Ecosystem Carbon Allocation of a Temperate Mixed Forest and a Subtropical Evergreen Forest in China

Ecosystem carbon allocation can indicate ecosystem carbon cycling visually through its quantification within different carbon pools and carbon exchange. Using the ecological inventory and eddy covariance measurement applied to both a mature temperate mixed forest in Changbai Mountain (CBM) and a mature subtropical evergreen forest in Dinghu Mountain (DHM), we partitioned the ecosystem carbon pool and carbon exchange into different components, determined the allocation and analyzed relationships within those components. Generally, the total carbon stock of CBM was slightly higher than that of DHM due to a higher carbon stock in the arbor layer at CBM. It was interesting that the proportions of carbon stock in vegetation, soil and litter were similar for the two mature forests. The ratio of vegetation carbon pool to soil carbon stock was 1.5 at CBM and 1.3 at DHM. However, more carbon was allocated to the trunk and root from the vegetation carbon pool at CBM, while more carbon was allocated to foliage and branches at DHM. Moreover, 77% of soil carbon storage was limited to the surface soil layer (0-20 cm), while there was still plentiful carbon stored in the deeper soil layers at DHM. The root/shoot ratios were 0.30 and 0.25 for CBM and DHM, respectively. The rates of net ecosystem productivity (NPP) to gross ecosystem productivity (GPP) were 0.76 and 0.58, and the ratios of ecosystem respiration (Re) to GPP were 0.98 and 0.87 for CBM and DHM, respectively. The net ecosystem carbon exchange/productivity (NEP) was 0.24 t C ha^-1 yr^-1 for CBM and 3.38 t C ha^-1 yr^-1 for DHM. Due to the common seasonal and inter-annual variations of ecosystem carbon exchange resulting from the influence of environmental factors, it was necessary to use the long record dataset to evaluate the ecosystem sink capacity.     

基于数值预报和随机森林算法的强对流天气分类预报技术

随机森林算法是当前得到较为广泛应用的机器学习方法之一,有着很高的预测精度,训练结果稳定,泛化能力强,解决多分类问题有明显优势。本文将随机森林算法应用于强对流的潜势预测和分类,分短时强降水、雷暴大风、冰雹和无强对流四种类别,基于2005—2016年NCEP 1°×1°再分析资料计算的对流指数和物理量,开展强对流天气的分类训练、0～12 h预报和检验,经2015—2016年独立测试样本检验表明,针对强对流发生站点的点对点检验,整体误判率为21. 9%,85次强对流过程基本无漏报,模型尤其适用于较大范围强对流天气。随机森林算法筛选的因子物理意义较为明确,和主观预报经验基本相符,模型准确率高,可用于日常业务。     

河南省森林火险月季尺度定量客观化预测

基于火灾资料和气象资料,利用数理统计方法和百分位法,分析了河南省林区火灾的气候特征及防火关键期高火险日数的月、季气候特征。结果表明,林区火灾次数年际波动较大,主要出现在每年的冬春季(12月次年4月),3月出现的次数最多,2月的次之。火灾峰值主要出现在13-16时。3月高火险日数存在显著增加的线性趋势,12月和1月高火险日数呈现先减少后增加的趋势。2月和4月高火险日数处在偏少的年代际背景下。林区春季高火险日数存在显著增加的线性趋势,在桐柏-大别山林区尤其明显。选取河南省防火关键期各月、季高火险日数与海温、积雪、环流场等130项环流指数的相关关系最好的因子,利用最优子集回归分别建立基于林区内各个气象站点的预测方程。通过回代检验和趋势异常综合评分(Ps),对回归方程预测效果进行检验,结果显示,回代曲线和历史曲线吻合好,表明预测方程预测结果接近实况。     

Evapotranspiration of a Populuseuphratica Oliv. forest and its controlling factors in the lowerHeihe RiverBasin, Northwest China

Evapotranspiration (ET) within an ecosystem is crucial for the water-limited environment that currently lacks adequate quantification in the arid region of Northwest China, mainly covered by phreatophytes, such as the Populus euphratica Oliv. tree and the Tamarix ramosissima Ledeb. shrub species. Accordingly, ET was measured for an entire year using eddy covariance (EC) in P. euphratica stands in the lower Heihe River Basin, Northwest China. During the growing season, the total ET was 850 mm, with a mean of 4.0 mm/d, which is obviously more than that observed at tree-level and standlevel scales, which was likely due to the different level of soil evaporation induced by irrigation via water conveyance. Factors associated with ET fall into either environmental or plant eco-physiological categories. Environmental factors account for at least 79% variation of ET, and the linear relationship between ET and the groundwater table (GWT) revealed the potential water use of P. euphratica forests under the non-water stress condition with the GWT less than 3 m deep. Plant eco-physiological parameters, specifically the leaf area index (LAI), have direct impact on the seasonal pattern of ET, which provides a valuable reference to the wide-area estimates of ET for riparian forests by using LAI. In conclusion, P.euphratica forests have high water use after water conveyance, which may be the result of long-term adapting to local climates and limited water availability.     

Classifying natural-language spatial relation terms with random forest algorithm

The exponential growth of natural language text data in social media has contributed a rich data source for geographic information. However, incorporating such data source for GIS analysis faces tremendous challenges as existing GIS data tend to be geometry based while natural language text data tend to rely on natural language spatial relation (NLSR) terms. To alleviate this problem, one critical step is to translate geometric configurations into NLSR terms, but existing methods to date (e.g. mean value or decision tree algorithm) are insufficient to obtain a precise translation. This study addresses this issue by adopting the random forest (RF) algorithm to automatically learn a robust mapping model from a large number of samples and to evaluate the importance of each variable for each NLSR term. Because the semantic similarity of the collected terms reduces the classification accuracy, different grouping schemes of NLSR terms are used, with their influences on classification results being evaluated. The experiment results demonstrate that the learned model can accurately transform geometric configurations into NLSR terms, and that recognizing different groups of terms require different sets of variables. More importantly, the results of variable importance evaluation indicate that the importance of topology types determined by the 9-intersection model is weaker than metric variables in defining NLSR terms, which contrasts to the assertion of ‘topology matters, metric refines’ in existing studies.     

基于随机森林模型的珠江三角洲30 m格网人口空间化

人口空间化是实现人口统计数据与其他环境资源空间数据融合分析的有效途径。本文选取夜间灯光数据、道路网数据、水域分布数据、建成区数据、数字高程模型和地形坡度数据作为影响珠江三角洲人口分布的变量因子,利用随机森林模型对珠江三角洲2010年人口数据进行了30 m格网空间化,并将模拟结果与三个公开数据集作精度对比,最后基于随机森林模型的变量因子重要性分析珠江三角洲人口空间分布的影响因素。结果表明：本文模拟整体精度达到82.32%,均优于WorldPop数据集以及中国公里网格人口数据集,接近GPW数据集,而且在人口密度中等区域模拟精度最高;通过对变量因子重要性进行度量,发现夜间灯光强度是珠江三角洲人口分布的最重要指示性指标,到水域的距离、到建成区的距离和路网密度对珠江三角洲人口分布均具有重要作用。利用随机森林模型结合多源信息能够实现高空间分辨率的人口空间化,可为精细化城市管理提供重要数据源,也可为相关政策决策制定提供支持。     

Interdecadal variation of precipitation days in August in the Korean Peninsula

The present study examines a climate regime shift in the time series of the number of rainy days during August in the Korean Peninsula. The statistical change-point analysis indicates that a significant shift occurred in the time series around 1998, providing a rationale to divide it into two parts: 1975–1997 for the shorter rainy-day period and 1998–2012 for the longer rainy-day period. To examine the cause of recent rapid increases in the number of days with precipitation in August in the Korean Peninsula, differences in the averages of large-scale environments between the 1998–2012 period and the 1975–1997 period were analyzed.The differences in stream flows showed that anomalous cyclones were reinforced in the East Asian continent while anomalous anticyclones were reinforced in the western North Pacific at all layers of the troposphere. The anomalous anticyclones reinforced in the western North Pacific were associated with the western North Pacific subtropical high (WNPSH) developed a little more toward the Korean Peninsula recently. Consequently, the Korean Peninsula has been affected by anomalous south westerlies that supplied warm and humid airs from low tropical regions to the Korean Peninsula. The vertical thermal instability (warm anomaly at lower-level and cold anomaly at middle and upper-level) developed near the Korean Peninsula. In addition, upper tropospheric jets were reinforced further recently near the Korean Peninsula to provide good environments for development of upward flows. The frequency of TCs that affect the Korean Peninsula in August also increased rapidly since 1998.     

南北盘江森林生态系统水源涵养功能评价

森林生态系统水源涵养功能是植被层、枯枝落叶层和土壤层对降雨进行再分配的复杂过程。运用综合蓄水能力法,基于森林资源二类调查数据,估算了贵州省南北盘江流域不同类型森林生态系统的林冠层截留降水量、枯落物持水量和土壤蓄水量,分析了流域尺度森林生态系统的水源涵养能力及其时空变化。结果表明：① 南北盘江流域森林涵养水源总量约6.13×10⁸m³,单位面积水源涵养量629.85 t/hm²,森林水源涵养能力空间分布呈现东高西低的趋势;② 不同类型森林来说,阔叶林和灌木林对区域水源涵养总量的贡献率最大,而混交林的单位面积水源涵养量最高;③ 不同林龄比较,幼龄林对区域水源涵养贡献率最高,达45.95%,但其单位面积水源涵养能力最差,过熟林的单位面积水源涵养能力最高;④ 就坡位而言,平地和中坡森林对区域水源涵养总量的贡献率最大,山谷森林单位面积水源涵养能力最高,山脊森林单位面积涵养水源能力最低;⑤ 近35 a来,随着生态工程的实施,森林生态系统水源涵养总能力以1 447.89×10⁴m³/a速度持续提升,单位面积水源涵养量以每年5.33 t/hm²的速度稳步提高。     

基于影响因子动态更新的都市圈国土-人口协同模拟

都市圈作为典型的复杂巨系统,其国土、人口、交通等要素呈现出共同演化、协同发展的特征。现有基于元胞自动机的空间模拟方法通常分别进行国土或人口模拟,忽略了国土、人口之间的协同演化,从而限制了模拟性能。本文提出一种影响因子动态更新策略用以表征国土、人口两种要素间的相互作用,拓展经典元胞自动机模型构建协同模拟算法,实现了都市圈国土与人口空间分布态势的精准模拟。本文以深莞惠都市圈为例,对提出算法进行了实验验证。实验结果表明,本文提出协同模拟算法在深莞惠都市圈的国土模拟品质因素为0.274、人口模拟平均绝对百分比误差23.55%,分别优于传统基于随机森林的元胞自动机算法0.24和29.33%;相较于传统模型,在国土模拟中本模型在对于建设用地的模拟准确度提升了约3%,在人口模拟中本模型在对人口高密度的区域模拟误差降低了约6%。本文进一步预测了深莞惠都市圈2030年国土和人口发展空间态势。研究结果可为都市圈重大基础设施选址和发展情景推演提供技术支撑。     

Otolith Microstructure Analysis Reveals Different Growth Histories of Japanese Sardine (Sardinops melanostictus) in the Oyashio Waters

After decades of low year classes,the stock of Japanese sardine(Sardinops melanostictus)has begun to recover since the mid-2000s.The hatch dates and otolith growth rates of age-0 juvenile sardine,which were collected in the subarctic Oyashio waters in autumn 2018,were determined from an otolith microstructure analysis.The sardines were hatched from late January to late April,while mostly in February and March.The otolith growth rate increased continuously up to 60 d after hatching and thereafter de-creased.The revealed growth rate in a crucial growth period is faster than that reported for juvenile sardines collected in the 1990s,which is coincided with the recent recovery trend of the sardine stock.Two groups with different hatch dates,growth histories,and migration routes were identified using unsupervised random forest clustering analysis.They were considered inshore and offshore migration individuals in accordance with recent researches.In the offshore group,a high proportion of sardine juveniles hatched late and grew faster in the Kuroshio-Oyashio transitional waters,a finding consistent with the hypothesis of growth-rate-dependent re-cruitment.This finding on the population composition and growth rate of juvenile sardine in the Oyashio waters can be a basis for an improved prediction of their survival and provides us with valuable information on the recruitment processes of this stock during the period of stock recovery.