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.     

大兴安岭塔河地区雷击火发生驱动因子综合分析

森林火灾是一个全球性问题,对森林资源和温室气体排放有重要影响,并严重影响人们生命财产安全。林火主要分为人为火(人为活动引起)和雷击火(雷电引起)两大类。在我国北方针叶林带,雷击火主要集中在黑龙江大兴安岭和内蒙古呼伦贝尔盟地区。大兴安岭塔河地区位于我国北方针叶林带,是森林火灾的重灾区。其中雷击火所占比例大约1/3以上。目前针对当地雷击火与影响因子的研究主要集中于气象因子,非气象因子(森林可燃物和地形特征)的研究受数据条件和技术手段限制研究报道较少。研究数据包含三部分,林火数据,气象数据和地理植被数据。林火数据包含1974—2009年间林火发生经纬度坐标,时间和面积等。气象数据主要包括每日尺度的最低气温,最高气温,平均风速,平均相对湿度等因子。根据加拿大火险天气指标系统计算出了出了细小可燃物湿度码(FFMC),干燥可燃物湿度码(DMC)和干旱码(DC)也没用于本研究。此外,基于1∶10万塔河地区数字化林相图提取了海拔、坡度、坡向、森林类型、优势树种、龄级等因子用于决策因子分析。研究数据分析过程主要应用Arc GIS10.0中的空间分析工具和SPSS19.0的逻辑斯蒂回归模型完成。研究结果显示"日最低气温","最大风速"和"最小相对湿度"3个气象因子及火险天气指标系统(FWI)中细小可燃物湿度码(FFMC)干旱码(DC)与雷击火发生概率显著相关(P0.05),模型整体拟合水平R2(CoxSnell)=0.326。在非气象因子与雷击火发生的逻辑斯蒂模型检验中,"地被物盖度"和"龄级"均在P=0.05水平上与雷击火发生显著相关,其模型的整体拟合水平R2(CoxSnell)为0.15。研究结论表明在分析雷击火发生的决策因子时,应该综合考虑气象、可燃物和林分因素。     

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...     

1961—2010年中国植被区的气候与林火动态变化

气候、植被和人为活动的变化影响到区域的林火动态．基于生态地理区研究全国尺度上林火动态的变化是科学林火管理的基础．根据中国地面气候资料日值数据,把1961—2010年气温和降水两个气象要素差值到网格点（空间分辨率0.25°×0.25°）,分析中国8个生态地理区森林分布区域的火险期气温和降水量变化,采用Mann-Kendall法分析气候和火动态的变化趋势．结果表明： 1961—2010年,中国森林分布区的平均气温呈现线性上升趋势,但降水量变化趋势不显著,所有生态地理区的火险期平均气温显著增加,中温带半干旱/干旱地区草原区增温最显著,而大部分区域的火险期降水量变化不明显.研究区火灾次数呈现明显的波动性,受害森林面积显著下降.除中温带干旱地区荒漠针叶林区的火灾次数和受害森林面积呈现显著的增加趋势外,其他生态地理区都表现为双峰型变化曲线.     

基于MODIS卫星火点的浙江省林火季节变化及驱动因子

研究林火变化趋势和驱动因子,可为林火预防和管理提供科学依据。本研究基于MODIS卫星火点数据,结合气象(日平均风速、日平均温度、日相对湿度、气温日较差、日累计降水)、人为(到公路距离、到铁路距离、到居民点距离、人口密度、人均GDP)、地形和植被因素(高程、坡度、植被覆盖度),运用趋势分析法、Logistic回归模型,对浙江省2001—2016年林火变化趋势和驱动因子进行研究。结果表明: 浙江省春、夏季林火呈显著上升趋势,秋、冬季林火呈先上升后下降趋势,秋季下降趋势显著。浙江省各季节林火预测模型拟合度均较高,模型预测准确率分别为75.8%(春季)、79.1%(夏季)、74.7%(秋季)和79.6%(冬季)。浙江省春、夏季林火发生与变化受气象、人为、地形和植被因素的显著影响;秋、冬季林火发生与变化主要受气象因素影响。在影响因素复杂、高火险区域分散的春、夏季,林火管理应重点加强人为活动管理和防火宣传教育;在秋、冬季,可通过在高火险区集中分布的西南地区增设瞭望塔和监控设备进行监测和管理。     

1961—2010年安徽省参考作物蒸散时空变化特征及成因

基于联和国粮农组织推荐的Penman Monteith公式和60个台站1961—2010年逐日气象观测资料,估算了安徽省的参考作物蒸散量(ET₀),在对ET₀空间分布特征和时间演变规律进行分析的基础上,定量探讨了安徽省影响ET₀变化的主导因素.结果表明: 研究期间,安徽省ET₀的年平均值约为878.58 mm·a^-1,夏季最大,冬季最小.年平均ET₀呈现由北向南、由低海拔向高海拔递减的空间分布特征.ET₀的变化主要归因于日照时数和风速,而气温和相对湿度的作用较小.由于日照时数和风速的共同负贡献明显超过气温和相对湿度的共同正贡献,导致安徽省ET₀整体上以-1.61 mm·a^-1的速率显著下降.ET₀在春季呈不显著的微弱上升趋势;夏季ET₀以-1.37 mm·a^-1的速率显著下降;秋、冬季的ET₀微弱下降,但趋势不显著.春、秋、冬季ET₀变化的主导因子是风速;夏季的主导因子是日照时数.ET₀变化的主导因子存在明显空间差异.有36.7%站点的年平均ET₀变化的主导因子是风速,主要分布在淮北南部和沿淮地区;其他大部分地区的主导因子都是日照时数.
     

基于InTEC模型的塔河森林净初级生产力影响因子定量分析

森林净初级生产力(NPP)是反映森林碳源/汇能力的重要参数,其时空变化同时受气象变化(大气温度、降水等)、大气成分变化(CO₂浓度、N沉降)和各种森林干扰的影响.然而,目前影响森林NPP变化的关键因子尚不明确.为了探究这一问题,本研究在综合考虑InTEC模型的干扰和非干扰因子的基础上,重新模拟了不同立地指数下的NPP-林龄关系,并嵌入1987—2015年林火数据,模拟1901—2015年塔河森林平均NPP变化特征,设计9种模拟情景定量分析1961—2015年不同影响因子对塔河森林NPP变化的贡献,并探究塔河森林NPP年际以及年代变化的主要影响因子,为森林经营提供指导性策略.结果表明: 1901—1960年,塔河森林NPP的变化趋势较为平稳,1960年以后NPP随干扰因子变化趋势显著.林火和立地指数(SCI)的引入,均在不同时间对NPP的分布特征产生了不同影响.1960年以后,塔河森林NPP大幅变化的主要原因是森林年龄和林火的干扰,其年际平均贡献率为-49%,其次是降水和CO₂,分别为-28%和17%,气温和氮沉降的平均贡献率分别为5%和1%.     

基于3PGS-MTCLIM模型模拟根河林区火后植被净初级生产力恢复及其影响因子

林火是大兴安岭林区主要的干扰因子,且对森林生态系统的碳平衡有着重要影响.火干扰强度以及不同地形条件所导致的山地气候差异是影响火后植被净初级生产力恢复过程的主导因素.本研究以内蒙古根河林区为例,使用多时相的Landsat TM遥感数据(2008—2012年)和1980—2010年间的气象资料,结合山地小气候模型MTCLIM与光能利用效率模型3PGS,模拟森林火后植被净初级生产力(NPP)的时空恢复过程,并探讨不同火烧强度和地形因子对NPP恢复进程的影响.结果表明: 3PGS-MTCLIM模型能够较准确地在小尺度范围内模拟NPP的空间分布格局,模拟结果与样地具有较好的对应关系,R²=0.828;3PGS-MTCLIM模型模拟火后NPP下降百分比在43%~80%,相对于火前NPP水平该区域的平均恢复周期大约为10年;火烧强度对火后恢复具有显著影响,火烧强度越强,NPP恢复所需要的周期越长,火后NPP恢复速度呈现先快后慢的增长趋势;地形因子中,海拔对火后NPP恢复程度的影响最明显,其次为坡度,而坡向的影响最小.     

基于FARSITE模型的丰林自然保护区潜在林火行为空间分布特征

将FARSITE火行为模型应用于丰林自然保护区林火行为预测,并根据Rothermel和Rinehart制定的林火行为等级标准,编制潜在林火行为空间区划图,以探讨林火行为的空间分布特征。研究结果表明:在有可能、易发生和极易发生3个森林火险等级下,丰林自然保护区林火行为主要分布在Class I和ClassⅡ等级上,使用手工工具可能从火头控制火势蔓延;林火行为等级空间分布特征较为明显,ClassⅢ等级的火行为主要分布在区域中东部,ClassⅡ主要分布在区域中部,而Class I则主要分布在区域四周;高强度林火行为主要分布在可燃物模型为FL-Ⅰ和FL-Ⅱ,海拔为300—400 m、坡度为平坡和缓坡、坡向为阳坡上。高强度林火发生在接近道路与居民点500 m的区域内分布面积明显高于分布在距离道路居民点500—1000 m和1000—1500 m区域。     

少动鞘脂单胞菌产结冷胶发酵培养基的响应面法优化

通过单因素试验分析不同碳源、氮源、无机盐对（Sphingomonas paucimobilisFJAT-5627）产胶量的影响,确定最适碳源、氮源、无机盐,并在单因素筛选试验的基础上,利用Box-Benhnken设计和响应面分析法对碳源、氮源和无机盐进行优化,得到少动鞘脂单胞菌产生结冷肢发酵培养基最佳优化组合.实验结果表明,少动鞘脂单胞菌产胶量发酵最适碳源、氮源和无机盐分别为淀粉、豆饼粉和KH₂PO₄.响应面法得到产胶量（Y）与碳源淀粉（x₁）、氮源豆饼粉（x₂）和无机盐KH₂PO₄（x₃）的回归方程为:Y=13.87+0.54x₁+0.22x₂-0.42x₃-3.26x₁²-1.85x₂²-1.51x₃²+0.053x₁x₂+0.067x₁x₃+0.4x₂x₃.优化培养基组合为:淀粉浓度为30g/L,豆饼粉浓度为5 g/L,KH₂PO₄的浓度为0.7g/L,且此组合下少动鞘脂假单胞发酵得到结冷胶可达23.87g/L.     

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.     

Spatiotemporal Variations of Fire Frequency in Central Boreal Forest

Determination of the direct causal factors controlling wildfires is key to understanding wildfire–vegetation–climate dynamics in a changing climate and for developing sustainable management strategies for biodiversity conservation and maintenance of long-term forest productivity. In this study, we sought to understand how the fire frequency of a large mixedwood forest in the central boreal shield varies as a result of temporal and spatial factors. We reconstructed the fire history of an 11,600-km² area located in the northwestern boreal forest of Ontario, using archival data of large fires occurring since 1921 and dendrochronological dating for fires prior to 1921. The fire cycle decreased from 295 years for the period of 1820–1920 to approximately 100 years for the period of 1921–2008. Spatially, fire frequency increased with latitude, attributable to higher human activities that have increased fragmentation and fire suppression in the southern portion of the study area. Fire frequency also increased with distance to waterbodies, and was higher on Podzols that were strongly correlated with moderate drainage and coniferous vegetation. The temporal increase of fire frequency in the central region, unlike western and eastern boreal forests where fire frequency has decreased, may be a result of increased warm and dry conditions associated with climate change in central North America, suggesting that the response of wildfire to global climate change may be regionally individualistic. The significant spatial factors we found in this study are in agreement with other wildfire studies, indicating the commonality of the influences by physiographic features and human activities on regional fire regimes across the boreal forest. Overall, wildfire in the central boreal shield is more frequent than that in the wetter eastern boreal region and less frequent than that in the drier western boreal region, confirming a climatic top-down control on the fire activities of the entire North American boreal forest.     

基于气象因子的森林火灾面积预测模型

通过统计分析理论研究了黑龙江省林火发生规律,并建立了基于气象因子的森林火灾面积预测模型．结果表明：兴安落叶松林区林火主要发生在4-6月和10月,阔叶红松林区林火主要发生在3-6月和10月;利用林火发生当日的平均风速、相对湿度和平均温度的取值范围可知,兴安落叶松林区发生高等级林火概率较大的月份依次为4月、5月和6月,阔叶红松林区则依次为5月、4月和3月．所建模型的平均精度达到63．3％,能够较精确地预测林火发生后林地可能的过火面积．     

Fire and the relative roles of weather,climate and landscape characteristics in the Great Lakes‐St. Lawrence forest of Canada

Question: In deciduous‐dominated forest landscapes, what are the relative roles of fire weather, climate, human and biophysical landscape characteristics for explaining variation in large fire occurrence and area burned? Location: The Great Lakes‐St. Lawrence forest of Canada. Methods: We characterized the recent (1959–1999) regime of large (≥ 200 ha) fires in 26 deciduous‐dominated landscapes and analysed these data in an information‐theoretic framework to compare six hypotheses that related fire occurrence and area burned to fire weather severity, climate normals, population and road densities, and enduring landscape characteristics such as surficial deposits and large lakes. Results: 392 large fires burned 833 698 ha during the study period, annually burning on average 0.07%± 0.42% of forested area in each landscape. Fire activity was strongly seasonal, with most fires and area burned occurring in May and June. A combination of antecedent‐winter precipitation, fire season precipitation deficit/surplus and percent of landscape covered by well‐drained surficial deposits best explained fire occurrence and area burned. Fire occurrence varied only as a function of fire weather and climate variables, whereas area burned was also explained by percent cover of aspen and pine stands, human population density and two enduring characteristics: percent cover of large water bodies and glaciofluvial deposits. Conclusion: Understanding the relative role of these variables may help design adaptation strategies for forecasted increases in fire weather severity by allowing (1) prioritization of landscapes according to enduring characteristics and (2) management of their composition so that substantially increased fire activity would be necessary to transform landscape structure and composition.     

气候变化和林火干扰对大兴安岭林区地上生物量影响的动态模拟

预测森林地上生物量对气候变化和林火干扰的响应是陆地生态系统碳循环研究的重要内容,气温、降水等因素的改变和气候变暖导致林火干扰强度的变化将会影响森林生态系统的碳库动态.东北森林作为我国森林的重要组成部分,对气候变化和林火干扰的响应逐渐显现.本文运用LANDIS PRO模型,模拟气候变化对大兴安岭森林地上生物量的影响,并比较分析了气候变暖对森林地上生物量的直接影响与通过林火干扰强度改变所产生的影响.结果表明: 未来气候变暖和火干扰增强情景下,森林地上生物量增加;当前气候条件和火干扰下,研究区森林地上生物量为(97.14±5.78) t·hm^-2;在B1F2预案下,森林地上生物量均值为(97.93±5.83) t·hm^-2;在A2F3预案下,景观水平第100～150和150～200年模拟时期内的森林地上生物量均值较高,分别为(100.02±3.76)和(110.56±4.08) t·hm^-2.与当前火干扰相比,CF2预案(当前火干扰增加30%)在一定时期使景观水平地上生物量增加(0.56±1.45) t·hm^-2,CF3预案(当前火干扰增加230%)在整个模拟阶段使地上生物量减少(7.39±1.79) t·hm^-2.针叶、阔叶树种对气候变暖的响应存在差异,兴安落叶松和白桦生物量随气候变暖表现为降低趋势,而樟子松、云杉和山杨的地上生物量则随气候变暖表现出不同程度的增加;气候变暖对针阔树种的直接影响具有时滞性,针叶树种响应时间比阔叶树种迟25～50年.研究区森林对高CO₂排放情景下气候变暖和高强度火干扰的共同作用较为敏感,未来将明显改变研究区森林生态系统的树种组成和结构.     

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。     

The effect of climate anomalies and human ignition factor on wildfires in Russian boreal forests

Over the last few years anomalies in temperature and precipitation in northern Russia have been regarded as manifestations of climate change. During the same period exceptional forest fire seasons have been reported, prompting many authors to suggest that these in turn are due to climate change. In this paper, we examine the number and areal extent of forest fires across boreal Russia for the period 2002-2005 within two forest categories: 'intact forests' and 'non-intact forests'. Results show a far lower density of fire events in intact forests (5-14 times less) and that those events tend to be in the first 10 km buffer zone inside intact forest areas. Results also show that, during exceptional climatic years (2002 and 2003), fire event density is twice that found during normal years (2004 and 2005) and average areal extent of fire events (burned area) in intact forests is 2.5 times larger than normal. These results suggest that a majority of the fire events in boreal Russia are of human origin and a maximum of one-third of their impact (areal extension) can be attributed to climate anomalies alone, the rest being due to the combined effect of human disturbances and climate anomalies.     

Climatic change and fire potential in South-Central British Columbia, Canada

The incidence and severity of forest fires are linked to the interaction between climate, fuel and topography. Increased warming and drying in the future is expected to have a significant impact on the risk of forest fire occurrence. An increase in fire risk is linked to the synchronous relationship between climate and fuel moisture conditions. A warmer, drier climate will lead to drier forest fuels that will in turn increase the chance of successful fire ignition and propagation. This interaction will increase the severity of fire weather, which, in turn, will increase the risk of extreme fire behaviour. A warmer climate will also extend fire season length, which will increase the likelihood of fires occurring over a greater proportion of the year. In this study of the North Okanagan area of British Columbia, Canada, the impacts of climate change of fire potential were evaluated using the Canadian Forest Fire Danger Rating System and multiple climate scenario analysis. Utilizing this approach, a 30% increase in fire season length was modelled to occur by 2070. In addition, statistically significant increases in fire severity and fire behaviour were also modelled. Fire weather severity was predicted to increase by 95% during the summer months by 2070 while fire behaviour was predicted to shift from surface fire‐intermittent crown fire regimes to a predominantly intermittent‐full crown fire regime by 2070 onwards. An increase in fire season length, fire weather severity and fire behaviour will increase the costs of fire suppression and the risk of property and resource loss while limiting human‐use within vulnerable forest landscapes. An increase in fire weather severity and fire behaviour over a greater proportion of the season will increase the risks faced by ecosystems and biodiversity to climatic change and increase the costs and difficulty of achieving sustainable forest management.