CSDMS 2015 annual meeting poster MeganCaldwell
Changes in Southern Rocky Mountain Forests: Using Ecosystem Process Modelling to Project Critical Transitions
Abstract:
High elevation spruce-fir and lodgepole forests are widely distributed across the Rocky Mountains in the US and Canada, and represent high to mixed fire severity regimes. These forests contribute substantial ecosystem services in each category (supporting, provisioning, regulating and cultural) at multiple scales. Fire is a primary disturbance impacting these forests and subsequently, ecosystem services. Our research study area is the northern Colorado Rockies, dominated by high elevation forests. Colorado’s climate has become substantially warmer over the past 30 years, where average temperatures have increased by 2.0°F and projections show further warming and precipitation variability. These changes raise concern about how future fires and related vegetation recovery will change, and how system drivers will change. The overall research objective this study focuses on how climate has influenced fires past and regeneration rates in the recent across high elevation forests, characterized previously by high to mixed-severity fire regimes. Greater predictive capacity and ecological understanding will come from dynamic ecosystem process modeling and systematic observations of past and present pattern. Critical transitions in regeneration patterns post-fire disturbance will be dependent upon the changes in biotic, abiotic and climatically drivers. This research both quantifies recent past and present heterogeneity in fire as well as fire recovery patterns. Recent conditions are quantified using the Burned Area Essential Climate Variable (BAECV) produced at USGS using an automated algorithm to detect burned areas from the Landsat archive. The BAECV product, Landsat NDVI, and high resolution temperature and precipitation data from the National Climate Data Center will be used to quantify heterogeneity in ecosystem response to higher temperatures. Using these data, a dynamic ecosystem process model (LANDIS) will be used to project future change to fire disturbances, recovery patterns and thresholds to critical transitions in ecosystem processes. Dynamic ecosystem modeling with new data provides insights complimentary to ecosystem recovery responses to increased temperatures and different precipitation regimes for adaptive land management to better manage forest ecosystems and ecosystem services.
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