European Journal of Forest Research

, Volume 133, Issue 2, pp 261–272 | Cite as

Efficiency of alternative forest inventory methods in partially harvested stands

  • Ben RiceEmail author
  • Aaron R. Weiskittel
  • Robert G. Wagner
Original Paper


Forest inventory is vital to all aspects of forest management and inventory methods can vary greatly in their accuracy, precision, efficiency and cost. In Maine, much of the forestland base has been managed using partial harvesting methods over the past two decades. These partial harvesting methods generally produce highly heterogeneous stand structures and composition. Consequently, it is currently unclear which inventory methods are best given the distinct spatial and structural heterogeneity that is created. We compared efficiency and stand-level inventory estimates using horizontal point, fixed area and horizontal line sampling measurement methods in 16 partially harvested stands across northern and central Maine. Some stand-level variables were sensitive to measurement method (e.g., volume, quadratic mean diameter and small stem density and basal area), while others were less sensitive (e.g., overall basal area and stem density). Efficiency, defined as a combination of precision of volume estimates and measurement time, varied among measurement methods at lower stand basal area values but was similar at higher basal area, with the exception of the fixed area method. Overall, horizontal line sampling proved to be a viable method in post-partial harvest stand conditions. Our results illustrate the trade-offs between precision and time costs involved in several measurement methods under a range of heterogeneous stand conditions.


Mensuration Variable radius sampling Horizontal line sampling Partial harvesting Big BAF 



This research was funded by the Northeastern States Research Cooperative, University of Maine School of Forest Resources and University of Maine Cooperative Forestry Research Unit (CFRU). Member organizations of the CFRU also provided the field sites for this research. Kasey Legaard and Erin Simons-Legaard of the University of Maine Image Analysis Laboratory (MIAL) provided key technical support for this project. This work was supported by the Maine Agricultural and Forestry Research Station at the University of Maine (Maine Agricultural and Forest Experiment Station Publication Number 3290).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ben Rice
    • 1
    Email author
  • Aaron R. Weiskittel
    • 1
  • Robert G. Wagner
    • 1
  1. 1.School of Forest ResourcesUniversity of MaineOronoUSA

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