The influence of climate change on the distribution of indigenous forest in KwaZulu-Natal, South Africa

Aims (1) To define the physical correlates of indigenous forest in KwaZulu-Natal province and develop a model, based on climatic parameters, to predict the potential distribution of forest subtypes in the province. (2) To explore the impact of palaeoclimatic change on forest distribution, providing an insight into the regional-scale/historical forces shaping the pattern and composition of present-day forest communities. (3) To investigate potential future shifts in forest distribution associated with projected climate change. Location KwaZulu-Natal province, South Africa. Methods A BIOCLIM-type approach is adopted. Bioclimatic ‘profiles’ for eight different forest subtypes are defined from a series of grid overlays of current forest distribution against nineteen climatic and geographical variables, using ArcInfo GIS grid-based processing. A principal components analysis is performed on a selection of individual forests to identify those variables most significant in distinguishing different forest subtypes. Five models are developed to predict the distribution of forest subtypes from their bioclimatic profiles. Maps of the potential distribution of forest subtypes predicted by these models under current climatic conditions are produced, and model accuracy assessed. One model is applied to two palaeoclimatic scenarios, the Last Glacial Maximum (LGM) (≈18,000 BP ) and the Holocene altithermal (≈7000 BP ), and to projected future climate under a doubling in global atmospheric carbon dioxide. Results Seven variables; altitude, mean annual temperature, annual rainfall range, potential evaporation, annual temperature range, mean annual precipitation and mean winter rainfall, are most important in distinguishing different forest subtypes. Under the most accurate model, the potential present-day distribution of all forest subtypes is more extensive than is actually observed, but is supported by recent historical evidence. During the LGM, Afromontane forest occupied a much reduced and highly fragmented area in the mid-altitude region currently occupied by scarp forest. During the Holocene altithermal, forest expanded in area, with a mixing of Afromontane and Indian Ocean coastal belt forest elements along the present-day scarp forest belt. Under projected climatic conditions, forest shifts in altitude and latitude and occupies an area similar to its current potential and more extensive than its actual current distribution. Main conclusions Biogeographical history and present physical diversity play a major role in the evolution and persistence of the diversity of forest in KwaZulu-Natal. It is important to adopt a long-term and regional perspective to forest ecology, biogeography, conservation and management. The area and altitudinal and latitudinal distribution of forest subtypes show considerable sensitivity to climate change. The isolation of forest by anthropogenic landscape change has limited its radiation potential and ability to track environmental change. Long-term forest preservation requires reserves in climatically stable areas, or spanning altitudinal or latitudinal gradients allowing for forest migration, along with innovative matrix management strategies. Dune, sand, swamp, riverine and lowland forest subtypes are most at risk. Scarp forests are highlighted as former refugia and important for the future conservation of forest biodiversity.     

植被对土壤热扩散特征的影响——以长白山阔叶红松林为例

土壤温度变化及热传递是影响土壤和大气水热交换的重要过程,而植被是决定这种变化和影响的环境因子之一。通过比较林地与裸地土壤热特性的差异分析植被对土壤热扩散的影响。研究内容包括观测2007年长白山阔叶红松林区不同深度的土壤温度以及同期土壤含水量和叶面积指数。分析不同深度林地与裸地土壤温度年周期特征,根据热传导方程估算各土壤层温度的阻尼深度和热扩散率,并探讨引起林地与裸地土壤热特性差异的可能原因。结果表明,林地与裸地的土壤温度有明显的时空变化规律。随着深度的增加,土壤温度年周期的振幅逐渐减小、相位逐渐增大、平均值逐渐升高。林地土壤温度年平均值低于裸地,表层年平均温度相差约0.8℃;地表以下相同深度处,林地土壤温度年周期的振幅约低于裸地2.6—2.9℃,相位约小于裸地0.2—0.24 rad(角速度),这表明林地土壤温度极大值和极小值出现的时间比裸地滞后约11—14d。土壤温度阻尼深度和热扩散率随深度的增加而逐渐增大,而在1.6—3.2m则略有降低的趋势。林地与裸地土壤温度和热特性的时空特征和差异可能与土壤含水量和叶面积指数有关。     

气候变暖背景下秦岭陕西段植被潜在分布区格局变化

植被分布在一定程度上受控于气候因子,在气候变化背景下,利用生物气候指标研究地带性植被的潜在分布区格局变化对于区域生态系统应对气候变化具有有益的参考价值。从生态气候学角度出发,利用植被热量指标——有效温暖指数(EWI),研究1959—2020年以及未来气候模式下秦岭山地陕西段植被潜在分布格局的变化。结果表明：(1)气候变暖导致植被热量指标发生变化,近62年来,秦岭山地陕西段EWI总体呈上升趋势,并于2001年发生上升突变。(2)基于EWI对秦岭陕西段植被类型的潜在分布区划分发现,2001年以前秦岭北坡无暖温带落阔常绿混交林的分布区,2001年后秦岭北坡渭河东部出现了该植被类型的潜在分布区。(3)随着气候变暖,秦岭陕西段暖温带植被潜在分布区不断扩张,而温带、寒温带以及高寒植被分布区持续缩减,同时各植被类型分布区的平均海拔高度均呈上移趋势。从面积及海拔变化幅度来看,秦岭南坡较北坡植被对气候变化更为敏感,高海拔区较低海拔区植被对气候变化更为敏感。(4)在代表性浓度路径4.5及8.5(RCP4.5及RCP8.5)情景下,未来50年,秦岭南北坡均将可能出现亚热带常绿阔叶林潜在分布区,亚热带常绿阔叶...     

Changes in seasonal precipitation distribution but not annual amount affect litter decomposition in a secondary tropical forest

In the tropics of South China, climate change induced more rainfall events in the wet season in the last decades. Moreover, there will be more frequently spring drought in the future. However, knowledge on how litter decomposition rate would respond to these seasonal precipitation changes is still limited. In the present study, we conducted a precipitation manipulation experiment in a tropical forest. First, we applied a 60% rainfall exclusion in April and May to defer the onset of wet season and added the same amount of water in October and November to mimic a deferred wet season (DW); second, we increased as much as 25% mean annual precipitation into plots in July and August to simulate a wetter wet season (WW). Five single‐species litters, with their carbon to nitrogen ratio ranged from 27 to 49, and a mixed litter were used to explore how the precipitation change treatments would affect litter decomposition rate. The interaction between precipitation changes and litter species was not significant. The DW treatment marginally accelerated litter decomposition across six litter types. Detailed analysis showed that DW increased litter decomposition rate in the periods of January to March and October to December, when soil moisture was increased by the water addition in the dry season. In contrast, WW did not significantly affect litter decomposition rate, which was consistent with the unchanged soil moisture pattern. In conclusion, the study indicated that regardless of litter types or litter quality, the projected deferred wet season would increase litter decomposition rate, whereas the wetter wet season would not affect litter decomposition rate in the tropical forests. This study improves our knowledge of how tropical forest carbon cycling in response to precipitation change.     

表征亚热带常绿林光合作用季节变化特征的多种植被指数

利用遥感方法可以在区域尺度反演地表植被的光合生理状况和生产力变化,但亚热带常绿林冠层结构季节变化较小,传统的光谱植被指数对植被光合作用难以准确捕捉。利用2014—2015年中国科学院广东省鼎湖山森林生态试验站多角度自动光谱观测系统的光谱反射数据,分别反演传统冠层结构型植被指数(NDVI)、光合生理生化型植被指数(CCI)和叶绿素荧光型植被指数(NDFI_(685)和NDFI_(760)),并利用不同类型植被指数的组合,构建多元线性回归模型。结果表明:亚热带常绿针阔混交林三种类型植被指数均与GPP的动态变化有显著的相关性,其中,NDVI是表征GPP较优的植被指数(R~2=0.60,P0.01),其次为CCI(R~2=0.55,P0.01),而NDFI能够作为辅助指数,有效提高NDVI(R~2=0.68,P0.001)和CCI(R~2=0.67,P0.001)表征GPP的程度。多个植被指数参与构建的多元回归模型能够有效提高亚热带地区常绿林GPP季节动态变化的拟合精度,提升遥感精确评估亚热带森林生产力的能力。     

气候变化对阔叶红松林潜在地理分布区的影响

物种地理分布主要取决于它对气候、地形等环境因子的适应性。基于22个环境因子和阔叶红松林的4类主要建群树种——红松、紫椴、水曲柳和蒙古栎的地理分布数据,采用最大熵模型模拟了阔叶红松林的潜在分布区域,并分析决定阔叶红松林地理分布的主要气候和地形因子,最后利用政府间气候变化专门委员会(IPCC)发布的3种排放场景(SRES-A2、SRES-A1B、SRES-B1)下2020、2050、2080年的气候数据预测阔叶红松林的未来潜在分布区。结果表明:各树种的受试者工作特征曲线下面积(AUC值)都大于0.8,说明模型有很好的预测能力;影响阔叶红松林分布的主导环境因子是年降雨量、季节性降雨量、海拔、年平均温度、最湿季度的平均温度。在基准气候条件下,阔叶红松林的高度适宜分布区主要分布在长白山和小兴安岭地区,占研究区总面积的11.69%,低度适宜区面积、不适宜区面积分别占研究区总面积的23%和65.31%。模型预测结果显示,未来在A2、A1B和B1气候情景下,阔叶红松林高度适宜区的南界与北界都向北移动,其面积有缩减的趋势,而低度适宜区的面积有增加的趋势。     

中国东北地区阔叶红松林与兴安落叶松林的碳通量特征及其影响因子比较

北半球中高纬度的森林生态系统在全球碳循环过程中扮演着非常重要的角色。基于中国东北地区阔叶红松林与兴安落叶松林2007年和2008年2a生长季的涡度相关通量资料及气象观测资料,比较分析了两类生态系统的碳通量特征及其环境控制因子。结果表明:研究期间,阔叶红松林与兴安落叶松林都表现为碳吸收,强度分别为199gCm-2(阔叶红松林2a生长季平均值)与49gCm-2(兴安落叶松林2008年生长季);阔叶红松林碳吸收强度在生长季的大部分时段都大于兴安落叶松林。半小时尺度上,两类生态系统的呼吸作用均与10cm土壤温度呈显著的指数相关,兴安落叶松林生态系统呼吸的温度敏感性(Q10=3.44)显著大于阔叶红松林(Q10=1.90);日尺度上,阔叶红松林与兴安落叶松林碳释放/吸收的转变临界温度为10℃左右。研究期间,兴安落叶松林生态系统的水分利用效率高于阔叶红松林生态系统。     

Spectral vegetation indices as the indicator of canopy photosynthetic productivity in a deciduous broadleaf forest

Aims Understanding of the ecophysiological dynamics of forest canopy photosynthesis and its spatial and temporal scaling is crucial for revealing ecological response to climate change. Combined observations and analyses of plant ecophysiology and optical remote sensing would enable us to achieve these studies. In order to examine the utility of spectral vegetation indices (VIs) for assessing ecosystem-level photosynthesis, we investigated the relationships between canopy-scale photosynthetic productivity and canopy spectral reflectance over seasons for 5 years in a cool, temperate deciduous broadleaf forest at 'Takayama' super site in central Japan.Methods Daily photosynthetic capacity was assessed by in situ canopy leaf area index (LAI), (LAI × V cmax [single-leaf photosynthetic capacity]), and the daily maximum rate of gross primary production (GPP max) was estimated by an ecosystem carbon cycle model. We examined five VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), green–red vegetation index (GRVI), chlorophyll index (CI) and canopy chlorophyll index (CCI), which were obtained by the in situ measurements of canopy spectral reflectance.Important findings Our in situ observation of leaf and canopy characteristics, which were analyzed by an ecosystem carbon cycling model, revealed that their phenological changes are responsible for seasonal and interannual variations in canopy photosynthesis. Significant correlations were found between the five VIs and canopy photosynthetic capacity over the seasons and years; four of the VIs showed hysteresis-type relationships and only CCI showed rather linear relationship. Among the VIs examined, we applied EVI–GPP max relationship to EVI data obtained by Moderate Resolution Imaging Spectroradiometer to estimate the temporal and spatial variation in GPP max over central Japan. Our findings would improve the accuracy of satellite-based estimate of forest photosynthetic productivity in fine spatial and temporal resolutions, which are necessary for detecting any response of terrestrial ecosystem to meteorological fluctuations.     

季节增温方式对小兴安岭红松针阔混交林演替的潜在影响

应用林窗模型LINKAGES对小兴安岭红松针阔混交林在不同季节增温方式下的未来演替过程进行了模拟预测.以温度增加5℃、降水无明显变化作为未来变暖气候的模拟假设,共设计3种气候变暖方式预案,分别为冬季增温幅度大于夏季、冬季与夏季增温幅度相同以及冬季增温幅度小于夏季.模拟结果表明,当冬季增温幅度大于夏季时,小兴安岭现存林分的演替受气候变暖的影响相对最小,树种组成仍然能够保持较为稳定的针阔混交林状态;当冬季增温幅度小于夏季时,现存林分的演替受气候变暖的影响最显著,树种衰退最迅速.可见,小兴安岭针阔混交林的演替与未来的增温方式关系密切,上限温度是现存树种能否继续存活的重要决定因子.     

Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach

Aim To understand drivers of vegetation type distribution and sensitivity to climate change. Location Interior Alaska. Methods A logistic regression model was developed that predicts the potential equilibrium distribution of four major vegetation types: tundra, deciduous forest, black spruce forest and white spruce forest based on elevation, aspect, slope, drainage type, fire interval, average growing season temperature and total growing season precipitation. The model was run in three consecutive steps. The hierarchical logistic regression model was used to evaluate how scenarios of changes in temperature, precipitation and fire interval may influence the distribution of the four major vegetation types found in this region. Results At the first step, tundra was distinguished from forest, which was mostly driven by elevation, precipitation and south to north aspect. At the second step, forest was separated into deciduous and spruce forest, a distinction that was primarily driven by fire interval and elevation. At the third step, the identification of black vs. white spruce was driven mainly by fire interval and elevation. The model was verified for Interior Alaska, the region used to develop the model, where it predicted vegetation distribution among the steps with an accuracy of 60–83%. When the model was independently validated for north‐west Canada, it predicted vegetation distribution among the steps with an accuracy of 53–85%. Black spruce remains the dominant vegetation type under all scenarios, potentially expanding most under warming coupled with increasing fire interval. White spruce is clearly limited by moisture once average growing season temperatures exceeded a critical limit (+2 °C). Deciduous forests expand their range the most when any two of the following scenarios are combined: decreasing fire interval, warming and increasing precipitation. Tundra can be replaced by forest under warming but expands under precipitation increase. Main conclusion The model analyses agree with current knowledge of the responses of vegetation types to climate change and provide further insight into drivers of vegetation change.     

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO₂, and few studies have considered how and to what extent climate change and CO₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP‐DGVM coupled with CLM3 and CLM4‐CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO₂ concentration. In the temperature sensitivity tests, warming reduced the global area‐averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP‐DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP‐DGVM and in semiarid and arid regions for CLM4‐CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO₂ concentration.     

气候变化对东北主要地带性植被类型分布的影响

准确地划分地带性主要植被类型分布的适宜区域,可为区域植被恢复与重建、生物多样性保护等工作提供有益的理论参考。在检验1961—2013年东北地区气候变化突变点的基础上,基于东北地区主要植被类型热量指标,研究气候变化对该区域主要植被类型适宜分布区域的影响,并利用2000年和2013年土地类型覆盖数据(MCD12Q1),对推算的适宜分布区域进行验证,结果表明:大兴安岭气温突变点为1982年,其它地区为1988年,东北地区各生态地理区年降水量没有明显的突变点。气温突变点后适宜在东北地区生长的主要植被种类没有变化,但各植被类型的分布区域均有所改变,其中高山冻原、亚高山矮曲林、寒温带针叶林和温带针阔叶混交林适宜分布区域面积减小,暖温带落叶阔叶林和温带草原面积增大。气温突变点前后各植被类型适宜分布区的地理中心均发生了不同程度的移动,其中移动距离最大的是南部地区的亚高山矮曲林,向东北方向移动了135.44km。与主要植被类型实际分布相对比,证明气候变化对研究区植被类型分布可能已经产生了影响。     

浙江省植被覆盖时空动态及其与生态气候指标的关系

对1982-2006年间浙江省归一化植被指数（NDVI）的时空变化及其与关键生态气候指标（生物热量指数和生物干湿度指数）的相关性进行了研究.结果表明：研究期间,浙江省植被覆盖总体呈缓慢下降趋势,NDVI显著减少的地区约占全省面积的30.71%;生态气候指标与滞后一年的NDVI显著相关,其中生物热量指数与NDVI呈显著负相关,生物干湿度指数与NDVI呈显著正相关,说明研究区湿度的增加可促进植被长势,而过高的热量对植被生长则具有明显的抑制作用.     

Multiple environmental changes drive forest floor vegetation in a temperate mountain forest

Human‐induced changes of the environment and their possible impacts on temperate forest understory plant communities have been examined in many studies. However, the relative contribution of individual environmental factors to these changes in the herb layer is still unclear. In this study, we used vegetation survey data covering a time period of 21 years and collected from 143 permanent plots in the Northern Limestone Alps, Austria. Data on soil chemistry (49 plots), light condition (51 plots), soil temperature and moisture (four and six plots), disturbance (all plots), climate (one station in a clearing area), and airborne sulfur (S) and nitrogen (N) deposition (two forest stands) were available for analyses. We used these data together with plot mean Ellenberg indicator values in a path analysis to attribute their relative contributions to observed vegetation changes. Our analysis reveals a strong directional shift of the forest understory plant community. We found strong evidence for a recovery of the ground‐layer vegetation from acidification as response to decreased S deposition. We did not observe a community response to atmospheric N deposition, but we found a response to altered climatic conditions (thermophilization and drying). The path analysis revealed that changes in the light regime, which were related to small‐scale disturbances, had most influence on herb layer community shifts. Thermophilization and drying were identified as drivers of understory community changes independent of disturbance events.     

近308年来大兴安岭北部森林植被气候生产潜力及其对气候变化的响应

揭示大兴安岭北部气候变化敏感区的气候生产潜力演变及其影响机理,对于维持东北地区生态系统平衡具有重要意义。基于标准树轮年表反演气象资料与研究区13个气象站观测数据组成的1707—2014年气象资料序列,利用Miami模型和小波分析等方法,分析了大兴安岭北部气候生产潜力演变及其对气候变化的响应。结果显示:1707年以来,气温、降水、蒸散和标准气候生产潜力变化均表现极显著增加趋势,标准气候生产潜力(W)变化率为1.79 kg hm~(-2)a~(-1),20世纪气候倾向率最大为10.14kg hm~(-2)a~(-1),温度气候生产潜力(WT)与降水气候生产潜力(WR)的比值21世纪最大,水热配比状态最好;4种气候生产潜力存在不同时间尺度的周期变化,但变化一致性较好,主周期均为215—219a;大兴安岭北部W呈现一致的正变化趋势,高值、次高值、低值中心分别在根河、塔河、鄂伦春偏南地区,振幅由西北向东南逐渐递减;W与年气温、降水量、蒸散量正相关显著,年平均气温每升高1℃、年降水量和蒸散量均增加10 mm,W变化率依次为453.71、74.40、219.01 kg/hm~2,且气温是影响W的主要因子;未来"暖湿型"气候对森林植被生长有利,而"冷干型"气候对森林植被生长不利,气候生产潜力增加(减少)幅度均为10.9%—21.7%。研究结果不仅可为区域尺度内研究森林植被气候生产潜力提供基础方法,而且对进一步估算森林碳汇、即将实施的碳交易及中国北部边疆生态安全研究和生态功能规划制定等具有重要参考价值。     

Streams in an uninhabited watershed have predictably different thermal sensitivities to variable summer air temperatures

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