Lisa Wainger

Spatial landscape indices in a hedonic framework: an ecological economics analysis using GIS

Abstract This paper develops a spatial hedonic model to explain residential values in a region within a 30-mile radius of Washington DC. Hedonic models of housing or land values are commonplace, but are rarely estimated for non-urban problems and never using the type of spatial data (geographical information system or GIS) available to us. Our approach offers the potential for a richer model, one that allows for spatial heterogeneity in estimation, and one that ties residential land values to features of the landscape. Beyond the traditional variables to explain residential values, such as man-made and ecological features of the parcel and distance to cities and natural amenities, we also hypothesize that the value of a parcel in residential land use is affected by the pattern of surrounding land uses, not just specific features of point locations. We have also created and added these variables to the hedonic model by choosing an appropriate area around an observation, and calculating measures of percent open space, diversity, and fragmentation of land uses, measured at different scales around that observation. These indices have, for the most part, been significant in the models. By including two of the landscape indices developed by landscape ecologists, we have developed a model that explains land and housing values more completely, by capturing how individuals value the diversity and fragmentation of land uses around their homes.

Modeling Complex Ecological Economic Systems: Toward an Evolutionary, Dynamic Understanding of People and Nature

Recent understanding about system dynamics and predictability that has emerged from the study of complex systems is creating new tools for modeling interactions between anthropogenic and natural systems. A range of techniques has become available through advances in computer speed and accessibility and by implementing a broad, interdisciplinary systems view.

Ecological economic modeling and valuation of ecosystems

Abstract We are attempting to integrate ecological and economic modeling and analysis in order to improve our understanding of regional systems, assess potential future impacts of various land-use, development, and agricultural policy options, and to better assess the value of ecological systems. Starting with an existing spatially articulated ecosystem model of the Patuxent River drainage basin in Maryland, we are adding modules to endogenize the agricultural components of the system (especially the impacts of agricultural practices and crop choice) and the process of land-use decision making. The integrated model will allow us to evaluate the indirect effects over long time horizons of current policy options. These effects are almost always ignored in partial analyses, although they may be very significant and may reverse many long-held assumptions and policy predictions. This paper is a progress report on this modeling effort, indicating our motivations, ideas, and plans for completion.

Patuxent landscape model: integrated ecological economic modeling of a watershed

The Patuxent Landscape Model (PLM) is designed to simulate fundamental ecological processes on the watershed scale, in interaction with an economic component that predicts the land use patterns. The paper focuses on the ecological component of the PLM and describes how the spatial and structural rescaling can be instrumental for calibration of complex spatially distributed models. The PLM is based on a modified General Ecosystem Model (GEM) that is replicated across a grid of cells that compose the rasterized landscape. Different habitats and land use types translate into different parameter sets to be fed into GEM. Cells are linked by horizontal fluxes of material and information, driven mostly by the hydrologic flows. This approach provides additional flexibility in scaling up and down over a range of spatial resolutions and is essential to track the land use change patterns generated by the economic component. Structural modularity is another important feature that is implemented in the general purpose software packages (Spatial Modeling Environment and Collaborative Modeling Environment), that the PLM employs.

Development of a general ecosystem model for a range of scales and ecosystems

Abstract We have developed a General Ecosystem Model (GEM) that is designed to simulate a variety of ecosystem types using a fixed model structure. 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. While the model may be used to simulate ecosystem dynamics for a single homogenous habitat, our primary objective is to replicate it as a “unit” model in heterogeneous, grid-based dynamic spatial models using different parameter sets for each habitat. Thus, we constrained the process (i.e., computational) complexity, yet targeted a level of disaggregation that would effectively capture the feedbacks among important ecosystem processes. A basic version was used to simulate the response of sedge and hardwood communities to varying hydrologic regimes and associated water quality. Sensitivity analyses provided examples of the model dynamics, showing the varying response of macrophyte production to different nutrient requirements, with subsequent changes in the sediment water nutrient concentrations and total water head. Changes in the macrophyte canopy structure resulted in differences in transpiration, and thus the total water levels and macrophyte production. The GEMs modular design facilitates understanding the model structure and objectives, inviting variants of the basic version for other research goals. Importantly, we hope that the generic nature of the model will help alleviate the “reinventing-the-wheel” syndrome of model development, and we are implementing it in a variety of systems to help understand their basic dynamics.

Integrated ecological economic modeling of the patuxent river watershed, Maryland

Understanding the way regional landscapes operate, evolve, and change is a key area of research for ecosystem science. It is also essential to support the “place-based” management approach being advocated by the U.S. Environmental Protection Agency and other management agencies. We developed a spatially explicit, process-based model of the 2352 km2 Patuxent River watershed in Maryland to integrate data and knowledge over several spatial, temporal, and complexity scales, and to serve as an aid to regional management. In particular, the model addresses the effects of both the magnitude and spatial patterns of human settlements and agricultural practices on hydrology, plant productivity, and nutrient cycling in the landscape. The spatial resolution is variable, with a maximum of 200 × 200 m to allow adequate depiction of the pattern of ecosystems and human settlement on the landscape. The temporal resolution is different for various components of the model, ranging from hourly time steps in the hydrologic sector to yearly time steps in the economic land-use transition module. We used a modular, multiscale approach to calibrate and test the model. Model results show good agreement with data for several components of the model at several scales. A range of scenarios with the calibrated model shows the implications of past and alternative future land-use patterns and policies. We analyzed 18 scenarios including: (1) historical land-use in 1650, 1850, 1950, 1972, 1990, and 1997; (2) a “buildout” scenario based on fully developing all the land currently zoned for development; (3) four future development patterns based on an empirical economic land-use conversion model; (4) agricultural “best management practices” that lower fertilizer application; (5) four “replacement” scenarios of land-use change to analyze the relative contributions of agriculture and urban land uses; and (6) two “clustering” scenarios with significantly more and less clustered residential development than the current pattern. Results indicate the complex nature of the landscape response and the need for spatially explicit modeling.

Science Priorities for Reducing the Threat of Invasive Species to Sustainable Forestry

Abstract Invasive species pose a major, yet poorly addressed, threat to sustainable forestry. Here we set forth an interdisciplinary science strategy of research, development, and applications to reduce this threat. To spur action by public and private entities that too often are slow, reluctant, or unable to act, we recommend (a) better integrating invasive species into sustainable forestry frameworks such as the Montréal Process and forest certification programs; (b) developing improved cost estimates to inform choices about international trade and pest suppression efforts; and (c) building distributed information systems that deliver information on risks, identification, and response strategies. To enhance the success of prevention and management actions, we recommend (a) advancing technologies for molecular identification, expert systems, and remote sensing; (b) evolving approaches for ecosystem and landscape management; and (c) better anticipating interactions between species invasions and other global change processes.

Realizing the Potential of Ecosystem Services: A Framework for Relating Ecological Changes to Economic Benefits

Increasingly government agencies are seeking to quantify the outcomes of proposed policy options in terms of ecosystem service benefits, yet conflicting definitions and ad hoc approaches to measuring ecosystem services have created confusion regarding how to rigorously link ecological change to changes in human well-being. Here, we describe a step-by-step framework for producing ecological models and metrics that can effectively serve an economic-benefits assessment of a proposed change in policy or management. A focus of the framework is developing comparable units of ecosystem goods and services to support decision-making, even if outcomes cannot be monetized. Because the challenges to translating ecological changes to outcomes appropriate for economic analyses are many, we discuss examples that demonstrate practical methods and approaches to overcoming data limitations. The numerous difficult decisions that government agencies must make to fairly use and allocate natural resources provides ample opportunity for interdisciplinary teams of natural and social scientists to improve methods for quantifying changes in ecosystem services and their effects on human well-being. This framework is offered with the intent of promoting the success of such teams as they support managers in evaluating the equivalency of ecosystem service offsets and trades, establishing restoration and preservation priorities, and more generally, in developing environmental policy that effectively balances multiple perspectives.

Adding fuel to the fire: the impacts of non-native grass invasion on fire management at a regional scale

Background Widespread invasion by non-native plants has resulted in substantial change in fire-fuel characteristics and fire-behaviour in many of the worlds ecosystems, with a subsequent increase in the risk of fire damage to human life, property and the environment. Models used by fire management agencies to assess fire risk are dependent on accurate assessments of fuel characteristics but there is little evidence that they have been modified to reflect landscape-scale invasions. There is also a paucity of information documenting other changes in fire management activities that have occurred to mitigate changed fire regimes. This represents an important limitation in information for both fire and weed risk management. Methodology/Principal Findings We undertook an aerial survey to estimate changes to landscape fuel loads in northern Australia resulting from invasion by Andropogon gayanus (gamba grass). Fuel load within the most densely invaded area had increased from 6 to 10 t ha−1 in the past two decades. Assessment of the effect of calculating the Grassland Fire Danger Index (GFDI) for the 2008 and 2009 fire seasons demonstrated that an increase from 6 to 10 t ha−1 resulted in an increase from five to 38 days with fire risk in the ‘severe’ category in 2008 and from 11 to 67 days in 2009. The season of severe fire weather increased by six weeks. Our assessment of the effect of increased fuel load on fire management practices showed that fire management costs in the region have increased markedly (∼9 times) in the past decade due primarily to A. gayanus invasion. Conclusions/Significance This study demonstrated the high economic cost of mitigating fire impacts of an invasive grass. This study demonstrates the need to quantify direct and indirect invasion costs to assess the risk of further invasion and to appropriately fund fire and weed management strategies.

Tradeoffs among Ecosystem Services, Performance Certainty, and Cost-efficiency in Implementation of the Chesapeake Bay Total Maximum Daily Load

The cost-effectiveness of total maximum daily load (TMDL) programs depends heavily on program design. We develop an optimization framework to evaluate design choices for the TMDL for the Potomac River, a Chesapeake Bay sub-basin. Scenario results suggest that policies inhibiting nutrient trading or offsets between point and nonpoint sources increase compliance costs markedly and reduce ecosystem service co-benefits relative to a least-cost solution. Key decision tradeoffs highlighted by the analysis include whether agricultural production should be exchanged for low-cost pollution abatement and other environmental benefits and whether lower compliance costs and higher co-benefits provide adequate compensation for lower certainty of water-quality outcomes.