Agro-ecoregionalization of Iowa using multivariate geographical clustering

Agriculture, Ecosystems and Environment

Volumn 123, Issue 1-3, 2008, Pages 161-174

  Williams, Carol L ^a   Hargrove, William W ^b   Liebman, Matt ^a   James, David E ^c  

^a IOWA STATE UNIVERSITY   (United States)

^b USDA FOREST SERVICE   (United States)

^c USDA ARS National Laboratory for Agriculture and the Environment   (United States)

Author keywords

Agroecopause; Agroecozone; MapCurves; Multivariate geographic clustering

Indexed keywords

AGRICULTURAL ECONOMICS; CLUSTER ANALYSIS; DATA SET; ECOREGION; ENVIRONMENTAL FACTOR; ENVIRONMENTAL IMPACT; LAND USE; MAP; MULTIVARIATE ANALYSIS;

IOWA; NORTH AMERICA; UNITED STATES;

EID: 35348966955     PISSN: 01678809     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agee.2007.06.006     Document Type: Article

References (75)

1. Batchelor W.D., Basso B., and Paz J.O. Examples of strategies to analyze spatial and temporal yield variability using crop models. Eur. J. Agron. 18 (2002) 141-158
2. Battelle, 2004. Iowa's bioscience pathway for development: summary and technical reports. In: Battelle Technology Partnership Practice. Battelle Memorial Institute, Columbus, OH.
3. Berdahl J.D., Frank A.B., Krupinsky J.M., Carr P.M., Hanson J.D., and Johnson H.A. Biomass yield, phenology, and survival of diverse switchgrass cultivars and experimental strains in western North Dakota. Agron. J. 97 (2005) 549-555
4. Bernert J.A., Eilers J.M., Sullivan T.J., Freemark K.E., and Ribic C. A quantitative method for delineating regions: an example for the Western Corn Belt Plains ecoregion of the USA. Environ. Mange. 21 (1997) 4005-4420
5. Boe A. Genetic and environmental effects on seed weight and seed yield in switchgrass. Crop Sci. 43 (2003) 63-67
6. Booth T.H. Predicting plant growth: Where will it grow? How well will it grow?. Proceedings of the 3rd International Conference/Workshop on Integrating GIS and Environmental Modelling, Santa Fe, New Mexico. Nat'l Ctr. for Geog. Info. and Analys., Santa Barbara (1996). http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/booth_trevor/booth.html http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/booth_trevor/booth.html
7. Bunce R.G.H., Barr C.J., Clark R.T., Howard D.C., and Lane A.M.J. Land classification for strategic ecological survey. J. Environ. Manage. 47 (1996) 37-60
8. Caldiz D.O., Gaspari F.J., Haverkort A.J., and Struik P.C. Agro-ecological zoning and potential yield of single or double cropping of potato in Argentina. Agric. For. Meteorol. 109 (2001) 311-320
9. Casler M.D. Ecotypic variation among switchgrass populations for the northern USA. Crop Sci. 45 (2005) 388-398
10. Casler M.D., and Boe A.R. Cultivar × environment interactions in switchgrass. Crop Sci. 43 (2003) 2226-2233
11. Cassida K.A., Muir J.P., Hussey M.A., Read J.C., Venuto B.C., and Ocumpaugh W.R. Biomass yield and stand characteristics of switchgrass in south central U.S. environments. Crop Sci. 45 (2005) 673-681
12. CIRAS, 2002. Biobased Products and Bioenergy Vision and Roadmap for Iowa. Center for Industrial Research and Service, Iowa State University, Ames, IA.
13. Collins, F.C. Jr., Bolstad, D.V., 1999. A comparison of spatial interpolation techniques in temperature estimation. In: Proceedings of the 3rd International Conference on Integrating GIS and Environmental Modelling. Santa Fe, NM. Available at: http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/collins_fred/collins.html.
14. Corbett J.D. The changing face of agroecosystem characterization: models and spatial data, the basis for robust agroecosystem characterization. Proceedings of the 3rd International Conference on Integrating GIS and Environmental Modelling. Santa Fe, NM (1996). http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/corbett_john/corbett.html http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/corbett_john/corbett.html
15. DeWit A.J.W., Boogaard H.L., and van Diepen C.A. Spatial resolution of precipitation and radiation: the effect on regional crop yield forecasts. Agric. For. Meteorol. 135 (2005) 156-168
16. ESRI, 2005. ArcGIS 9.1. Redlands. Environmental Systems Research Institute, California, USA.
17. Fan S., Hazell P., and Haque T. Targeting public investments by agroecological zone to achieve growth and poverty alleviation goals in rural India. Food Policy 25 (2000) 411-428
18. FAO. Agro-Ecological Zoning: Guidelines (1996), Food and Agricultural Organization of the United Nations, Rome
19. Ghaffari A., Cook H.F., and Lee H.C. Integrating climate, soil and crop information: a land suitability study using GIS. Proceedings of the 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and Research Needs. Banff, Alberta, Canada, 2-8 September (2000). http://www.colorado.edu/research/cires/banff/pubpapers/129/ http://www.colorado.edu/research/cires/banff/pubpapers/129/
20. Hansen J.W., and Jones J.W. Scaling-up crop models for climate variability applications. Agric. Syst. 65 (2000) 43-72
21. Hargrove, W.W., Hoffman, F.M., 1999. Using multivariate clustering to characterize ecoregion borders. Available at: http://research.esd.ornl.gov/∼hnw/pubs.html.
22. Hargrove W.W., and Hoffman F.M. Potential of multivariate quantitative methods for delineation and visualization of ecoregions. Environ. Manage. 34 1 (2004) S39-S60
23. Hargrove W.W., Hoffman F.M., and Hessburg P.F. MapCurves: a quantitative method for comparing categorical maps. J. Geogr. Syst. 8 (2006) 187-208
24. Heaton E., Voigt T., and Long S.P. A quantitative review comparing the yields of two candidate C4 perennial biomass crops in relation to nitrogen, temperature and water. Biomass Bioenergy 27 (2004) 21-30
25. HPRCC, 2005. High Plains Regional Climate Center. Available at: http://www.hprcc.unl.edu.
26. IDALS, 2004. Iowa Agricultural Statistics. Iowa Department of Agriculture and Land Stewardship, http://www.agriculture.state.ia.us/quickFacts2.htm.
27. IEM, 2005. Iowa Environmental Mesonet. Iowa State University, Department of Agronomy. Ames, Iowa, USA. http://mesonet.agron.iastate.edu/index.phtml.
28. ISPAID, 2004. Iowa Soil Properties And Interpretations Database Manual, Version 7.0. Iowa State University, Iowa Agriculture and Home Economics Experiment Station, University Extension Service.
29. ISU Bioeconomy Initiative, 2003. Annual Report for FY 2002-03: Progress and Achievements, Challenges and Plants for Optimization of Success. Office of Biorenewables Programs, Iowa State University, Ames, Iowa.
30. Jagtap S.S., and Jones J.W. Adaptation and evaluation of the CROPGRO-soybean model to predict regional yield and production. Agric. Ecosyst. Environ. 93 (2002) 73-85
31. Kravchenko A.N., and Bullock D.G. Correlation of corn and soybean grain yield with topography and soil properties. Agron. J. 92 (2000) 75-83
32. Kupfer J.A., and Franklin S.B. Evaluation of an ecological land type classification system, Natchez Trace State Forest, western Tennessee, USA. Landscape Urban Plan. 49 (2000) 179-190
33. Leathwick J.R., Overton J.McC., and McLeod M. An environmental domain classification of New Zealand and its use as a tool for biodiversity management. Conserv. Biol. 17 (2003) 1612-1623
34. Lee D.K., and Boe A. Biomass production of switchgrass in central South Dakota. Crop Sci. 45 (2005) 2583-2590
35. Lemus R., Brummer E.C., Moore K.J., Molstad N.E., Burras C.L., and Barker M.F. Biomass yield and quality of 20 switchgrass populations in southern Iowa, USA. Biomass Bioenergy 23 (2002) 433-442
36. Liu M., and Samal A. A fuzzy clustering approach to delineate agroecozones. Ecol. Model. 149 (2002) 215-228
37. Loomis R.S., and Connor D.J. Crop Ecology: Productivity and Management in Agricultural Systems (1992), Cambridge University Press, Cambridge, MA
38. Lugo A.E., Brown S.L., Dodson R., Smith T.S., and Shugart H.H. The Holdridge life zones of the conterminous United States in relation to ecosystem mapping. J. Biogeogr. 26 (1999) 1025-1038
39. MacEachren A.M., and Davidson J.V. Sampling and isometric mapping of continuous surfaces. Am. Cartographer 14 (1987) 299-320
40. McDonald R., McKnight M., Weiss D., Selig E., O'Connor M., Violin C., and Moody A. Species compositional similarity and ecoregions: do ecoregion boundaries represent zones of high species turnover?. Biol. Conserv. 126 (2005) 24-40
41. MCC, 2005. Missouri Climate Summary. Missouri State Climatologist. Missouri Climate Center. 302 ABNR, Columbia, MO 65211.
42. McMahon G., Gregonis S.M., Waltman S.W., Omernik J.M., Thorson T.D., Freeouf J.A., Rorick A.H., and Keys J.E. Developing a spatial framework of common ecological regions for the conterminous United States. Environ. Manage. 28 (2001) 293-316
43. Metzger M.J., Bunce R.G.H., Jongman R.H.G., Mucher C.A., and Watkins J.W. A climatic stratification of the environment of Europe. Global Ecol. Biogeogr. 14 (2005) 549-563
44. MRCC, 2005. Illinois Climate Summaries. Midwestern Regional Climate Center. Available at: http://mcc.sws.uiuc.edu.
45. Moser D., Zechmeiser H.G., Plutzar C., Sauberer N., Wrbka T., and Grabherr G. Landscape patch shape complexity as an effective measure for plant species richness in rural landscapes. Landscape Ecol. 17 (2002) 657-669
46. Munier B., Birr-Pedersen K., and Schou J.S. Combined ecological and economic modelling in agricultural land use scenarios. Ecol. Model. 174 (2004) 5-18
47. NASS, 2005. Agricultural Statistics Database. United States Department of Agriculture, National Agricultural Statistics Service. Available at: http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.asp.
48. Nix, H.A., 1981. Simplified simulation models based on specified minimum data sets: the CROPEVAL concept. In: Berg, A. (Ed.), Application of Remote Sensing to Agricultural Production Forecasting. Commission of the European Communities, Directorate General Information Market & Innovation, Rotterdam. Available at: http://cres.anu.edu.au/outputs/growest.php.
49. NRCS, 1999. Soil Taxonomy, a Basic System of Soil Classification for Making and Interpreting Soil Surveys, 2nd ed. United States Department of Agriculture, Natural Resource Conservation Service.
50. NRCS, 2002. Major Land Resource Area (MLRA) Boundaries for the Conterminous United States. United States Department of Agriculture, Natural Resource Conservation Service. Available at: http://www.nrcs.usda.gov/TECHNICAL/land/aboutmaps/us48mlra.html.
51. Openshaw S. A geographical solution to scale and aggregation problems in region-building, partitioning and spatial modeling. Trans. Inst. Br. Geogr. 2 (1977) 459-472
52. Pariyar, M.P., Singh, G., 1994. GIS-based model for agro-ecological zoning: a case study of Chitwan District, Nepal. In: Proceedings of the 15th Asian Conference on Remote Sensing. Bangalore, India, 17-23 November. At: www.gisdevelopment.net/aars/acrs/1994/ts1/ts1004pf.htm.
53. Patel, N.R., 2004. Remote sensing and GIS application in agro-ecozoning. In: Sivakumar, M.V.K, Roy, P.S., Harmsen, K., Saha, S.K. (Eds.), Proceedings of the Training Workshop. Dehra Dun, India, 7-11 July, pp. 213-233 (World Meteorology Organization, Geneva, Switzerland).
54. Prentice I.C., Cramer W., Harrison S.P., Leemans R., Monserud R.A., and Solomon A.M. A global biome model based on plant physiology and dominance, soil properties and climate. J. Biogeogr. 19 (1992) 117-134
55. Prior J.C. Landforms of Iowa (1991), University of Iowa Press, Iowa City
56. Pullar, D., Low Choy, S., Rochester, W., 2005. Ecoregion classification using a Bayesian approach and model-based clustering. In: Zerger, A. Argent, R.M. (Eds.), MODSIM 2005 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand. Available at: http://www.iemss.org/iemss2004/pdf/landscape/pullecor.pdf.
57. Sanderson M.A., Reed R.L., McLaughlin S.B., Wullschleger S.D., Conger B.V., Parrish D.J., Wolf D.D., Taliaferro C., Hopkins A.A., Ocumpaugh W.R., Hussey M.A., Read J.C., and Tischler C.R. Switchgrass as a sustainable bioenergy crop. Bioresource Technol. 56 (1999) 83-93
58. Santelmann M., Freemark K., Sifneos J., and White D. Assessing effects of alternative agricultural practices on wildlife habitat in Iowa, USA. Agric. Ecosys. Environ. 113 (2006) 243-253
59. SAS, 2001. Statistical Analysis Software. SAS Institute Inc., Cary, North Carolina, USA.
60. Strahler A.N., and Strahler A.H. Elements of Physical Geography (1984), John Wiley & Sons, New York
61. Swinton, S.M., Quiroz, R.A., Paredes, S., Reinoso, J.R., Valdiva, R., 2001. Using farm data to validate agroecological zones in the Lake Titicaca basin, Peru. In: Proceedings of the 3rd International Symposium on Systems Approaches for Agricultural Development. http://www.cipotato.org/training/SAADIII/Papers/IV-0-10.pdf.
62. Thompson R.S., Shafer S.L., Anderson K.H., Strickland L.E., Pelltier R.T., Bartlein P.J., and Kerwin M.W. Topographic, bioclimatic, and vegetation characteristics of three ecoregion classification systems in North America: comparisons along continent-wide transects. Environ. Manage. 34 1 (2005) S125-S148
63. USDA, 2006. Land resource regions and major land resource areas of the United States, the Caribbean, and the Pacific Basin. In: U.S. Department of Agriculture Handbook. United States Department of Agriculture, Natural Resources Conservation Service. 296 pp.
64. USGS, 1999. United States Geological Survey. National Elevation Dataset. Acquired at: Natural Resources Geographic Information Systems Library, Geographic Information Systems Support and Research Facility, Iowa State University: ftp://ftp.igsb.uiowa.edu/GIS_Library/IA_State/Elevation.
65. USGS, 2007. http://ned.usgs.gov.
66. Van Esbroeck G.A., Hussey M.A., and Sanderson M.A. Variation between Alamo and Cave-in-Rock switchgrass in response to photoperiod extension. Crop Sci. 42 (2003) 639-643
67. Veldkamp A., Kok K., De Koning G.H.J., Schoorl J.M., Sonneveld M.P.W., and Verburg P.H. Multi-scale system approaches in agronomic research at the landscape level. Soil Till. Res. 58 (2001) 129-140
68. Verdoodt A., and Van Ranst E. Environmental assessment tools for multi-scale land resources information systems: a case study of Rwanda. Agric. Ecosyst. Environ. 114 (2006) 170-184
69. Viglizzo E.F., Pordomingo A.J., Castro M.G., Lértora F.A., and Bernardos J.N. Scale-dependent controls on ecological functions in agroecosystems of Argentina. Agric. Ecosyst. Environ. 101 (2004) 39-51
70. Virgilio, de N., Monti A., and Venturi G. Spatial variability of switchgrass (Panicum virgatum L.) yield as related to soil parameters in a small field. Field Crop Res. 101 (2007) 232-239
71. Vogel K.P., Schmer M.R., and Mitchell R.B. Plant adaptation regions: ecological and climatic classification of plants. Range. Ecol. Manage. 58 (2005) 315-319
72. Waltman W.J., Waltman S.W., Mortenson D.A., and Miller D.A. A new geography of agriculture: understanding patterns, trends and processes at multiple spatial and temporal scales. In: Stamatiadis S., Lynch J.M., and Scheppers J.S. (Eds). Remote Sensing for Agriculture and the Environment (2004) 262-276 (Peripheral Editions, Larissa, Greece)
73. Wassenaar T., Lagacherie P., Legros J.-P., and Rounsevell M.D.A. Modelling wheat yield responses to soil and climate variability at the regional scale. Climate Res. 11 (1999) 209-220
74. Young J.A., Christensen B.M., Schaad M.S., Herdendorf M.E., Vance G.F., and Munn L.C. A geographic information system to identify areas for alternative crops in northwestern Wyoming. In: Janick J. (Ed). Perspectives on New Crops and New Uses (1999), ASHS Press, Alexandria 176-180
75. Zhou Y., Narumalani S., Waltman W.J., Waltman S.W., and Palecki M.A. A GIS-based spatial pattern analysis model for eco-region mapping and characterization. Int. J. Geophys. Inform. Sci. 17 (2003) 445-462