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      Wildfire smoke impacts lake ecosystems

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          Abstract

          Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities.

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          Most cited references108

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          Global fire emissions estimates during 1997–2016

          Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2016. The modeling system, based on the Carnegie–Ames–Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1) new burned area estimates with contributions from small fires, (2) a revised fuel consumption parameterization optimized using field observations, (3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2  ×  10 15  grams of carbon per year (Pg C yr −1 ) during 1997–2016, with a maximum in 1997 (3.0 Pg C yr −1 ) and minimum in 2013 (1.8 Pg C yr −1 ). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (−19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5 Pg C yr −1 . The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org .
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            Estimating the volume and age of water stored in global lakes using a geo-statistical approach

            Lakes are key components of biogeochemical and ecological processes, thus knowledge about their distribution, volume and residence time is crucial in understanding their properties and interactions within the Earth system. However, global information is scarce and inconsistent across spatial scales and regions. Here we develop a geo-statistical model to estimate the volume of global lakes with a surface area of at least 10 ha based on the surrounding terrain information. Our spatially resolved database shows 1.42 million individual polygons of natural lakes with a total surface area of 2.67 × 106 km2 (1.8% of global land area), a total shoreline length of 7.2 × 106 km (about four times longer than the world's ocean coastline) and a total volume of 181.9 × 103 km3 (0.8% of total global non-frozen terrestrial water stocks). We also compute mean and median hydraulic residence times for all lakes to be 1,834 days and 456 days, respectively.
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              Estimated Global Mortality Attributable to Smoke from Landscape Fires

              Background: Forest, grass, and peat fires release approximately 2 petagrams of carbon into the atmosphere each year, influencing weather, climate, and air quality. Objective: We estimated the annual global mortality attributable to landscape fire smoke (LFS). Methods: Daily and annual exposure to particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) from fire emissions was estimated globally for 1997 through 2006 by combining outputs from a chemical transport model with satellite-based observations of aerosol optical depth. In World Health Organization (WHO) subregions classified as sporadically affected, the daily burden of mortality was estimated using previously published concentration–response coefficients for the association between short-term elevations in PM2.5 from LFS (contrasted with 0 μg/m3 from LFS) and all-cause mortality. In subregions classified as chronically affected, the annual burden of mortality was estimated using the American Cancer Society study coefficient for the association between long-term PM2.5 exposure and all-cause mortality. The annual average PM2.5 estimates were contrasted with theoretical minimum (counterfactual) concentrations in each chronically affected subregion. Sensitivity of mortality estimates to different exposure assessments, counterfactual estimates, and concentration–response functions was evaluated. Strong La Niña and El Niño years were compared to assess the influence of interannual climatic variability. Results: Our principal estimate for the average mortality attributable to LFS exposure was 339,000 deaths annually. In sensitivity analyses the interquartile range of all tested estimates was 260,000–600,000. The regions most affected were sub-Saharan Africa (157,000) and Southeast Asia (110,000). Estimated annual mortality during La Niña was 262,000, compared with 532,000 during El Niño. Conclusions: Fire emissions are an important contributor to global mortality. Adverse health outcomes associated with LFS could be substantially reduced by curtailing burning of tropical rainforests, which rarely burn naturally. The large estimated influence of El Niño suggests a relationship between climate and the burden of mortality attributable to LFS.
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                Journal
                Global Change Biology
                Global Change Biology
                Wiley
                1354-1013
                1365-2486
                June 2024
                June 05 2024
                June 2024
                : 30
                : 6
                Affiliations
                [1 ] Department of Environmental Science and Policy University of California Davis Davis California USA
                [2 ] Department of Watershed Sciences and Ecology Center Utah State University Logan Utah USA
                [3 ] Ecosystems and Global Change Group, School of the Environment Trent University Peterborough Ontario Canada
                [4 ] Ecosystems and Global Change Group, Department of Plant Sciences University of Cambridge Cambridge UK
                [5 ] Minnesota Pollution Control Agency St. Paul Minnesota USA
                [6 ] Universidade Do Estado de Minas Gerais (UEMG), Unidade Divinópolis Divinópolis Minas Gerais Brazil
                [7 ] Department of Biology and Global Water Center University of Nevada Reno Nevada USA
                [8 ] Department of Civil and Environmental Engineering University of California Davis Davis California USA
                [9 ] National Scientific and Technical Research Council (CONICET) Buenos Aires Argentina
                [10 ] Department of Biology Franklin and Marshall College Lancaster Pennsylvania USA
                [11 ] Department of Civil and Environmental Engineering/Tahoe Environmental Research Center University of California Davis Davis California USA
                [12 ] Department of Land, Air and Water Resources University of California Davis Davis California USA
                [13 ] Department of Fisheries and Wildlife Michigan State University East Lansing Michigan USA
                [14 ] Institute of Arctic and Alpine Research, University of Colorado Boulder Boulder Colorado USA
                [15 ] Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge Tennessee USA
                [16 ] Department of Biology Queen's University Kingston Ontario Canada
                [17 ] Instituto Argentino de Oceanografía, Universidad Nacional del Sur (UNS)‐CONICET Bahía Blanca Buenos Aires Argentina
                [18 ] Departamento de Geografía y Turismo Universidad Nacional del Sur Bahía Blanca Buenos Aires Argentina
                [19 ] Department of Ecology and Evolutionary Biology University of California Irvine Irvine California USA
                [20 ] School of Civil and Environmental Engineering, Cornell University Ithaca New York USA
                Article
                10.1111/gcb.17367
                d50adcb4-f1c2-40c6-adba-a9f5b956f055
                © 2024

                http://creativecommons.org/licenses/by/4.0/

                http://creativecommons.org/licenses/by/4.0/

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