Assessing benthic health under multiple human pressures in Bohai Bay (China), using density and biomass in calculating AMBI and M‐AMBI

In recent decades, China has undergone an impressive development, which has produced increasing human pressures including coastal degradation. Bohai Bay, located in the west of the Bohai Sea (north of China), has been affected by various human pressures, including waste water discharges, land reclamation and oil exploitation. To monitor the effects of these pressures on this ecosystem, benthic macroinvertebrates and environmental variables (dissolved oxygen, nutrients, metals, etc.) were sampled in 2009 and 2011. To assess the ecological status of the benthic communities, the AZTI Marine Biotic Index (AMBI) and multivariate‐AMBI (M‐AMBI) were used, including both density and biomass in the calculation. This is the first research in which M‐AMBI based on biomass (M‐bAMBI) is applied. Both methods showed that the nearshore areas, especially close to the Haihe and Jiyun estuaries, were affected by human pressures, with a clear gradient of decreasing impacts offshore. The ecological status as assessed using density and biomass was quite similar. Significant relationships were also found between both methods and environmental variables. The use of AMBI and M‐AMBI, based upon density and biomass, in assessing the ecological status of water bodies in China seems to be promising.     

Impact of the central Pacific zonal wind divergence and convergence on the central Pacific El Nio event

The central Pacific(CP) zonal wind divergence and convergence indices are defined, and the forming mechanism of CP El Nio(La Nia) events is discussed preliminarily. The results show that the divergence and convergence of the zonal wind anomaly(ZWA) are the key process in the forming of CP El Nio(La Nia) events. A correlation analysis between the central Pacific zonal wind divergence and convergence indices and central Pacific El Nio indices indicates that there is a remarkable lag correlation between them. The central Pacific zonal wind divergence and convergence indices can be used to predict the CP events. Based on these results, a linear regression equation is obtained to predict the CP El Nio(La Nia) events 5 months ahead.     

连续降温对大菱鲆成鱼代谢机能的影响

为了探寻连续降温对大菱鲆成鱼血清、肝脏及肌肉能量代谢等指标的影响,将大菱鲆从正常养殖水温18℃快速连续降温至1℃,并在18℃、13℃、8℃、5℃、3℃和1℃共计6个温度点取血采样,分别测定血清中的总蛋白(TP)、白蛋白(ALB)、高密度脂蛋白胆固醇(HDL-C)、低密度脂蛋白胆固醇(LDL-C)、甘油三酯(TG)、总胆固醇(TC)、总胆红素(TBIL)、血糖(GLU)以及肝脏中的糖原和肌肉中的乳酸等指标,实验数据采用SPSS 17.0统计软件进行单因素方差分析。结果发现,随着温度降低,大菱鲆的血清TP浓度呈先下降后升高的趋势,且在13℃和3℃时出现显著性差异(P<0.05);血清ALB浓度则呈现升高趋势,在3℃时显著高于1℃(P<0.05);血清TC浓度呈现升高趋势,且3℃时显著高于18℃(P<0.05); GLU浓度呈先降低后升高趋势,且8℃时显著高于13℃(P<0.05);尿素浓度呈先降低后升高再降低趋势,且8℃时显著高于1℃(P<0.05);肝糖原浓度在各温度之间无显著差异(P>0.05);肌肉中乳酸含量呈先升高后降低趋势,且5℃时显著高于18℃(P<0.05);其余指标则无显著性差异(P>0.05)。结果表明：当温度在18℃～8℃时,降温对大菱鲆体内代谢影响不大;当温度降到8℃～3℃时,大菱鲆体内开始出现应激反应;当温度继续降低至1℃时,大菱鲆体内的各种代谢基本处于停滞状态。     

Climatic Indices Influencing the Long-Term Variability of Mediterranean Heat and Water Fluxes: The North Atlantic and Mediterranean Oscillations

Interannual to interdecadal precipitation (P), evaporation (E), water deficit (E-P), and total heat flux have been correlated with North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) indices to explore the influence of large-scale atmospheric forcing on the variability of the Mediterranean water and heat budgets. Basin-averaged precipitation decrease from the mid-1960s to the late 1980s clearly corresponds to a switch from a low to a high state of both indices. The variability of E-P is not so well correlated with the atmospheric indices because of the different sensitivity of E and P that leads to correlations of opposite sign in the eastern and western sub-basins. The effectiveness of the NAO and MO indices is quite similar for P and E-P but the regional MO index has turned out to be a more successful indicator of interdecadal evaporation and net heat flux because, from the mid-1970s to the early 1990s, correlation with the NAO index decreases considerably. Because the MO centre remains relatively steady, it influences most of the Mediterranean Sea year round, so it is more suitable for monitoring long-term water and especially heat budget variability.     

浅谈如何提高地面气象观测质量综合指数

通过对在综合气象业务改革的地面气象观测质量的考核内容的分析。提出出了台站提高地面气象观测质量综合指数的方法,为台站提高地面气象观测质量提供参考。     

Quantile Trends in Temperature Extremes in China

A number of recent studies have examined trends in extreme temperature indices using a linear regression model based on ordinary least-squares. In this study, quantile regression was, for the first time, applied to examine the trends not only in the mean but also in all parts of the distribution of several extreme temperature indices in China for the period 1960-2008. For China as a whole, the slopes in almost all the quantiles of the distribution showed a notable increase in the numbers of warm days and warm nights, and a significant decrease in the number of cool nights. These changes became much fas- ter as the quantile increased. However, although the number of cool days exhibited a significant decrease in the mean trend estimated by classical linear regression, there was no obvious trend in the upper and lower quantiles. This finding suggests that examining the trends in different parts of the distribution of the time-series is of great importance. The spatial distribution of the trend in the 90th quantile indicated that there was a pronounced increase in the numbers of warm days and warm nights, and a decrease in the number of cool nights for most of China, but especially in the northern and western parts of China, while there was no significant change for the number of cool days at almost all the stations.     

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R² = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.     

A visible band index for remote sensing leaf chlorophyll content at the canopy scale

Leaf chlorophyll content is an important variable for agricultural remote sensing because of its close relationship to leaf nitrogen content. The triangular greenness index (TGI) was developed based on the area of a triangle surrounding the spectral features of chlorophyll with points at (670 nm, R₆₇₀), (550 nm, R₅₅₀), and (480 nm, R₄₈₀), where R_λ is the spectral reflectance at wavelengths of 670, 550 and 480, respectively. The equation is TGI = −0.5[(670 − 480)(R₆₇₀ − R₅₅₀) − (670 − 550)(R₆₇₀ − R₄₈₀)]. In 1999, investigators funded by NASA's Earth Observations Commercialization and Applications Program collaborated on a nitrogen fertilization experiment with irrigated maize in Nebraska. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and Landsat 5 Thematic Mapper (TM) data were acquired along with leaf chlorophyll meter and other data on three dates in July during late vegetative growth and early reproductive growth. TGI was consistently correlated with plot-averaged chlorophyll-meter values at the spectral resolutions of AVIRIS, Landsat TM, and digital cameras. Simulations using the Scattering by Arbitrarily Inclined Leaves (SAIL) canopy model indicate an interaction among TGI, leaf area index (LAI) and soil type at low crop LAI, whereas at high LAI and canopy closure, TGI was only affected by leaf chlorophyll content. Therefore, TGI may be the best spectral index to detect crop nitrogen requirements with low-cost digital cameras mounted on low-altitude airborne platforms.     

GIS approach to scale issues of perimeter-based shape indices for drainage basins

Abstract

Shape indices have been in use for several decades to describe the characteristics and hydrological properties of drainage basins. Due to the fractal behaviour of the basin boundary, perimeter-based shape indices depend on the scale at which they are determined. Therefore, these indices cannot objectively compare drainage basins across a range of scales and basin sizes. This paper presents an objective GIS-based methodology for determining scale-dependent shape indices from gridded drainage basin representations. The scale effect is addressed by defining a representative scale at which the indices should be determined, based on a threshold symmetric difference between two grids representing the drainage basin at different resolutions.