Abstract This study examined carbon (C), water, and energy exchanges across different cropping systems in the Great Lakes region using eddy covariance (EC) fluxes from an agricultural flux tower site (CA‐TPA) in southern Ontario, Canada. The site was cultivated with corn in 2020 and 2021, sweet potato in 2022, and tobacco in 2023. The site was a strong C sink during the corn years, with annual net ecosystem productivity (NEP) values of 538 ± 4.9 and 301 ± 3.7 g C m −2 yr −1 in 2020 and 2021, respectively. In contrast, it became a C source in 2022 under sweet potato, exhibiting an annual NEP of −86 ± 2.1 g C m −2 yr −1 . Under tobacco in 2023, the site transitioned to a weak carbon sink, with an annual NEP of 29 ± 1.6 g C m −2 yr −1 . Crop yield (CY) was 537 and 491 g C m 2 for corn in 2020 and 2021, respectively, 118 g C m 2 for sweet potato in 2022, and 124 g C m 2 for tobacco in 2023. It resulted in an annual net ecosystem carbon balance (NECB) of 1, −190, −205, and −95 g C m 2 yr −1 for 2020, 2021, 2022, and 2023, respectively, indicating an overall net C loss from all three cropping systems after accounting for harvested biomass. Annual evapotranspiration (ET) totals were 661, 727, 745, and 722 mm yr −1 for 2020–2023, accounting for approximately 58%, 72%, 78%, and 74% of annual precipitation. The study results provide insights to support climate‐smart crop management practices in the region.

Intensively managed grasslands have been found to be either net greenhouse gas (GHG) sources or sinks depending on management and climate, where the uptake of carbon dioxide (CO2) is balanced by respiration, crop harvest, and the emission of potent non-CO2 GHGs. This study reports eddy-covariance measurements of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4), combined with non-gaseous imports and exports of carbon to determine the net greenhouse gas balance (NGB) of a conventionally managed forage field on a dairy farm in Agassiz, British Columbia, Canada. The forage crop (ryegrass and tall fescue) was intensively managed via 'cut and carry', where the crop was harvested and removed from the field up to 6 times a year. The field received multiple applications of dairy manure slurry and was additionally fertilized with inorganic nitrogen. A previous study determined that the field was a weak or moderate source of C in terms of the net ecosystem carbon balance (NECB); this study additionally reports that the field was a GHG source during 2020 and 2021 (NGB values of 2038 +/- 890 and 901 +/- 920 g CO2-eq m-2 y-1, respectively, where the +/- term indicates the uncertainty range). Elevated N2O emissions were observed after dairy manure slurry and N-fertilizer application, and the magnitude and duration of these post-management N2O fluxes were associated with variations in near-surface soil volumetric water content. Multiple soil freezing events were associated with elevated N2O fluxes, with the magnitude of fluxes associated with freezing intensity, and were determined to be a substantial proportion of annual N2O emissions when growing season emissions were suppressed.

Abstract The carbon (C) storage of boreal peatlands is threatened by an intensifying wildfire regime. Between 2019 and 2023 we used eddy covariance and surface closed chambers to monitor two permafrost peatlands in boreal western Canada that burned in 2019 and 2007. Deeper thaw, warmer soils, and slow vegetation recovery caused the 2019 Burn to be a net carbon dioxide (CO2) source (+130 g C m−2 yr−1) for four years post‐fire, despite reduced soil respiration. The 2007 Burn was a sink (−11 g C m−2 yr−1) 13–15 years post‐fire, similar to undisturbed peatlands. We estimate that wildfire caused a loss (∼2.9 kg C m−2) from permafrost peatlands, with ∼1.7 kg C m−2 due to combustion and ∼1.2 kg C m−2 due to net CO2 losses during post‐fire succession. This highlights the importance of the post‐fire CO2 losses and emphasizes the vulnerability of permafrost peatland soil C to fire.

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15-70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

Wetlands provide many ecosystem services such as carbon sequestration, climate regulation, biodiversity and water quality enhancement. Through evaporative cooling, wetland ecosystems also play a significant role in the regulation of local and regional climate by creating microclimates, which benefit local flora and fauna. In this study, the cooling effect of wetlands was evaluated by examining the differences in aerodynamic temperature (Taero) between wetlands and nearby croplands in the Prairie Pothole Region of Canada. The cooling effect refers to the reduction of air or surface temperature through evapotranspiration and thermal dissipation from the environment. We utilized turbulent flux and meteorological data gathered through eddy covariance measurements over three years (2021-2023) from three distinct wetland sites and two cropland types. Our findings reveal that during the growing season (May to September), wetlands exhibit significantly lower temperatures compared to the croplands, with mean daytime cooling (Taero reduction) ranging from 1.4 degrees C to 3.0 degrees C. On hot days (air temperature > 25 degrees C), wetlands with more open water provided even greater cooling, reducing temperatures by up to 5.4 degrees C compared to nearby croplands. Each wetland is characterized by unique biophysical properties such as surface and aerodynamic conductances, which result in distinct energy flux dynamics generating different mechanisms driving the daytime cooling. Higher evaporative fraction strongly drives the cooling effect in wetlands compared to croplands. These results underscore the notable cooling potential of wetlands and highlight their importance in regulating local and regional climates, ultimately contributing to the understanding of how wetland conservation, restoration and management can contribute to natural climate solutions.

The shortage of decades‐long continuous measurements of ecosystem processes limits our understanding of how changing climate impacts forest ecosystems. We used continuous eddy‐covariance and hydrometeorological data over 2002–2022 from a young Douglas‐fir stand on Vancouver Island, Canada to assess the long‐term trend and interannual variability in evapotranspiration (ET) and transpiration (T). Collectively, annual T displayed a decreasing trend over the 21 years with a rate of 1% yr−1, which is attributed to the stomatal downregulation induced by rising atmospheric CO2 concentration. Similarly, annual ET also showed a decreasing trend since evaporation stayed relatively constant. Variability in detrended annual ET was mostly controlled by the average soil water storage during the growing season (May–October). Though the duration and intensity of the drought did not increase, the drought‐induced decreases in T and ET showed an increasing trend. This pattern may reflect the changes in forest structure, related to the decline in the deciduous understory cover during the stand development. These results suggest that the water‐saving effect of stomatal regulation and water‐related factors mostly determined the trend and variability in ET, respectively. This may also imply an increase in the limitation of water availability on ET in young forests, associated with the structural and compositional changes related to forest growth.

Intensively managed grasslands have been found to be either carbon (C) sources or sinks depending on management and climate. This study reports the net ecosystem production (NEP) and latent heat fluxes (7E) from a managed forage field at a dairy farm in Agassiz, British Columbia, Canada. The forage crop (ryegrass and tall fescue) was harvested up to 6 times a year. The field received multiple applications of dairy manure slurry and was also fertilized with inorganic nitrogen. Eddy-covariance measurements of NEP were combined with C imports (manure additions) and exports (harvested biomass) to determine the net ecosystem C balance (NECB), and values of gross primary production (GPP) and 7E were used to determine water use efficiency (WUE). In terms of environmental controls on NEP, variability of daytime NEP was well described by fitting measured incoming photosynthetically active radiation with a rectangular hyperbolic light-response curve, but variability in nighttime NEP was less effectively described by soil temperature and soil moisture. After accounting for C imports and exports, the NECB of the field was -315 +/- 141 and -51 +/- 148 g C m-2 y-1 (+/- indicates the uncertainty range) during the 2020 and 2021 study years, respectively, indicating C was lost from the field and was strongly influenced by C imports and exports relative to NEP. Higher than normal soil moisture and precipitation as well as higher than normal air temperature were both found to suppress GPP and ecosystem respiration (Re), but annual NEP was more impacted by soil moisture in the first year (2020) due to its effect of lowering GPP compared to high air temperature (including the 2021 Pacific Northwest heat dome) and low soil moisture in the second year due to their greater impact on Re relative to GPP. Crop harvests were found to substantially reduce both GPP and WUE which suggests that the intensity of management in terms of harvest frequency could be modified to improve long-term C sequestration.

There are numerous strategies and concepts that management can use in order to improve the organizational business performance of companies in modern business conditions. Research shows that one of the most prevalent principles in the past few years is the use of Lean tools, which enable managers to continuously improve their business. Since in most cases the problem of choosing Lean tools is solved through experience, the paper proposes the application of an integrated multi-criteria approach for decision-making. The evaluation of the relative importance of the criteria was performed using the AHP method, while the selection of the most suitable Lean tool was carried out using the ELECTRE method, the PROMETHEE method and the Compromise Programming method, using specially developed software for that purpose. The aim of this paper is to point out the importance and quality of the application of the proposed model in real and modern conditions of business and organization.

This research paper analyzes the speckle noise distributions in images for denoising performance prediction through the prism of spatial domain. The values at the maximum, minimum and middle of spectrum in spatial domain are taken as reference values. All obtained results give a better overview of the "nature" of the digital images in comparison to the theoretical definitions of noises and images as digital signals. Therefore, analyses of the noises in the 2D spectrum give good recommendations for improvement of the filters. The main aim in this study is to investigate which speckle noise distributions in images has the strongest influence for denoising performance prediction. The clean images are available and we adopt it for evaluating our network. In our experiments, Peak Signal to Noise Ratio (PSNR), normalized color difference (NCD), and feature similarity index for color image quality assessment (FSIMc), are used to measure denoising performance. is selected as the evaluation index of the image. Studies on speckle noise distributions in images show that such distribution do have certain disciplines. ALOHA filter is the most influential for the denoising performance prediction.

Quantifying the emissions of the three main biogenic greenhouse gases (GHGs), carbon dioxide (CO 2 ), nitrous oxide (N 2 O) and methane (CH 4 ), from agroecosystems is crucial. In this study continuous measurements of N 2 O, and CH 4 emissions from potato and pea crops in southwest British Columbia, Canada were made using the eddy‐covariance (EC) technique. Flux footprint analysis, coupled with EC and manual nonsteady state chamber measurements, was used to address the spatial heterogeneity resulting from the field edge at the study site. Flux footprint corrections had a larger effect on N 2 O fluxes than CO 2 fluxes because of a more pronounced difference in N 2 O fluxes between the crop and edge areas. After flux footprint corrections, the potato and pea crops were both weak CO 2 sinks with annual net ecosystem exchange values of −57 ± 9 and −97 ± 16 g C m −2 yr −1 , respectively. However, after taking carbon (C) export via crop harvest and C import via seeding into account, the potato crop shifted to being a moderate C source of 284 ± 55 g C m −2 yr −1 , while the pea crop became near C neutral, sequestering only 30 ± 26 g C m −2 yr −1 . Annual GHG balances, quantified by converting N 2 O and CH 4 to CO 2 equivalents as pulse emissions using respective global warming potentials on a 100‐year timescale, were 417 ± 88 and 152 ± 106 g CO 2 e m −2 yr −1 for the potato and pea crops, respectively, with N 2 O contributing the largest proportion to annual total GHG balances and outweighing the CO 2 uptake from the atmosphere.

Arctic wetlands are known methane (CH 4 ) emitters but recent studies suggest that the Arctic CH 4 sink strength may be underestimated. Here we explore the capacity of well-drained Arctic soils to consume atmospheric CH 4 using >40,000 hourly flux observations and spatially distributed flux measurements from 4 sites and 14 surface types. While consumption of atmospheric CH 4 occurred at all sites at rates of 0.092 ± 0.011 mgCH 4 m −2 h −1 (mean ± s.e.), CH 4 uptake displayed distinct diel and seasonal patterns reflecting ecosystem respiration. Combining in situ flux data with laboratory investigations and a machine learning approach, we find biotic drivers to be highly important. Soil moisture outweighed temperature as an abiotic control and higher CH 4 uptake was linked to increased availability of labile carbon. Our findings imply that soil drying and enhanced nutrient supply will promote CH 4 uptake by Arctic soils, providing a negative feedback to global climate change.

Peatland rewetting, a management effort to restore water levels in previously drained peatlands, is important for re-establishing the role of these peatlands as carbon (C) sinks. Since rewetted peatlands have a highly variable response to interannual variations in climatic conditions and functional changes, long term studies of C fluxes in these ecosystems are needed. Here, we evaluated the impact of climate variability and functional change on the interannual variability of CO2 and CH4 fluxes at Burns Bog, a rewetted temperate bog on the Pacific Coast in Canada, based on five years of eddy covariance measurements. We found that the site alternated between being an annual-scale net CO2 sink or source, ranging from-32.6 +/- 21.5 (+/- 95% CI) to 11.9 +/- 15.1 g CO2-C m-2 yr-1, respectively, while consistently being a CH4 source, ranging from 11.6 +/- 0.7 to 18.0 +/- 1.6 g CH4-C m-2 yr-1. Over the five-year period, mean annual CH4 emissions (13.7 +/- 2.5 g CH4-C m-2 yr-1; +/- SD across years) entirely offset the CO2 sink (-12.3 +/- 20.4 g CO2-C m-2 yr-1), resulting in the site being near-carbon neutral over this period (1.3 +/- 23.9 g C m-2 yr-1). This finding indicates that excluding CH4 fluxes from the net C balance results in an overestimation of the net C uptake at this site. Annual CO2 emissions from the bog were greatest in the year with a dry and warm summer, emphasizing the importance of temperature and water table depth at the bog. Regardless of the greenhouse gas (GHG) metrics (i.e., global warming potential or sustained global warming potential) used in calculating the annual CO2-eq balance, the site consistently had a positive GHG balance across the study period. Despite mainly acting as a GHG source, the rewetted site will likely have a cooling effect on the climate system over long timescales compared to drained bogs that are large CO2 sources.

In this article the main aim was to identify the most influential attributes for optimal conditions for directed energy deposition through the melt pool optimization and monitoring. The main goal is to track the melt pool geometries such as width and depth. The goal of this study is to use an adaptive neural fuzzy inference system (ANFIS) to categorize the various melt pool depth input values. The procedure was optimized using ANFIS based on seven processing factors. Laser power (P), scanning speed (V), melt pool width (W), melt pool length (L), build height (BH), melt pool height (H), and melt pool tilt are the input parameters (I). Skillful prediction might be critical in achieving optimal circumstances throughout the deposition process. According to the findings, laser power has the greatest influence on melt pool depth. The combination of laser power and melt pool width produces the least training error and hence has the greatest impact on melt pool depth. The study, which takes into account many input parameters at the same time, is thought to be the first on a modest scale and will pique everyone's curiosity.

The effectiveness of the teaching process and learning is partly determined by the quality of the teaching material. Digital teaching material means all material that can be used and distributed in electronic form. This paper presents aspects of the application of e-materials in the teaching process, which are based on technological progress and the development of new possibilities. The paper discusses the types of e-materials as well as their role in the teaching process.

Society faces many challenges in transitioning toward sustainable development, and education is key to make this transition happen. Through education we influence on human consciousness, create their needs and changing behavior. One of most important educational programs is environmental education. It brings motivations, skills, values and commitment that people need to efficiently manage their earth’s resources and take responsibility for maintaining environmental quality and understand the problems they face. The limitation of access to certain resources is getting closer and we need to be aware of those limitations and put those in center of our life and work. The most effective way for doing it is throught environmental education started from earliest age. The limitation of access to certain resources is getting closer, and this fundamentally changes our relationship to economics, politics and ecology. This paper discusses the imperative of action within the limits of the finite world. The paper emphasizes the pressure on natural resources, which means that politics and the economy will have to undergo a radical transformation in order to be suitable not only today, but also in the future

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (R-e) over 1996-2016, but R-e was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post-drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two-factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R-2 > .5). The temperature sensitivities of all three C fluxes (NEP, GEP and R-e) declined over the study period (p < .05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over-maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001-2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over-mature, associated with the structural and compositional changes that accompany forest ageing.

Introduction One of the most popular electric motors for traction drive applications is permanent magnet synchronous machine (PMSM). This is due to the high energy and power density of the PMSM. Also, assembly costs of the PMSM are moderate. However, temperature monitoring of the PMSM is very difficult to achieve due to complicated measurement devices for internal components of the PMSM. Materials and methods Therefore, the main goal of the study was to establish regression models for estimation of the optimal parameters for the temperature prediction. The regression models will be created by input/output data pairs so there is no need-to-know internal physical knowledge of the PMSM. The main aim is to achieve predictive capable models for the temperature. Results Also, according to the regression model’s precision one can determine the input parameters influence on the temperatures of the internal components of the PMSM. Hence one king of ranking process will be performed in order to select which factors have the most influence on the temperatures. Conclusion The repression models will be created by neuro fuzzy logic procedure since the procedure could handle high nonlinearity between input and output data pairs.

Making strategic decisions in the environmental sector is a complex process because circumstances require rapid results in the conditions of inherited decades of problems. The entry of the Republic of Serbia into the EU implies redefining environmental decisions and priorities, which in expert, theoretical and practical terms brings with it a number of challenges. The potential of software support for strategic decision-making in a highly turbulent environment, in a Covid 19 pandemic, could contribute to shortening the time dimension of decision-making, a clearer perception of the relationship of individual environmental factors to the environment, and thus a different approach to solving this problem. The paper presents the development of a software support model for quantitative analysis of the environment presented through the SWOT matrix and its importance in the strategic determination of the use of software decision making potential in environmental protection, specifically in the importance of its application in construction waste management.