Key Environmental Parameters Research Articles

A novel theoretical model for predicting the individuals’ thermal sensations based on air temperature and biomarkers measured by wearable devices

Optimal control of indoor thermal environments based on real-time monitoring of occupants' feeling of warmth (a.k.a. thermal sensation) is one of the effective strategies to improve building energy efficiency and occupant comfort. Accordingly, developing an individual (or personal) thermal comfort model based on continuous observation of biomarkers (often measured by wearable devices) has received much research attention in recent years. Whilst almost all the comfort prediction models presented in the literature are based on a data-driven approach and machine learning techniques, this paper presents a novel theoretical model aimed at explaining the causal relationship in the prediction of thermal sensations based on key environmental and physiological parameters, incl. skin temperature, heart rate, and air temperature. The proposed model is grounded on the ASHRAE thermal sensation index (TSENS) and is based on mediating effects of thermoregulatory and cardiac responses. The new model's performance was evaluated under different thermal environmental conditions by comparing it against the PMV values and the experimental data available from the literature. Results showed that the proposed model could accurately predict individual thermal sensations by monitoring the air temperature, overall or wrist skin temperature, and heart rate (or metabolic rate). This model can provide new insight into individual thermal comfort assessment and can be used alone or in combination with data-driven machine learning models for continuous monitoring of thermal comfort conditions.

Production of rhamnolipid biosurfactants in solid-state fermentation: process optimization and characterization studies

BackgroundRhamnolipids are a group of the extracellular microbial surface-active molecules produced by certain Pseudomonas species with various environmental and industrial applications. The goal of the present research was to identify and optimize key process parameters for Pseudomonas aeruginosa PTCC 1074s synthesis of rhamnolipids utilizing soybean meal in solid state fermentation. A fractional factorial design was used to screen the key nutritional and environmental parameters to achieve the high rhamnolipid production. Response surface methodology was used to optimize the levels of four significant factors.ResultsThe characterization of biosurfactant by TLC, FT-IR and H-NMR showed the rhamnolipids presence. In the optimum conditions (temperature 34.5 °C, humidity 80%, inoculum size 1.4 mL, and glycerol 5%), the experimental value of rhamnolipid production was 19.68 g/kg dry substrate. The obtained rhamnolipid biosurfactant decreased water's surface tension from 71.8 ± 0.4 to 32.2 ± 0.2 mN/m with a critical micelle concentration of nearly 70 mg/L. Additionally, analysis of the emulsification activity revealed that the generated biosurfactant was stable throughout a broad pH, temperature, and NaCl concentration range.ConclusionsThe current study confirmed the considerable potential of agro-industrial residues in the production of rhamnolipid and enhanced the production yield by screening and optimizing the significant process parameters.

IoT-Based Smart Wireless Communication System for Electronic Monitoring of Environmental Parameters with a Data-Logger

As the transition toward automated industrial environments gains momentum, the necessity for dependable, real-time environmental monitoring systems becomes increasingly critical. Addressing this urgent need, this paper unveils a sophisticated IoT-based wireless communication system specifically engineered for electronic monitoring of key environmental parameters. An Arduino Nano microcontroller is central to the system’s design, which interfaces with a diverse suite of sensors to monitor temperature, humidity, gas concentrations, and even emergency conditions like fire hazards. Leveraging the capabilities of an nRF24L01 wireless module, the system transmits these multi-faceted sensor readings in real time to a control unit. Once received, the data is vividly displayed on an (organic light emitting diode) OLED screen and logged onto a Micro-SD card for subsequent analysis and historical trend monitoring. Additionally, the system features audio-visual alerts through an electric buzzer and LED, providing instantaneous warnings in critical situations. Notably, the sensor data undergoes rigorous validation by being compared with reference values obtained from NASA’s official databases, ensuring high accuracy and reliability. This comprehensive solution significantly advances industrial safety and efficiency, serving as a robust tool for monitoring and responding to environmental changes in real time.

When should bees be flower constant? An agent-based model highlights the importance of social information and foraging conditions.

Many bee species show flower constancy, that is, a tendency to visit flowers of one type during a foraging trip. Flower constancy is important for plant reproduction, but the benefits of constancy to bees is unclear. Social bees, which often use communication about food sources, show particularly strong flower constancy. We aimed to better understand the benefits of flower constancy in social bees and how these benefits depend on foraging conditions. We hypothesised that sharing social information increases the benefits of flower constancy because social foragers share information selectively about high-quality food sources, thereby reducing the need to sample alternatives. We developed an agent-based model that allowed us to simulate bee colonies with and without communication and flower constancy in different foraging environments. By varying key environmental parameters, such as food source numbers and reward size, we explored how the costs and benefits of flower constancy depend on the foraging landscape. Flower constancy alone performed poorly in all environments, while indiscriminate flower choice was often the most successful strategy. However, communication improved the performance of flower constant colonies considerably in most environments. This combination was particularly successful when high-quality food sources were abundant and competition was weak. Our findings help explain why social bees tend to be more flower constant than solitary bees and suggest that flower constancy can be an adaptive strategy in social bees. Simulations suggest that anthropogenic changes of foraging landscapes will have different effects on the foraging performance of bees that vary in flower constancy.

Analysis of full-scale riser responses in field conditions based on Gaussian mixture model

Offshore slender marine structures experience complex and combined load conditions from waves, current and vessel motions that may result in both wave frequency and vortex shedding response patterns. Field measurements often consist of records of environmental conditions and riser responses, typically with 30 min intervals. These data can be represented in a high-dimensional parameter space. However, it is difficult to visualize and understand the structural responses, as they are affected by many of these parameters. It becomes easier to identify trends and key parameters if the measurements with the same characteristics can be grouped together. Cluster analysis is an unsupervised learning method, which groups the data based on their relative distance, density of the data space, intervals, or statistical distributions. In the present study, a Gaussian mixture model guided by domain knowledge has been applied to analyze field measurements. Using the 242 measurement events of the Helland-Hansen riser, it is demonstrated that riser responses can be grouped into 12 clusters by the identification of key environmental parameters. This results in an improved understanding of complex structure responses. Furthermore, the cluster results are valuable for evaluating the riser response prediction accuracy.

STOCHOS: Stochastic opportunistic maintenance scheduling for offshore wind farms

Despite the promising outlook, the numerous economic and environmental benefits of offshore wind energy are still compromised by its high Operations and Maintenance (O&M) expenditures. On one hand, offshore-specific challenges such as site remoteness, harsh weather, transportation requirements, and production losses, significantly inflate the O&M costs relative to land-based wind farms. On the other hand, the uncertainties in weather conditions, asset degradation, and electricity prices largely constrain the farm operator’s ability to identify the time windows at which maintenance is possible, let alone optimal. In response, we propose STOCHOS, short for the stochastic holistic opportunistic scheduler—a maintenance scheduling approach tailored to address the unique challenges and uncertainties in offshore wind farms. Given probabilistic forecasts of key environmental and operational parameters, STOCHOS optimally schedules the offshore maintenance tasks by harnessing the opportunities that arise due to favorable weather conditions, on-site maintenance resources, and maximal operating revenues. STOCHOS is formulated as a two-stage stochastic mixed-integer linear program, which we solve using a scenario-based rolling horizon algorithm that aligns with the industrial practice. Tested on real-world data from the U.S. North Atlantic where several offshore wind farms are in-development, STOCHOS demonstrates considerable improvements relative to prevalent maintenance benchmarks, across various O&M metrics, including total cost, downtime, resource utilization, and maintenance interruptions.

Exploration of β-glucosidase-producing microorganisms community structure and key communities driving cellulose degradation during composting of pure corn straw by multi-interaction analysis

Poor management of crop residues leads to environmental pollution and composting is a sustainable practice for addressing the challenge. However, knowledge about composting with pure crop straw is still limited, which is a novel and feasible composting strategy. In this study, pure corn straw was in-situ composted for better management. Community structure of β-glucosidase-producing microorganisms during composting was deciphered using high-throughput sequencing. Results showed that the compost was mature with organic matter content of 37.83% and pH value of 7.36 and pure corn straw could be composted successfully. Cooling phase was major period for cellulose degradation with the highest β-glucosidase activity (476.25 μmol·p-Nitr/kg·dw·min) and microbial diversity (Shannon index, 3.63; Chao1 index, 500.81). Significant compositional succession was observed in the functional communities during composting with Streptomyces (14.32%), Trichoderma (13.85%) and Agromyces (11.68%) as dominant genera. β-Glucosidase-producing bacteria and fungi worked synergistically as a network to degrade cellulose with Streptomyces (0.3045**) as the key community revealed by multi-interaction analysis. Organic matter (−0.415***) and temperature (−0.327***) were key environmental parameters regulating cellulose degradation via influencing β-glucosidase-producing communities, and β-glucosidase played a key role in mediating this process. The above results indicated that responses of β-glucosidase-producing microorganisms to cellulose degradation were reflected at both network and individual levels and multi-interaction analysis could better explain the relationship between variables concerning composting cellulose degradation. The work is of significance for understanding cellulose degradation microbial communities and process during composting of pure corn straw.

Soil moisture is a primary driver of comammox Nitrospira abundance in New Zealand soils

The objectives of this study were to investigate the abundance and community composition of comammox Nitrospira under: (i) pasture-based dairy farms from different regions, and (ii) different land uses from the same region and soil type. The results clearly showed that comammox Nitrospira were most abundant (3.0 × 106 copies) under the west coast dairy farm conditions, where they were also significantly more abundant than canonical ammonia oxidisers. This was also true in the Canterbury dairy farm. The six land uses investigated were pine monoculture, a long term no input ecological trial, sheep + beef and Dairy, both irrigated and non-irrigated. It was concluded that comammox Nitrospira was most abundant under the irrigated dairy farm (2.7 × 106 copies). Contrary to the current industry opinion, the relatively high abundance of comammox Nitrospira under fertile irrigated dairy land suggests that comammox Nitrospira found in terrestrial ecosystems may be copiotrophic. it was also determined that comammox Nitrospira was more abundant under irrigated land use than their non-irrigated counterparts, suggesting that soil moisture is a key environmental parameter influencing comammox abundance. Comammox abundance was also positively correlated with annual rainfall, further supporting this theory. Phylogenetic analysis of the comammox Nitrospira detected determined that 17 % of the comammox community belonged to a newly distinguished subclade, clade B.2. The remaining 83 % belonged to clade B.1. No sequences from clade A were found.

Unraveling the ameliorative potentials of native lichen Pyxine cocoes (Sw.) Nyl., during COVID 19 phase.

Due to the rapid increase in the novel coronavirus virulence, the entire world implemented the practice of lockdown along with the constraint of human movement. The obligation of quarantine halted most of the commercial and industrial movement that prominently disturbed the distinct key environmental parameters directly associated with the plant’s and animal’s health conditions. In this regard, the research aims to study the sudden shut-off of vehicular activity impact on the naturally growing lichen of the genus Pyxine cocoes. The results showed an increase in the pigments, Fv/Fm ratio, and phytohormones during the lockdown and concurrently the decreasing levels in the post-lockdown period. Interestingly, modulations in the phytohormones occur in the lockdown period as compared to the post-lockdown period. The metals Al, Cr, and Fe show the highest increasing trends in the unlocking period, whereas As, Cd, Pb, Cu, Hg, Mn, and Zn show very little variation during the running and post-lockdown phases. The lichen photosynthetic activity justifies further examination as initial biological indicators of the abrupt environmental variations prompted by such types of atmospheric situations and, to a greater extent, for the risk assessment in the near future. In conclusion, stress-phytohormone and amino acids play a significant role as stress reducers. Although lichens are well known for long environmental assessment, the present study will provide qualitative and quantitative variation in physiochemical changes in the short term and sudden environmental fluctuations.Highlights• Qualitative and quantitative variation in biochemical parameters in lichen during and post-lockdown period was analyzed.• Stress-phytohormone and amino acids play a significant role as stress reducers.• Selectivity sequence reflection in heavy metal accumulation may be used in future studies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00484-022-02386-z.

Measuring soil pH at in situ like conditions using optical pH sensors (pH-optodes)

Soil pH is undoubtedly one of the key environmental parameters influencing soil biology and biogeochemistry. Nevertheless, measuring soil pH at in situ like conditions is not trivial. The current gold standard requires preparing a soil suspension with water or CaCl2, in which the soil pH can be assessed. Obviously, this is far from in situ conditions. In this study we evaluate optical pH sensors, so-called pH optodes, as an alternative technology to measure soil pH both in wet and dry soils. Our results indicate that pH optodes have the potential to sense soil pH in a wide range of soil water contents. We also compared our results to the standard slurry method and to measurements using a classical glass pH electrode.

Comparing Modelling and Experiments for Prediction of Atmospheric Corrosion Under Controlled Dynamic Thin Film and Droplet Electrolytes

Corrosion prediction by multiscale modelling aims to achieve the required paradigm shift in the lifetime prediction of metals. Modelling of atmospheric corrosion, for example, based on Finite Element Modelling (FEM) requires an exact description of the boundary region between metal and electrolyte. This requires a radically different research approach for the electrolyte in contact with the metal surface. The critical issue is that most corrosion experiments in fundamental research are performed “in solution” under the assumption that the electrolyte layer is thick enough to approximate it as “infinite”, ignoring significant local effects introduced by dynamic electrolyte dimensions caused by droplets and puddles. In other words, a major part of the research in academia is not relevant to mimic the actual conditions encountered on the metal surface. To create accurate numerical models, we first and foremost needed to abandon this "infinite" and “stationary” approximation and consider dynamic and finite electrolyte dimensions. During atmospheric corrosion of metals, the evolution of the thin-film electrolyte thickness is the primary factor determining the corrosion rate. A full understanding the evolution of the electrolyte thickness and properties as a function of the key environmental parameters is yet to be achieved. A novel methodology has been developed to conduct experiments under a regulated environment to measure the film thickness evolution or individual droplets on an undisturbed metal surface [1]. Experimental results are compared with FEM models predicting both the electrolyte formation as well as the related corrosion. The heat transfer coefficient is noted as a critical parameter influencing both the film characteristics and the resulting corrosion rate. This model was tested in case of cut-edge corrosion of galvanized steel. Combining the in-house MiTReM (Multi ion Transfer Reaction electrochemical model) with the electrolyte film thickness model, we could see that the corrosion rates become very critical in the range of 20 µm [2]. The next step was to go into the dimension of droplets. A thorough literature review [3] was made and published around modelling of droplet formation and corrosion, forming a base for further progress and improvements. The literature study also highlighted that the topic of droplet formation is relatively new within the corrosion research community. A new approach [4] was proposed to numerically predict and study atmospheric corrosion under droplet size distributions. The proposed methodology allows for a corrosion prediction based on observed droplet size distributions and droplet contact angles. A mechanistic finite element model, including oxygen transport and Butler-Volmer kinetics, is solved to obtain the current density for the droplet geometry. This is done for a range of both droplet radii and contact angles. The computed corrosion current densities are then adapted onto imposed droplet distributions for a calculation of overall corrosion current. This allows for a calculated material loss estimation for different distributions and electrolyte configurations and shows the extent of the impact of the droplet distribution on atmospheric corrosion. This model is validated by comparing with experiments introducing droplet-induced corrosion in a lab scale reactor that allows monitoring in parallel droplet geometry and corrosion as function of induced thermal cycles in a controlled atmosphere. Keywords: Atmospheric corrosion, FEM modelling, thin electrolyte films, droplets

Plant Carbon Sources for Denitrification Enhancement and Its Mechanism in Constructed Wetlands: A Review

Nitrogen pollution in water bodies is a serious environmental problem worldwide. Plant carbonsource (PCS) enhanced denitrification in constructed wetlands (CWs) for wastewater with low chemical oxygen demand to total nitrogen (COD/N) has been one of the most exciting research topics. This paper summarized the related studies with VOSviewer software and found that the major interests were denitrification performance and mechanism in CWs. This article mainly focused on the PCSs’ characteristics, denitrification rate, the influences of key environmental and operational parameters, surface morphology variation, microbial community structure, and denitrification genes. Engineering prospects and existing problems were also introduced. PCSs’ degradation consumes DO and creates favorable conditions for denitrification. The COD/N of wastewater should be maintained at 4–5 by adding PCSs, thus improving denitrification performance and reducing nitrous oxide emission. Aerobic degradation, anaerobic fermentation, dissimilatory nitrate reduction to ammonium, and sulfate reduction processes may consume the carbon released by PCSs depending on the influent quality and environmental conditions. More attention should be paid to the reduction of greenhouse gases and emerging pollutants in CWs with PCSs.

Co-transport of less soluble accessory minerals during expansion of compacted bentonite and its impacts on erosion

Compacted bentonite is considered as an engineered barrier in geological disposal of nuclear waste in fractured rocks. One concern with this concept is that the expansion of bentonite into fractures as the system saturates may lead to its erosion by flowing water. The loss of bentonite through erosion over long times may compromise the barrier. Commercial bentonite contains less soluble accessory minerals and experimental observations have shown that these are co-transported with clay minerals during expansion and form a mineral film at the eroding boundary. Quantifying the effects of the mineral film on the erosion rate is important for the assessment of the long-term sealing capacity of bentonite barriers. The paper presents a model for the extrusion of bentonite into fractures that considers key processes governing the co-transport of less soluble accessory minerals and explains why and where the mineral film forms and how it affects the erosion rate.The model is tested against two sets of published experimental data. It is demonstrated that the model predicts the phenomena observed in experiments: the build-up of a mineral film near the extrusion boundary; and the progressive growth of the mineral film thickness. Importantly, the model allows for investigating the effects of key environmental and material parameters – water chemistry, filtration coefficient, and mineral fraction – on the expansion and erosion. The results of such investigations are presented. It is shown that higher water ion concentration, larger filtration coefficient, and larger fraction of accessory minerals retard the swelling and extrusion of bentonite, thus reducing the overall erodibility. It is further shown that the presence of less soluble accessory minerals may reduce the loss of bentonite by a factor of 2 compared to a pure bentonite.

Water quality assessment and the influence of landscape metrics at multiple scales in Poyang Lake basin

Stream water quality has been increasingly deteriorated in recent decades because of anthropogenic activities. Assessing water quality via key environmental parameters and quantifying the respective influence of landscape metrics like landscape configuration, land use composition and topography, which can overall represent anthropogenic activities, can facilitate the development of improved water quality management strategies. However, few studies concentrate on the quantitative effect of these landscape metrics groups on the change of key water quality parameters. In this study, with Poyang Lake basin, we selected key factors of the 14 environmental variables for the cost-effective water quality evaluation model of the minimum water quality index (WQImin) by the random forest method and quantified the contribution of different groups of landscape metrics on key water quality parameters by redundancy analysis and variance partitioning analysis. The results indicated that six water quality parameters of ammonium (NH4+-N), total nitrogen (TN), permanganate index (CODMn), dissolved oxygen (DO), fecal coliforms (F.coli) and total phosphorus (TP) can significantly represent the overall water quality of the Poyang Lake basin. Based on WQImin, the water quality of Fuhe River and Xiushui River was significantly better than that of Ganjiang River, Raohe River, and Xinjiang River in Poyang Lake basin. The contribution of landscape metrics to water quality variation followed the order of landscape configuration (19.0–22.5%) > land use composition (5.2–20.2%) > topography (5.7–8.0%). Here, Build-up land was the environmental factor contributing most significantly to the variation in water quality at both spatial and seasonal scales (5.7–21%). Build-up land, Agricultural land, Contagion index and Cohesion index were positively correlated with TN, TP, CODMn, and NH4+-N and negatively with DO at different scales; Grassland, Forest land, Hypsometric Integral index, Slope, and Mean Shape index showed the opposite relationship. The influence of these landscape types changed with spatial and seasonal scales, more significantly explaining variations in water quality during the dry season and at buffer scale. Changes in water quality at the spatial scale were most sensitive to land use composition. Our results represent a basis for the improvement of water quality management.

Occurrence of Phthalate Acid Esters (PAEs) in Protected Agriculture Soils and Implications for Human Health Exposure.

This study explored occurrence of phthalic acid esters (PAEs) in protected agriculture soils and assessed their potential health risks to humans. Results showed that DEHP and DBP were the most abundant PAEs congeners, with mean concentrations of 318.68μg/kg and 137.56μg/kg, respectively. DOP and BBP concentrations were relatively low, and DMP and DEP were not detected in all samples. DBP concentrations were higher than the allowable concentration standard value. Additionally, soil pH and organic matter were key environmental parameters which may play the vital roles to the occurrence of organic pollutants. Heath risk assessment results indicated that dermal contact was the predominant human exposure route under non-dietary conditions, and children obtained higher health risk scores than adults. In summary, the overall health risk scores were at an acceptable level. These results provide insights for assessing soil environmental safety and ecological risks in protected agricultural soil.

Is It the Same Every Summer for the Euphausiids of the Ross Sea?

The pelagic ecosystem in the Ross Sea has one central component that is very important for energy exchanges between upper and lower trophic levels: the Middle Trophic Level. Krill species are the most important and abundant organisms within this level. Several acoustic surveys were conducted in the western Ross Sea over the past 25 years, revealing that Euphausia superba is by far the most abundant species of krill in the Ross Sea during austral summer, and that its core distribution is concentrated in the northern part, bordering the Southern Ocean. Euphausia crsytallorophias, the second most abundant krill species, is more concentrated in the central Ross Sea, generally near the coast. Data on krill biomass were collected in December and January from 1994 to 2016 and analyzed together with key environmental parameters by means of two-way ANOVA in order to explain species behavior and identify possible environmental drivers. Temperature and dissolved oxygen influenced the biomass of both species of krill, while other environmental parameters only affected one species. In conclusion, the biomass of both species has varied over the years, possibly due to a complex synergy of environmental drivers.

Prototyping an IoT-based system for monitoring building indoor environment

PurposeThis study aims to develop an architectural prototype of a Cyber-Physical System (CPS), as well as lay a technological foundation for future smart housing with improved health and well-being outcomes for its occupants.Design/methodology/approachThis study deploys smart sensors to monitor the key environmental parameters of a house. Using Internet of Things technology, a prototype of a CPS has been developed for capturing the environmental conditions over time. A case study involving a property in New Zealand was undertaken to validate the prototype.FindingsThe study proposes a monitoring platform, enabled by the CPS and smart sensing devices, that collects, shares, stores, analyses and visualises indoor environment data. The reliability and accuracy of the monitoring system were enhanced by comparing the activity of house occupants with sensor data.Research limitations/implicationsDue to limited time, the prototype was tested in one house for a period of one month. Air quality was not considered in this study. However, the work suggests that such an approach provides an effective solution for government organisations and housing agencies to collect information for the purpose of assessing building thermal performance.Originality/valueThis research proposes a new lens consisting of a home environment monitoring application with health and well-being implications. It could also be used to inform the future design of healthy homes and buildings, both in New Zealand and internationally.

Seasonal Changes in Shell Microstructure of Some Common Bivalve Molluscs in the Mid-Atlantic Region

Bivalve molluscs record histories of individual growth as alternating periods of activity (shell deposition) and inactivity (growth cessation marks) within their multilayered shells, and in some species, as alternating sublayers with different morphology. Shell growth patterns reflect tidal, daily, and seasonal cycles of key environmental parameters, such as submergence and temperature, which influence physiology (e.g., feeding, respiration, metabolic rates, and reproductive cycles). Knowledge of the periodicity of formation of various structures within the shell enables researchers to place a calendar across the growth history of an animal knowing only the date of collection. In turn, this enables both the determination of age (essential in studies of population dynamics) and the assessment of how bivalve populations responded to known environmental events, be they anthropogenic or natural, after the event has occurred. Seasonal microstructural shell growth patterns of six common bivalve species living in fresh (Corbicula fluminea O. F. Müller, 1774), brackish (Rangia cuneata G. B. Sowerby I, 1832), lower estuarine (Geukensia demissa Dillwyn, 1817), coastal (Mytilus edulis Linnaeus, 1758 and Mya arenaria Linnaeus, 1758), and continental shelf (Spisula solidissima Dillwyn, 1817) habitats in the mid-Atlantic region of the United States are documented using optical and scanning electron microscopy based on collections in the late 1980s. Some of the works have been published previously, but the results for each of the six species are combined and summarized in one volume as a guide to the seasonal shell microstructure for some common bivalves in New Jersey waters. The utility of shell growth pattern analysis in environmental impact assessments and population dynamics studies is evaluated within each habitat and example applications are provided. Although the results reported here were from studies conducted over 30 y ago, they represent collectively a contribution to our knowledge of molluscan shell microstructure that remain relevant today and are published as a coherent monograph before they are lost as so many other important unpublished works have been as time ran out on aging authors before they could relay the precious secrets they uncovered over the years.

Meta-analysis of diazotrophic signatures across terrestrial ecosystems at the continental scale.

Biological nitrogen fixation performed by diazotrophs forms a cornerstone of Earth's terrestrial ecosystem productivity. However, the composition, diversity and distribution of soil diazotrophs are poorly understood across different soil ecosystems. Furthermore, the biological potential of the key diazotroph species in relation to key environmental parameters is unknown. To address this, we used meta-analysis approach to merge together 39 independent diazotroph amplicon sequencing (nifH gene) datasets consisting of 1988 independent soil samples. We then employed multiple statistical analyses and machine-learning approaches to compare diazotroph community differences and indicator species between terrestrial ecosystems on a global scale. The distribution, composition and structure of diazotroph communities varied across seven different terrestrial ecosystems, with community composition exhibiting an especially clear effect. The Cyanobacteria were the most abundant taxa in crust ecosystems (accounting for ~45% of diazotrophs), while other terrestrial ecosystems were dominated by Proteobacteria, including Alpha-, Beta- and Gamma-Proteobacteria (accounting for ~70% of diazotrophs). Farmland ecosystems harboured the highest and crust ecosystems the lowest alpha and phylogenetic diversities. Azospirillum zeae, Skermanella aerolata and four Bradyrhizobium species were identified as key indicator species of potential diazotroph activity. Overall, diazotroph abundances and distribution were affected by multiple environmental parameters, including soil pH, nitrogen, organic carbon, C:N ratio and annual mean precipitation and temperature. Together, our findings suggest that based on the relative abundance and diversity of nifH marker gene, diazotrophs have adapted to a range of environmental niches globally.

Spatiotemporal quantification of key environmental changes in Stok and Kang Yatze regions of Ladakh Himalaya, India

Tourism fuelled economic transformation of Ladakh region is bringing a change in demography and livelihood preferences leading to increased exploitation of scarce natural resources. In addition to the nerve centre of tourism-related activities (Leh city), rural hinterlands of Ladakh are also witnessing a stark transformation in land and resource use patterns. In this study, we quantified and assessed the changes in key environmental parameters of rural Ladakh between 1969 and 2020. We observed a decrease in glacier area, glacier volume and vegetation cover by approximately 19%, 13% and 14%, whereas built-up and lake area increased by approximately 238% and 122%, respectively. Simultaneously, local population of the region doubled while tourism footprint increased by approximately 620-folds. The study highlights the environmental changes happening at a higher rate in rural regions around Leh city. Therefore, need of the hour is to recognize the disruptive changes being brought in the traditional way of life and to devise strategies to reorient the development paradigm towards sustainable resource use and management.