The role of periodic boundary forcing in plankton pattern formation

We consider one and two-dimensional minimal models in plankton dynamics. The influence of oscillating boundary forcing functions as agents for triggering pattern formation is discussed. In particular it is found that in these conditions population waves arise for one dimensional models, while for two dimensional models, different amplitudes and frequencies in the boundary forcing generate definite patterns, mimicking the boundary term. This happens even though the model we investigate is very simple. The emergence of these features is an interesting metaphor for the fundamental biological problem of how pattern formation processes may be inevitable in natural heterogeneous ecosystems.     

Improve Compliance with Limited Resources by a Three-Group Inspection Regime

Frequent monitoring and relatively high fines are usually necessary to bring about improvements in environmental quality, but more challenging for many countries with limited human, material, and financial resources is to put them into practice. This paper developed a three-group model of a state-dependent enforcement in a repeated game to improve the policy implementation under limited inspection capacities. A certain number of firms are grouped (group 1, group 2, group 3) for different supervision intensity (e.g., the order of inspection probability corresponding to each group is p ₁?<?p ₂?<?p ₃) based on their environmental performance. The optimal policy parameters, such as inspection probability of each group and the probability that a firm found in compliance is moved to a better reputation group, were obtained as the basis for regulator’s policy making. Numerical simulations indicated that the three-group inspection regime can significantly increase compliance rate as compared with static enforcement with the same monitoring probability. Among the number of firms in each group under steady state conditions, group 2 had the most, group 1 was the second, and group 3 had the smallest. Analysis and prediction of a three-group reputation example provided a good experiment for the model. The results give a practical reference for the policy makers with inspection capacity constraints to achieve higher compliance rate.     

Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.     

Earth-tide-induced fluctuations in the salinity of an inland river,New South Wales,Australia: a short-term study

Wybong Creek discharges salts into the agriculturally and industrially important Hunter River in New South Wales, Australia. Abrupt increases in salinity occur periodically in the mid-Wybong Creek catchment. In order to understand the processes which cause these abrupt increases, changes in surface and groundwater were investigated. It is shown that salinity increases can be attributed to highly discrete groundwater discharge directly into the river from below. Hourly electrical conductivity data measured in the river showed regular, diurnal electrical conductivity fluctuations of up to 350 μS cm^?1. These fluctuations could not be attributed to barometric pressure, temperature, or evapotranspiration. Instead, a similar periodicity in surface water electrical conductivity and groundwater height in nearby groundwater wells was found. Fluctuations were of similar periodicity to the orthotides which cause fluctuations in surface water height and are induced by Earth tides. The geology in the mid-catchment area indicates conditions are optimal for Earth tides to impact groundwater. The reporting of orthotidal changes in water chemistry in this article is believed to be the first of its kind in the scientific literature, with the large fluctuations noted having important implications for water monitoring and management in the catchment. Further research investigating Earth-tide-induced phases of groundwater heights will better constrain the relationships between surface water chemistry and groundwater height.     

Assessment of aluminum bioavailability in alum sludge for agricultural utilization

Inorganic aluminum ions, [Al(H₂O)₆]³⁺, [Al(OH)(H₂O)₅]²⁺, and [Al(OH)₂(H₂O)₄]⁺, are toxic to a number of crops. The aim of this study was to estimate the danger of soil contamination of bioavailable aluminum and heavy metals forms because of alum sludge which was a by-product of water, and wastewater treatment technology using aluminum coagulant is introduced into the soil. Aluminum and selected heavy metal fractionation was carried out in the post-coagulation sludge collected at a water treatment plant (where aluminum was used as a coagulant), fermented sewage sludge at a municipal wastewater treatment plant (which did not apply aluminum coagulant), and soil from water treatment plant as well as the mixtures of sludge and soil. It has been found that post-coagulation sludge used as natural fertilizer is a secondary source of bioavailable aluminum, especially when aluminum coagulants are used during water and wastewater treatment. The evaluation of applicability of the sludge to very weak acidic and acidic agricultural soils was carried out. The authors shall debate the question whether, in this case, the Regulation of EU and Polish Government on sewage sludge should also take the bioavailable aluminum into account and add to the list of the elements whose allowable contents are limited.     

Quality assessment of groundwater from the south-eastern Arabian Peninsula

Assessment of groundwater quality plays a significant role in the utilization of the scarce water resources globally and especially in arid regions. The increasing abstraction together with man-made contamination and seawater intrusion have strongly affected groundwater quality in the Arabia Peninsula, exemplified by the investigation given here from the United Arab Emirates, where the groundwater is seldom reviewed and assessed. In the aim of assessing current groundwater quality, we here present a comparison of chemical data linked to aquifers types. The results reveal that most of the investigated groundwater is not suitable for drinking, household, and agricultural purposes following the WHO permissible limits. Aquifer composition and climate have vital control on the water quality, with the carbonate aquifers contain the least potable water compared to the ophiolites and Quaternary clastics. Seawater intrusion along coastal regions has deteriorated the water quality and the phenomenon may become more intensive with future warming climate and rising sea level.     

Variability in the phytoplankton community of Kavaratti reef ecosystem (northern Indian Ocean) during peak and waning periods of El Niño 2016

El Niño, an interannual climate event characterized by elevated oceanic temperature, is a prime threat for coral reef ecosystems worldwide, owing to their thermal threshold sensitivity. Phytoplankton plays a crucial role in the sustenance of reef trophodynamics. The cell size of the phytoplankton forms the “master morphological trait” with implications for growth, resource acquisition, and adaptability to nutrients. In the context of a strong El Niño prediction for 2015–2016, the present study was undertaken to evaluate the variations in the size-structured phytoplankton of Kavaratti reef waters, a major coral atoll along the southeast coast of India. The present study witnessed a remarkable change in the physicochemical environment of the reef water and massive coral bleaching with the progression of El Niño 2015–2016 from its peak to waning phase. The fluctuations observed in sea surface temperature, pH, and nutrient concentration of the reef water with the El Niño progression resulted in a remarkable shift in phytoplankton size structure, abundance, and community composition of the reef waters. Though low nutrient concentration of the waning phase resulted in lower phytoplankton biomass and abundance, the diazotroph Trichodesmium erythraeum predominated the reef waters, owing to its capability of the atmospheric nitrogen fixation and dissolved organic phosphate utilization.     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.