Influence of Disturbance on Temperate Forest Productivity

Emily B. Peters, Kirk R. Wythers, John B. Bradford, Peter B. Reich

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Climate, tree species traits, and soil fertility are key controls on forest productivity. However, in most forest ecosystems, natural and human disturbances, such as wind throw, fire, and harvest, can also exert important and lasting direct and indirect influence over productivity. We used an ecosystem model, PnET-CN, to examine how disturbance type, intensity, and frequency influence net primary production (NPP) across a range of forest types from Minnesota and Wisconsin, USA. We assessed the importance of past disturbances on NPP, net N mineralization, foliar N, and leaf area index at 107 forest stands of differing types (aspen, jack pine, northern hardwood, black spruce) and disturbance history (fire, harvest) by comparing model simulations with observations. The model reasonably predicted differences among forest types in productivity, foliar N, leaf area index, and net N mineralization. Model simulations that included past disturbances minimally improved predictions compared to simulations without disturbance, suggesting the legacy of past disturbances played a minor role in influencing current forest productivity rates. Modeled NPP was more sensitive to the intensity of soil removal during a disturbance than the fraction of stand mortality or wood removal. Increasing crown fire frequency resulted in lower NPP, particularly for conifer forest types with longer leaf life spans and longer recovery times. These findings suggest that, over long time periods, moderate frequency disturbances are a relatively less important control on productivity than climate, soil, and species traits.

Original languageEnglish (US)
Pages (from-to)95-110
Number of pages16
JournalEcosystems
Volume16
Issue number1
DOIs
StatePublished - Jan 2013

Bibliographical note

Funding Information:
We thank Scott Ollinger for help with PnET-CN parameters and algorithms; Peter Snyder for advice on climate data; Matthew Peters for providing soil water holding capacity data; and all the researchers whose work provided useful comparative data. This work was funded by a Discovery Grant from the University of Minnesota’s Institute on the Environment, the Wilderness Research Foundation, and the Superior National Forest. We also thank the NSF LTER program (DEB 0620652) for support.

Keywords

  • Great Lakes
  • N mineralization
  • NPP
  • PnET
  • disturbance
  • foliar N

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