GIS in Collaborative Forest Management Planning

Author’s Note
Over the last 20 years, the use of collaborative processes for forest management planning has become ubiquitous. These processes utilize key stakeholders to develop plans in order to attain broad consensus. GIS mapping and visualizations are increasingly being utilized to identify priority areas for active management. This annotated bibiliography documents the tools and resources used to help guide collaborative planning processes, as well as potential future techniques.

Annotated Bibliography

Balram, S., & Dragicevic, S. (2006). Modeling Collaborative GIS processes Using Soft Systems Theory, UML, and Object Oriented Design. Transactions in GIS, 10(2), 199-218.

This paper delves into integrating several collaborative GIS processes in order to develop a generic design that can be standardized. The collaborative spatial Delphi (CSD) methodology is used as the framework, and principles are integrated from object-oriented design and analysis, soft systems theory, and the unified modeling language (UML). The resulting models identify the roles of the actors within a system as Stakeholder, Facilitator, and Technical Support, and identifies the process by which consensus is reached. It also identifies the steps at which maps and visualization would be best utilized, and what data is useful for each step in the process.

Cannon, J., Hickey, R., & Gaines, W. (2018). Using GIS and the Ecosystem Management Decision Support Tool for Forest Management on the Okanogan-Wenatchee National Forest, Washington State. Journal of Forestry, 116(5), 460-472.

The Ecosystem Management Decision Support (EMDS) Tool was developed to evaluate and prioritize landscapes based on several criteria, including: vegetation, fire risk, insect risk, wildlife habitats, as well as an assessment of acquatic/road interactions which was generated through a different modeling tool, the NetMap acquatic platform. Departure maps were generated for the analysis. The resulting combined resource model was used by the team to identify a specific area to target for treatment.

Collins, B. M., Stephens, S. L., Moghaddas, J. J., & Battles, J. (2010). Challenges and Approaches in Planning Fuel Treatments across Fire-Excluded Forested Landscapes. Journal of Forestry, 24-31.

This paper discusses the gap between modeled ecosystem treatments, and the actual treatments implemented on the landscape. Treating 20% of the landscape appeared to have the best effect in reducing fire threat, as long as it’s implemented strategically. Constraints on treatments include habitat preservation, human communities, funding, and regulations and appeals. A combination of modeling and adaptive resource management with a diverse stakeholder group is recommended.

Coppes, J., & Braunisch, V. (2013). Managing visitors in nature areas: where do they leave trails? A spatial model. Wildlife Biology, 19(1), 1-11.

Managing outdoor recreation and human disturbance is challenged by the lack of data on where humans go off trail; in person surveys are often unreliable. Human disturbance can be especially problematic in winter, when sensitive species need to conserve energy. The study used probability of leaving the trail as a function of topography, forest structure, and tourism infrastructure, along with habitat information, to identify locations where mitigation measures would be most effective. Max ENT was used in order to model species distributions when reliable absence data are missing. Overall this was a very low cost methodology to model use, and identify direct management interventions and locations.

de Groot, R. S., Alkemade, R., Braat, L., Hein, L., & Willemen, L. (2010). Challenges in integrating the concept of ecosystem services and values in landscape planning, management and decision making. Ecological Complexity, 7, 260-272.

In this paper de Groot et all discuss the challenges and potential solutions to including ecosystem services in landscape management. Integrating ecosystem services in natural land management is “not only ecologically more sustainable, and socio-culturally preferable, but frequently also economically more beneficial than converted systems.” To develop indicators for sustainable use, they reviewed the service, the ecological process or component, then the state indicator – how much the service is present – and the performance indicator – how much can the service be used/provided sustainably. From these they can link ecosystem management to these services. Mapping and spatial data like GIS is discussed as being used to identify land use changes, biodiversity, etc. These should be linked with participatory trade-off assessments, and made accessible to policy makers, stakeholders and the general public, through resources like the ARIES project and other resources.

Felipe-Lucia, M. R., Martin-Lopez, B., Lavorel, S., Berraquero-Diaz, L., Escalera-Reyes, J., & Comin, F. A. (2015). Ecosystem Services Flows: Why Stakeholders’ Power Relationships Matter. PLoS ONE, 10(7). Retrieved from https://doi.org/10.1371/journal.pone.0132232

The authors explore stakeholder power dynamics over ecosystem services and their effect on how ecosystem services flow and are benefitted or degraded. They found that land managers and recreationalists have the strongest power dynamics in stakeholder processes. Recognizing power differentials between stakeholders helps indicate a) key stakeholders & managers that provide access, b) the high impact stakeholders that prevent function of ecosystem services. Collaborative planning processes can be hindered by not taking power relationships into account.

Lawrence, A., & Stewart, A. (2011). Sustainable Forestry Decisions: On the Interface Between Technology and Participation. Mathematical and Computational Forestry and Natural-Resource Sciences, 42-52.

A review of various tools available to forest managers that support participatory decision-making or generate the forest management alternatives. GIS visualization tools is suggested to be better used as part of participatory decision-making. Visualizations are valuable for increasing engagement, but can be potentially misrepresentative.

Lei, S., Iles, A., & Kelly, M. (2015). Characterizing the Networks of Digital Information that Support Collaborative Adaptive Forest Management in Sierra Nevada Forests. Environmental Management, 94-109.

Lei et al used the Sierra Nevada Adaptive Management Program (2005-2015) as a framework through which to analyze digital information networks that support collaborative adaptive forest management. Using citation analysis, web analytics, and content analysis, the authors were able to draw out information on how knowledge was produced, transported, used, and monitored. LiDAR analysis was used during the project, and that research was some of the more highly cited papers. Author recommendations emphasized 1) utilization of multiple information channels with different time scales, 2) efficient design of information architecture for web tools and channels, 3) make information public early and share information often, 4) identify knowledge brokers (knowledge disseminators); 5) create opportunities for participation and social networking; 6) monitor information. This can help inform knowledge dissemination with digital tools, such as a GIS web tool or other mapping resources.

Lewis, J. L., & Sheppard, S. R. (2006). Culture and communication: Can landscape visualization improve forest management consultation with indigenous communities? Landscape and Urban Planning, 77, 291-313.

In order to increase indigenous community member engagement with collaborative forest management processes, Lewis & Sheppard compared 2D simple forest management maps to 3D rendered visualizations. This small study showed that older tribal members appeared to relate to and understand the visualizations much more than the 2D maps, though the maps were still considered important for additional context. This suggests that visualizations may help engage individuals who have less map reading experience, provide access and opportunity for learning, and increase engagement with the decision-making process.

Martins, H., & Borges, J. G. (2007). Addressing collaborative planning methods and tools in forest management. Forest Ecology and Management, 248, 107-118.

A review of different methodologies and tools that could be used to develop the framework for forest management. Defines these methodologies and tools within the context of a 3 step planning process: 1) problem identification; 2) problem modelling; and 3) problem solving. Maps and visualization is discussed as being an important part of the initial stages of Group Decision Support systems.

Mladenoff, D. J. (2004). LANDIS and forest landscape models. Ecological Modeling, 7-19.

This paper provides information on how the LANDIS model was developed, including the history of forest management, disturbance, and landscape modeling. This raster model is a well-developed general model that has been modified for use in many different countries and forest types. LANDIS II integrates biomass as well.

NCSU Geoforall lab. (2018, 3 16). Tangible Landscape – Applications. Retrieved from Tangible Landscape: http://tangible-landscape.github.io/index.html

The Tangible Landscape website, which has publications, informational videos and demonstrations, and information on how to build your own tangible landscape.

Shepperd, S. R., & Meitner, M. (2005). Using multi-criteria analysis and visualization for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 171-187.

Participatory sustainable forest management processes have been utilized on a limited basis, making exploration of different techniques and methodologies important. This multi-criteria approach, called a public MCA, assessed the use of GIS based forest modeling and realistic visualizations. This study also used individual stakeholder groups to determine priorities, which could be a good model for a highly divisive area. The visualizations were popular with stakeholders, but their effectiveness was to be determined, but could be more important in later study phases.

Sturtevant, B. R., Scheller, R. M., Miranda, B. R., Shinneman, D., & Syphard, A. (2009). Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II. Ecological Modelling, 3380-3393.

This paper discusses dynamic fire and fuel extensions that were developed for LANDIS II – an update of LANDIS that increased flexibility and variability over time. LANDIS II introduced the Dynamic Fuel System and the Dynamic Biomass Fuel System to assign fuel types to forested cells. The Dynamic Fire System extension models fire frequency, fire size, fire weather, fire spread, and fire effects. The paper includes two test cases, including one in the Sierra Nevada range. Generally this fire extension provides detailed information, but may be substituted with less complex Forest Landscape Simulation Models if fire behavior is not a key part of the study.

The LANDIS II Foundation. (2019, 3 15). The LANDIS-II Landscape Change Model. Retrieved from LANDIS II: http://www.landis-ii.org/home

The website for the LANDIS II landscape model. Includes information on updates, training events, extensions, and publications that have used the model.

Tonini, F., Shoemaker, D., Petrasova, A., Harmon, B., Petras, V., Cobb, R. C., . . . Meentemeyer, R. K. (2017). Tangible geospatial modeling for collaborative solutions to invasive species management. Environmental Modelling and Software, 176-188.

Tangible Landscape is an open source interactive tool, that uses a combination of physical modeling infrastructure and real time GIS modeling to help direct management decisions. This particular study reviewed using the model on a demonstration basis for consensus-building, as an example of how it could be used for collaborative forest management.

Van Berkel, D. B., Tabrizian, P., Dorning, M. A., Smart, L., Newcomb, D., Mehaffey, M., . . . Meentemeyer, R. K. (2018). Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR. Ecosystem Services, 326-335.

To quantify cultural ecosystem services, Van Berkel et al used LiDAR data and landscape photographs from social media to create a viewshed of cultural resources. Those resources were then categorized for the various services. This method is unique, and can highlight the importance of certain attractions, but can potentially misrepresent areas, or accidentally prioritize one use type over another.

References

Balram, S., & Dragicevic, S. (2006). Modeling Collaborative GIS processes Using Soft Systems Theory, UML, and Object Oriented Design. Transactions in GIS, 10(2), 199-218.

Collins, B. M., Stephens, S. L., Moghaddas, J. J., & Battles, J. (2010). Challenges and Approaches in Planning Fuel Treatments across Fire-Excluded Forested Landscapes. Journal of Forestry, 24-31.

Coppes, J., & Braunisch, V. (2013). Managing visitors in nature areas: where do they leave trails? A spatial model. Wildlife Biology, 19(1), 1-11.

Felipe-Lucia, M. R., Martin-Lopez, B., Lavorel, S., Berraquero-Diaz, L., Escalera-Reyes, J., & Comin, F. A. (2015). Ecosystem Services Flows: Why Stakeholders’ Power Relationships Matter. PLoS ONE, 10(7). Retrieved from https://doi.org/10.1371/journal.pone.0132232

Lawrence, A., & Stewart, A. (2011). Sustainable Forestry Decisions: On the Interface Between Technology and Participation. Mathmatical and Computational Forestry and Natural-Resource Sciences, 42-52.

Lei, S., Iles, A., & Kelly, M. (2015). Characterizing the Networks of Digital Information that Support Collaborative Adaptive Forest Management in Sierra Nevada Forests. Environmental Management, 94-109.

Lewis, J. L., & Sheppard, S. R. (2006). Culture and communication: Can landscape visualization improve forest management consultation with indigenous communities? Landscape and Urban Planning, 77, 291-313.

Martins, H., & Borges, J. G. (2007). Addressing collaborative planning methods and tools in forest management. Forest Ecology and Management, 248, 107-118.

Mladenoff, D. J. (2004). LANDIS and forest landscape models. Ecological Modeling, 7-19.

NCSU Geoforall lab. (2018, 3 16). Tangible Landscape – Applications. Retrieved from Tangible Landscape: http://tangible-landscape.github.io/index.html

Shepperd, S. R., & Meitner, M. (2005). Using multi-criteria analysis and visualization for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 171-187.

The LANDIS II Foundation. (2019, 3 15). The LANDIS-II Landscape Change Model. Retrieved from LANDIS II: http://www.landis-ii.org/home

Use of GIS mapping and visualizations in Collaborative Forest Landscape Management Processes

Annotated Bibliography

References

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