This integrated project takes a systems approach to integrate ecology and
economics for a managed forest landscape in Michigan’s Upper Peninsula that has been experiencing low tree regeneration due to overabundant white-tailed deer, and
declines in habitat for songbirds of conservation concern due to deer impacts and
To achieve this goal, our objectives are to:
- develop and validate a
systems ecological-economic model
- conduct simulation experiments and test
hypotheses using the model
- use research products for education and
The comprehensive model incorporates a variety of information on plants, wildlife,
market and non-market values, and management activities. It will be a powerful
simulation tool for addressing many fundamental questions that have important
implications for management.
Figure 1. Hierarchical consideration of processes in the study area
The model will be spatially explicit (grid-based), with locations of objects (e.g., forest stands) built into the model. The model will also be hierarchically structured reflecting the differences in spatial scales relevant to each model component (Figure 1). For example, our vegetation submodel will integrate data from four spatial scales [landscape, patch (e.g., forest stand), grid cell (30 m x 30 m corresponding to Landsat ETM+ pixel resolution and field plot size), and individual trees], while the non-market value component of the economic submodel will only incorporate data from the two largest scales.
Figure 2. Conceptual framework of the integrated ecological-economic model
The conceptual framework (Figure 2) consists of vegetation, deer, bird and economic submodels with inputs, outputs and model integration. Harvest scenarios are composed of different harvesting frequencies, intensities, areas and locations. The input data are classified into ecological and economic categories. The ecological inputs are used to initialize and run three ecological submodels (vegetation, deer and bird submodels). The economic submodel inputs include economic values for ecological variables (e.g., tree diameter, relative deer density, bird species richness). The outputs from the sub-models will be integrated spatially and temporally according to their meaningful resolutions (i.e., grid cell, patch or landscape).
During both development and use of the model collaboration and consultation with a variety of key management stakeholders, including federal and state management organisations, non-governmental organisations and private land holders, will ensure the model is developed with the needs of management and users in mind. Because the model will be web-based and user friendly, it will greatly
assist in research, management, education, and extension.
The model also provides the means to address many basic questions regarding the long-term ecological and economic effects of timber harvesting and deer browsing disturbances for which traditional experiments are inadequate or infeasible at large scales. This innovative and timely project will provide critical stand-level and landscapescale
- long-term ecological and economic responses to deer
abundance and forest harvest regimes
- economic trade-offs between various
- ways to improve management and sustain forest and
The information and methods generated from this project will also be
applicable to sustainable management in many other similar landscapes of the Great
Lakes region and eastern North America impacted by abundant deer and timber
Whilst much of the data collection for this project is complete, the modeling phase is now being initiated. This website will serve as a resource for the modeling project, detailing its development and eventually hosting the model. The website will be modified and regularly updated so please check back frequently. A presentation outlining the current state of the project is available (works best with Firefox browser). Feel free to contact the research team (below) with any questions.
Ecological Economic Modelling Research Team
Jack Liu [email@example.com]
Frank Lupi [firstname.lastname@example.org]
Mike Walters [email@example.com]
Kim Hall [firstname.lastname@example.org]
James Millington [email@example.com]