Simple Spatial Modeling Tool for Prioritizing Prescribed Burning Activities at the Landscape Scale

Abstract:   Resources for prescribed fire are frequently insufficient to manage public lands for all conservation and resource management objectives, necessitating prioritization of the application of fire across the landscape within any given year. Defining tradeoffs when applying prescribed fire to large landscapes is problematic not only because of the complexity of weighing competing management objectives at the landscape scale, but also because of the difficult nature of independently applying need-to-burn criteria to large areas. We present a case study of a simple modeling process implemented at Eglin Air Force Base in the Florida Panhandle (U.S.A.) to prioritize the application of prescribed fire. In a workshop setting, managers and biologists identified key conservation criteria and landscape management objectives that drive the application of prescribed fire. Remote sensing and other spatial data were developed to directly or indirectly represent all these criteria. Using geographic information system software, managers and biologists weighted each criterion according to its relative contribution to overall burn prioritization, and individual values for the criterion were scored according to how they influence the need to burn. Subsequently, this process has been validated and modified through ecological monitoring. This modeling process has also been applied to the 77,400-ha Blackwater River State Forest, public land adjacent to Eglin Air Force Base, demonstrating its applicability to lands with varying management priorities. The advantages of this model-based approach for prioritizing prescribed fire include the reliance on accessible, inexpensive software, the development of spatially explicit management objectives, the ease of transferability, and clearly stated assumptions about management that may be tested and reviewed through monitoring and public comment.     

Effects of Climate Change on Population Persistence of Desert-Dwelling Mountain Sheep in California

Abstract:  Metapopulations may be very sensitive to global climate change, particularly if temperature and precipitation change rapidly. We present an analysis of the role of climate and other factors in determining metapopulation structure based on presence and absence data. We compared existing and historical population distributions of desert bighorn sheep ( Ovis canadensis ) to determine whether regional climate patterns were correlated with local extinction. To examine all mountain ranges known to hold or to have held desert bighorn populations in California and score for variables describing climate, metapopulation dynamics, human impacts, and other environmental factors, we used a geographic information system (GIS) and paper maps. We used logistic regression and hierarchical partitioning to assess the relationship among these variables and the current status of each population (extinct or extant). Parameters related to climate—elevation, precipitation, and presence of dependable springs—were strongly correlated with population persistence in the twentieth century. Populations inhabiting lower, drier mountain ranges were more likely to go extinct. The presence of domestic sheep grazing allotments was negatively correlated with population persistence. We used conditional extinction probabilities generated by the logistic-regression model to rank native, naturally recolonized, and reintroduced populations by vulnerability to extinction under several climate-change scenarios. Thus risk of extinction in metapopulations can be evaluated for global-climate-change scenarios even when few demographic data are available.     

ASSESSMENT OF POTENTIAL ATMOSPHERIC TRANSPORT AND DEPOSITION PATTERNS DUE TO RUSSIAN PACIFIC FLEET OPERATIONS

A probabilistic analysis of atmospheric transport and deposition patterns from two nuclear risk sites-Kamchatka and Vladivostok-situated in the Russian Far East to countries and geographical regions of interest (Japan, China, North and South Koreas, territories of the Russian Far East, State of Alaska, and Aleutian Chain Islands, US) was performed. The main questions addressed were the following: Which geographical territories are at the highest risk from hypothetical releases at these sites? What are the probabilities for radionuclide atmospheric transport and deposition on different neighboring countries in case of accidents at the sites? For analysis, several research tools developed within the Arctic Risk Project were applied: (1) isentropic trajectory model to calculate a multiyear dataset of 5-day forward trajectories that originated over the site locations at various altitudes; (2) DERMA long-range transport model to simulate 5-day atmospheric transport, dispersion, and deposition of 137Cs for 1-day release (at the rate of 10(10) Bq/s); and (3) a set of statistical methods (including exploratory, cluster, and probability fields analyses) for evaluation of trajectory and dispersion modeling results. The possible impact (on annual, seasonal, and monthly basis) of selected risk sites on neighboring geographical regions is evaluated using a set of various indicators. For trajectory modeling, the indicators examined are: (1) atmospheric transport pathways, (2) airflow probability fields, (3) fast transport probability fields, (4) maximum possible impact zone, (5) maximum reaching distance, and (6) typical transport time fields. For dispersion modeling, the indicators examined are: (1) time integrated air concentration, (2) dry deposition, and (3) wet deposition. It was found for both sites that within the boundary layer the westerly flows are dominant throughout the year (more than 60% of the time), increasing with altitude of free troposphere up to 85% of the time. For the Kamchatka site, the US regions are at the highest risk with the average times of atmospheric transport ranging from 3 to 5.1 days and depositions of 10(-1) Bq/m2 and lower. For the Vladivostok site, the northern China and Japan regions are at the highest risk with the average times of atmospheric transport of 0.5 and 1.6 days, respectively, and depositions ranging from 10(0) to 10(+2) Bq/m2. The areas of maximum potentially impacted zones are 30 x 10(4) km2 and 25 x 10(4) km2 for the Kamchatka and Vladivostok sites, respectively.