Contact:
Lisa Wainger
University of Maryland Institute for Ecological Economics
Center for Environmental and Estuarine Studies
P.O. Box 38
Solomons, MD 20688
wainger@cbl.cees.edu
Our project aims to integrate knowledge and develop new tools to enhance predictive understanding of watershed ecosystems (including processes and mechanisms that govern the interconnected dynamics of water, nutrients, toxins, and biotic components) and their linkage to human factors affecting water and watersheds. The goal is effective sustainable ecosystem management at the watershed scale.
Major research questions include:
(1) What are the quantitative, spatially explicit and dynamic linkages between land use and terrestrial and aquatic ecosystem structure and function;
(2) What are the quantitative effects of various combinations of natural and anthropogenic stressors on watershed ecosystems and how do these effects change with scale; and
(3) What are useful ways to measure changes in the total value of the landscape including both marketed and non-marketed (natural system) components and how effective are alternative mitigation approaches, management strategies, and policy options toward increasing this value.
The proposed research will achieve these goals by integrating ongoing and new scientific studies over a range of scales in the Patuxent River watershed in Maryland. Another version of the model is currently being implemented in the Everglades in Florida to examine the implications of management strategies on elements of the ecosystem such as water levels, nutrient dynamics, and plant successional patterns (Fitz et al. 1993). The Patuxent project is part of an ongoing modeling effort, currently funded by NSF/EPA Water and Watersheds Program for three years.
We have developed a General Ecosystem Model (GEM) that is designed to simulate a variety of ecosystem types using a process-based fixed model structure (Fitz et al. 1995). Driven largely by hydrologic algorithms for upland, wetland and shallow-water habitats, the model captures the response of macrophyte and algal communities to simulated levels of nutrients, water, and environmental inputs. It explicitly incorporates ecological processes that determine water levels, plant production, nutrient cycling associated with organic matter decomposition, consumer dynamics, and fire. To simulate an entire watershed, we replicate the GEM "unit" model and divide the watershed into homogenous grid-cell units and use GIS to link cells to the parameter set for its habitat type and location in the watershed.
We have developed an ecological landscape model (the Patuxent Landscape Model or PLM) that links together GEM unit models on the landscape, and we are in the process of linking an economic model which endogenizes economic components to produce an integrated ecological economic model. The PLM contains about 6,000 spatial cells each containing a GEM with 21 state variables. Calibration and testing of this model is being carried out using available data. We are working collaboratively with other researchers to find funds for further field data collection efforts. Data have been collected to initialize, calibrate or validate the model with land use from 1973, 1981, 1985, and 1991, stream flow, water quality and other data . The intent is to run scenarios to the year 2020.. Effort will then be devoted to simulating past behavior of the landscape.
The spatial resolution of the PLM (0.04 km2) allows evaluation of impacts from changes in land use type or practices for particular groups of cells in the watershed. The aim is to be able to estimate selected key indicator variables for the Patuxent River watershed. The model can estimate impacts of specific land use patterns on loads to the Patuxent River estuary. The ecosystem functions and the parameters of those functions that are simulated for any given cell in the landscape are dictated by the cell's land use or habitat designation at the beginning of any simulation time step. Then, conditioned on that land use and the stocks of the state variables at that point in time in the cell, the processes and fluxes are calculated. When these changes are programmed, the simulation can estimate impacts on runoff variables including nitrogen, phosphorus, organic matter and suspended inorganic sediments. The effects of vegetative buffers and retention ponds on urban and agriculture runoff can be simulated as plants retard erosion and take up nutrients. Evaluations of various mixes and ratios of land use can also be performed.
The ecological model calculates land use designation through a "habitat switching" model which determines when, through natural succession or weather-driven ecological catastrophe (e.g. flood, forest fire), the habitat shifts from one type to another. Recognizing that the ecological effects of human activity are driven by the specific uses humans choose to make of the stock of natural capital, one of the major contributions of the economics modeling effort is an understanding of how land use decisions are made by individuals and how they are related to both the ecological and economic features of the landscape. See description of land use change model for details. The second type of contribution being made by the economics extension of the PLM is in modeling conditional human interactions, in this case, farmer's choice of crops and best management practices adoption, as functions of ecological and economic forces are currently underway.
Contact:
Dr. Nancy Bockstael
Agricultural and Resource Economics
University of Maryland
2200 Symons Hall
nancyb@arec.umd.edu
The economic model of land use conversion that will be linked with the Costanza et al. PLM model will provide a means of describing the evolving landscape under different policy scenarios on land use controls, non-point source pollution regulations, etc. With this understanding, the effect of differing regulatory environments will be more predictable, leading to improved methods for valuing ecosystem configurations and a greater ability to assess the benefits and costs of regulatory consequences. Ultimately the model will generate information that could inform the process of valuing the ecosystem as a regional landscape rather than a conglomeration of isolated goods and services.
Configuration and reconfiguration of the landscape occurs as a result of ecological and economic factors. The potential benefits of an integrated model of the ecosystem and the economy include a more accurate reflection of how the distribution of human activities such as farming, electric power generation, commercial and residential development, recreation, wastewater treatment, and highway construction affect the ecosystem. It also provides a basis for understanding how the ecosystem landscape affects human decisions because we will understand better the effect on the quality and value of goods and services, such as recreation, wildlife enjoyment, water quantity and quality, and aspects of the quality of life as reflected in property values.
The ultimate goal of the economic model for this interdisciplinary effort is to be able to predict on an annual basis the probability that a given parcel of land, of a given description and in a given location, will remain in its current use or be converted to an alternative use. As a result, the ability to make spatially specific predictions of land use changes should have payoffs for policy formation because public goods and land use management controls are so location specific. While the conversion process will be affected by inertia and other disequilibrium considerations and constrained by zoning and other land use controls, the change in land use probabilities are likely to be functions of the value of the parcel in alternative uses. Consequently the analysis must be able to explain what factors affect land values in alternatives uses. We first develop a hedonic model to predict residential land values, the results of which are then used in a model to predict land use change from forestry and agricultural land uses to residential land uses.
The empirical models that economists have developed to explain and predict housing values and land values are hedonic pricing models, which have been used with great success during the past 25 years. Economic theory relates the selling price of a piece of property as the present value of the future stream of rents from that property. The hedonic model relates the differences in selling prices of houses to a number of factors, including the quality of the housing structure on the property, neighborhood characteristics, the accessibility to the central business district, as well as the environmental amenities associated with the property. The estimated hedonic model is then used to predict the value of forested and agricultural land in residential uses, and the residential value is used as an explanatory variable in a model of land use conversion.
In the land use conversion model we predict the relative probabilities of conversion from a "develop-able" state (agriculture or forest) to residential use. The preliminary model is a discrete choice model, where the dependent variable is a zero/one variable indicating whether a parcel was or was not developed. Explanatory variables include the predicted value of the parcel in residential use (predicted from the hedonic model), its predicted value in agricultural use, factors that affect the costs of conversion, zoning regulations that affect minimum lot size, and plans for public sewer service provision. Factors that affect costs of conversion include soil type, slope and whether the land is forested. The latter requires clearing costs as compared to development of pasture or cropland. Steep slopes often preclude development (either practically or because of county controls on environmentally sensitive areas) and differing soil types are more or less suitable for excavation and construction.
The model attempts to capture the the interrelationship over time and space of humans and land use; how humans impact the spatial landscape and in turn, how the spatial landscape influences what individuals value. Location matters because scale and non-linearities in relationships between human activities and ecosystem effects matter. The spatial arrangement of land use matters to a host of ecosystem processes, making it useful for the economic analysis to adopt a spatially articulated approach. Such an approach may also improve the quality of the economic modeling since for some goods, most obviously land but also many public goods, value is affected dramatically by location.