Skip to main content Accessibility help
×
Hostname: page-component-5c6d5d7d68-wpx84 Total loading time: 0 Render date: 2024-08-07T15:25:06.970Z Has data issue: false hasContentIssue false

7 - Limitations, Challenges, and Solutions to Integrating Carbon Dynamics with Land-Use Models

Published online by Cambridge University Press:  05 February 2013

Daniel G. Brown
Affiliation:
University of Michigan, Ann Arbor
Derek T. Robinson
Affiliation:
University of Waterloo, Ontario
Nancy H. F. French
Affiliation:
Michigan Technological University
Bradley C. Reed
Affiliation:
United States Geological Survey, California
Get access

Summary

Introduction

Research efforts have combined land-use and land-cover change (LUCC) and carbon (C) dynamics to estimate the flux and storage of C under different land-use and land-management regimes (e.g., see Chapters 10 and 11). Ultimately, this research arena seeks to understand the C sequestration implications of different land-use change processes or futures. However, despite the need for simulation tools to produce robust predictions of C dynamics under different land-use and land-cover scenarios, there are relatively few models that integrate LUCC and C cycle dynamics. To be clear, many publications document the C balance of specific land-cover scenarios; however, there is an important distinction between modeling land-use change endogenously (such that it changes dynamically as a result of the modeled processes) and incorporating an exogenous land-cover scenario (with a prespecified set of land-cover data) in a C model.

The integration of land-use and C-cycle modeling is necessary for several reasons, most notably for the development and implementation of climate change policy (see Chapter 8). National and international science communities have emphasized the need for integrating land-use and C dynamics (e.g., the International Geosphere-Biosphere Programme [IGBP], Global Land Project [GLP], International Human Dimensions Programme on Global Environmental Change [IHDP]; see Chapter 1); however, the C and LUCC modeling communities often operate as somewhat disparate fields of research. Development of international climate negotiations and treaties, such as the Kyoto Protocol and the United Nations Framework Convention on Climate Change Good Practice Guidance for Land Use, Land-Use Change, and Forestry (UNFCCC GPG-LULUCF), relies on current estimates of C pools and fluxes, as well as our expectations for how land-use change will influence C dynamics in the future.

Type
Chapter
Information
Land Use and the Carbon Cycle
Advances in Integrated Science, Management, and Policy
, pp. 178 - 208
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agarwal, C., Green, G.M., Grove, J.M., Evans, T.P., and Schweik, C.M. 2002. A review and assessment of land-use change models: Dynamics of space, time, and human choice. Gen. tech. rep. NE–297, U.S. Department of Agriculture.
Andersson, K.A., Evans, T.P., and Richards, K.R. 2008. National forest carbon inventories: Policy needs and assessment capacity. Climatic Change, 93:69–101.CrossRefGoogle Scholar
Baker, W.L. 1989. A review of models of landscape change. Landscape Ecology, 2(2):111–133.CrossRefGoogle Scholar
Bakker, M.M., and Veldkamp, A. 2008. Modelling land change: The issue of use and cover in wide-scale applications. Journal of Land Use Science, 3(4):203–213.CrossRefGoogle Scholar
Batty, M., Couclelis, H., and Eichen, M. 1997. Urban systems as cellular automata. Environment and Planning B: Planning and Design, 24:159–164.CrossRefGoogle Scholar
Bennet, D.A., and Tang, W. 2006. Modelling adaptive, spatially aware, and mobile agents: Elk migration in Yellowstone. International Journal of Geographical Information Science, 20(9):1039–1066.CrossRefGoogle Scholar
Berger, T. 2001. Agent-based spatial models applied to agriculture: A simulation tool for technology diffusion, resource use changes and policy analysis. Agricultural Economics, 25:245–31.CrossRefGoogle Scholar
Bondeau, A., Smith, P.C., Zaehle, S., Schaphoff, S., Lucht, W., Cramer, W., …Smith, B. 2007. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biology, 13:679–706.CrossRefGoogle Scholar
Borschchev, A., Karpov, Y., and Kharitonov, V. 2002. Distributed simulation of hybrid systems with AnyLogic and HLA. Future Generation Computer Systems, 18(6):829–839.CrossRefGoogle Scholar
Brown, D.G., and Robinson, D.T. 2006. Effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecology and Society, 11(1):46 [online]. URL: .CrossRefGoogle Scholar
Clarke, K.C. 2008. A decade of cellular urban modeling with SLEUTH: Unresolved issues and problems. In Planning support systems for cities and regions, ed. Brail, R.K.. Cambridge, MA: Lincoln Institute of Land Policy, pp. 47–60.Google Scholar
Comber, A.J. 2008. The separation of land cover from land use using data primitives. Journal of Land Use Science, 3(4):215–229.CrossRefGoogle Scholar
Coops, N.C., and Waring, R.H. 2001. The use of multiscale remote sensing imagery to derive regional estimates of forest growth capacity using 3-PGS. Remote Sensing of Environment, 75:324–334.CrossRefGoogle Scholar
Danielsen, F., Beukema, H., Burgess, N.D., Parish, F., Bruehl, C.A., Donald, P.F.,… Fitzherbert, E. 2008. Biofuel plantations on forested lands: Double jeopardy for biodiversity and climate. Conservation Biology, 23(2):348–358.CrossRefGoogle ScholarPubMed
Evans, T.P., Phanvilay, K., Fox, J., and Vogler, J. 2011. An agent-based model of agricultural innovation, land-cover change and household inequality: The transition from swidden cultivation to rubber plantations in Laos PDR. Journal of Land Use Science, 6(2–3):151–173.CrossRefGoogle Scholar
Filatova, T., van der Veen, A., and Parker, D.C. 2009. Land market interactions between heterogeneous agents in a heterogeneous landscape-tracing the macro-scale effects of individual trade-offs between environmental amenities and disamenities. Canadian Journal of Agricultural Economics, 57:431–459.CrossRefGoogle Scholar
Fragkias, M., and Geoghegan, J. 2010. Commercial and industrial land use change, job decentralization and growth controls: A spatially explicit analysis. Journal of Land Use Science, 5(1):45–66.CrossRefGoogle Scholar
Geist, H.J., and Lambin, E.F. 2001. What drives tropical deforestation? A meta-analysis of proximate and underlying causes of deforestation based on subnational case study evidence. Rep. series no. 4. LUCC International Project Office, Louvain-la-Neuve, Belgium.
Geist, H.J., and Lambin, E.F. 2002. Proximate causes and underlying driving forces of tropical deforestation. BioScience, 52(2):143–150.CrossRefGoogle Scholar
Guo, L.B., and Gifford, R.M. 2002. Soil carbon stocks and land use change: A meta analysis. Global Change Biology, 8:345–360.CrossRefGoogle Scholar
Guzmán-Álvarez, J.R., and Navarro-Cerrillo, R.M. 2008. Modelling potential abandonment and natural restoration of marginal olive groves in Andalusia (south of Spain). Journal of Land Use Science, 3(2):113–129.CrossRefGoogle Scholar
Hirsch, A.I., Little, W.S., Houghton, R.A., Scott, N.A., and White, J.D. 2004. The net carbon flux due to deforestation and forest re-growth in the Brazilian Amazon: Analysis using a process-based model. Global Change Biology, 10:908–924.CrossRefGoogle Scholar
Houghton, R.A. 2008. Carbon flux to the atmosphere from land-use changes: 1850–2005. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.Google Scholar
Huigen, M.G.A. 2004. First principles of the MameLuke multi-actor modelling framework for land use change, illustrated with a Philippine case study. Journal of Environmental Management, 72:5–21.CrossRefGoogle ScholarPubMed
Iovanna, R., and Vance, C. 2007. Modeling of continuous-time land cover change using satellite imagery: An application from North Carolina. Journal of Land Use Science, 2(3):147–166.CrossRefGoogle Scholar
Irwin, E.G., and Geoghegan, J. 2001. Theory, data, methods: Developing spatially explicit economic models of land-use change. Agriculture, Ecosystems, and Environment, 85:7–23.CrossRefGoogle Scholar
Janssen, M.A., and Ostrom, E. 2006. Empirically based, agent-based models. Ecology and Society, 11(2):37 [online]. URL: .CrossRefGoogle Scholar
Jantz, C.A., Goetz, S.J., Donato, D., and Claggett, P. 2010. Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model. Computers, Environment, and Urban Systems, 34(1):1–16.CrossRefGoogle Scholar
Jensen, N.H., and Veihe, T. 2009. Modelling the effect of land use and climate change on the water balance and the nitrate leaching in eastern Denmark. Journal of Land Use Science, 4(1):53–72.CrossRefGoogle Scholar
Klein Goldewijk, K. 2001. Estimating global land use change over the past 300 years: The HYDE database. Global Biogeochemical Cycles, 15:417–433.CrossRefGoogle Scholar
Lambin, E.F. 1997. Modelling and monitoring land-cover change processes in tropical regions. Progress in Physical Geography, 21(3):375–393.CrossRefGoogle Scholar
Liu, J., Dietz, T., Carpenter, S.R., Alberti, M., Folke, C., Moran, E.,…Taylor, W.W. 2007. Complexity of coupled human and natural systems. Science, 317(5844):1513–1516.CrossRefGoogle ScholarPubMed
Liu, J., Liu, S., Loveland, T.R., and Tieszen, L.L. 2008. Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics. Ecological Modelling, 219:361–372.CrossRefGoogle Scholar
Liu, J., Vogelmann, J.E., Zhu, Z., Key, C.H., Sleeter, B., Price, D.T.,…Jiang, H. 2011. Estimating California ecosystem carbon storage using process model and land cover disturbance data: 1951–2000. Ecological Modelling, 222:2333–2341.CrossRefGoogle Scholar
Luus, K.A., Robinson, D.T., and Deadman, P.J. 2011. Representing ecological processes in agent-based models of land use and cover change. Journal of Land Use Science, iFirst:1–24.
Lysenko, M., and D’Souza, R.M. 2008. A framework for megascale agent based model simulations on graphics processing units. Journal of Artificial Societies and Social Simulation, 11(4):10 [online]. URL: .Google Scholar
Matsushita, B., Xu, M., Chen, J., Kameyama, J., and Tamura, M. 2004. Estimation of regional net primary productivity (NPP) using a process-based ecosystem model: How important is the accuracy of climate data?Ecological Modelling, 178(3–4):371–388.CrossRefGoogle Scholar
Matthews, R., Gilbert, N., Roach, A., Polhill, J., and Gotts, N. 2007. Agent-based land-use models: A review of applications. Landscape Ecology, 22(10):1447–1459.CrossRefGoogle Scholar
McGarigal, K., Cushman, S.A., Neel, C.M., and Ene, E. 2002. FRAGSTATS: Spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetts, Amherst.
Miller, J.D., and Yool, S.R. 2002. Modeling fire in semi-desert grassland/oak woodland: The spatial implications. Ecological Modelling, 153(3):229–245.CrossRefGoogle Scholar
Monticino, M., Acevedo, M., Callicott, B., Cogdill, T., and Lindquist, C. 2006. Coupled human and natural systems: A multi-agent-based approach. Environmental Modelling and Software, 22:656–663.CrossRefGoogle Scholar
Murty, D., Kirschbaum, M.U.F., McMurtie, R.E., and McGilvray, H. 2002. Does conversion of forest to agricultural land change soil carbon and nitrogen? A review of the literature. Global Change Biology, 8:105–123.CrossRefGoogle Scholar
North, M.J., Howe, T.R., Collier, N.T., and Vos, J.R. 2007. A declarative model assembly infrastructure for verification and validation. In Advancing social simulation: The first world congress, ed. Takahashi, S., Sallach, D.L., and Rouchier, J.. Heidelberg: Springer, pp. 129–140.CrossRefGoogle Scholar
Ooba, M., Wang, Q., Murakami, S., and Kohata, K. 2010. Biogeochemical model (BGC-ES) and its basin-level application for evaluating ecosystem services under forest management practices. Ecological Modelling, 221(16):1979–1994.CrossRefGoogle Scholar
Parker, D.C., Berger, T., and Manson, S., eds. 2002. Agent-based models of land-use and land-cover change. Report and review of an international workshop. Irvine, California, October 4–7, 2001.
Pijanowski, B.C., Alexandridis, K.T., and Muller, D. 2006. Modelling urbanization patterns in two diverse regions of the world. Journal of Land Use Science, 1(2–4):83–108.CrossRefGoogle Scholar
Pontius, R.G., Cornell, J., and Hall, C. 2001. Modeling the spatial pattern of land-use change with GEOMOD2: Application and validation for Costa Rica. Agriculture, Ecosystems, and Environment, 85(1–3):191–203.CrossRefGoogle Scholar
Pontius, R.G., Huffaker, D., and Denman, K. 2004. Useful techniques of validation for spatially explicit land-change models. Ecological Modelling, 179(4):445–461.CrossRefGoogle Scholar
Post, W.M., and Mann, L.K. 1990. Changes in soil organic carbon and nitrogen as a result of cultivation. In Soils and greenhouse effect, ed. Bouwman, A.F.. New York: Wiley, pp. 401–406.Google Scholar
Potter, C., Klooster, S., Steinbach, M., Tan, P., Kumar, V., Shekhar, S., and Carvalhos, C.R. 2004. Understanding global teleconnections of climate to regional model estimates of Amazon ecosystem carbon fluxes. Global Change Biology, 10:693–703.CrossRefGoogle Scholar
Ramankutty, N., and Foley, J.A. 1999. Estimating historical changes in global land cover: Croplands from 1700 to 1992. Global Biogeochemical Cycles, 13:997–1027.CrossRefGoogle Scholar
Ray, D.K., and Pijanowski, B.C. 2010. A backcast land use change model to generate past land use maps: Application and validation at the Muskegon River watershed of Michigan, USA. Journal of Land Use Science, 5(1):1–29.CrossRefGoogle Scholar
Rindfuss, R.R., Walsh, S.J., Mishra, V., Fox, J., and Dolcemascolo, G.P. 2003. Linking household and remotely sensed data: Methodological and practical problems. In People and the environment: Approaches for linking household and community surveys to remote sensing and GIS, ed. Fox, J., Rindfuss, R. R., Walsh, S. J., and Mishra, V.. Boston: Kluwer Academic Publishers, pp. 1–29.Google Scholar
Robinson, D.T., Brown, D.G., and Currie, W.S. 2009. Modelling carbon storage in highly fragmented and human-dominated landscapes: Linking land-cover patterns and ecosystem models. Ecological Modelling, 220:1325–1338.CrossRefGoogle Scholar
Robinson, D.T., Brown, D.G., Parker, D.C., Schreinemachers, P., Janssen, M.A., Huigen, M., …Barnaud, C. 2007. Comparison of empirical methods for building agent-based models in land use science. Land Use Science, 2:31–55.CrossRefGoogle Scholar
Robinson, D.T., Murray-Rust, D., Rieser, V., Melicic, V., and Rounsevell, M. 2012. Modelling the impacts of land system dynamics on human well-being: Using an agent-based approach to cope with data limitations in Koper, Slovenia. Computers, Environment, and Urban Systems, 36(2):164–175.CrossRefGoogle Scholar
Robinson, D.T., Shipeng, S., Hutchins, M., Riolo, R.L., Brown, D.G., Parker, D.C., Currie, W.S., Filatova, T., and Kiger, S.. Effects of land markets and land management on ecosystem function: A framework for modelling exurban land-changes. Environmental Modelling and Software, .2012.06.016.
Rounsevell, M.D.A., Robinson, D.T., and Murray-Rust, D. 2012. From actors to agents in socio-ecological systems models. Philosophical Transactions of the Royal Society B, 367:259–269.CrossRefGoogle ScholarPubMed
Running, S.W. 1984. Microclimate control of forest productivity: Analysis by computer simulation of annual photosynthesis/transpiration balance in different environments. Agricultural and Forest Meteorology, 32:267–288.CrossRefGoogle Scholar
Running, S.W., and Coughlan, J.C. 1988. A general model of forest ecosystem processes for regional applications: 1. Hydrologic balance, canopy gas exchange and primary production processes. Ecological Modelling, 42:125–154.CrossRefGoogle Scholar
Running, S.W., and Hunt, R.E. 1993. Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models. In Scaling physiological processes: Leaf to globe, ed. Ehleringer, J.R. and Field, C.B.. Salt Lake City, UT: Academic Press, pp. 141–496.CrossRefGoogle Scholar
Running, S.W., Knight, D.H., and Fahey, T.J. 1983. Description and application of H2OTRANS: A stand level hydrologic model for western coniferous forests. In Analysis of ecological systems: State-of-the-art in ecological modelling, ed. Lauenroth, W.K., Skogerboe, G.V., and Flug, M.. Amsterdam: Elsevier, pp. 489–496.CrossRefGoogle Scholar
Running, S.W., Waring, R.H., and Rydell, R.A. 1975. Physiological control of water flux in conifers: A computer simulation model. Oecologia (Berlin), 18:1–16.CrossRefGoogle ScholarPubMed
Schweik, C., Evans, T., and Grove, J.M. 2005. Open source and open content: A framework for global collaboration in social-ecological research. Ecology and Society, 10(1):33 [online]. .CrossRefGoogle Scholar
Schweik, C., Grove, J.M., and Evans, T.P. 2004. The open-source paradigm and the production of scientific information: A future vision and implications for developing countries. In Open access and the public domain in digital data and information for science: Proceedings of an international symposium, ed. Esanu, J.M. and Uhlir, P.F.. Washington, DC: National Academies Press, pp. 103–109.Google Scholar
Sevcikova, H., Wang, L., Waddell, P., and Borning, A. In review. Agile modeling for urban and environmental systems: The open platform for urban simulation. Submitted to Environmental Modelling and Software.
Simmons, J. 2003. Cities in decline: The future of urban Canada. Toronto: Centre for the Study of Commercial Activity.Google Scholar
Sitch, S., Smith, B., Prentice, I.C., Arneth, A., Bondeau, A., Cramer, W., …Venesvsky, S. 2003. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biology, 9:161–185.CrossRefGoogle Scholar
Sohl, T.L., Sayler, K.L., Drummond, M.A., and Loveland, T.R. 2007. The FORE-SCE model: A practical approach for projecting land cover change using scenario-based modeling. Journal of Land Use Science, 2(2):103–126.CrossRefGoogle Scholar
Sun, S., and Manson, S.M. 2010. An agent-based model of housing search and intraurban migration in the twin cities of Minnesota. Session 7: Spatial agent-based models for socio-ecological systems. In Proceedings of the International Environmental Modelling and Software Society (iEMSs) 2010 International Congress on Environmental Modelling and Software, ed. Swayne, D.A., Yang, W., Voinov, A.A., Rizzoli, A., and Filatova, T., Fifth Biennial Meeting, Ottawa, Ontario, Canada. .Google Scholar
Tews, J., Esther, A., Milton, S.J., and Jeitsch, F. 2006. Linking a population model with an ecosystem model: Assessing the impact of land use and climate change on savanna shrub cover dynamics. Ecological Modelling, 195(3–4):219–228.CrossRefGoogle Scholar
Theobald, D.M. 2001. Land-use dynamics beyond the American urban fringe. The Geographical Review, 91(3):544–564.CrossRefGoogle Scholar
Trines, E., Hohne, N., Jung, M., Skutsch, M., Petsonk, A., Silva-Chavez, G.,…Schlamadinger, B. 2006. Climate change scientific assessment and policy analysis: Integrating agriculture, forestry and other land use in future climate regimes. Bilthoven, The Netherlands: Environmental Assessment Agency.Google Scholar
U.S. Department of Agriculture. 2009. Summary report: 2007 national resources inventory, Natural Resources Conservation Service, Washington, DC, and Center for Survey Statistics and Methodology, Iowa State University, Ames, Iowa. .Google Scholar
Veldkamp, A., and Fresco, L.O. 1996. CLUE: A conceptual model to study the conversion of land use and its effects. Ecological Modelling, 85:253–270.CrossRefGoogle Scholar
Verburg, P.H., Schot, P.P., Dijst, M.J., and Veldkamp, A. 2004. Land use change modelling: Current practice and research priorities. GeoJournal, 61:309–324.CrossRefGoogle Scholar
Waddell, P. 2002. UrbanSim: Modeling urban development for land use, transportation and environmental planning. Journal of the American Planning Association, 68(3):297–314.CrossRefGoogle Scholar
Waldrop, M.M. 1990. Asking for the moon. Science, 247:637–638.CrossRefGoogle Scholar
Walsh, S.J., Entwisle, B., Rindfuss, R.R., and Page, P.H. 2006. Spatial simulation modelling of land use/land cover change scenarios in northeastern Thailand: A cellular automata approach. Journal of Land Use Science, 1(1):5–28.CrossRefGoogle Scholar
Wilensky, U. 1999. NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, Illinois. .Google Scholar
Xu, Z., Ward, S., Chen, C., Blumfield, T., Prasolova, N., and Liu, J. 2008. Soil carbon and nutrient pools, microbial properties and gross nitrogen transformations in adjacent natural forest and hoop pine plantations of subtropical Australia. Journal of Soils and Sediments, 8(2):99–105.CrossRefGoogle Scholar
Xu, X., Gao, Q., Liu, Y., Wang, J., and Zhang, Y. 2009. Coupling a land use model and an ecosystem model for a crop-pasture zone. Ecological Modelling, 220:2503–2511.CrossRefGoogle Scholar
Yadav, V., Del Grosso, S.J., Parton, W.J., and Malanson, G.P. 2008. Adding ecosystem function to agent-based land use models. Land Use Science, 3:27–40.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×