A comparison of growth patterns between non‐indigenous Halophila nipponica and the native sympatric Zostera marina on the southern coast of the Korean peninsula

The growth dynamics of two co‐occurring seagrass species, Zostera marina and Halophila nipponica, were examined on the southern coast of the Korean peninsula. Zostera marina is a native dominant seagrass species in Korean coastal waters, whereas H. nipponica is a non‐native tropical and subtropical species that has extended its distributional range to the temperate coastal areas of Korea. To examine the differences in the growth dynamics of H. nipponica and Z.  marina, their morphology, density, productivity and biomass, as well as local environmental conditions, were monitored monthly from January 2008 to July 2009. Underwater irradiance at the study site was the highest in April 2009 and the lowest in January 2008. Water temperature ranged from 10.4°C in January 2009 to 24.8°C in September 2008. Significant differences in growth dynamics were observed between the species, due to the effect of water temperature at the study site. Density and areal productivity were the highest in April 2008 and June 2008, respectively, for Z.  marina but the highest in July 2008 for H. nipponica. Leaf size, shoot height and shoot weight were the highest in July 2008 for Z.  marina but the highest in August 2008 or September 2008 for H. nipponica. The productivity of both species was strongly correlated with water temperature at the study site. However, the productivity of these species was not strongly correlated with underwater irradiance or the nutrient availability of either the water column or sediment pore water. Zostera marina exhibited the ecological characteristics of a temperate seagrass, whereas H. nipponica retained the features of a subtropical/tropical seagrass, even after adapting to the temperate coastal waters of Korea.     

Sensitivity of MM5 and WRF mesoscale model predictions of surface winds in a typhoon to planetary boundary layer parameterizations

Sea surface winds and coastal winds, which have a significant influence on the ocean environment, are very difficult to predict. Although most planetary boundary layer (PBL) parameterizations have demonstrated the capability to represent many meteorological phenomena, little attention has been paid to the precise prediction of winds at the lowest PBL level. In this study, the ability to simulate sea winds of two widely used mesoscale models, fifth-generation mesoscale model (MM5) and weather research and forecasting model (WRF), were compared. In addition, PBL sensitivity experiments were performed using Medium-Range Forecasts (MRF), Eta, Blackadar, Yonsei University (YSU), and Mellor–Yamada–Janjic (MYJ) during Typhoon Ewiniar in 2006 to investigate the optimal PBL parameterizations for predicting sea winds accurately. The horizontal distributions of winds were analyzed to discover the spatial features. The time-series analysis of wind speed from five sensitivity experimental cases was compared by correlation analysis with surface observations. For the verification of sea surface winds, QuikSCAT satellite 10-m daily mean wind data were used in root-mean-square error (RMSE) and bias error (BE) analysis. The MRF PBL using MM5 produced relatively smaller wind speeds, whereas YSU and MYJ using WRF produced relatively greater wind speeds. The hourly surface observations revealed increasingly strong winds after 0300 UTC, July 10, with most of the experiments reproducing observations reliably. YSU and MYJ using WRF showed the best agreements with observations. However, MRF using MM5 demonstrated underestimated winds. The conclusions from the correlation analysis and the RMSE and BE analysis were compatible with the above-mentioned results. However, some shortcomings were identified in the improvements of wind prediction. The data assimilation of topographical data and asynoptic observations along coast lines and satellite data in sparsely observed ocean areas should make it possible to improve the accuracy of sea surface wind predictions.     

Phylogenetic diversity of planktonic bacteria in the Chukchi Borderland region in summer

Planktonic bacteria are abundant in the Chukchi Borderland region. However, little is known about their diversity and the roles of various bacteria in the ocean. Seawater samples were collected from two stations K2S and K4S where sea ice was melting obviously. The analysis of water samples with fluorescence in situ hybridization (FISH) showed that DMSP-degrading bacteria accounted for 13% of the total bacteria at the station K2S. No aerobic anoxygenic phototrophic (AAP) bacteria were detected in both samples. The bacterial communities were characterized by two 16S rRNA gene clone libraries. Sequences fell into four major lineages of the domain Bacteria, including Proteobacteria (Alpha, Beta and Gamma subclasses), Bacteroidetes, Actinobacteria and Firmicutes. No significant difference was found between the two clone libraries. SAR11 and Rhodobacteraceae clades of Alphaproteobacteria and Pseudoalteromonas of Gammapro-teobacteria constituted three dominant fractions in the clone libraries. A total of 191 heterotrophic bacterial strains were isolated and 76% showed extracellular proteolytic activity. Phylogenetic analysis reveals that the isolates fell into Gammaproteobacteria, Bacteroidetes, Actinobacteria and Firmicutes. The most common genus in both the bacterial isolates and protease-producing bacteria was Pseudoalteromonas. UniFrac data showed suggestive differences in bacterial communities between the Chukchi Borderland and the northern Bering Sea.     

Nitrogen budget of the eelgrass, Zostera marina in a bay system on the south coast of Korea

Above- and below-ground productivities and tissue N content were measured monthly to quantify N incorporation to sustain eelgrass growth in Koje Bay on the south coast of Korea from January to December 2002. N acquisition was also estimated through measurements of N uptake kinetics, tissue biomass, and in situ inorganic N concentrations in water column and sediments. Above- and below-ground productivities were highest in summer and lowest in late fall and winter. Leaf tissue N content was highest in December and lowest in July, while rhizome tissue N content was highest in October and lowest in April. Estimated monthly N incorporation by leaf tissues based on the leaf productivity and N content ranged from 0.4 g N m^?2 month^?1 in November to 2.0 g N m^?2 month^?1 in May. N incorporation by below-ground tissues ranged from 0.1 g N m^?2 month^?1 in February to 0.2 g N m^?2 month^?1 in October. Annual whole plant N incorporation was 14.5 g N m^?2 y^?1, and N incorporation by leaf tissues accounted for about 87 % of total N incorporation. Maximum uptake rate (V _max ) and half saturation constant (K _m ) of leaf NH₄ ⁺ uptake were significantly lower than those of root NH₄ ⁺ uptake. Above- and below-ground biomass ranged from 20.8 g DW m^?2 and 8.6 g DW m^?2 in winter to 350.0 g DW m^?2 and 81.3 g DW m^?2 in spring, respectively. NH₄ ⁺ concentrations varied from 0.2 to 4.3 mM in water column and from 93.0 to 551.7 mM in sediment pore water. Based on these measurements, annual N acquisition by root tissues contributed slightly higher than that by leaf tissues to total plant N acquisition. During winter, monthly leaf N acquisition was lower than monthly leaf N incorporation. This implies that Z. marina has internal nitrogen retention system to offset the shortage and excess of nitrogen.     

Massive sedimentation of fine sediment with organic matter and enhanced benthic-pelagic coupling by an artificial dyke in semi-enclosed Chonsu Bay, Korea

To assess the impact of an artificial dyke in Chonsu Bay (CBD) on the organic carbon (C(org)) cycle, we measured excess (210)Pb activities, C(org) and nitrogen content in sediment cores. The C(org) oxidation rates (C(ox)) on the surface sediment and benthic nutrient fluxes were also quantified with an in situ benthic chamber. The higher excess (210)Pb inventory, C(org) and nitrogen in cores near the CBD indicated lateral transport and local, massive deposition of particulate matter due to tidal circulation altered by artificial dyke construction. The C(ox) in sediment near the CBD was about twice as high as that out of the bay, suggesting the importance of benthic remineralization of organic matter. The benthic fluxes of dissolved inorganic nitrogen and phosphate were four to six times higher than those outside the bay, corresponding to 141% and 131% respectively, of the requirements for primary production.     

Comparison of transfer functions in statistical downscaling models for daily temperature and precipitation over Canada

This study compares three linear models and one non-linear model, specifically multiple linear regression (MLR) with ordinary least squares (OLS) estimates, robust regression, ridge regression, and artificial neural networks (ANNs), to identify an appropriate transfer function in statistical downscaling (SD) models for the daily maximum and minimum temperatures (T_max and T_min) and daily precipitation occurrence and amounts (P_occ and P_amount). This comparison was made over twenty-five observation sites located in five different Canadian provinces (British Columbia, Saskatchewan, Manitoba, Ontario, and Québec). Reanalysis data were employed as atmospheric predictor variables of SD models. Predictors of linear transfer functions and ANN were selected by linear correlations coefficient and mutual information, respectively. For each downscaled case, annual and monthly models were developed and analysed. The monthly MLR, annual ANN, annual ANN, and annual MLR yielded the best performance for T_max, T_min, P_occ and P_amont according to the modified Akaike information criterion (AICu). A monthly MLR is recommended for the transfer functions of the four predictands because it can provide a better performance for the T_max and as good performance as the annual MLR for the T_min, P_occ, and P_amount. Furthermore, a monthly MLR can provide a slightly better performance than an annual MLR for extreme events. An annual MLR approach is also equivalently recommended for the transfer functions of the four predictands because it showed as good a performance as monthly MLR in spite of its mathematical simplicity. Robust and ridge regressions are not recommended because the data used in this study are not greatly affected by outlier data and multicollinearity problems. An annual ANN is recommended only for the T_min, based on the best performance among the models in terms of both the RMSE and AICu.     

Estimation of non-CO2 GHGs emissions by analyzing burn severity in the Samcheok fire, South Korea

This study was performed to estimate the emission of non-CO 2 greenhouse gases(GHGs) from biomass burning at a large fire area.The extended methodology adopted the IPCC Guidelines(2003) equation for use on data from the Samcheok forest fire gathered using 30 m resolution Landsat TM satellite imagery,digital forest type maps,and growing stock information per hectare by forest type in 1999.Normalized burn ratio(NBR) technique was employed to analyze the area and severity of the Samcheok forest fire that occurred in 2000.The differences between NBR from pre-and post-fire datasets are examined to determine the extent and degree of change detected from burning.The results of burn severity analysis by dNBR of the Samcheok forest fire area revealed that a total of 16,200 ha of forest were burned.The proportion of the area characterized by a ’Low’ burn severity(dNBR below 152) was 35%,with ’Moderate’(dNBR 153-190) and ’High’(dNBR 191-255) areas were at 33% and 32%,respectively.The combustion efficiency for burn severity was calculated as 0.43 for crown fire where burn severity was ’High’,as 0.40 for ’Moderate’ severity,and 0.15 for ’Low’ severity surface fire.The emission factors for estimating non-CO 2 GHGs were separately applied to CO 130,CH 4 9,NO x 0.7 and N 2 O 0.11.Non-CO 2 GHGs emissions from biomass burning in the Samcheok forest fire area were estimated to be CO 44.100,CH 4 3.053,NO x 0.238 and N 2 O 0.038 Gg.     

Temporal trend, spatial distribution, and terrestrial sources of PBDEs and PCBs in Masan Bay, Korea

Congener specific determination of polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) was carried out in 21 surface sediment samples and a sediment core from Masan Bay, Korea. Among the 40 PBDE congeners targeted only 29 were detectable. PBDE congener profile within sediments was dominated by BDE-209 followed by BDEs-99, -47, -153 and -183, sequentially. In surface sediments, the average ΣPBDEs levels approached that of average ΣPCBs values. However, trends observed in the sediment core suggest that this pattern will alter over time and result in higher surface sediment PBDE concentrations than PCBs in future. Various diffuse and point sources for PBDEs and PCBs were identified in this location. Shipping and other industrial activities were associated with PCB contamination while domestic and industrial waste discharges corresponded with PBDE contamination. The average concentration for PBDEs and PCBs in surface sediments were 5.7, 7.2 ng/g dry weight, respectively.     

决策树在遥感影像分类中的应用

在充分了解决策二叉树分类过程的基础上, 以西藏波密地区的TM遥感影像为研究对象, 提取并分析各种典型地物的反射光谱特征, 利用不同地物的光谱差异并结合人工目视判读建立了一组能够精确、快速划分遥感影像的分类规则。用ENVI建立分类决策树对实验区遥感影像进行分类, 并将分类结果和传统的最大似然法相比较。结果表明:决策树分类的总体精度和Kappa分别为97.15%和0.9644, 优于传统的最大似然法, 取得了较为满意的分类结果。