Applications of Geographic Information Systems and Geostatistics in Plant Disease Epidemiology and Management.

Information management will be a key to improving farm practices in the coming decades. It makes sense to organize farm information in spatial databases because agricultural systems are inherently spatial. Biological and physical aspects of agricultural systems create spatial heterogeneity, and as a result, patchiness is the rule in the occurrence and distribution of plant pathogens and disease (3). Plant disease management practices can be improved by putting epidemiological information in the same format as other farm information using a geographic information system (GIS). A GIS is a computer system capable of assembling, storing, manipulating, and displaying data referenced by geographic coordinates (45). GIS can now be installed on any recent model desktop computer (e.g., a Pentium personal computer with at least 32 MB of RAM is adequate for most applications) and does not require an in-depth understanding of the statistical and mathematical basis of the technology. The large commercial push toward precision farming is based on combining GIS with sophisticated hardware for geographically referenced yield data and variable rate applications of fertilizers and other farm chemicals. GIS can be adapted to any size operation, and data can be incorporated at any scale from a single field to an agricultural region. Many problems should be studied at more than one scale. Part of the art of GIS database development is to decide what scale to use and which kinds of information to include at each scale. The ability of government institutions, the nation’s agricultural colleges and experiment stations, and private enterprise to provide spatially referenced information will open the way to farmers, pest control advisors, extension workers, and others to evaluate plant disease problems in a spatial context. New tools, including global positioning systems (GPS) and geostatistics, are available to use in connection with GIS. While these tools can be used at any scale, our efforts have been at the regional scale in generally arid irrigated agricultural areas. We focus on spatial relationships of landscape features that interact with the progress of an epidemic to refine cultural management strategies for plant disease control. Examples from this work will be used to illustrate the application of GPS, GIS, and geostatistics following a general

[1]  William E. Fry,et al.  Population Genetics and Intercontinental Migrations of Phytophthora Infestans , 1992 .

[2]  T. Bernhardsen.  Geographic Information Systems: An Introduction , 1999 .

[3]  Paul Teng,et al.  Biological Impact and Risk Assessment in Plant Pathology , 1993 .

[4]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[5]  P. de Reffye,et al.  Analysis and Mapping of the Spatial Spread of African Cassava Mosaic Virus Using Geostatistics and the Kriging Technique , 1989 .

[6]  J. C. Zadoks,et al.  A geostatistical analysis of the spatio - temporal development of downy mildew epidemics in cabbage , 1994 .

[7]  Trevor J. Davis,et al.  Modelling Uncertainty in Natural Resource Analysis Using Fuzzy Sets and Monte Carlo Simulation: Slope Stability Prediction , 1997, Int. J. Geogr. Inf. Sci..

[8]  Donald E. Myers,et al.  Interpolation and estimation with spatially located data , 1991 .

[9]  Michael F. Goodchild.  Geographic Information Systems , 2001 .

[10]  T. Gottwald,et al.  Analysis of the spatial spread of sharka (plum pox virus) in apricot and peach orchards in eastern Spain. , 1995 .

[11]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[12]  H. C. Weltzien.  Use of Geophytopathological Information , 1988 .

[13]  Merritt R. Nelson,et al.  Preliminary Investigation of Sweet Potato Whitefly Population Dynamics Across Arizona , 1993 .

[15]  Clayton V. Deutsch,et al.  GSLIB: Geostatistical Software Library and User's Guide , 1993 .

[16]  Marcia L. Gumpertz,et al.  Geostatistical analysis of Phytophthora epidemic development in commercial bell pepper fields , 1995 .

[17]  K. L. Heong,et al.  Use of Geographical Information Systems in Analyzing Large Area Distribution and Dispersal of Rice Insects in South Korea , 1993 .

[18]  R. H. Callihan,et al.  GPS and GIS for Weed Surveys and Management , 1993, Weed Technology.

[19]  A. Journel.  Fundamentals of geostatistics in five lessons , 1991 .

[20]  P. Cotty,et al.  Virulence and cultural characteristics of two Aspergillus flavus strains pathogenic on cotton. , 1989 .

[21]  Barak A. Cohen,et al.  Historical and recent migrations of Phytophthora infestans: chronology, pathways and implications. , 1993 .

[22]  R. C. Seem.  Geographic Information Systems for localized pest predictions1 , 1993 .

[23]  M. Goodchild,et al.  Environmental Modeling with GIS , 1994 .

[24]  Yvan Pannatier,et al.  Variowin: Software for Spatial Data Analysis in 2D , 1996 .

[25]  P. W. Borth,et al.  Stochastic Simulation for Characterizing Ecological Spatial Patterns and Appraising Risk. , 1993, Ecological applications : a publication of the Ecological Society of America.

[26]  R. E. Schneider,et al.  Use of cellulose-acetate electrophoresis for rapid identification of allozyme genotypes of Phytophthora infestans , 1995 .

[27]  Helena Mitasova,et al.  Using a geographic information System (GIS) for herbicide management , 1996 .

[28]  Michael Edward Hohn,et al.  An Introduction to Applied Geostatistics: by Edward H. Isaaks and R. Mohan Srivastava, 1989, Oxford University Press, New York, 561 p., ISBN 0-19-505012-6, ISBN 0-19-505013-4 (paperback), $55.00 cloth, $35.00 paper (US) , 1991 .

[29]  B. Cohen,et al.  Panglobal distribution of a single clonal lineage of the Irish potato famine fungus. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[30]  Merritt R. Nelson,et al.  Geographic information systems and geostatistics in the design and validation of regional plant virus management programs , 1994 .

[31]  David J. Mulla,et al.  Geostatistical Tools for Modeling and Interpreting Ecological Spatial Dependence , 1992 .

[32]  James H. Everitt,et al.  Using airborne video, global positioning system, and geographical information system technologies for detecting and mapping citrus blackfly infestations , 1994 .

[33]  K. G. Rohrbach,et al.  Analysis of the spatial pattern of plant pathogens and diseased plants using geostatistics. , 1988 .

[34]  J. Estes,et al.  Geographic Information Systems: An Introduction , 1990 .

[35]  Laurence V. Madden,et al.  Introduction to Plant Disease Epidemiology , 1990 .

[36]  T. P. Robinson.  Insect Migration: Geographic information systems and remotely sensed data for determining the seasonal distribution of habitats of migrant insect pests , 1995 .

[37]  R. Webster,et al.  Geostatistical analysis of cyst nematodes in soil , 1992 .

[38]  Donald E. Myers,et al.  To be or not to be... stationary? That is the question , 1989 .

[39]  P. Cotty,et al.  Spatial and Temporal Patterns of Aspergillus flavus Strain Composition and Propagule Density in Yuma County, Arizona, Soils. , 1997, Plant disease.

[40]  Jürgen Kranz,et al.  Experimental Techniques in Plant Disease Epidemiology , 1988, Springer Berlin Heidelberg.

[41]  Andrew M. Liebhold,et al.  Geostatistics and Geographic Information Systems in Applied Insect Ecology , 1993 .

[42]  P. Cotty.  Influence of field application of an atoxigenic strain of Aspergillus flavus on the populations of A. flavus infectiing cotton bolls and on the aflatoxin content of cottonseed , 1994 .

[43]  John P. Wilson,et al.  Coupling Geographic Information Systems and Models for Weed Control and Groundwater Protection , 1993, Weed Technology.