Steen-Adams, M. M., J. Abrams, H. Huber-Stearns, C. Moseley and C. Bone. 2020. Local-level emergence of network governance within the US Forest Service: A case study of mountain pine beetle outbreak from Colorado, USA. Forest Policy and Economics, 118, 102204.2019
Bone, C. and M. Nelson. 2019. The Impact of Multi-Year Temperature Averages on Modelling Bark Beetle Winter Survival. Forests, 10(10): 866.
Altaweel, M., C. Bone, and J. Abrams. 2019. A content analysis and topic modelling approach for analyzing responses to ecological disturbances. Ecological Informatics 51: 82-95.
Huber-Stearns, H., C. Moseley, C. Bone, N. Mosurinjohnan K.M. Lyon. 2019 An initial look at contracted wildfire response capacity in the American West. Journal of Forestry 117 (1), 1-8
Nelson, M., M. Altaweel, J. Murphy and C. Bone. 2018. Cyclic epidemics, population crashes, and irregular eruptions in simulated populations of the Mountain Pine Beetle, Dendroctonus ponderosae. Ecological Complexity, 36:218-229.
Bone, C. 2018. Agent-based Modeling. The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2018 Edition), John P. Wilson (ed.). DOI:10.22224/gistbok/2018.2.7.
Abrams, J., H. Huber-Sterns, C. Bone, C. Grummon and C. Moseley. 2017. Adaptation to a landscape-scale mountain pine beetle epidemic in the era of networked governance: the enduring importance of bureaucratic institutions. Ecology and Society, 22(4).
Havasova, M. and C. Bone. 2017. Simulating bark beetle population dynamics in response to windthrow events. Ecological Complexity, 32: 21-30.
Lyon, K.M., H. Huber-Sterns, C. Moseley, C. Bone and N. Mosurinjohn. 2017. Sharing contracted resources for fire suppression: engine dispatch in the Northwestern United States. International Journal of Wildland Fire 26(2): 113-121.
Nelson, M., M. Ciochinna and C. Bone. 2016. Assessing spatiotemporal relationships between wildfire and mountain pine beetle disturbances across multiple time lag. Ecospheres 7(10): e01482.
Bone, C. 2016. A complex adaptive theoretical modeling approach for sustainable forestry in China. Technological Forecasting and Environmental Change. 112: 138-144.
Morris, E. and C. Bone. 2016. Identifying Spatial Data Availability and Spatial Data Needs for Chagas Disease Mitigation in South America. Spatial and Spatio-temporal Epidemiology 17:45-58.
Bone, C., C. Moseley, K. Vinyeta and R.B. Bixler. 2016. Employing resilience in the United States Forest Service. Land Use Policy 52: 430-438.
Kenbeek, S., C. Bone and C. Moseley. 2016. A network modeling approach to policy implementation in natural resource management agencies. Computers, Environment and Urban Systems 57:155-177.
Nelson, M. and C. Bone. 2015. Effectiveness of dynamic quarantines against pathogen spread in models of the horticultural trade network. Ecological Complexity 24:14-28.
O'Sullivan, D., T. Evans, S. Manson, S. Metcalf, A. Ligmann-Zielinska, and C. Bone. 2015. Strategic directions for agent-based modeling: avoiding the YAAWN syndrome. Journal of Land Use Science 11: 1-11.
Bone, C. and M. Altaweel. 2014. Modeling micro-scale ecological processes and emergent patterns of mountain pine beetle epidemics. Ecological Modelling, 289: 45-58.
Bone, C., A. Ager, K. Buzel and L. Tierney. 2014. A geospatial search engine for discovering multi-format geospatial data across the web. International Journal of Digital Earth. DOI:10.1080/17538947.2014.966164.
Bone, C., B. Johnson, M. Nielsen-Pincus, E. Sproles, and J. Bolte. 2014. A temporal variant-invariant validation approach for agent-based models of landscape dynamics. Transactions in GIS, 18: 161-182.
Bone, C., J. White, M. Wulder, C. Robertson, and T. Nelson. 2013. The impact of forest pattern on host selection by mountain pine beetle at different beetle population densities. Forests, 4(2) 279-295.
Bone, C., M. Wulder, J. White, C. Robertson, and T. Nelson. 2013. A GIS-based risk rating of forest insect outbreaks using aerial overview surveys and the local Moran’s I statistic. Applied Geography, 40: 161-170.
Altaweel, M. and C. Bone. 2012. Applying content analysis for investigating the reporting of water issues. Computers, Environment and Urban Systems, 8: 733-761.
Bone, C., S. Dragićević and R. White. 2011. Modeling-in-the-middle: bridging the gap between agent-based modeling and multi-objective decision making for land use change. International Journal of Geographical Information Science, 25:717-737.
Bone, C., L. Alessa, A. Kliskey and M. Altaweel. 2011. Assessing the impacts of local knowledge and technology on climate change vulnerability in remote communities. International Journal of Environmental Research and Public Health, 8: 733-761.
Alessa, L, M. Altaweel, A. Kliskey, C. Bone, W. Schnabel, and K. Stevenson. 2011. Alaska’s freshwater resources: issues affecting local and international interests. Journal of the American Water Resource Association 47: 143-157.
Bone, C., L. Alessa, M. Altaweel and A. Kliskey. 2010. The influence of statistical methods and reference dates for estimating temperature trends in Alaska. Journal of Geophysical Research 115 : doi : doi:10.1029/2010JD014289.
Bone, C. and S. Dragićević. 2010. Incorporating spatio-temporal knowledge in an intelligent agent model for natural resource management. Landscape and Urban Planning 96: 123-133.
Bone, C. and S. Dragićević. 201b. Simulation and validation of a reinforcement learning agent-based model for multi-stakeholder forest management. Computers, Environment and Urban Systems, 34: 162-174.
Altaweel, M., Alessa, L., Kliskey, A. and C. Bone. 2010. Monitoring land use: capturing change through an information fusion approach. Sustainability, 2(5): 1182-1203.
Altaweel, M., L. Alessa, A. Kliskey, and C. Bone. 2010. A framework to structure agent-based modeling data for social-ecological systems. Structure and Dynamics: eJournal of Anthropological and Related Sciences, 4(1).
Bone, C. and S. Dragićević. 2009. GIS and intelligent agents for natural resource allocation: A reinforcement learning approach. Transactions in GIS, 13: 253-272.
Bone, C. and S. Dragićević. 2009. Evaluating spatio-temporal complexities of forest management: An integrated agent-based modeling and GIS approach. Environmental Modeling and Assessment, 14: 481-496.
Bone, C. and S. Dragićević. 2009. Defining transition rules with reinforcement learning for modeling land cover change. Simulation, 85(5): 291-305.
Bone, C., Dragićević, S., & Roberts, A. 2007. Evaluating forest management practices using a GIS-based cellular automata modeling approach with multispectral imagery. Environmental Modeling & Assessment, 12(2): 105-118.
Bone, C., S. Dragićević and A. Roberts. 2006. A fuzzy-constrained cellular automata model of forest insect infestations. Ecological Modelling, 192(1-2): 107-125.
Bone, C., Dragićević, S., and Roberts, A. 2005. Integrating high resolution RS, GIS and fuzzy set theory for identifying susceptibility areas of forest insect infestations. International Journal of Remote Sensing, 26(10): 4809-4828.