Large wildland fires in three diverse regions in Spain from 1978 to 2010.

Aim of study: Large wildland fires (LWF) are major disturbance processes affecting many ecosystems each year. In last decades, socio-economic changes have contributed to major changes in land uses. This study assess trends in number, burned area and average size of large wildfires (> 100 ha) from 1978 to 2010 in Spain.Area of study: This work analyzes three clearly different regions of Spain (Mediterranean coast, MC, Mediterranean Interior, MI, Northwestern Spain, NW).Material and Methods: We studied historical wildland fire data from Spain’s EGIF database (General Statistics on Wildland Fires). We selected only wildland fires larger than 100 ha. All LWF were analyzed to test trends in number of fires, burned area and mean fire size.Main results: The number of LWF decreased in all regions but the burned area only decreased in MC and NW regions. However, both the number of LWF and the burned area did not decrease after 1995 in any region. The average size of LWF did not change in any of the three regions. Fires larger than 500 ha were very significant due to the high percentage of area burned in relation to the total area burned by fires larger than 100 ha (79.3 % in MC, 63.9 % in MI, and 35.7% in NW).Research highlights: After 1995, the number of LWF and burned area did not decrease. Additional actions are required including learned lessons from past LWF spread, and better trained fire suppression workers and more fuel management.Keywords: large wildland fires; trends; forest management; Spain

Fire behavior modeling for operational decision-making

Simulation frameworks are necessary to facilitate decision-making to many fire agencies. An accurate estimation of fire behavior is required to analyze potential impact and risk. Applied research and technology together have improved the implementation of fire modeling, and decision-making in operational environments.Dr Cardil acknowledges the support of Technosylva USA and Wageningen University in his research stays in the USA and the Netherlands to develop this work. The authors of this paper acknowledges the support of the EUfunded PYROLIFE project (Reference: 860787; https://pyrolife.lessonsonfire.eu/), a project in which a new generation of experts will be trained in integrated wildfire management

Spatio-Temporal Domains of Wildfire-Prone Teleconnection Patterns in the Western Mediterranean Basin

This work explores the main climate teleconnections influencing the Western Mediterranean Basin to outline homogeneous fire-prone weather domains combining cross-correlation time series and cluster analysis. We found a zonal effect of the Scandinavian pattern over the entire region with an interesting alternation of phases from positive during winter-spring (increased rainfall leading to fuel accumulation) to negative (dry conditions) modes during summer controlling burned area and fire size. The North Atlantic Oscillation (NAO) dominates the number of fires over the Iberian Peninsula (IP) while the Western Mediterranean Oscillation pattern modulates fire activity over the Mediterranean coast in the IP (linked to westerly winds), Southern France, Corsica and Sardinia (rainfall regulation). These distinctive influence traits resulted in three different domains splitting the IP into a Mediterranean rim along the coast (from southern Spain to southwestern France) and an inland and western region (Portugal plus western Spain); and a third in southeastern France, Corsica and Sardinia

Coupled effects of climate teleconnections on drought, Santa Ana winds and wildfires in southern California

Projections of future climate change impacts suggest an increase of wildfire activity in Mediterranean ecosystems, such as southern California. This region is a wildfire hotspot and fire managers are under increasingly high pressures to minimize socio-economic impacts. In this context, predictions of high-risk fire seasons are essential to achieve adequate preventive planning. Regional-scale weather patterns and climatic teleconnections play a key role in modulating fire-conducive conditions across the globe, yet an analysis of the coupled effects of these systems onto the spread of large wildfires is lacking for the region. We analyzed seven decades (1953–2018) of documentary wildfire records from southern California to assess the linkages between weather patterns and large-scale climate modes using various statistical techniques, including Redundancy Analysis, Superposed Epoch Analysis and Wavelet Coherence. We found that high area burned is significantly associated with the occurrence of adverse weather patterns, such as severe droughts and Santa Ana winds. Further, we document how these fire-promoting events are mediated by climate teleconnections, particularly by the coupled effects of El Niño Southern Oscillation and Atlantic Multidecadal Oscillation

Cross-landscape fuel moisture differences impact simulated fire behaviour

BackgroundPredicting fire behaviour is an ongoing challenge in temperate peatlands and heathlands, where live fuels can form the dominant fuel load for wildfire spread, and where spatial heterogeneity in fuel moisture is important but not typically represented in fuel models.AimsWe examine the impact of fuel moisture variation on simulated fire behaviour across a temperate peatland/heathland landscape.MethodsWe collected field measurements of fuel moisture content in Calluna vulgaris shrub from 36 sites across the North Yorkshire Moors, United Kingdom. We used these to define fuel moisture inputs within existing shrubland fuel models to simulate fire behaviour in BehavePlus.Key resultsSimulated rates of spread varied with fuel moisture content; average mean variance of 23–80% from the landscape average rate of spread. The driest sites had simulated rates of spread up to 135% above the landscape average and the wettest sites up to 86% below average. Fuel model selection dramatically impacted simulated rates of spread by a factor of five.ConclusionsWe need to constrain the role of live fuel moisture within temperate fuel models to develop accurate fire behaviour predictions.ImplicationsCapturing cross-landscape heterogeneity in fire behaviour is important for safe and effective land and wildfire management decision-making

Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

[EN] Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Objectbased image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantationsSIWe thank the Portuguese Science Foundation (grant number PD/BD/128489/2017)) for funding the research activities of Diogo Cosenza. This research was supported by RPJ17014 internal project-from Navigator company and BioEcosys ‘Forest ecosystem management decision-making methods an integrated bioeconomic approach to sustainability’, reference LISBOA–01–0145–FEDER–030391 - PTDC/ASP-SIl/30391/2017, funded by the Fundação para a Ciência e a Tecnologia (FCT, Portugal

Emerging threats linking tropical deforestation and the COVID-19 pandemic

Tropical deforestation drivers are complex and can change rapidly in periods of profound societal transformation, such as those during a pandemic. Evidence suggests that the COVID-19 pandemic has spurred illegal, opportunistic forest clearing in tropical countries, threatening forest ecosystems and their resident human communities. A total of 9583 km2 of deforestation alerts from Global Land Analysis & Discovery (GLAD) were detected across the global tropics during the first month following the implementation of confinement measures of local governments to reduce COVID-19 spread, which is nearly double that of 2019 (4732 km2). We present a conceptual framework linking tropical deforestation and the current pandemic. Zoonotic diseases, public health, economy, agriculture, and forests may all be reciprocally linked in complex positive and negative feedback loops with overarching consequences. We highlight the emerging threats to nature and society resulting from this complex reciprocal interplay and possible policy interventions that could minimize these threats