Long-term Trends and Temporal Heterogeneity of Water Quality in Tidally Mixed Estuarine Waters

Dynamics of water quality in the Keonggi Bay, a shallow macrotidal temperate estuary of Yellow Sea, Korea were identified using the major water quality parameters such as dissolved oxygen (DO), ammonia, nitrate, phosphate, and chemical oxygen demand (COD). The study area during the last 18 years was in eutrophic and mesotrophic water in terms of the nutrient eutrophication index even with a slight decrease in DIN and COD concentrations during recent years. Monthly values of nitrate and ammonia significantly correlated with SS and salinity, respectively, indicating that re-suspension of sediment by vertical mixing and freshwater input are critical factors of monthly fluctuation in water quality. The lack of significant autocorrelation in water quality parameters suggested a significant tidal effect on temporal water quality fluctuation in the tidally mixed estuarine system. Principal component analysis (PCA) revealed a clear pattern of long-term trends of water quality. The early 1980s were the periods of best water quality, with worst conditions during the late 1980s and early 1990s. These long-term trends of water quality were well discriminated by PCA which can be further applied for the whole ecosystem interpretation with biological variables.     

黑河下游荒漠河岸林典型样带植被空间异质性

应用地统计学的理论与方法,分析了黑河流域下游荒漠河岸林主要种群,即老林胡杨(Popu luseuphratica)、幼林胡杨、柽柳(Tamarix chinensis)和苦豆子(Sophora alopecuroides)的空间异质性程度、异质性组成及尺度依赖问题.结果表明:黑河下游荒漠河岸林种群斑块格局明显,斑块内部异质性较小,斑块之间异质性增强,出现空间异质性变化较大的尺度为430m.而斑块内部因不同种群而变化,苦豆子和柽柳具有较大的空间异质性尺度,分别为43m和55m.老林和幼林胡杨种群的空间异质性尺度(8m和13m)较小,但异质性存在多尺度变化.采用30m分辨率的遥感数据能够较好地分析种群斑块格局,但是对种群内的空间异质性分析需要更高的分辨率.     

Triple oxygen isotope constraints on the origin of ocean island basalts

Understanding the origin of ocean island basalts(OIB) has important bearings on Earth's deep mantle.Although it is widely accepted that subducted oceanic crust, as a consequence of plate tectonics, contributes material to OIB's formation, its exact fraction in OIB's mantle source remains ambiguous largely due to uncertainties associated with existing geochemical proxies. Here we show, through theoretical calculation, that unlike many known proxies, triple oxygen isotope compositions(i.e.D^(17 )O) in olivine samples are not affected by crystallization and partial melting. This unique feature, therefore, allows olivine D^(17 )O values to identify subducted oceanic crusts in OIB's mantle source. Furthermore, the fractions of subducted ocean sediments and hydrothermally altered oceanic crust in OIB's mantle source can be quantified using their characteristic D^(17 )O values. Based on published D^(17 )O data, we estimated the fraction of subducted oceanic crust to be as high as 22.3% in certain OIB, but the affected region in the respective mantle plume is likely to be limited.     

时空统计学在贫困研究中的应用及展望

消除贫困是人类社会的共同目标.贫困分布具有明显的空间特征,同时呈现出空间异质性和空间相关性.时空统计学以时空分析为优势,在贫困的时空分布及形成机制研究中发挥了重要作用.本文综述了不同时期我国贫困分布的空间特征、贫困数据的空间类型和特征以及贫困时空分布的影响因素,并总结了时空统计学方法在贫困空间研究中的4类应用,包括:探...     

古尔班通古特沙漠南缘干季土壤水分含量空间异质性

土壤水分含量是荒漠植被发育的主要制约因子。对古尔班通古特沙漠南缘个体、群落、丘间地0~100 cm干季土壤水分含量的空间异质性进行分析。结果表明：（1）同尺度下,土壤水分含量随土层深度增加呈显著升高趋势,且表层土壤水分含量的变异系数高于其他土层。（2）个体尺度,梭梭树干基部周围土壤水分含量在垂直和水平方向存在格局分异。垂直方向,土壤水分含量随土层深度增加呈升高趋势。水平方向,随距树干基部距离增加,坡顶土壤水分含量呈升高趋势,坡中和坡底土壤水分含量呈降低趋势,但没有显著差异。（3）梭梭群落尺度上土壤水分含量异质性较强,且呈斑块状分布。（4）地形是影响丘间地尺度土壤水分含量空间分异的主要因素,形成坡底土壤水分含量最高、坡中次之、坡顶最低的空间分布格局。     

基于断层运动和应力演化分析断层强震危险程度的研究进展

震间断层强震危险性研究是地震中长期预测中的基础科学问题, 其中断层运动及应力演化的研究对认识地震的孕育发生、 破裂过程具有重要意义, 为地震危险性分析提供科学依据。 本文首先回顾了震间断层运动模型的理论研究进展; 其次, 简略地回顾了断层不均匀性和断层摩擦定律的研究历程, 论述了确定摩擦参数、 圈定凹凸体的发展趋势与研究动态, 并阐述了基于断层不均匀性和断层摩擦定律的强震过程数值模拟的应用; 最后, 论述了基于断层运动和应力演化分析断层中长期强震危险程度的应用, 并叙述了与地震短期、 临震预测密切相关的断层运动成核过程。     

Physical disturbance and subtidal habitat structure on open rocky coasts: Effects of wave exposure, extent and intensity

Canopy-forming algae occur across of range of energy environments (i.e., wave sheltered to exposed coasts) where disturbances are frequent (i.e., gap formation) and benthic patterns largely reflect variation in post-disturbance processes. Disturbances vary in extent (area affected) and intensity (degree of damage), and this may affect recolonisation at local scales. On an open oceanic coast, we tested whether habitat structure (patches of canopy algae) differed between heavy and relatively lighter wave exposure (sheltered vs. exposed sides of islands), and whether wave exposure affected the response of prominent habitat-formers to varying disturbance regimes (different sizes of partial and complete canopy removal). Observations of naturally occurring patterns showed sheltered coasts to be characterised by small patches of fucoids, whereas exposed coasts were characterised by large patches of kelp. Canopy-gaps were larger at exposed than sheltered coasts, and mixed canopies constituted > 24% of the subtidal rocky habitat independently of wave exposure. Experimental disturbances showed the local density of kelps to affect recovery through greater recruitment to partial clearings (80% canopy removal). Fucalean algae, on the other hand, mainly recruited into complete clearings (100% removal), but when their recruits were abundant, they also recruited into partial clearings. The covers of filamentous, turf-forming algae increased in all clearings, and more so at exposed than sheltered sites. Extent of disturbance had no detectable effect on recolonisation by canopy-forming algae across the scales examined (i.e., 1.5 m, 3 m diameter loss of canopy). Recolonisation varied among islands kilometres apart, and correlations (r > 0.85) between cover of canopies and cover of their recruits in clearings at the scale of sites, suggested that differences in propagule supply could account for variation in patterns of recolonisation at scales of kilometres. There was no evidence to suggest that the effect of disturbance depended on wave exposure within the range of exposures tested in this study (i.e. open coasts). We recognise that wave exposure can be fundamental to habitat structure of subtidal rocky coasts, but we suggest that its influence may be mediated by the biological setting (e.g., canopy composition).     

Leaf to canopy upscaling approach affects the estimation of canopy traits

In remote sensing applications, leaf traits are often upscaled to canopy level using sunlit leaf samples collected from the upper canopy. The implicit assumption is that the top of canopy foliage material dominates canopy reflectance and the variability in leaf traits across the canopy is very small. However, the effect of different approaches of upscaling leaf traits to canopy level on model performance and estimation accuracy remains poorly understood. This is especially important in short or sparse canopies where foliage material from the lower canopy potentially contributes to the canopy reflectance. The principal aim of this study is to examine the effect of different approaches when upscaling leaf traits to canopy level on model performance and estimation accuracy using spectral measurements (in-situ canopy hyperspectral and simulated Sentinel-2 data) in short woody vegetation. To achieve this, we measured foliar nitrogen (N), leaf mass per area (LMA), foliar chlorophyll and carbon together with leaf area index (LAI) at three vertical canopy layers (lower, middle and upper) along the plant stem in a controlled laboratory environment. We then upscaled the leaf traits to canopy level by multiplying leaf traits by LAI based on different combinations of the three canopy layers. Concurrently, in-situ canopy reflectance was measured using an ASD FieldSpec-3 Pro FR spectrometer, and the canopy traits were related to in-situ spectral measurements using partial least square regression (PLSR). The PLSR models were cross-validated based on repeated k-fold, and the normalized root mean square errors (nRMSE_cv) obtained from each upscaling approach were compared using one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. Results of the study showed that leaf-to-canopy upscaling approaches that consider the contribution of leaf traits from the exposed upper canopy layer together with the shaded middle canopy layer yield significantly (p < 0.05) lower error (nRMSE_cv < 0.2 for canopy N, LMA and carbon) as well as high explained variance (R² > 0.71) for both in-situ hyperspectral and simulated Sentinel-2 data. The widely-used upscaling approach that considers only leaf traits from the upper illuminated canopy layer yielded a relatively high error (nRMSE_cv>0.2) and lower explained variance (R² < 0.71) for canopy N, LMA and carbon. In contrast, canopy chlorophyll upscaled based on leaf samples collected from the upper canopy and total canopy LAI exhibited a more accurate relationship with spectral measurements compared with other upscaling approaches. Results of this study demonstrate that leaf to canopy upscaling approaches have a profound effect on canopy traits estimation for both in-situ hyperspectral measurements and simulated Sentinel-2 data in short woody vegetation. These findings have implications for field sampling protocols of leaf traits measurement as well as upscaling leaf traits to canopy level especially in short and less foliated vegetation where leaves from the lower canopy contribute to the canopy reflectance.