Advertisement

Human Ecology

, Volume 22, Issue 3, pp 279–316 | Cite as

A regional analysis of Barí land use intensification and its impact on landscape heterogeneity

  • Clifford A. Behrens
  • Michael G. Baksh
  • Michel Mothes
Article

Abstract

Since pacification 30 years ago, the Barí of northwest Venezuela have aggregated in villages and have begun to produce cattle and some crops for sale in regional markets. This research analyzes satellite imagery to compare patterns of land use among Barí settlements that differ in their population size, cattle holdings, and distance to nearest marketplace. These comparisons indicate that settlement history mediates the effect of population pressure and herd sizes on land use. Moreover, intensification of land use is associated with greater deforestation and a more heterogeneous landscape, but less biodiversity in woody species.

Key words

cultural ecology land use landscape Barí remote sensing geographical information system 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aitchison, J. (1986).The Statistical Analysis of Compositional Data. Monographs on statistics and applied probability, Chapman and Hall, New York.Google Scholar
  2. Alenderfer, M. S., and Blashfield, R. K. (1984).Cluster Analysis. Sage University Paper series on Quantitative Applications in the Social Sciences, series no. 07-044, Sage, Newbury Park, CA.Google Scholar
  3. Anderson, J. R., Hardy, E., Roach, J., and Witmer, R. (1976).A Land Use and Land Cover Classification System for Use with Remote Sensor Data. U.S. Geological Survey Professional Paper 964, U.S. Government Printing Office, Washington, DC.Google Scholar
  4. Baksh, M. (1991). Applications of a hand-held GPS receiver in South American rain forests. In Behrens, C., and Sever, T. (eds.),Applications of Space-Age Technology in Anthropology, Conference Proceedings. NASA Science and Technology Laboratory, Stennis Space Center, MS, p. 227–236.Google Scholar
  5. Baudry, J. (1993). Landscape dynamics and farming systems: Problems of relating patterns and predicting ecological changes. In Bunce, R., Ryszkowski, L., and Paoletti, M. (eds.),Landscape Ecology and Agroecosystems. Lewis Publishers, Boca Raton, FL, p. 21–40.Google Scholar
  6. Beckerman, S. (1980). Fishing and hunting by the Barí of Colombia. In Hames, R. (ed.),Working Papers on South American Indians (Vol. 2). Bennington College, Bennington, Vermont, p. 67–111.Google Scholar
  7. Beckerman, S. (1983). Barí swidden gardens: Crop segregation patterns.Human Ecology 11: 85–101.Google Scholar
  8. Behrens, C. A. (1990). Qualitative and quantitative approaches to the analysis of anthropological data: A new synthesis.Journal of Quantitative Anthropology 2: 25–48.Google Scholar
  9. Behrens, C. A. (1991). Applications of satellite image processing to the analysis of Amazonian cultural ecology. In Behrens, C., and Sever, T. (eds.),Applications of Space-Age Technology in Anthropology, Conference Proceedings. NASA Science and Technology Laboratory, Stennis Space Center, MS, p. 9–33.Google Scholar
  10. Behrens, C. A. (1992a). A formal justification for the application of GIS to the cultural ecological analysis of land use intensification and deforestation in the Amazon. In Aldenderfer, M., and Maschner, H. (eds.),The Anthropology of Human Behavior through Geographic Information and Analysis. Cambridge University Press, Cambridge. In press.Google Scholar
  11. Behrens, C. A. (1992b). Labor specialization and the formation of markets for food in a Shipibo subsistence economy.Human Ecology 20(3): 435–462.Google Scholar
  12. Bennett, I. M. (1991). Barí loricarid collection and the value of information: An application of optimal foraging theory.Human Ecology 19(4): 517–527.Google Scholar
  13. Blalock, H. M., Jr. (1972).Social Statistics (2nd Ed.) McGraw-Hill, New York.Google Scholar
  14. Boserup, E. (1965).The Conditions of Agricultural Growth: The Economics of Agrarian Change Under Population Pressure. Aldine, Chicago.Google Scholar
  15. Burrough, P. A. (1986).Principles of Geographical Information Systems for Land Resources Assessment. Monographs on Soil and Resources Survey, No. 12, Clarendon Press, Oxford.Google Scholar
  16. Cibula, W. G., and Nyquist, M. O. (1987). Use of topographic and climatological models in a geographical data base to improve landsat MSS classification for Olympic National Park.Photogrammetric Engineering and Remote Sensing 53(1): 67–75.Google Scholar
  17. Clarke, K. C. (1990).Analytical and Computer Cartography. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  18. Conant, F. P. (1990). 1990 and beyond: Satellite remote sensing and ecological anthropology. In Moran, E. (ed.),The Ecosystem Approach in Anthropology. University of Michigan Press, Ann Arbor, p. 357–388.Google Scholar
  19. Dale, V. H., O'Neill, R. V., Pedlowski, M., and Southworth, F. (1993). Causes and effects of land-use change in central RondÔnia, Brazil.Photogrammetric Engineering & Remote Sensing 59(6): 997–1005.Google Scholar
  20. Edgington, E. S. (1987).Randomization Tests (2nd Ed.). Marcel Dekker, New York.Google Scholar
  21. Gross, D. (1990). Ecosystems and methodological problems in ecological anthropology. In Moran, E. (ed.),The Ecosystem Approach in Anthropology. University of Michigan Press, Ann Arbor, p. 309–319.Google Scholar
  22. Grossman, L. S. (1984). Collecting time-use data in Third World rural communities.Professional Geographer 36(4): 444–454.Google Scholar
  23. Guyer, J. I., and Lambin, E. F. (1993). Land use in an urban hinterland: Ethnography and remote sensing in the study of African intensification.American Anthropologist 95(4): 839–859.Google Scholar
  24. Hutchinson, C. F. (1982). Techniques for combining Landsat and ancillary data for digital classification improvement.Photogrammetric Engineering and Remote Sensing 48(1): 123–130.Google Scholar
  25. Jacobs, M. (1988).The Tropical Rain Forest: A First Encounter. Springer-Verlag, Berlin.Google Scholar
  26. Jensen, J. R. (1986).Introductory Digital Image Processing: A Remote Sensing Perspective. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  27. Johnson, A. W., and Behrens, C. A. (1989). Time allocation research and aspects of method in cross-cultural research.Journal of Quantitative Anthropology 1: 313–334.Google Scholar
  28. King, A. W. (1991). Translating models across scales in the landscape. In Turner, M., and Gardner, R. (eds.),Quantitative Methods in Landscape Ecology: The Analysis and Interpretation of Landscape Heterogeneity. Springer-Verlag, New York, p. 479–517.Google Scholar
  29. Kummer, D. M. (1992). Remote sensing and tropical deforestation: A cautionary note from the Philippines.Photogrammetric Engineering and Remote Sensing 58(10): 1469–1471.Google Scholar
  30. Lillesand, T. M., and R. W. Kiefer, (1987).Remote Sensing and Image Interpretation (2nd ed.). John Wiley and Sons, New York.Google Scholar
  31. Lizarralde, R. (1991). Barí settlement patterns.Human Ecology 19(4): 437–452.Google Scholar
  32. Lizarralde, R., and Beckerman, S. (1982). Historia contemporánea de los Barí.Antropologica 58: 3–52.Google Scholar
  33. Lizarralde, R. and Lizarralde, M. (1991). Barí exogamy among their territorial groups: Choice and/or necessity.Human Ecology 19: 453–467.Google Scholar
  34. Loker, W. M. (1993). The human ecology of cattle raising in the Peruvian Amazon: The view from the farm.Human Organization 52(1): 14–24.Google Scholar
  35. Maguire, D. J., Goodchild, M. F., and Rhind, D. W. (eds.) (1991).Geographical Information Systems: Principles and Applications. John Wiley & Sons, New York.Google Scholar
  36. Moran, E. F. (1990). Levels of analysis and analytical level shifting: Examples from Amazonian ecosystem research. In Moran, E. (ed.),The Ecosystem Approach in Anthropology. University of Michigan Press, Ann Arbor, p. 279–308.Google Scholar
  37. O'Neill, R. V., Krummel, J. R., Gardner, R. H., Sugihara, G., Jackson, B., DeAngelis, D. L., Milne, B. T., Turner, M. G., Zygmunt, B., Christensen, S. W., Dale, B. H., and Graham, R. L. (1988). Indices of landscape pattern.Landscape Ecology 1(3): 13–162.Google Scholar
  38. Quattrochi, D. A., and Pelletier, R. E. (1991). Remote sensing for analysis of landscapes: An introduction. In Turner, M., and Gardner, R. (eds.),Quantitative Methods in Landscape Ecology: The Analysis and Interpretation of Landscape Heterogeneity. Springer-Verlag, New York, p. 51–76.Google Scholar
  39. Reining, P. (1979).Challenging Desertification in West Africa: Insights from LANDSAT into Carrying Capacity, Cultivation, and Settlement Sites in Upper Volta and Niger. Center for International Studies, Ohio University, Athens.Google Scholar
  40. Richards, J. A. (1986).Remote Sensing Digital Image Analysis: An Introduction. Springer-Verlag, New York.Google Scholar
  41. Richards, J. A., Landgrebe, D. A., and Swain, P. H. (1982). A means for utilizing ancillary information in multispectral classification.Remote Sensing of Environment 12: 463–477.Google Scholar
  42. Ringrose, S., Matheson, W., Tempest, F. and Boyle, T. (1990). The development and causes of range degradation features in southeast Botswana using multi-temporal Landsat MSS imagery.Photogrammetric Engineering and Remote Sensing 56(9): 1253–1262.Google Scholar
  43. Rivet, P., and de Armellanda, C. (1950). Les Indiens Motilones.Journal de la Société des Américanistes 39: 15–57.Google Scholar
  44. Ruthenberg, H. (1980).Farming Systems in the Tropics. Clarendon Press, Oxford.Google Scholar
  45. SAS Institute (1988).SAS/STAT User's Guide, Release 6.03 Edition. SAS Institute, Cary, NC.Google Scholar
  46. Schowengerdt, R. A. (1983).Techniques for Image Processing and Classification in Remote Sensing. Academic Press, Orlando.Google Scholar
  47. Snyder, J. P. (1987).Map Projections—A Working Manual. Geological Survey Bulletin P-1395. U.S. Government Printing Office, Washington, DC.Google Scholar
  48. Spellerberg, I. F. (1991).Monitoring Ecological Change. Cambridge University Press, Cambridge.Google Scholar
  49. Strahler, A. H., Logan, T. L., and Bryant, N. A. (1978). Improving forest cover classification accuracy from Landsat by incorporating topographic information.Proceedings of the Twelfth International Symposium on Remote Sensing of Environment. Ann Arbor, Michigan, p. 927–942.Google Scholar
  50. Summer Institute of Linguistics (1983).Literature Preparation in the Languages of Colombia and the Work of the Summer Institute of Linguistics. Summer Institute of Linguistics, University of Oklahoma.Google Scholar
  51. Turner, B. L., II, Hanham, R. O., and Portararo, A. V. (1977). Population pressure and agricultural intensity.Annals of the Association of American Geographers 67: 384–396.Google Scholar
  52. Turner, M. G. (1989). Landscape ecology: The effect of pattern on process.Annual Review of Ecological Systems 20: 171–197.Google Scholar
  53. Uerkvitz, R. (1992). Settlement size and demographic inferences: A structural approach.Journal of Quantitative Anthropology 3: 297–323.Google Scholar
  54. Urban, D. L., O'Neill, R. V., and Shugart, H. H. (1987). Landscape ecology.BioScience 37(2): 119–127.Google Scholar
  55. U.S. Army Corps of Engineers (1993).GRASS 4.1. Construction Engineering Research Laboratory (CERL), Champaign, IL.Google Scholar
  56. Whittaker, R. H. (1965). Dominance and diversity in land plant communities.Science 147: 250–260.Google Scholar
  57. Wilkie, D. S. (1989). Performance of a backpack GPS in a tropical rain forest.Photogrammetric Engineering and Remote Sensing 55(12): 1747–1749.Google Scholar
  58. Wilson, E. O. (ed.) (1988).Biodiversity. National Academy Press, Washington, DC.Google Scholar

Copyright information

© Plenum Publishing Corporation 1994

Authors and Affiliations

  • Clifford A. Behrens
    • 1
  • Michael G. Baksh
    • 2
  • Michel Mothes
    • 3
  1. 1.Bell Communications ResearchMorristown
  2. 2.Tierra Environmental ServicesSan Diego
  3. 3.Escuela de EcologíaUniversidad de los AndesMéridaVenezuela

Personalised recommendations