Forest fires and climate-induced tree range shifts in the western US

Due to climate change, plant populations experience environmental conditions to which they are not adapted. Our understanding of the next century’s vegetation geography depends on the distance, direction, and rate at which plant distributions shift in response to a changing climate. In this study we test the sensitivity of tree range shifts (measured as the difference between seedling and mature tree ranges in climate space) to wildfire occurrence, using 74,069 Forest Inventory Analysis plots across nine states in the western United States. Wildfire significantly increased the seedling-only range displacement for 2 of the 8 tree species in which seedling-only plots were displaced from tree-plus-seedling plots in the same direction with and without recent fire. The direction of climatic displacement was consistent with that expected for warmer and drier conditions. The greater seedling-only range displacement observed across burned plots suggests that fire can accelerate climate-related range shifts and that fire and fire management will play a role in the rate of vegetation redistribution in response to climate change.

Architecture of GIS Solutions for Detection and Development of Wildfire Database

This research paper presents organization of the business environment for work with geographic information systems (GIS) which are based on open source. The solution is completely open source: operating system, working environment and supporting apps. The architecture consists of: server, workstations, mobile devices and sensors. Software packages for each architecture segment will be displayed. The goal is to achieve a complete business environment for work with open source GIS, thus minimizing the costs of system development and maintenance. The illustrated example shows the possibility of applying GIS within a forestry company, in the field of wildfire monitoring and data collection and registering the possibility of wildfire occurrence using IoT.

Wildfire Risk Assessment and Zoning by Integrating Maxent and GIS in Hunan Province, China

Forest wildfire is an important threat and disturbance facing natural forest ecosystems. Conducting wildfire risk assessments and zoning studies are of great practical significance in guiding wildfire prevention, curbing fire occurrence, and mitigating the environmental effects of wildfire. Taking Hunan Province, China as the case area, this study used remotely sensed high-temperature fire data as the wildfire sample. Twelve factors related to topography, climatic conditions, vegetation attributes, and human activities were used as environmental variables affecting wildfire occurrence. Then, a Maxent wildfire risk assessment model was constructed with GIS, which analyzed the contribution, importance, and response of environmental variables to wildfire in Hunan Province. The results show that (1) the Maxent model has high applicability and feasibility when applied to wildfire risk assessment after a test of wildfire sample sites; (2) the importance of meteorological conditions and vegetation status variables to wildfire are 54.64% and 25.40%, respectively, and their contribution to wildfire are 43.03% and 34.69%, respectively. The interaction between factors can enhance or weaken the contribution of factors on wildfire. (3) The mechanism for the effects of environmental variables on wildfire is not linear as generally believed; temperature, aridity, land use type, GDP, distance from the road, and population density have a nonlinear positive correlation with the probability of wildfire occurrence. Elevation, slope, precipitation, wind speed, and vegetation cover within the suitable interval positively contribute to the probability of wildfire, while the environmental conditions outside the suitable interval curb the occurrence of wildfire. The response of wildfire probability to forest density is U-shaped, which means either too high or too low will promote the occurrence of wildfire. (4) There is geographical variation of wildfire risk in Hunan Province. The areas at high risk and below account for 74.48% of the total area, while the areas at significantly high risk and above account for a relatively low proportion, 25.52%.

Understanding Grass Invasion, Fire Severity, and Acacia koa Regeneration for Forest Restoration in Hawaiʻi Volcanoes National Park

With invasive grasses increasing wildfire occurrence worldwide, a better understanding of the relationships between native plants, fire, and invasive grass is needed to help restoration plans facilitate ecosystem resilience. Invasive grasses are particularly problematic for altering fire regimes in the tropics, yet in Hawaiʻi, restoration sites are often planted with monocultures of the native tree Acacia koa, which can promote grass growth via nitrogen fixation. This, combined with the difficulty of estimating pre-fire grass cover under thick canopies, complicates attempts to restore Hawaiian ecosystems. We studied the 2018 Keauhou Ranch Fire in Hawaiʻi to investigate three questions: (1) at what level of precision can pre-fire grass cover be accurately estimated from oblique aerial photos? (2) how are post-fire A. koa regeneration densities affected by fire severity? and (3) how are post-fire A. koa regeneration densities affected by pre-fire grass cover and its interaction with fire severity? We collected burn severity and post-fire regeneration data from 30 transects stratified across mid-elevation woodland, montane woodland, and montane shrubland communities. We evaluated visual estimates of pre-fire grass cover from oblique aerial imagery with quantitative in situ data from 60 unburned transects of the same cover types. Pre-fire estimates of grass cover categories were 67% accurate in montane woodland (n = 9) and 100% accurate in montane shrubland (n = 11), but only 20% accurate in mid-elevation woodland (n = 10). In montane woodlands with low pre-fire tree densities, A. koa regeneration densities were higher with increased fire severity, but this trend reversed when pre-fire tree densities were high. We detected no effect of pre-fire grass cover, nor its interaction with fire severity, on A. koa regeneration density. This indicates that restoration through the planting of A. koa may be successful in promoting fire-resilient A. koa forest, although there are potential issues to consider regarding the effects that A. koa’s grass promotion may have on other species within the ecosystem.