use the above example to illustrate the linkage among different components of a plant-soil-climate-system as projected by the interaction between the shelterbelt and plants under its influence. Other human influences manifested in various types of management practices also can be modeled in a similar manner so long as the relationship governing the interaction and interplay between the adjoining components are adequately understood, properly described, and mathematically expressed.

The arrows between adjacent components shown in Figure 1 can be treated as the information carrying bonding rods for the formation of basic building blocks linking existing models and databases developed for these components. Through further integration of these building blocks possibly using interactive and interrogative expert systems, the complex natural system as depicted in Figure 1 can be properly modeled. The interaction and interplay among various components of the plant-soil-climate-system under the influence of other living organisms and human interventions are highly dynamic. Depending on needs of the user, one can modify the suggested conceptual framework by subtracting or adding other elements of interest to simplify or enhance the modeling effort.

SUMMARY
Plant-soil-climate-system science offers a new conceptual framework for analyzing economic and ecological aspects of plant performance in natural and cultivated environments. A critical link in this modeling framework is the ability to simulate interactions mediated by fluids of the atmosphere and soil. Recent advances in this area offer new opportunities for modeling multi-scale interactions within natural systems.

REFERENCES
Bryan, F. O., B. G. Kauffman, W. G. Large, and P. R. Gent. 1996. The NCAR CSM Flux Coupler. NCAR Technical Note NCAR/TN-424+SRT. National Center for Atmospheric Research, Boulder, CO. 58 pp.

Gutowski, W. J., E. S. Takle, R. W. Arritt. 1996. Planned Mesoscale Climate Simulations for TAR Impacts Assessments. Interfacing Mesoscale Climate Models with Impacts Assessment: A Workshop, 5 - 6 December 1996, Boulder, Colorado.

Lovelock, J. E. 1982. Gaia as Seen Through the Atmosphere. Biomineralization and Biological Metal Accumulations (ed. by P. Westbroek and E. W de Jong. D. Reidel Publishing Co., Dordrecht, The Netherlands 15-25.

Wang, H., J. Shen, and E. S. Takle. 1997. Influences of Agroforestry Ecosystem on Evapotranspiration and Soil Moisture. 13th Conference on Hydrology. Amer. Meteorol. Soc. Long Beach, CA. 360-361.

Wang, H., and E. S. Takle.1995a. Boundary-Layer Flow and Turbulence near Porous Obstacles. I. Derivation of a General Equation Set for a Porous Medium. Boundary-Layer Meteorology, 74, 73-88.

Wang, H., and E. S. Takle. 1995b. A Numerical Simulation of Boundary-Layer Flows near Shelterbelts. Boundary Layer Meteorology, 75, 141-173

Wang, H., and E. S. Takle. 1996. Modeling the Evapotranspiration and Energy Partition of Inhomogeneous Agroecosystems. 22nd Conference on Agricultural and Forest Meteorology, Atlanta, GA, Amer. Meteor. Soc.

Zeng, X., R. A. Pielke, and R. Eykholt. 1990. Chaos in Daisyworld. Tellus, 42B, 309-318.

Fig. 1. Conceptual framework for linking models and databases on plants, soil, climate, insects, pathogens, and human influences.

Fig. 2. Components of the surface energy budget during a 24-hour period at various distances from the shelter as simulated by the shelterbelt model: (a) Latent heat (LE) in W/m2, (b) Sensible heat in W/m2. Shelter porositity is medium dense and surface is moist but not saturated. Values in the far lee (right-hand side of the graph) approximate the unsheltered values.

Fig. 3. 183-day simulations of evapotranspiration (LE) and heat fluxes (H) as a function of time and distance from the shelter. The daily averaged LE and H are shown. Figures are plotted only for the first 90 days.

Fig. 4. 183-day simulations of soil moisture in three different levels. Plots give only the first 90 days. Figure 2a shows results for 5H downwind, and Figure 2b gives values at 45 H downwind (essentially unsheltered).