Impacts of ash-induced environmental alkalinization on fish physiology, and their implications to wildfire-scarred watersheds.

Changes in land use, a warming climate and increased drought have amplified wildfire frequency and magnitude globally. Subsequent rainfall in wildfire-scarred watersheds washes ash into aquatic systems, increasing water pH and exposing organisms to environmental alkalinization. In this study, 15 or 20 °C-acclimated Chinook salmon (Oncorhynchus tshawytscha) yearlings were exposed to an environmentally-relevant ash concentration (0.25 % w/v), increasing water pH from ∼8.1 to ∼9.2. Salmon experienced significant disturbance to blood plasma pH (pHe) and red blood cell intracellular pH (RBC pHi) within 1 h, but recovered within 24 h. Impacts on plasma ion concentrations were relatively mild, and plasma glucose increased by 2- to 4-fold at both temperatures. Temperature-specific differences were observed: 20 °C salmon recovered their pHe more rapidly, perhaps facilitated by higher basal metabolism and anaerobic metabolic H+ production. Additionally, 20 °C salmon experienced dramatically greater spikes in plasma total ammonia, [NH3] and [NH4+] after 1 h of exposure that decreased over time, whereas 15 °C salmon experienced a gradual nitrogenous waste accumulation. Despite pHe and RBC pHi recovery and non-lethal nitrogenous waste levels, we observed 20 % and 33 % mortality in 15 and 20 °C treatments within 12 h of exposure, respectively. The mortalities cannot be explained by high water pH alone, nor was it likely to be singularly attributable to a heavy metal or organic compound released from ash input. This demonstrates post-wildfire ash input can induce lethal yet previously unexplored physiological disturbances in fish, and further highlights the complex interaction with warmer temperatures typical of wildfire-scarred landscapes.

Biomonitoring of firefighters' exposure to priority pollutant metal(loid)s during wildland fire combat missions: Impact on urinary levels and health risks.

Wildland firefighters are exposed to metal(loid)s released during wildfires through vegetation combustion, which also promotes remobilization of accumulated anthropogenic metal(loid)s. Studies biomonitoring metal(loid)s exposure promoted exclusively by wildfire suppression activities are lacking. This work aimed to characterize, for the first time, the impact of real-life wildland firefighting operations on urinary levels of priority pollutant metal(loid)s [14 included in ATSDR, 11 in USEPA, and 4 in Human Biomonitoring for Europe Initiative priority lists] in firefighters. Spot urines were sampled pre-exposure (105 non-smokers, 76 smokers) and post-exposure to firefighting activities (20 non-smokers, 25 smokers); among those, paired samples were collected from 14 non-smoking and 24 smoking firefighters. Smokers displayed significantly higher baseline levels of zinc (28 %), lithium (29 %), cadmium (55 %), rubidium (13 %), and copper (20 %) than non-smokers. Following wildfire suppression, the concentration of the WHO potentially toxic metal(loid)s rose from 2 % to 3 % in smokers and 2 % to 5 % in non-smokers (up to 4 % for all firefighters and up to 5 % in paired samples). Levels of nickel (33-53 %), antimony (45-56 %), and cesium (40-47 %) increased significantly post-exposure in non-smokers (in all firefighters and in paired samples), whose urinary concentrations were generally more impacted by wildfire emissions than those of smokers. Arsenic (80 %) displayed the only significant increase post-exposure in smokers, being the best discriminant of exposure to wildfire emissions in these subjects. Significant positive correlations were found for age and/or career length with cadmium, lead, barium, strontium, and mercury, and for body mass index with arsenic. The reference/guidance values were exceeded for arsenic, zinc, cesium, nickel, antimony, cadmium, lead, thallium, mercury, copper, and cobalt in 1-90 % of firefighters suggesting augmented health risks due to wildfire combating and emphasizing the need of mitigation strategies. This study also provides biomonitoring data to help setting reference values for the occupationally exposed part of population.

Transcriptome analysis reveals activation of detoxification and defense mechanisms in smoke-exposed Merlot grape (Vitis vinifera) berries.

A significant consequence of climate change is the rising incidence of wildfires. When wildfires occur close to wine grape (Vitis vinifera) production areas, smoke-derived volatile phenolic compounds can be taken up by the grape berries, negatively affecting the flavor and aroma profile of the resulting wine and compromising the production value of entire vineyards. Evidence for the permeation of smoke-associated compounds into grape berries has been provided through metabolomics; however, the basis for grapevines' response to smoke at the gene expression level has not been investigated in detail. To address this knowledge gap, we employed time-course RNA sequencing to observe gene expression-level changes in grape berries in response to smoke exposure. Significant increases in gene expression (and enrichment of gene ontologies) associated with detoxification of reactive compounds, maintenance of redox homeostasis, and cell wall fortification were observed in response to smoke. These findings suggest that the accumulation of volatile phenols from smoke exposure activates mechanisms that render smoke-derived compounds less reactive while simultaneously fortifying intracellular defense mechanisms. The results of this work lend a better understanding of the molecular basis for grapevines' response to smoke and provide insight into the origins of smoke-taint-associated flavor and aroma attributes in wine produced from smoke-exposed grapes.

Deep learning models map rapid plant species changes from citizen science and remote sensing data.

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model-Deepbiosphere-not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Long-term exposure to wildland fire smoke PM2.5 and mortality in the contiguous United States.

Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM2.5), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM2.5 and nonaccidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous United States, 2007 to 2020. Controlling for nonsmoke PM2.5, air temperature, and unmeasured spatial and temporal confounders, we found a nonlinear association between 12-mo moving average concentration of smoke PM2.5 and monthly nonaccidental mortality rate. Relative to a month with the long-term smoke PM2.5 exposure below 0.1 µg/m3, nonaccidental mortality increased by 0.16 to 0.63 and 2.11 deaths per 100,000 people per month when the 12-mo moving average of PM2.5 concentration was of 0.1 to 5 and 5+ µg/m3, respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality were all found to be associated with long-term wildland fire smoke PM2.5 exposure. Smoke PM2.5 contributed to approximately 11,415 nonaccidental deaths/y (95% CI: 6,754, 16,075) in the contiguous United States. Higher smoke PM2.5-related increases in mortality rates were found for people aged 65 and above. Positive interaction effects with extreme heat were also observed. Our study identified the detrimental effects of long-term exposure to wildland fire smoke PM2.5 on a wide range of mortality outcomes, underscoring the need for public health actions and communications that span the health risks of both short- and long-term exposure.

Short-term effects of wildfire-specific fine particulate matter and its carbonaceous components on perinatal outcomes: A multicentre cohort study in New South Wales, Australia.

BACKGROUND: Epidemiological evidence on the association between wildfire-specific fine particulate matter (PM2.5) and its carbonaceous components with perinatal outcomes is limited. We aimed to examine the short-term effects of wildfire-specific PM2.5 and its carbonaceous components on perinatal outcomes. METHODS: A multicentre cohort of 9743 singleton births during the wildfire seasons from 1 September 2009 to 31 December 2015 across six cities in New South Wales, Australia were linked with daily wildfire-specific PM2.5 and carbonaceous components (organic carbon and black carbon). Adjusted distributed lag Cox regression models with spatial clustering were performed to estimate daily and cumulative adjusted hazard ratios (aHRs) during the last four gestational weeks for preterm birth, stillbirth, nonvertex presentation, low 5-min Apgar score, special care nursery/neonatal intensive care unit (SCN/NICU) admission, and caesarean section. RESULTS: Daily aHRs per 10 µg/m3 PM2.5 showed nearly inverted 'U'-shaped positive associations and daily cumulative aHRs that increased with increasing duration of the exposures. The aHRs for lag 0-6 days were 1.17 (95 % CI: 1.04, 1.32) for preterm birth, 1.40 (95 % CI: 1.11, 1.78) for stillbirth, 1.20 (95 % CI: 1.08, 1.33) for nonvertex presentation, 1.12 (95 % CI: 0.93, 1.35) for low 5-min Apgar score, 0.99 (95 % CI: 0.83, 1.19) for SNC/NICU admission, and 1.01 (95 % CI: 0.94, 1.08) for caesarean section. Organic carbon and black carbon components for lag 0-6 days showed positive associations. The highest component-specific aHRs were 1.09 (95 % CI: 1.03, 1.15) and 4.57 (95 % CI: 1.96, 10.68) for stillbirth per 1 µg/m3 organic carbon and black carbon, respectively. The subgroups identified as most vulnerable were female births, births to mothers with low socioeconomic status, and births to mothers with high biothermal exposure. CONCLUSIONS: Positive associations of short-term wildfire-specific PM2.5 exposure and its carbonaceous components with adverse perinatal outcomes suggest that policies to reduce exposure would benefit public health.

High-resolution temperature, salinity and depth data from southeastern Australian estuaries, 2018-2021.

Estuaries are the important interface between the land and sea, providing significant environmental, economic, cultural and social values. However, they face unprecedented pressures including eutrophication, harmful algal blooms, habitat loss, and extreme weather due to climate change. Here we present an open access, quality-controlled water quality dataset collected from twelve diverse estuaries spanning 1000 km along the southeastern Australian coastline. Water depth, temperature and salinity data were collected across two years (2018-2021) capturing drought, wildfire and flood periods, using high accuracy Seabird MicroCAT field sensors located within oyster leases. These fully autonomous instruments collected and transmitted data every 10 minutes before downstream quality checking and uploading onto a public website. Simultaneous, high-resolution, longitudinal environmental data collected across multiple estuaries throughout a range of extreme weather events are exceptionally rare in the Southern Hemisphere, yet provide an invaluable resource for the aquaculture industry, researchers and environmental regulators alike.

Forest fire size amplifies postfire land surface warming.

Climate warming has caused a widespread increase in extreme fire weather, making forest fires longer-lived and larger1-3. The average forest fire size in Canada, the USA and Australia has doubled or even tripled in recent decades4,5. In return, forest fires feed back to climate by modulating land-atmospheric carbon, nitrogen, aerosol, energy and water fluxes6-8. However, the surface climate impacts of increasingly large fires and their implications for land management remain to be established. Here we use satellite observations to show that in temperate and boreal forests in the Northern Hemisphere, fire size persistently amplified decade-long postfire land surface warming in summer per unit burnt area. Both warming and its amplification with fire size were found to diminish with an increasing abundance of broadleaf trees, consistent with their lower fire vulnerability compared with coniferous species9,10. Fire-size-enhanced warming may affect the success and composition of postfire stand regeneration11,12 as well as permafrost degradation13, presenting previously overlooked, additional feedback effects to future climate and fire dynamics. Given the projected increase in fire size in northern forests14,15, climate-smart forestry should aim to mitigate the climate risks of large fires, possibly by increasing the share of broadleaf trees, where appropriate, and avoiding active pyrophytes.

Dwelling proximity to wildfire and spina bifida risk in offspring.

OBJECTIVE: To evaluate the association between wildfire exposure in pregnancy and spina bifida risk. METHODS: This retrospective cohort study used the California Office of Statewide Health Planning and Development Linked Birth File with hospital discharge data between 2007 and 2010. The Birth File data were merged with the California Department of Forestry and Fire Protection data of the same year. Spina bifida was identified by its corresponding ICD-9 code listed on the hospital discharge of the newborn. Wildfire exposure was determined based on the zip code of the woman's home address. Pregnancy was considered exposed to wildfire if the mother lived within 15 miles of a wildfire during the pregnancy or within 30 days prior to pregnancy. RESULTS: There were 2,093,185 births and 659 cases of spina bifida between 2007 and 2010. The births were analyzed using multivariable logistic regression models and adjusted for potential confounders. Exposure to wildfire in the first trimester was associated with higher odds of spina bifida (aOR= 1.43 [1.11-1.84], p-value = 0.01). Wildfire exposure 30 days before the last menstrual period and during the second and third trimesters were not associated with higher spina bifida risk. CONCLUSION: Wildfire exposure has shown an increased risk of spina bifida during the early stages of pregnancy.

Spatiotemporal changes and background atmospheric factors associated with forest fires in Turkiye.

In this study, spatiotemporal analysis of forest fires in Turkiye was undertaken, with a specific focus on the large-scale atmospheric systems responsible for causing these fires. For this purpose, long-term variations in forest fires were classified based on the occurrence types (i.e. natural/lightning, negligence/inattention, arson, accident, unknown). The role of large-scale atmospheric circulations causing natural originated forest fires was investigated using NCEP/NCAR Reanalysis sea level pressure, and surface wind products for the selected episodes. According to the main results, Mediterranean (MeR), Aegean (AR), and Marmara (MR) regions of Turkiye are highly susceptible to forest fires. Statistically significant number of forest fires in the MeR and MR regions are associated with global warming trend of the Eastern Mediterranean Basin. In monthly distribution, forest fires frequently occur in the MeR part of Turkiye during September, August, and June months, respectively, and heat waves are responsible for forest fires in 2021. As a consequence of the extending summer Asiatic monsoon to the inner parts of Turkiye and the location of Azores surface high over Balkan Peninsula result in atmospheric blocking and associated calm weather conditions in the MeR (e.g. Mugla and Antalya provinces). When this blocking continues for a long time, southerly winds on the back slopes of the Taurus Mountains create a foehn effect, calm weather conditions and lack of moisture in the soil of Antalya and Mugla settlements trigger the formation of forest fires.

Temporal assessment of forest cover dynamics in response to forest fires and other environmental impacts using AI.

The rapid reduction of forests due to environmental impacts such as deforestation, global warming, natural disasters such as forest fires as well as various human activities is an escalating concern. The increasing frequency and severity of forest fires are causing significant harm to the ecosystem, economy, wildlife, and human safety. During dry and hot seasons, the likelihood of forest fires also increases. It is crucial to accurately monitor and analyze the large-scale changes in the forest cover to ensure sustainable forest management. Remote sensing technology helps to precisely study such changes in forest cover over a wide area over time. This research analyzes the impact of forest fires over time, identifies hotspots, and explores the environmental factors that affect forest cover change. Sentinel-2 imagery was utilized to study changes in Brunei Darussalam's forest cover area over five years from 2017 to 2022. An object-based approach, Simple Non-Iterative Clustering (SNIC), is employed to cluster the region using NDVI values and analyze the changes per cluster. The results indicate that the area of the clusters reduced where fire incidence occurred as well as the precipitation dropped. Between 2017 and 2022, the increased forest fires and decreased precipitation levels resulted in the change in cluster areas as follows: 66.11%, 69.46%, 68.32%, 73.88%, 77.27%, and 78.70%, respectively. Additionally, hotspots in response to forest fires each year were identified in the Belait district. This study will help forest managers assess the causes of forest cover loss and develop conservation and afforestation strategies.

A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future directions.

Forest fire risk assessment plays a crucial role in the environmental management of natural hazards, serving as a key tool in the prevention of forest fires and the protection of various species. As these risks continue to evolve with environmental changes, the pertinence of contemporary research in this field remains undiminished. This review constructs a comprehensive taxonomic framework for classifying the existing body of literature on forest fire risk assessment within forestry studies. The developed taxonomy categorizes existing studies into 8 primary categories and 23 subcategories, offering a structured perspective on the methodologies and focus areas prevalent in the domain. We categorize a sample of 170 articles to present recent trends and identify research gaps in forest fire risk assessment literature. The classification facilitates a critical evaluation of the current research landscape, identifying areas in need of further exploration. Particularly, our review identifies underrepresented methodologies such as optimization modeling and some advanced machine learning techniques, which present routes for future inquiry. Moreover, the review underscores the necessity for model development that is tailored to specific regional data sets but also adaptable to global data resources, striking a balance between local specificity and broad applicability. Emphasizing the dynamic nature of forest fire behavior, we advocate for models that integrate the burgeoning field of machine learning and multi-criteria decision analysis to refine predictive accuracy and operational effectiveness in fire risk assessment. This study highlights the great potential for new ideas in modeling techniques and emphasizes the need for increased collaboration among research communities to improve the effectiveness of assessing forest fire risks.

Post-fire recovery of nematode communities along a slope gradient in a pine forest.

We investigated the enduring consequences of a wildfire on nematode diversity and abundance in a pine forest, employing a slope gradient approach. Our primary objective was to determine the extent of post-fire alterations in the nematode community 3 years after the incident, to understand if the ecosystem has returned to its pre-fire state or has transitioned to a distinctive ecological environment. Three distinct burned pine forest sites at varying elevations were sampled to capture short-scale soil property variations due to slope gradients, while unburned forest sites served as controls. A consistent pattern emerged where the lowest altitude sites exhibited the highest nematode abundances, although still lower than unburned sites. Fire-induced changes were profound, shifting from fungivore dominance in unburned sites to bacterivore and herbivore dominance in burned sites. Alterations in soil properties post-fire, particularly reduced organic matter and nitrogen content, were closely associated with nematode community shifts. Water availability played a crucial role with lower moisture levels at higher elevations impacting nematode populations. Structural differences in the nematode community primarily resulted from fire disturbance rather than altitude. This study emphasizes the persistent and transformative impact of wildfire on nematode communities, highlighting the intricate interplay between ecological disturbances, soil properties, and nematode trophic dynamics.

Gestational exposure to wildfire PM2.5 and its specific components and the risk of gestational hypertension and eclampsia in the southwestern United States.

In the southwestern United States, the frequency of summer wildfires has elevated ambient PM2.5 concentrations and rates of adverse birth outcomes. Notably, hypertensive disorders in pregnancy (HDP) constitute a significant determinant associated with maternal mortality and adverse birth outcomes. Despite the accumulating body of evidence, scant research has delved into the correlation between chemical components of wildfire PM2.5 and the risk of HDP. Derived from data provided by the National Center for Health Statistics, singleton births from >2.68 million pregnant women were selected across 8 states (Arizona, AZ; California, CA, Idaho, ID, Montana, MT; Nevada, NV; Oregon, OR; Utah, UT, and Wyoming, WY) in the southwestern US from 2001 to 2004. A spatiotemporal model and a Goddard Earth Observing System chemical transport model were employed to forecast daily concentrations of total and wildfire PM2.5-derived exposure. Various modeling techniques including unadjusted analyses, covariate-adjusted models, propensity-score matching, and double robust typical logit models were applied to assess the relationship between wildfire PM2.5 exposure and gestational hypertension and eclampsia. Exposure to fire PM2.5, fire-sourced black carbon (BC) and organic carbon (OC) were associated with an augmented risk of gestational hypertension (ORPM2.5 = 1.125, 95 % CI: 1.109,1.141; ORBC = 1.247, 95 % CI: 1.214,1.281; OROC = 1.153, 95 % CI: 1.132, 1.174) and eclampsia (ORPM2.5 = 1.217, 95 % CI: 1.145,1.293; ORBC = 1.458, 95 % CI: 1.291,1.646; OROC = 1.309, 95 % CI: 1.208,1.418) during the pregnancy exposure window with the strongest effect. The associations were stronger that the observed effects of ambient PM2.5 in which the sources primarily came from urban emissions. Social vulnerability index (SVI), education years, pre-pregnancy diabetes, and hypertension acted as effect modifiers. Gestational exposure to wildfire PM2.5 and specific chemical components (BC and OC) increased gestational hypertension and eclampsia risk in the southwestern United States.

Robust differential gene expression patterns in the prefrontal cortex of male mice exposed to an occupationally relevant dose of laboratory-generated wildfire smoke.

Wildfires have become common global phenomena concurrent with warmer and drier climates and are now major contributors to ambient air pollution worldwide. Exposure to wildfire smoke has been classically associated with adverse cardiopulmonary health outcomes, especially in vulnerable populations. Recent work has expanded our understanding of wildfire smoke toxicology to include effects on the central nervous system and reproductive function; however, the neurotoxic profile of this toxicant remains ill-explored in an occupational context. Here, we sought to address this by using RNA sequencing to examine transcriptomic signatures in the prefrontal cortex of male mice modeling career wildland firefighter smoke exposure. We report robust changes in gene expression profiles between smoke-exposed samples and filtered air controls, evidenced by 2,862 differentially expressed genes (51.2% increased). We further characterized the functional relevance of these genes highlighting enriched pathways related to synaptic transmission, neuroplasticity, blood-brain barrier integrity, and neurotransmitter metabolism. Additionally, we identified possible contributors to these alterations through protein-protein interaction network mapping, which revealed a central node at ß-catenin and secondary hubs centered around mitochondrial oxidases, the Wnt signaling pathway, and gene expression machinery. The data reported here will serve as the foundation for future experiments aiming to characterize the phenotypic effects and mechanistic underpinnings of occupational wildfire smoke neurotoxicology.

Determination of forest fire risk with respect to Marchalina hellenica potential distribution to protect pine honey production sites in Turkey.

Turkey is the leading producer of pine honey worldwide, accounting for 90% of global production, largely due to the presence of Marchalina hellenica populations. However, in recent years, devastating forest fires have caused substantial damage to Pinus brutia forests and M. hellenica populations, leading to a dramatic decline in pine honey production areas. The urgency for early intervention procedures against forest fires and relocation of M. hellenica populations to other P. brutia forests has become apparent. A comprehensive assessment of 25 criteria was conducted to investigate the thresholds and behaviors of each criterion, which play a vital role in the distribution of M. hellenica, using the maximum entropy model (MaxEnt). To evaluate the impact of forest fires on the distribution of M. hellenica, the potential locations of pine honey production areas were determined for 2022. Furthermore, the susceptibility of forest fires was modeled for all pine honey production months. The findings revealed that forest fires have destroyed 384.9 km2 (12.8% of the total pine honey production area), predominantly in August and September, with the most severe damage in Marmaris (156 km2) and significant impacts in Ula, Köycegiz, and Milas. The analysis facilitates the estimation of new areas suitable for M. hellenica and pine honey production while providing valuable insights into strategies for mitigating forest fires and formulating proactive protection protocols.