粤港澳大湾区红树林长时间序列遥感监测

随着遥感数据量的爆发式增长,对变化过程分析的精细化要求与本地算力不足之间的矛盾日益突出。GEE（Google Earth Engine）地理云平台的出现,解决了用户算力紧张的行业痛点。本文以粤港澳大湾区为研究区,在GEE的支持下,构建1987年—2020年年度湿地分类数据集,分析大湾区红树林的时间阶段性特征和空间扩张过程,结合连续长历时分析对变化时间点的准确识别,揭示了保护区设立与滩涂造林等工程在红树林保护与修复中的积极成效。主要结论有：（1）截止到2020年,大湾区共有红树林2174 ha,81%的红树林集中在深圳湾、淇澳岛和镇海湾;（2）大湾区的红树林经历了由平稳发展（1987年—2003年）到快速增长（2003年—2020年）的变化过程,其主要增量来源于镇海湾（40%）和淇澳岛（28%）;（3）淇澳岛和镇海湾的红树林仍处于快速增长期,但淇澳岛增速最快,从2002年至今面积翻了30倍,深圳湾则在早期的快速增长（1987年—2009年）后进入平稳期（2009年—2020年）;（4）由于保护区设立时间较早,深圳湾成为大湾区唯一一个形成稳定核心区的红树林分布区,镇海湾虽然拥有最大的红树林面积,但林道狭窄,景观破碎,生态系统反而更加脆弱;（5）设立自然保护区和滩涂造林都对红树林面积增长起到了积极作用。本研究为大湾区海岸带湿地生态系统保护与修复提供科学的证据支持,对沿海生态屏障建设具有一定的指导作用。     

基于随机森林的国产小卫星遥感影像分类研究

近年来随着小卫星数量与传感器类型的快速增加,急需研究和发展快速可靠的小卫星遥感影像分类方法。针对分类方法各具局限性、具体应用中最优分类器选取困难等问题,本文基于多分类器集成学习的思路,引入随机森林(Random Forests)方法用于小卫星遥感影像分类。采用灾害监测预报小卫星(HJ-1)、北京1号小卫星(BJ-1)两种国产小卫星多光谱遥感影像进行试验,并与传统分类方法进行比较,结果表明,随机森林比最大似然分类器(MLC)、支持向量机分类器(SVM)等具有更好的稳定性、更高的分类精度和更快的运算速度,具有很好的适用性。     

Detecting nutrient deficiency in spruce forests using multispectral satellite imagery

Nutrient deficiency in forest stands has a negative impact on timber production. Although there are numerous studies investigating nutrient deficiency in forests using remote sensing, research has usually focused on extracting nutrient/pigment concentrations using hyperspectral imagery. Results of studies using this method of assessment are uncertain at the canopy level. This study proposes using freely available multispectral imagery to identify nutrient deficiency in commercially managed forest plantations. A classification map of nutrient deficient, healthy, and a third class, other, for State spruce forests in the Republic of Ireland was constructed using multispectral Sentinel 2 images from Spring and a Random Forest model. The forest area of interest (AOI) was Sitka spruce or Norway spruce plantations greater than 12 years old. Results showed that the overall accuracy was 89% and the associated Kappa Index of agreement was 79%. An unbiased area estimator was vital for an accurate estimate of the scale of nutrient deficiency, which concluded that 23% of the AOI was nutrient deficient. Early detection of nutrient deficiency is crucial to mitigate negative impacts on productivity so a time series analysis of the spectral response of healthy and nutrient deficient classes using Google Earth Engine's Landsat 5, 7, and 8 archive was carried out. A control of known nutrient deficient sites, as identified through foliar analysis, was used for comparison with the nutrient deficient and healthy training data. The spectral response showed a decrease through time for all of the foliar analysis and training data using the green (520–600 nm), red (630–690 nm), and SWIR spectra (1550–1700 nm) during Spring. This decreasing trend is due to the growth of foliage, with the difference in spectral response between nutrient deficient and healthy stands being attributed to the presence of chlorosis in stands suffering from nutrient deficiency. Spectral thresholds using digital numbers for nutrient deficient stands were identified for an operational optimum age cohort of between 10–12 years old which will be used for early detection.     

Multi-level filtering segmentation to measure individual tree parameters based on Lidar data: Application to a mountainous forest with heterogeneous stands

This paper presents a method for individual tree crown extraction and characterisation from a canopy surface model (CSM). The method is based on a conventional algorithm used for localising LM on a smoothed version of the CSM and subsequently for modelling the tree crowns around each maximum at the plot level. The novelty of the approach lies in the introduction of controls on both the degree of CSM filtering and the shape of elliptic crowns, in addition to a multi-filtering level crown fusion approach to balance omission and commission errors. The algorithm derives the total tree height and the mean crown diameter from the elliptic tree crowns generated. The method was tested and validated on a mountainous forested area mainly covered by mature and even-aged black pine (Pinus nigra ssp. nigra [Arn.]) stands. Mean stem detection per plot, using this method, was 73.97%. Algorithm performance was affected slightly by both stand density and heterogeneity (i.e. tree diameter classes’ distribution). The total tree height and the mean crown diameter were estimated with root mean squared error values of 1.83 m and 1.48 m respectively. Tree heights were slightly underestimated in flat areas and overestimated on slopes. The average crown diameter was underestimated by 17.46% on average.     

东亚上空急流位置经向变化及其与东亚夏季气候异常的联系

利用1979—2010年逐月CMAP降水资料和NCEP/NCAR再分析资料集,通过定义夏季东亚急流位置指数,采用统计和动力诊断方法研究了东亚上空急流位置经向变化及其与东亚夏季气候的联系。所定义的东亚急流位置指数较好地反映了东亚上空急流位置的经向移动。结果表明:东亚上空急流经向位置的移动存在显著的年际变化,其主要周期为2~3 a和8 a。当夏季东亚急流位置偏北(南)时,从低纬到高纬,东亚地区降水异常主要呈现出偏多—偏少—偏多(偏少—偏多—偏少)的经向分布;相应地,气温则在副热带西太平洋地区偏低(高),我国华东、华北及日本地区气温偏高(低),西伯利亚东部较高纬地区气温偏低(高)。东亚上空急流经向位置异常年,异常环流随高度呈略有西倾的准正压结构。东亚上空急流经向位置的偏北(南)与由西太平洋—南海热带地区非绝热加热相关的经圈环流异常有关,亦与中纬度波扰能量东传有关,并由此可部分解释我国长江中下游至日本地区的气温异常偏高(低)。     

Decentralization, forests and livelihoods: Theory and narrative

This paper discusses the theory of decentralized forest management, the associated narrative and the underlying hypotheses. That discussion informs the assessment of whether decentralization can lead to forest conservation. The paper argues that the ideal model of democratic decentralization described in the literature is unlikely to be implemented given the governance constraints present in many tropical forest countries. Even if that model could be implemented, it is shown that decentralization cannot be expected to necessarily lead to forest conservation. The policies required to complement the current decentralization model are discussed, including financial incentives and monitoring and evaluation mechanisms.     

冬季赤道太平洋不同类型海温异常表征指数的再构建

利用1963—2013年Hadley中心月平均海表温度资料,以及NCEP/NCAR再分析资料,根据两类厄尔尼诺事件发生时北半球冬季赤道太平洋地区海温异常的不同空间分布特征,即赤道中太平洋CP型和东太平洋EP型海温异常空间分布,从寻找与之相似的空间型角度出发,设计了一组新的海温异常指数I_(CP)和I_(EP)。与以往ENSO指数相比,新指数组I_(CP)和I_(EP)不仅表示了空间上相互独立的海温异常分布,而且在相同的研究时段内,因时间域上相互独立而能更好地表征和区分两类El Ni?o/La Ni?a事件。据此,采用该新指数组探讨了与中部型和东部型海温异常事件相关的热带太平洋的主要海气耦合特征。结果表明,与传统的东部型El Ni?o事件发生时最大暖海温中心位于赤道东太平洋地区不同,中部型El Ni?o事件,异常增暖中心位于赤道中太平洋。中部型时异常Walker环流的上升支向西偏移,异常降水集中于热带中太平洋,不似东部型时异常限定于赤道东太平洋地区。不论哪类事件,海洋性大陆均可受到影响,即CP或EP型El Ni?o发生时,海洋性大陆区域降水偏少。但比较而言,中部型ENSO对海洋性大陆区域的影响更大。     

Observations of canopy storage capacity and wet canopy evaporation in a humid boreal forest

Evaporation of intercepted rain by a canopy is an important component of evapotranspiration, particularly in the humid boreal forest, which is subject to frequent precipitation and where conifers have a large surface water storage capacity. Unfortunately, our knowledge of interception processes for this type of environment is limited by the many challenges associated with experimental monitoring of the canopy water balance. The objective of this study is to observe and estimate canopy storage capacity and wet canopy evaporation at the sub-daily and seasonal time scales in a humid boreal forest. This study relies on field-based estimates of rainfall interception and evapotranspiration partitioning at the Montmorency Forest, Québec, Canada (mean annual precipitation: 1600 mm, mean annual evapotranspiration: 550 mm), in two balsam fir-white birch forest stands. Evapotranspiration was monitored using eddy covariance sensors and sap flow systems, whereas rainfall interception was measured using 12 sets of throughfall and six stemflow collectors randomly placed inside six 400-m² plots. Changes in the amount of water stored on the canopy were also directly monitored using the stem compression method. The amount of water intercepted by the forest canopy was 11 ± 5% of the total rainfall during the snow-free (5 July–18 October) measurement periods of 2017 and 2018. The maximum canopy storage estimated from rainfall interception measurements was on average 1.6 ± 0.7 mm, though a higher value was found using the stem compression method (2.2 ± 1.6 mm). Taking the average of the two forest stands studied, evaporation of intercepted water represented 21 ± 8% of evapotranspiration, while the contribution of transpiration and understory evapotranspiration was 36 ± 9% and 18 ± 8%. The observations of each of the evapotranspiration terms underestimated the total evapotranspiration observed, so that 26 ± 12% of it was not attributed. These results highlight the importance to account for the evaporation of rain intercepted by humid boreal forests in hydrological models.     

Northern landscapes in transition: Evidence,approach and ways forward using the Krycklan Catchment Study

Improving our ability to detect changes in terrestrial and aquatic systems is a grand challenge in the environmental sciences. In a world experiencing increasingly rapid rates of climate change and ecosystem transformation, our ability to understand and predict how, when, where, and why changes occur is essential for adapting and mitigating human behaviours. In this context, long-term field research infrastructures have a fundamentally important role to play. For northern boreal landscapes, the Krycklan Catchment Study (KCS) has supported monitoring and research aimed at revealing these changes since it was initiated in 1980. Early studies focused on forest regeneration and microclimatic conditions, nutrient balances and forest hydrology, which included monitoring climate variables, water balance components, and stream water chemistry. The research infrastructure has expanded over the years to encompass a 6790 ha catchment, which currently includes 11 gauged streams, ca. 1000 soil lysimeters, 150 groundwater wells, >500 permanent forest inventory plots, and a 150 m tall tower (a combined ecosystem-atmosphere station of the ICOS, Integrated Carbon Observation System) for measurements of atmospheric gas concentrations and biosphere-atmosphere exchanges of carbon, water, and energy. In addition, the KCS has also been the focus of numerous high resolution multi-spectral LiDAR measurements and large scale experiments. This large collection of equipment and data generation supports a range of disciplinary studies, but more importantly fosters multi-, trans-, and interdisciplinary research opportunities. The KCS attracts a broad collection of scientists, including biogeochemists, ecologists, foresters, geologists, hydrologists, limnologists, soil scientists, and social scientists, all of whom bring their knowledge and experience to the site. The combination of long-term monitoring, shorter-term research projects, and large-scale experiments, including manipulations of climate and various forest management practices, has contributed much to our understanding of boreal landscape functioning, while also supporting the development of models and guidelines for research, policy, and management.     

Ecohydrological modelling in a deciduous boreal forest: Model evaluation for application in non-stationary climates

Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one-dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm³/cm³. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.