Linking Forest Fire Regimes and Climate—A Historical Analysis in a Dry Inner Alpine Valley

Forest fire regimes are likely to experience considerable changes in the European Alps due to climatic changes. However, little is known about the recent regional fire history and the impact of local climate on the fire regime during the 20th century. We therefore reconstructed the fire history in a dry continental valley of the Swiss Alps (Valais) over the past 100 years based on documentary evidence, and investigated the relationship between the reconstructed fire regime and the local climatic variability. We compared the impact of temperature, precipitation, drought and dry foehn winds on fire frequency, extent of burnt area, and fire seasonality on various spatial and temporal scales. In the subalpine zone, the fire regime appears to have been mainly driven by temperature and precipitation, whereas these variables seem to have played only a secondary role in the colline–montane zones. Here, foehn winds and, probably, non-climatic factors seem to have been more important. Temperature and precipitation played a major role in shaping fire frequency and burnt area in the first half of the 20th century, but lost their importance during the second half. Our case study illustrates the occurrence of different fire regime patterns and their driving forces on small spatial scales (a few hundred square kilometers). We conclude that the strong rise in temperature over the past century has not profoundly changed the fire regime in Valais, but in the second half of the 20th century temperature was no longer a strong determinant for forest fires as compared to human activities or biomass availability in forests. Author contributions: T.Z., H.B., M.C., and M.B. conceived of or designed study; T.Z. performed research and analyzed data; T.Z., H.B., M.C., and M.B. wrote the paper.     

大兴安岭人为火发生影响因素及气候变化下的趋势

我国重要的北方针叶林地区大兴安岭是林火高发地区.受气候变暖影响,该地区林火发生频率将会发生显著变化.模拟人为火的发生分布与影响因素之间的关系、加强气候变化下人为火的发生分布预测,对于林火管理和减少森林碳损失具有重要作用.本文采用点格局分析方法,基于大兴安岭1967—2006年的火烧数据,建立人为火空间分布与影响因素之间的关系模型,该模型以林火发生次数为因变量,选取非生物因子(年均温和降水量、坡度、坡向和海拔)、生物因子(植被类型)和人为活动因子(距离道路距离、距离居民点距离、道路密度)共9个因子为自变量.并采用RCP 2.6和RCP 8.5气候情景数据代替当前气候情景预测2050年大兴安岭人为火的空间分布状况.结果表明: 点格局模型能够较好地模拟人为火发生分布与空间变量的关系,可以预测未来气候下人为火的发生概率.其中,气候因子对人为火的发生具有明显的控制作用,植被类型、海拔和人为活动等因子对人为火的发生也具有重要影响.林火发生预测结果表明,未来气候变化下,南部地区的林火发生概率将进一步增加,北部和沿主要道路干线附近将成为新的人为火高发区.与当前相比,2050年大兴安岭人为火的发生概率将增加72.2%～166.7%.在未来气候情景下,人为火的发生更多受气候和人为活动因素的控制.     

Scale matters: fire–vegetation feedbacks are needed to explain tropical tree cover at the local scale

At a broad (regional to global) spatial scale, tropical vegetation is controlled by climate; at the local scale, it is believed to be determined by interactions between disturbance, vegetation and local conditions (soil and topography) through feedback processes. It has recently been suggested that strong fire–vegetation feedback processes may not be needed to explain tree‐cover patterns in tropical ecosystems and that climate–fire determinism is an alternative possibility. This conclusion was based on the fact that it is possible to reproduce observed patterns in tropical regions (e.g. a trimodal frequency distribution of tree cover) using a simple model that does not explicitly incorporate fire–vegetation feedback processes. We argue that these two mechanisms (feedbacks versus fire–climate control) operate at different spatial and temporal scales; it is not possible to evaluate the role of a process acting at fine scales (e.g. fire–vegetation feedbacks) using a model designed to reproduce regional‐scale pattern (scale mismatch). While the distributions of forest and savannas are partially determined by climate, many studies are providing evidence that the most parsimonious explanation for their environmental overlaps is the existence of feedback processes. Climate is unlikely to be an alternative to feedback processes; rather, climate and fire–vegetation feedbacks are complementary processes at different spatial and temporal scales.     

气候变化背景下江西省林火空间预测

林火是森林生态系统中重要的干扰因子之一,深刻地影响森林景观结构和功能。在全球气候化背景下,揭示气候变化对林火空间分布格局的影响,可为林火管理和防火资源分配提供科学指导。因此,基于江西省2001—2015年MODIS火影像数据(MCD14ML)和年均气温、年均降水量、植被、地形、人口密度、距道路距离、距居民点距离7个因子数据,利用增强回归树模型:(1)分析林火发生影响因子的相对重要性及其边际效应;(2)将GFDL-CM3和GISS-E2-R气候变化模式中的年均气温和年均降水量作为未来的气象数据,在3个温室气体排放量情景(RCP2.6、RCP4.5、RCP8.5)下,对2050年(2041—2060的平均值)和2070年(2061—2080的平均值)江西省林火分布进行预测,生成林火发生概率图。并采用受试者工作特征(ROC曲线)和混淆矩阵评估模型预测的精度。研究结果表明:(1)年均气温和海拔与江西省林火发生的相关性较强,年均降水量、居民点距离、人口密度、道路距离与林火发生的相关性较弱,但是与林火发生密切相关的如降水、风速等也应重点关注;(2)训练数据(70%)和验证数据(30%)的AUC值(ROC曲线下面积值)均为0.736,混淆矩阵对火点预测的正确率为67.8%,表明模型能够较好地预测研究区林火的发生;(3)在RCP8.5排放情景中林火发生的增幅最明显,其增幅较大的区域由赣南向赣北移动;(4)未来2050年和2070年林火发生与当前气候(2001—2015年)下相比,赣州市、鹰潭市的增幅较为明显,其他区域不明显。江西省各林业管理部门要加强林火高发区及潜在发生区的森林监测和管理,加大防火宣传力度,提升民众的森林防火意识。     

Spatial Controls of Pre–Euro-American Wind and Fire Disturbance in Northern Wisconsin (USA) Forest Landscapes

We elucidate spatial controls of wind and fire disturbance across northern Wisconsin (USA), where climatic and topographic gradients are not strong, using data from the original US Public Land Survey (PLS) notes. These records contain information on the location and extent of heavy windthrows and stand-replacing fires prior to Euro-American settlement. The spatial patterns of windthrow and fire were spatially clustered at all scales in this historical environment, with stronger associations at local than regional scales. Logistic regression shows environmental variables to have a strong influence on this pattern. In the case of heavy windthrow, environmental drivers of disturbance pattern are fairly consistent across the region. The effects of climate and vegetation are predominant at all scales, but effects are often indirect, with strong interactions between them. Interactions between these two drivers and soil characteristics are also sometimes present. In contrast, models of stand-replacing fire show simple and direct control within and across fire-prone landscapes of historical northern Wisconsin, with climate and physiography as the main factors explaining the distribution of fire disturbance. This simple and direct control is lost at the regional scale, where climate, physiographic, soil, and vegetation variables, along with interactions between them, are significant factors. Contrary to other regions, the topographic effects are generally not important in predicting either wind or fire disturbance. Our work suggests that, in landscapes that lack strong environmental patterning, climate maintains its role as a primary driver of these natural disturbances, but topography is replaced by interactions and feedbacks with other forms of environmental heterogeneity.     

Fire regimes of China: inference from statistical comparison with the United States

Aim Substantial overlap in the climate characteristics of the United States and China results in similar land‐cover types and weather conditions, especially in the eastern half of the two countries. These parallels suggest similarities in fire regimes as well, yet relatively little is known about the historical role of fire in Chinese ecosystems. Consequently, we aimed to infer fire regime characteristics for China based on our understanding of climate–fire relationships in the United States. Location The conterminous United States and the People's Republic of China. Methods We used generalized additive models to quantify the relationship between reference fire regime classes adopted by the LANDFIRE initiative in the United States, and a global climate data set. With the models, we determined which climate variables best described the distribution of fire regimes in the United States then used these models to predict the spatial distribution of fire regimes in China. The fitted models were validated quantitatively using receiver operating characteristic area under the curve (AUC). We validated the predicted fire regimes in China by comparison with palaeoecological fire data and satellite‐derived estimates of current fire activity. Results Quantitative validation using the AUC indicated good discrimination of the distribution of fire regimes by models for the United States. Overall, fire regimes with more frequent return intervals were more likely in the east than in the west. The resolution of available historical and prehistorical fire data for China, including sediment cores, allowed only coarse, qualitative validation, but provided supporting evidence that fire has long been a part of ecosystem function in eastern China. MODIS satellite data illustrated that fire frequency within the last decade supported the classification of much of western China as relatively fire‐free; however, much of south‐eastern China experiences more fire activity than predicted with our models, probably as a function of the extensive use of fire by people. Conclusions While acknowledging there are many cultural, environmental and historical differences between the United States and China, our fire regime models based on climate data demonstrate potential historical fire regimes for China, and propose that large areas of China share historical fire–vegetation–climate complexes with the United States.     

Vegetation controls vary across space and spatial scale in a historic grassland‐forest biome boundary

Ecological boundaries are critical landscape regions of transition between adjacent ecological systems. While environmental controls of boundaries may operate in a scale‐dependent manner, multiple‐scale comparisons of vegetation–environment relationships have been characterized for few boundary systems. We used approximately 250 000 point records on the occurrence of woody versus grassland vegetation in conjunction with climatic, topographical, and soils data to evaluate scale effects and spatial heterogeneity in a 650‐km section of the historic prairie–forest biome boundary of Minnesota, USA. We chose this as a model system because of the availability of historical vegetation data, a considerable spatial extent, a sharp ecological transition, and the ability to avoid confounding from more recent anthropogenic land use change. We developed modeling techniques using hierarchical variance partitioning in a spatially‐structured format that allowed us to simultaneously evaluate vegetation–environment relationships across two‐dimensional space (i.e. the prairie‐forest boundary) and across spatial scales (i.e. varying extents). Soils variables displayed the least spatial autocorrelation at shortest lag distances and tended to be the least important predictors of woody vegetation at all spatial extents. Topographical variables displayed greater spatial heterogeneity in regions dominated by forest compared with prairie and were more important at fine‐intermediate spatial scales, highlighting their likely control on fire regimes. An integrated climatic variable (precipitation minus potential evapotranspiration) displayed a trend of increasing spatial variance across the study region and was unambiguously the strongest biome boundary control, although its joint influence with fire was difficult to characterize. Spatially heterogeneous vegetation–environment relationships were observed at all scales, especially at finer scales. Our results suggest that the importance of environmental controls changes smoothly rather than discretely across scales and demonstrate the need to account for spatial non‐stationarity and scale to predict and understand vegetation distribution across ecological boundaries.     

Precipitation‐use efficiency along a 4500‐km grassland transect

Aims Clarifying the spatiotemporal variations in precipitation‐use efficiency (PUE), the ratio of vegetation above‐ground productivity to annual precipitation, will advance our understanding of how ecosystems' carbon and water cycles respond to climate change. Our goal is to investigate the variations in PUE at both regional and site scales along a 4500‐km climate‐related grassland transect. Location The Inner Mongolian Plateau in northern China and the Qinghai‐Tibetan Plateau. Methods We collected data on 580 sites from four data sources. The data were acquired through field surveys and long‐term in situ observations. We investigated the relationships between precipitation and PUE at both regional and site scales, and we evaluated the effects of the main biotic and climatic factors on PUE at both spatial scales. Results PUE decreased with decreasing mean annual precipitation (MAP), except for a slight rise toward the dry end of the gradient. The maximum PUE showed large site‐to‐site variation along the transect. Vegetation cover significantly affected the spatial variations in PUE, and this probably accounts for the positive relationship between PUE and MAP. However, there was no significant relationship between inter‐annual variations in precipitation or vegetation cover and PUE within given ecosystems along the transect. Conclusions The findings of this research contradict the prevailing view that a convergent maximum PUE exists among diverse ecosystems, as presented in previous reports. Our findings also suggest the action of distinct mechanisms in controlling PUE at different spatial scales. We propose the use of a conceptual model for predicting vegetation productivity at continental and global scales with a sigmoid function, which illustrates an increasing PUE with MAP in arid regions. Our approach may represent an improvement over use of the popular Miami model.     

森林可燃物及其管理的研究进展与展望

森林可燃物是森林生态系统的基本组成部分, 是影响林火发生及火烧强度的重要因素之一, 因此, 受到国内外学者的广泛关注。该文从以下4个方面综述了国内外可燃物研究的最新进展: 森林可燃物特性, 森林可燃物类型与火行为, 森林可燃物类型、载量的调查与制图, 森林可燃物管理。同时提出了我国森林可燃物今后的研究方向: 开展多尺度可燃物研究; 可燃物类型与火行为的研究; 把以试验观测为基础的静态研究与以空间技术和生态模型为基础的动态预测相结合, 研究可燃物处理效果; 全球气候变化背景下可燃物处理与碳收支。     

A simplified GIS approach to modeling global leaf water isoscapes

The stable hydrogen (delta(2)H) and oxygen (delta(18)O) isotope ratios of organic and inorganic materials record biological and physical processes through the effects of substrate isotopic composition and fractionations that occur as reactions proceed. At large scales, these processes can exhibit spatial predictability because of the effects of coherent climatic patterns over the Earth's surface. Attempts to model spatial variation in the stable isotope ratios of water have been made for decades. Leaf water has a particular importance for some applications, including plant organic materials that record spatial and temporal climate variability and that may be a source of food for migrating animals. It is also an important source of the variability in the isotopic composition of atmospheric gases. Although efforts to model global-scale leaf water isotope ratio spatial variation have been made (especially of delta(18)O), significant uncertainty remains in models and their execution across spatial domains. We introduce here a Geographic Information System (GIS) approach to the generation of global, spatially-explicit isotope landscapes (= isoscapes) of "climate normal" leaf water isotope ratios. We evaluate the approach and the resulting products by comparison with simulation model outputs and point measurements, where obtainable, over the Earth's surface. The isoscapes were generated using biophysical models of isotope fractionation and spatially continuous precipitation isotope and climate layers as input model drivers. Leaf water delta(18)O isoscapes produced here generally agreed with latitudinal averages from GCM/biophysical model products, as well as mean values from point measurements. These results show global-scale spatial coherence in leaf water isotope ratios, similar to that observed for precipitation and validate the GIS approach to modeling leaf water isotopes. These results demonstrate that relatively simple models of leaf water enrichment combined with spatially continuous precipitation isotope ratio and climate data layers yield accurate global leaf water estimates applicable to important questions in ecology and atmospheric science.     

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes.     

Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis Program,Landsat, and LANDFIRE

The concentrations of CO₂ and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High Plateaus. We also estimated that 8054 Mg AFBC were released from 2.24 km² burned forest area in the Longston fire. These results demonstrate that an AFBC spatial map and estimated biomass carbon consumption can readily be generated using existing database. The methodology provides a consistent, practical, and inexpensive way for estimating AFBC at 30-m resolution over large areas throughout the United States.     

基于主成分分析的广西省干旱时空格局

广西省地处喀斯特地貌区,土壤保水效率低,且年降水时空分布不均,研究干旱时空分布尤为重要。基于广西省1981—2010年20个气象站实测和2011—2100年HadGEM2-ES模型模拟数据,利用标准化降水指数(SPI, Standardized Precipitation Index)和标准化降水蒸散指数(SPEI,Standardized Precipitation Evapotranspiration Index),分析广西省干旱的时空变化。对不同时间尺度的SPI和SPEI应用主成分分析(PCA,Principal Component Analysis)确定干旱的空间模式,结果揭示了3个空间分布明确的区域:桂东北地区(PC1),桂西北地区(PC2)和桂南地区(PC3)。各区域干旱的时空变化和频率分布差异显著。PC1和PC3的SPEI-12呈负增长趋势,PC2的SPEI-12呈正增长趋势,且PC1、PC2和PC3的SPI-12均大于SPEI-12。年尺度(SPEI-12)上PC1和PC3的干旱频率大于PC2,其干旱频率分别为34.24%和35.83%。SPI和SPEI在空间和时间尺度上相关,且具有高度可比性。SPEI因子载荷的空间模式优于SPI,严重干旱年份(1988、1996和2003年)的SPI值明显小于SPEI,且SPEI检测到的干旱频率较高。研究结果可作为广西省干旱预测、评估及其风险管理和应用决策的重要科学基础,也可为广西省区域社会经济发展提供重要的科学参考。     

Empirical modelling of lake water-temperature relationships: a comparison of approaches

1.  As a result of the role that temperature plays in many aquatic processes, good predictive models of annual maximum near-surface lake water temperature across large spatial scales are needed, particularly given concerns regarding climate change. Comparisons of suitable modelling approaches are required to determine their relative merit and suitability for providing good predictions of current conditions. We developed models predicting annual maximum near-surface lake water temperatures for lakes across Canada using four statistical approaches: multiple regression, regression tree, artificial neural networks and Bayesian multiple regression.
2.  Annual maximum near-surface (from 0 to 2 m) lake water-temperature data were obtained for more than 13 000 lakes and were matched to geographic, climatic, lake morphology, physical habitat and water chemistry data. We modelled 2348 lakes and three subsets thereof encompassing different spatial scales and predictor variables to identify the relative importance of these variables at predicting lake temperature.
3.  Although artificial neural networks were marginally better for three of the four data sets, multiple regression was considered to provide the best solution based on the combination of model performance and computational complexity. Climatic variables and date of sampling were the most important variables for predicting water temperature in our models.
4.  Lake morphology did not play a substantial role in predicting lake temperature across any of the spatial scales. Maximum near-surface temperatures for Canadian lakes appeared to be dominated by large-scale climatic and geographic patterns, rather than lake-specific variables, such as lake morphology and water chemistry.     

Spatial patterns and drivers of fire occurrence and its future trend under climate change in a boreal forest of Northeast China

Understanding the spatial patterns of fire occurrence and its response to climate change is vital to fire risk mitigation and vegetation management. Focusing on boreal forests in Northeast China, we used spatial point pattern analysis to model fire occurrence reported from 1965 to 2009. Our objectives were to quantitate the relative importance of biotic, abiotic, and human influences on patterns of fire occurrence and to map the spatial distribution of fire occurrence density (number of fires occurring over a given area and time period) under current and future climate conditions. Our results showed human‐caused fires were strongly related to human activities (e.g. landscape accessibility), including proximity to settlements and roads. In contrast, fuel moisture and vegetation type were the most important controlling factors on the spatial pattern of lightning fires. Both current and future projected spatial distributions of the overall (human‐ + lightning‐caused) fire occurrence density were strongly clustered along linear components of human infrastructure. Our results demonstrated that the predicted change in overall fire occurrence density is positively related to the degree of temperature and precipitation change, although the spatial pattern of change is expected to vary spatially according to proximity to human ignition sources, and in a manner inconsistent with predicted climate change. Compared to the current overall fire occurrence density (median value: 0.36 fires per 1000 km² per year), the overall fire occurrence density is projected to increase by 30% under the CGCM3 B1 scenario and by 230% under HadCM3 A2 scenario in 2081–2100, respectively. Our results suggest that climate change effects may not outweigh the effects of human influence on overall fire occurrence over the next century in this cultural landscape. Accurate forecasts of future fire‐climate relationships should account for anthropogenic influences on fire ignition density, such as roads and proximity to settlements.     

Can we project changes in fish abundance and distribution in response to climate?

Large‐scale and long‐term changes in fish abundance and distribution in response to climate change have been simulated using both statistical and process‐based models. However, national and regional fisheries management requires also shorter term projections on smaller spatial scales, and these need to be validated against fisheries data. A 26‐year time series of fish surveys with high spatial resolution in the North‐East Atlantic provides a unique opportunity to assess the ability of models to correctly simulate the changes in fish distribution and abundance that occurred in response to climate variability and change. We use a dynamic bioclimate envelope model forced by physical–biogeochemical output from eight ocean models to simulate changes in fish abundance and distribution at scales down to a spatial resolution of 0.5°. When comparing with these simulations with annual fish survey data, we found the largest differences at the 0.5° scale. Differences between fishery model runs driven by different biogeochemical models decrease dramatically when results are aggregated to larger scales (e.g. the whole North Sea), to total catches rather than individual species or when the ensemble mean instead of individual simulations are used. Recent improvements in the fidelity of biogeochemical models translate into lower error rates in the fisheries simulations. However, predictions based on different biogeochemical models are often more similar to each other than they are to the survey data, except for some pelagic species. We conclude that model results can be used to guide fisheries management at larger spatial scales, but more caution is needed at smaller scales.     

Revisiting the provenance delineation of a widespread shrub, <Emphasis Type="Italic">Frangula alnus</Emphasis>—the role of spatial,temporal and environmental patterns

Including population genetic aspects into the selection of planting material within the framework of conservation and restoration measures is of vital importance for the long-term persistence of populations. This is especially true facing climate change since genetic diversity and the spread of potentially beneficial alleles are important for the adaptability of populations. Therefore, knowledge about genetic variability within and between populations is a critical aspect when determining provenance regions. In our study, we investigated the population genetic structure of a widespread, insect-pollinated and mainly bird-dispersed shrub species, Frangula alnus, on the basis of seven microsatellites and two chloroplast DNA markers throughout Germany. The aim was to determine the spatial, temporal and ecological processes genetically structuring populations to critically revise existing provenance regions. Therefore, we conducted analyses on different spatial scales (country-wide, regional and local) using the two different marker sets in addition to environmental variables. We detected distinct patterns on all spatial scales which indicated influences of historic recolonization processes, regional differences of seed dispersal across the landscape, as well as small-scale spatial genetic structures attributable to local dispersal processes. No relation of underlying environmental gradients such as temperature or precipitation and genetic patterns was found. We conclude that different aspects of historic and more recent gene flow shape population genetic structures and that a thorough analysis on a variety of spatial, temporal and environmental scales is necessary to appropriately select planting material for conservation and restoration measures. Correspondingly, management advice regarding provenance delineations will be provided.     

Do lakes feel the burn? Ecological consequences of increasing exposure of lakes to fire in the continental United States

Wildfires are becoming larger and more frequent across much of the United States due to anthropogenic climate change. No studies, however, have assessed fire prevalence in lake watersheds at broad spatial and temporal scales, and thus it is unknown whether wildfires threaten lakes and reservoirs (hereafter, lakes) of the United States. We show that fire activity has increased in lake watersheds across the continental United States from 1984 to 2015, particularly since 2005. Lakes have experienced the greatest fire activity in the western United States, Southern Great Plains, and Florida. Despite over 30 years of increasing fire exposure, fire effects on fresh waters have not been well studied; previous research has generally focused on streams, and most of the limited lake‐fire research has been conducted in boreal landscapes. We therefore propose a conceptual model of how fire may influence the physical, chemical, and biological properties of lake ecosystems by synthesizing the best available science from terrestrial, aquatic, fire, and landscape ecology. This model also highlights emerging research priorities and provides a starting point to help land and lake managers anticipate potential effects of fire on ecosystem services provided by fresh waters and their watersheds.