Palaeoenyironments and human impact at Burraga Swamp in Montane rainforest,Barrington tops National Park,New South Wales,Australia

Palaeoecological studies have identified the broad patterns of environmental and climate change in highland south‐eastern Australia, but the detail of human impact on a variety of parameters and their interlinkages is largely missing. This study compares the erosion, productivity, fire and vegetation history in prehistoric and historical times at Burraga Swamp in montane rainforest in New South Wales. The known human impact is meagre; the major presently sustained impacts involve forestry in the surrounding sclerophyll forests and a low level of visits to the swamp by day‐walkers. While no significant changes in the largely oligotrophic conditions or in fire frequency were detected, changes in erosion rates and some vegetation change can be attributed to impacts since European settlement. There has been a small decline in eucalypts and a loss of fern cover, while grasses, Urtica and exotic species have expanded. It is clear that upland sites are sensitive to environmental change including low‐level human impact.     

基于改进雨林模糊神经网络模型的页岩储层总有机碳含量评价方法

由于采用常规测井曲线评价页岩储层总有机碳含量的精度不高,泛化能力不强,需要大量样本。针对这些问题,改 进了神经网络算法,以增加模型的预测能力。利用模糊系统优化细胞神经网络结构,以增强其逻辑推理能力,提高其对模 糊数据的敏感性;选择能有效避免“虚拟碰撞”的雨林算法,并针对其存在的缺陷进行改进;利用改进雨林优化算法对网 络的初始权值阈值进行优化,避免网络陷入局部极小。分析测井特征曲线的物理意义,选择密度测井曲线与自然伽马能谱 测井曲线作为网络的输入,以总有机碳含量作为输出,通过70块岩心样本网络学习与26块岩心样本预测,证明了新网络模 型的优越性。结果表明,新模型回判将相对误差从23.189%减小到17.185%,预测相对误差由52.421%减小到15.158%,具 有更强的学习能力与泛化能力,更适用于页岩储层总有机质含量的测井评价。     

巴西热带雨林森林景观转化时空特征及破碎化分析

巴西热带雨林地区森林景观转化及破碎化导致森林生态系统的功能和区域环境发生变化,并引起全球范围内的关注。以欧洲太空局全球土地利用/土地覆被数据和Landsat解译数据为基础,利用热点提取、信息熵、地统计分析模型及轨迹分析的方法探讨不同砍伐阶段森林破碎性的变化特点以及森林破碎化与整个区域景观格局变化的相关性。结果表明：① 热带雨林地区的森林面积迅速减少,其中,Rondonia州、Maton Grosso州和Para州最为典型。② 森林破碎性的变化趋势并非整体性的增加或减少,而是出现明显的局地性特点;③ 森林砍伐的数量与土地系统的信息熵呈正相关,即森林的数量及质量直接决定巴西热带雨林地区的土地系统稳定性。     

巴西土地利用/覆盖变化时空格局及驱动因素

土地利用/覆盖变化(LUCC)是全球变化研究的热点问题之一。本文采用人机交互方法基于2005 年基准年的Landsat TM/ETM遥感影像修正欧空局GlobalCover 2005 年土地利用数据,进而采用逆时相目视解译法从1980年基准年的Landsat MSS/TM遥感影像数据提取1980-2005 年土地利用/覆盖变化信息,分析其变化的时空格局及驱动因素。结果表明:1980-2005年的25年间,巴西土地利用/覆盖变化面积达79.43万km²,占土地总面积的9.33%。其中,单纯耕地像元面积增加了20.18 万km²;耕地/自然植被镶嵌混合像元区面积增加了10.70 万km²;林地面积减少了53.12 万km²;灌丛与草地净增加21.10 万km²;水体面积增加0.46 万km²;城乡建设用地面积增加7573.87 km²。由此导致热带和亚热带湿润阔叶林生态地理区、热带和亚热带干旱阔叶林生态地理区、热带及亚热带草原生态地理区、草原和沼泽湿地生态地理区、沙漠和旱生植物生态地理区以及红树林生态地理区内分别呈现不同的土地利用/覆盖变化特征。近25 年间,地形地貌、气候、植被等自然地理条件深刻影响着土地利用的宏观格局,而土地利用政策调控、经济及对外贸易发展、人口增加及空间迁移、道路修建等是导致巴西土地利用变化的主要原因。     

桂西南喀斯特季节性雨林凋落叶分解速率和养分含量特征分析

森林凋落物是森林生态系统极其重要的组成部分, 了解凋落物分解过程有助于理解森林生态系统的物质循环和养分平衡的机理。本研究以桂西南喀斯特季节性雨林凋落叶为研究对象, 将2018年全年收集的凋落叶混合均匀后采用分解袋法进行原位分解实验, 探讨桂西南喀斯特季节性雨林凋落物的分解特征。结果发现: 凋落叶在分解过程中整体失重模式呈现先快后慢的变化趋势, 且不同生境类型下凋落叶失重率为: 洼地＞坡地＞峰顶; 分解过程中C含量呈波动状态, 但总体表现为下降趋势, 而N含量呈无规则波动; 失重率与海拔呈显著负相关, 并在分解初期和中后期与坡度呈显著负相关, C含量变化同海拔呈显著正相关, 而与其他环境因子的相关性则随分解时间的变化而变化。桂西南喀斯特季节性雨林凋落叶分解速率低于亚热带常绿落叶阔叶混交林, 但与同类型的喀斯特森林退化区相当; 喀斯特季节性雨林不同生境类型代表的微环境因子对凋落叶的分解具有重要影响, 其中海拔引起的温度和湿度的差异是影响喀斯特季节性雨林凋落叶分解速率和C、N含量变化的主要因素。     

老挝NM地区地球物理勘查效果

在老挝中北部的热带雨林地区,进行了高精度磁法和激电中梯法测量。根据该区的地质特征,分析得出磁、电异常区走向总体呈NWW向分布,其分布范围基本与接触带矽卡岩矿化体的分布范围相一致。通过对比高精度磁法和激电中梯法的找矿效果,发现在热带雨林地区运用高精度磁法测量要明显好于激电中梯测量,同时高精度磁法测量还具有成本低、便于操作等优点。     

Streamflow response to native forest restoration in former Eucalyptus plantations in south central Chile

Global increases in intensive forestry have raised concerns about forest plantation effects on water, but few studies have tested the effects of plantation forest removal and native forest restoration on catchment hydrology. We describe results of a 14-year paired watershed experiment on ecological restoration in south central Chile which documents streamflow response to the early stages of native forest restoration, after clearcutting of plantations of exotic fast-growing Eucalyptus, planting of native trees, and fostering natural regeneration of native temperate rainforest species. Precipitation, streamflow, and vegetation were measured starting in 2006 in four small (3 to 5 ha) catchments with Eucalyptus globulus plantations and native riparian buffers in the Valdivian Coastal Reserve. Mean annual precipitation is 2500 mm, of which 11% occurs in summer. Streamflow increased, and increases persisted, throughout the first 9 years of vigorous native forest regeneration (2011 to 2019). Annual streamflow increased by 40% to >100% in most years and >150% in fall and summer of some years. Streamflow was 50% to 100% lower than before treatment in two dry summers. Base flow increased by 28% to 87% during the restoration period compared to pre-treatment, and remained elevated in later years despite low summer precipitation. Overall, these findings indicate that removal of Eucalyptus plantations immediately increased streamflow, and native forest restoration gradually restored deep soil moisture reservoirs that sustain base flow during dry periods, increasing water ecosystem services. To our knowledge this is the first study to assess catchment streamflow response to native forest restoration in former forest plantations. Therefore, the results of this study are relevant to global efforts to restore native forest ecosystems on land currently intensively managed with fast-growing forest plantations and may inform policy and decision-making in areas experiencing a drying trend associated with climate change.     

Support vector machines for tree species identification using LiDAR-derived structure and intensity variables

Tree species identification and forest type classification are critical for sustainable forest management and native forest conservation. Recent success in forest classification and tree species identification using LiDAR (light detection and ranging)-derived variables has been reported in many studies. However, there is still considerable scope for further improvement in classification accuracy. It has driven research into more efficient classifiers such as support vector machines (SVMs) to take maximum advantage of the information extracted from LiDAR data for potential increases in the accuracy of tree species classification. This study demonstrated the success of the SVMs for the identification of the Myrtle Beech (the dominant species of the Australian cool temperate rainforest in the study area) and adjacent tree species – notably, the Silver Wattle at individual tree level using LiDAR-derived structure and intensity variables. An overall accuracy of 92.8% was achieved from the SVM approach, showing significant advantages of the SVMs over the traditional classification methods such as linear discriminant analysis in terms of classification accuracy.     

利用GLASS LAI数据分析1982-2012年亚马逊热带雨林变化

利用1982-2012年的GLASS LAI数据,结合世界粮农组织(FAO)2000年发布的全球生态环境分类图,对亚马逊热带雨林31年的植被变化进行了综合分析,采用点与面相结合的分析方法,全面地反映雨林植被的变化情况。不同于过去研究中固定研究范围或直接研究整个南美洲区域,本文采用动态静态边界相结合的方法,在考虑热带雨林动态范围变化的同时也强调研究区域的内部变化。结果显示,亚马逊热带雨林叶面积指数在31年中整体呈现波动变化,进入2000年以后,热带雨林范围内平均叶面积指数先下降后增加,整体相对稳定。在空间分布上,由于人类毁林开荒,巴西境内的热带雨林以及热带雨林部分边缘地带的叶面积指数在31年中明显下降,热带雨林东南边界持续收缩;除此之外,雨林内部的叶面积指数波动上升,这是受到全球气候变暖的影响。结果与过去的研究进行对比,具有较好的一致性。研究论证了利用具有中国自主知识产权的GLASS LAI数据可以进行长时间序列大尺度的地表植被状况监测。     

Throughfall and its spatial variability in a temperate rainforest of simple structure

There are few throughfall data from southern hemisphere closed-forest, and none from Tasmanian callidendrous cool-temperate rainforest, which has a simpler structure than most primary rainforests. We determined throughfall, measured its local spatial variation, and tested its relationships with rainfall, rainfall intensity, wind speed, canopy dryness, canopy cover, and other structural variables in a cool-temperate callidendrous rainforest in Tasmania. Eighty-two percent of the precipitation was measured as throughfall, which occurred after 2.3 mm of rain fell on dry canopies. The cumulative rainfall in 25 randomly located funnel rain gauges on the forest floor varied from 160 to 567 mm. Canopy cover and other structural variables did not predict the spatial pattern of throughfall. While throughfall in rainfall events was related to rainfall amount and intensity, wind speed did not affect throughfall as a percentage of rainfall. Percentages of throughfall to rainfall over 100 for many low rainfall events may indicate a contribution of fog drip to precipitation on the forest floor. The high local spatial variability in throughfall indicates the mean moisture conditions on the forest floor may not be a good indicator of the potential for localised fire damage.