Forest fire threatens global carbon sinks and population centres under rising atmospheric water demand

Road fragment edges enhance wildfire incidence and intensity, while suppressing global burned area

Landscape fragmentation is statistically correlated with both increases and decreases in wildfire burned area (BA). These different directions-of-impact are not mechanistically understood. Here, road density, a land fragmentation proxy, is implemented in a CMIP6 coupled land-fire model, to represent fragmentation edge effects on fire-relevant environmental variables. Fragmentation caused modelled BA changes of over ±10% in 16% of [0.5°] grid-cells. On average, more fragmentation decreased net BA globally (-1.5%), as estimated empirically. However, in recently-deforested tropical areas, fragmentation drove observationally-consistent BA increases of over 20%. Globally, fragmentation-driven fire BA decreased with increasing population density, but was a hump-shaped function of it in forests. In some areas, fragmentation-driven decreases in BA occurred alongside higher-intensity fires, suggesting the decoupling of fire severity traits. This mechanistic model provides a starting point for quantifying policy-relevant fragmentation-fire impacts, whose results suggest future forest degradation may shift fragmentation from net global fire inhibitor to net fire driver.

Global rise in forest fire emissions linked to climate change in the extratropics

Climate change increases fire-favorable weather in forests, but fire trends are also affected by multiple other controlling factors that are difficult to untangle. We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to increases in fire-favorable weather, compounded by increased forest cover and productivity. This contributed to a 60% increase in forest fire carbon emissions from forest ecoregions globally. Our results highlight the increasing vulnerability of forests and their carbon stocks to fire disturbance under climate change.

Advancements in remote sensing for active fire detection: A review of datasets and methods

This study comprehensively and critically reviews active fire detection advancements in remote sensing from 1975 to the present, focusing on two main perspectives: datasets and corresponding instruments, and detection algorithms. The study highlights the increasing role of machine learning, particularly deep learning techniques, in active fire detection. Looking forward, the review outlines current challenges and future research opportunities in remote sensing for active fire detection. These include exploring data quality management and multi-modal learning, developing spatiotemporally explicit models, investigating self-supervised learning models, improving explainable and interpretable models, integrating physical-process based models with machine learning, and building digital twins to replicate wildfire dynamics and perform what-if scenario analysis. The review aims to serve as a valuable resource for informing natural resource management and enhancing environmental protection efforts through the application of remote sensing technology.

The impacts of rising vapour pressure deficit in natural and managed ecosystems

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Carbon emissions from the 2023 Canadian wildfires

The 2023 Canadian forest fires have been extreme in scale and intensity with more than seven times the average annual area burned compared to the previous four decades1. Here, we quantify the carbon emissions from these fires from May to September 2023 on the basis of inverse modelling of satellite carbon monoxide observations. We find that the magnitude of the carbon emissions is 647 TgC (570-727 TgC), comparable to the annual fossil fuel emissions of large nations, with only India, China and the USA releasing more carbon per year2. We find that widespread hot-dry weather was a principal driver of fire spread, with 2023 being the warmest and driest year since at least 19803. Although temperatures were extreme relative to the historical record, climate projections indicate that these temperatures are likely to be typical during the 2050s, even under a moderate climate mitigation scenario (shared socioeconomic pathway, SSP 2-4.5)4. Such conditions are likely to drive increased fire activity and suppress carbon uptake by Canadian forests, adding to concerns about the long-term durability of these forests as a carbon sink5-8.

Rapid summer Russian Arctic sea-ice loss enhances the risk of recent Eastern Siberian wildfires

In recent decades boreal wildfires have occurred frequently over eastern Siberia, leading to increased emissions of carbon dioxide and pollutants. However, it is unclear what factors have contributed to recent increases in these wildfires. Here, using the data we show that background eastern Siberian Arctic warming (BAW) related to summer Russian Arctic sea-ice decline accounts for ~79% of the increase in summer vapor pressure deficit (VPD) that controls wildfires over eastern Siberia over 2004-2021 with the remaining ~21% related to internal atmospheric variability associated with changes in Siberian blocking events. We further demonstrate that Siberian blocking events are occurring at higher latitudes, are more persistent and have larger zonal scales and slower decay due to smaller meridional potential vorticity gradients caused by stronger BAW under lower sea-ice. These changes lead to more persistent, widespread and intense high-latitude warming and VPD, thus contributing to recent increases in eastern Siberian high-latitude wildfires.

The interior climate and its microclimatic variation of temperate forests in Northern Patagonia, Argentina

Knowledge on mesoclimatic zonation and microclimatic variations within mountain forest ecosystems is crucial for understanding regional species turnover and effects of climate change on these systems. The temperate mountain forests in the Andean region of South America are among the largest and contiguous natural deciduous forest areas in the world. Due to their pronounced disturbance regime and different successional stages, a climatic zonation combined with the characterisation of its microclimatic variation is important to identify thresholds of species occurrences.We used micro-loggers to measure air temperature and relative humidity for one year at 40 measurement locations along longitudinal and elevation gradients in mountain forests in Northern Patagonia, Argentina. Our results unveil mesoclimatic patterns within these forests characterised by variations in temperature and vapour pressure deficit along the elevational gradient in general, but also at different times of the year. For example, Austrocedrus chilensis and Nothofagus dombeyi forests differed mainly by temperature and its diurnal range in the warmest months of the year. Also, differences between forest stands and gaps were more pronounced in the warmest months of the year and at lower elevations, with up to 2.5 K higher temperatures in the second half of the day in gaps. We found clear indications that shrubland of Nothofagus antarctica representing a successional stage after disturbances alters the mesoclimatic pattern, favouring forest fire ignition. Such mesoclimatic variations have a major influence on tree species turnover and ecological processes within these forest ecosystems.The findings contribute to our understanding of the complex interplay between topography, climate, and vegetation in shaping the spatial patterns of species occurrences.

Australia's Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change

We examine the characteristics and causes of southeast Australia's Tinderbox Drought (2017 to 2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterized by cool season rainfall deficits of around -50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapor pressure deficits, and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9 to -13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of droughts.

Quantification of Bioaccessible and Environmentally Relevant Trace Metals in Structure Ash from a Wildland-Urban Interface Fire

Wildfires at the wildland-urban interface (WUI) are increasing in frequency and intensity, driven by climate change and anthropogenic ignitions. Few studies have characterized the variability in the metal content in ash generated from burned structures in order to determine the potential risk to human and environmental health. Using inductively coupled plasma optical emission spectroscopy (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS), we analyzed leachable trace metal concentration in soils and ash from structures burned by the Marshall Fire, a WUI fire that destroyed over 1000 structures in Boulder County, Colorado. Acid digestion revealed that ash derived from structures contained 22 times more Cu and 3 times more Pb on average than surrounding soils on a mg/kg basis. Ash liberated 12 times more Ni (mg/kg) and twice as much Cr (mg/kg) as soils in a water leach. By comparing the amount of acid-extractable metals to that released by water and simulated epithelial lung fluid (SELF), we estimated their potential for environmental mobility and human bioaccessibility. The SELF leach showed that Cu and Ni were more bioaccessible (mg of leachable metal/mg of acid-extractable metal) in ash than in soils. These results suggest that structure ash is an important source of trace metals that can negatively impact the health of both humans and the environment.

Plant hydraulics at the heart of plant, crops and ecosystem functions in the face of climate change

Plant hydraulics is crucial for assessing the plants' capacity to extract and transport water from the soil up to their aerial organs. Along with their capacity to exchange water between plant compartments and regulate evaporation, hydraulic properties determine plant water relations, water status and susceptibility to pathogen attacks. Consequently, any variation in the hydraulic characteristics of plants is likely to significantly impact various mechanisms and processes related to plant growth, survival and production, as well as the risk of biotic attacks and forest fire behaviour. However, the integration of hydraulic traits into disciplines such as plant pathology, entomology, fire ecology or agriculture can be significantly improved. This review examines how plant hydraulics can provide new insights into our understanding of these processes, including modelling processes of vegetation dynamics, illuminating numerous perspectives for assessing the consequences of climate change on forest and agronomic systems, and addressing unanswered questions across multiple areas of knowledge.

Critical fire weather conditions during active fire spread days in Canada

A spread day is defined as a day in which fires grow a substantial amount of area; such days usually occur during high or extreme fire weather conditions. The identification and prediction of a spread day based on fire weather conditions could help both our understanding of fire regimes as well as forecasting and managing fires operationally. This study explores the relationships between fire weather and spread days in the forested areas of Canada by spatially and temporally matching a daily fire growth database to a daily gridded fire weather database that spans from 2001 to 2019. By examining the correlations between spread day fire weather conditions and location, conifer coverage (%), and elevation, we found that a spread day happens under less severe fire weather conditions as latitude increases for the entire study area and as conifer coverage increases within non-mountainous study areas. In the western mountain areas, however, with increasing conifer coverage more severe fire weather conditions are required for a spread day to occur. Using two modeling approaches, we were able to identify spread day indicators (generalized additive model) and to predict the occurrence of spread days (semi-binomial regression model) by Canadian Ecozones both annually and seasonally. Overall, Fine Fuel Moisture Code (FFMC), Initial Spread Index (ISI), and Fire Weather Index (FWI) performed the best in all models built for spread day identification and prediction but varied depending on the conditions mentioned above. FFMC was the most consistent across all spatial and temporal scales.