Analyzing crop change scenario with the SmartScape™ spatial decision support system

Agricultural land use is increasingly changing due to different anthropogenic activities. A combination of economic, socio-political, and cultural factors exerts a direct impact on agricultural changes. This study aims to illustrate how stakeholders and policymakers can take advantage of a web-based spatial decision support system (SDSS), namely SmartScape™ to either test existing crop change policies or produce effective crop change decisions using tradeoff analysis. We addressed the consequences of two common crop change scenarios for Dane county in Wisconsin, United States, (a) replacing perennial energy crops with annual energy crops and (b) replacing annual energy crops with perennial energy crops. The results suggested that converting areas under grass and alfalfa production that were located on high quality soil and flat slope to corn promoted a net-income and availability of gross biofuel. Additionally, the model outcome proposed that converting areas under corn and soy production that were located on high slope to grass promoted net-energy, phosphorus loading, soil loss, soil carbon sequestration, nitrous oxide emission, grassland bird habitat, pollinator abundance, and biocontrol. Therefore, SmartScape™ can assist strategic crop change policy by comparing the tradeoff among ecosystem services to ensure that crop change policies have outcomes that are agreeable to a diversity of policymakers.

[1]  Jimmy R. Williams,et al.  An integrative modeling framework to evaluate the productivity and sustainability of biofuel crop production systems , 2010 .

[2]  Amin Tayyebi,et al.  Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster–vector routines with remote sensing and GIS , 2014, Int. J. Geogr. Inf. Sci..

[3]  Mahmoud Reza Delavar,et al.  COMBINING MULTI CRITERIA DECISION MAKING AND DEMPSTER SHAFER THEORY FOR LANDFILL SITE SELECTION , 2010 .

[4]  Timothy D. Meehan,et al.  Ecosystem-Service Tradeoffs Associated with Switching from Annual to Perennial Energy Crops in Riparian Zones of the US Midwest , 2013, PloS one.

[5]  B. Pijanowski,et al.  The effects of China's cultivated land balance program on potential land productivity at a national scale , 2014 .

[6]  Ron Janssen,et al.  Why are spatial decision support systems not used? Some experiences from the Netherlands , 2003, Comput. Environ. Urban Syst..

[7]  A. McMichael,et al.  Ecosystems and Human well-being , 2003 .

[8]  Mohammad Javad Yazdanpanah,et al.  URBAN EXPANSION SIMULATION USING GEOSPATIAL INFORMATION SYSTEM AND ARTIFICIAL NEURAL NETWORKS , 2009 .

[9]  G. Taylor,et al.  Identifying potential environmental impacts of large-scale deployment of dedicated bioenergy crops in the UK , 2009 .

[10]  S. Polasky,et al.  Environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[11]  B. Pijanowski,et al.  Urban expansion and its consumption of high-quality farmland in Beijing, China , 2015 .

[12]  Bryan C. Pijanowski,et al.  Evidence for increased monoculture cropping in the Central United States , 2013 .

[13]  S. Carpenter,et al.  Global Consequences of Land Use , 2005, Science.

[14]  Katrin Vogel,et al.  Assessing biodiversity on the farm scale as basis for ecosystem service payments. , 2012, Journal of environmental management.

[15]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[16]  Bryan C. Pijanowski,et al.  Two rule-based Urban Growth Boundary Models applied to the Tehran Metropolitan Area, Iran , 2011 .

[17]  Bryan C. Pijanowski,et al.  Comparing three global parametric and local non-parametric models to simulate land use change in diverse areas of the world , 2014, Environ. Model. Softw..

[18]  Mark A. Nearing,et al.  Error Assessment in the Universal Soil Loss Equation , 1993 .

[19]  E. Vaz,et al.  The future of landscapes and habitats: The regional science contribution to the understanding of geographical space , 2016 .

[20]  E. Bennett,et al.  Interactions Among Ecosystem Services Across Land Uses in a Floodplain , 2014 .

[21]  Xiangzheng Deng,et al.  Impacts of land-use change on valued ecosystem service in rapidly urbanized North China Plain , 2015 .

[22]  W. Rossing,et al.  Exploring multi-scale trade-offs between nature conservation, agricultural profits and landscape quality—A methodology to support discussions on land-use perspectives , 2007 .

[23]  C. Fürst,et al.  Assessment of the effects of forest land use strategies on the provision of ecosystem services at regional scale. , 2013, Journal of environmental management.

[24]  J. Arnold,et al.  SWAT2000: current capabilities and research opportunities in applied watershed modelling , 2005 .

[25]  Randall A. Kramer,et al.  Valuing ecosystem services from wetlands restoration in the Mississippi Alluvial Valley , 2010 .

[26]  Susanne Frank,et al.  Cross-Sectoral Resource Management: How Forest Management Alternatives Affect the Provision of Biomass and Other Ecosystem Services , 2015 .

[27]  Andrew D. Jones,et al.  Supporting Online Material for: Ethanol Can Contribute To Energy and Environmental Goals , 2006 .

[28]  Nitin Khanna,et al.  Assessing uncertainty dimensions in land-use change models: using swap and multiplicative error models for injecting attribute and positional errors in spatial data , 2014 .

[29]  Bryan C. Pijanowski,et al.  Modeling multiple land use changes using ANN, CART and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[30]  Richard C. Lathrop,et al.  Phosphorus Loads to Surface Waters: A Simple Model to Account for Spatial Pattern of Land Use , 1996 .

[31]  S. Carpenter,et al.  Science for managing ecosystem services: Beyond the Millennium Ecosystem Assessment , 2009, Proceedings of the National Academy of Sciences.

[32]  M. Wimberly,et al.  Recent land use change in the Western Corn Belt threatens grasslands and wetlands , 2013, Proceedings of the National Academy of Sciences.

[33]  Stan Geertman,et al.  Potentials for Planning Support: A Planning-Conceptual Approach , 2006 .

[34]  James A. Larson,et al.  Estimating Regional Changes in Soil Carbon with High Spatial Resolution , 2008 .

[35]  Ralf Wieland,et al.  LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies. , 2013, Journal of environmental management.

[36]  B. Pekin.  Effect of Widespread Agricultural Chemical Use on Butterfly Diversity across Turkish Provinces , 2013, Conservation biology : the journal of the Society for Conservation Biology.

[37]  Jacinto F. Fabiosa,et al.  Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change , 2008, Science.

[38]  Brian S. McIntosh,et al.  Tools to think with? Towards understanding the use of computer-based support tools in policy relevant research , 2007, Environ. Model. Softw..

[39]  R. O'Neill,et al.  The value of the world's ecosystem services and natural capital , 1997, Nature.

[40]  Wallace E. Tyner,et al.  The US Ethanol and Biofuels Boom: Its Origins, Current Status, and Future Prospects , 2008 .

[41]  D. Landis,et al.  Pest-Suppression Potential of Midwestern Landscapes under Contrasting Bioenergy Scenarios , 2012, PloS one.

[42]  J. Waddington,et al.  Cutover peatlands: A persistent source of atmospheric CO2 , 2002 .

[43]  M. Jha,et al.  Implications of biofuel policy‐driven land cover change for rainfall erosivity and soil erosion in the United States , 2013 .

[44]  Bryan C. Pijanowski,et al.  A big data urban growth simulation at a national scale: Configuring the GIS and neural network based Land Transformation Model to run in a High Performance Computing (HPC) environment , 2014, Environ. Model. Softw..

[45]  N. Batjes,et al.  Modeling global annual N2O and NO emissions from fertilized fields , 2002 .

[46]  R. Isaacs,et al.  Landscape composition influences pollinators and pollination services in perennial biofuel plantings , 2014 .

[47]  Eric Vaz,et al.  Spatiotemporal simulation of urban growth patterns using agent-based modeling: The case of Tehran , 2013 .

[48]  Integrating agricultural pest biocontrol into forecasts of energy biomass production , 2014 .

[49]  Bryan C. Pijanowski,et al.  Land use legacies of the Ohio River Basin: Using a spatially explicit land use change model to assess past and future impacts on aquatic resources , 2015 .

[50]  Anthony J. Jakeman,et al.  A methodology for the design and development of integrated models for policy support , 2011, Environ. Model. Softw..