Rachel A. Loehman

The FireBGCv2 landscape fire and succession model: a research simulation platform for exploring fire and vegetation dynamics

Fire management faces important emergent issues in the coming years such as climate change, fire exclusion impacts, and wildland-urban development, so new, innovative means are needed to address these challenges. Field studies, while preferable and reliable, will be problematic because of the large time and space scales involved. Therefore, landscape simulation modeling will have more of a role in wildland fire management as field studies become untenable. This report details the design and algorithms of a complex, spatially explicit landscape fire and vegetation model called FireBGCv2. FireBGCv2 is a C++ computer program that incorporates several types of stand dynamics models into a landscape simulation platform. FireBGCv2 is intended as a research tool. Descriptions of FireBGCv2 code, sample input files, and sample output are included in this report, but this report is not intended as a users manual because the inherent complexity and wide scope of FireBGCv2 makes it unwieldy and difficult to use without extensive training. The primary purpose of this report is to document FireBGCv2 in adequate detail to interpret simulation results.

Exploring Interactions Among Multiple Disturbance Agents in Forest Landscapes: Simulating Effects of Fire, Beetles, and Disease Under Climate Change

Interactions among disturbance, climate, and vegetation determine landscape patterns and influence ecosystem processes. Dynamic and reciprocal interactions among disturbances can also temporarily or persistently alter landscape trajectories, especially in new climate regimes. Ecological models are used routinely to explore ecological dynamics across heterogeneous landscapes, but few models are able to simulate effects of multiple interacting disturbance events. Projecting how multiple disturbance interactions might result in novel and emergent landscape behaviors is critical for addressing climate change impacts and designing land management strategies that are appropriate for future climates. In this chapter, we demonstrate the importance of interacting disturbances using an example from fire-dominated, pine forested ecosystems of the northern Rocky Mountains, USA, where mountain pine beetle (Dendroctonus ponderosae), white pine blister rust (Cronartium ribicola), and wildland fire interact with the vegetation and climate to create unique landscape behaviors. First, we synthesized the literature on the effects of these three disturbances and their interactions in the northern Rockies forests. Then we used the mechanistic landscape process model FireBGCv2 to simulate effects of multiple disturbance interactions on vegetation composition and basal area for two landscapes under current and projected future climates. Our findings are that (1) multiple disturbance interactions influence landscape patterns more than single or no disturbances; (2) disturbance responses are typically indirect feedbacks mediated through changes in vegetation and fuels; (3) disturbance interactions may overwhelm direct effects of climate changes or effects of a single disturbance on ecosystems, and (4) exploring disturbance interactions demands a mechanistic simulation approach to fully represent those important ecological processes that are directly and indirectly affected by disturbances and their interactions. Disturbances and their interactions must be addressed to properly assess future landscape changes under projected climate regimes.

Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential

Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre- and post-fire imagery to estimate the degree of fire-induced ecological change. Here, we introduce methods to produce three Landsat-based fire severity metrics using the Google Earth Engine (GEE) platform: The delta normalized burn ratio (dNBR), the relativized delta normalized burn ratio (RdNBR), and the relativized burn ratio (RBR). Our methods do not rely on time-consuming a priori scene selection but instead use a mean compositing approach in which all valid pixels (e.g., cloud-free) over a pre-specified date range (pre- and post-fire) are stacked and the mean value for each pixel over each stack is used to produce the resulting fire severity datasets. This approach demonstrates that fire severity datasets can be produced with relative ease and speed compared to the standard approach in which one pre-fire and one post-fire scene are judiciously identified and used to produce fire severity datasets. We also validate the GEE-derived fire severity metrics using field-based fire severity plots for 18 fires in the western United States. These validations are compared to Landsat-based fire severity datasets produced using only one pre- and post-fire scene, which has been the standard approach in producing such datasets since their inception. Results indicate that the GEE-derived fire severity datasets generally show improved validation statistics compared to parallel versions in which only one pre-fire and one post-fire scene are used, though some of the improvements in some validations are more or less negligible. We provide code and a sample geospatial fire history layer to produce dNBR, RdNBR, and RBR for the 18 fires we evaluated. Although our approach requires that a geospatial fire history layer (i.e., fire perimeters) be produced independently and prior to applying our methods, we suggest that our GEE methodology can reasonably be implemented on hundreds to thousands of fires, thereby increasing opportunities for fire severity monitoring and research across the globe.

Effects of Climate Change on Ecological Disturbance in the Northern Rockies

Disturbances alter ecosystem, community, or population structures and change elements of the biological and/or physical environment. Climate changes can alter the timing, magnitude, frequency, and duration of disturbance events, as well as the interactions of disturbances on a landscape, and climate change may already be affecting disturbance events and regimes. Interactions among disturbance regimes, such as the co-occurrence in space and time of bark beetle outbreaks and wildfires, can result in highly visible, rapidly occurring, and persistent changes in landscape composition and structure. Understanding how altered disturbance patterns and multiple disturbance interactions might result in novel and emergent landscape behaviors is critical for addressing climate change impacts and for designing land management strategies that are appropriate for future climates. This chapter describes the ecology of important disturbance regimes in the Northern Rockies region, and potential shifts in these regimes as a consequence of observed and projected climate change. We summarize five disturbance types present in the Northern Rockies that are sensitive to a changing climate—wildfires, bark beetles, white pine blister rust (Cronartium ribicola), other forest diseases, and nonnative plant invasions—and provide information that can help managers anticipate how, when, where, and why climate changes may alter the characteristics of disturbance regimes.

Effects of Climate Change on Forest Vegetation in the Northern Rockies

Increasing air temperature, through its influence on soil moisture, is expected to cause gradual changes in the abundance and distribution of tree, shrub, and grass species throughout the Northern Rockies, with drought tolerant species becoming more competitive. The earliest changes will be at ecotones between lifeforms (e.g., upper and lower treelines). Ecological disturbance, including wildfire and insect outbreaks, will be the primary facilitator of vegetation change, and future forest landscapes may be dominated by younger age classes and smaller trees. High-elevation forests will be especially vulnerable if disturbance frequency increases significantly. Increased abundance and distribution of non-native plant species, as well as the legacy of past land uses, create additional stress for regeneration of native forest species.