Spatial distribution of soil organic carbon and its influencing factors at different soil depths in a semiarid region of China

Studying spatial variability of soil organic carbon (SOC) is crucial for understanding the largest active carbon pool in terrestrial ecosystems. The main objectives ofves of this study were (1) to analyze the spatial pattern of SOC at different depths and (2) to define the soil properties affecting the spatial patterns of SOC at different depths. A total of 910 soil samples were collected at different locations and soil layers in a semiarid zone (3800 km²) of northeastern China. A geostatistical approach was used to predict and map SOC at different depths while the soil properties affecting the spatial patterns of SOC were analyzed by using canonical correspondence analysis. As expected, SOC content decreased gradually with depth and such a SOC decrease depended on soil type, which resulted the main factor affecting horizontal and vertical distributions of SOC content. Slope and bulk density exhibited a negative correlation with SOC content, whereas vegetation index, soil moisture content, elevation, and aspect showed a positive correlation. Sensitivity of SOC to influencing factors differed with increasing soil depth. SOC was significantly correlated with vegetation and bulk density on topsoil, while soil moisture and aspect played an important role in controlling SOC with increasing depth.     

Digital soil mapping in a Himalayan watershed using remote sensing and terrain parameters employing artificial neural network model

Digital soil mapping relies on field observations, laboratory measurements and remote sensing data, integrated with quantitative methods to map spatial patterns of soil properties. The study was undertaken in a hilly watershed in the Indian Himalayan region of Mandi district, Himachal Pradesh for mapping soil nutrients by employing artificial neural network (ANN), a potent data mining technique. Soil samples collected from the surface layer (0–15 cm) of 75 locations in the watershed, through grid sampling approach during the fallow period of November 2015, were preprocessed and analysed for various soil nutrients like soil organic carbon (SOC), nitrogen (N) and phosphorus (P). Spectral indices like Colouration Index, Brightness Index, Hue Index and Redness Index derived from Landsat 8 satellite data and terrain parameters such as Terrain Wetness Index, Stream Power Index and slope using CartoDEM (30 m) were used. Spectral and terrain indices sensitive to different nutrients were identified using correlation analysis and thereafter used for predictive modelling of nutrients using ANN technique by employing feed-forward neural network with backpropagation network architecture and Levenberg–Marquardt training algorithm. The prediction of SOC was obtained with an R² of 0.83 and mean squared error (MSE) of 0.05, whereas for available nitrogen, it was achieved with an R² value of 0.62 and MSE of 0.0006. The prediction accuracy for phosphorus was low, since the phosphorus content in the area was far below the normal P values of typical Indian soils and thus the R² value observed was only 0.511. The attempts to develop prediction models for available potassium (K) and clay (%) failed to give satisfactory results. The developed models were validated using independent data sets and used for mapping the spatial distribution of SOC and N in the watershed.     

Prediction of spatial soil organic carbon distribution using Sentinel-2A and field inventory data in Sariska Tiger Reserve

Dynamic and vigorous top soil is the source for healthy flora, fauna, and humans, and soil organic matters are the underpinning for healthy and productive soils. Organic components in the soil play significant role in stimulating soil productivity processes and vegetation development. This article deals with the scientific demand for estimating soil organic carbon (SOC) in forest using geospatial techniques. We assessed distribution of SOC using field and satellite data in Sariska Tiger Reserve located in the Aravalli Hill Range, India. This study utilized the visible and near-infrared reflectance data of Sentinel-2A satellite. Three predictor variables namely Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, and Renormalized Difference Vegetation Index were derived to examine the relationship between soil and SOC and to identify the biophysical characteristic of soil. Relationship between SOC (ground and predicted) and leaf area index (LAI) measured through satellite data was examined through regression analysis. Coefficient of correlation (R ²) was found to be 0.95 (p value < 0.05) for predicted SOC and satellite measured LAI. Thus, LAI can effectively be used for extracting SOC using remote sensing data. Soil organic carbon stock map generated through Kriging model for Landsat 8 OLI data demonstrated variation in spatial SOC stocks distribution. The model with 89% accuracy has proved to be an effective tool for predicting spatial distribution of SOC stocks in the study area. Thus, optical remote sensing data have immense potential for predicting SOC at larger scale.     

Assessment of bioclimatic comfort conditions based on Physiologically Equivalent Temperature (PET) using the RayMan Model in Iran

In this study thermal comfort conditions are analyzed to determine possible thermal perceptions during different months in Iran through the Physiologically Equivalent Temperature (PET). The monthly PET values produced using the RayMan Model ranged from ?7.6°C to 46.8°C. Over the winter months the thermal comfort condition (18–23°C) were concentrated in southern coastal areas along the Persian Gulf and Oman Sea. Most of the country experienced comfort conditions during the spring months, in particular in April, while during the summer months of July and August no thermal comfort conditions were observed. In November coastal areas of the Caspian Sea had the same physiological stress level of thermal comfort as April. The map produced showing mean annual PET conditions demonstrated the greatest spatial distribution of comfortable levels in the elevation range from 1000 to 2000 meter a.s.l., with annual temperatures of 12–20°C and annual precipitation of under 200 mm. The statistical relationship between PET conditions and each controlling parameter revealed a significant correlation in areas above 2000 meter, annual temperature over 20°C and annual precipitation of 200–400 mm with a correlation coefficient (R ²) of 0.91, 0.97 and 0.96, respectively.     

Elemental distribution of coastal sea and stream sediments in the island-arc region of Japan and mass transfer processes from terrestrial to marine environments

A total of 49 elements have been identified in 338 coastal sea sediment samples collected from an area situated off the Ise-Tokai region of Japan for a nationwide marine geochemical mapping project. The spatial distribution patterns of the elemental concentrations in coastal seas along with the existing geochemical maps in terrestrial areas were used to define the natural geochemical background variation, mass transport, and contamination processes. The elemental concentrations of coastal sea sediments are determined primarily by particle size and regional differences. Most elemental concentrations increase with a decrease in particle size. Some elements such as Ca, Mn, and Yb are found to exist in large quantities in coarse particles containing calcareous shells, Fe–Mn oxides, and felsic volcanic sediments. Regional differences reflect the mass transfer process from terrestrial areas to coastal seas and the influence of the local marine geology. An analysis of variance (ANOVA) reveals that for many elements, the particle size effect is predominant over regional difference. The mean chemical compositions of coastal sea sediments are similar to those of stream sediments in adjacent terrestrial areas and in the upper crust of Japan. This observation supports the fact that coastal sea sediments have certainly originated from terrestrial materials. However, the spatial distributions of elemental concentrations are not always continuous between the land and coastal seas. The scale of mass movement observed in marine geochemical maps occurs at a distance of 20 km from the river mouth. A detailed examination of the spatial distribution patterns of K (K₂O) and Cr concentrations suggests that terrestrial materials supplied through rivers are deposited near the shore initially, and then gravity-driven processes shift the sediments deeper into the basin. Contamination with heavy metals such as Zn, Cd and Pb was observed in coastal bays surrounded by urban and industrial areas. It is noteworthy that the areas with the highest concentration of these elements usually do not occur near the shore (not near the contamination source) but at the center of the bay. Unexpected low concentrations of Zn, Cd and Pb near shore may either be due to a decreased anthropogenic load in the most recent sediments or to dilution by unpolluted flood sediments.     

喀斯特石漠化治理措施对土壤颗粒有机碳与团聚体有机碳的影响

文章以耕地为对照,分析不同石漠化治理措施（花椒林和次生林）对土壤0~20 cm土层有机碳(SOC)、颗粒有机碳(POC)、矿物结合有机碳(MOC)和团聚体有机碳的影响,探讨POC、MOC与SOC、团聚体有机碳的关系。结果表明:与耕地相比,花椒林和次生林均不同程度提高SOC、POC、MOC和团聚体有机碳含量。0~10 cm土层次生林SOC含量和各粒径团聚体有机碳含量均显著高于耕地和花椒林,在10~20 cm土层无显著差异;0~20 cm土层花椒林和次生林土壤POC含量显著高于耕地,MOC无显著差异。POC/SOC范围为20.38%~45.27%,花椒林和次生林显著高于耕地。相反,MOC/SOC为耕地显著高于花椒林和次生林 。退耕为花椒林和次生林后,SOC含量的增加主要以POC含量增加为主。次生林和花椒林>2 mm粒径对SOC贡献率显著高于耕地,但0.25~2 mm粒径、0.053~0.25 mm粒径和 < 0.053 mm粒径对SOC贡献率显著低于耕地。其相关分析表明:POC、MOC与SOC、团聚体有机碳的关系均呈正相关,表现为次生林 > 花椒林 > 耕地。退耕恢复为花椒林和次生林后,SOC、POC和MOC增加量与团聚体有机碳增加量显著相关,其以次生林的相关性较强。石漠化治理措施改变SOC物理组分及其组成以及它们之间的关系,从而促进有机碳的积累。      

Distribution of biochemical constituents in the surface sediments of western coastal Bay of Bengal: influence of river discharge and water column properties

Biochemical composition of surface sediment samples from off major and minor rivers along the east coast of India revealed that spatial distribution of sediment organic carbon (SOC) composition was mainly governed by differential characteristics of discharged water and associated biogeochemical processes in the water column. The northwest (NW) region of coastal Bay of Bengal was influenced by discharges from Ganges river while peninsular (monsoonal) rivers influenced the southwest (SW) region. The NW region characterized by low nutrients suspended particulate matter (SPM), high phytoplankton biomass in the water column and high SOC while contrasting to that observed in the SW region. The isotopic ratios of SOC (?22 ‰) in the NW region were close to that of organic matter derived from phytoplankton (?23 ‰) suggesting in situ production is the major source whereas terrigeneous source contributed significantly in the SW region (?19.6 ‰). Though low in situ biological production in the SW region, relatively higher total carbohydrates (TCHO) were found than in the NW and insignificant difference of total and free amino acid concentrations between NW and SW were resulted from faster removal of organic matter to the sediment in association with SPM in the SW region. Higher proteins concentrations than total amino acids indicate that nitrogenous organic matter is preserved in the former form. The protein to TCHO ratio was lower in the SW suggesting significant contribution of aged and non-living organic matter in this region.     

Heavy metal concentrations in sediments and in mussels from Argentinean coastal environments,South America

Among environmental contaminants, heavy metals are currently considered to be some of the most toxic ones present worldwide due to their harmful effects on organisms and ability to bioaccumulate in aquatic systems. In this work, the concentration of heavy metals (Cd, Cu, Pb, Zn, Ni and Cr) in Brachidontes rodriguezii and in the fine sediments of several coastal sites at the southwest of Buenos Aires Province, Argentina is analyzed. The Bahía Blanca Estuary and Pehuen-Có beach are located in a highly complex oceanographic and ecological regional system, which creates the basis of one of the most valuable Argentinean habitats for fishing commercial species. An assessment, which involved analyzing distribution pattern of trace metals, comparative studies with sediment and ecological quality guidelines; and a sequential and integrated index analyses approach (containing Metal Pollution Index, Biosediment Accumulation Factor, Geo-accumulation Index (Igeo), Pollution Load Index and the mean Probable Effect Level quotients), was followed to estimate enrichment and risks of heavy metals in the sediments and in the mussels from these study areas. The results showed higher concentrations of some heavy metals (e.g., Cd, Cr and Ni) in mussels collected at Pehuen-Có, while no spatial differences in sediments were observed. According to the international environmental regulations, mean values of trace metals in mussels allowed to place both sites between “unpolluted and moderately polluted” and between the “low and medium category” of pollution. Furthermore, the mean concentrations found were within the detected ranges in other coastal sites worldwide.     

I–P<Subscript>2</Subscript>O<Subscript>5</Subscript> diagrams as an indicator of depositional environment in marine sediments: preliminary findings (Sri Lanka)

The concentrations of Br and I in marine sediments have been used to categorize the sedimentary environments of different coastal regions of the world with respect to organic matter contents. The present study uses the concentrations of Br, I and P₂O₅ of different marine settings as a new proxy to interpret the depositional environments. A total of 150 coastal lagoon sediment samples (suspended sediments, surface sediments and sediment cores) were analyzed for Br, I and P₂O₅ concentrations by X-ray fluorescence spectrometry. They were compared with the Br, I and P₂O₅ concentrations of the 2004 Indian Ocean tsunami sediments. Sediments from various sources are separately clustered in I–Br plot and a trivial negative correlation is found for the whole plot. A similar correlation pattern exists in the I–P₂O₅ diagram. This correlation is explained by the distribution of marine plants (higher and lower) in different sedimentary environments of the coastal profile. Therefore, the concentration of I and its relation to P₂O₅ can be used as a tool to identify sediment depositional environments in marine settings.     

Polycyclic aromatic hydrocarbons (PAHs) in particle-size fractions of urban topsoils

Polycyclic aromatic hydrocarbons’ (PAHs) concentrations in bulk samples are commonly used to assess contamination but PAHs are unevenly distributed among particle-size fractions. Seventeen urban surface soil samples from the city of Xuzhou, China, were collected and then fractionated into five size fractions (2,000–300, 300–150, 150–75, 75–28, and <28 μm). The concentrations of 12 US EPA PAHs were measured using gas chromatograph/mass spectrometry in various fractions, and the bulk soil samples and distribution patterns of PAHs in different particle-size fractions were investigated. The mean concentration of total PAHs in bulk soil samples was 1,879 ng/g. The median concentrations for all individual PAH were higher for the 75–2,000 μm fraction than for the <75 μm fraction. The distribution factors for various PAHs in <28 μm soil fraction were closely correlated (r = ?0.661, p < 0.019) to bulk soil fugacity capacity. The values of PAH isomer indicated that traffic emissions might be the major origin of PAHs in Xuzhou surface soils. Spearman correlation analysis was performed and the result suggested that soil organic carbon might be a factor controlling the concentrations of PAHs in soils.     

Spatial prediction of soil water content in karst area using prime terrain variables as auxiliary cokriging variable

In karst areas, accurately measuring and managing the spatial variability of soil water content (SWC) is very critical in settling numerous issues such as karst rocky desertification, ecosystem reconstruction, etc. In these areas, SWC exhibits strong spatial dependence, and it is a time and labor consuming procedure to measure its spatial variability. Therefore, estimation of this kind of soil property at an acceptable level of accuracy is of great significance. This study was conducted to evaluate and compare the spatial estimation of SWC by using ordinary kriging (OK) and cokriging (COK) methods with prime terrain variables, tending to predict SWC using limited available sample data for a 2,363.7 km² study area in Mashan County, Guangxi Zhuang Autonomous Region, Southwest China. The measured SWC ranged from 3.36 to 26.69 %, with a mean of 17.34 %. The correlation analysis between SWC and prime terrain variables indicated that SWC showed significantly positive correlation with elevation (r is 0.46, P < 0.01), and significantly negative correlation with slope (r is ?0.30, P < 0.01); however, SWC was not significantly correlated with aspect in the study area. Therefore, elevation and slope were used as auxiliary data together for SWC prediction using COK method, and mean error (ME) and root mean square error were adopted to validate the prediction of SWC by these methods. Results indicated that COK with prime terrain variables data was superior to OK with relative improvement of 28.52 % in the case of limited available data, and also revealed that such elevation and slope data have the potential to improve the precision and reliability of SWC prediction as useful auxiliary variables.     

Factors controlling regional spatial distribution of 53 elements in coastal sea sediments in northern Japan: Comparison of geochemical data derived from stream and marine sediments

In all, 53 elements were analyzed in 1406 coastal sea sediment samples collected from an area off Hokkaido and the Tohoku region of Japan during a nationwide marine geochemical mapping project. The spatial distribution patterns of the elemental concentrations in coastal seas along with the existing geochemical maps in terrestrial areas were used to define natural geochemical background variation and mass transport processes. The terrestrial area is covered by mafic volcanic rocks and accretionary complexes associated with ophiolite, which has small amounts of felsic volcanic rocks and granite. The spatial distribution patterns of elements enriched in mafic lithologies such as Fe (Total Fe₂O₃) and Sc in marine environments are influenced by adjoining terrestrial materials. The spatial distribution patterns of Cr and Ni concentrations, which are highly abundant in ultramafic rocks on land, are used to evaluate the mass transport from land to the sea and the dispersive processes caused by oceanic currents. The scale of mass transport by oceanic currents occurs up to a distance of 100–200 km from the coast along the coastal areas. The regional differences of elements rich in felsic lithologies such as K (K₂O), Nb and La in marine sediments are determined mainly by the relative proportion of minerals and lithic fragments enriching felsic materials to those associated with mafic materials. The spatial distribution of elemental concentration is not always continuous between the land areas and coastal sea areas. That difference is interpreted as resulting from (1) transportation of marine sediments by oceanic currents and storm waves, (2) contribution of volcanic materials such as tephra, (3) occurrence of shell fragments and foraminifera tests and (4) distribution of relict sediments of the last glacial age and early transgression age. Contamination with Cu, Zn, Cd, As, Mo, Sn, Sb, Hg, Pb and Bi was not observed in marine environments because the study area has little anthropogenic activity. Terrestrial materials are the dominant source for these metals. The Mo, Cd, Sn, Sb, Hg, Pb and Bi are abundant in silty and clayey sediments locally because of early diagenetic processes, authigenic precipitation and organic substances associated with these elements. The spatial distribution of As concentration shows exceptions: it is concentrated in some coarse and fine sands on the shelf. The enrichment is explained by adsorption of As, sourced from a coal field, to Fe hydroxide.     

The scale effect on the soil spatial heterogeneity of Haloxylon ammodendron (C. A. Mey.) in a sandy desert

Haloxylon ammodendron Bge (C.A. Mey.) is a dominant shrub species in the Gurbantonggut Desert and plays an important role in preventing wind erosion and combating desertification, typically by developing fertile islands in desert ecosystems; however, such islands often depend on the scales. An experiment was conducted to determine the scale dependence for the soil spatial heterogeneity of H. ammodendron in the Gurbantonggut Desert using the soil pH, electrical conductivity (EC), soil organic carbon (SOC), and total nitrogen (TN). The results showed that the soil EC, SOC and TN were significantly higher at the individual scale than the population scale. Moreover, the coefficients of variation (CV %) of the soil parameters at the individual scale were greater than they were at the population scale, with all except for pH (CV = 4.35 % for individual scale and CV = 2.87 % for population scale) presenting a moderate degree of variability (10 % < CV < 100 %). A geostatistical analysis revealed a strong spatial dependence [C ₀ /(C ₀ + C) < 25 %] within the distance of ranges for the tested parameters at both scales. The kriging interpolation results presented significant accumulation of soil SOC and TN around the shrub center and formed a significant “fertile island” at the individual scale, whereas the soil EC was much lower at the shrub center. At the population scale, patch fragments of the soil chemical properties were observed; however, not all individuals presented significant fertile islands or salt islands, and the soil EC presented a similar distribution as SOC and TN. These differences suggested that different mechanisms controlled the spatial distribution of soil minerals at the two scales and that the spatial heterogeneities are scale-dependent in a desert ecosystem.     

Distribution of Diatoms Along Environmental Gradients in the Charlotte Harbor,Florida (USA), Estuary and Its Watershed: Implications for Bioassessment of Salinity and Nutrient Concentrations

The relative abundance of diatom species in different habitats can be used as a tool to infer prior environmental conditions and evaluate management decisions that influence habitat quality. Diatom distribution patterns were examined to characterize relationships between assemblage composition and environmental gradients in a subtropical estuarine watershed. We identified environmental correlates of diatom distribution patterns across the Charlotte Harbor, Florida, watershed; evaluated differences among three major river drainages; and determined how accurately local environmental conditions can be predicted using inference models based on diatom assemblages. Sampling locations ranged from freshwater to marine (0.1–37.2 ppt salinity) and spanned broad nutrient concentration gradients. Salinity was the predominant driver of difference among diatom assemblages across the watershed, but other environmental variables had stronger correlations with assemblages within the subregions of the three rivers and harbor. Eighteen indicator taxa were significantly affiliated with subregions. Relationships between diatom taxon distributions and salinity, distance from the harbor, total phosphorus (TP), and total nitrogen (TN) were evaluated to determine the utility of diatom assemblages to predict environmental values using a weighted averaging-regression approach. Diatom-based inferences of these variables were strong (salinity R ²?=?0.96; distance R ²?=?0.93; TN R ²?=?0.83; TP R ²?=?0.83). Diatom assemblages provide reliable estimates of environmental parameters on different spatial scales across the watershed. Because many coastal diatom taxa are ubiquitous, the diatom training sets provided here should enable diatom-based environmental reconstructions in subtropical estuaries that are being rapidly altered by land and water use changes and sea level rise.     

Field-scale spatial distribution characteristics of soil nutrients in a newly reclaimed sandy cropland in the Hexi Corridor of Northwest China

Conversion of native desert to irrigation cropland often results in the changes of soil processes and properties. The objective of this study was to investigate the changes of soil nutrients and their spatial distribution characteristics of a newly reclaimed cropland at the initial stage of the conversion using statistical and geo-statistical methods. Soil samples were collected at regular intervals from a cropland of 0.24 ha, and their nutrient indicators determined. The mean contents of soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), available potassium (AK), and pH value in this newly reclaimed sandy cropland were averaged at 4.45 g kg^?1, 0.49 g kg^?1, 19.99 mg kg^?1, 21.08 mg kg^?1, 121.60 mg kg^?1, and 8.98, respectively. The ranges were less than 20 m for the semivariogram of SOC, TN, and pH, but exceeded 20 m for AN, AP, and AK. The ratios of nugget-to-sill were less than 10 % for the semivariogram of SOC, TN, and pH, but exceeded 25 % for AN, AP, and AK. There were similar distribution characteristics for SOC, AN, and pH, with different sizes of patches present; such distribution patterns were related to the regular planting of orchard and the interval application of manures. There were big-sized patches in the distributions of AN, AP, and AK. Topography was the main factor causing the spatial heterogeneity of available N, P, K, and the 4 years (2001–2004) of cropping affected the distribution patterns of these nutrient variables. The conversion of native desert to irrigation cropland caused significant increases in soil nutrients, but their spatial distributions had large variations. This study identified the main factors affecting the spatial distribution of each soil nutrient variable, including the environment factors and anthropogenic management practices. There is a great potential to improve the productivity and soil fertility for the newly reclaimed sandy cropland, only if the appropriate and sustainable soil management practices are adopted.     

Towards spatial geochemical modelling: Use of geographically weighted regression for mapping soil organic carbon contents in Ireland

It is challenging to perform spatial geochemical modelling due to the spatial heterogeneity features of geochemical variables. Meanwhile, high quality geochemical maps are needed for better environmental management. Soil organic C (SOC) distribution maps are required for improvements in soil management and for the estimation of C stocks at regional scales. This study investigates the use of a geographically weighted regression (GWR) method for the spatial modelling of SOC in Ireland. A total of 1310 samples of SOC data were extracted from the National Soil Database of Ireland. Environmental factors of rainfall, land cover and soil type were investigated and included as the independent variables to establish the GWR model. The GWR provided comparable and reasonable results with the other chosen methods of ordinary kriging (OK), inverse distance weighted (IDW) and multiple linear regression (MLR). The SOC map produced using the GWR model showed clear spatial patterns influenced by environmental factors and the smoothing effect of spatial interpolation was reduced. This study has demonstrated that GWR provides a promising method for spatial geochemical modelling of SOC and potentially other geochemical parameters.     

Methylmercury Bioaccumulation in an Urban Estuary: Delaware River,USA

Spatial variation in mercury (Hg) and methylmercury (MeHg) bioaccumulation in urban coastal watersheds reflects complex interactions between Hg sources, land use, and environmental gradients. We examined MeHg concentrations in fauna from the Delaware River estuary, and related these measurements to environmental parameters and human impacts on the waterway. The sampling sites followed a north to south gradient of increasing salinity, decreasing urban influence, and increasing marsh cover. Although mean total Hg in surface sediments (top 4 cm) peaked in the urban estuarine turbidity maximum and generally decreased downstream, surface sediment MeHg concentrations showed no spatial patterns consistent with the examined environmental gradients, indicating urban influence on Hg loading to the sediment but not subsequent methylation. Surface water particulate MeHg concentration showed a positive correlation with marsh cover whereas dissolved MeHg concentrations were slightly elevated in the estuarine turbidity maximum region. Spatial patterns of MeHg bioaccumulation in resident fauna varied across taxa. Small fish showed increased MeHg concentrations in the more urban/industrial sites upstream, with concentrations generally decreasing farther downstream. Invertebrates either showed no clear spatial patterns in MeHg concentrations (blue crabs, fiddler crabs) or increasing concentrations further downstream (grass shrimp). Best-supported linear mixed models relating tissue concentration to environmental variables reflected these complex patterns, with species specific model results dominated by random site effects with a combination of particulate MeHg and landscape variables influencing bioaccumulation in some species. The data strengthen accumulating evidence that bioaccumulation in estuaries can be decoupled from sediment MeHg concentration, and that drivers of MeHg production and fate may vary within a small region.     

The ecological condition of dead-end canals of the Delaware and Maryland coastal bays

Manmade, dead-end canals are common in residential developments along the coastal bays of Delaware and Maryland. The close proximity of housing to the water and the concentration of boating activities enhances the potential for anthropogenic stress to living resources in these poorly flushed aquatic systems. Measurements of water quality, sediment contaminants, and benthic macroinvertebrate assemblages were taken in 25 randomly selected canals and compared to 175 non-canal sites located throughout the coastal bays. The mean bottom dissolved oxygen concentrations in canals was half that found in non-canal sites. Mean water-column and benthic chlorophyll concentrations were, respectively, two times and four times higher in the canals. Sediment contaminant concentrations were significantly higher in the canals compared to the coastal bays, and exceeded published guideline values indicating possible adverse ecological effects. The contaminants of greatest concern in the canals included arsenic, copper, polyaromatic hydrocarbons, polychlorinated biphenyls, and several banned, persistent pesticides (DDT, dieldrin, endrin, and chlordane). Benthic macroinvertebrate assemblages in canals were severely degraded; mean species richness, abundance, and biomass were 1/7, 1/10, and 1/20, respectively, of the values for the remaining coastal bays. A single pollution-tolerant polychaete species (Streblospio benedicti) comprised approximately three-fourths (70%) of the community in the canals. Deep (>1 m) and muddy canals were in poorer condition than shallow and sandy ones.     

Influence of sediment provenance on background values of potentially toxic metals from near-surface sediments of Po coastal plain (Italy)

Systematic variability in metal concentrations is recorded in near-surface (1 m deep) Late Quaternary sediments of Po coastal plain, across the boundary between alluvial deposits of Apenninic provenance and a formerly active, now abandoned, delta lobe of the Po River. In the latter area, high Cr and Ni concentrations, exceeding the national standard limits, are attributed to sediment provenance from ultramafic source rocks of Po catchment basin, and not to anthropogenic impact. Spatial distribution of carbonate-related elements, such as Ca and Sr, displays consistent differences between the two areas, confirming a primary control of provenance domains on sediment composition. Accurate facies characterization of near-surface sediments, coupled with detailed information on sediment dispersal patterns, enable a reliable interpretation of the spatial variability of major elements and trace metals in the study area. Particularly, detailed reconstructions of source area composition and changes in flow directions through historical times allow precise correlation of apparently anomalous geochemical patterns with distinctive depositional events, such as shifts in channel course, crevasse splay formation and beach-ridge evolution. The findings of unusually high, natural (provenance-controlled) heavy metal concentrations in pre-industrial near-surface levels highlight the contribution of a sedimentological approach to a reliable interpretation of geochemical data. This should be taken into account when determining background values versus anthropogenic impact.