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FBGC Projects

Wildlife HSI
CLIMET
TIPPING POINTS
FIRECLIM
PALEOBGC
Cross-Model Comparison
Predicting Lynx Habitat
WildFIRE PIRE
GRAZE-BGC
FISHFRY
GNLCC

 

Wildlife HSI

Modeling wildlife habitat suitability under potential future climate regimes, with incorporation of potential management strategies to restore and sustain critical habitat.

We are using the FireBGCv2 modeling platform to evaluate shifts in wildlife habitat suitability resulting from climate changes and shifting disturbance regimes. Landscape- and species-specific habitat suitability indices reflect potential occupancy based on dominant vegetation species and structural composition. These landscape attributes vary with changes in climate and following disturbance events such as wildfires or mountain pine beetle epidemics. Wildlife habitat suitability models can be used to 1) assess the potential of current landscapes to support specific wildlife species; 2) evaluate the effects of projected changes in climate and disturbance on landscape vegetation/habitat suitability; and 3) test suites of management strategies for restoring or maintaining critical habitat under future climate regimes.

We have developed wildlife habitat suitability index (HSI) models for grizzly bears and Canada lynx in Glacier National Park, and are incorporating avian HSI models for species in Montana and Oregon. For more information on avian research visit the Birds and Burns Network.

Photos: Some of the wildlife species included in  the project – Elk and grizzly bear

elkbears

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CLIMET

Understanding species migration and fire dynamics under future climates

We incorporate multiple potential future climate regimes spanning a range of warm-wet and hot-dry conditions, and couple these with varying levels of fire management treatments and disturbance processes such as mountain pine beetle epidemics and white pine blister rust to evaluate the isolated and synergistic effects of climate, wildfires, and other disturbance on species distributions, vegetation structure, carbon balance, fuels accumulation, wildlife habitat suitability, and hydrologic dynamics. In addition, we evaluate climate effects on wildfire spatial patterns and severity, and test a variety of landscape restoration treatments under potential future climate regimes. Our results are synthesized across the simulation landscapes to quantify landscape vulnerabilities and potential climate- and wildfire-driven shifts in processes and functions across ecological gradients.

climet mapImage: climet map

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TIPPING POINTS:

Assessing critical climate-driven thresholds in landscape dynamics using spatial simulation modeling: climate change tipping points in fire management.

 

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FIRECLIM

Assessing and adaptively managing wildfire risk in the wildland-urban interface for future climate and land use changes.
The effects of climate change and land and wildland fire management agencies’ decisions on fuel loads, area burned, and ecological conditions in WUIs will be simulated at the 30-m2 resolution using a GIS-based, mechanistic ecological modeling system that integrates the FSPro (Fire Spread Probability), Fire-BGCv2 (BGC stands for biogeochemical), FARSITE (Fire Area Simulator), and FlamMap models. FSPro (Fire Spread Probability) will be used to simulate fire ignitions in each WUI. FSPro is a spatial model that calculates the probability of fire spread from a current fire perimeter or ignition point for a specified time period (McDaniel undated). Fire-BGCv2 will be used to simulate tree growth, organic matter decomposition, litterfall and other ecological processes using detailed physical biogeochemical relationships. Fire-BGCv2 is a spatially-explicit, stochastic, tree succession model that produces a spatial simulation of fire on a landscape (such as a WUI) and assesses the effects of fire on ecosystem conditions (Keane et al. 1996ab; 1997; 1999) using probability functions with ecologically-derived parameters. Primary canopy processes of interception, evaporation, transpiration, photosynthesis, and respiration are simulated at a daily time step at the stand-level. Driving variables for these processes will be taken from daily weather data extrapolated across the WUI using the DAYMET program and database (Thorton et al. 1997). DAYMET generates daily surfaces of temperature, precipitation, humidity, and radiation over large regions of complex terrain (http://www.daymet.org/). Fire ignition will be stochastically simulated based on weather and fuelbed characteristics.  First, the project area landscape will be projected forward in time for 100 years under the various climate change and land management scenarios and various maps of landscape conditions, including fuels, vegetation, and productivitiy, will be output every 10 years.  These maps will be used as inputs to FSPro, FARSITE, and FLAMMAP to calculate spatially explicit maps of fire risk and hazard.  Growth, spread (i.e., area burned), and behavior of fire will be mechanistically computed using the Rothermel (1972) fire spread model as implemented in the FARSITE model (Finney 1998). FARSITE is a fire behavior and growth simulation model that simulates the spread of wildfires across a landscape (USDA Forest Service 2003) (Figure 7). Average simulated fire behavior across stands in a WUI will be used to calculate fuel consumption and tree mortality (Keane et al. 1996a). The area burned under each CLEW future and for each year of the evaluation period will be estimated by inputting simulated fuel loads and landscape attributes for pixels to the FARSITE and FlamMap models (Finney et al. 1998; Farris et al. 1999). FlamMap is a fire behavior mapping and analysis program that computes potential fire behavior characteristics (i.e., spread rate, flame length, fireline intensity, etc.) over an entire FARSITE landscape for constant weather and fuel moisture conditions. FSPro, Fire-BGCv2, FARSITE, and FlamMap will be used to simulate landscape and fire dynamics in all future WUIs in Flathead County (and possibly pixels adjacent to the boundaries of WUIs) for three to four land and wildland fire management practices and three climate change scenarios over a 50-year period at a 30-m2 pixel resolution. Management practices will be implemented across WUIs based on parameters (e.g., treatment stand characteristics, acres treated per year, and harvest diameter ranges) specified by the project team in collaboration with the land and wildland fire management agencies’ panel.  The effects of management practices and climate scenarios on ecological conditions in WUIs will be evaluated based on the concept of historical range of variability (HRV) (Holsinger et al. 2006). In particular, spatial and tabular output from the Fire-BGCv2 model from a 5,000-year simulation parameterized with historical fire regime and weather data will be compared to the simulations of future landscapes under alternative management practices and future climate scenarios to determine how close or departed the future simulated landscapes are from their HRV.

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PALEOBGC

Linking the past with the future: Reconstruction of historic and prehistoric ecosystem dynamics through integration of fire and forest histories and dynamic ecosystem modeling.

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Cross-Model Comparison

Comparison of process scales and climate change drivers among three vegetation-fire simulation modeling platforms: FireBGCv2, MC1, and Climate-FVS.

Image: cross model map

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Predicting Lynx Habitat

Managers can use simulation modeling to understand future conditions and test how different management treatments might affect wildlife habitat. Simulations are useful when attempting to assess future impacts of climate change, since there is no precedent managers can use for reference. Modeling also allows for landscape-level analysis, which is particularly important for wide-ranging species.

FFS research ecologists Robin Silverstein and Robert Keane, coordinating with the Rocky Mountain Research Station wildlife unit, are testing the use of simulation modeling to predict future habitat suitability for Canada lynx (Lynx canadensis). The Canada lynx is a specialist predator feeding primarily on showshoe hare. Snowshoe hare have specific habitat requirements that are, therefore, shared by Canada lynx: areas of high-altitude forest with dense cover of shrubs and saplings. Studying a portion of the Flathead National Forest northeast of Big Fork, Montana, the researchers have modeled future scenarios that vary by climate change, fuel treatments, and fire suppression. Results suggest that climate change and fuel treatments at expected future levels do not affect lynx habitat very much. However, fire suppression has a much more noticeable impact on lynx habitat.

These findings illustrate the important role fire plays in first providing and then removing quality lynx habitat. Lynx and snowshoe hare require a density of understory vegetation that primarily occurs about 10 to 20 years after fire. Without fire, the succession of plants moves beyond the structural stage snowshoe hare prefer for hiding cover. When fire is too frequent, the succession cycle is continually restarted and fails to reach the intermediary stages considered quality lynx habitat. The current level of fire suppression, set to 90 percent in the model, maintained more quality lynx habitat then allowing natural fires to burn. This result may be an artifact of nearly a century of fire suppression yielding a forest that simply can’t be returned to natural conditions in the current climate without consequences to wildlife. This work provides important insights into the long-term preservation of wildlife habitat as well as adapts vegetation and disturbance simulation model to the field of wildlife habitat modeling.

Photo: Example of Lynx habitat suitability maps at future 10-year intervals under climate change without fire suppression or fuel treatments.

Example of Lynx habitat

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WildFIRE PIRE

Feedbacks and consequences of altered fire regimes in the face of climate and land-use change in Tasmania, New Zealand, and the western U.S. (http://www.wildfirepire.org/)
While field studies of wildland fire dynamics provide the foundation for fire sciences, ecological modeling has a critical role by allowing field data to be integrated with other ecological research to explore fire interactions in space and time.  Simulation modeling provides an effective, standardized, and objective context to evaluate fire regimes and ecological change.  Mechanistic landscape models can be used to explore fire, climate, and vegetation interactions and to quantify fire regimes in space and time. Most importantly, simulation models can help predict potential fire dynamics under future climates to provide fire scientists critical information to mitigate any adverse effects. Last, and most importantly, models can be used to extrapolate and expand field study results across large temporal and spatial scales. 
We will apply the FireBGCv2 model to three 50-100K ha landscapes; 1) Yellowstone National Park in the United States, 2) a landscape in New Zealand to be named later, and 3) a landscape in Tasmania to be named later.  The resolution, extent, and detail of the landscapes will be decided in future.  All modelers will be encouraged to apply their models to these three landscapes but they will be responsible for teaching the model to the post-doc.  All input map layers, parameterizations, and initial conditions will be documented and posted to the web site.  The YNP study landscape has been sampled and all digital maps have been collected and can be posted by September 2011.  Information on the Tasmania or New Zealand study landscapes will either be supplied by the cooperators or collected by the Wildfire-PIRE personnel.
We will explore landscape-climate-fire-vegetation dynamics using FireBGCv2 and all other models using a simulation experiment that employs scenarios to describe model behavior under various conditions.  Under this format, we will specify a set of scenarios that are designed to emphasize differences in model behavior over diverse climate, fire, and vegetation conditions.  Presented here is the draft experimental design; the actual simulation experiment design will be formalized over Year 2 through interaction with modelers and Wildfire-PIRE collaborators.  The following primary scenarios and levels will be simulated:

  • Climate.  Four different climate scenarios will be simulated
    • Historical climates.  Paleoclimatic scenarios will be developed by the Wildfire-PIRE scientists and used as input to the model.
    • Contemporary scenario.  Taken from weather data collected for the target landscapes.
    • B2 scenario – Warm Moist.  A synthesis of the B2 scenario will be compiled from the seven GCMs for each landscape.
    • A2 scenario – Warm Dry. A synthesis of the A2 scenario will be compiled from the seven GCMs for each landscape
  • Fire Ignitions. Several fire scenarios will be simulated to mimic past, current, and future fire ignition patterns.
    • Lightning ignitions. Random ignition patterns will be simulated.
    • Aboriginal ignitions.  Ignition patterns will be simulated based on spatial data of past aboriginal land use.
    • Future ignitions. A digital layer of future ignition probabilities will be developed based on predicted land use and fire management plans.
  • Exotic Invasion.  Two scenarios will be used to explore the effect of exotic invasions on fire regimes and vegetation dynamics.
    • No exotics.  Only native species will be modeled.
    • Exotics.  Exotic species will be included in the simulation.

Many response variables will be used to detect changes between scenarios and models.  These response variables are scale dependent and reflect the variables need to successfully complete the simulation objectives.  They are output in tables and digital maps. They can be modified and others can be added later:

  • Landscape. Fire rotation (yr), fire return interval (yr), carbon (kg/m2, NPP, NEP, GPP, NEE, fireC, abovegroundC, belowgroundC), pollen load, charcoal deposition.
  • Stand. Fuels (coarse woody, fine woody, litter, duff, shrub, herb), carbon (same as above), structure (dominant species, canopy cover, basal area, density), exotics (abundance)
  • Fire. Fire intensity, severity, tree mortality, fuel consumption, carbon emissions.
  • Tree. Species distribution and species.

Models will be initialized using local vegetation, fire, topography, soils, and climate data collected for each landscape.  Parameterization of the models will be done for each landscape using data collected during past studies, literature reviews, and Wildfire-PIRE data collection.   We will run the model for 500 years and output response and explanatory variables are decadal timesteps.  We will also output maps of fire intensities, severities, and vegetation composition.  For the paleoclimatic scenarios, we will run the model for 14,000 years to attempt to replicate the paleo-record of pollen and charcoal.  Results will be analyzed using MANOVA, regression tree, and multivariate techniques to determine the subtle differences and similarities between and across the three landscapes by scenario.

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GRAZE-BGC

Strategic role of large herbivore grazing on succession, fuels, and fire dynamics in a changing climate.

Vegetation mosaics are shaped by multiple driving factors that interact across time and space.  Climate, fire, forest practices, and grazing by large herbivores typically operate together in landscapes, and interactions and feedbacks among these factors can challenge efforts to predict vegetation dynamics.  Succession and episodic disturbance can be modeled interactively with spatially-explicit Landscape Fire Succession Models (LFSMs), but these models have yet to fully integrate ungulate herbivory as an interactive driver of succession. We modified a complex LFSM, FireBGCv2, to include a spatially-explicit herbivory module, GrazeBGC. The resulting system integrates multi-herbivore stocking, inter- and intra-specific forcing of grazing intensity, and herbivore dietary selectivity to modify fuels, which contribute to landscape fire regimes. A full factorial experiment in a 9,000-ha grass-tree mosaic with five grazing regimes (no herbivores, wildlife-only, livestock-only, wildlife + livestock, wildlife + double livestock), three climates (historical, B2: +3oC, A2: +6oC) and two fire-management scenarios (historical fire, fire suppression) generated interactive influences on spatially-explicit undergrowth biomass (shrub, herb, total) and surface-fire (intensity; flame length; scorch height; soil heat; smoke CO, CO2, CH4, PM2.5). Effects increased with herbivore biomass demand, but also with biophysical site productivity, fire-suppression, and climate change. Multi-species grazing that approximated historical herbivore populations significantly modified stand-scale biomass and fire behavior, but less intense grazing regimes that involved only wildlife or only livestock were less effectual. However herbivory’s effects at that scale were contingent on the landscape’s future regimes for fire suppression and climate, which together interacted with herbivory to modify the accrual of undergrowth biomass over time. Stand-scale effects of grazing affected the landscape’s fire-return interval as well, but otherwise did not “scale up” to significantly modify respiration, primary production, carbon, or the total area burned by individual fires. As modeled here, potential climate change and future fire suppression exerted stronger effects on fire behavior and metabolism at landscape scale than did herbivory, probably because those agents influenced more fuel components than did herbivores in this forest-dominated vegetation mosaic.

Image: grazing

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FISHFRY

Wildland fire affects native fishes sin the Rocky Mountain West by removing riparian vegetation, increasing solar radiation to the stream, and leading to warmer summer water temperature.
Thermal regimes in freshwater ecosystems are warming in response to increases in air temperature associated with global climate change.  Projected changes in climate are also expected to change fire regimes across the western US, which could increase stream temperatures by reducing shading associated with near-stream vegetation. We linked a statistical regression model predicting daily stream temperatures to a spatially explicit landscape fire and vegetation model (FireBGCv2) to explore interactions among vegetation, disturbance, climate and hydrology across a montane landscape in the Northern Rocky Mountains.  Specifically, we were interested in how stream temperatures might respond to future climate change (i.e. A2, B2 climate scenarios) in a fire-prone watershed and the role that fire management actions such as fuel reduction and fire suppression could play in tempering stream thermal responses. We found that basin scale air temperature increases associated with future climate scenarios would account for a larger proportion of stream temperature increases than changes in wildfire regimes. Moreover, imposing various fire management strategies to limit the prevalence of wildfires had no discernible effect on basin scale stream temperature patterns. These patterns emerge because wildfires typically affect only a subset of streams in a network and because climate-induced shifts to fire and vegetation patterns promoted transition from a historically mixed to a non-lethal surface fire regime where lower fire severities lessened effects on stream temperature.  Additional refinement is needed to improve techniques for estimating fire disturbance effects on stream temperature, but this study indicates that although wildfire may cause locally important, short-term increases in stream temperature, rising air temperatures from climate change will be the primary factor that causes departures from historical stream temperatures in this mountainous watershed. 

photo: fish

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GNLCC

Whitebark pine (Pinus albicaulis) forests are declining across most of their range in North America because of the combined effects of mountain pine beetle (Dendroctonus ponderosae) outbreaks, fire exclusion policies, and the exotic pathogen Cronartium ribicola, which infects five-needle white pines and causes the disease white pine blister rust. Predicted changes in climate may exacerbate whitebark pine decline by (1) accelerating succession to more shade tolerant conifers, (2) creating environments that are unsuitable for the species, (3) increasing the frequency and severity of mountain pine beetle outbreaks and wildland fire events, and (4) facilitating the spread of blister rust. Yet, whitebark pine tolerates a variety of stressful conditions and has the broad genetic diversity to adapt to changes in climate and disturbance. The on-going decline in this high-elevation tree species poses serious consequences for upper subalpine and treeline ecosystems and, as a consequence, whitebark pine is now a candidate species for listing under the Endangered Species Act. The large, nutritious seeds produced by this pine are an important food for many bird and mammal species, and whitebark pine communities provide nesting sites and habitat for many other wildlife species. Whitebark pine seeds are dispersed long distances by Clark’s nutcrackers (Nucifraga columbiana), which cache seeds in a variety of terrain and community types, including recent burns and other disturbed areas. The unclaimed seeds often germinate and produce hardy seedlings. These seedlings can survive on harsh, arid sites, and act as nurse trees to less hardy conifers and vegetation. Since more than 90 percent of whitebark pine forests exist on public land in the United States and Canada, a trans-boundary, range-wide whitebark pine restoration strategy was developed to coordinate and inform restoration efforts across federal and provincial land management agencies. However, this restoration strategy failed to fully address projected effects of climate change on whitebark pine restoration efforts and existing stands. In this report, we present guidelines for restoring whitebark pine under future climates using the range-wide restoration strategy structure. General restoration guidelines considering effects of climate change are given to each of the strategy’s guiding principles: (1) promote rust resistance, (2) conserve genetic diversity, (3) save seed sources, and (4) employ restoration treatments. We then provide specific guidelines for each of the strategy’s actions: (1) assess condition, (2) plan activities, (3) reduce disturbance impacts, (4) gather seed, (5) grow seedlings, (6) protect seed sources, (7) implement restoration treatments, (8) plant burned areas, (9) monitor activities, and (10) support research. We used information from two sources to include climate change impacts on whitebark pine restoration activities. First, we conducted an extensive and comprehensive review of the literature to assess climate change impacts on whitebark pine ecology and management. Second, we augmented this review with results from a comprehensive simulation experiment using the spatially explicit, ecological process model FireBGCv2 that simulated various climate change (RCP4.5 and RCP8.5), management (thinning and prescribed burning, planting), and fire exclusion (90 percent suppression, 50 percent suppression, no suppression) scenarios. We analyzed two simulated response variables (whitebark pine basal area, proportion of the landscape that is whitebark pine dominated) to explore which restoration scenarios have the best chance of succeeding in the future. We also ran FireBGCv2 to evaluate the effects of specific rangewide restoration actions with and without climate change. Our findings indicate that, with management intervention in the form of planting rust-resistant seedlings and employing proactive restoration treatments, whitebark pine can be returned to the high mountain settings of western North America to create resilient upper subalpine forests of the future. The report is written as companion guide to the rangewide restoration strategy for planning, designing, implementing, and evaluating fine-scale restoration activities for whitebark pine by addressing climate change impacts.

Photo: gnlcc project

Photo: gnlcc project

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Modified: Apr 19, 2016