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History and General Description of the Dynamic Global Vegetation Model MC1

Dominique Bachelet

Conservation Biology Institute, Corvallis, Oregon, USA

ABSTRACT

The model MC1 was designed during the second phase of the Vegetation Ecosystem Modeling and Analysis Project (VEMAP), a collaborative multiagency project designed to simulate and understand ecosystem dynamics for the continental United States [VEMAP members, 1995]. The goal was to focus on transient vegetation dynamics and to link biogeography and biogeochemistry models so that the trajectory of ecosystems between historical and future time periods could be simulated. The model was designed to simulate the potential vegetation that would occur without direct intervention by industrialized societies. Since then, applications of MC1 have included effects of humans on vegetation through cattle grazing and fire suppression as well as direct (CO2) and indirect (climate) effects of increasing greenhouse gas concentrations. The MC1 model has been used in many projects, at various spatial scales (50 m-50 km) and for different spatial domains (national parks to global) as illustrated by over 80 reports and publications using its projections of vegetation response to climate change. This chapter briefly describes its history and its design.

1.1. MODEL HISTORY

To prepare for the effects of climate change on terrestrial ecosystems, it is essential to understand how climate has driven vegetation distribution and the carbon cycle in the past and how it may affect them in the future. It is well recognized that land use may have transformed some landscapes more than climate, but future land use changes will depend on social and political decisions that are impossible to forecast while climate models can provide robust projections of climate futures. Moreover, anthropogenic influences do not affect all ecosystems equally. Many ecosystems still strongly reflect direct climatic influences, and their response to climate change is likely to influence the ecosystem services they provide. While farmers have access to management alternatives (irrigation, fertilizers, pesticides, genetically modified annual crops) that can alleviate some of the more negative effects of weather, foresters and pastoralists have adapted their management practices to account for climatic influences and will continue to do so, benefiting from projections of natural vegetation responses to change. Therefore many climate change research projects have focused on understanding the effects of future climate on natural vegetation.

The Vegetation Ecosystem Modeling and Analysis Project (VEMAP) was a collaborative multiagency project designed to simulate and understand ecosystem dynamics in the conterminous United States [VEMAP members, 1995]. During the first phase of VEMAP, potential vegetation maps for historical and for future conditions were generated by the static biogeography models MAPSS (Mapped Atmosphere Plant Soil System) [Neilson, 1995], BIOME2 [Prentice et al., 1992], and DOLY (Dynamic glObaL phytogeographY) [Woodward et al., 1995] using 30-year average observed as well as projected climate data, providing instantaneous snapshots of what was (historical starting point) and what might become (future endpoint) the vegetation distribution over the country without describing the path it might follow to get there. The gridded vegetation maps produced by the static models were then provided to three biogeochemistry models, CENTURY [Parton et al., 1987, 1988, 1993], BIOME-BGC (Biome BioGeochemical Cycle) [Hunt and Running, 1992; Running and Hunt, 1993], and TEM (Terrestrial Ecosystem Model) [McGuire et al., 1992; Melillo et al., 1993; Tian et al., 2000], to calculate the carbon stocks that matched the simulated vegetation type for these two time periods. Phenology and fire disturbance were prescribed in all cases. The underlying assumption was that chronic change was happening and that ecosystem trajectories between 2000 and 2100 were linear. However, scientists believed this assumption might be wrong and wanted to create a model that could explore transient ecosystem dynamics during the 21st century. One of the hypotheses was that land could first "greenup" with warmer temperatures but instead of increasing its productivity continuously until 2100 could be affected by the exceedence of a particular climatic threshold causing a "browndown" driven by increasing evaporative demand and drought stress associated with vegetation shifts, declines in productivity, and carbon losses.

During the second phase of VEMAP, instead of focusing on instantaneous snapshots of what might happen in terms of vegetation type change and concurrent shifts in the location of carbon sources and sinks, the goal was to focus on year-to-year variations and link biogeography and biogeochemistry models so that the trajectory of the ecosystems between historical and future time periods was simulated. At the time there were only a couple of research groups addressing this issue. A team composed of Oregon State University scientists including Chris Daly, Jim Lenihan, and Dominique Bachelet, under the leadership of USFS Ron Neilson and with financial support from the USDA Forest Service, started to link the biogeography rules adapted from the MAPSS biogeography model [Neilson, 1995] to a modified version of the CENTURY biogeochemistry model [Metherell et al., 1993] in order to create what was to become the model MC1 [Bachelet et al., 2001a, 2003]. Two other VEMAP-related projects emerged to link biogeochemistry models and biography models, MAPSS with BIOME-BGC (the BIOMAP model, originally started by Ron Neilson, now retired, remains under construction by John Kim, USFS), MAPSS with TEM (project lead by Jeff Borchers terminated before the new model was finished). Neither of the two latter projects provided usable DGVMs to this date. Other combinations of models were never explored by other group members despite the original project objectives.

For MC1, climate-based rules were extracted from the MAPSS biogeography model while the species-specific set of parameters in the CENTURY biogeochemistry model were replaced by globally relevant lifeform parameters. These parameters were defined so as to vary continuously with the fraction of each lifeform under different climate conditions. On the basis of climate zones and a few climatic indices (growing season precipitation, mean monthly minimum temperature), lifeform combinations were used to specify general vegetation types (e.g. maritime evergreen needleleaf forest) defined further by biomass thresholds [unlike the MAPSS model approach of using leaf area index (LAI)-based on an optimized hydrological budget-and ignoring the carbon budget]. The CENTURY code was modified, and only the "savanna" mode was implemented whereby grasses and trees competed for resources at all time. 1 Moreover, deep water was made accessible only to tree roots and surface nitrogen was preferentially accessible to grasses. The first area where the model was tested (at 50-m resolution) and competition between trees and grasses simulated at an existing ecotone, was Wind Cave National Park in South Dakota [Daly et al., 2000; Bachelet et al., 2000].

Since then, the MC1 model has been used in many projects, at various spatial scales and for different domains. After Lenihan et al. [2003] started producing results for the state of California, Galbraith et al. [2006] considered MC1 projections as "an essential first step" for an integrated assessment of the potential overall effects of climate change on the status and distribution of California's major vegetation communities. Gucinski [2005] was one of the first to use it for natural resource management purposes. It was later used at the Nature Conservancy to anticipate and plan for potential biome shifts under warming climates [Aldous et al., 2007] and to design sustainable strategies for prairie chicken conservation [McLachlan et al., 2011]. Projections of changes in fire regimes [Bachelet et al., 2008] have been used for regional climate change assessments [e.g., Kueppers et al., 2009; Halofsky et al., 2014]. They and other model results were included in climate change adaptation reports [e.g., Doppelt et al., 2008, 2009; Halofsky et al., 2011] and used in various workshops [e.g., Barr et al., 2010, 2011; Koopman et al., 2010, 2011] where stakeholders had an opportunity to learn to interpret model results and discuss implications. An up-to-date list of publications that have included MC1 results as an important part of the work published is available in Appendix 1.

To expand the visibility and use of the model, the MC1 code has been made available under version control and is currently provided through an Oregon State University website (https://sites.google.com/site/mc1dgvmusers/home/mc1-source-repository-at-the-osu-biological-ecological-engineering-dept). A webpage was designed specifically for MC1 users interested in learning about the latest code revisions (https://sites.google.com/site/mc1dgvmusers/). In 2010, a users' network was created to share MC1 code updates and simulation-related issues between users (http://groups.google.com/group/mc1-dgvm-users). An MC1...