Forest fire risk estimation in a typical temperate forest in Northeastern China using the Canadian forest fire weather index: case study in autumn 2019 and 2020

Environmental effects of a management method used after fire on development of temperate Scots pine ecosystem: a 15-year study from Poland

Due to the ongoing climate changes, temperate forests are increasingly exposed to fires. However, until now the functioning of post-fire temperate forest ecosystems with regard to used forest management method has been weakly recognized. Here, we examined three variants of forest restoration after fire (two variants of natural regeneration with no soil preparation-NR, and artificial restoration by planting following soil preparation-AR) regarding their environmental consequences in development of post-fire Scots pine (Pinus sylvestris) ecosystem. The study was conducted using a 15-year timespan in a long-term research site located in the Cierpiszewo area (N Poland) being one of the biggest post-fire grounds in European temperate forests in last decades. We focused on soil and microclimatic variables as well as on growth dynamics of post-fire pines generation. We found that the restoration rates of soil organic matter, carbon and most studied nutritional elements stocks were higher in NR plots than in AR. This could be primarily linked to the higher (p < 0.05) density of pines in naturally regenerated plots, and the subsequent faster organic horizon reconstruction after fire. The difference in tree density also involved regular differences in air and soil temperature among plots: consistently higher in AR than in both NR plots. In turn, lower water uptake by trees in AR implied that soil moisture was constantly the highest in this plot. Our study delivers strong arguments to pay more attention to restore post-fire forest areas with the use of natural regeneration with no soil preparation.

Assessing the Effectiveness of Silvicultural Treatments on Fire Behavior in the Hyrcanian Temperate Forests of Northern Iran

We implemented a fire modeling approach to evaluate the effectiveness of silvicultural treatments in reducing potential losses to the Hyrcanian temperate forests of northern Iran, in the Siahkal National Forest (57,110 ha). We compared the effectiveness of selection cutting, low thinning, crown thinning, and clear-cutting treatments implemented during the last ten years (n = 241, 9500-ha) on simulated stand-scale and landscape-scale fire behavior. First, we built a set of fuel models for the different treatment prescriptions. We then modeled 10,000 fires at the 30-m resolution, assuming low, moderate, high, very high, and extreme weather scenarios and human-caused ignition patterns. Finally, we implemented a One-way ANOVA test to analyze stand-level and landscape-scale modeling output differences between treated and untreated conditions. The results showed a significant reduction of stand-level fire hazard, where the average conditional flame length and crown fire probability was reduced by about 12 and 22%, respectively. The conifer plantation patches presented the most significant reduction in the crown fire probability (>35%). On the other hand, we found a minor increase in the overall burn probability and fire size at the landscape scale. Stochastic fire modeling captured the complex interactions among terrain, vegetation, ignition locations, and weather conditions in the study area. Our findings highlight fuel treatment efficacy for moderating potential fire risk and restoring fuel profiles in fire-sensitive temperate forests of northern Iran, where the growing persistent droughts and fuel buildup can lead to extreme fires in the near future.

Mapping burn severity and monitoring CO content in Türkiye's 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform

This study investigated forest fires in the Mediterranean of Türkiye between July 28, 2021, and August 11, 2021. Burn severity maps were produced with the difference normalised burned ratio index (dNBR) and difference normalised difference vegetation index (dNDVI) using Sentinel-2 images on the Google Earth Engine (GEE) cloud platform. The burned areas were estimated based on the determined burning severity degrees. Vegetation density losses in burned areas were analysed using the normalised difference vegetation index (NDVI) time series. At the same time, the post-fire Carbon Monoxide (CO) column number densities were determined using the Sentinel-5P satellite data. According to the burn severity maps obtained with dNBR, the sum of high and moderate severity areas constitutes 34.64%, 20.57%, 46.43%, 51.50% and 18.88% of the entire area in Manavgat, Gündoğmuş, Marmaris, Bodrum and Köyceğiz districts, respectively. Likewise, according to the burn severity maps obtained with dNDVI, the sum of the areas of very high severity and high severity constitutes 41.17%, 30.16%, 30.50%, 42.35%, and 10.40% of the entire region, respectively. In post-fire NDVI time series analyses, sharp decreases were observed in NDVI values from 0.8 to 0.1 in all burned areas. While the Tropospheric CO column number density was 0.03 mol/m² in all regions burned before the fire, it was observed that this value increased to 0.14 mol/m² after the fire. Moreover, when the area was examined more broadly with Sentinel 5P data, it was observed that the amount of CO increased up to a maximum value of 0.333 mol/m². The results of this study present significant information in terms of determining the severity of forest fires in the Mediterranean region in 2021 and the determination of the CO column number density after the fire. In addition, monitoring polluting gases with RS techniques after forest fires is essential in understanding the extent of the damage they can cause to the environment.