我国西南喀斯特森林生态系统生态化学计量学研究

喀斯特森林生态系统作为喀斯特生态系统的重要组成部分,其生态化学计量特征是喀斯特生态系统研究的热点。对比其他森林生态系统,我国西南喀斯特森林生态系统的植物具有较高的C含量和较低的N、P含量,植物生长一般会受到N、P的限制;凋落物和土壤N、P含量较高,不同植被类型土壤P含量有很大差异;随着植被正向演替的进行,土壤N含量和凋落物N、P含量有逐渐增加的趋势;喀斯特森林生态系统化学计量特征主要受到植物个体差异、气候、地形和人类活动的影响。文中系统总结了我国西南喀斯特森林生态系统的研究概况、生态化学计量特征、影响因素及研究方向,并针对我国西南喀斯特森林生态系统生态化学计量学研究亟待解决的科学问题从4个方面进行了研究展望。     

基于蓄积的森林生物量估算方法的对比分析

正森林生物量是指一个森林群落在一定时间内积累的有机质总量,是森林生态系统重要的特征数据,因此世界各国越来越重视对森林生物量的监测与研究[1-3],建立的生物量模型众多[4-6]。大尺度森林生物量监测,是以省、流域、国家乃至全球为对象,在估算方法一致的前提下,对多个时间点的森林生物     

瘦西湖风景区森林生态系统建设与规划

瘦西湖风景区森林生态系统建设与规划是城市森林生态体系研究与示范扬州试验点的重要组成部分，是实现风景区可持续发展的的重要条件。介绍了利用历史遗存植物造景、坚持乡土树种地被植物应用、加强生物多样性原则、开发水生湿地植被景观、推进生物防治管理等景区森林生态系统建设的基本原则；并就自然植被资源保护、湿地植物景观体现以及生态绿地模式建设等设想，对景区森林生态系统可持续发展的建设目标进行了初步规划和探讨。     

瘦西湖风景区森林生态系统建设

瘦西湖风景区森林生态系统建设是城市森林生态体系研究与示范扬州试验点的重要组成部分。本文利用历史遗存植物造景、坚持乡土树种地被植物应用、加强生物多样性原则、开发水生湿地植被景观、推进生物防治管理等,阐明了景区森林生态系统建设的基本原则;并就自然植被资源保护、湿地植物景观以及生态绿地模式建没等设想,对景区森林生态系统可持续发展的建设目标进行了探讨。       

加勒比松凋落物对土壤性状的影响

加勒比松(Pinus caribaea Morelet)生长快、适应性强、耐瘠薄土壤,是南亚热带低海拔丘陵地区造林绿化的主要树种之一[1].由于纯松林结构简单、生态效益差[2],在纯松林下套种阔叶树进行改造,可以建成针阔混交林,为修复脆弱的生态系统提供了一条有效途径.土壤影响着林木的生长,土壤理化性质是土壤质量的重要指标[3-4],土壤微生物和酶在分解凋落物及土壤的生化循环中起重要作用[5-6],影响植物养分的吸收[7-10],二者越来越多地被用做土壤肥力的一个指标[6,11].由于土壤的物理、化学和生物性质相互作用,土壤质量应该结合物理的、化学的和生物的因子进行评价[12].森林凋落物是林地养分的主要来源,可以改变森林土壤的理化性质,并对土壤微生物产生影响.     

加强森林抚育对提升云南景洪植物多样性的作用

指出了森林植物的多样性对于人类的生存与发展、森林生态系统的完善以及生态功能的实现都具有十分重要的作用和意义,对森林多样性的重要作用进行了阐述,对森林抚育对云南省景洪市植物多样性的影响进行了分析,探讨了云南省景洪市开展森林抚育提升植物多样性的重要举措。     

云南松光合特性日进程及与叶面微气象因子的相关性分析

云南松(Pinus yunnanensis Franch.)是常绿针叶乔木,云南的重要乡土树种.在云南的亚热带高原,从南到北,从东到西,海拔700～3200m都有大面积分布,其森林面积约占云南森林面积的70%[1],是云贵高原荒山造林的先锋树种,不仅具有较强的水土保持、水源涵养、改善环境,同时提供大量的建筑用材和林副产品,在生态经济建设中发挥了重大作用[2].有关云南松形态特征、分子遗传、良种选育、木材利用等多方面的研究取得了一些成果[3-8],对其光合生理生态特性方面研究较少.光合作用是植物一切生理活动的基础,其大小不仅与自身遗传特性有关,而且受众多环境因子的影响[9].     

深圳市宝安区森林生态质量分析

基于2008年森林资源与生态状况档案更新数据,对深圳市宝安区树种结构、龄组结构、公顷蓄积、公顷植物生物量、生态功能等级、森林自然度、森林健康状况、森林景观等级等森林生态质量指标进行分析．分析评价结果：森林生态功能一般,林分质量不高,树种结构有待优化改善,森林健康状况良好,森林景观度不高,森林生态系统主要为受人为活动严重制约和影响的人工生态系统．     

森林环境——土壤、生物、地形的生态因子

一、森林与土壤的生态关系土壤是生态系统中物质与能量交换的重要场所,又是生态系统中生物部分和无机环境部分相互作用的产物。森林植物和土壤之间有着频繁的物质交换,彼此强烈影响。因此,土壤是一个重要的生态因子。 1.土壤的物理性状与森林的关系土壤物理性状是指土壤质地、结构、容量、孔隙度等因素。本文着重介绍土壤质地     

海南岛尖峰岭卵叶樟种群结构与分布格局动态研究

卵叶樟(Cinnamomum rigidissimum H. T. Chang)是樟科(Lauraceae)樟属(Cinnamomum Trew)植物,是第一批被列入<国家重点保护植物名录>的二级重点保护物种[1],具有重要的经济和科研价值.根据以往调查,卵叶樟在海南尖峰岭的数量较少,一般生长在海拔6001 000 m的热带山地雨林中,这与森林商业性采伐和盗伐等人为干扰活动导致森林环境变迁有关[2-3].种群是群落构成的基本单位,种群结构不仅对群落结构有直接影响,而且能客观地体现群落的发展趋势[4].研究种群空间格局及其动态可为研究森林群落演替趋势、森林生态系统可持续经营提供基础理论,其数量分析指数还可为生物多样性保护、森林可持续经营评价等提供可靠依据[5].本文通过探讨卵叶樟种群结构和分布格局及其动态的数量特征,为探讨其濒危机制及合理保护提供理论依据.     

Comparison and Dynamic Calibration between LAI Values of Larix principis-rupprechtii Plantation Determined by Canopy Scanner and Litter-fall Collection

In order to test the accuracy of the usually-used fixed calibration factor of the canopy scanner of LAI-2000 for measuring the leaf area index(LAI),a Larix principis-rupprechtii plantation was chosen in the small watershed of Xiangshuihe located at the Liupan Mountains of Ningxia Hui Autonomous Region of NW China,the LAI was measured in October 2010,a period from full canopy to the total fall of needles,by using both the LAI- 2000 and litterfall collection method.Then,a comparison was made between the LAI values determined by the litter-fall collection and that calculated based on the figures read from LAI-2000 and the fixed calibration factor(1.49).It showed that the average of LAI measurements of the 2 methods was very close,with a difference of only 5%.However,the calculated LAI from LAI-2000 was obviously higher than the true values determined by litter-fall collection when the canopy was full of needles;and obviously lower than the true value when the canopy was sparse after needle falling.The reason may be that LAI-2000 takes the projection of twigs as needles.So,a dynamic calibration factor is needed,especially in the seasons when the needle amount and the percentage of twigs projection in crown projection change quickly.Therefore,a statistic relation in a quadratic polynomial form between the 2 series of LAI data was well fitted. This relation can be used for a more accurate estimation of LAI based on the data read from the easilyused canopy scanners like LAI-2000.     

基于土壤水分承载力的林分密度计算与调控——以六盘山华北落叶松人工林为例

立地水分条件决定的植被承载力是干旱缺水地区森林合理经营的重要依据。考虑到干旱缺水地区的森林蒸散耗水在水分输出中占据绝对主导地位,其大小直接与叶面积指数(LAI)相关,将林冠LAI在生长季一段时间内的最大值(LAImax)作为植被承载力(LAIc)的量化指标,利用冠层分析仪(LAI-2000),在六盘山香水河小流域和叠叠沟小流域的44个华北落叶松人工林样地,实测了冠层LAI的季节动态变化,研究了生长季内LAImax与林分断面积、郁闭度、平均树高、密度等常用林分结构指标的关系。结果表明:LAImax与林分不同结构指标均呈幂函数关系,其决定系数(R2)依次为0.84、0.82、0.56、0.47,说明能同时反映林分密度和树体大小的林分断面积与林冠LAI相关最紧密。将LAImax与林分断面积的幂函数关系嵌入了林分平均胸径与林分密度和林龄关系的模型,用以描述LAImax与林龄和密度的关系,并利用样地实测数据拟合了模型参数。拟合建立的模型对所有样地的LAImax的计算值与实测值的相对误差平均为8.6%(0%20.4%),能较好地描述LAI与林龄和密度的关系。利用此模型,进一步导出了能依据给定的LAIc,简捷计算出不同林龄时的可承载林分密度的模型,从而为基于立地水分植被承载力的林分密度管理和森林多功能经营等提供技术支持。     

Response of LAI-2000 estimates to changes in plant surface area index in a Scots pine stand

We assessed the accuracy with which the LAI-2000 plant canopy analyzer measured changes in leaf area index (LAI) and plant area index (PAI) in a 25-year-old Scots pine (Pinus sylvestris L.) stand. Stand density was 2100 stems ha(-1) and mean tree height was 8.7 m. Needle and branch areas of the stand were reduced progressively to zero by the stepwise removal of branches on all trees growing in a circular plot with a radius of 25 m. An LAI-2000 estimate was taken after each step reduction. The needle and branch surface areas removed at each step were estimated from direct measurements and were compared with the changes in the LAI-2000 estimates. Initially (before removal of branches), directly measured PAI was 5.2 (needles = 86%, branches = 8% and stems = 6%). The LAI-2000 estimate of total surface area was 66% of direct PAI and 77% of direct LAI. There was a nonlinear relationship between the LAI-2000 estimate and directly measured PAI, such that their ratio (equivalent to the clumping factor) increased from 0.66 to 1.05 with decreasing PAI. At the last measurement, when only stems were left, the LAI-2000 estimate agreed well with the direct measurement of PAI. The LAI-2000 underestimated the direct measurement of LAI at the first three steps when LAI was > 2 and the proportion of woody area was small (< 20%). However, because the LAI-2000 estimate included stem and branch areas, it overestimated the direct measurement of LAI at the last three measurements when the proportion of woody area was large (> 20%).     

Effects of leaf aggregation in a broad-leaf canopy on estimates of leaf area index by the gap-fraction method

We compared leaf area index (LAI) estimates of a broad-leaf tropical hardwood, Metrosideros polymorpha Gaud (‘Ōhi’a), using a optical method (LI-COR LAI-2000) and direct determination (harvest and allometry). There was a strong correlation between LAI estimates by the two methods, but direct estimates were higher than the optical estimates by a factor of 2.44. The ratio of harvest leaf area to projected leaf area within twigs was similar (2.42) to that of whole plots, suggesting that aggregation of leaves at this scale of branching may account for most of the underestimate by the optical method. The within-branch ratio of actual to projected leaf area did not differ among three sites on three islands of varying land surface age but similar climate, suggesting that a correction factor determined by harvest could be used to adjust optical estimates of LAI in other M. polymorpha forests.     

Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods

Leaf area index (LAI) was estimated at 15 sites in the Swiss Long-Term Forest Ecosystem Research Programme (LWF) in 2004–2005 using two indirect techniques: the LAI-2000 plant canopy analyzer (Licor Inc.) and digital hemispherical photography, applying several exposure settings. Hemispherical photographs of the canopy were analysed using Hemisfer, a software package that offers several new features, which were tested here: (1) automatic thresholding taking the gamma value of the picture into account; (2) implementation of several equations to solve the gap-fraction inversion model from which LAI estimates are derived; (3) correction for ground slope effects, and (4) correction for clumped canopies. In seven broadleaved stands in our sample set, LAI was also estimated semi-directly from litterfall. The various equations used to solve the gap-fraction inversion model generated significantly different estimates for the LAI-2000 measurements. In contrast, the same equations applied in Hemisfer did not produce significantly different estimates. The best relationship between the LAI-2000 and the Hemisfer estimates was obtained when the hemispherical photographs were overexposed by one to two stops compared with the exposure setting derived from the reading of a spotmeter in a canopy gap. There was no clear general relationship between the litterfall and the LAI-2000 or the hemispherical photographs estimates. This was probably due to the heterogeneity of the canopy, or to biased litterfall collection at sites on steep slopes or sites subject to strong winds. This study introduces new arguments into the comparison of the advantages and drawbacks of the LAI-2000 and hemispherical photography in terms of applicability and accuracy.     

Calibration and assessment of seasonal changes in leaf area index of a tropical dry forest in different stages of succession

A simple measure of the amount of foliage present in a forest is leaf area index (LAI; the amount of foliage per unit ground surface area), which can be determined by optical estimation (gap fraction method) with an instrument such as the Li-Cor LAI-2000 Plant Canopy Analyzer. However, optical instruments such as the LAI-2000 cannot directly differentiate between foliage and woody components of the canopy. Studies investigating LAI and its calibration (extracting foliar LAI from optical estimates) in tropical forests are rare. We calibrated optical estimates of LAI from the LAI-2000 with leaf litter data for a tropical dry forest. We also developed a robust method for determining LAI from leaf litter data in a tropical dry forest environment. We found that, depending on the successional stage of the canopy and the season, the LAI-2000 may underestimate LAI by 17% to over 40%. In the dry season, the instrument overestimated LAI by the contribution of the woody area index. Examination of the seasonal variation in LAI for three successional stages in a tropical dry forest indicated differences in timing of leaf fall according to successional stage and functional group (i.e., lianas and trees). We conclude that when calculating LAI from optical estimates, it is necessary to account for the differences between values obtained from optical and semi-direct techniques. In addition, to calculate LAI from litter collected in traps, specific leaf area must be calculated for each species rather than from a mean value for multiple species.     

Optical and litter collection methods for measuring leaf area index in an old-growth temperate forest in northeastern China

Hemispherical photographs combined with litter collection were applied to determine seasonal dynamics of leaf area index (LAI) between the period of maximum leaf area and the leafless period from an old-growth temperate forest in the Xiaoxing’an Mountains, northeastern China. Our objective is to explore the change in the relationship between “true” LAI and effective LAI (calculated only from hemispherical photography) and to find the best LAI estimation models. Effective LAI in November is corrected for contribution of woody material and clumping at shoot and beyond shoot levels, to give minimum “true” LAI. The “true” LAI in each period is estimated as a sum of the minimum “true” LAI and litter collection LAI in each period. Power function regression calibration models were then carried out between “true” LAI and effective LAI in each period and the entire litter-fall period. Then, significance tests were applied to detect the differences among different models. The results showed that the average “true” LAI ranged from 2.74 ± 0.54 on November 1 to 6.64 ± 1.34 on July 1. For the entire season, average effective LAI was 53.16 % lower than the average “true” LAI. After significance tests, calibration models were classified into two types: (1) maximum LAI period and the period of maximum leaf fall; (2) the period during which leaves began falling and all deciduous leaves had fallen. Based on our experience, we believe that the classified models can produce reliable and accurate LA1 values for the needle and broad-leaved mixed forest stands under the non-destructive condition.     

Estimation of LAI in the forested watershed using ASTER data based on Price’s model in summer and winter

Leaf area index (LAI) is an important parameter to identify the water balance in forested watershed as a biological factor influencing directly on the evapotranspiration in the forest area. The purpose of this study was to estimate the LAI in a small forested watershed in summer and winter by applying the Terra/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to the LAI estimation method. In this study, the estimation was based on the absorption and scattering processes of the solar radiation in the vegetation canopy and the spectral reflectance characteristics of soil vegetation. First, we estimated LAI based on Price’s model by application of ASTER data on the forested watershed located in the Tenzan Mountains of Saga, Japan. To validate the results of LAI estimation, secondly, we compared them to the measured LAI obtained by a plant canopy analyzer (LAI-2000) on the observation area inside the target region. This study showed that the LAI estimation method was a feasible and accurate method as indicated by the high relationship (r = 0.97) between LAI derived from ASTER data and LAI measured by LAI-2000. This paper is the first report on LAI estimation using Terra/ASTER data based on Price’s model and field investigation. This LAI estimation method is a reliable and applicable method.     

Importance of woody materials for seasonal variation in leaf area index from optical methods in a deciduous needleleaf forest

Woody materials (woody area index, WAI) is a key error source in estimating leaf area index (LAI) by optical methods, but how to correct the error caused by WAI during different seasons has not reached consensus. In this study, effective plant area index (PAI_e) was first estimated using two indirect optical methods (digital hemispherical photography, DHP, and LAI-2000) in a deciduous needleleaf forest, and then four different schemes for correcting the contribution of WAI to PAI_e were tested here. We also directly estimated the seasonality of LAI by a litter collection method and an allometric method. Directly subtracting WAI from PAI resulted in a greater degree of uncertainty in correcting seasonal changes of PAI_e from both DHP and LAI-2000. Therefore, we introduced a new correction factor, the stem-to-total area ratio, which was reasonable and useful for quantifying seasonal changes in the contribution of WAI to PAI_e. We finally recommend a practical scheme for correcting PAI_e from both DHP and LAI-2000, with accuracies as high as 88% and 87% during most growing seasons, respectively. Additionally, LAI values estimated from allometry were concordant with those estimated from litter collection, indicating that the allometry method is useful for tracking seasonal changes in LAI.     

Validation of an efficient visual method for estimating leaf area index in clonal Eucalyptus plantations

Leaf area index (LAI) is a key ecophysiological parameter in forest stands because it characterises the interface between atmospheric processes and plant physiology. Several indirect methods for estimating LAI have been developed. However, these methods have limitations that can affect the estimates. This study aimed to evaluate the accuracy and applicability of a visual method for estimating LAI in clonal Eucalyptus grandis × E. urophylla plantations and to compare it with hemispherical photography, ceptometer and LAI-2000^® estimates. Destructive sampling for direct determination of the actual LAI was performed in 22 plots at two geographical locations in Brazil. Actual LAI values were then used to develop a field guide with photographic images representing an LAI range of 1.0–5.0 m² m^?2 (leaf area/ground area). The visual LAI estimation guide was evaluated with 17 observers in the field. The average difference between actual LAI and visual LAI estimation was 12% and the absolute difference between the two methods was less than or equal to 0.5 m² m^?2 in 77% of plots. Pearson’s correlation coefficients were high between actual LAI and hemispherical photographs (0.8), visual estimation (0.93) and LAI-2000^® (0.99) and low for the ceptometer (0.18). However, absolute values differed among methods, with the average difference between the actual and estimated LAI of [12]% for visual estimation, 28% for the LAI-2000^®, 37% for the ceptometer and ?43% for hemispherical photographs. The LAI-2000^® and ceptometer overestimated LAI in all plots, whereas hemispherical photographs underestimated the values in all measurements, showing that these methods need calibration to be used. No differences were observed between actual LAI and visual estimates across stand ages of 2–8 years and LAI of 1.5–5.3 m² m^?2 (P > 0.05). The results show that visual estimation of LAI in Eucalyptus stands is a practical method that is unaffected by atmospheric characteristics and can be used on an operational scale.