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Forest Disturbance Processes


More on LANDIS-II

LANDIS-II models forest succession, disturbance (including fire, wind, harvesting, insects, global change), and seed dispersal across large (>1 million ha) landscapes. 

Featured Publication

Gustafson, E.J., A.M.G. De Bruijn, M.E. Kubiske, Robert E. Pangle, Jean-Marc Limousin, Nate McDowell, B.R. Sturtevant, Jordan Muss, William T. Pockman.  2015.  Integrating ecophysiology and forest landscape models to better project drought effects under climate change.  Global Change Biology 21:843–856.  

Increasing the reliability of predictions of the landscape effects of climate change

Research Issue

[photo:] Precipitation manipulation experiment in a piñon pine - juniper ecosystem at the Sevilleta Long Term Ecological Research (LTER) site at the Sevilleta National Wildlife Refuge in central New Mexico, USA.Climate change is producing new environmental conditions that have not existed for study in the scientific age.  It is quite possible that many of the empirically-derived relationships developed under the conditions of the past for predicting forest dynamics will be rendered obsolete by climate change.  For example, forest growth and yield models are based on empirical relationships measured nearly a century ago when CO2 and temperatures were lower.  Recent research suggests that tree growth in the Midwest may be up to 20% higher in the current century because of CO2 fertilization.

Our Research

We developed a new approach (PnET-Succession) to simulate forest growth and competition within the forest landscape model, LANDIS-II.  The approach increases the use of mechanistic relationships based on “first principles” (fundamental and unequivocally known) to directly link tree growth, competition and death to temperature, precipitation and CO2 concentration.  The PnET-Succession extension of LANDIS-II incorporates components of the widely used PnET-II ecophysiology model.  When coupled with mechanistic disturbance extensions (e.g., wildfire, insect outbreaks, timber harvest) within the LANDIS-II modeling platform, the outcome of the complex interactions among tree growth and competition for light and water, changing disturbance regimes and increasing incidence of warm and drought years can be reliably predicted for large forested landscapes over century time scales.

Expected Outcomes

Forest landscape models that make more reliable projections under climate change are expected to provide critical and reliable insights about the relative effectiveness of alternative forest management strategies to maintain ecosystem goods and services into the distant future.

Research Results

Gustafson, E.J.; De Bruijn, A.M.G.; Kubiske, M.E.; Pangle, Robert E.; Limousin, Jean-Marc; McDowell, Nate; Sturtevant, B.R.; Muss, Jordan; Pockman, William T.  2015.  Integrating ecophysiology and forest landscape models to better project drought effects under climate change.  Global Change Biology 21:843–856.  

De Bruijn, A.; Gustafson, E.J.; Sturtevant, B.R.; Foster, J.R.; Miranda, B.R.; Lichti, N.I.; Jacobs, D.F.  2014.  Toward more robust projections of forest landscape dynamics under novel environmental conditions: embedding PnET within LANDIS-II.  Ecological Modelling 287:44–57. 

Gustafson, E.J.; Keane, R.E.  2014.  Predicting Changes in Forest Composition and Dynamics – Landscape-scale Process Models.  Online: https://www.fs.usda.gov/ccrc/topics/process-models. 

Gustafson, E.J.  2013.  When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world.  Landscape Ecology 28:1429-1437. 

Research Participants

Principal Investigator

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Last Modified: April 1, 2015