Geo-spatial analysis of the temporal trends of kharif crop phenology metrics over India and its relationships with rainfall parameters

The Global Inventory Modeling and Mapping Studies bimonthly Normalized Difference Vegetation Index (NDVI) data of 8?×?8 km spatial resolution for the period of 1982–2006 were analyzed to detect the trends of crop phenology metrics (start of the growing season (SGS), seasonal NDVI amplitude (AMP), seasonally integrated NDVI (SiNDVI)) during kharif season (June to October) and their relationships with the amount of rainfall and the number of rainy days over Indian subcontinent. Direction and magnitude of trends were analyzed at pixel level using the Mann–Kendall test and further assessed at meteorological subdivision level using field significance test (α?=?0.1). Significant pre-occurrence of the SGS was observed over northern (Punjab, Haryana) and central (Marathwada, Vidarbha and Madhya Maharashtra) parts, whereas delay was found over southern (Rayalaseema, Coastal Andhra Pradesh) and eastern (Bihar, Gangetic West Bengal and Sub-Himalayan West Bengal) parts of India. North, west, and central India showed significant increasing trends of SiNDVI, corroborating the kharif food grain production performance during the time frame. Significant temporal correlation (α?=?0.1) between the rainfall/number of rainy days and crop phenology metrics was observed over the rainfed region of India. About 35–40 % of the study area showed significant correlation between the SGS and the rainfall/number of rainy days during June to August. June month rainfall/number of rainy days was found to be the most sensitive to the SGS. The amount of rainfall and the number of rainy days during monsoon were found to have significant influence over the SiNDVI in 24–30 % of the study area. The crop phenology metrics had significant correlation with the number of rainy days over the larger areas than that of the rainfall amount.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

Impact of intensive horticulture practices on groundwater content of nitrates, sodium, potassium, and pesticides

A monitoring program of nitrate, nitrite, potassium, sodium, and pesticides was carried out in water samples from an intensive horticulture area in a vulnerable zone from north of Portugal. Eight collecting points were selected and water-analyzed in five sampling campaigns, during 1 year. Chemometric techniques, such as cluster analysis, principal component analysis (PCA), and discriminant analysis, were used in order to understand the impact of intensive horticulture practices on dug and drilled wells groundwater and to study variations in the hydrochemistry of groundwater. PCA performed on pesticide data matrix yielded seven significant PCs explaining 77.67% of the data variance. Although PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types. However, a visible differentiation between the water samples was obtained. Cluster and discriminant analysis grouped the eight collecting points into three clusters of similar characteristics pertaining to water contamination, indicating that it is necessary to improve the use of water, fertilizers, and pesticides. Inorganic fertilizers such as potassium nitrate were suspected to be the most important factors for nitrate contamination since highly significant Pearson correlation (r = 0.691, P < 0.01) was obtained between groundwater nitrate and potassium contents. Water from dug wells is especially prone to contamination from the grower and their closer neighbor's practices. Water from drilled wells is also contaminated from distant practices.     

Methane oxidation and abundance of methane oxidizers in tropical agricultural soil (vertisol) in response to CuO and ZnO nanoparticles contamination

There is worldwide concern over the increase use of nanoparticles (NPs) and their ecotoxicological effect. It is not known if the annual production of tons of industrial nanoparticles (NPs) has the potential to impact terrestrial microbial communities, which are so necessary for ecosystem functioning. Here, we have examined the consequences of adding the NPs particularly the metal oxide (CuO, ZnO) on CH₄ oxidation activity in vertisol and the abundance of heterotrophs, methane oxidizers, and ammonium oxidizers. Soil samples collected from the agricultural field located at Madhya Pradesh, India, were incubated with either CuO and ZnO NPs or ionic heavy metals (CuCl₂, ZnCl₂) separately at 0, 10, and 20 μg g^?1 soil. CH₄ oxidation activity in the soil samples was estimated at 60 and 100 % moisture holding capacity (MHC) in order to link soil moisture regime with impact of NPs. NPs amended to soil were highly toxic for the microbial-mediated CH₄ oxidation, compared with the ionic form. The trend of inhibition was Zn 20?>?Zn 10?>?Cu 20?>?Cu 10. NPs delayed the lag phase of CH₄ oxidation to a maximum of 4-fold and also decreased the apparent rate constant k up to 50 % over control. ANOVA and Pearson correlation analysis (α?=?0.01) revealed significant impact of NPs on the CH₄ oxidation activity and microbial abundance (p?<?0.0001, and high F statistics). Principal component analysis (PCA) revealed that PC1 (metal concentration) rendered 76.06 % of the total variance, while 18.17 % of variance accounted by second component (MHC). Biplot indicated negative impact of NPs on CH₄ oxidation and microbial abundance. Our result also confirmed that higher soil moisture regime alleviates toxicity of NPs and opens new avenues of research to manage ecotoxicity and environmental hazard of NPs.     

Factors regulating trophic status in a large subtropical reservoir, China

We evaluated a 4-year data set (July 2003 to June 2007) to assess the trophic state and its limiting factors of Three-Gorges Reservoir (TGR), China, a large subtropical reservoir. Based on Carlson-type trophic state index (TSI)_CHL, the trophic state of the system was oligotrophic (TSI_S?< 40) in most months after the reservoir became operational, although both TSI_TP and TSI_TN were higher than the critical value of eutrophic state (TSI_S?>?50). Using Carlson’s (1991) two-dimensional approach, deviations of the TSI_S indicated that factors other than phosphorus and nitrogen limited algal growth and that nonalgal particles affected light attenuation. These findings were further supported by the significant correlation among the values of TSI_CHL ? TSI_SD and nonvolatile suspended solids and water residence time. The logarithmic model showed that an equivalent TSI_CHL and TSI_SD could be found at τ?=?54 days in the TGR (Fig. 7). Accordingly, nonalgal particulates dominated light attenuation and limited algal biomass of the reservoir when τ?<?54 days.     

Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry

Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter ??_t,τ, beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.     

Concentrations of some heavy metals in water, suspended solids, and biota species from Maluan Bay, China and their environmental significance

Concentrations of heavy metals (Cu, Zn, Cd, and Pb) in surface water (including total recoverable, dissolved, suspended solids) and in aufwuchs encrusted on Moerella iridescens Benson from seven selected sites and two reference sites in Maluan Bay were investigated in order to understand current metal contamination due to industrialization and urbanization in Xiamen, China. The muscle tissues of the study species (Penceus penicillatus, Scylla serrata Forskal, Harengula zunasi Bleeker, Tillapia nilotica) from a trawling area within Maluan Bay were also analyzed in order to evaluate its safety as seafood. Based on the obtained data, metal concentrations in surface water were compared with Marine Seawater Quality Standards of China and the US EPA acute and chronic criteria, which showed that Maluan Bay may be subjected to different levels of contamination by the metals. Metal concentrations under study in the edible parts (muscle) of the investigated biota species were within the safety permissible levels for human consumption. Through Pearson??s correlation analysis, the relationships between metal concentrations in surface water and in M. iridescens were evaluated. Copper concentrations in M. iridescens were more strongly positively correlated with particulate copper in suspended solids and total recoverable copper in water rather than with dissolved copper at the sampling sites. The data suggested that copper-rich suspended solids contributed substantially to copper accumulation by M. iridescens and played a critical role in the pathway of copper into the food chain. The conclusions of this investigation are likely to be applicable to other relevant scenarios.     

Hierarchy of factors affecting the social perception of dam reservoirs

This study presents an assessment of factors that influence how people who live in the vicinity of dams view such projects. The usefulness of the principal component analysis (PCA) method for identifying variables that determine individuals' opinion about large dam projects was reviewed. The study focuses on people affected by the construction of the Mucharski Reservoir in the Polish Carpathians. The construction took over 30 years and took place at a time when Poland transitioned from a planned economy to a free market one.We used in-depth interviews (N = 96) and a set of 18 factors classified as personal, emotional and economic. Our results indicate that the variables that significantly affect social perception of dam projects by the local population include their opinion regarding the viability of the project, sense of security, personal benefits, the extent to which they have accepted the structure, respecting the local community's interests when drafting the development plans and new opportunities. The results allow for the future optimization of research tools used to comprehensively examine social perception of hydraulic structures. Using PCA allowed us to take semi-structured data from interviews and extract meaningful relationships between the various inputs, show correlations between seemingly unrelated data, as well as explain the variances within the studied population. It also shows that PCA can be a useful tool for analyzing data that is not formally structured.     

Chemometric characterization of river water quality

Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box–whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO ₄ ^2? ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward’s method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson’s correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO ₄ ^2? ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson’s correlation (r) values that indicated significant and positive correlation between variables in the same group. Box–whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO ₄ ^2? ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March–June) and the lowest during monsoon season (July–October). Temperature was the highest in summer and the lowest in winter (November–February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in summer season.     

Assessment of trace element contamination in sediment cores from the Pearl River and estuary,South China: geochemical and multivariate analysis approaches

Twenty-four major and trace elements and the mineralogical composition of four sediment cores along the Pearl River and estuary were analyzed using ICP-AES, ICP-MS, and X-ray diffraction (XRD) to evaluate contamination levels. The dominant minerals were quartz, kaolinite, and illite, followed by montmorillonite and feldspars, while small amounts of halite and calcite were also observed in a few samples. Cluster analysis (CA) and principal component analysis (PCA) were performed to identify the element sources. The highest metal concentrations were found at Huangpu, primarily due to wastewater treatment plant discharge and/or the surreptitious dumping of sludge, and these data differed from those of other sources. Excluding the data from Huangpu, the PCA showed that most elements could be considered as lithogenic; few elements are the combination of lithogenic and anthropogenic sources. An antagonistic relationship between the anthropogenic source metals (K, Ba, Zn, Pb, Cd, Ag, Tl, and U) and marine source metals (Na, Mg, Ti, V, and Ca) was observed. The resulting normalized Al enrichment factor (EF) indicated very high or significant pollution of Cd, Ag, Cu, Zn, Mo, and Pb at Huangpu, which may cause serious environmental effects. Conflicting results between the PCA and EF can be attributed to the background values used, indicating that background values must be selected carefully.