Vegetation structure and greenness in Central Africa from Modis multi-temporal data

African forests within the Congo Basin are generally mapped at a regional scale as broad-leaved evergreen forests, with the main distinction being between terra-firme and swamp forest types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organization and their relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified 22 vegetation types (six savannas, two swamp forests, 14 forest types) improving existing vegetation maps. Among forest types, we showed strong variations in stand structure and deciduousness, identifying (i) two blocks of dense evergreen forests located in the western part of the study area and in the central part on sandy soils; (ii) semi-deciduous forests are located in the Sangha River interval which has experienced past fragmentation and human activities. For all vegetation types enhanced vegetation index profiles were highly seasonal and strongly correlated to rainfall and to a lesser extent, to light regimes. These results are of importance to predict spatial variations of carbon stocks and fluxes, because evergreen/deciduous forests (i) have contrasted annual dynamics of photosynthetic activity and foliar water content and (ii) differ in community dynamics and ecosystem processes.     

Modelling riparian forest distribution and composition to entire river networks

Aim: Developing a methodology to map the distribution of riparian forests to entire river networks and determining the main environmental factors controlling their spatial patterns. Location: Cantabrian region, northern Spain. Methods: We mapped the riparian forests at a physiognomic and phytosociological level by delimiting riparian zones and generating vegetation distribution models based on remote sensing data (Landsat 8 OLI and LiDAR PNOA). We built virtual watersheds to define a spatial framework where the catchment environmental information can be specified for each river reach, in combination with the vegetation map. In order to determine the drivers that play a significant role in the observed spatial patterns in riparian forests, based on our data sets we modelled interactions between environmental information and riparian vegetation by using the Random Forest algorithm. Results: The modelling results obtained reliably reproduced the variation of riparian forest structure and composition across Cantabrian watersheds. The produced maps were highly accurate, with a more than 70% overall accuracy for forest occurrence. A clear differentiation between Eurosiberian (habitats 91E0 and 9160) and Mediterranean (92E0) riparian forests was shown on both sides of the mountain range. Topography and land use were the main drivers defining the distribution of riparian forest as a physiognomic unit. In turn, altitude, climate and percentage of pasture were the most relevant factors determining their composition (phytosociological approach). Conclusions: Our study confirms that anthropic control ultimately defines the distribution of vegetation in the riparian area at a regional to local scale. Human disturbances constrain the extension of forest patches across their potential distribution defined by topoclimatic boundaries, which establish a clear limit between Mediterranean and Eurosiberian biogeographical regions.     

Arthropod assemblages deep in natural forests show different responses to surrounding land use

Many contemporary landscapes have vast areas of production land-uses within landscape mosaics, which may impact species dispersal and occurrence. Here, we determined the extent to which commercial exotic plantation forests affect arthropod diversity associated with natural Afrotemperate forests in the southern Cape Afrotemperate landscape mosaic, South Africa. Natural forests and fynbos vegetation naturally coexist here, with the addition of exotic plantation forests to form a heterogeneous landscape. Epigaeic arthropods were collected by means of pitfall trapping at stations along transects from inside natural Afrotemperate forest, across the edge and into the surrounding land use, which included natural fynbos vegetation, mature forestry plantation blocks (Pinus radiata) and areas where plantations have been clear-felled. Stations were set at 5, 10, 20, 30 and 50 m to both sides of the forest edge with the addition of 100 m stations situated in the natural forest. Arthropod assemblages were distinct in all land-use types. Natural edge effect between forest and fynbos, as measured by arthropod compositional changes, was 20 m into natural forests, yet when bordered by plantations this edge increased up to 30 m into the forest. Once plantations were clear-felled, edge effects increased up to 50 m into natural forests. Responses in terms of assemblage composition and species richness were however taxon specific. Results show that (1) pine plantations are not alternative habitat for native Afrotemperate forest arthropods, (2) there were stark changes in arthropod assemblage composition at edges between these land-use types and (3) that the effects of timber plantation practices (re: clear-felling) also penetrate deep into surrounding natural forests and need to be considered in regional landscape planning. The need for an effective rehabilitation strategy of clear-felled areas is identified as key priority for bordering natural forests. Ongoing monitoring in both the disturbed area and the adjoining natural forest should be undertaken to ensure sufficient recovery.     

Vegetation classification of East China with multi-temporal NOAA-AVHRR data

East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests, a unique vegetation type mainly distributed in East Asia with the largest distribution in China. It is important to be able to monitor and estimate forest biomass and production, regional carbon storage, and global climate change impacts on these important vegetation types. In this paper, we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region. Nineteen maximum normalized difference vegetation index (NDVI) composite images (acquisition time span of 7 months from February to August), which were derived from 10 days National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) channel 1 and channel 2 observations, an unsupervised classification method, and the ISODATA algorithm were employed to identify the vegetation types. To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water, the images were processed using principal component analysis (PCA). The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system: evergreen broad-leaved forest, coniferous forest, bamboo forest, shrub-grass, aquatic vegetation, and agricultural vegetation. The spatial distribution and areal extent for the coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were calculated and compared with the Vegetation Atlas of China at a 1:1,000,000 scale. The spatial accuracy and the area accuracy for coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were 79.2%, 91.3%, 68.2% and 95.9% and 92.1%, 95.9%, 63.8% and 90.5%, respectively. The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%, respectively; the spatial accuracy of aquatic vegetation was 69.6%, but there was a significant difference in its area accuracy because image acquisition did not cover the full year. Our study demonstrated the feasibility of using NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China. The spatial location of the six identified vegetation types agreed with the actual geographical distribution of the vegetation types in East China. __________ Translated from Acta Phytoecologica Sinica, 2005, 29(3): 436–443 [译自: 植物生态学报, 2005, 29(3): 436–443]     

广西1:2500000植被图的编制及其说明

本图以现实植被为表现对象,在编制过程中也应用了潜在植被的概念来处理地带性植被类型的残存片断。图例的划分是根据植物群落学的原则,共分三级,个别到四级。第一级根据群落的外貌,第二级是优势成分的生活型,第三级是优势种或标志种(此级相当于群系或群系的结合),第四级是群落中灌木层的优势种(此级相当于群丛组)。后两级为制图单位。在图斑的概括过程中,采取了三个措施：(1)突出实占面积较大的植被类型,(2)适当夸大地带性植被的图斑,(3)利用符号标志某些面积极小的植被类型。除正式图例44个外,另有附加图例7个,全图概略地反映广西植被地理分布的规律。     

Spatial distribution of young forests and carbon fluxes within recent disturbances in Russia

Forest stand age plays a major role in regulating carbon fluxes in boreal and temperate ecosystems. Young boreal forests represent a relatively small but persistent source of carbon to the atmosphere over 30 years after disturbance, while temperate forests switch from a substantial source over the first 10 years to a notable sink until they reach maturity. Russian forests are the largest contiguous forest belt in the world that accounts for 17% of the global forest cover; however, despite its critical role in controlling global carbon cycle, little is known about spatial patterns of young forest distribution across Russia as a whole, particularly before the year 2000. Here, we present a map of young (0–27 years of age) forests, where 12‐ to 27‐year‐old forests were modeled from the single‐date 500 m satellite record and augmented with the 0‐ to 11‐year‐old forest map aggregated from the 30 m resolution contemporary record between 2001 and 2012. The map captures the distribution of forests with the overall accuracy exceeding 85% within three largest bioclimatic vegetation zones (northern, middle, and southern taiga), although mapping accuracy for disturbed classes was generally low (the highest of 31% for user's and producer's accuracy for the 12–27 age class and the maximum of 74% for user's and 32% for producer's accuracy for the 0–11 age class). The results show that 75.5 ± 17.6 Mha (roughly 9%) of Russian forests were younger than 30 years of age at the end of 2012. The majority of these 47 ± 4.7 Mha (62%) were distributed across the middle taiga bioclimatic zone. Based on the published estimates of net ecosystem production (NEP) and the produced map of young forests, this study estimates that young Russian forests represent a total sink of carbon at the rate of 1.26 Tg C yr^?1.     

Ground vegetation in the Mongolian taiga forest‐steppe ecotone does not offer evidence for the human origin of grasslands

Question: Is the vegetation of meadow and mountain steppes distinct from the ground vegetation of light taiga forests in the transitional zone between these biomes? Location: Western Khentey Mountains, northern Mongolia. Methods: Vegetation was recorded from 100‐m² plots from all dominant types of light taiga forest and dry grassland. Distinctness of ground vegetation was studied with Detrended Correspondence Analysis (DCA). Results: Ground vegetation in the light taiga was significantly different from the herbal vegetation of meadow and mountain steppes. Clear separation was only absent for the Car ex amgunensis meadow steppes that occur in a narrow strip along the forest edge and are partly shaded by trees. Forest and steppe communities followed a moisture gradient according to the DCA ordination with light taiga forests at the moistest sites and steppe communities at the driest sites. Ulmus pumila open woodlands diverged from this pattern, because of their close spatial and phytosociological relationship to mountain steppes. Conclusions: The present results do not support the assumption that grasslands in Mongolia's transitional zone between forest and steppe would generally resemble the ground vegetation of light taiga forests. This contradicts a published hypothesis stating that the vegetation of meadow and mountain steppes would not clearly differ from ground vegetation of light taiga forests in the forest‐steppe transitional zone of Mongolia.     

Aquatic and terrestrial vegetation of the Prespa area

We studied the vegetation of the aquatic ecosystems ofLake Mikri Prespa. The lacustrine vegetationcomprises three distinct forms: floating plants,benthic hydrophytes and helophytes, which aredescribed and classified from the phytosociologicalpoint of view, as follows: (a) the vegetation of thefloating plants belong to the Lemnetea class and isrepresented by two plant communities; (b) thevegetation of the benthic hydrophytes, belongs to thePotametea class consisting of two differentcategories, namely the submersed formations and theemergent formations of the hydrophytes. Various plantcommunities were recognised in this type of vegetationand three among them are considered as the mostrepresentative; (c) the vegetation of helophytes, theprevailing life form in this wetland, belongs to thePhragmitetea class and is represented mainly by sevenwell organised plant communities. The respectivevegetation of two of the five more important wetlandsites is described.The terrestrial vegetation is composed of forestand meadow vegetation. The forest vegetation of theNational Park belongs to the class Querco-Fagetea andshows the following zonation: (a) in the vicinity ofthe lake, at the elevation of 860–1000 m, twoassociations have been found: the mixed deciduous andevergreen forests of Ostryo-Carpinion orientalis andthe evergreen forests of Ostryo-Carpinion adriaticum;(b) the deciduous oak forests surround the previouszone at the altitude of 900–1300 m with two principalassociations, namely the Quercetum frainetto and theQuercetum petraeae; (c) in the upper forest layerbetween 1200–1800 m asl, dominate beech forests of theassociation Fagion moesiacum and the less extensiveoccurrence of the mixed beech-fir stands (Ass.Abieti-Fagetum moesiacum).The zone above the tree limit is distinguished by itssubalpine character semi-shrub vegetation extendinghigher than the forest (1800–2000 m), whereas alpine meadowscover the vegetation at higheraltitudes. On the plains and in the forest clearingsexist herbaceous meadow formations of variablestructure, in parallel with the vegetation of specifichabitats, such as nitrophilous and ammophilousplants.     

河北小五台山主要植被类型的分布与地形的关系：基于遥感信息的分析

小五台山是河北省最高峰,具有较完整的暖温带植被垂直带谱。本文通过野外群落植被调查,结合由TM遥感影像解译1：50000地形图制作的DEM数据而得到的植被图,分析了小五台山主要植被群落的分布状况及其与地形的关系。结果表明,小五台山从低海拔到高海拔,依次出现灌丛、阔叶林、针阔混交林、暗针叶林、矮林、灌丛、草甸等植被类型。森林景观的面积最大,占总面积的60．7％;平均斑块面积最大的是阔叶林和亚高山草甸,斑块破碎化最严重的是水体和针阔混交林。不同的植被类型在不同的地形条件下分布特点不同,林地在北坡所占面积比例(占总面积的75％)远大于南坡(46%),说明水分条件是小五台山森林分布的限制因子之一;灌丛和草甸与林地相反。随海拔高度的变化,不同植被类型的分布面积比例发生变化,出现替代现象,形成植被垂直带谱。由于坡度的影响,增加了带谱内植被组成的复杂性。     

Mapping land cover and forest density in Zagros forests of Khuzestan province in Iran: A study based on Sentinel-2, Google Earth and field data

Zagros forests in western Iran have widely been destroyed because of various reasons. This study was performed to provide the land cover and forest density maps in Zagros forests of Khuzestan province using Sentinel-2, Google Earth and field data. The forest boundary in Khuzestan province was digitized in Google Earth. Sentinel-2 satellite images were provided for the study area. One 1:25000 index sheet of Iranian Mapping Organization (IMO) was selected as pilot area in the province. Sentinel-2 image of the pilot area was classified using different supervised classification algorithms to select the best algorithm for land cover mapping in Khuzestan province. In addition, to evaluate the accuracy of Google Earth data, field sampling was performed using random plots in different land covers. Field data of forest plots were applied to investigate tree canopy cover percent (forest density), as well. Classification of Sentinel-2 image in Zagros area of Khuzestan province was done using the best algorithm and the land cover was obtained. The forest density map was also obtained using a linear regression model between tree canopy cover percent (obtained from field plots) and normalized difference vegetation index (NDVI) (obtained from NDVI map). Finally, the accuracy of land cover map was assessed by some square plots on Google Earth. Results demonstrated that support vector machine (SVM) algorithm had the highest accuracy for land cover mapping. Results also showed that Google Earth images had a good accuracy in the Zagros forests of Khuzestan province. Results demonstrated that NDVI has been a good predicator to estimate tree canopy cover in the study area. Based on results, an area of 443,091.22 ha is covered by Zagros forests in Khuzestan province. Results of accuracy assessment of the land cover map showed the good accuracy of this map in Khuzestan province (overall accuracy: 91% and kappa index: 0.83). For optimum management of Zagros forests, it is suggested that the land cover and forest density mapping will be performed using SVM algorithm, NDVI, and Sentinel-2 satellite images in Zagros forests of Khuzestan province in the certain periods.     

基于NOAA-AVHRR数据的中国东部地区植被遥感分类研究

该文采用 19幅 (时间跨 8个月 ) 时间序列的NOAA_AVHRR的归一化植被指数 (NDVI) 最大值合成影像遥感数据, 经过主分量分析 (Principlecomponentanalysis, PCA) 处理后, 用非监督分类方法的ISODATA算法, 对中国东部地区的 (五省一市 ) 植被进行分类, 结果可以分出 2 8种土地覆盖类型, 除了两种类型为水体和城市或裸地外, 其余 2 6种类型均为植被类型, 根据中国植被分类系统, 这 2 6类可以归并为 6大植被类型 :1) 常绿阔叶林 ;2 ) 针叶林 ;3) 竹林 ;4 ) 灌草丛 ;5 ) 水生植被 ;6 ) 农业植被。用 1∶10 0 0 0 0 0数字化《中国植被图集》的植被类型检验遥感分类结果表明, 针叶林、灌草丛、常绿阔叶林和农业植被的分类具有较高的位置精度和面积精度, 位置精度分别为 79.2 %、91.3%、6 8.2 %和 95.9%, 面积精度分别达到 92.1%、95.9%、6 3.8%和 90.5 %。这 6大植被类型在地理空间上的分布规律与中国东部常绿阔叶林区植被的地带性分布基本一致。     

四川岷山火溪河地区人为干扰后的植被组成及分布

以平武县地形图、植被图、野外植被调查结果为数据源制作研究区植被图和数字高程模型(Digital Elevation Model,DEM),在Arcview GIS平台下通过植被分类和图层叠加分析法,研究了人为干扰后植被的组成及植被类型在主要地形梯度上的分布特征。结果表明:(1)受人为干扰特别是森林采伐活动影响,研究区针阔混交林消失,针叶林面积缩小,阔叶林和灌丛面积增加。(2)植被类型在海拔梯度上分布规律性明显;除农田外,其它植被类型在坡度上的面积比例与研究区面积在各坡度段所占比例很相似;针叶林、阔叶林、农田、灌丛对坡向有明显选择性。(3)人为干扰活动改变了研究区植被类型及其面积比重,并使植被在海拔段上的分布带有明显人类干扰的痕迹。     

A global overview of the conservation status of tropical dry forests

Aim To analyse the conservation status of tropical dry forests at the global scale, by combining a newly developed global distribution map with spatial data describing different threats, and to identify the relative exposure of different forest areas to such threats. Location Global assessment. Methods We present a new global distribution map of tropical dry forest derived from the recently developed MODIS Vegetation Continuous Fields (VCF) product, which depicts percentage tree cover at a resolution of 500 m, combined with previously defined maps of biomes. This distribution map was overlaid with spatial data to estimate the exposure of tropical dry forests to a number of different threats: climate change, habitat fragmentation, fire, human population density and conversion to cropland. The extent of tropical dry forest currently protected was estimated by overlaying the forest map with a global data set of the distribution of protected areas. Results It is estimated that 1,048,700 km² of tropical dry forest remains, distributed throughout the three tropical regions. More than half of the forest area (54.2%) is located within South America, the remaining area being almost equally divided between North and Central America, Africa and Eurasia, with a relatively small proportion (3.8%) occurring within Australasia and Southeast Asia. Overall, c. 97% of the remaining area of tropical dry forest is at risk from one or more of the threats considered, with highest percentages recorded for Eurasia. The relative exposure to different threats differed between regions: while climate change is relatively significant in the Americas, habitat fragmentation and fire affect a higher proportion of African forests, whereas agricultural conversion and human population density are most influential in Eurasia. Evidence suggests that c. 300,000 km² of tropical dry forest now coincide with some form of protected area, with 71.8% of this total being located within South America. Main conclusions Virtually all of the tropical dry forests that remain are currently exposed to a variety of different threats, largely resulting from human activity. Taking their high biodiversity value into consideration, this indicates that tropical dry forests should be accorded high conservation priority. The results presented here could be used to identify which forest areas should be accorded highest priority for conservation action. In particular, the expansion of the global protected area network, particularly in Mesoamerica, should be given urgent consideration.     

Vegetation classification,mapping, and monitoring at Voyageurs National Park,Minnesota: An application of the U.S. National Vegetation Classification

Question: How can the U.S. National Vegetation Classification (USNVC) serve as an effective tool for classifying and mapping vegetation, and inform assessments and monitoring? Location: Voyageurs National Park, northern Minnesota, U.S.A and environs. The park contains 54 243 ha of terrestrial habitat in the sub-boreal region of North America. Methods: We classified and mapped the natural vegetation using the USNVC, with ‘alliance’and ‘association’as base units. We compiled 259 classification plots and 1251 accuracy assessment test plots. Both plot and type ordinations were used to analyse vegetation and environmental patterns. Color infrared aerial photography (1:15840 scale) was used for mapping. Polygons were manually drawn, then transferred into digital form. Classification and mapping products are stored in publicly available databases. Past fire and logging events were used to assess distribution of forest types. Results and Discussion: Ordination and cluster analyses confirmed 49 associations and 42 alliances, with three associations ranked as globally vulnerable to extirpation. Ordination provided a useful summary of vegetation and ecological gradients. Overall map accuracy was 82.4%. Pinus banksiana - Picea mariana forests were less frequent in areas unburned since the 1930s. Conclusion: The USNVC provides a consistent ecological tool for summarizing and mapping vegetation. The products provide a baseline for assessing forests and wetlands, including fire management. The standardized classification and map units provide local to continental perspectives on park resources through linkages to state, provincial, and national classifications in the U.S. and Canada, and to NatureServe's Ecological Systems classification.     

Vegetation classification of East China with multi-temporal NOAA-AVHRR data

East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests,a unique vegetation type mainly distributed in East Asia with the largest distnbution in China.It is important to be able to monitor and estimate forest biomass and production,regional carbon storage,and global climate change impacts on these important vegetation types.In this paper,we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region.Nineteen maximum normalized difference vegetation index(NDVI)composite images(acquisition time span of 7 months from February to August),which were derived from 10 days National Oceanographic and Atmospheric Administration(NOAA)Advanced Very High Resolution Radiometer(AVHRR)channel 1 and channel 2 observations,an unsupervised classification method,and the ISODATA algorithm were employed to identify the vegetation types.To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water,the images were processed using principal component analysis(PCA).The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system:evergreen broad-leaved forest,coniferous forest,bamboo forest,shrub-grass,aquatic vegetation,and agricultural vegetation.The spatial distribution and areal extent for the coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were calculated and comscale.The spatial accuracy and the area accuracy for coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were 79.2%,91.3%,68.2% and 95.9% and 92.1%,95.9%,63.8% and 90.5%,respectively.The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%,respectively;the spatial accuracy of aquatic vegetation was 69.6%,but there was a significant difference in its area accuracy because image acquisition did not cover the full year.Our study demonstrated the fea sibility of using NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China.The spatial location of the six identified vegetation types agreed with the actual geo graphical distribution of the vegetation types in East China.     

Using climatically based random forests to downscale coarse‐grained potential natural vegetation maps in tropical Mexico

Questions: Can the accuracy of coarse resolution potential vegetation maps be improved through downscaling to finer resolution climatic grids? Can output from random forests produce new insight into the climatic characteristics that are associated with the structural characteristics of the vegetation? Location: Southern Mexico. Methods: A potential vegetation map (National Atlas of Mexico) at a 1:4 000 000 scale, was downscaled to a 1 km² grid resolution using climatically based random forests models. The resulting map was then evaluated against 256 inventory plots sampled at the transition between different vegetation types in Southern Mexico. Results: Downscaling increased accuracy up to 0.40, as measured by the Kappa Index of Agreement. Multivariate analysis of the results allowed the association between Rzedowski's classification and climatic variation to be explored. This confirmed that many of the structural aspects of the vegetation that are used by the Rzedowski classification are closely associated with climate, but it also revealed weaknesses in the underlying basis of this classification system. Conclusions: Rzedowski's scheme for vegetation classification may require further modification in order to be an effective tool for research into vegetation–climate relationships.     

中国热带森林植被类型研究历史和划分探讨

热带森林是我国森林植被的重要组成部分,明确其森林植被类型分类对于生物多样性维持机制研究和保护管理等都具有重要意义。该文以中国热带森林植被分类研究中存在的问题为出发点,通过阐述我国各省区植被类型分类的研究历史,在综合考虑多种生物和非生物影响因素的基础上,提出一个新的热带森林植被类型分类框架以供探讨。结果表明:(1)尽管针对我国热带森林的分布范围和群落特征等都已开展了诸多研究,但对我国热带森林植被类型的划分依据和分类体系仍存在争议。(2)尽管我国的热带森林都处于季风气候区带内,但许多热带地区的森林植被类型并不只是受季风影响,而是气候带、关键气候因子、地形、土壤反馈和物种适应等多种因素共同作用的结果。(3)我国的热带森林植被包括5个植被型,即非典型性热带雨林、热带季雨林、热带山地雨林、热带山顶苔藓矮林(热带云雾林)和热带针叶林,其中热带季雨林植被型包含4种植被亚型[热带落叶季雨林、热带半落叶(半常绿)季雨林、热带常绿季雨林和热带石灰岩(石山)季雨林]。(4)阐明了上述热带森林植被型和植被亚型在我国各省区的分布情况,并提出未来有必要对人工恢复后的热带森林进行评估和植被类型划分。综上所述,该文提出一个新的热带森林植被类型分类框架,以期为今后基于不同地区开展热带森林比较研究提供参考。     

Forest structure and biomass in post-agricultural forests: Lessons learned with new spatial tools

Questions: With calls for afforestation to sequester carbon due to climate change, agricultural land will be converted to forests in the near future. Little is known about how the ecosystem services of reforested landscapes with an agricultural land-use history will differ from reference forests. Our objectives were to (i) test the hypothesis that forests with a history of agricultural land use can provide the same carbon storage and biomass ecosystem services as adjacent reference forests, given some recovery time; (ii) explore whether there is a lag in the recovery of forest community composition due to prior agricultural land use; and (iii) demonstrate how remote-sensing methods can improve our understanding of land-use legacies at large spatial scales. Location: Finger Lakes National Forest, NY, USA. Methods: Using historic air photos, landscape-scale lidar, and field surveys, we compared differences in biomass storage, forest structure, and vegetation communities between reference forests and post-agricultural forests at different stages of regeneration in the Finger Lakes National Forest, New York, USA. We also used lidar to create a spatial model of biomass across the landscape to analyze the spatial distribution of biomass across our study area. Results: We found biomass and forest structure in post-agricultural forests generally recovered to levels typical of reference forests within 50 years of abandonment. Conversely, we found the composition of woody and herbaceous communities still varied between reference and post-agricultural forests after 50 years of abandonment. Conclusions: Collectively our results indicate afforestation efforts can be effective for carbon sequestration at early stages of forest succession. Our spatial model of biomass indicated that biomass levels can be low in forests with extensive edge. Further research is needed to understand how contemporary landscape structure interacts with legacy effects of agriculture to affect biomass and other ecosystem services.     

Assessment of biodiversity in Central Federal District using satellite-based maps of terrestrial ecosystems

A research study of the ecosystem biodiversity of the Central Federal District (CFD) has been carried out at the regional level with the use of the map of vegetation in the terrestrial ecosystems, which was created on the basis of the high spatial resolution (30 m) data obtained from the Landsat satellite series. Numerical characteristics such as the areas of the forest and other terrestral ecosystems; the number of forest plots; their average areas in a federal region; the disturbed forest land areas over the past 5 years; the proportions of the coniferous, deciduous, and mixed forests; and the total number of ecosystem types found in the federal region are calculated for each federal region in the Russian Federation within the CFD. The dominant landscape type is defined using a regular grid whose cell size matches the size of the average basal area of the forest plot on the vegetation map. The areas of the forest, agricultural, grassland, and agro-forest landscapes within each grid cell are estimated. The dominant landscape areas are assessed for each federal region; the analysis reveals that, on average, a quarter of all land areas in the district are occupied by agroforest landscapes. A logical sequence of research activities has been presented to assess the indicators of biodiversity in the forest and other terrestrial ecosystems and their functions and services.