Skip to main content

Advertisement

SpringerLink
Log in

Analyzing the impacts of forest disturbance on individual tree diameter increment across the US Lake States

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Disturbances play a critical role in forest ecosystem dynamics. Disturbances cause changes in forest structure which in turn influence the species composition of the site and alter landscape patterns over time. The impacts of disturbance are seen over a broad spectrum of spatial scales and varying intensities, ranging from biotic agents such as insect and leaf disease outbreaks to abiotic agents such as a windstorm (a stand-replacing disturbance). This study utilized Forest Inventory and Analysis (FIA) data collected between 1999 and 2014 in the US Lake States (Michigan, Minnesota, and Wisconsin) to examine the impacts that disturbances have on the growth of residual trees using species-specific diameter increment equations. Results showed that animal and weather damage were the most common disturbance agents and fires were the least common in the region. Results also indicated that while the diameter increment equations performed well on average (overprediction of 0.08 ± 1.98 cm/10 years in non-disturbed stands), when the data were analyzed by species and disturbance agent, the model equation was rarely validated using equivalence tests (underprediction of 0.30 ± 2.24 cm/10 years in non-disturbed stands). This study highlights the importance of monitoring forest disturbances for their impacts on forest growth and yield.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Baker, W. L. (1995). Longterm response of disturbance landscapes to human intervention and global change. Landscape Ecology, 10, 143–159.

    Article  Google Scholar 

  • Bechtold, W. A., & Patterson, P. L. (2005). The enhanced forest inventory and analysis program, General Technical Report SRS-80. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station.

  • Brand, G. J., Nelson, M. D., Wendt, D. G., & Nimerfro, K. K. (2000). The hexagon/panel system for selecting FIA plots under an annual inventory. In R. E. McRoberts, G. A. Reams, & P. C. Van Deusen, (Eds.), Proceedings of the First Annual Forest Inventory and Analysis Symposium. General Technical Report NC-213. (pp. 8–13). St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station.

  • Bruce, D. (1977). Yield differences between research plots and managed forests. Journal of Forestry, 75(1), 14–17.

    Google Scholar 

  • Canavan, S. J., & Ramm, C. W. (2000). Accuracy and precision of 10 year predictions for Forest Vegetation Simulator-Lake States. Northern Journal of Applied Forestry, 17, 62–70.

    Google Scholar 

  • Chen, C., Weiskittel, A., Bataineh, M., & MacLean, D. A. (2017). Evaluating the influence of varying levels of spruce budworm defoliation on annualized individual tree growth and mortality in Maine, USA and New Brunswick, Canada. Forest Ecology and Management, 396, 184–194.

    Article  Google Scholar 

  • Cornett, M. W., Frelich, L. E., Puettmann, K. J., & Reich, P. B. (2000). Conservation implications of browsing by Odocoileus virginianus in remnant upland Thuja occidentalis forests. Biological Conservation, 93, 359–369.

    Article  Google Scholar 

  • Crocker, S. J., Liknes, G. C., McKee, F. R., Albers, J. S., & Aukema, B. H. (2016). Stand-level factors associated with resurging mortality from eastern larch beetle (Dendroctonus simplex LeConte). Forest Ecology and Management, 375, 27–34.

    Article  Google Scholar 

  • Crookston, N. L., & Dixon, G. E. (2005). The Forest Vegetation Simulator: a review of its applications, structure, and content. Computers and Electronics in Agriculture, 49(1), 60–80.

    Article  Google Scholar 

  • Crookston, N. L., Colbert, J. J., Thomas, P. W., Sheehan, K. A. & Kemp, W. P. (1990). User's guide to the western spruce budworm modeling system. General Technical Report INT-274. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station.

  • Crookston, N. L., Rehfeldt, G. E., Dixon, G. E., & Weiskittel, A. R. (2010). Addressing climate change in the forest vegetation simulator to assess impacts on landscape forest dynamics. Forest Ecology and Management, 260(7), 1198–1211.

    Article  Google Scholar 

  • Dale, V. H., Joyce, L. A., McNulty, S., Neilson, R. P., Ayres, M. P., Flannigan, M. D., et al. (2001). Climate change and forest disturbances. BioScience, 51(9), 723–734.

    Article  Google Scholar 

  • Deo, R. K., & Froese, R. E. (2013). Refitting the large-tree diameter growth equations of the Lake States and Central States variants of the Forest Vegetation Simulator. School of Forest Resources and Environmental Science, Michigan Technological University. https://www.researchgate.net/publication/328974689_Refitting_the_Large-Tree_Diameter_Growth_Equations_of_the_Lake_States_and_Central_States_Variants_of_the_Forest_Vegetation_Simulator/stats. Accessed 18 Nov 2018.

  • Dixon, G. E., & Keyser, C. E. (2008). Lake States (LS) variant overview-Forest Vegetation Simulator. Revised October, 2017. Internal Report. Fort Collins, CO: U.S. Department of Agriculture, Forest Management Service Center.

  • Fox, J. C., Ades, P. K., & Bi, H. (2001). Stochastic structure and individual-tree growth models. Forest Ecology and Management, 154, 261–276.

    Article  Google Scholar 

  • Frelich, L. E., & Lorimer, C. G. (1991). Natural disturbance regimes in hemlock-hardwood forests of the upper Great Lakes region. Ecological Monographs, 61, 145–164.

    Article  Google Scholar 

  • García, O. (2006). Scale and spatial structure effects on tree size distributions: implications for growth and yield modelling. Canadian Journal of Forest Research, 36, 2983–2993.

    Article  Google Scholar 

  • Gertner, G. Z., & Dzialowy, P. J. (1984). Effects of measurement errors on an individual tree based growth projection system. Canadian Journal of Forest Research, 14, 311–316.

    Article  Google Scholar 

  • Henning, J. G., & Burk, T. E. (2004). Improving growth and yield estimates with a process model derived growth index. Canadian Journal of Forest Research, 34, 1274–1282.

    Article  Google Scholar 

  • Johnsen, K., Samuelson, L., Teskey, R., Mcnulty, S., & Fox, T. (2001). Process models as tools in forestry research and management. Forest Science, 47(1), 2–8.

    Google Scholar 

  • Lacerte, V., Larocque, G. R., Woods, M., Parton, W. J., & Penner, M. (2006). Calibration of the forest vegetation simulator (FVS) model for the main forest species of Ontario, Canada. Ecological Modelling, 199(3), 336–349.

    Article  Google Scholar 

  • Lessard, V. C., McRoberts, R. E., & Holdaway, M. R. (2001). Diameter growth models using Minnesota forest inventory and analysis data. Forest Science, 47, 301–310.

    Google Scholar 

  • Marsden, M. A., Eav, B. B., & Thompson, M. K. 1993. User's guide to the Douglas-fir Beetle Impact Model. General Technical Report RM-250. Fort Collins, CO: U.S. Department of Agriculture, Rocky Mountain Forest and Range Experiment Station.

  • Munro D. D. (1974). Forest growth models—a prognosis. In: Growth models for tree and stand simulation. Research Note Number 30. Stockholm, Sweden. Swedish Royal College of Forestry.

  • Parkhurst, D. F. (2001). Statistical significance tests: equivalence and reverse tests should reduce misinterpretation. Bioscience, 51, 1051e7.

    Article  Google Scholar 

  • Payandeh, B., & Papadopol, P. (1994). Partial calibration of ‘ONTWIGS’: a forest growth and yield projection system adapted for Ontario. Northern Journal of Applied Forestry, 11, 41–46.

    Google Scholar 

  • Pokharel, B., & Froese, R. E. (2008). Evaluating alternative implementations of the Lake States FVS diameter increment model. Forest Ecology and Management, 255, 1759–1771.

    Article  Google Scholar 

  • Pretzsch, H. (2005). Diversity and productivity of forests: evidence from long term experimental plots. In M. Scherer-Lorenzen, C. Körner, & E.-D. Schulze (Eds.), Forest diversity and function: temperate and boreal systems (pp. 41–64).

    Chapter  Google Scholar 

  • Raymond, C. L., Healey, S., Peduzzi, A., & Patterson, P. (2015). Representative regional models of post-disturbance forest carbon accumulation: integrating inventory data and a growth and yield model. Forest Ecology and Management, 336, 21–34.

    Article  Google Scholar 

  • Reyer, C. P. O., Bathgate, S., Blennow, K., Borges, J. G., Bugmann, H., Delzon, S., Faias, S. P., Garcia-Gonzalo, J., Gardiner, B., Gonzalez-Olabarria, J. R., Gracia, C., Hernández, J. G., Kellomäki, S., Kramer, K., Lexer, M. J., Lindner, M., van der Maaten, E., Maroschek, M., Muys, B., Nicoll, B., Palahi, M., Palma, J. H. N., Paulo, J. A., Peltola, H., Pukkala, T., Rammer, W., Ray, D., Sabaté, S., Schelhaas, M. J., Seidl, R., Temperli, C., Tomé, M., Yousefpour, R., Zimmermann, N. E., & Hanewinkel, M. (2017). Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests? Environmental Research Letters, 12(3), 34027.

    Article  Google Scholar 

  • Robinson, A. (2016). equivalence: provides tests and graphics for assessing tests of equivalence. R package version 0.7.2. https://CRAN.R-project.org/package=equivalence. Accessed 18 Nov 2018.

  • Robinson, A. P., & Froese, R. E. (2004). Model validation using equivalence tests. Ecological Modelling, 176(3–4), 349–358.

    Article  Google Scholar 

  • Runkle, J. R. (1982). Patterns of disturbance in some old-growth mesic forests of eastern North America. Ecology, 63, 1533–1546.

    Article  Google Scholar 

  • Russell, M. B., D'Amato, A. W., Albers, M. A., Woodall, C. W., Puettmann, K. J., Saunders, M. R., & VanderSchaaf, C. L. (2015). Performance of the Forest Vegetation Simulator in managed white spruce plantations influenced by eastern spruce budworm in northern Minnesota. Forest Science, 61, 723–730.

    Article  Google Scholar 

  • Russell, M. B., Patton, S. R., Wilson, D. C., Domke, G. M., & Frerker, K. L. (2018). Impacts of alternative harvesting and natural disturbance scenarios on forest biomass in the Superior National Forest, USA. Forests, 9(8), 491.

    Article  Google Scholar 

  • Seidl, R., Schelhaas, M.-J., Rammer, W., & Verkerk, P. J. (2014). Increasing forest disturbances in Europe and their impact on carbon storage. Nature Climate Change, 4, 806–810.

    Article  CAS  Google Scholar 

  • Trasobares, A., Zingg, A., Walthert, L., & Bigler, C. (2016). A climate-sensitive empirical growth and yield model for forest management planning of even-aged beech stands. European Journal of Forest Research, 135, 263–282.

    Article  Google Scholar 

  • US Forest Service. (2014). The Forest Inventory and Analysis database: database description and user guide version 6.0 for phase 2. Washington D.C.

  • Waring, K. M., & O’Hara, K. L. (2005). Silvicultural strategies in forest ecosystems affected by introduced pests. Forest Ecology and Management, 209, 27–41.

    Article  Google Scholar 

  • Wellek, S. (2003). Testing statistical hypotheses of equivalence. London: Chapman and Hall.

    Google Scholar 

  • Woods, A., & Coates, K. D. (2013). Are biotic disturbance agents challenging basic tenets of growth and yield and sustainable forest management? Forestry, 86(5), 543–554.

    Article  Google Scholar 

Download references

Acknowledgments

We thank Ram Deo, Chad Keyser, Jacob Muller, and two anonymous reviewers for their comments that improved this manuscript.

Funding

This work was supported by the Minnesota Agricultural Experiment Station (project 42-063).

Author information

Authors and Affiliations

  1. Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN, 55108, USA

    Macklin J. Glasby

  2. Department of Forest Resources, University of Minnesota, 1530 Cleveland Ave. N, St. Paul, MN, 55108, USA

    Matthew B. Russell

  3. USDA Forest Service, Northern Research Station, 1992 Folwell Ave, St. Paul, MN, 55108, USA

    Grant M. Domke

Authors
  1. Macklin J. Glasby
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matthew B. Russell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Grant M. Domke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthew B. Russell.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Glasby, M.J., Russell, M.B. & Domke, G.M. Analyzing the impacts of forest disturbance on individual tree diameter increment across the US Lake States. Environ Monit Assess 191, 56 (2019). https://doi.org/10.1007/s10661-019-7187-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-019-7187-8

Keywords

Search

Navigation