Short- to medium-term effects of crown and surface fires on soil respiration in a Canadian boreal forest

Fires are an important perturbation for the carbon (C) dynamics of boreal forests, especially when they are stand-replacing. In North American boreal forests, crown fires are predominant and, therefore, the most studied. However, surface fires can also lead to major tree mortality with substantial implications for the C balance. Here, we assess the short- (hours – days) to medium-term (1 – 3 years) effects of the different fire types (surface vs. crown) on the postfire soil C effluxes in jack pine and black spruce forest stands in the Northwest Territories, Canada. We found that while trees were instantly killed by the four crown fires studied, trees also died within one year after two of three surface fires studied. Associated with this tree mortality, soil autotrophic respiration decreased after both fire types, although at different timings. The soil heterotrophic respiration was either lower or unchanged when measured 1 – 3 years after either fire type, but was increased when measured immediately after a surface fire, possibly due to the interaction between ash generation and wetting performed to suppress the fire. Our results suggest that both fire types can thus substantially alter C fluxes in the short- to medium-term, both through changes in vegetation and the soil environment.

Post-fire insect fauna explored by crown fermental traps in forests of the European Russia

Wildfires considerably affect forest ecosystems. However, there is a lack of data on the post-fire status of insect communities in these ecosystems. This paper presents results of a study conducted in 2019 which considered the post-fire status of the insect fauna in a Protected Area, Mordovia State Nature Reserve (Republic of Mordovia, centre of European Russia), considered as regional hotspot of insect diversity in Mordovia. We sampled insects on intact (unburned, control) and fire-damaged (burnt in 2010) sites and compared the alpha-diversity between sites. In total, we sampled and analysed 16,861 specimens belonging to 11 insect orders, 51 families and 190 species. The largest orders represented in the samples were Coleoptera (95 species), Diptera (54 species), Hymenoptera (21 species), and Neuroptera (11 species). Other insect orders were represented by between one and four species. The largest four orders (Coleoptera, Lepidoptera, Diptera and Hymenoptera) represented 96.7% of all studied specimens. We found that in the ninth year after low intensity surface fire damage, the insect diversity had returned to a similar level to that of the control (unburned) sites. Sites damaged by crown wildfire differed considerably from other sites in terms of a negative impact on both species diversity and the number of specimens. This indicates the serious effect of the crown fires on the biodiversity and consequent long-term recovery of the damaged ecosystem.

Holocene Fire Regime Changes in the Southern Lake Baikal Region Influenced by Climate-Vegetation-Anthropogenic Activity Interactions

Catastrophic fire years that have taken place during the last decade in Siberia, and more generally within the boreal forest, have been directly linked to global warming and had strong repercussions on boreal ecosystems and human populations. In this context the study of the past dynamics of these fires is essential for understanding their links with climate, vegetation and human activity changes on longer time scales than the last few decades. However, few studies on fire dynamics are available for Siberia, and none have been conducted for the entire Holocene period. This study presents the first fire history reconstruction of this area during the Holocene based on charcoals sequestered in sediments of two lakes located on the southern shore of Lake Baikal, in Siberia. The results show a similar trend in the two lakes, with high frequency and high peak magnitude during the Early Holocene and low magnitudes after 6500 cal. yr BP. This difference is interpreted as crown fires versus surface fires. According to pollen records (Dulikha, Vydrino, Ochkovoe) available near the studied lakes, a vegetation transition occurred at the same time. Picea obovata, which has a tree structure prone to crown fires, was dominant during the Early humid Holocene. After 6500 cal. yr BP, conditions were drier and Pinus sylvestris and Pinus sibirica became the dominant species; their tree structure favors surface fires. In addition to vegetation dynamics, the nearby pollen sequence from Dulikha has been used to provide quantitative estimates of past climate, indicating an Early to Middle Holocene climatic optimum between 8000 and 5000 cal. yr BP and an increase in temperatures at the end of the Holocene. These results have been compared to outputs from regional climate models for the Lake Baikal latitudes. Fire dynamics appear to have been more linked to the vegetation than climatic conditions. Over the past 1500 years, the greater presence of human populations has firstly resulted in an increase in the fire frequency, then in its maintenance and finally in its suppression, which may possibly have been due to very recent fire management, i.e., after ca 500 cal. BP.

Intensive Wildfire Associated With Volcanism Promoted the Vegetation Changeover in Southwest China During the Permian−Triassic Transition

Palaeo-wildfire, which had an important impact on the end Permian terrestrial ecosystems, became more intense in the latest Permian globally, evidenced by extensive occurrence of fossil charcoals. In this study, we report abundant charcoals from the upper part of the Xuanwei Formation and the Permian–Triassic transitional Kayitou Formation in the Lengqinggou section, western Guizhou Province, Southwest China. These charcoals are well-preserved with anatomical structures and can be classified into seven distinctive types according to their characteristics. Organic carbon isotopic analyses of both bulk rocks and charcoals show that the δ13Corg values in the Kayitou Formation are notably more negative than those in the Xuanwei Formation, with a negative excursion of 4.08‰ immediately above the volcanic ash bed in the middle of the uppermost coal bed of the Xuanwei Formation. Charcoals with high reflectance values (Romean = 2.38%) are discovered below the ash bed. By contrast, the reflectance values (Romean = 1.51%) of the charcoals in the Kayitou Formation are much lower than those of the Xuanwei Formation, indicating the palaeo-wildfire types have changed from crown fires to surface fires, which was probably due to the retrogression of vegetation systems during the extinction. Based on the above evidence, we suppose that palaeo-wildfires became more frequent and more severe since the climate became drier during the latest Permian in Southwest China, and the eventual vegetation changeover of the terrestrial ecosystems in Southwest China could be caused by volcanism.

Wildfire during deposition of the “Illinger Flözzone” (Heusweiler-Formation, “Stephanian B”, Kasimovian–Ghzelian) in the Saar-Nahe Basin (SW-Germany)

Wildfires occurred more or less regularly in many Pennsylvanian ecosystems, not only in seasonally dry regions but also in the ever wet tropics. One of the reasons for this was probably the relatively high atmospheric oxygen conditions prevailing during this period. The present study reports evidence for the occurrence of wildfires during deposition of the Upper Pennsylvanian Heusweiler Formation (“Stephanian B”, Kasimovian–Gzhelian) in the intramontane Saar-Nahe (or Saar-Lorraine) Basin in SW-Germany. Based on anatomical features of the charcoal, as well as the co-occurring adpression flora, it seems possible that some of the fires occurred in an ecosystem inhabited by Cordaites. Some of the charcoal fragments exhibit traces of pre-charring decay by fungi, indicating either the consumption of litter by ground or surface fires, or of still standing (partly) dead trees by crown fires.

4. Containing and suppressing fire

‘Containing and suppressing fire’ compares urban and pastoral understandings of fire. Prevention and suppression measures for one country may not be relevant in another, and even in the case of wildfires, one region may contain many different biomes, so formulating fire suppression policies can be complex. Some low-intensity surface fires may help prevent more dangerous crown fires; an urban understanding of all landscape fires as negative is not always helpful. With the increased popularity of living among flammable vegetation, the speed of wildfires can take some people by surprise. In urban fires, smoke has long been recognized as dangerous, but smoke from wildfires and peat burning can also cause health problems.

Predicting Forest Fire Numbers Using Deterministic-Probabilistic Approach

The annual task of forecasting forest fire danger is becoming increasingly relevant, especially in the context of global warming. The forecast of surface fires is most important, as more than 80% of all vegetation fires are surface fires. Practically all crown fires develop from surface fires. This chapter discusses the deterministic-probabilistic method for predicting the number of forest fires in a controlled forest area. This methodology is based on the assumption that the number of registered and projected forest fires is related to the probability of their occurrence. The influence of forest fire retrospective data on the predicted number of forest fires for some sites of the Timiryazevskiy forestry of the Tomsk region was studied. This chapter presents the results of a comparative analysis of forecast data and statistics.

The influence of prescribed burning and wildfire on lidar-estimated forest structure of the New Jersey Pinelands National Reserve

Prescribed burning is a common land management tool used to reduce fuels, emulate the effects of wildfire and increase heterogeneity in fire-prone ecosystems. However, the forest structure created by prescribed burning is likely to be dissimilar to that produced by wildfire. We used three-dimensional estimates of canopy bulk density (CBD) from lidar data to explore the relationship between fire type, number of burns and fuel structure/forest structure in the New Jersey Pinelands National Preserve, USA. We found that in areas of previous prescribed fires, as the number of fires increased, the understorey (1–2m) exhibited a slight decrease in CBD, while the upper canopy (15–23m) had higher values of CBD for ≥4 fires, though these differences were not statistically significant. However, an increasing number of wildfires was associated with a statistically significant increase in CBD in the mid-storey (3–7m) and a decrease in CBD in the canopy (≥8m). These results have important implications for forest resource managers because they indicate that prescribed burning reduces ladder fuels that lead to torching and crown fires, but it does not replicate the structure created by wildfire.

Frequency of Dynamic Fire Behaviours in Australian Forest Environments

Wildfires can result in significant social, environmental and economic losses. Fires in which dynamic fire behaviours (DFBs) occur contribute disproportionately to damage statistics. Little quantitative data on the frequency at which DFBs occur exists. To address this problem, we conducted a structured survey using staff from fire and land management agencies in Australia regarding their experiences with DFBs. Staff were asked which, if any, DFBs were observed within fires greater than 1000 ha from the period 2006–2016 that they had experience with. They were also asked about the nature of evidence to support these observations. One hundred thirteen fires were identified. Eighty of them had between one and seven DFBs with 73% (58 fires) having multiple types of DFBs. Most DFBs could commonly be identified through direct data, suggesting an empirical analysis of these phenomena should be possible. Spotting, crown fires and pyro-convective events were the most common DFBs (66%); when combined with eruptive fires and conflagrations, these DFBs comprise 89% of all cases with DFBs. Further research should be focused on these DFBs due to their high frequencies and the fact that quantitative data are likely to be available.

Potential of Sentinel-2A Data to Model Surface and Canopy Fuel Characteristics in Relation to Crown Fire Hazard

Background: Crown fires are often intense and fast spreading and hence can have serious impacts on soil, vegetation, and wildlife habitats. Fire managers try to prevent the initiation and spread of crown fires in forested landscapes through fuel management. The minimum fuel conditions necessary to initiate and propagate crown fires are known to be strongly influenced by four stand structural variables: surface fuel load (SFL), fuel strata gap (FSG), canopy base height (CBH), and canopy bulk density (CBD). However, there is often a lack of quantitative data about these variables, especially at the landscape scale. Methods: In this study, data from 123 sample plots established in pure, even-aged, Pinus radiata and Pinus pinaster stands in northwest Spain were analyzed. In each plot, an intensive field inventory was used to characterize surface and canopy fuels load and structure, and to estimate SFL, FSG, CBH, and CBD. Equations relating these variables to Sentinel-2A (S-2A) bands and vegetation indices were obtained using two non-parametric techniques: Random Forest (RF) and Multivariate Adaptive Regression Splines (MARS). Results: According to the goodness-of-fit statistics, RF models provided the most accurate estimates, explaining more than 12%, 37%, 47%, and 31% of the observed variability in SFL, FSG, CBH, and CBD, respectively. To evaluate the performance of the four equations considered, the observed and estimated values of the four fuel variables were used separately to predict the potential type of wildfire (surface fire, passive crown fire, or active crown fire) for each plot, considering three different burning conditions (low, moderate, and extreme). The results of the confusion matrix indicated that 79.8% of the surface fires and 93.1% of the active crown fires were correctly classified; meanwhile, the highest rate of misclassification was observed for passive crown fire, with 75.6% of the samples correctly classified. Conclusions: The results highlight that the combination of medium resolution imagery and machine learning techniques may add valuable information about surface and canopy fuel variables at large scales, whereby crown fire potential and the potential type of wildfire can be classified.