Name: Exposure to Wildfire Exclusion

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Description: The Terrestrial Condition Assessment (TCA) was adapted to understand the ecological condition and potential threats to MOG in an integrated way. The TCA was developed by the Forest Service, and it leverages nationally consistent datasets to model ecological integrity on National Forest System (NFS) lands at the mid-level using land-type associations (LTA) or comparable spatial units representing ecosystems (Cleland et al. 2017, Nelson et al. 2015 Winthers et al. 2005). The TCA model is supported through the Ecosystem Management Decision Support (EMDS) logic model which provides transparency and repeatability for TCA while allowing TCA to incorporate information about the relationships between indicators and metrics of ecological integrity.The initial version of MOG-CA focuses on current conditions and threats with the portion of the model devoted to future threats to be developed later. The architecture of the model consists of a network of logic networks, in which each logic network evaluates evidence for a proposition (e.g., threat is absent) in terms of two or more logical premises or parameters (values/thresholds that define a condition). Each path through the logic architecture terminates in a data input that is interpreted based on the premises/parameters, and subsequently synthesized with the other data inputs for each Fireshed Project Area. The model is data driven and therefore, evidence based. Where TCA evaluates ecological integrity (Overall Terrestrial Condition) as the absence of ecological stressors, the MOG-CA model evaluates the overall MOG condition as the absence of detrimental conditions and potential threats. Along these lines, the overall MOG condition can be thought of as an inference about MOG integrity.The area of a landscape with a deficient fire frequency was estimated by comparing observed fire frequencies to historical mean fire return intervals (MFRI, LF2016_BPS_200_CONUS). Observed fire frequencies were calculated by determining the frequency of fire for each pixel based on vector data of observed fires from various sources from 1923 to 2023. The ratio of observed to historical fire frequencies was used to determine pixels that are burning less frequently than expected, as determined by LANDFIRE MFRI. These pixels were then used to determine the percent area of the landscape deficient in fire based on fire frequencies which were used as the inputs in the EMDS logic model to produce the fire deficit scores.Fire deficit scores for each Fireshed Project Area range from -1 to +1. Classes represent even divisions (ranges of 0.4) of the full range of possible model scores (very highest score = +1, very lowest score =−1). Threat classes in order from order from highest score (+1) to lowest score (-1): Very Good Condition = Very Low Risk (1): 1 – 0.6Good Condition = Low Risk (2): 0.2 – 0.6Moderate Condition = Moderate Risk (3): -0.2 – 0.2Poor Condition = High Risk(4): -0.2 – -0.6Very Poor Condition = Very High Risk (5): -1 – -0.6

Copyright Text: Sarah Anderson; Keith Reynolds; Ray Davis; Ryan Rock

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