气候变暖背景下内蒙古大兴安岭林区森林可燃物干燥状况的变化

可燃物湿度是评价林火发生危险程度的最直接指标.林火的发生和蔓延很大程度上受气象条件的制约,气候变暖对林火产生重要影响.利用每日气象数据和加拿大火险天气指数系统(FWI),计算了1972～2005年内蒙古大兴安岭林区森林可燃物的3个湿度码,即细小可燃物湿度码(FFMC)、半腐层湿度码(DMC)和干旱码(DC);并分别春季防火期、秋季防火期及夏季非防火期,研究了3个湿度码长时间序列的变化趋势,在此基础上分析了气候变暖背景下林区可燃物干燥状况的变化及对林火的影响.结果表明:1972～2005年FFMC、DMC和DC的季节性均值都呈增加趋势,且夏季FFMC和DMC增加趋势显著;这意味着1972～2005年可燃物的干燥状况呈增加趋势,其中夏季非防火期表层和半腐层可燃物的增加趋势显著.可燃物干燥状况的增加,特别是夏季可燃物干燥状况的增加,是近些年林区夏季雷击火灾频发的主要原因之一.半腐层和深层可燃物干燥状况的增加,会加大火灾控制和火场清理的难度.在未来更暖的气候条件下,林区可燃物的干燥状况会变得更加严峻.     

基于FWI湿度码的塔河林业局地表凋落物含水率预测

加拿大火险天气指标系统(FWI)是目前世界上应用最广的火险天气系统,其可燃物含水率预测方法成为一种重要的研究方法.本文以黑龙江省大兴安岭地区塔河林业局典型林分为研究对象,通过野外地表凋落物含水率的连续观测,分析了凋落物含水率与FWI系统3个湿度码\[细小可燃物湿度码（FFMC）、枯落物下层湿度码（DMC）、干旱码（DC）\]之间的关系.结果表明： 对于研究地区8个样地单独取样的地表凋落物,用FWI系统的湿度码FFMC所建立的线性预测方程的平均绝对误差和平均相对误差分别为14.9%和70.7%,低于气象要素回归模型,说明采用FWI湿度码来预测地表凋落物含水率具有一定优势,可用于预测可燃物含水率,但这种优势是有限的.今后应加强对FWI系统在我国应用的修正工作,特别是雨后可燃物湿度码的修正.     

黑龙江省大兴安岭地区塔河县森林火险天气指标动态

基于大兴安岭地区塔河县1974-2008年森林火灾数据和同期气象数据,结合加拿大火险天气系统(CFFWIS),定量和定性分析了该区森林火险天气指标动态.结果表明:1974-2008年,研究区森林火灾年均发生次数呈增加趋势,2000-2008年森林火灾年均发生次数比1974-1999年增加了72.2%;可燃物湿度码、火行为指标和火灾控制难易度指标总体呈增加趋势,且这种增加趋势随着时间的推进更加明显.未来该区森林火灾发生概率将显著递增,可燃物将更加干燥,林火强度增强,控制火灾将更加困难,火险天气状况更加严峻.该区应重点加大森林火灾的防控,尤其是夏季火灾的防控;并应加大计划可燃物的烧除,减少可燃物载量,从可燃物这一源头上减少火灾发生概率和降低火灾强度.     

基于负二项和零膨胀负二项回归模型的大兴安岭地区雷击火与气象因素的关系

雷击火的发生与气象因子之间存在着密切的关系。该文选用符合大兴安岭地区林火发生数据结构的负二项(negative binomial,NB)和零膨胀负二项(zero-inflated negative binomial,ZINB)两种模型对大兴安岭林区1980–2005年间雷击火的发生与气象因素间的关系进行建模分析,并与以往研究中所使用的最小二乘(OLS)回归方法相对比。使用SAS和R-Project统计软件进行模型拟合运算,计算得出模型各参数。结果表明,NB和ZINB模型对数据拟合较好,模型内各气象因子显著性水平较高,对雷击火发生次数均具有较好的预测能力。运用AIC和Vuong等检验方法,进一步比较了NB和ZINB模型对数据的拟合水平以及模型预测水平,结果表明ZINB模型无论在数据拟合还是模型预测上都要优于NB模型。提出了大兴安岭地区林火发生与气象因子关系的最优模型。     

贵州省林火发生驱动因子及预测模型

中国西南林区火源复杂,人为干扰大,多为喀斯特地貌和农林交错区,山形复杂,是中国林火发生的重灾区。分析该区域林火发生驱动因子,并进行火险区划,对于该地区合理的林火管理工作具有重要意义。本研究以西南地区的贵州省为对象,基于2011—2020年的森林火点数据、地理空间数据、气象数据、植被数据和人类活动数据等,利用ArcGIS 10.7的空间分析和R Studio等软件分析贵州省近10年林火分布时空格局,得到林火发生的驱动因子和概率预测模型,分别绘制春夏秋冬4个季节的贵州省林火发生概率和森林火险区划图。结果表明：近10年,贵州省火点数量逐年呈下降趋势,每年主要集中在1—3月,占全年火点数量的61%;距居民点距离、距铁路距离、人口密度、逐月平均空气温度、逐月平均相对湿度和逐月累计降雨量对贵州省林火发生概率有显著影响,得到模型的预测准确率为81.9%,曲线下面积为0.904;贵州省春季林火发生概率高于其他季节,且春、秋和冬季的森林火灾高火险区主要集中在贵州省西部,而夏季则主要是贵州东部的林火发生概率较高。研究得到贵州省林火发生驱动因子和基于季节火险区划图,对于该地区科学林火管理具有重要意义,贵州西...     

大兴安岭地区森林雷击火与闪电的关系

林火是森林生态系统的重要影响因子.随着全球气候变暖,林火,特别是雷击火有增多的趋势.本文对我国东北大兴安岭地区1966-2007年的林火数据及相应的闪电和气象资料进行分析.结果表明:1966-2007年,该地区雷击火的次数及其过火面积都呈显著增加趋势.影响雷击火的气象条件与研究时间尺度有关,年尺度的雷击火与降水显著相关,相关系数达-0.489;月尺度的雷击火则与气温显著相关,相关系数为0.18.雷击火与闪电的关系也与时间尺度有关,年尺度的雷击火与闪电关系不明显,受降水影响较大;月尺度的雷击火与闪电具有较好的相关性,且受降水的影响;日尺度的雷击火在降水量＞5 mm时与闪电关系不明显,但当降水量＜5 mm时,雷击火与闪电次数呈正相关.据此,发展了基于闪电定位仪数据的火险指数算法以及大兴安岭地区的森林雷击火预报模型.经2005-2007年雷击火验证,该模型的预报准确率＞80％.     

基于卷积神经网络及气象要素回归法的地表死可燃物含水率预测模型

地表可燃物含水率是森林火险等级和火行为变化的重要指标,其预测模型对于火险预测、火灾管理等具有显著作用。本研究基于蒙古栎及樟子松林地的野外气象因子以及地表死可燃物含水率数据,进行气象因子随机森林相对重要性排序以及皮尔逊相关性分析,并使用深度学习中的卷积神经网络以及气象要素回归法预测可燃物含水率。结果表明：野外蒙古栎的可燃物含水率显著高于樟子松。随机森林结果表明,对于可燃物含水率具有显著作用的因子排列顺序从大到小为湿度、温度、降雨、风速、太阳辐射;相关性分析表明,当日的温度、湿度、降雨对于可燃物含水率具有显著影响,同时,气象因子之间也存在一定的相关性。卷积神经网络模型对于蒙古栎及樟子松林地表可燃物含水率的预测R²分别为0.928、0.905,平均绝对误差(MAE)分别为6.1%、8.1%,平均相对误差(MRE)分别为8.9%、4.2%;气象要素回归法的R²分别为0.495、0.525,MAE分别为30.5%、39.5%,MRE分别为52.1%、32.6%,卷积神经网络模型精度显著高于气象要素回归法。研究表明,深度学习的卷积神经网络能够为今后的可燃...     

我国北方针叶林人为火发生的预测模型

我国北方针叶林带是重要的森林资源储藏地,也是林火发生的重灾区,其自然火和人为火所占比例相当. 气象因子、地形特征、植被条件、人为基础设施等因素对人为火发生具有显著影响,国内目前应用空间分析技术对北方针叶林带人为火影响因子的研究还存在一定不确定性. 本文基于1974—2009年间人为火的空间地理坐标,结合研究地的气象因子、基础地理信息及矢量化林相图,应用ArcGIS 10.0中的空间分析工具和SPSS 19.0的逻辑斯蒂回归模型对影响人为火发生的主要驱动因子进行分析,并建立人为火发生的概率模型. 利用HADCM2模式下研究区域未来气象数据对塔河地区2015年人为火发生情况进行计算.结果表明： 距离铁路距离（x₁）和平均相对湿度（x₂）对研究区域人为火发生具有显著影响,并得到火险概率模型P=1/［1+e^{-(3.026-0.00011x1-0.047x₂)}］. 模型校验结果显示,模型的准确度可达到80%.林火发生预测结果表明,塔河地区2015年 4—6月、8月为人为火高发期,其中,4—5月的林火发生概率最高.从火险空间分布来看,高火险主要集中在塔河西部和西南部,铁路线路主要包含在此区域.     

我国林火发生预测模型研究进展

通过文献回顾,总结了国内林火发生预测模型的研究现状,并从林火发生驱动因子、林火发生概率预测模型、林火发生频次预测模型和模型检验方法等方面进行归纳分析。得出以下结论: 1)气象、地形、植被、可燃物、人类活动等因素是影响林火发生及模型预测精度的主要驱动因子;2)林火发生概率模型中,地理加权逻辑斯蒂回归模型考虑了变量之间的空间相关性,Gompit回归模型适宜非对称结构的林火数据,随机森林模型不需要多重共线性检验,在避免过度拟合的同时提高了预测精度,是林火发生概率预测模型的优选方法之一;3)林火发生频次模型中,负二项回归模型更适合对过度离散数据进行模拟,零膨胀模型和栅栏模型可以处理林火数据中包含大量零值的问题;4)ROC检验、AIC检验、似然比检验和Wald检验方法是林火概率和频次模型的常用检验方法。林火发生预测模型研究仍是我国当前林火管理工作的重点,预测模型的选择需要依据不同地区林火数据特点。此外,构建林火预测模型时需要考虑更多的影响因素,以提高模型预测精度;未来,需要进一步探索其他数学模型在林火发生预测中的应用,不断提高林火发生预测模型的准确度。     

大兴安岭呼中林区虫害与火干扰交互作用的长期模拟

虫害和林火是森林生态系统的两种主要干扰类型,各种干扰在大时空尺度上存在一定的交互作用.本文采用空间直观景观模型LANDIS模拟虫害和林火在300年内的交互作用.结果表明:虫害干扰降低了细可燃物载量,提高了模拟前期(0～100 a)和中期(100～200 a)的粗可燃物载量,降低了模拟前期和中期的林火频率,不同干扰预案模拟后期(200～300 a)火烧频率的结果比较接近;虫害干扰降低了模拟前期和后期的火烧强度,增加了模拟中期的火烧强度,提高了模拟中期的森林火险等级,降低了模拟前期和后期的火险等级.人类灭火可增加虫害的发生面积,因此建议森林管理部门采取适当的防虫措施,不可只注重灭火,可以采取可燃物去除和计划火烧等方式管理林火,促进森林生态系统的可持续发展.     

Historic distribution and driving factors of human-caused fires in the Chinese boreal forest between 1972 and 2005

Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire management. The aims of the study were: (i) to describe the history of human-caused fires by season and size of burned area over time; (ii) to identify the spatial patterns of human-caused fires and test for the existence of 'hotspots' to determine their exact locations in the Daxing'an Mountains; (iii) to determine the driving factors that determine the spatial distribution and the possibility of human-caused fire occurrence.Methods In this study, K -function and Kernel density estimation were used to analyze the spatial pattern of human-caused fires. The analysis was conducted in S-plus and ArcGIS environments, respectively. The analysis of driving factors was performed in SPSS 19.0 based on a logistic regression model. The variables used to identify factors that influence fire occurrence included vegetation types, meteorological conditions, socioeconomic factors, topography and infrastructure factors, which were extracted and collected through the spatial analysis mode of ArcGIS and from official statistics, respectively.Important findings The annual number of human-caused fires and the area burnt have declined since 1987 due to the implementation of a forest fire protection act. There were significant spatial heterogeneity and seasonal variations in the distribution of human-caused fires in the Daxing'an Mountains. The heterogeneity was caused by elevation, distance to the nearest railway, forest type and temperature. A logistic regression model was developed to predict the likelihood of human-caused fire occurrence in the Daxing'an Mountains; its global accuracy attained 64.8%. The model was thus comparable to other relevant studies.     

Spatial and temporal variation in historic fire regimes in subalpine forests across the Colorado Front Range in Rocky Mountain National Park, Colorado, USA

Aim The historical variability of fire regimes must be understood in the context of drivers of the occurrence of fire operating at a range of spatial scales from local site conditions to broad‐scale climatic variation. In the present study we examine fire history and variations in the fire regime at multiple spatial and temporal scales for subalpine forests of Engelmann spruce–subalpine fir (Picea engelmannii, Abies lasiocarpa) and lodgepole pine (Pinus contorta) of the southern Rocky Mountains. Location The study area is the subalpine zone of spruce–fir and lodgepole pine forests in the southern sector of Rocky Mountain National Park (ROMO), Colorado, USA, which straddles the continental divide of the northern Colorado Front Range (40°20′ N and 105°40′ W). Methods We used a combination of dendroecological and Geographic Information System methods to reconstruct fire history, including fire year, severity and extent at the forest patch level, for c. 30,000 ha of subalpine forest. We aggregated fire history information at appropriate spatial scales to test for drivers of the fire regime at local, meso, and regional scales. Results The fire histories covered c. 30,000 ha of forest and were based on a total of 676 partial cross‐sections of fire‐scarred trees and 6152 tree‐core age samples. The subalpine forest fire regime of ROMO is dominated by infrequent, extensive, stand‐replacing fire events, whereas surface fires affected only 1–3% of the forested area. Main conclusions Local‐scale influences on fire regimes are reflected by differences in the relative proportions of stands of different ages between the lodgepole pine and spruce–fir forest types. Lodgepole pine stands all originated following fires in the last 400 years; in contrast, large areas of spruce–fir forests consisted of stands not affected by fire in the past 400 years. Meso‐scale influences on fire regimes are reflected by fewer but larger fires on the west vs. east side of the continental divide. These differences appear to be explained by less frequent and severe drought on the west side, and by the spread of fires from lower‐elevation mixed‐conifer montane forests on the east side. Regional‐scale climatic variation is the primary driver of infrequent, large fire events, but its effects are modulated by local‐ and meso‐scale abiotic and biotic factors. The low incidence of fire during the period of fire‐suppression policy in the twentieth century is not unique in comparison with the previous 300 years of fire history. There is no evidence that fire suppression has resulted in either the fire regime or current forest conditions being outside their historic ranges of variability during the past 400 years. Furthermore, in the context of fuel treatments to reduce fire hazard, regardless of restoration goals, the association of extremely large and severe fires with infrequent and exceptional drought calls into question the future effectiveness of tree thinning to mitigate fire hazard in the subalpine zone.     

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.     

大兴安岭森林火烧恢复年限对土壤磷及其有效性的影响

林火是大兴安岭地区森林生态系统的重要影响因子,对地下土壤养分,特别是磷及其有效性变化长时间序列研究,将有助于林火后植被恢复管理、模型模拟及科学评价。选择呼中、南瓮河、双河、图强、塔河、加格达奇、满归等地区火后恢复2-50年样地48块,并以火烧区域周边相似地形地貌、未经火烧区域为配对对照样地,野外调查记录地形地貌和地理位置数据,室内分析土壤全磷和速效磷。配对t检验、冗余排序分析、趋势分析、离散性分析等处理相结合,试图找出火烧后土壤磷及其有效性变化特征。研究结果表明：（1）整体数据平均值及离散程度表明,火后全磷及速效磷均值均稍低于对照,火后二者的离散程度为37%-49%,低于对照样地6-22个百分点;区分不同恢复时间,配对t检验未发现火烧样地土壤磷与对照间的显著差异。（2）以火烧对照比值及差值进行趋势分析发现,相对于对照,火烧后全磷呈现先增加后降低的变化趋势（R²=0.89-0.95,P=0.07-0.15）,火后20-30年间开始低于对照样地。速效磷也呈类似变化趋势,但是相关性较低（R²=0.44-0.67,P=0.44-0.66）;速效磷占比年代变化趋势不明显（R²=0.08-0.12,P > 0.95）。（3）RDA排序分析表明,火烧导致恢复年限成为影响磷变化的最主要因素（15.3%）,其次是经度（10.7%）;而在对照样地中,纬度是土壤磷变化最关键影响因素,能够解释其变化总量的27.6%。研究结果为森林火后土壤养分管理以及森林演替生态评价提供重要参数。     

树种水平的大兴安岭地上生物量变化特征及其与气候和干扰的关系

树种水平地上生物量(每个树种的地上生物量)是衡量森林生态系统结构功能的重要指标。为揭示树种水平森林地上生物量变化机制及其与气候变化和干扰的关系,运用KNN (k-nearest neighbor distance)方法将森林调查数据和MODIS数据相结合,估算了黑龙江大兴安岭2000、2010和2015年树种水平的森林地上生物量,在此基础上运用典型对应分析和随机森林方法,分析了研究区树种水平地上生物量变化特征及其与气候和干扰因素的关系。研究结果表明:2000—2015年期间,研究区总的森林地上生物量增加了8.9%(0.41×10~8 t),其中2010—2015年期间地上生物量的增加速度要明显高于2000—2010年;地上生物量增加最多的树种为白桦(Betula platyphylla Suk.),与2000年相比生物量增加了0.40×10~8 t,其次为樟子松(Pinus sylvestris var.mongolica Litv.)、山杨(Populus davidiana Dode)和蒙古栎(Quercus mongolica Fisch. ex Ledeb.),落叶松(Larix gmelinii(Rupr.) Kuzen)地上生物量下降了0.08×10~8 t,柳树(Chosenia arbutifolia(Pall.) A. Skv.)和云杉(Picea koraiensis Nakai)基本上没有变化;林火、采伐和造林等森林干扰均对树种水平地上生物量影响显著,林火对树种水平地上生物量的影响要高于造林和采伐;气候要素显示出了比干扰要素更为重要的作用,多年平均温度和降水解释了最多的树种水平地上生物量变异。年均温度与阔叶树种的生物量以及林火干扰有显著的正相关性,与总的森林地上生物量呈现出显著的负相关,与落叶松和白桦表现出微弱的负相关,预示着气候变暖将影响该区域的树种组成并降低该区域的森林生产力。     

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.     

不同强度火干扰下盘古林场天然落叶松林的空间结构

基于2011年7月大兴安岭外业调查数据以林隙为主要研究对象,选取景观生态学中斑块类型指数分析样地内林隙状况,并结合林木分布状态,分析不同强度林火干扰对天然落叶松林空间结构的影响。结果表明:在受中度林火干扰的林分内,只保留了少量的落叶松中径木、大径木,先锋树种在林分内呈现聚集分布;在未受林火干扰的林分和受林火轻微干扰的林分内,天然落叶松均呈现显著聚集分布;由于受到不同强度的林火干扰,林下区域与林隙区域出现不同程度的相互转化,林分空间结构发生了改变。林分按照所受林火干扰强度的递减,在同一时间不同空间上表现出了森林循环过程中所经历的林隙阶段状态、建立阶段状态、成熟阶段状态。     

比较逻辑斯蒂与地理加权逻辑斯蒂回归模型在福建林火发生的适用性

林火预测预报是科学有效进行林火管理的前提,是林业管理部门和科研工作者的广泛关注的领域。逻辑斯蒂回归(Logistic Regression,LR)是目前国内外广泛应用于森林火灾预测的模型方法,然而近年来有学者发现该方法没有充分考虑林火影响因子的空间相关性和异质性,从而导致模型拟合结果偏差。地理加权逻辑斯蒂回归(Geographically weighted logistic regression,GWR)模型考虑到了模型变量之间的空间相关性,有效提高的模型的拟合能力。为探讨GWLR模型在福建林火预测上的适用性,本研究应用LR和GWLR两种方法分别建立福建省森林火灾与气象因子的预测模型,通过模型拟合能力对比,判断在GWLR的适用性。研究以2000—2005年福建地区森林火灾卫星火点数据和每日气象因子为基础,将全样本分为60%的建模数据和40%的校验数据,并重复5次,建立5个样本组。选择在5个样本组中3个及以上表现显著的变量进入最终模型。研究结果表明GWLR在模型拟合度、模型残差、空间自相关性以及预测准确率等方面均优于LR模型,说明充分考虑模型变量的空间异质性有助于提高模型的预测精度,同时也验证了GWLR在福建地区林火预测上的适应性。此外,模型参数结果显示,"日最高地表气温"、"日最低地表气温"、"日平均风速"、"24小时降水量"、"日最高本站气压"、"日照时数"、"日最高气温"和"日最小相对湿度"8个因子对福建省林火发生有显著影响,研究结论为福建地区林火预测预报提供了新的方法。     

Fire disturbance and forest structure in an old‐growth Pinus ponderosa forest,southern Cascades,USA

Questions: Did fire regimes in old‐growth Pinus ponderosa forest change with Euro‐American settlement compared to the pre‐settlement period? Do tree age structures exhibit a pattern of continuous regeneration or is regeneration episodic and related to fire disturbance or fire‐free periods? Are the forests compositionally stable? Do trees have a clumped spatial pattern and are clumps even‐ or mixed‐age? How might information from this old‐growth forest inform current restoration and management practices? Location: A 235‐ha old‐growth forest in the Ishi Wilderness, southern Cascade Mountains, California. Methods: Age, size, and spatial pattern of trees were quantified in seven stands. Fire history was reconstructed using fire scar dendrochronology. The influence of fire on stand structure was assessed by comparing fire history with age, size, and spatial structure of trees and identifying and measuring trees killed by two recent fires. Results: Species composition in plots was similar but density and basal area of tree populations varied. Age structure for P. ponderosa and Quercus kelloggii showed periods of episodic recruitment that varied among plots. Fire disturbance was frequent before 1905, with a median period between fires of 12 years. Fire frequency declined after 1905 but two recent fires (1990, 1994) killed 36% and 41% of mostly smaller diameter P. ponderosa and Q. kelloggii. Clusters of similar age trees occurred at scales of 28‐1018 m² but patches were not even‐aged. Interactions between tree regeneration and fire promoted development of uneven age groups of trees. Conclusions: Fire disturbance strongly influenced density, basal area, and spatial structure of tree populations. Fire exclusion over the last 100 years has caused compositional and structural changes. Two recent fires, however, thinned stands and created gaps favorable for Q. kelloggii and P. ponderosa regeneration. The effects of infrequent 20th century fire indicate that a low fire frequency can restore and sustain structural characteristics resembling those of the pre‐fire suppression period forest.