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Environmental flow (e-flow) decision making relies on flow-ecology models to predict ecological outcomes under different flow regimes. While expert knowledge has traditionally informed these models, there is increasing use of data-driven approaches. We investigated data integration for Bayesian conditional probability networks (CPNs) developed through expert elicitation in an e-flows assessment in Victoria, Australia. Using synthetic datasets based on monitoring data, we assessed the impact of varying data characteristics on model outcomes. Incorporating 10 years of data had the greatest influence on model predictions compared to the expert-based models, with diminishing additional effect for longer records. Notably, the expert model based on the most non-conforming expert opinion was more sensitive to data integration than a model based on harnessing the opinion of all experts, highlighting the importance of considering diverse experiential knowledge. We provide recommendations on leveraging limited datasets and models to guide efficient monitoring and management. • Exploration of a method to incorporate monitoring data into expert-opinion built Bayesian CPNs. • Synthetic data records of varying characteristics were used to assess impact on model outcomes. • Demonstrate that complementary use of expert opinion and empirical data can enrich modeling approaches. • Monitoring data can complement expert elicitation in models to assess uncertainty and direct management efforts. [ABSTRACT FROM AUTHOR]

• Vegetation Quality Assessment measures losses and gains in vegetation quality and extent. • An objective, repeatable workflow for quantifying impacts and monitoring restoration progress. • Stratified-random sampling reduces bias and enables estimation of error and uncertainty. • Quality measured by overlap between indicator distributions in impacted and undisturbed vegetation. • Distribution overlap provides a novel and intuitive index of similarity to benchmark. Governments and society increasingly are demanding that industrial projects result in a net positive impact (NPI) on biodiversity. Impacts are commonly measured in terms of losses and gains of area and quality of vegetation, where quality refers to how closely a site matches the condition of native vegetation in its undisturbed state. Existing vegetation quality frameworks share a number of limitations, including little or no replication, uncertain scope of inference, vulnerability to bias, and inability to measure error. Here we present the Vegetation Quality Assessment (VQA) framework, a sampling-based extension of Quality Hectares that measures vegetation quality in terms of overlap between the probability distributions of ecological indicators at a project site and in undisturbed (benchmark) vegetation of the same kind. Distribution overlap incorporates natural variation at the landscape scale and provides an intuitive measure of quality that varies between 0 and 1. Indicators are measured using a stratified-random sampling design that minimizes bias and supports inference at the scale of the project landscape. Confidence limits of quality and quality hectares are determined by bootstrapping; power and minimum sample sizes are estimated by Monte Carlo simulation. Multiple assessments track losses and gains of quality hectares and enable accurate accounting of progress to NPI. The VQA framework can be implemented using a variety of vegetation sampling methods, allowing existing vegetation databases to be leveraged as sources of data. We conclude by demonstrating the application of VQA at several mining operations in the Elk Valley of southeastern British Columbia, Canada. [ABSTRACT FROM AUTHOR]

The Arctic is under great pressure due to climate change. Drones are increasingly used as a tool in ecology and may be especially valuable in rapidly changing and remote landscapes, as can be found in the Arctic. For effective applications of drones, decisions of both ecological and technical character are needed. Here, we provide our method planning workflow for generating ground-cover maps with drones for ecological monitoring purposes. The workflow includes the selection of variables, layer resolutions, ground-cover classes and the development and validation of models. We implemented this workflow in a case study of the Arctic tundra to develop vegetation maps, including disturbed vegetation, at three study sites in Svalbard. For each site, we generated a high-resolution map of tundra vegetation using supervised random forest (RF) classifiers based on four spectral bands, the normalized difference vegetation index (NDVI) and three types of terrain variables—all derived from drone imagery. Our classifiers distinguished up to 15 different ground-cover classes, including two classes that identify vegetation state changes due to disturbance caused by herbivory (i.e., goose grubbing) and winter damage (i.e., ‘rain-on-snow’ and thaw-freeze). Areas classified as goose grubbing or winter damage had lower NDVI values than their undisturbed counterparts. The predictive ability of site-specific RF models was good (macro-F1 scores between 83% and 85%), but the area of the grubbing class was overestimated in parts of the moss tundra. A direct transfer of the models between study sites was not possible (macro-F1 scores under 50%). We show that drone image analysis can be an asset for studying future vegetation state changes on local scales in Arctic tundra ecosystems and encourage ecologists to use our tailored workflow to integrate drone mapping into long-term monitoring programs.

An automatic hydro-meteorological station (AHMS) was designed to monitor the littoral zone of Lake Baikal in areas with high anthropogenic pressure. The developed AHMS was installed near the Bolshiye Koty settlement (southern basin). This AHMS is the first experience focused on obtaining the necessary competencies for the development of a monitoring network of the Baikal natural territory. To increase the flexibility of adjustment and repeatability, we developed AHMS as a low-cost modular system. AHMS is equipped with a weather station and sensors measuring water temperature, pH, dissolved oxygen, redox potential, conductivity, chlorophyll-a, and turbidity. This article describes the main AHMS functions (hardware and software) and measures taken to ensure data quality control. We present the results of the first two periods of its operation. The data acquired during this periods have demonstrated that, to obtain accurate measurements and to detect and correct errors that were mainly due to biofouling of the sensors and calibration bias, a correlation between AHMS and laboratory studies is necessary for parameters such as pH and chlorophyll-a. The gained experience should become the basis for the further development of the monitoring network of the Baikal natural territory.

Regardless of the efforts of the European Union, freshwaters are in a state of environmental crisis. The Water Framework Directive has established a basis for the protection and restoration of European inland and coastal waters. In parallel, the Birds and Habitats Directives protect, maintain or restore, at favourable conservation status, selected species and habitats under a representative network of protected areas. Hence, the interplay between the EU regulations is of high scientific interest and practical relevance. In this article, Greece is used as a case study to explore whether anticipated synergies between the Water Framework Directive and the Nature Directives result in a better ecological status in the protected areas than in the non-protected ones. We investigated whether the ecological qualities that are defined by three biological quality elements (BQEs) differ between the WFD monitoring sites that are located within the Natura 2000 protected areas and those that are not. We identified a total of 148 river monitoring sites that are located within the Natura 2000 network, which corresponds to 30% of the WFD monitoring network. By employing ordered logit models for each BQE, we found that the ecological quality has the same likelihood to fail the WFD target of “good” quality for sites that are located within and outside the Natura 2000 protected areas. Our results confirmed our hypothesis that the EU directives have little synergy when it comes to restoration of ecological status of Greek running waters, according to the WFD.

Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analysis, and testing of acoustic arrays for localizing acorn woodpeckers using their vocalizations. Each acoustic array consists of four microphones arranged in a square. All four audio channels within the same acoustic array are finely synchronized within a few micro seconds. We apply the approximate maximum likelihood (AML) method to synchronized audio channels of each acoustic array for estimating the direction-of-arrival (DOA) of woodpecker vocalizations. The woodpecker location is estimated by applying least square (LS) methods to DOA bearing crossings of multiple acoustic arrays. We have revealed the critical relation between microphone spacing of acoustic arrays and robustness of beamforming of woodpecker vocalizations. Woodpecker localization experiments using robust array element spacing in different types of environments are conducted and compared. Practical issues about calibration of acoustic array orientation are also discussed.

Introduction. The article presents the issue of improving soil quality continues needs to be urgent. In particular, the task of improving the quality of agricultural land and considering the qualitative characteristics as an object of management remains unresolved, which necessitates further systematic research in this direction. Aim and tasks. The purpose of the article is to substantiate the essence of soil quality management, the creation of land masses with appropriate soil characteristics as a means of obtaining safe products of standardized quality, maintaining the quality of the natural environment, preventing its degradation and using innovative industrial technologies in alternative agricultural systems. The task is in the justification that qualitative soil properties and fertility are inextricably linked. Research results. The processes of soil formation and soil fertility are determined by a number of natural factors and the nature of economic activity, which affects not only the arable layer but also deeper soil horizons, as well as groundwater and groundwater. The optimal parameters of fertility indices should be established for each type of soil, if they can vary according to the fertility patterns as a combination of soil properties and modes that ensure the productivity of the land, the high quality and safety of the agricultural products derived from them. Returning lands to their original state is not always possible, but it is necessary. The application of certain approaches and technologies of updating the qualitative state of agricultural land causes the formation of conditionally clean land masses among those who potentially can become, after a certain time, suitable for obtaining safe production products. Ecologically clean land massifs, regardless of the degree of environmental readiness for economic use, are spatially limited, artificially created territories, the peculiar feature of which is the minimal cultivation of soil, the compliance with ampeloecological and agroecological requirements of cultivating those or other crops, the presence of indicator plants regulating contamination, the remoteness from pollutants, control of all agrotechnical measures, preservation and regulation of soil fertility. Conclusion. To achieve ecological purity is possible through a variety of activities. Land massifs with special characteristics play an important role and have a close connection with modern agrotechnologies that differ from agrotechnical measures, with a more systematic and more closely related to the microperiods of agricultural crop development. It is determined that the management of ecological agriculture will facilitate the creation of land uses with special characteristics, which are achieved through the implementation of the general laws of agriculture and a number of principles, among which the principles of environmental orientation are combined with the principles that facilitate their implementation.

Aim. Environment quality estimation and its probable changes in the presence of anthropogenous influence on the Tatarstan republic natural reserved fond objects with fluctuating asymmetry method on different species of organisms was carried out.Methods. Gathering of scientific material was carried out at the 2012-2013 years period at the natural reserved fond objects territory – Tatarstan republic state natural complex wildlife areas. For land ecosystems estimation the morphometric parameters of birch leafs was used, for water ecosystems characteristic – the morphometric parameters of most ordinary species of fish (small fry, golden crucian, bream) and amphibians (pond and lake frog). Morphometric measurements results of indicator organisms was statistically processed, fluctuating asymmetry parameter was calculated, according received results the state of ecosystems was estimated.Results. The state of some especially protected natural areas at the Tatarstan republic was estimated. Applicability of fluctuating asymmetry parameter for complex ecosystem estimation was proved. Received results can be used as a matter for ecological risk estimation methodic developing for Tatarstan republic territory.Main conclusions. The investigated areas ecological status was estimated as “relatively normal”. The fluctuating asymmetry parameter in similar conditions for phytoindicator was higher than for zooindicators Results analysis was shown the need of using different indicators for complex characteristic of environmental quality.

The study was conducted to evaluate dynamics of air pollution during inhalational anaesthesia with sevoflurane in In Vitro Fertilization. Measurements of volatile organic compounds (VOC) were performed using portable photoionization gas analyzer in 5 areas of operating room during 7 working days and near the patient’s head and in the location of anaesthesia apparatus during 14 days without additional air cleaning. Then we used air carbone filter and measured VOC during next 14 days (49 anaesthesias altogether). Maximal air pollution was detected in the awakening period. There were no VOC traces in the area of embryologist during all periods of inhalational anaesthesia. It was shown that air pollution level reduced significantly after air carbone filter installation.

Abstract Organizations tasked with implementing long‐term ecological monitoring programs often struggle to stay funded. Government agencies are typically the only entities with sufficient capacity and motivation to support long‐term scientific programs that generate data for environmental management and conservation. Taxpayers bear this funding burden, yet we know of no studies assessing public perception of government‐led long‐term monitoring. We present the results of a survey designed to assess willingness to pay (WTP) for the benefits resulting from long‐term ecological monitoring in Southeast Alaska for residents and visitors. We hypothesized that four factors have the potential to influence preferences for long‐term ecological monitoring: (1) type of ecosystem service monitored (intermediate vs. final); (2) place of residence; (3) prior knowledge of monitoring; and (4) sociodemographic characteristics. We defined final ecosystem services as ecosystem attributes that have clear relevance to human well‐being and intermediate ecosystem services as those required to produce final services. We found a greater WTP for programs monitoring intermediate ecosystem services, longer‐running programs, and programs covering a larger spatial extent. Respondents with higher income and conservative political preferences were more likely to choose no monitoring program at all (status quo), whereas respondents with previous knowledge of monitoring were generally more supportive of long‐term monitoring programs.

Coral reefs are exceptionally biodiverse and human dependence on their ecosystem services is high. Reefs experience significant direct and indirect anthropogenic pressures, and provide a sensitive indicator of coastal ocean health, climate change, and ocean acidification, with associated implications for society. Monitoring coral reef status and trends is essential to better inform science, management and policy, but the projected collapse of reef systems within a few decades makes the provision of accurate and actionable monitoring data urgent. The Global Coral Reef Monitoring Network has been the foundation for global reporting on coral reefs for two decades, and is entering into a new phase with improved operational and data standards incorporating the Essential Ocean Variables (EOVs) (www.goosocean.org/eov) and Framework for Ocean Observing developed by the Global Ocean Observing System. Three EOVs provide a robust description of reef health: hard coral cover and composition, macro-algal canopy cover, and fish diversity and abundance. A data quality model based on comprehensive metadata has been designed to facilitate maximum global coverage of coral reef data, and tangible steps to track capacity building. Improved monitoring of events such as mass bleaching and disease outbreaks, citizen science, and socio-economic monitoring have the potential to greatly improve the relevance of monitoring to managers and stakeholders, and to address the complex and multi- dimensional interactions between reefs and people. A new generation of autonomous vehicles (underwater, surface, and aerial) and satellites are set to revolutionize and vastly expand our understanding of coral reefs. Promising approaches include Structure from Motion image processing, and acoustic techniques. Across all systems, curation of data in linked and open online databases, with an open data culture to maximize benefits from data integration, and empowering users to take action, are priorities. Action in the next decade will be essential to mitigate the impacts on coral reefs from warming temperatures, through local management and informing national and international obligations, particularly in the context of the Sustainable Development Goals, climate action, and the role of coral reefs as a global indicator. Mobilizing data to help drive the needed behavior change is a top priority for coral reef observing systems.

Based on the characteristics of remote sensing images of mine vegetation, this research studied the application of deep belief network model in mine vegetation identification. Through vegetation identification and classification, the ecological environment index of mining area was determined according to the analysis of vegetation and coverage. Deep learning algorithm is adopted to improve the depth study, the vegetation coverage in the analysis was studied. Parameters and parameter values were selected for identification by establishing the optimal experimental design. The experimental results were compared with remote sensing images to determine the accuracy of deep learning identification and the effectiveness of the algorithm. When the sample size is 2,000,000 pixels, through repeated tests and classification effect comparison, the optimal parameter setting suitable for mine vegetation identification is obtained. Parameter setting: the number of network layers is 3 layers; the number of hidden layer neurons is 60. The learning rate is 0.01 and the number of iterations is 2. The average recognition rate of vegetation coverage was 95.95%, outperforming some other models, and the accuracy rate of kappa coefficient was 0.95, which can accurately reflect the vegetation coverage. The clearer the satellite image is, the more accurate the recognition result is, and the accuracy is closer to 100%. The identification of vegetation coverage has important guiding significance for determining the area and area of ecological restoration.

An important requirement towards formulating appropriate management and conservation measures for biological diversity is to devise efficient and cost-effective monitoring protocols that yield coherent data. Environmental monitoring investigations have been typically based on species level responses of biodiversity to environmental disturbances. Considering that this exercise is cost-intensive and the species identification keys are unavailable for some geographical areas, efforts are now afoot to test the efficacy of supra-specific taxa in resolving distribution patterns of biota, analogous to that of species. This study was aimed at testing the efficacy of Taxonomic Sufficiency (TS), a data reduction technique, in deciphering spatio-temporal variations of macrobenthos in the tropical coastal waters of northwest India. The macrobenthic indicator taxon, Polychaeta, was analyzed at five transects that included two marine protected areas, during the three major seasons. The consistency of spatio-temporal trends of polychaete assemblages, derived from four taxonomic levels and subjected to five types of data transformation was scrutinized. Univariate indices indicated that coarser taxonomic levels except order, maintained the indicative responses spatio-temporally, similar to the species level. Spatial variability was appropriately indicated by all data matrices. Temporal variation was evident only with family data subjected to fourth root or log data transformations. The TS approach succeeded in this tropical ecoregion owing to the consistent and sizable proportion of monotypic polychaete taxon and uniformity in responses of the constituents of higher polychaete taxon. CCA results revealed that a similar set of environmental variables influenced the polychaete distribution at all the taxonomic levels; however, spatial variations detected at species level diminished with reduced taxonomic breadth. Results indicated that meaningful robust data for deriving coastal management initiatives can be achieved cost-effectively by the adoption of TS approach for the ecologically and economically important 2360 km long northwest Indian coastline. • Applicability of TS was tested using polychaetes in northwest Indian coastal waters. • Coarser taxonomic analysis upto family level was reliable proxy for species. • Fourth root and log data transformations performed better than the extremities. • Similar environmental variables were identified by CCA at all taxonomic levels. • Spatial variations were diminished at higher taxonomic levels in the ordination plots. [ABSTRACT FROM AUTHOR]

Tree survival is a performance metric for urban forestry initiatives, and an understanding of the factors that influence mortality can help managers target resources and enhance survival. Furthermore, urban tree planting investments depend on tree survival to maximize ecosystem services. In this literature review, we categorized factors commonly associated with urban tree mortality and summarized mortality rates published in 56 studies, focusing on studies of trees along streets, in yards, and in landscaped parks. Study designs included quantitative field monitoring of uneven-aged tree populations and tracking planting cohorts of even-aged trees, as well as qualitative analyses. Annual mortality rates ranged from 0.6 to 68.5% for cohort studies and 0 to 30% for repeated inventories of uneven-aged trees. The 1st, 2nd, and 3rd quartiles of annual mortality were 2.8 to 3.8%, 4.4 to 6.5%, and 7.1 to 9.3% for planting cohorts, and 1.6%, 2.3 to 2.6%, and 3.0 to 3.3% for repeated inventories of uneven-aged trees (ranges reflect studies that reported a range for the time period or mortality rate). For cohort studies, annual mortality tended to be highest during the first five years after planting. The most commonly cited biophysical factors associated with mortality were taxa (15 articles), tree size/age (13 articles), and site characteristics (12 articles). The most commonly cited human-related factors were stewardship, maintenance, and vandalism (15 articles). More long-term studies are needed to investigate how site characteristics influence mortality, including rarely examined soil and microclimate characteristics. Future research should also examine institutional structures related to mortality outcomes, as well as parcel-level sociodemographic factors and resident behaviors. [ABSTRACT FROM AUTHOR]

The frequency and duration of episodic ocean warming events are increasing, threatening the integrity of coral reefs globally. Interspecific differences in susceptibility to heat stress result from variable capacities of corals to resist bleaching or to persist in a bleached state. During shorter bleaching events, stress responses occur rapidly and the "window" for detecting bleaching is tightly constrained. However, during longer bleaching events, we argue that the timing of surveys can radically influence results, which need to be interpreted with care. For example, although "heat-resistant" corals may survive prolonged bleaching events, they have a greater chance of being recorded as having bleached because they can persist for longer in a bleached state. This could lead to erroneous conclusions about their vulnerability to heat stress compared with taxa that bleach and die rapidly. Therefore, as bleaching events lengthen, it is vital to consider not only temperature at the time of sampling, but also the accumulation of heat stress over the entire warming event. We present a simplified conceptual framework and an example from the Central Pacific to emphasize the importance of survey timing to perceived susceptibility of coral taxa to bleaching. [ABSTRACT FROM AUTHOR]

During long-term monitoring, protocols suitable in the initial context may have to change afterward because of unforeseen events. The outcome for management can be important if the consequences of changing protocols are not understood. In Tuamotu Archipelago atolls, French Polynesia, the density of giant clams (Tridacna maxima) has been monitored for 12 years, but massive mortalities and collapsing densities forced to shift from a line-intercept transects and quadrats (LIT-Q) method to a belt-transect (BT) method. We investigated with a simulation approach the conditions (density, size structure, aggregation of giant clam populations) under which the two methods provided different results. A statistical model relating the BT density to the LIT-Q density was validated using new field data acquired on the same sites with both protocols, on two atolls. The BT method usually provided higher estimates of density than the LIT-Q method, but the opposite was found for very high densities. The shape of the relationship between measurements depended on population size structure and on aggregation. Revisiting with the model the historical LIT-Q densities suggested that densities have been underestimated in the past but previously detected trends in population trajectories remained valid. The implication of these findings for management are discussed. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems constitute only a small fraction of the planet's water resources, yet support much of its diversity, with freshwater fish accounting for more species than birds, mammals, amphibians or reptiles. Fresh waters are, however, particularly vulnerable to anthropogenic impacts, including habitat loss, climate and land use change, pollution and biological invasions. This environmental degradation, combined with unprecedented rates of biodiversity change, highlights the importance of robust and replicable programmes to monitor freshwater fish. Such monitoring programmes can have diverse aims, including confirming the presence of a single species (e.g., early detection of alien species), tracking changes in the abundance of threatened species, or documenting long‐term temporal changes in entire communities. Irrespective of their motivation, monitoring programmes are only fit for purpose if they have clearly articulated aims and collect data that can meet those aims. This review, therefore, highlights the importance of identifying the key aims in monitoring programmes and outlines the different methods of sampling freshwater fish that can be used to meet these aims. We emphasize that investigators must address issues around sampling design, statistical power, species' detectability, taxonomy and ethics in their monitoring programmes. Additionally, programmes must ensure that high‐quality monitoring data are properly curated and deposited in repositories that will endure. Through fostering improved practice in freshwater fish monitoring, this review aims to help programmes improve understanding of the processes that shape the Earth's freshwater ecosystems and help protect these systems in face of rapid environmental change. [ABSTRACT FROM AUTHOR]

We present the results of devising new techniques and technical means for utilizing small-sized unmanned aerial vehicles (UAVs) in ecological monitoring of marine water basins in compliance with the MARPOL 73/78 international convention. The development of a hardware-software complex is described for the system of recognizing oil spills using elements of artificial intelligence. The laboratory experiments on identifying oil spills by laser induced fluorescence (LIF) methods are presented, as well as the methods of recording the spectrum of upward solar radiation. [ABSTRACT FROM AUTHOR]

Highlights • Adjusted FQAI can be employed successfully for evaluating arid ecosystems ecological condition. • Adjusted FQAI signals anthropogenic disturbance in arid ecosystems more than the other variants of floristic quality indices. • The anthropogenic disturbance index provide a quantitative measure to relatively compare disturbance levels among sites. • The use of multiple bioindicators in site assessments is key for comprehensive appraisal of ecological conditions. Abstract Northwestern coastal desert of Egypt is under pressure of human-induced changes due urban sprawl and agricultural practices leading to negative impacts on existing natural habitats. Assessing the impact of land-use changes on the ecological integrity is crucial for management and conservation efforts in the region. Floristic quality (FQ) assessment indices are important bioassessment tools that can be used to evaluate how anthropogenic changes may influence vegetation quality, species composition and environmental integrity. The approach is primarily stationed on floristic composition and disturbance tolerance at study sites. The objectives of this study were to: 1) study how anthropogenic disturbances due to land use/cover changes in the northwestern coastal desert affected its ecological quality as indicated by FQ indices; and 2) to evaluate the use of FQ indices as tools for characterizing anthropogenic disturbance among the habitats of Mediterranean desert ecosystem. Stands representing the main habitats were surveyed during 2011 through 2015 and data were compared to historic data collected before the developmental activities. The study revealed a trend of decline with time in the floristic quality of the study area as was indicated by floristic quality measures used (mean coefficient of conservatism, FQAI, and adjusted FQAI). Similar trend of decline in native and perennial species richness, and increase in non-native and annual species richness was observed for the period investigated from 1980s to time. At the habitat level, similar trend of decline in the floristic quality was observed, with the current time attaining the least values of FQ indices for all the habitats. The anthropogenic disturbance index (ADI) was developed in the current study as a quantitative measure of the level of disturbance and as an indicator to evaluate site's ecological condition. The ADI exhibited significant negative relationship with the FQ indices, revealing that it can be recognized as useful index of anthropogenic disturbance that would complement the use of FQ indices in evaluating site ecological condition. The high association between ADI and the adjusted FQAI compared to the FQAI, confirms that the former signals the level of disturbance better than later. Although the adjusted FQAI has been developed and used in assessing vegetation quality of wetland, the current study revealed that it can be employed successfully for assessing and monitoring changes in vegetation quality and ecological integrity of deserts and arid ecosystems. For full and comprehensive evaluation of site's ecological condition, the use of multiple bioindicators is recommended. [ABSTRACT FROM AUTHOR]

The paper discusses the technique of environmental condition monitoring based on the phenomenon of nuclear magnetic resonance (NMR). Express control is an integral part of agriculture. It is especially necessary when working on the farm or in the fields. In this case, situations often arise when it is impossible to deliver samples for research in a stationary laboratory (e.g., results are needed immediately or samples can change their properties during transportation). Now, there are many methods for monitoring the states of media in the express mode. Therefore, a brief review of these methods as well as their limitations was carried out. To overcome these limitations, a new technological solution was proposed for the creation of an NMR spectrometer. The proposed compact NMR spectrometer allows measuring the longitudinal and transverse relaxation times of the medium. To enhance its functionality, a new magnetic system and a signal registration circuit have been developed. These improvements allow detection of the NMR signal at different frequencies, thus registering the signal spectrum. With the help of the proposed device, studies of various media have been carried out; the results of these studies are presented. [ABSTRACT FROM AUTHOR]

High‐throughput environmental sensing technologies are increasingly central to global monitoring of the ecological impacts of human activities. In particular, the recent boom in passive acoustic sensors has provided efficient, noninvasive, and taxonomically broad means to study wildlife populations and communities, and monitor their responses to environmental change. However, until recently, technological costs and constraints have largely confined research in passive acoustic monitoring (PAM) to a handful of taxonomic groups (e.g., bats, cetaceans, birds), often in relatively small‐scale, proof‐of‐concept studies.The arrival of low‐cost, open‐source sensors is now rapidly expanding access to PAM technologies, making it vital to evaluate where these tools can contribute to broader efforts in ecology and biodiversity research. Here, we synthesise and critically assess the current emerging opportunities and challenges for PAM for ecological assessment and monitoring of both species populations and communities.We show that terrestrial and marine PAM applications are advancing rapidly, facilitated by emerging sensor hardware, the application of machine learning innovations to automated wildlife call identification, and work towards developing acoustic biodiversity indicators. However, the broader scope of PAM research remains constrained by limited availability of reference sound libraries and open‐source audio processing tools, especially for the tropics, and lack of clarity around the accuracy, transferability and limitations of many analytical methods.In order to improve possibilities for PAM globally, we emphasise the need for collaborative work to develop standardised survey and analysis protocols, publicly archived sound libraries, multiyear audio datasets, and a more robust theoretical and analytical framework for monitoring vocalising animal communities. [ABSTRACT FROM AUTHOR]

The dynamics of oil contamination of profile-differentiated soils of the Precarpathian region in the area of influence of deep wells of the Vilhivska oil exploration area of the Boryslav-Pokuttya oiland- gas bearing area is investigated. The research was conducted during 2007-2016. Soils were tested in the intervals of the distribution of humus-eluviated (H (e) gl), eluvial-humous (Eh (gl)), iluvial (Ih (gl)) horizons, iluviated parent rock (Pigl), and unchanged parent rock (Quaternary sediments) to the depth up to 2.0 m. The concentrations of oil products in pollution sources are analyzed. The zoning of the research territory according to the distribution of elementary geochemical landscapes is carried out. Within the various elementary geochemical landscapes, regularities in the horizontal and radial distribution of oil products have been revealed. The highest pollutants concentration is established in the silts of elementary transsuperaqual landscapes in the number up to 1750 mg/kg. In deeper horizons, the concentration of pollutants decreases nonlinearly, and the dynamics of this process is different in various elementary geochemical landscapes. The dynamics of the change in the oil concentration over time during the 9-year period of field observations were established. In particular, 1.5 years after the drilling operations cessation, the average concentration of oil products in the interval of the humus-eluviated horizon decreased 2.7 times and more than 4 times after 2.5 years. In the interval of the eluv ial-humus horizon, the dynamics of the pollutant concentration change was less intensive, as the processes of desalination and decomposition of oil products were accompanied by the introduction of new pollutant amounts from the upper horizons. Obtained results are unique considering the natural conditions and long duration of the study (9 years). It can be useful in predicting changes in the concentration of oil products in soils, in designing environmental protection measures and civil protection measures. Highlighted in the article, the results of research support and develop the theory of geochemistry of technogenesis, the theory of geochemical landscapes, creating a reliable experimental basis for improving the scientific methods of ecological and crisis monitoring. [ABSTRACT FROM AUTHOR]

Acquisition of air pollution source data is a key part of building ecological monitoring database, and a new data acquisition technology of air pollution source is studied. The problem of locating air pollution sources is modeled as the problem of parameter identification of sparse systems by using the location algorithm based on sparse system identification. The sparse signals are reconstructed by using the least mean square error optimization method of L1 - norm regularization based on incomplete random sampling data, and the air pollution sources are accurately located. The air pollution sources are collected by ZigBee sensor network based on the results of the location of air pollution sources. While describing the hardware working principle of sensor and concentrator nodes, the key functions of data acquisition in ZigBee sensor network are designed. Through the storage table and writing method based on Hbase design, the collected air pollution source data are stored. The results show that the rate of missing report of air pollution source data collected by the research technology is between 0.1% and 1.0%, and the time of using different air pollution source materials is about 50ms. It is a data acquisition technology of air pollution source with high performance. [ABSTRACT FROM AUTHOR]

The research urgency is caused by the trends to find effective ways of crises overcoming, which acquires in the XX1 century global nature due to many factors of human activities that damage the environment. It is established that as a key strategy for solving this problem, the leading position is devoted to the rethinking of the individual ecological culture ethical values, based on the principles of unity of man and the environment; the organization of economic activity on the basis of ethical values of nature management and forecasting the consequences of their behavior for the environment; the recognition of the right of wildlife all kinds to the equal value of life on Earth with man. This strategy determines the need for scientific substantiation of the theoretical and methodical approach to rethinking the interaction principles between man and the environment, providing for the formation of a system of values, value orientations, interests, needs, attitudes, experience of the individual in making new, environmentally-oriented decisions and norms of behavior in relation to the natural environment. In this regard, the main attention in this article is devoted to the development and testing of universal ethical principles of the individual's ecological culture innovative model, raising to the rank of law the equal coexistence of man and nature and the development of sustainable interaction of ecology, economy and production. With the help of environmental monitoring, implemented as a leading method of research, the effectiveness of the ethical principles' universals of the model of man and nature equal coexistence is experimentally tested and justified. The article reveals the prerequisites for the transformation of the individual's ecological culture; the content of ethical principles' universals for rethinking the ecological culture of the individual is established; on the basis of the results of the study the structure and content of axiological, cognitive, procedural, orientation components of the innovative model od individual's ecological culture is justified and the practical importance in the implementation of ethical principles' universals of the model is proved. [ABSTRACT FROM AUTHOR]

Evaluation of the population density in many ecological and biological problems requires a satisfactory degree of accuracy. Insufficient information about the population density, obtained from sampling procedures negatively, impacts on the accuracy of the estimate. When dealing with sparse ecological data, the asymptotic error estimate fails to achieve a reliable degree of accuracy. It is essential to investigate which factors affect the degree of accuracy of numerical integration methods. When the number of traps is less than the recommended threshold, the degree of accuracy will be negatively affected. Therefore, available numerical integration methods cannot guarantee a satisfactory degree of accuracy, and in this sense the error will be probabilistic rather than deterministic. In other words, the probabilistic approach is used instead of the deterministic approach in this instance; by considering the error as a random variable, the chance of obtaining an accurate estimation can be quantified. In the probabilistic approach, we determine a threshold number of grid nodes required to guarantee a desirable level of accuracy with the probability equal to one.

Deep-sea ecological monitoring is increasingly recognized as indispensable for the comprehension of the largest biome on Earth, but at the same time it is subjected to growing human impacts for the exploitation of biotic and abiotic resources. Here, we present the Naples Ecological REsearch (NEREA) stand-alone observatory concept (NEREA-fix), an integrated observatory with a modular, adaptive structure, characterized by a multiparametric video-platform to be deployed in the Dohrn canyon (Gulf of Naples, Tyrrhenian Sea) at ca. 650 m depth. The observatory integrates a seabed platform with optoacoustic and oceanographic/geochemical sensors connected to a surface transmission buoy, plus a mooring line (also equipped with depth-staged environmental sensors). This reinforced high-frequency and long-lasting ecological monitoring will integrate the historical data conducted over 40 years for the Long-Term Ecological Research (LTER) at the station “Mare Chiara”, and ongoing vessel-assisted plankton (and future environmental DNA-eDNA) sampling. NEREA aims at expanding the observational capacity in a key area of the Mediterranean Sea, representing a first step towards the establishment of a bentho-pelagic network to enforce an end-to-end transdisciplinary approach for the monitoring of marine ecosystems across a wide range of animal sizes (from bacteria to megafauna).

Progress in sensor technologies has allowed real-time monitoring of soil water. It is a challenge to model soil water content based on remote sensing data. Here, we retrieved and modeled surface soil moisture (SSM) at the U.S. Climate Reference Network (USCRN) stations using Sentinel-1 backscatter data from 2016 to 2018 and ancillary data. Empirical machine learning models were established between soil water content measured at the USCRN stations with Sentinel-1 data from 2016 to 2017, the National Land Cover Dataset, terrain parameters, and Polaris soil data, and were evaluated in 2018 at the same USCRN stations. The Cubist model performed better than the multiple linear regression (MLR) and Random Forest (RF) model (R2 = 0.68 and RMSE = 0.06 m3 m-3 for validation). The Cubist model performed best in Shrub/Scrub, followed by Herbaceous and Cultivated Crops but poorly in Hay/Pasture. The success of SSM retrieval was mostly attributed to soil properties, followed by Sentinel-1 backscatter data, terrain parameters, and land cover. The approach shows the potential for retrieving SSM using Sentinel-1 data in a combination of high-resolution ancillary data across the conterminous United States (CONUS). Future work is required to improve the model performance by including more SSM network measurements, assimilating Sentinel-1 data with other microwave, optical and thermal remote sensing products. There is also a need to improve the spatial resolution and accuracy of land surface parameter products (e.g., soil properties and terrain parameters) at the regional and global scales.

The relevance of the research is caused by the need to monitor heavy metal content in ecosystems and human bio-substrates as the initial stage in assessing their impact on ecosystems and human body for determination the regional ecological standards taking into account natural and technogenic specificity of the region. The aim of this study was to evaluate soil content of Pb, Zn, Sr, Cu, Ni, Co, Cr, As, V at 30 monitoring sites of residential areas in the central, southern, eastern, northwestern, western and northern regions of the Crimean peninsula. Methods. The total content of Pb, Zn, Sr, Cu, Ni, Co, Cr, As, V in samples of soil was determined using x-ray spectrometer "Spektroskan Max-GV" in the laboratory of Soil Science Department in Academy of biology and biotechnology in Southern Federal University. Results. Exceedances of the maximum permissible concentrations were determined for Cr, Co, Pb, while As and Zn showed excess rarely. The maximum values of exceedances were as follows: 6,6 for As; 2,1 for Pb; 1,1 for V; 1,7 for Zn; 1,1 for Ni of maximum permissible concentration, 2,8 for Co; 2,6 for Cu; 1,7 for Cr and Sr of clarkes for settlements. The comparative analysis of heavy metals distribution in soil of the regions with different natural and anthropogenic conditions allows assuming that the revealed heavy metals exceedances are mostly of an anthropogenic origin. Further studies including the reserved territories of the Crimea are needed to identify the geochemical soil characteristics and their origin at different regions.

Emerging technologies have led to an increase in species observations being recorded via digital images. Such visual records are easily shared, and are often uploaded to online communities when help is required to identify or validate species. Although this is common practice, little is known about the accuracy of species identification from such images. Using online images of newts that are native and non-native to the UK, this study asked holders of great crested newt (Triturus cristatus) licences (issued by UK authorities to permit surveying for this species) to sort these images into groups, and to assign species names to those groups. All of these experts identified the native species, but agreement among these participants was low, with some being cautious in committing to definitive identifications. Individuals’ accuracy was also independent of both their experience and self-assessed ability. Furthermore, mean accuracy was not uniform across species (69–96%). These findings demonstrate the difficulty of accurate identification of newts from a single image, and that expert judgements are variable, even within the same knowledgeable community. We suggest that identification decisions should be made on multiple images and verified by more than one expert, which could improve the reliability of species data.