Temporal Monitoring Research Articles

Forecasting Groundwater Remediation Timeframes: Site‐Specific Temporal Monitoring Results May Not Predict Future Performance

AbstractAt contaminated sites, groundwater monitoring results are commonly used (quantitatively or qualitatively) to predict remediation timeframes. If results are predictive, then there should be a strong positive correlation between attenuation rates for the first half of a temporal monitoring record and attenuation rates for the second half of the same record. We utilized the GeoTracker database to evaluate the power of historical groundwater monitoring results to predict future attenuation rates. For two data sets (petroleum and chlorinated solvent), we found a small negative correlation between the first‐order concentration vs. time attenuation rate observed during the earlier part of the monitoring record and the later part of the monitoring record: benzene—correlation coefficient (r) = −0.11, methyl tert‐butyl ether (MTBE)—r = −0.12, trichloroethene (TCE) = −0.12. For each data set, a small negative correlation between the first‐order attenuation rate observed during the earlier part of the monitoring record and the later part of the monitoring record was also observed for a subset of monitoring records exhibiting the best model fits (R2 > 0.8), a subset with a statistically significant (p < 0.05) positive attenuation rate for the first half of the monitoring record. For the TCE data set, this negative correlation was also observed for a subset of monitoring records with no change in site remedy during the monitoring period (r = −0.22). Our analysis suggests that the historical concentration vs. time attenuation rate for a contaminant at an individual site or monitoring well is a poor predictor of the future rate.

Detection and Measurement of Picoseconds-Pulsed Laser Energy Using a NbTiN Superconducting Filament

We investigate non-equilibrium states created by a laser beam incident on a superconducting NbTiN filament subject to an electrical pulse at 4 K. In absence of the laser excitation, when the amplitude of the current pulse applied to the filament exceeds the critical current value, we monitored the delay time <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$t_{d}$</tex-math></inline-formula> that marks the collapse of the superconducting phase which is then followed by a voltage rise. We linked the delay time to the applied current using the time-dependent Ginzburg-Landau (TDGL) theory, which enabled us to deduce the cooling (or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">heat-removal</i> ) time from the fit to the experimental data. Subsequently, we exposed the filament biased with a current pulse close to its critical value to a focused laser beam, inducing a normal state in the impact region of the laser beam. We showed that the energy of the incident beam and the incurred delay time are related to each other by a simple expression, that enables direct measurement of incident beam energy by temporal monitoring of the transport response. This method can be extended for usage in single-photon detection regime, and be used for accurate calibration of an arbitrary light source.

FU Orionis disk outburst: Evidence for a gravitational instability scenario triggered in a magnetically dead zone

Context. FUors outbursts are a crucial stage of accretion in young stars. However, a complete mechanism at the origin of the outburst still remains missing. Aims. We aim to constrain the instability mechanism in the star FU Orionis itself by directly probing the size and evolution in time of the outburst region with near-infrared (NIR) interferometry, and to confront it with physical models of this region. Methods. As the prototype of the FUors class of objects, FU Orionis has been a regular target of NIR interferometry. In this paper, we analyze more than 20 years of NIR interferometric observations to perform a temporal monitoring of the region of the outburst, and compare it to the spatial structure deduced from 1D magneto-hydrodynamic (MHD) simulations. Results. We measure from the interferometric observations that the size variation of the outburst region is compatible with a constant or slightly decreasing size over time: -0.56-0.36+0.14 AU/100 yr and -0.30-0.19+0.19 AU/100 yr in the H and K bands, respectively. The temporal variation and the mean size probed by NIR interferometry are consistently reproduced by our 1D MHD simulations. We find that the most compatible scenario is a model of an outburst occurring in a magnetically layered disk, where a magneto-rotational instability (MRI) is triggered by a gravitational instability (GI) at the outer edge of a dead zone. The scenario of a pure thermal instability (TI) fails to reproduce our interferometric sizes because it can only be sustained in a very compact zone of the disk &lt;0.1 AU. The comparison between the data and the MRI-GI models favors MHD parameters of αMRI = 10−2, TMRI = 800 K, and Σcrit = 10 g cm−2, with more work needed in terms of observations and modeling in order to improve the precision of these values. Locally, in the very inner part of the disk, TI can be triggered in addition to MRI-GI, which qualitatively better matches our observation but is not strongly constrained by the currently available data. The scenario of MRI-GI could be compatible with an external perturbation that enhances the GI, such as tidal interaction with a stellar companion, or a planet at the outer edge of the dead zone. Conclusions. We favor a layered-disk model driven by MRI turbulence in order to explain the spatial structure and temporal evolution of the outburst region on FU Orionis. Understanding this phase will provide a crucial link between the early phase of disk evolution and the process of planet formation in the first inner astronomical units.

Measuring Vertical Urban Growth of Patna Urban Agglomeration Using Persistent Scatterer Interferometry SAR (PSInSAR) Remote Sensing

In the present study, the vertical and horizontal growth of Patna Urban Agglomeration was evaluated using the Persistent Scatterer Interferometry Synthetic Aperture Radar (PSInSAR) technique during 2015–2018. The vertical urban growth assessment of the city landscape was assessed using microwave time series (30 temporal) datasets of Single Look Complex (SLC) Sentinel-1A interferometric Synthetic Aperture Radar using SARPROZ software (ver. 2020). This study demonstrated that peripheral city regions experienced higher vertical growth (~4 m year−1) compared to the city core regions, owing to higher urban development opportunities leading to significant land use alterations, the development of high-rise buildings, and infrastructural development. While the city core of Patna observed an infill and densification process, as it was already saturated and highly densified. The rapidly urbanizing city in the developing region witnessed a considerable horizontal urban expansion as estimated through the normalized difference index for built-up areas (NDIB) and speckle divergence (SD) using optical Sentinel 2A and microwave Sentinel-1A ground range detected (GRD) satellite data, respectively. The speckle divergence-based method exhibited high urban growth (net growth of 11.28 km2) with moderate urban infill during 2015–2018 and reported a higher accuracy as compared to NDIB. This study highlights the application of SAR remote sensing for precise urban area delineation and temporal monitoring of urban growth considering horizontal and vertical expansion through processing a long series of InSAR datasets that provide valuable information for informed decision-making and support the development of sustainable and resilient cities.

Temporal Error Monitoring Does Not Depend on Working Memory.

Working memory (WM) and metacognition has been documented to be in a reciprocal relationship. This study aims to address if temporal error monitoring performance can be diminished with increased working memory load. We hypothesized that if temporal error monitoring has commonalities with perceptual error monitoring, temporal error monitoring performance should be diminished by increased working memory load. Participants completed a temporal error monitoring task in a dual task design in which the secondary task was a letter alphabetization task. Results revealed no disrupting effect of WM load on either confidence or short-long judgments as being different metrics of temporal error monitoring ability. These results demonstrate that unlike perceptual error monitoring, WM and temporal error monitoring have distinct processing mechanisms. With this result, the current study suggests that temporal and perceptual error monitoring may partially rely on different mechanisms. Results are discussed within A Theory of Magnitude (ATOM), pacemaker-accumulator model and temporal error monitoring frameworks.

A synergetic approach for quantification and analysis of coal fires in Jharia Coalfield, India

Temporal monitoring and understanding of the dynamics of coal fires in the Jharia Coalfield (JCF) are required to reduce its effect on sustainable industrial growth, environment & human safety. This research explores temporal dataset of Landsat 8 OLI Thermal Infrared Sensor (TIRS) from 2015 to 2019 to detect, map and quantify coal fire affected areas in JCF at the colliery level. The results indicated that the East Barora, Sijua, Katras, Kusunda, Kustore, Pootkee Balihari, Bastacolla, Jharia, and Lodna are intensely fire-affected collieries with a significant increase in risk area from 4.57 km2 in 2015 to 11.43 km2 in 2019. The central part of the area is highly affected. The extent of coal fire shows temporal fluctuation between 2015 and 2019, but overall exhibit a significant increase from 2.76 km2 to 7.52 km2. Sijua, Katras, Kusunda, Lodna, and Kustor occupying the central and southeastern parts of the JCF, respectively, constitute nearly ∼85% of the total fire. However, in comparison to the information inferred from the field-based knowledge, the results derived from satellite-based observations are slightly underestimated due to the reason that the coal fire-derived thermal anomalies are the function of depth, intensity and proportion of coal fire in a coarse resolution TIR pixel, structural attributes, interventions from the mining operation and regional land use planning. Further, the risk areas map out using the TIR-based approach have been integrated with the prevailing structural attributes and Landsat 8 OLI-derived surface thermal anomalies, which enabled an understanding of the dynamics of coal fire propagation in JCF.

Nitrate attenuation with rising groundwater levels: An integrated assessment using isotope tracers and microbial signatures

Nitrate contamination of groundwater has long been a source of concern. Most field studies conducted in areas with rising groundwater levels have found an increase in nitrate concentration owing to nitrate leaching, but they have not investigated the possible biogeochemical processes. In this study, dual nitrate isotopes and microbial signatures were combined to assess and quantify nitrate attenuation in the North China Plain with an apparent groundwater-level recovery trend over the past decade. Significant denitrification was revealed using the dual nitrate isotopes on the temporal scale. High-throughput sequencing provided microbial functional and taxonomic evidence, showing the relative abundances of denitrification-related functional genes negatively related to the nitrate concentration. Nitrate attenuation was strengthened in the aquifer as the groundwater levels rose, with a larger temporal enrichment factor (ε) value of −25‰ compared with the spatial ε value of −5‰. This study is the first to reveal the mechanisms of nitrate attenuation in aquifers undergoing groundwater-level recovery with an integrated assessment using nitrate isotope tracers and microbial signatures. In identifying the main nitrate attenuation processes, it is important to consider the scale and domain of interest and to conduct sufficient spatial and temporal monitoring to capture transient conditions.

Spatio-temporal modelling of the effect of environmental and land-use factors on species-rich calcareous grasslands

The abundance of sensitive plant species in calcareous grasslands is threatened by agricultural intensification with nutrient addition and increased livestock densities as well as by land abandonment. The Hill-Shannon diversity is decreasing, and the species composition of Danish calcareous grassland is generally unstable and is expected to experience further change in the coming years. In order to quantify the effects of selected environmental and land-use factors on the observed variation and changes in the vegetation of calcareous grasslands, large-scale spatial and temporal pin-point plant cover monitoring data are fitted in a structural equation model. The analyzed vegetation data come from 100 Danish sites monitored over an eight-year period. The important sources of measurement and sampling uncertainties have been included using a hierarchical model structure. Furthermore, the measurement and sampling uncertainties are separated from the process uncertainty, which is important when generating ecological predictions that may feed into local conservation management decisions. There were significant negative effects of grazing and nitrogen deposition on the change in cover of sensitive plant species. Whereas the negative effect of nitrogen deposition on the cover of sensitive species was expected, it was surprising that the model results suggest that sensitive species may be subjected to overgrazing by the grazing regimes that are currently applied at protected Danish calcareous grasslands. The standardized regression coefficients suggest that the effects of both grazing and nitrogen deposition are relatively benign compared to the effects of soil type, soil pH and precipitation. The relatively large effect of precipitation is interesting, since it is predicted that the amount of precipitation and its distribution over the seasons will change due to climate change, and the results suggest that climate change may lead to important species compositional changes in calcareous grasslands. The fitted model may be used to quantify the uncertainties when generating ecological forecasting and local adaptive management plans. More specifically, this study suggests that it is relevant to rethink the currently used criteria for vegetation height when assessing the conservation status of calcareous grasslands.

Évolution des environnements de la Lagune de Tunis du Pléistocène moyen à l’Holocène

The lake of Tunis, located in northern Tunisia, is part of the coastal wetlands sensitive to climatic and anthropic variations. This fragile ecosystem was an open bay 190 ka BP ago. Today, it is separated from the Mediterranean by a sandy barrier fed mainly by the Madjerda wadi. This study, based on a multidisciplinary geological approach, examines the evolution of the dynamics of the Tunis Lake, as well as the recent environmental changes that control the sedimentation. Two cores LN1 (55m) and LS1 (40m) were collected in the alluvial deposits, respectively in the North-East and South-East of the Lake. These cores have been studied in detail to determine the spatio-temporal distribution of the sedimentary stock. The data from this study complemented by those from previous work allowed us to refine and establish spatio-temporal correlation scenarios of the sediments filling the Tunis lagoon. These correlations are established between the LN1 core and the core taken at the SE (LS1). Spatial and temporal monitoring of sediment deposition in these cores has revealed a general regressive evolutionary trend, from a frankly marine environment to a lagoon environment more or less communicating with the sea, from the Middle Pleistocene (an age between 159 and 205 ka) to the present Holocene. The identification of ostracod associations typical of open marine or lagoon environments and of benthic foraminifera associations of lagoon environments has allowed us to trace the history of the Tunis Lake over the last two millennia. It begins with an open marine environment (around 2030 years BP) followed by an open lagoon environment around 1700 years BP.

A Framework Using Open-Source Software for Land Use Prediction and Climate Data Time Series Analysis in a Protected Area of Portugal: Alvão Natural Park

Changes in land use and land cover (LULC) in protected areas can lead to an ecological imbalance in these territories. Temporal monitoring and predictive modeling are valuable tools for making decisions about conserving these areas and planning actions to reduce the pressure caused by activities such as agriculture. This study accordingly developed an LULC analysis framework based on open-source software (QGIS and R language) and predictive methodology using artificial neural networks in the Alvão Natural Park (PNA), a protected area in northern Portugal. The results show that in 2041, Agriculture and Open Space/Non-vegetation classes will evidence the greatest decrease, while Forest and Bushes will have expanded the most. Spatially, the areas to the west and northeast of the protected area will experience the most significant changes. The relationship of land use classes with data from the climate model HadGEM3-GC31-LL (CMIP6) utilizing scenarios RCP 4.5 and 8.5 demonstrates how through the period 2041–2060 there is a tendency for increased precipitation, which when combined with the dynamics of a retraction in classes such as agriculture, favors the advancement of natural classes such as bushes and forest; however, the subsequent climate data period (2061–2080) projects a decrease in precipitation volumes and an increase in the minimum and maximum temperatures, defining a new pattern with an extension of the period of drought and precipitation being concentrated in a short period of the year, which may result in a greater recurrence of extreme events, such as prolonged droughts that result in water shortages and fires.

ID: 212135 Noninvasive Human Immunotyping Through Machine Learning Using the Autonomic Nervous System

The extreme diversity of the human immune system, forged and maintained throughout evolutionary history, has to date provided a potent defense against pathogens [1]. Intrinsically variable autonomic neuro-immune regulation via β-adrenergic receptor and α7-nicotinic acetylcholine receptor activity is controlled by polymorphic genes and environmental sensors [2, 3]. While most healthy humans have the capacity to activate various types of immune cells, interferons, inflammasome activity, and vagal anti-inflammatory reflexes, individuals differ in the degree to which they are primed for each functional configuration. Virulent emerging pathogens inherently circumvent these functional immune configurations and can impose a dysregulated hyperinflammatory response [4]. Here we detect host-dependent baseline autonomic gradient drive (AGD) bias through high temporal resolution physiological monitoring. Similar to immune bias, AGD bias shown to predict current inflammatory status as well as severity of future inflammatory sequela and disease.

Agreement Study between Total Leukocyte Count Methodologies in South American Sea Lions (Otaria byronia) and Peruvian Fur Seals (Arctocephalus australis).

South American sea lions (Otaria byronia) and Peruvian fur seals (Arctocephalus australis) are sympatric species inhabiting the coastal Peruvian marine ecosystem. Declining abundance has prompted population health monitoring programs, including temporal monitoring of blood parameters. Several methods exist to determine total leukocyte count, yet no studies have evaluated agreement between methods in pinnipeds. We assessed agreement between total leukocyte counts determined by blood film estimate, Leuko-TIC, HemoCue, and UNOPETTE methods by using archival results from pinnipeds at Punta San Juan, Peru. Blood film estimates were prospectively performed, and resulting data were compared with retrospective leukocyte counts obtained from both species between 2009 and 2019 by using the other methodologies. Agreement in hematologic counts between methods was evaluated using Passing-Bablok regression and Bland-Altman plots (α=0.05). In total, 295 individuals (201 A. australis and 94 O. byronia) were included in the analysis. The blood film estimate method resulted in the highest leukocyte values (P<0.0001). Leuko-TIC counts were significantly higher than HemoCue counts (P<0.0001). Constant and proportional error was present in the agreement between the blood film estimate method and the other methods. Given the variation demonstrated between the different methodologies, additional research is needed to further evaluate agreement between these methodologies. The results underscore the importance of maintaining consistency in leukocyte count methodology for monitoring trends in population health over time. Method consistency may be the more important clinical consideration for assessing changes in leucocyte count over time and avoiding apparent changes depending on the methodology used.

Payment for environmental services related to aquifers: a review of specific issues and existing programmes

In Europe, payment for environmental services is increasingly perceived as an alternative to government-led incentives for promoting pro-environmental land use and attaining policy objectives of groundwater quality and quantity. The processes linking land-use decisions and ecosystem services related to aquifers (EcSA) are complex, involving different time and space scales. This raises specific challenges for the effectiveness of payment for environmental services related to aquifers (PEvSA). After defining the concepts of PEvSA, we highlight these challenges—uncertain links between land use and EcSA, spatial and temporal dimensions, monitoring and compliance issues, the invisibility of aquifers and the social equity/efficiency dilemma—and identify good practice and innovative designs for addressing them. We then review how existing PEvSA schemes throughout the world have succeeded, or not, in addressing these challenges and identify evidence of their effectiveness. We conclude that future implementation of PEvSA should pursue (i) the use of science-based approaches for determining land-use prescription; (ii) the adoption of result-oriented payments adapted to PEvSA; (iii) the use of longer term contracts adapted to water transfer time in aquifers; (iv) a finer spatial targeting of PEvSA; (v) the use of contracts with collective conditionality; and (vi) the labelling of products that generate EcSA as ways for stimulating demand. We finally call for establishing formal evidence of the impact of PEvSA on EcSA.

Normalized Temperature Drought Index (NTDI) for Soil Moisture Monitoring Using MODIS and Landsat-8 Data

As the fundamental regulator of energy exchange in the vegetation–soil–atmosphere circulation system, soil moisture is a key parameter for drought monitoring and is indispensable to the land surface hydrological processes. In order to overcome the constraints of the Perpendicular Drought Index, PDI (performs poorly over the fields with dense vegetation and hard to construct the soil line), and the Temperature Vegetation Drought Index, TVDI (requires similar atmospheric forcing and large enough dimension of mapping area), in soil moisture monitoring, a new drought index (Normalized Temperature Drought Index, NTDI) is proposed to explore the spatiotemporal changes of soil moisture by substituting red and near-infrared reflectances with vegetation index and normalized land surface temperature on the basis of the PDI framework. Victoria, Australia, was selected as the study area as it experiences many severe droughts and has been affected for more than ten years. Time series of satellite-based data were applied to evaluate the effectiveness and applicability of the NTDI at the regional scale. Results indicated that the expression of the soil line representing the water condition of the bare soil is easier to obtain in the new trapezoid framework and has good fits with the coefficients of determination (R2) of more than 0.8. Compared with PDI, TVDI and Modified PDI (MPDI) at the cropping sites, NTDI exhibits a relatively better performance in soil moisture monitoring for most days where the R2 achieved can reach to more than 0.7 on DOY 242, 254 and 272. Meanwhile, spatial–temporal mappings of the four drought indices from satellite data were conducted, and the NTDI presented the slightly seasonal variation and effectively described the real spatial characteristics of regional drought. Overall, the NTDI seems to a viable approach and can provide insight into spatial and temporal soil moisture monitoring at different scales.

Temporal groundwater quality, health risks and source point management zonation of multi-aquifers in Jilin Qian'an, Northeastern China.

Jilin Qian'an, located in Northeastern China's Songnen Plain, relies almost exclusively on groundwater for drinking. The quaternary phreatic aquifer (Q3) is distinguished by high geogenic fluoride and arsenic concentrations, which necessitates reliance on quaternary confined (Q1) and neogene confined (N) aquifers (deeper aquifers) as source point management (SPM) alternatives. However, deeper aquifers are contaminated, necessitating temporal monitoring and unique management strategies. Using 165 samples, this study investigated the appropriateness of deeper restricted aquifers as a continuous SPM alternative by assessing the spatiotemporal groundwater quality and human health risk of the multi-aquifers in Jilin Qian'an from the 1980s to the 2010s. In addition, a source point management zonation (SPMZ) was implemented to define the specific intervention necessary in various portions of the study area. Results indicate water quality parameters were within recommended limits for most samples except fluoride, while arsenic was the most significant heavy metal pollutant. Mean groundwater mineralization in all the aquifers increased with time. Deeper aquifers are still a better alternative to the shallow phreatic aquifer as groundwater quality in the study is of the order N > Q1 > Q3 in the respective aquifers. Cancer risk assessment (CR) shows increases from 2001 to the 2010s in all aquifers except in Q3. SPMZ delineated: High As and high F zones; high As and low F zones; high As zones; high F zones; low F zones; and safe zones. Localized intervention based on SPMZ is recommended, along with the use of alternative water sources.

Dujiangyan irrigation system optimization (DISO): A novel metaheuristic algorithm for dam safety monitoring

This work utilizes a novel metaheuristic algorithm named Dujiangyan Irrigation System Optimization (DISO) to resolve the dam deformation prediction problem. The Dujiangyan irrigation system (DIS) served as the model for the DISO algorithm, which has good metaheuristic algorithmic properties to handle various issues. This study utilizes the Fish Mouth project, the Baopingkou project, and the DIS's water separation and sand discharge principle. With the help of a mathematical model and implementation, DISO can perform the optimization process in various search spaces. Two comparative experiments with various characteristics are performed to evaluate the effectiveness of the DISO algorithm. 29 CEC 2017 benchmark test functions, 4 high-constrained test functions, and 2 typical engineering design challenges are chosen in the first step. 14 advanced heuristic techniques are chosen from the literature, and the statistical outputs of these techniques are examined and compared. Three nonparametric statistical tests are performed to confirm the proposed algorithm's effectiveness. The results demonstrate that the DISO algorithm outperforms all the evaluated algorithms. In the following stage, the proposed algorithm is applied to the dam deformation prediction problem, and a KICA-DISO-SVM spatial–temporal monitoring model is established for dams. The findings of the studies indicate that the proposed method can effectively monitor the influence of dam displacement on dam operation. The proposed model overcomes the inability of the standard single measurement point mode to capture the intrinsic relationship of the spatial deformation field accurately. The suggested DISO technique offers encouraging outcomes in resolving complex optimization problems.

A review on efforts for improvement in medicinally important chemical constituents inAconitum through biotechnological interventions.

The genus Aconitum belongs to the family Ranunculaceae, is endowed with more than 350 species on the earth. Medicinally important aconitine type of diterpenoid alkaloids are the characteristic compounds in most of the Aconitum species. The present review endeavored the major research carried out in the field of genetic resource characterization, pharmacological properties, phytochemistry, major factors influencing quantity, biosynthetic pathways and processing methods for recovery of active ingredients, variety improvement, propagation methods, and important metabolite production through cell/organ culture of various Aconitum species. More than 450 derivatives of aconitine-type C19 and C20-diterpenoid alkaloids along with a few other non-alkaloidal compounds, such as phenylpropanoids, flavonoids, terpenoids, and fatty acids, have been identified in the genus. A few Aconitum species and theircommon diterpenoid alkaloid compounds are also well characterized for analgesic, inflammatory and cytotoxic properties. However, the different isolated compound needs to be validated for supporting other traditional therapeutical uses of the plant species. Aconitine alkaloids shared common biosynthesis pathway, but their diversification mechanism remains unexplored in the genus. Furthermore, the process needs to be developed on secondary metabolite recovery, mass-scale propagation methods, and agro-technologies for maintaining the quality of products. Many species are losing their existence in nature due to over-exploitation or anthropogenic factors; thus, temporal monitoring of the population status in its habitat, and suitable management programs for ascertaining conservation needs to be developed.

Monitoring of intergranular variables for predicting technical breakage of wheat grains stored in vertical silos

The increase in the silos temperature and intergranular relative humidity can alter the equilibrium moisture content of the grains mass causing losses. Thus, the objective was to evaluate the temporal monitoring of temperature, relative humidity, and intergranular carbon dioxide for the prediction of dry matter loss in wheat grains stored in vertical silos, using a mathematical model and machine learning algorithms. Under these conditions, wheat grains had a slight increase in metabolic activity, causing a dry matter loss of 0.035–0.041%. The intergranular temperature, relative humidity, and carbon dioxide results were similar to the measurements on the surface of the grain mass. It was concluded that the monitoring of temperature, relative humidity, and the concentration of carbon dioxide in the intergranular air indirectly and early determined the changes in the quality of wheat grains during storage. Although the metabolic activity of wheat grains was low, as the lots remained in hygroscopic equilibrium with moisture contents close to 12% (w.b.), the temporal detection characterized the loss of dry matter and the reduction of grain weight stored. Finally, the Artificial Neural Networks and Multiple Linear Regression model satisfactorily predicted the dry matter loss of stored wheat grain mass.

Improving accuracy of quantifying nitrate removal performance and enhancing understanding of processes in woodchip bioreactors using high-frequency data

Woodchip bioreactors have gained popularity in many countries as a conservation practice for reducing nitrate load to freshwater. However, current methods for assessing their performance may be inadequate when nitrate removal rates (RR) are determined from low-frequency (e.g., weekly) concurrent sampling at the inlet and outlet. We hypothesised that high-frequency monitoring data at multiple locations can help improve the accuracy of quantifying nitrate removal performance, enhance the understanding of processes occurring within a bioreactor, and therefore improve the design practice for bioreactors. Accordingly, the objectives of this study were to compare RRs calculated using high- and low-frequency sampling and assess the spatiotemporal variability of the nitrate removal within a bioreactor to unravel the processes occurring within a bioreactor. For two drainage seasons, we monitored nitrate concentrations at 21 locations on an hourly or two-hourly basis within a pilot-scale woodchip bioreactor in Tatuanui, New Zealand. A novel method was developed to account for the variable lag time between entry and exit of a parcel of sampled drainage water. Our results showed that this method not only enabled lag time to be accounted for but also helped quantify volumetric inefficiencies (e.g., dead zone) within the bioreactor. The average RR calculated using this method was significantly higher than the average RR calculated using conventional low-frequency methods. The average RRs of each of the quarter sections within the bioreactor were found to be different. 1-D transport modelling confirmed the effect of nitrate loading on the removal process as nitrate reduction followed Michaelis-Menten (MM) kinetics. These results demonstrate that high-frequency temporal and spatial monitoring of nitrate concentrations in the field allows improved description of bioreactor performance and better understanding of processes occurring within woodchip bioreactors. Thus, insights gained from this study can be used to optimise the design of future field bioreactors.

Baseline genetic distinctiveness supports structured populations of thornback ray in the Mediterranean Sea

Abstract The thornback ray (Raja clavata) is the most important chondrichthyan in terms of landings in the Mediterranean Sea. Intense harvesting may induce negative genetic effects reducing the resilience of overfished species. For this reason, genetic diversity information should be considered in fisheries management and conservation policies. Microsatellite markers were used to unravel the genetic features (variability, connectivity, sex‐biased dispersal) of R. clavata populations, both at the small (around the coast of Sardinia, western Mediterranean Sea) and larger spatial scales (at the pan‐Mediterranean level, and between the Atlantic Ocean and the Mediterranean Sea). Individual clustering, multivariate and variance analyses rejected the hypothesis of genetic homogeneity, with significant genetic differences between Mediterranean and Atlantic rays, as well as within the Mediterranean Sea between its western and eastern basins. The data indicated that both the Strait of Gibraltar and the Sicilian Channel seem to be effective in limiting the dispersal of thornback ray individuals, but a further structuring was identified, with the significant genetic differentiation of the populations located in the Algero‐Provençal and Tyrrhenian basins. Such a fine‐scale arrangement suggests the occurrence of additional barriers to species dispersal. A lack of significant genetic differentiation, stable over the years, was measured at a local scale among R. clavata Sardinian samples. Several possible mechanisms, both biological and abiotic (e.g. migratory behaviour, waterfronts and oceanographic discontinuities), are discussed. Overall, the genetic data presented, both at the local and regional level, could represent the baseline information for the temporal monitoring of populations and assessing the effects of present or future fisheries‐related management actions. The data obtained are information of paramount importance for minimizing the gaps in our current knowledge of the genetic diversity of thornback rays and maximizing the information needed for the correct protection of R. clavata populations.