Spatial Scales Research Articles

Application timing affects the efficacy of Bacillus thuringiensis subsp. kurstaki against Tortrix viridana in deciduous oak forests

The green oak leaf roller moth, Tortrix viridana, is one of the main defoliators of deciduous oaks in the Mediterranean region. Although aerial applications of Btk-based insecticides represent the most effective method to control the larval populations of this pest at a large spatial scale, the optimal time window for sprayings has not yet been defined. Accordingly, experimental trials were conducted in a Quercus pubescens forest district in Sardinia (Italy) involving both large-scale aerial treatments and small-scale applications from the ground. The aim of our work was to study how different larval development stages and/or sprouting phenological phases of the host trees affect Btk efficacy. Aerial sprayings were conducted in 2003 and 2004 in two different areas of about 300 ha, selected according to altitude and exposure to simulate three different application timings against different larval instars and sprouting phenological phases. From-the-ground applications were carried out in 2021 in a Q. pubescens forest stand by applying Btk-based insecticides at different timings, and the overall Q. pubescens phenological stage and the distribution of T. viridana larval development stages were assessed accordingly. The effectiveness of Btk applications was evaluated by estimating larval mortality 7, and 14 days after aerial applications, and 7, 14 and 21 days after ground applications. Defoliation due to T. viridana was also evaluated at the end of larval development in all years. In both 2003 and 2004, the average larval mortality due to Btk exceeded 80 % two weeks after aerial applications across all application timings. Damage caused by T. viridana varied with Btk application timing, with the later applications showing a higher defoliation than other timings. In ground application experiments, larval mortality significantly increased when Btk was sprayed against a larval population primarily composed of IV instars, which were feeding on sprouts with leaves that were spread out and had not fully developed internodes, thus resulting in a significative reduction of insect damage. Our findings indicate that, in accordance with the strict synchrony between the larval development and the oak flushing, the optimal timing for Btk application against T. viridana can be defined based on the bud burst phenological phase. In particular, the prevalence of sprout with expanding leaf surface allowing insecticidal droplet interception and the simultaneous presence of susceptible larval instars (within the IV), resulted in an increased treatment efficacy.

Continental-scale nutrient and contaminant delivery by Pacific salmon.

The movement of large amounts of nutrients by migrating animals has ecological benefits for recipient food webs1,2 that may be offset by co-transported contaminants3,4. Salmon spawning migrations are archetypal of this process, carrying marine-derived materials to inland ecosystems where they stimulate local productivity but also enhance contaminant exposure5-7. Pacific salmon abundance and biomass are higher now than in the last century, reflecting substantial shifts in community structure8 that probably altered nutrient versus contaminant delivery. Here we combined nutrient and contaminant concentrations with 40 years of annual Pacific salmon returns to quantify how changes in community structure influenced marine to freshwater inputs to western North America. Salmon transported tonnes of nutrients and kilograms of contaminants to freshwaters annually. Higher salmon returns (1976-2015) increased salmon-derived nutrient and contaminant inputs by 30% and 20%, respectively. These increases were dominated by pink salmon, which are short-lived, feed lower in marine food webs than other salmon species, and had the highest nutrient-to-contaminant ratios. As a result, the delivery of nutrients increased at a greater rate than the delivery of contaminants, and salmon inputs became more ecologically beneficial over time. Even still, contaminant loadings may represent exposure concerns for some salmon predators. The Pacific salmon example demonstrates how long-term environmental changes interact with nutrient and contaminant movement across large spatial scales and provides a model for exploring similar patterns with other migratory species9.

Assessing the Tumor Immune Landscape Across Multiple Spatial Scales to Differentiate Immunotherapy Response in Metastatic Non-Small Cell Lung Cancer

Although immune checkpoint inhibitor-based therapy has shown promising results in non-small cell lung cancer patients with high programmed death-ligand 1 expression, not all patients respond to therapy. The tumor microenvironment (TME) is complex and heterogeneous, making it challenging to understand the key agents and features that influence response to therapies. In this study, we leverage multiplex fluorescent immunohistochemistry to quantitatively assess interactions between tumor and immune cells in an effort to identify patterns occurring at multiple spatial levels of the TME. To do so, we introduce several computational methods novel to a data set of 1,269 multiplex fluorescent immunohistochemistry images from a cohort of 52 patients with metastatic non-small cell lung cancer. With the spatial G-cross function, we quantify the degree of cell interaction at an entire image level, where we see significantly increased activity of cytotoxic T cells and helper T cells with epithelial tumor cells in responders to immune checkpoint inhibitor-based (P = .022 and P < .001, respectively) and decreased activity of T-regulatory cells with epithelial tumor cells compared with nonresponders (P = .010). By leveraging spatial overlap methods, we define tumor subregions (which we call the tumor “periphery,” “edge.” and “center”) and discover more localized immune-immune interactions influencing positive response, including those between cytotoxic T cells and helper T cells with antigen presenting cells in these subregions specifically. Finally, we trained an interpretable deep learning model that identified key cellular regions of interest that most influenced response classification (area under the curve = 0.71 ± 0.02). Assessing spatial interactions within these subregions further revealed new insights that were not significant at the whole image level, particularly the elevated association of antigen presenting cells and T-regulatory cells with one another in responder groups (P = .024). Altogether, we demonstrate that elucidating patterns of cell composition and interplay across multiple levels of spatial analyses can improve our understanding of the TME and better differentiate patient responses to immunotherapy.

Divergent roles of landscape and young streamflow fraction in stream water quality over seven catchments

Landscape patterns and water age are considered to play similar roles in influencing water quality, as human-caused landscape fragmentation usually leads to complex hydrological pathways and older water ages. The young streamflow fraction (Fyw), which can significantly alter water age, is believed to disproportionately impact water quality. Landscape and Fyw thus may play different roles in streamwater quality, but this assumption has not been examined. Here we examined the roles of Fyw (estimated by the amplitudes of seasonal cycles of oxygen isotope ratios in precipitation (Ap) and streamwater (As)) and landscape pattern (reflected by common landscape metrics) in streamwater quality over 7 forest-dominated catchments in eastern China. Landscape metrics, indicating land use arrangement, were closely related to multiple water quality parameters, suggesting a close association between stream water quality (sinks) and land use (sources). The Fyw had a positive relationship with ammonia nitrogen (R2 = 0.51, P = 0.044) and a negative relationship with nitrate nitrogen (R2 = 0.62, P = 0.022). The Fyw, determined by the heterogeneous-independent As/Ap, offers the possibility of modeling nitrogen compounds across multiple spatial scales. Importantly, the water quality parameters that significantly correlated with Fyw did not correlate with the landscape metrics. Differences in correlations of landscape and Fyw to water quality parameters imply that landscape and Fyw differed in their roles in water quality parameters, as well as the consideration for different water quality management strategies for different contaminants.

Evaluation of flood metrics across the Mississippi-Atchafalaya River Basin and their relation to flood damages.

Societal risks from flooding are evident at a range of spatial scales and climate change will exacerbate these risks in the future. Assessing flood risks across broad geographical regions is a challenge, and often done using streamflow time-series records or hydrologic models. In this study, we used a national-scale hydrological model to identify, assess, and map 16 different streamflow metrics that could be used to describe flood risks across 34,987 HUC12 subwatersheds within the Mississippi-Atchafalaya River Basin (MARB). A clear spatial difference was observed among two different classes of metrics. Watersheds in the eastern half of the MARB exhibited higher overall flows as characterized by the mean, median, and maximum daily values, whereas western MARB watersheds were associated with flood indicative of high extreme flows such as skewness, standardized streamflow index and top days. Total agricultural and building losses within HUC12 watersheds were related to flood metrics and those focused on higher overall flows were more correlated to expected annual losses (EAL) than extreme value metrics. Results from this study are useful for identifying continental scale patterns of flood risks within the MARB and should be considered a launching point from which to improve the connections between watershed scale risks and the potential use of natural infrastructure practices to reduce these risks.

Occupancy dynamics of the mottled owl Strix virgata using object-based image analysis along an urbanized Neotropical gradient

Urbanization has profound effects on wildlife. Although some species benefit or even thrive in urban environments, most species respond differently to the varying degrees of disturbance that can be found across an urbanized landscape. Quantifying the effects of urbanization in wildlife distributions, however, is complicated: species vary in their patterns of presence/absence, abundance, and detectability across spatial and temporal scales, e.g., daily, seasonal, or throughout the annual cycle. Here, we use occupancy models to offer a realistic approach to the study of populations of urban owls. Most studies on owl population dynamics have not considered temporal variation in occupancy between seasons or assess the uneven effects of urbanization along a habitat gradient. We investigated the seasonal habitat associations of mottled owls along an urban gradient in the Neotropical city of Xalapa, Veracruz, Mexico. Using high-resolution satellite images and object-based image classification techniques, were analyzed the relationship between different vegetation and environmental characteristics with the occupancy of mottled owls. We employed different sampling techniques, including playback surveys and silent listening periods, to detect the presence or absence of owls along a gradient from highest to lowest urbanization. Environmental data and different vegetation types were used to analyze the habitat associations of mottled owls during January (late non-breeding season) and May (late breeding season) of 2023. In total, we detected 68 mottled owls during the non-breeding season and 102 during the breeding season, with higher detection rates in areas with >28 % forest surface. Our results revealed that the best occupancy model included forest and forest division (occupancy), ambient noise and moonlight (detection) for the non-breeding season, as well as urban, forest, grass, and forest division (occupancy), and noise (detection) for the breeding season. The percentage of forested and grass areas positively influenced mottled owl occupancy while the percentage of urbanization and forest division influenced it negatively. Moonlight was positively related to mottled owl detection, while ambient noise had a negative effect on detection probabilities of mottled owls during both seasons. Forested areas emerged as pivotal for owl occupancy, indicating their sensitivity to forest changes along the urban gradient. With urban areas increasing, the interplay between forest division, ambient noise, and moonlight unveils critical insights into mottled owl behavior and habitat dynamics, underscoring the necessity for informed conservation strategies amidst urban expansion. Future research should survey different years to provide a more robust assessment of the dynamic occupancy of mottled owls in Neotropical urban gradients.

Study of the Dynamic Adaptive Calculation Method for River Water Environmental Capacity

Controlling the total amount of river pollutant discharge is an important means of water resource protection and management, and it is also a necessary condition for ensuring the normal functioning of water areas. The total amount of pollutant discharge is closely related to the water environmental capacity (WEC). Shifting from the traditional method of calculating WEC to dynamic analyses and calculations, concerning practical applications, in this paper, a dynamic adaptive calculation method is proposed for the river WEC that considers the changes in adaptive demand and hydrological conditions. In this method, the dynamic WEC is represented by intervals based on dynamic changes in different spatial and temporal scales, various calculation methods, hydrological conditions, and parameters. According to the calculation results for the WEC, a variable interval was formed. Taking the Shaanxi section of the main stream of the Wei River as the research object, with the support of an integrated platform, the dynamic adaptive calculation of the WEC in the Shaanxi section of the Wei River was realized, and a corresponding simulation system was constructed. The verification results show that (1) the dynamic calculation of WEC can be realized by freely combining different model methods and calculation conditions; (2) the WEC is described using a variable interval, which has strong applicability and operability; and (3) the simulation system can quickly adapt to the changing needs of practical applications and provide managers with visual and credible decision support. The research results provide a theoretical basis for river water environment pollution prevention and environmental management decision-making and help in the high-quality development of the river basin.

Oyster reefs as habitat for aquatic macrofauna in a Gulf of Mexico estuary: biotic complexity at spatial, ecological, and demographic scales

Oysters are important marine foundation species across the world, particularly in estuaries of the Gulf of Mexico. One important function of oysters in estuaries is the provision of 3-dimensional habitat that is used by a wide range of species. In this study, the biotic diversity of mid-bay intertidal oyster reefs found in a Gulf of Mexico estuary was examined at nested ecological and demographic scales. Fishery-independent data collections made in East Matagorda Bay, Texas, USA, were used to compare community structure and diversity at mid-bay reefs to undifferentiated shoreline habitats. Despite similar diversity metrics, there were differences in community structure that were driven by differences in spatial habitat use by several common species. Below the community scale, demographic differences in spotted seatrout Cynoscion nebulosus habitat use were observed, with smaller and younger individuals found along reefs, and larger and older individuals found along shorelines. This finding was more pronounced for male spotted seatrout in the spring. The observed spatial habitat use patterns at nested ecological scales (community, inter-species, intra-species) highlight the importance of oyster reefs for maintaining diversity in Gulf of Mexico estuaries, and more broadly support the notion that heterogeneity in localized habitats drives biotic diversity at the estuary scale. Conservation of oyster reefs as critical habitat should be considered along with conservation of oysters themselves when balancing the ecological value of oysters against the commercial value of oyster fisheries.

Spatial and temporal mush heterogeneity during eruptions recorded in clinopyroxene from the 2021 paroxysms at Mt. Etna, Italy

Textural and compositional zoning of volcanic minerals archives pre-eruptive magma processes. Crystals erupted simultaneously may be sampled from different regions of the plumbing system and hence record variable histories due to complex magma dynamics. In addition, crystals erupted throughout the course of an eruption may record temporal variations in the plumbing system. To resolve mush variability on both spatial and temporal scales, we investigate clinopyroxene erupted during a series of paroxysmal episodes between February–April 2021 at Mt. Etna, Italy. Using a combination of high-resolution geochemical techniques, we observe that Cr enrichments in clinopyroxene mantle zones, grown upon eruption-triggering mafic rejuvenation, exhibit both temporal and spatial (sample-scale) variability. Temporal variability correlates with changes in glass compositions, attesting to the ability of clinopyroxene to track magma maficity throughout an eruption. Spatial variability, indicated by the scatter of Cr concentrations, is greatest for the first event and lowest for the final paroxysm. In conjunction with core textures, degree of sector enrichment and thermobarometry, our data suggest that the onset of the paroxysms was preceded by the remobilisation of a mid-crustal clinopyroxene mush (534 ± 46 MPa) by hot, mafic magma causing variable resorption of mush-derived crystal cores. Towards the end of the eruption, waning magma supply led to less efficient mush remobolisation and mixing, resulting in homogenous crystal populations. Our results highlight that clinopyroxene Cr contents and sector enrichment can be used to track mafic rejuvenation and magma evolution throughout eruptions, while also reflecting spatial heterogeneities within the plumbing system.

Fungal community composition varies spatially in a commercial potato field in response to soil properties and topographic features

The factors influencing the spatial distribution of fungal communities are commonly examined over large spatial scales but not at smaller scales. Given this, the extent to which soil properties and topographic features contribute to the diversity and distribution of fungal communities in an agricultural field needs to be further explored. We investigated the spatial distribution of soil fungal community composition from a ~1100 m long transect with 83 sampling points in a commercial potato field with a rolling landform. The relative abundance of Ascomycota, Basidiomycota and Mortierellomycota showed medium to strong spatial dependence with an autocorrelation range varying from ~43 to 92 m, similar to the autocorrelation range of soil properties and topographic features. Most of the variability in fungal and saprotrophic community composition was explained by soil properties (15% and 11%, respectively) and spatial distance (16% and 15% respectively). While topographic features contributed 8% and 5% of variability to total fungi and saprotrophic community composition, respectively. The fungal and saprotrophic community compositions were correlated with SOC, pH and slope curvature, however, richness and Pielou’s evenness of the fungal communities and fungal biomass were not correlated with soil properties or topographic features. The results suggest that the spatial variation in fungal and saprotrophic community composition in response to soil properties and topographic features in this agricultural landscape was due to differences in assemblages of fungal Amplicon Sequence Variants (ASVs) but not in differences in the number of fungal ASVs or fungal biomass measured using phospholipids fatty acids.

Small-scale Helmholtz resonators with grazing turbulent boundary layer flow

ABSTRACT Helmholtz resonators flush-mounted in a wall beneath turbulent boundary layer flow are studied by focusing on their flow-induced excitation and effect on the grazing turbulent flow. A particular focus lies on single resonators tuned to the most intense spatio-temporal fluctuations in the near-wall vertical velocity and wall-pressure, residing at a spatial scale of λ x + ≈ 250 (or temporal scale of T + ≈ 25 ). Resonators are examined in a boundary layer flow at R e τ ≈ 2280 . Two neck-orifice diameters of d + ≈ 68 and 102 are considered, and for each value of d + three different resonance frequencies are studied (corresponding to a period of T + ≈ 25 , as well as one lower, and one higher, period). The response of the TBL flow is analysed by employing velocity data from hot-wire anemometry and particle image velocimetry measurements. Passive resonance only affects streamwise velocity fluctuations in the region y + ≲ 25 , while vertical velocity fluctuations due to resonance reach up to y + ≈ 100 . A narrow-band increase in streamwise turbulence kinetic energy at the resonance scale co-exists with a more than 20% attenuation of lower-frequency energy. Current findings on single resonator cases will aid in the development of passive surfaces with distributed resonators for boundary-layer flow control.

Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages.

Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we have engineered robotic neural recording devices-'cranial exoskeletons'-that assist mice in maneuvering recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. We discovered optimal controller parameters that enable mice to locomote at physiologically realistic velocities while maintaining natural walking gaits. We show that mice learn to work with the robot to make turns and perform decision-making tasks. Robotic imaging and electrophysiology headstages were used to record recordings of Ca2+ activity of thousands of neurons distributed across the dorsal cortex and spiking activity of hundreds of neurons across multiple brain regions and multiple days, respectively.

Innovations through crop switching happen on the diverse margins of US agriculture

Crop switching, in which farmers grow a crop that is novel to a given field, can help agricultural systems adapt to changing environmental, cultural, and market forces. Yet while regional crop production trends receive significant attention, relatively little is known about the local-scale crop switching that underlies these macrotrends. We characterized local crop-switching patterns across the United States using the US Department of Agriculture (USDA) Cropland Data Layer, an annual time series of high resolution (30 m pixel size) remote-sensed cropland data from 2008 to 2022. We found that at multiple spatial scales, crop switching was most common in sparsely cultivated landscapes and in landscapes with high crop diversity, whereas it was low in homogeneous, highly agricultural areas such as the Midwestern corn belt, suggesting a number of potential social and economic mechanisms influencing farmers' crop choices. Crop-switching rates were high overall, occurring on more than 6% of all US cropland in the average year. Applying a framework that classified crop switches based on their temporal novelty (crop introduction versus discontinuation), spatial novelty (locally divergent versus convergent switching), and categorical novelty (transformative versus incremental switching), we found distinct spatial patterns for these three novelty dimensions, indicating a dynamic and multifaceted set of cropping changes across US farms. Collectively, these results suggest that innovation through crop switching is playing out very differently in various parts of the country, with potentially significant implications for the resilience of agricultural systems to changes in climate and other systemic trends.

Estimating soil moisture from environmental gamma radiation monitoring data

AbstractSoil moisture (SM) information is invaluable for a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents root‐zone SM for longer periods and larger spatial scales. One option for root‐zone SM observation is terrestrial gamma radiation (TGR), as it is inversely related to SM. Hence, the near real‐time data of more than 5000 environmental gamma radiation (EGR) monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) is a potential source to develop a root‐zone SM product for Europe without extra investments in SM sensors. This study aims to investigate to what extent the EURDEP data can be used for SM estimation. For this, two EGR monitoring stations were equipped with in situ SM sensors to measure reference SM. The terrestrial component of EGR was extracted after eliminating the contributions of rain washout and secondary cosmic radiation, and used to obtain a functional relationship with SM. We predicted the weekly volumetric SM with a root mean square error of 7%–9% from TGR measurements. Nevertheless, we believe that this technique, due to its greater penetration depth and long data legacy, can provide useful data complementary to satellite‐based remote sensing techniques to estimate root‐zone SM at the continental scale.

Indoor environmental evaluation of traditional Chinese medicine clinic – taking the treatment space as an example

ABSTRACT Currently, there are no targeted standards and norms for Chinese medicine clinic diagnosis and treatment space. This study conducted field research in nine Chinese medicine clinics located in Hangzhou. The field research included the measurement of physical environment data in addition to the patients' subjective evaluation of the factors of the physical environment and design within the clinics, followed by statistical data analysis. The results show that the order of importance of physical environment factors in the diagnosis and treatment space was as follows: air quality > sound pressure level > humidity > temperature and the order of importance of the design factors were as follows: access route > supporting facilities > overall style > spatial scale > barrier-free design > cultural atmosphere and the order of importance of the spatial scale factors were as follows: area > the number of beds > window-to-wall ratio > floor height. The study presents the reference values of the physical environment parameters and spatial scale of the Chinese medicine clinics and the importance ranking of each factor.

The intricacies of vegetation responses to changing moisture conditions.

A long-standing debate looks at whether air or soil dryness is more limiting to vegetation water use and productivity. The answer has large implications for future ecosystem functioning, as atmospheric dryness is predicted to increase globally while changes in soil moisture are predicted to be far more variable. Here, I review the complexities that contribute to this debate, including the strong coupling between atmospheric and soil dryness, and the widespread heterogeneity in vegetation hydraulic traits, acclimations, and adaptations to water stress. I discuss solutions to improve understanding and modeling of vegetation sensitivity to dryness, including how different types of observational data can be used together to gain insight into vegetation response to water stress across spatial and temporal scales.

Small-scale geographic differences in multiple-driver environmental variability can modulate contrasting phenotypic plasticity despite high levels of gene flow

Climate change is altering not only the mean conditions of marine environments, but also their temporal variability and predictability. As these alterations are not uniform across seascapes, their biological effects are expected to accentuate intra-specific differences in the adaptive capacity (e.g., plasticity and evolutionary potential) of natural populations. To test this theoretical framework, we assessed the phenotypic and genetic profiles of mussel from three study sites across a multi-driver heterogeneous environmental mosaic in Chilean Patagonia. Our study reveals that temporal variability, predictability, and exposure to extreme events (low pH/low salinity), collectively, can modulate the plasticity and optimal conditions of mussels. Despite these phenotypic differences, we observed low genetic differentiation, likely resulting from significant gene flow induced by aquaculture, ultimately diminishing variation among individuals from different geographic areas. Our findings underscore how variability and predictability are essential factors shaping phenotypic diversity, even at small spatial scales. Balancing these factors could enhance species resilience and ecological success, crucial for biodiversity conservation amidst climate change.

Evaluating the suitability of large-scale datasets to estimate nitrogen loads and yields across different spatial scales

Decision makers are often confronted with inadequate information to predict nutrient loads and yields in freshwater ecosystems at large spatial scales. We evaluate the potential of using data mapped at large spatial scales (regional to global) and often coarse resolution to predict nitrogen yields at varying smaller scales (e.g., at the catchment and stream reach level). We applied the SPAtially Referenced Regression On Watershed attributes (SPARROW) model in three regions: the Upper Midwest part of the United States, New Zealand, and the Grande River Basin in southeastern Brazil. For each region, we compared predictions of nitrogen delivery between models developed using novel large-scale datasets and those developed using local-scale datasets. Large-scale models tended to underperform the local-scale models in poorly monitored areas. Despite this, large-scale models are well suited to generate hypotheses about relative effects of different nutrient source categories (point and urban, agricultural, native vegetation) and to identify knowledge gaps across spatial scales when data are scarce. Regardless of the spatial resolution of the predictors used in the models, a representative network of water quality monitoring stations is key to improve the performance of large-scale models used to estimate loads and yields. We discuss avenues of research to understand how this large-scale modelling approach can improve decision making for managing catchments at local scales, particularly in data poor regions.

Assessing the distribution and ecotoxicological risks of organochlorine pesticides in a river-wetland system of the Manipur River basin, India

ABSTRACT The present study aims to evaluate the distribution of organochlorine pesticides in the Loktak Lake and its draining rivers over a spatial and seasonal scale. Organochlorine pesticides including α- HCH, β- HCH, γ- HCH, δ- HCH, Aldrin, 4,4-DDE, Endrin, Endosulfan II, 4,4-DDD, Endrin Aldehyde, Endosulfan sulphate and 4,4-DDT were analysed in the water and sediments adopting gas chromatography and mass spectrometric techniques. The concentration of pesticides recorded the highest concentration of 2271 ng/l in the water samples and 5319 ng/g in sediment samples. In water samples, Endosulfan II, Endrin and γ- HCH were present at the higher concentrations, whereas α-BHC was recorded at the lowest at 0.78 ng/l. In sediment samples, 4, 4-DDT recorded the highest concentration, followed by 4,4-DDD and Endosulfan II. Human health risk assessment based on water consumption shows higher risk potential from five pesticides. Pesticides in the region may pose a threat to the wetland comprising vital flora and fauna of the biodiversity hotspot. The bacterial population was more or less related to the pesticide concentration, with a lower population at less contaminated sites.

CNN for scalar-source distance estimation in grid-generated turbulence

Countermeasures against material leakage in industrial plants call for rapid leak source estimation techniques based on limited downstream information. Assuming that such scalar diffusion occurs in a turbulent environment, it is necessary to extract features from its instantaneous local concentration distribution and estimate the distance from the observation point to the source. To this end, we proposed an estimation method using a supervised deep learning of a convolutional neural network (CNN) and investigated its estimation performance in grid-generated turbulence fields. The grid turbulence fields were reproduced by direct numerical simulations at three Reynolds numbers (Re), and the CNN was trained using two-dimensional distribution images of passive scalars downstream. We confirmed that the images large enough to cover the spatial integral length scales of the scalar resulted in high estimation accuracy. For images with a coarsened brightness gradation, the small-scale feature of scalar fluctuations was lost, and the CNN attained a low estimation accuracy. By training the CNN with high-Re images, a high estimation accuracy was obtained, even for low-Re images. The opposite case (low-Re training and high-Re estimation) yielded low accuracy, where the CNN significantly underestimated the distance against the source. Based on these results, we discussed the generalizability and essential features to be learned by the CNN.