基于数字相机图像的长白山森林物候模拟

植被物候作为全球植被和陆面过程模型的重要参数,对其状态的准确描述在很大程度上决定着模型的模拟精度。温带森林作为北半球中高纬度地区主要植被类型及全球重要碳源,研究其物候期的变化将提高对区域碳通量的估算精度。本文以长白山阔叶红松林为研究对象,探讨了数字相机图像在物种尺度物候模拟及群落尺度物候模型改进方面的作用,结果如下：（1）物种尺度上,利用数字相机能获取两种植被（红松,蒙古栎）较为准确的物候期（与人工观测数据比较,绝对误差〈3d）;（2）群落尺度上,基于数字相机图像获取的冠层状态数据提高了基于气象数据的物候模型（GSI：growingseasonindex）的模拟精度（R2=0．9）,尤其是秋季物候模拟,为进一步分析群落物候的环境控制因子提供了有力手段。研究表明：数字相机不仅能够提供精确地基于物种尺度的物候数据,还可为遥感物候数据的校正提供参考,同时为生态模型中物候模块的改进及降低区域尺度碳通量模拟不确定性提供了新的思路。     

Spatial pattern and compositive structure of forests in Guizhou

Remote-sensing and field data of Guizhou forest resources in 2000 are processed using ArcGIS, with the production of forest resource distribution map, forest age class structure map, and forest canopy distribution map. Analysis of these data shows that: (1) though there are multiple types of forest resources, forest coverage is low (only 25.27%, excluding sparse woodland, shrub and underage-forest); (2) the geographical distribution of forests is quite uneven, mainly in the southeast of the province and in Zunyi prefecture; (3) the zonal evergreen broad-leaved forests have been seriously destroyed, with striking secondary features, i.e., coniferous forest and shrubbery account for the greatest proportion of Guizhou forests; (4) the timber-forest is much larger in area than shelter-forest and economic forest; (5) young-and-middle aged forests are more widely distributed than near-and-over matured forest; and (6) the forest of Guizhou is not enough to effectively protect the environment of karst mountain areas of the province.     

Spatial pattern and compositive structure of forests in Guizhou

Remote-sensing and field data of Guizhou forest resources in 2000 are processed using ArcGIS, with the production of forest resource distribution map, forest age class structure map, and forest canopy distribution map. Analysis of these data shows that: (1) though there are multiple types of forest resources, forest coverage is low (only 25.27%, excluding sparse woodland, shrub and underage-forest); (2) the geographical distribution of forests is quite uneven, mainly in the southeast of the province and in Zunyi prefecture; (3) the zonal evergreen broad-leaved forests have been seriously destroyed, with striking secondary features, i.e., coniferous forest and shrubbery account for the greatest proportion of Guizhou forests; (4) the timber-forest is much larger in area than shelter-forest and economic forest; (5) young-and-middle aged forests are more widely distributed than near-and-over matured forest; and (6) the forest of Guizhou is not enough to effectively protect the environment of karst mountain areas of the province.     

Remote Sensing Indices to Measure the Seasonal Dynamics of Photosynthesis in a Southern China Subtropical Evergreen Forest

The accurate measurement of the dynamics of photosynthesis in China’s subtropical evergreen forest ecosystems is an important contribution to carbon (C) sink estimates in global terrestrial ecosystems and their responses to climate change. Eddy covariance has historically been the only direct method to assess C flux of whole ecosystems with high temporal resolution, but it suffers from limited spatial resolution. During the last decade, continuous global monitoring of plant primary productivity from spectroradiometer sensors on flux towers and satellites has extended the temporal and spatial coverage of C flux observations. In this study, we evaluated the performance of two physiological remote sensing indices, fluorescence reflectance index (FRI) and photochemical reflectance index (PRI), to measure the seasonal variations of photosynthesis in a subtropical evergreen forest ecosystem using continuous canopy spectral and flux measurements in the Dinghushan Nature Reserve in southern China. The more commonly used NDVI has been shown to be saturated and mainly affected by illumination (R²=0.88, p < 0.001), but FRI and PRI could better track the seasonal dynamics of plant photosynthetic functioning by comparison and are less affected by illumination (R²=0.13 and R²=0.51, respectively) at the seasonal scale. FRI correlated better with daily gross primary production (GPP) in the morning hours than in the afternoon hours, in contrast to PRI which correlated better with light-use efficiency (LUE) in the afternoon hours. Both FRI and PRI could show greater correlations with GPP and LUE respectively in the senescence season than in the recovery-growth season. When incident PAR was taken into account, the relationship between GPP and FRI was improved and the correlation coefficient increased from 0.22 to 0.69 (p < 0.001). The strength of the correlation increased significantly in the senescence season (R ²=0.79, p < 0.001). Our results demonstrate the application of FRI and PRI as physiological indices for the accurate measurement of the seasonal dynamics of plant community photosynthesis in a subtropical evergreen forest, and suggest these indices may be applied to carbon cycle models to improve the estimation of regional carbon budgets.     

南岭国家级自然保护区森林景观格局变化与动态模拟

基于eCogntion、ArcGIS 和IDRISI 软件,采用景观格局指数分析广东南岭国家级自然保护区1988~2009 年景观类型数量及空间格局的变化;运用CA-Markov 模型模拟流域2010年的景观格局,预测2021 年的景观格局。结果表明,研究区森林景观类型以常绿阔叶林和针叶林为主;景观破碎度增加,斑块复杂程度提高,各景观类型的分布更加趋于复杂化;CA-Markov模型预测表明,2010~2021 年景观破碎度有所降低,多样性增加。     

How green was my valley: forest canopy density in relation to topography and anthropogenic effects in Manipur valley,India

Forest canopy density (FCD) is a major factor in the evaluation of forest status and is an important indicator of possible management interventions. The study uses the FCD model with Landsat TM and Landsat 8 OLI images to assess canopy density in India’s Manipur valley and surrounding hills. Normalized difference built-up index (NDBI) was used to extract built-up areas and population density was retrieved from LandScan data, while elevation and slope were obtained from ASTER DEMs (30 m). Four types of canopy density were delineated with crown cover above 71%, 41–70%, 11–40%, below 10% and areas with no canopy cover, that is 0%. A sharp decline in forest area occurred during 1989–2016 at a rate of loss of 2.9 % year-1 with an average rate of deforestation of 3051 ha year-1. Dense forests exhibited remarkable degradation, especially towards the central valley. The variation in the topographical (elevation and slope) gradient resulted in significant differences in the canopy density over the study area barring some hill slopes. Population pressure and various developmental activities in recent decades led to forest degradation in this fragile yet rich Eastern Himalaya biodiversity hotspot.     

DISTRIBUTION PATTERNS OF LEAF AREA INDEX FOR MAJOR CONIFEROUS FOREST TYPES IN CHINA

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基于阈值分割的黑龙江省森林类型遥感识别

全球变化背景下,准确获取森林覆盖是监测森林资源动态、实现林业可持续发展的重要基础。为将省级尺度森林资源清查面积资料空间化,以黑龙江省为例,利用1999-2003年该省森林资源清查面积数据,结合2000年500 m分辨率的MODIS数据,构建了基于阈值分割的森林类型遥感识别方法。该方法利用不同地表覆被类型归一化植被指数时间序列的季节分异特征,以森林资源清查面积为标准,设定森林类型的划分阈值,识别了黑龙江省森林类型的空间分布。最后,基于分层随机抽样和精度评价方法,表明森林类型识别结果与地面参考数据具有较高的一致性,总体分类精度为78.1%;特别是季节特征明显的落叶林,精度可达80%以上。本文所构建的方法可将森林清查统计数据进行准确的空间定位,同时结合多期森林资源连续清查资料和遥感信息,可为识别并量化区域生态系统生物量和碳库变化等提供科技支撑。     

天山中部天然云杉林凋落物层水文生态功能研究

选取了4种不同郁闭度天然云杉林分,通过对凋落物层的蓄积量、最大持水量、最大持水率、吸水速率及有效拦蓄量进行测定分析,研究了其水文生态功能.结果表明:郁闭度为0.8的云杉林分凋落物层蓄积量最大为21.99 t/hm2,而郁闭度为0.2的云杉林分凋落物层蓄积量最小仅为10.20 t/hm2,4种林分凋落物蓄积量交化总体趋势...     

Heterogeneity of water-retention capacity of forest and its influencing factors based on meta-analysis in the Beijing-Tianjin-Hebei region

Water retention is important in forest ecosystem services.The heterogeneity analysis of water-retention capacity and its influencing factors is of great significance for the construction of water-retention functional areas,restoration of vegetation,and the protection of forest ecosystems in the Beijing-Tianjin-Hebei region.A total of 1366 records concerning water-retention capacity in the canopy layer,litter layer,and soil layer of forest ecosystem in this region were obtained from 193 literature published from 1980 to 2017.The influencing factors of water-retention capacity in each layer were analyzed,and path analysis was used to investigate the contribution of the factors to the water-retention capacity of the three layers.The results showed that mixed forests had the highest water-retention capacity,followed by broad-leaved forests,coniferous forests,and shrub forests.In addition,no matter the forest type,the ranking of the water-retention capacity was soil layer,canopy layer,and litter layer from high to low.The main influencing factors of water-retention capacity in forest canopy were leaf area index and maximum daily precipitation(R2=0.49),and the influencing coeffi-cients were 0.34 and 0.30,respectively.The main influencing factors of water-retention ca-pacity in the litter layer were semi-decomposed litter(R2=0.51),and the influencing coefficient was 0.51.The main influencing factors of water-retention capacity in the soil layer were non-capillary porosity and soil depth(R2=0.61),the influencing coefficients were 0.60 and 0.38, respectively.This study verifies the simulation of the water balance model or inversion of remote sensing of the water-retention capacity at the site scale,and provides scientific basis for further study of the impact of global change on water retention.     

中国矮曲林的分布特征及生态意义

矮曲林是山地森林带在严酷的自然环境影响下发展演化而成的特殊植物群落,对中国山地植被和垂直带的研究具有重要的地理和生态意义。本文选择20世纪30年代以来在国内外文献中发表的52个矮曲林数据,结合Worldclim气候数据等,对中国矮曲林的类型和分布及其相应的气候条件进行了研究。结果表明：①中国的矮曲林主要包括山顶苔藓矮曲林、寒温性偃松矮曲林和岳桦矮曲林3类;其中,山顶苔藓矮曲林主要分布于秦巴山区以南的山地,而偃松矮曲林和岳桦矮曲林主要分布于东北地区。②山顶苔藓矮曲林主要由亚热带、热带地区的常绿阔叶林在山顶或山脊受山顶效应等的影响演化而来;而寒温性矮曲林主要由寒温性针叶林或针阔混交林在山顶或山脊条件下长期演化而来。山顶苔藓矮曲林自东向西随地势升高,其分布的海拔高度也逐渐升高;寒温性偃松矮曲林和岳桦矮曲林分布高度自南向北逐渐降低。③矮曲林分布在气候林线以下的山地,其气候条件足以支撑山地森林的发育,但由于山顶效应的存在(如强风、气候干冷或湿冷及土壤贫瘠等),只能发育矮曲林而非垂直地带性的山地森林。④中国东南部的很多山地高度小于3000 m,山顶效应明显,矮曲林广泛发育,造成了假林线的普遍存在。     

Characteristics of evapotranspiration from a permafrost black spruce forest in interior Alaska

Here, the year 2011 characteristics of evapotranspiration and the energy budget of a black spruce forest underlain by permafrost in interior Alaska were explored. Energy balance was nearly closed during summer, and the mean value of the daily energy balance ratio (the ratio of turbulent energy fluxes to available energy) from June to August was 1.00, though a large energy balance deficit was observed in the spring. Such a deficit was explained partly by the energy consumed by snowmelt. Ground heat flux played an important role in the energy balance, explaining 26.5% of net radiation during summer. The mean daily evapotranspiration of this forest during summer was 1.37 mm day^?1 – considered typical for boreal forests. The annual evapotranspiration and sublimation yielded 207.3 mm year^?1, a value much smaller than the annual precipitation. Sublimation accounted for 8.8% (18.2 mm year^?1) of the annual evapotranspiration and sublimation; thus, the sublimation is not negligible in the annual water balance in boreal forests. The daytime average decoupling coefficient was very small, and the mean value was 0.05 during summer. Thus, evapotranspiration from this forest was mostly explained by the component from the dryness of the air, resulting from the aerodynamically rough surface of this forest.     

贵州森林的空间格局及组成结构

利用ArcGIS,对贵州省2000年所作的森林资源连续清查遥感判读样点数据进行处理和分析,提取了森林资源分布图、林龄结构分布图、郁闭度分布图等系列森林景观图;分析结果表明：(1) 贵州森林植被类型多样,但覆盖率相对较低,全省森林覆盖率为25.27 % (不含疏林、灌木林、未成林造林地面积);(2) 森林地理分布不均匀,主要分布在黔东南及北部的遵义地区;(3) 地带性植被常绿阔叶林破坏严重,森林具有明显的次生性,表现为针叶林和灌木林所占比重大;(4) 林种结构的特点是用材林占比重大,防护林、经济林所占比重小;(5) 林龄结构的特点是幼中龄林为主,近成过熟林面积、蓄积比重都相对较小;(6) 贵州森林不能充分发挥森林植被对喀斯特山区生态环境的保护功能。     

广东南岭国家级自然保护区森林鸟类多样性监测

野生鸟类资源是自然保护区生物多样性的重要组成部分,为了解广东南岭国家级自然保护区鸟类种类和数量动态变化以及鸟类栖息地环境状况,2017年4月、7月和10月对区内11条鸟类监测样线进行了调查。调查结果显示：1）记录鸟种11目27科89种,其中雀形目15科61种;发现频次888次,记录数量3 367只,频次和数量均居前五的有栗背短脚鹎Hemixos castanonotus、灰眶雀鹛Alcippe morrisonia、灰树鹊Dendrocitta formosae、红嘴相思鸟Leiothrix lutea。2）居留型以留鸟为主,共61种,占68.5%;夏候鸟15种,占16.9%;旅鸟7种,占7.9%;冬侯鸟6种,占6.7%。鸟类区系组成以东洋界鸟种为主,共62种,占总数的69.7%;广布种19种,占21.3%;古北种8种,占9.0%。3）4月份是南岭鸟类繁殖活跃期,也是调查记录鸟种和数量最多的月份。11条样线中,相思坑、炉田、横水、南木、泽子坪、电视台、第一峰鸟类多样性（Shannon Wiener index）较高,怡坑、仙洞、担杆冲、竹坳多样性较低。4）根据海拔和植被类型,样线鸟类群落可分为4类：低海拔针阔混交林、常绿阔叶林、高海拔针阔混交林和山顶矮林。300~1 500 m的针阔混交林和常绿阔叶林生境鸟类群落并没有很大差异,优势种均为栗背短脚鹎、灰眶雀鹛、灰树鹊等;而高海拔山顶矮林（1 300~1 800 m）生境鸟种则明显不同,以画眉科（Timaliidae）的红嘴相思鸟、红头穗鹛、赤尾噪鹛、褐胸噪鹛、灰眶雀鹛及莺科（Sylviidae）的金头缝叶莺、比氏鹟莺、栗头鹟莺、冠纹柳莺为主。建议建立南岭鸟类多样性监测网络和评价体系,以鸟类长期监测数据,如种类变化、种群波动,作为评价保护区生态环境质量的指标。     

Research on Forest Phenology Prediction based on LSTM and GRU Model

Research on forest phenology is an important parameter related to climate and environmental changes. An optical camera was used as a near-earth remote sensing satellite device to obtain forest images, and the data of Green excess index (GEI) in the images were calculated, which was fitted with the seasonal variation curve of GEI data by double Logistic method and normalization method. LSTM and GRU deep learning models were introduced to train and test the GEI data. Moreover, the rationality and performance evaluation of the deep learning model were verified, and finally the model predicted the trend of GEI data in the next 60 days. Results showed: In the aspects of forest phenology training and prediction, GRU and LSTM models were verified by histograms and autocorrelation graphs, indicating that the distribution of predicted data was consistent with the trend of real data, LSTM and GRU model data were feasible and the model was stable. The differences of MSE, RMSE, MAE and MAPE between LSTM model and GRU model were 0.0014, 0.013, 0.008 and 5.26%, respectively. GRU had higher performance than LSTM. The prediction of LSTM and GRU models about GEI data for the next 60 days both showed a trend chart consistent with the change trend of GEI data in the first half of the year. GRU and LSTM were used to predict GEI data by deep learning model, and the response of LSTM and GRU deep learning models in forest phenology prediction was realized, and the performance of GRU was better than that of LSTM model. It could further reveal the growth and climate change of forest phenology in the future, and provide a theoretical basis for the application of forest phenology prediction.     

How changes of groundwater level affect the desert riparian forest ecosystem in the Ejina Oasis,Northwest China

Groundwater is a key factor controlling the growth of vegetation in desert riparian systems. It is important to recognise how groundwater changes affect the riparian forest ecosystem. This information will not only help us to understand the ecological and hydrological process of the riparian forest but also provide support for ecological recovery of riparian forests and water-resources management of arid inland river basins. This study aims to estimate the suitability of the Water Vegetation Energy and Solute Modelling(WAVES) model to simulate the Ejina Desert riparian forest ecosystem changes,China, to assess effects of groundwater-depth change on the canopy leaf area index(LAI) and water budgets, and to ascertain the suitable groundwater depth for preserving the stability and structure of desert riparian forest. Results demonstrated that the WAVES model can simulate changes to ecological and hydrological processes. The annual mean water consumption of a Tamarix chinensis riparian forest was less than that of a Populus euphratica riparian forest, and the canopy LAI of the desert riparian forest should increase as groundwater depth decreases. Groundwater changes could significantly influence water budgets for T. chinensis and P. euphratica riparian forests and show the positive and negative effects on vegetation growth and water budgets of riparian forests. Maintaining the annual mean groundwater depth at around 1.7-2.7 m is critical for healthy riparian forest growth. This study highlights the importance of considering groundwater-change impacts on desert riparian vegetation and water-balance applications in ecological restoration and efficient water-resource management in the Heihe River Basin.     

Assessment of spatial and temporal dynamics of tropical forest cover: A case study in Malkangiri district of Orissa, India

Tropical forests have been recognized as having global conservation importance. However, they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa, India, during 1973–2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest, open forest, scrub land, agriculture, barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation, shifting cultivation, dam and road construction, unregulated management actions, and social pressure. A significant increase of 1222.8 km2 agriculture area (1973–2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences, including decline in forest cover, soil erosion, and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests, which are rapidly being deforested.     

秦巴山区马尾松林和油松林的空间分布及亚热带与暖温带界线划分

秦岭不仅是中国南北的地理分界线,也是中国亚热带和暖温带的气候分界线,在中国地理生态格局中占有重要的地位和作用。由于过渡带的复杂性、过渡性和异质性以及划分指标、研究目的的不同,学术界关于这一南北地理—生态分界线的具体位置一直有争论。为了进一步揭示秦巴山区过渡带的特征,明确中国南北地理—生态分界线的位置,本文选择马尾松（Pinus massoniana）林和油松（Pinus tabulaeformis）林这两类分别代表中国南方亚热带针叶林和北方温带针叶林的植被,结合研究区SRTM地形数据、气温和降水数据等,以年降水、最冷月（1月）气温、最热月（7月）气温和年均温为气候指标,详细分析了这两类植被在秦巴山区的空间分布及二者分界线处的气候条件。结果表明：① 马尾松林和油松林的分界线及相应位置的气候指标可以作为亚热带与暖温带界线划分的植被—气候指标之一。秦巴山区亚热带针叶林（马尾松林）与温带针叶林（油松林）的分界线位于伏牛山南坡至汉中盆地北缘一线（秦岭南坡）海拔1000~1200 m处;分界线处气候指标稳定：年降水750~1000 mm,年均温12~14 ℃,最冷月气温0~4 ℃,最热月气温22~26 ℃。② 通过综合的植被—气候指标来划分秦巴山区亚热带和暖温带的界线,能更科学地确定气候带分界线的位置及过渡带的特征,更全面地反映地表植被—气候格局的变化。此外,秦巴山区亚热带与暖温带的界线应该是由亚热带与暖温带针叶林分界线、阔叶林分界线、灌丛分界线等组成的一个过渡带。本文的研究结果为亚热带与暖温带划分指标的选取提供了一定的科学依据。     

基于PnET-CN模型的亚热带人工针叶林生产力与固碳潜力模拟研究

A generalized, lumped-parameter ecological model PnET-CN was calibrated and validated for a subtropical coniferous plantation in southern China. PnET-CN model describes the biogeochemical cycles of carbon (C) and nitrogen (N) and can assist in estimating carbon sequestration potential. For validation of PnET-CN, data from coniferous forest plantations in southern China was used. Simulated daily gross primary productivity (GPP) from 2005 to 2007 agreed well with observations (R2=0.56, S.D.=0.009). Simulations of monthly soil res-piration (Rs) from 2005-2007 agreed well with Rs observations (R2=0.67, S.D. =0.03). Simu-lated annual net primary productivity (NPP) from 1998-2006 was 803 33 gCm 2a 1, about 4% higher than NPP observation (752 51 gCm 2a 1). Simulations of annual NEP from 2005 2007 only overestimate 9 gCm 2a 1 (4%), 4 gCm 2a 1 (1%) and 34 gCm 2a 1 (8%) compared to NEP observations, respectively. Simulated annual foliar N concentration (FolNCon) (1.09%) is 10% lower than observed monthly FolNCon (0.87%-1.58%). Simulated annual N leaching (0.26 gNm 2) is about 10% lower than leaching observation (0.29 gNm 2). PnET-CN model valida-tion indicates that PnET-CN is capable to simulate daily GPP, annual NPP, annual NEP, monthly Rs, annual FolNCon and annual nitrate N leaching for subtropical coniferous planta-tions in southern China. The results obtained from the validation test revealed that PnET-CN model can be used to simulate carbon sequestration of planted coniferous forests in southern China to a high level of precision. Sensitivity analysis suggests that great care should be taken in developing generalizations as to how forests will respond to a changing climate. PnET-CN performed satisfactorily in comparison to other models that have already been calibrated and validated in coniferous planted subtropical forests in China. Based on PnET-CN validation and its comparison to other models, future improvement of PnET-CN should focus on seasonal foliar N dynamics and the effects of water stress on autotrophic respirations in subtropical coniferous plantations in southern China.     

热带森林覆被的时空动态评价——以印度Malkangiri district of Orissa为例

Tropical forests have been recognized as having global conservation importance. However,they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa,India,during 1973-2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973),Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest,open forest,scrub land,agriculture,barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation,shifting cultivation,dam and road construction,unregulated management actions,and social pressure. A significant increase of 1222.8 km2 agriculture area (1973-2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences,including decline in forest cover,soil erosion,and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests,which are rapidly being deforested.