The LANDIS-II Foundation is hosting a training workshop this summer for new LANDIS-II users in Portland, OR. The training will be held , and and will precede the Ecological Society of America Meeting, also in Portland.
The LANDIS-II training is designed for those interested in learning how to use LANDIS-II. The course will be led by Drs. Melissa Lucash and Robert Scheller, with additional instructors to be determined. The course will cover parameterizing and analyzing the outputs of multiple LANDIS-II extensions, including forest succession (including NECN/ Century), fire, wind, harvesting, and insects.
The total cost of the 2-day training session is $300 and includes two complementary lunches and a copy of the latest LANDIS-II training manual. Sessions will be held on the Portland State University campus. Participants will be expected to bring their own laptop computer with LANDIS-II installed (instructions provided).
If you’d like to reserve a spot for the training session, please email Dr. Lucash at email@example.com. Please register early if you’d like to attend, as the training is limited to 25 participants.
Eric J. Gustafson, Northern Research Station, Rhinelander WI, USA
Because LANDIS-II is being used to make projections under novel environmental conditions that have no empirically observed analog (e.g., climate change), it is becoming critical to strengthen the links between the fundamental drivers of tree cohort growth and competition (temperature, precipitation, CO2 concentration) within the process extensions of LANDIS-II. A more mechanistic approach (PnET-Succession) to simulating growth within LANDIS-II was recently developed by De Bruijn et al. (2014) by embedding algorithms of the PnET-II stand-level ecophysiology model (Aber et al. 1995) within the Biomass Succession extension to more mechanistically simulate growth as a competition for light and water to support photosynthesis. Where the Biomass Succession extension simulates growth and competition among tree species cohorts using an average maximum aboveground net primary productivity that is not linked to weather extremes within a time step, PnET-Succession mechanistically simulates photosynthesis monthly using physiological attributes such as light and water use efficiency and drought tolerance. PnET-Succession models soil water monthly as a function of soil texture, precipitation, interception, evaporation and consumption by trees (similar to DGVMs), allowing response to extreme drought events rather than being limited to the mean weather values (typically decadal) used by less mechanistic approaches. Accordingly, photosynthetic rates (and respiration rates) vary monthly by species and cohorts as a function of precipitation and temperature (among other factors, including CO2 concentration), which directly affect competition and ultimately successional outcomes.
The opportunities afforded by this approach for simulating climate change effects on forests are significant. First, because there are several parameters related to drought-tolerance (including cohort establishment and CO2 effects on conductance) and temperature effects (on photosynthesis and respiration), the differential effects of climate on the ability of species to compete can result in altered successional outcomes through time. These outcomes are an emergent property of the mechanistic simulation of growth that accounts for the monthly interaction of precipitation, temperature, light (including seasonal cloudiness), CO2 concentration and species’ physiological attributes, rather than phenomenological estimates of their combined effects based on behavior seen under past conditions. Second, because the extension tracks carbon reserves, drought and competition induced growth reductions can cause carbon reserves to become depleted by respiration, which can result in direct mortality (McDowell et al. 2013), or the level of carbon reserves can be used by disturbance extensions to realistically target disturbance-induced mortality to stressed cohorts (complete or partial mortality of cohorts). Physiological water stress may be dependent on either the intensity or duration of water limitations (or both) depending on the ability of a species to extract water from the soil and maintenance respiration rates, including interactions with all the other factors that affect growth (e.g., light, temperature, CO2). Physiological light or temperature stress is similarly dependent on the intensity and duration of shading and heat waves. For studies of the effects of climate change on forest successional dynamics, a weather stream of temperature, precipitation and radiation from downscaled global circulation models can allow growth and establishment rates to vary monthly, rather than using longer-term averages that make it difficult to simulate extreme events. Mortality is simulated when moisture, heat or light stress depresses growth rates below respiration levels long enough to reduce carbon reserves below survival thresholds, or when a disturbance targets stressed cohorts.
This more mechanistic approach to modeling drought effects at landscape scales is conceptually appealing because of its reliance on first principles and ecological theory, but it does require more input parameters and therefore increases parameter uncertainty. However, less mechanistic approaches result in uncertainty when extrapolating phenomenological relationships beyond the domain in which they were developed to the novel conditions of the future (Keane et al. in press). Thus, both approaches result in uncertainty, but the extrapolation uncertainty of phenomenological approaches has increasingly been deemed to exceed the parameter uncertainty of mechanistic approaches (Cuddington et al. 2013, Gustafson 2013). The more mechanistic approach also increases run times, but because the mechanistic approach causes many cohorts to die before their longevity age, fewer cohorts must be simulated, resulting in only modest performance declines.
Some tests of PnET-Succession have been conducted. Gustafson et al. (2015) used it to predict the outcome of a precipitation manipulation experiment in a piñon-juniper ecosystem in New Mexico (USA), with considerable success. Importantly, they discovered that the amount of non-structural carbon reserves (NSC) predicted by PnET-Succession was negatively related to the incidence of mortality on experimental plots. Another test of the ability of the extension to predict cohort mortality as a function of drought in more diverse forest of the upper Midwest was recently completed (Gustafson et al. in review). A more comprehensive evaluation of the response of Midwestern species assemblages to variation in temperature, precipitation and cloudiness is underway (Gustafson et al. in prep). PnET-Succssion is also being used for climate change research by Jonathan Thompson and Matthew Duveneck (Harvard University) and Renaud Colmant (FAO, Rome).
PnET-Succession was officially released on the LANDIS-II website in August 2015.
Aber JD, SV Ollinger, CA Federer et al. 1995. Predicting the effects of climate change on water yield and forest production in the northeastern United States. Climate Research 5:207-222.
Cuddington K, Fortin M-J, Gerber LR, Hastings A, Liebhold A, O’Connor M, and Ray C. 2013. Process-based models are required to manage ecological systems in a changing world. Ecosphere 4, 20, http://dx.doi.org/10.1890/ES12-00178.1.
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 EJ. 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.
Gustafson, E.J., A.M.G. De Bruijn, M.E. Kubiske, R. E. Pangle, J.-M. Limousin, N. McDowell, B.R. Sturtevant, J. Muss, W. T. Pockman. 2015. Integrating ecophysiology and forest landscape models to better project drought effects under climate change. Global Change Biology 21:843–856, doi: 10.1111/gcb.12713.
Gustafson, E.J., A.M.G. De Bruijn, B.R. Miranda, B.R. Sturtevant. in review. Mechanistic modeling of drought effects on landscape forest succession. Ecosphere.
Gustafson, E.J., A.M.G. De Bruijn, B.R. Sturtevant, B.R. Miranda. in prep. Using first principles to increase the robustness of forest landscape models for projecting climate change impacts. Outlet TBD.
Keane RE, Miller C, Smithwick E, McKenzie D, Falk D, Kellogg L. in press. Representing climate, disturbance, and vegetation interactions in landscape models. Ecological Modelling.
McDowell NG, Fisher RA, Xu C, et al. 2013. Evaluating theories of drought-induced vegetation mortality using a multimodel–experiment framework. New Phytologist 200:304–321.
Introducing LANDIS-II version 6.1!
This latest version of the LANDIS-II core includes just a few minor changes requested by the user community. Please consult the release notes for details on the specific changes that were made. For those wishing to upgrade, we recommend uninstalling version 6.0 before upgrading to 6.1. Unfortunately this does also entail re-installing all of your extensions.
LANDIS-II version 6.1 has been tested and found to be compatible with extensions than run under version 6.0, but if you run into any problems don't hesitate to let us know.
We have just published the third edition of our definitive guide to using LANDIS-II, 'Forecasting Forested Landscapes: An Introduction to LANDIS-II with Exercises' The book provides a broad introduction to forest landscape modeling generally, LANDIS-II specifically, and it includes the same exercises used in our regular training sessions (see above).
The book is on sale at: https://www.createspace.com/5464520. All proceeds go to The LANDIS-II Foundation to maintain the model and supporting systems.
Attached here is the Summer 2014 Newsletter. Thanks for all contributions and be sure to tell us when you have a new publication or if you would like your own project page.
The Age-only Succession extension has been updated to version 4.0. Version 4 allows for dynamic probability of establishment over time.
The other base extensions (disturbance and output) were also updated so that their example files are compatible with Age-only Succession v4. There were no other substantial changes to the base disturbance and output extensions.
A proposal (attached) has been approved by the Technical Advisory Committee to modify the Biomass Extensions. The revised extensions will be released in mid-July 2014.
We have just published our definitive guide to using LANDIS-II, 'Forecasting Forested Landscapes: An Introduction to LANDIS-II with Exercises' The book provides a broad introduction to forest landscape modeling generally, LANDIS-II specifically, and it includes the same exercises used in our regular training sessions (see above).
The book is on sale at: https://www.createspace.com/4771081. All proceeds go to The LANDIS-II Foundation to maintain the model and supporting systems.
We held our first LANDIS-II training session at Harvard Forest (HF) this week (4/8- 4/10). The class was taught by Drs. Lucash (PSU), Duveneck (HF) and Thompson (HF). There were 10 attendees from U. VT, U. Maine, Harvard Forest, U. Montreal, UQAT (Canada), and Bournemouth U. (U.K.). The first two days were similar to past training sessions but the final day was devoted to our first four hour Century training workshop. It went well! Thanks to all the instructors and participants.