Over the last several decades, researchers have published almost 50 articles from their research at Upham Woods – articles that have been cumulatively cited over 6,600 times! Below is a list of these articles. As you may notice, research at Upham Woods has been heavily focused on both the natural sciences and education/learning sciences. Most of the natural science research taken place on our property answers questions about forest ecosystems and processes, and nutrient cycling by using remote sensing and other spatial analysis tools. Education and learning research has focused on the integration of technology into STEM-education and inquiry-based learning in outdoor settings.

Natural Science Publications

  1. Aber, J. D., Melillo, J. M., Nadelhoffer, K. J., McClaugherty, C. A., & Pastor, J. (1985). Fine root turnover in forest ecosystems in relation to quantity and form of nitrogen availability: a comparison of two methods. Oecologia66(3), 317-321.
  2. Aber, J. D., Wessman, C. A., Peterson, D. L., Melillo, J. M., & Fownes, J. H. (1990). Remote sensing of litter and soil organic matter decomposition in forest ecosystems. In Remote sensing of biosphere functioning (pp. 87-103). Springer, New York, NY.
  3. Anderson, R. C., & Loucks, O. L. (1973). Aspects of the biology of Trientalis borealis Raf. Ecology54(4), 798-808.
  4. Berg, B., & McClaugherty, C. (1987). Nitrogen release from litter in relation to the disappearance of lignin. Biogeochemistry4(3), 219-224.
  5. Berg, B., & McClaugherty, C. (1989). Nitrogen and phosphorus release from decomposing litter in relation to the disappearance of lignin. Canadian Journal of Botany67(4), 1148-1156.
  6. Berg, B., Ekbohm, G., & McClaugherty, C. (1984). Lignin and holocellulose relations during long-term decomposition of some forest litters. Long-term decomposition in a Scots pine forest. IV. Canadian Journal of Botany62(12), 2540-2550.
  7. Berg, B., Johansson, M. B., Ekbohm, G., McClaugherty, C., Rutigliano, F., & Santo, A. V. D. (1996). Maximum decomposition limits of forest litter types: a synthesis. Canadian Journal of Botany74(5), 659-672.
  8. Binkley, D., Aber, J., Pastor, J., & Nadelhoffer, K. (1986). Nitrogen availability in some Wisconsin forests: comparisons of resin bags and on-site incubations. Biology and Fertility of Soils2(2), 77-82.
  9. Bortolot, Z. J., & Wynne, R. H. (2003). A method for predicting fresh green leaf nitrogen concentrations from shortwave infrared reflectance spectra acquired at the canopy level that requires no in situ nitrogen data. International Journal of Remote Sensing24(3), 619-624.
  10. Card, D. H., Peterson, D. L., Matson, P. A., & Aber, J. D. (1988). Prediction of leaf chemistry by the use of visible and near infrared reflectance spectroscopy. Remote Sensing of Environment26(2), 123-147.
  11. Clark, R. N., Swayze, G., Heidebrecht, K., Goetz, A. F., & Green, R. O. (1993, October). Comparison of methods for calibrating AVIRIS data to ground reflectance. In 5th Annual Airborne Geoscience Workshop. AVIRIS. Jet Propulsion Laboratory, Pasadena, Calif (pp. 35-36).
  12. Currie, W. S., & Aber, J. D. (1997). Modeling leaching as a decomposition process in humid montane forests. Ecology78(6), 1844-1860.
  13. Goetz, A. F., & Heidebrecht, K. B. (1996, November). Full-scene subnanometer HYDICE wavelength calibration. In Hyperspectral Remote Sensing and Applications (Vol. 2821, pp. 85-92). International Society for Optics and Photonics.
  14. Hendricks, J. J., Aber, J. D., Nadelhoffer, K. J., & Hallett, R. D. (2000). Nitrogen controls on fine root substrate quality in temperate forest ecosystems. Ecosystems3(1), 57-69.
  15. Kokaly, R. F., & Clark, R. N. (1999). Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote sensing of environment67(3), 267-287.
  16. Martin, M. E. (1994). Measurements of foliar chemistry using laboratory and airborne high spectral resolution visible and infrared data.
  17. Martin, M. E., & Aber, J. D. (1993). Measurements of canopy chemistry with 1992 AVIRIS data at Blackhawk Island and Harvard Forest.
  18. Martin, M. E., & Aber, J. D. (1993). Measurements of canopy chemistry with 1992 AVIRIS data at Blackhawk Island and Harvard Forest.
  19. Martin, M. E., & Aber, J. D. (1997). Estimating forest canopy characteristics as inputs for models of forest carbon exchange by high spectral resolution remote sensing. In The Use of Remote Sensing in the Modeling of Forest Productivity (pp. 61-72). Springer, Dordrecht.
  20. Martin, M. E., & Aber, J. D. (1997). High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes. Ecological applications7(2), 431-443.
  21. Martin, M. E., Newman, S. D., Aber, J. D., & Congalton, R. G. (1998). Determining forest species composition using high spectral resolution remote sensing data. Remote Sensing of Environment65(3), 249-254.
  22. McLellan, T. M., Aber, J. D., Martin, M. E., Melillo, J. M., & Nadelhoffer, K. J. (1991). Determination of nitrogen, lignin, and cellulose content of decomposing leaf material by near infrared reflectance spectroscopy. Canadian Journal of Forest Research21(11), 1684-1688.
  23. Pastor, J., Aber, J. D., McClaugherty, C. A., & Melillo, J. M. (1982). Geology, soils and vegetation of Blackhawk Island, Wisconsin. American Midland Naturalist, 266-277.
  24. Pastor, J., Aber, J. D., McClaugherty, C. A., & Melillo, J. M. (1984). Aboveground production and N and P cycling along a nitrogen mineralization gradient on Blackhawk Island, Wisconsin. Ecology65(1), 256-268.
  25. Peters, E. B., Wythers, K. R., Bradford, J. B., & Reich, P. B. (2013). Influence of disturbance on temperate forest productivity. Ecosystems16(1), 95-110.
  26. Peterson, D. L., Aber, J. D., Matson, P. A., Card, D. H., Swanberg, N., Wessman, C., & Spanner, M. (1988). Remote sensing of forest canopy and leaf biochemical contents. Remote Sensing of Environment24(1), 85-108.
  27. Sahrawat, K. L., Keeney, D. R., & Adams, S. S. (1985). Rate of aerobic nitrogen transformations in six acid climax forest soils and the effect of phosphorus and CaCO3. Forest Science31(3), 680-684.
  28. Scott, N. A., & Binkley, D. (1997). Foliage litter quality and annual net N mineralization: comparison across North American forest sites. Oecologia111(2), 151-159.
  29. Serbin, S. P., Singh, A., McNeil, B. E., Kingdon, C. C., & Townsend, P. A. (2014). Spectroscopic determination of leaf morphological and biochemical traits for northern temperate and boreal tree species. Ecological Applications24(7), 1651-1669.
  30. Spanner, M. A., Peterson, D. L., Acevedo, W., & Matson, P. (1985). High Resolution Spectrometry of Leaf and Canopy Chemistry for Biochemical Cycling.
  31. Vitousek, P. M. (1994). Factors controlling ecosystem structure and function. Factors of Soil Formation: A Fiftieth Anniversary Retrospective33, 87-97.
  32. Wessman, C. A. (1991). Remote sensing of soil processes. Agriculture, Ecosystems & Environment34(1-4), 479-493.
  33. Wessman, C. A., Aber, J. D., & Peterson, D. L. (1989). An evaluation of imaging spectrometry for estimating forest canopy chemistry. International Journal of Remote Sensing10(8), 1293-1316.
  34. Wessman, C. A., Aber, J. D., Peterson, D. L., & Melillo, J. M. (1988). Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems. Nature335(6186), 154-156.

Environmental Education Publications

  1. Eitel, K., Hougham, J. R., Miller, B., Schon, J., & LaPaglia, K. (2013). Upload download: Empowering students through technology-enabled problem-based learning. Science Scope36(7), 32.
  2. Greenwood, D. A., & Hougham, R. J. (2015). Mitigation and adaptation: critical perspectives toward digital technologies in place-conscious environmental education. Policy futures in education13(1), 97-116.
  3. Hougham, R. J., Herde, I., Loveland, J., Olsen, S., Morgan, T., Steinhauer, M., Goodrow, Z., Myers, M., & Oszuscik, S. (2020). Science to Story, Story to Social. Connected Science Learning, 2(2). Retrieved from
  4. Hougham, J., Morgan, T., Olsen, S., & Herde, I. (2019). Status and Needs of Environmental Education Related Organizations in Wisconsin: Results from the 2019 state-wide survey. Madison, WI: University of Wisconsin – Madison Division of Extension.
  5. Hougham, J., Olsen, S., Herde, I., Christian, A., Schuh, C., Goodrow, Z., & Drogemuller, T. (2020). Research Accelerators: Milwaukee Environmental STEM (E-STEM) Project 2019. Madison, WI: University of Wisconsin – Madison Division of Extension.
  6. Hougham, R. J., & Kerlin, S. (2016). To unplug or plug in. Green Teacher, (111).
  7. Hougham, R. J., Eitel, K. C. B., & Miller, B. G. (2015). Technology-enriched STEM investigations of place: Using technology to extend the senses and build connections to and between places in science education. Journal of Geoscience Education63(2), 90-97.
  8. Hougham, R. J., Nutter, M., & Graham, C. (2018). Bridging natural and digital domains: Attitudes, confidence, and interest in using technology to learn outdoors. Journal of Experiential Education41(2), 154-169.
  9. Hougham, R. J., Nutter, M., Gilbertson, M., & Bukouricz, Q. Digital Environmental Literacy: Student Generated Data and Inquiry.
  10. Hougham, R. J., Nutter, M., Nussbaum, A., Riedl, T., Myers, M., Berget, L., … & Oszuscik, S. (2016). Engaging At-Risk Populations Outdoors, Digitally.
  11. Schon, J., Eitel, K. B., Hendrickson, D., & Hougham, J. (2015). Creating a research to classroom pipeline: closing the gap between science research and educators.
  12. Schon, J., Hougham, R. J., Eitel, K., & Hollenhorst, S. (2014). The value of a tree: comparing carbon sequestration to forest products. Science Scope37(7), 27.
  13. Veletsianos, G., Miller, B. G., Eitel, K. B., Eitel, J. U., Hougham, R. J., & Hansen, D. (2015). Lessons learned from the design and development of technology-enhanced outdoor learning experiences. TechTrends: Linking Research and Practice to Improve Learning59(4), 78-86.
  14. Zocher, J. L., & Hougham, R. J. (2020). Implementing Ecopedagogy as an Experiential Approach to Decolonizing Science Education. Journal of Experiential Education, 1053825920908615.