Circular Buffer Research Articles

Comparison of Spatial Modelling Approaches on PM10 and NO2 Concentration Variations: A Case Study in Surabaya City, Indonesia.

Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM10) and nitrogen dioxide (NO2) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM10 variations and 46%, 47%, and 48% of NO2 variations, respectively. The GTWR model performed better (R2 = 0.51 for PM10 and 0.48 for NO2) than the other two models (R2 = 0.49–0.50 for PM10 and 0.46–0.47 for NO2), LUR and GWR. In the PM10 model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO2 variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM10 and NO2, was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM10 and NO2 concentration variations within areas across Asia.

Morphology, germination, and geographic distribution of Pentaclethra macroloba (Fabaceae): a hyperdominant Amazonian tree

Introduction: Pentaclethra macroloba is a hyperdominant tree in the Amazon estuary of great socioeconomic importance for the region because the oil from its seeds is a powerful herbal medicine. Objective: We aimed to characterize the morphological structure, the morphological adaptations in response to the daily flooding of the Amazon estuary and the biogeographic area of P. macroloba. Methods: Detailed description of the external morphology, from germination to the adult tree, was obtained from individuals located in floodplain forest, Northeast Amazonia. The occupation area and the geographical extension of P. macroloba were determined from point of geographical coordinates of botanical samples deposited in the digital collections of Mobot and SpeciesLink. Results: Adult individuals have adapted structures in response to daily flooding, such as: adventitious roots to increase respiratory efficiency and lenticels in the trunk, serving as a connection point for oxygen transport between the root and the aerial part. Dried fruit favours the activation of the explosive dehiscence mechanism, allowing the seed to be expelled long distance. Deltoid shape of the seed allows water fluctuation and more efficient dispersal. Seedling is phanerocotylar hypogeal and with one pair of reserve cotyledons that provide the seedling an extra source of energy to escape the flood. Germination rate was 78 % and the speed was 0.2 seeds.day-1. Circular buffer method revealed the presence of 123 subpopulations of P. macroloba distributed in a radius of 5 699 943 km² across the Neotropical region. Conclusions: Much of the morphological structures of P. macroloba are adaptive and evolutionary responses to the periodically flooded environment of the Amazon estuary, showing that these environments select the trees, best adapted, to inhabit the flood. P. macroloba has a wide geographical area denotes the plasticity of adapting to different environments, which may justify its monodominance in some regions.

A Zynq-Based Flexible ADC Architecture Combining Real-Time Data Streaming and Transient Recording

The RFX-mod2 Nuclear Fusion experiment is an upgrade of RFX-mod, which was shutdown in 2016. Among the other improvements in the machine structure and diagnostics, a larger number of electromagnetic probes (EMs) is foreseen to provide more information about plasma instabilities and to allow an improved real-time plasma control. An analog-to-digital converter (ADC) architecture able to provide, at the same time, both transient recording and real-time streaming, as well as field-programmable gate array (FPGA)-based time integration of the inputs, is foreseen in RFX-mod2. Transient recording provides full-speed data acquisition (up to 1 MSample/s) by recording data in local memory and reading memory content after the plasma discharge. Real-time streaming of the subsampled data is required for active control. The chosen technology is based on the XILINX Zynq architecture that provides, in the same chip, a multicore Advanced RISC Machines (ARM) processor tightly coupled to an FPGA. Time-critical functions are carried out by the FPGA, such as the management of the circular data buffer, low-pass filtering for subsampling of the samples to be streamed, and digital integration. Other functions are carried out by the processor, such as the management of the configuration setting, received via Transmission Control Protocol (TCP)/IP or Hypertext Transfer Protocol (HTTP), the data readout of acquired samples in transient recording buffers, and network data streaming of data collected for active real-time plasma control.

A high resolution multi-phase clock Time-Digital Convertor implemented on Kintex-7 FPGA

Time-digital Converter (TDC) aims to measure the arrival time of the leading edge of the pulse signal. Our recent work presented a high resolution multi-phase TDC based on the Kintex-7 Field Programmable Gate Array (FPGA) device. A simple I/O tile based circular input buffer is employed to oscillate the input signal periodically, and then a multi-phase TDC based on ISERDES core with a 625 ps bin size is used to accomplish the multiple measurements for getting higher resolution performance. In this paper, the design concept, architecture, as well as kernel implementation considerations are all discussed. To evaluate the TDC's performance, we built a verification system based on Kintex-7 FPGA. Initial test results indicate that the TDC's effective bin size is successfully reduced from 625 ps to 78.125 ps, and the measured dual-channel time resolution is better than 35 ps RMS.

Active living environments, physical activity and premature cardiometabolic mortality in Canada: a nationwide cohort study

ObjectiveTo evaluate sex-specific and age-specific associations of active living environments (ALEs) with premature cardiometabolic mortality.DesignPopulation-based retrospective cohort study.SettingResidential neighbourhoods (1000-metre circular buffers from the centroids of dissemination areas) across Canada...

School-based Greenness and its Association with Overweight and Obesity in Children and Adolescents: a National Cross-Sectional Study in China

Background: Prior investigations on the associations of greenness exposure, which is generally assessed at participants’ home addresses, with obesity are still controversial. Furthermore, few documented evidences have focused on the association between childhood obesity and school-based greenness exposure.Objective: This study aimed to assess the associations between school-based greenness and markers of adiposity in children and adolescents in China.Method: We performed a national cross-sectional analysis of a representative sample including 56,620 children and adolescents aged 6-18 years in seven municipalities/provinces across China. We utilized the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) within 100-, 500-, and 1,000m circular buffers around each school’s address to evaluate greenness exposures. We estimated the associations of greenness with changes in BMI z-scores and waist circumference as well as odds ratio of overweight and/or obesity using two-level logistic and generalized linear mixed regression models. We also took consideration of the modifying effects of ambient air pollution and physical activity into the greenness-adiposity associations. Result: We found that BMI z-scores (-0.13, 95%CI:-0.13, -0.07) and waist circumference (-0.63, 95%CI:-1.2, -0.06) were decreased when NDVI-1000m per interquartile (IQR, 0.13 unit) increase in adjusted model. And an IQR increase in NDVI of three different buffers was associated with 10-21% lower odds ratio (OR) of overweight and/or obesity. We also found that the associations were more pronounced in boys, urban dwellers and children with lower parental education levels. Air pollution mediated 9.8-56.9% of the greenness-obesity associations, but no mediating effects were observed for physical activity.Conclusion: Higher school-based greenness exposure was associated with decreased BMI z-scores and lower relative prevalence of overweight and/or obesity in children and adolescents. Ambient air pollutants may partially mediate the greenness-adiposity associations.

Greenspace exposure and non-injury mortality in UK Biobank

Background: Some cohort studies have shown a protective association of greenness and non-injury mortality, after adjustment for personal contextual and area-level confounding factors, though evidence in the UK is predominantly from ecological studies. We aimed to assess the association of greenspace and non-injury mortality in the UK, using rich confounder data available in the UK Biobank cohort. Methods: We used Ordnance Survey MasterMap Greenspace data, categorized into 18 greenspace functions (e.g., private garden, public park, allotment, cemetery, playing field, etc.) to assess associations of survival and total greenspace cover (18 categories combined) in multiple buffer sizes (100 m, 500 m, 1000 m) surrounding UK Biobank residential addresses (n = 277,236). We used Cox-proportional hazards models, with age as the underlying timescale, adjusted for sex, household income, pack years smoking, alcohol consumption and neighbourhood deprivation. Results: We showed protective associations for UK Biobank participants living in the most green compared to the least green quintile of total greenspace cover in a 100 m circular distance buffer for non-injury mortality (HR = 0.91; 95% CI = 0.84, 0.99). Results were consistent with previous studies, which have shown a small protective association, after adjustment for confounders. Function-specific analyses showed that protective associations of private (residential) garden and mortality remained when other functional greenspace categories were excluded from analysis. Across all buffer sizes, over 50% of total greenspace cover was classified as private (residential) garden, which has important implications for environmental equality. Conclusion: Further analyses of greenspace categories, grouped by function (e.g., private (residential) gardens versus public parks, playing fields and sports facilities) will offer novel insight into specific mechanistic pathways connecting greenspace and health (e.g., the contribution of physical activity), which is critical for designing and/or retrofitting urban environments for health.

Smartphone Mobile Sensing and Geospatial Physical Activity Space Analytics in the PASTA-LA study

Physical activity is intimately linked to the built environment and health. Major on-going efforts are being made to increase physical activity rates in urban settings. One such effort, quickly becoming prevalent across many global cities, is the implementation of bike sharing programs. In October 2017, UCLA launched the Bruin Bike Share program. It provided a unique opportunity to conduct a before-and-after natural intervention study, the Physical Activity through Sustainable Transport Approaches in Los Angeles (PASTA-LA) study, to assess the health-related outcomes of bike-sharing programs. During the 2016-2018 study period, the PASTA-LA study enrolled 440 physically-capable participants from the UCLA-Westwood area. Participants were administered online questionnaires and a smartphone app (MOVES) was deployed on their phones for location and activity tracking. A nested sample of 140 participants were also outfitted with research grade GPS and accelerometers for comparison. Across all participants, over 30 million observations of location and activity were recorded. Using these ‘big data’, we can address our specific research questions: (1) can smartphones be used instead of expensive research-grade devices without sacrificing measurement validity, and (2) can these ‘big data’ be used to model Physical Activity Spaces (PASs) to better quantify environmental context. We have addressed these research questions using advanced geospatial and geostatistical approaches. To evaluate context variable allocation for individuals, we have used location and activity levels (steps) to demonstrate the predictive accuracy of four approaches to defining physical activity space: (1) circular home buffers, (2) directional ellipses, (3) machine learning route allocation models, and (4) kernel density ranking. These models can be used to quantify variables such as exposure to green space, dose of air pollution, and other neighborhood-based statistics that are instrumental for spatial models of association (e.g. such as the impact of heat exposure on physical activity rates, as moderated by green space access.)

Association of early life and acute pollen exposure with lung function and exhaled nitric oxide (FeNO). A prospective study up to adolescence in the GINIplus and LISA cohort

BackgroundPollen exposure has both acute and chronic detrimental effects on allergic asthma, but little is known about its wider effects on respiratory health. This is increasingly important knowledge as ambient pollen levels are changing with the changing global climate. ObjectiveTo assess associations of pollen exposure with lung function and fractional exhaled nitric oxide (FeNO) at age 15 in two prospective German birth cohorts, GINIplus and LISA. MethodsBackground city-specific pollen exposure was measured in infancy (during the first three months of life), and contemporary (on the day of and 7 days prior to lung function measurement). Greenness levels within circular buffers (100–3000 m) around the birth and 15-year home addresses were calculated using the satellite-derived Normalized Difference Vegetation Index. Regression models were used to assess the associations of grass and birch pollen with lung function and FeNO, and the modifying effects of residential greenness were explored. ResultsCumulative early life exposure to grass pollen was associated with reduced lung function in adolescence (FEV1: −4.9 mL 95%CI: −9.2, −0.6 and FVC: −5.2 mL 95%CI: −9.8, −0.5 per doubling of pollen count). Acute grass pollen exposure was associated with increased airway inflammation in all children, with higher FeNO increases in children living in green areas. In contrast acute birch pollen exposure was associated with reduced lung function only in children sensitised to birch allergens. ConclusionThis study provides suggestive evidence that early pollen exposure has a negative effect on later lung function, which is in turn influenced by acute pollen exposures.

Greenness surrounding schools and adiposity in children and adolescents: Findings from a national population-based study in China

BackgroundPrevious studies have indicated that exposure to green space may benefit human health. However, the available evidence concerning the effects of greenness, especially school-based greenness, on pediatric obesity is scarce. ObjectiveTo explore the association between school-based greenness and adiposity in children and adolescents in China. MethodWe conducted a nationwide cross-sectional study of 56,620 children and adolescents (aged 6–18 years) in seven provinces/municipalities across China. School-based greenness was assessed using satellite-derived Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) within 100-, 500-, and 1000-m circular buffers around each school's address. Generalized linear mixed regression models were used to estimate associations of greenness with BMI z-scores (zBMI), waist circumference, and prevalent overweight/obesity. We also explored the potential mediating role of ambient air pollution and physical activity in the greenness-adiposity associations. ResultIn the adjusted model, an IQR increase in NDVI-1000m was associated with lower zBMI (β: -0.11, 95% confidence interval[CI]: -0.13,-0.09) and waist circumference (β: -0.64, 95%CI: -0.78,-0.50). Consistently, an IQR increase in NDVI-100m, NDVI-500m, NDVI-1000m was associated with 7–20% lower odds of overweight/obesity in the adjusted models. Air pollutants mediated 6.5–29.1% of the association between greenness and zBMI. No significant mediation effect was observed for physical activity. ConclusionHigher school-based greenness levels were associated with lower zBMI, waist circumference, and lower odds of overweight and obesity in children and adolescents. Ambient air pollutants may partially mediate the greenness-adiposity associations.

General recurrence-relation generation scheme for molecular integral evaluation.

We develop a new scheme for evaluating different molecular integrals using Gaussian type orbitals. In this new scheme, the evaluation of integrals is performed in two steps during runtime. The first step is a top-down procedure that maps each recurrence relation into a jagged array (array of arrays), where each element of a member array represents either the final results or some intermediate integrals that are stored in our developed data structure "coarse-grained circular buffer". This step is the same for all different one- and two-electron operators so that the same algorithm and source codes can be used. In the second step, a bottom-up procedure is carried out that computes all the intermediate and the final molecular integrals by backtracking elements from the last member array of each jagged array. Different source codes should in principle be used for different electron operators in the second step, but which can be generated automatically by our developed recurrence-relation compiler. The currently proposed general recurrence-relation generation scheme provides a new, generic and automatic programming way for various one- and two-electron integrals needed in computational chemistry. Users can even introduce new electron operators and evaluate their integrals during runtime by combining the implementation of the proposed new scheme and the just-in-time compilation technique.

Visitor bikeshare usage: tracking visitor spatiotemporal behavior using big data

Bikeshare programs are a popular, convenient, and sustainable mode of transportation that provide a range of benefits to urban communities such as reduction in carbon emissions, decreased travel times, financial savings, and heightened physical activity. Although, tourists are especially inclined to use bikeshare to explore a destination as the programs are a convenient, cheap, flexible, and an active alternative to vehicles and mass transit little research or attention has focused on visitor usage. As such the current study investigated the spatial-temporal usage patterns of bikeshare by visitors to an urban community using GPS based big data (N = 353,733). The results revealed differential usage patterns between visitors and local residents based on user provided ZIP Codes using a 50 mile geometric circular buffer around the urban destination. The visitors and residents significantly varied on numerous trip behaviors including route selection, time of rental, checkout/check-in locations, distance, speed, duration, and physical activity intensity. The user patterns uncovered suggest visitors primarily use bikeshare for leisure based urban exploration, compared to residents’ primary use of bikeshare to be public transportation related. Implications for bikeshare, urban planning, and tourism management are provided aimed at delivering a more sustainable and richer visitor experience.

Environmental Factors Influencing the Occurrence of Unhealthy Tapirs in the Southern Yucatan Peninsula.

Information about the effects of environmental degradation on the health of terrestrial forest wildlife is limited, especially for rare species. In this study, we analyse the influence of ecological factors such as landscape characteristics and seasonality on the health status of Baird's tapirs in Calakmul, Mexico. We collected georeferenced photographic records of healthy (n = 32) and unhealthy (n = 22) tapirs from 2008 to 2019 and characterized landscape composition around each record at three spatial scales (circular buffers of 1, 2 and 3-km radii according to Baird's tapir home ranges). Our logistic model building process consisted in selecting the best spatial scale for each landscape cover class, before including them along with distance to human settlements and seasonality in a full model. The model that best explained the occurrence of unhealthy tapirs included the percentage of agriculture within a 1-km radius. This study hints at the negative effect that land-use change to agriculture occurring in Calakmul might have on tapir health, with 95.45% of unhealthy tapirs recorded in such landscapes. Further studies should investigate the proximate determinants of tapir health in anthropogenic landscapes, which might be linked to stress or to contact with domestic animals.

Design of an interface for teaching cardiovascular physiology to anesthesia clinicians with a patient simulator connected to a minimally invasive cardiac output monitor (LiDCO rapid\xae)

Cardiovascular physiology can be simulated in patient simulators but is limited to the simulator monitor curves and parameters, missing some important data that today is known as essential to fluid management and therapeutic decision in critical ill and high-risk surgical patients. Our main objective was to project and implement a unidirectional communication channel between a pre-existing patient simulator and a minimally invasive cardiac output monitor (LiDCO rapid®); a monitor that connects to real patients and interprets the arterial wave. To connect the patient simulator to the hemodynamic monitor, firstly, we had to assess both systems and design a communication channel between them. LiDCO monitor accepts as an input an analog voltage varying between 0 V and 5 V and that every volt is directly proportional to a blood pressure (mmHg) value ranging from 0 mmHg (0 V) to 500 mmHg (5 V). A Raspberry Pi 0 (Rpi0) with a WIFI chip integrated was needed and added to a digital analogue converter connected to the board. We designed a system that allowed us to collect, interpret and modify data, and feed it to the LiDCO rapid® monitor. We had developed a Python® script with three independent threads and a circular buffer to handle the data transmission between both systems. The LiDCO hemodynamic monitor successfully received data sent from our setup like a real patient arterial wave pulse and interpreted it to estimate several hemodynamic parameters, as cardiac output, stroke volume, systemic vascular resistance, pulse pressure variation, and stroke volume variation. The connection between the patient simulator and the LiDCO monitor is being used to create arterial curves and other hemodynamic parameters for clinical scenarios where residents and anesthesiologists can simulate a variety of unstable hemodynamic conditions, preparing them to face similar situations with real patients in a safe environment and with their own monitors.

Grass Buffer Strips Improve Soil Health and Mitigate Greenhouse Gas Emissions in Center-Pivot Irrigated Cropping Systems

Declining water resources and soil degradation have significantly affected agricultural sustainability across the world. In the southern High Plains of USA, buffer strips of perennial grasses alternating with cultivated corn strips were introduced in center-pivot irrigated crop fields to increase agronomic production and ecosystem services. A study was conducted to evaluate soil carbon (C) and nitrogen (N) dynamics, greenhouse gas (GHG) emissions, and soil health benefits of integrating circular grass buffer strips in the center-pivot irrigated corn production system. Multiple parameters were assessed in the grass buffer strips, and at distances of 1.52, 4.57, and 9.14 m away from the edges of grass strips in corn strips. While grasses in the buffer strips depleted N compared to corn strips, potential C mineralization (PCM) was 52.5% to 99.9% more in grass strips than in corn strips. Soil microbial biomass C (MBC) content was 36.7% to 52.5% greater in grass strips than in corn strips. Grass buffer also reduced carbon dioxide (CO2) and nitrous oxide (N2O) emissions from corn strips. Grass buffer strips can improve soil health and sustainability in center-pivot irrigated cropping systems by increasing soil C components and reducing GHG emissions.

Monitoring, Mapping, and Modeling Spatial-Temporal Patterns of PM2.5 for Improved Understanding of Air Pollution Dynamics Using Portable Sensing Technologies.

Fine particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) is highly variable in space and time. In this study, the dynamics of PM2.5 concentrations were mapped at high spatio-temporal resolutions using bicycle-based, mobile measures on a university campus. Significant diurnal and daily variations were revealed over the two-week survey, with the PM2.5 concentration peaking during the evening rush hours. A range of predictor variables that have been proven useful in estimating the pollution level was derived from Geographic Information System, high-resolution airborne images, and Light Detection and Ranging (LiDAR) datasets. Considering the complex interplay among landscape, wind, and air pollution, variables influencing the PM2.5 dynamics were quantified under a new wind wedge-based system that incorporates wind effects. Panel data analysis models identified eight natural and built environment variables as the most significant determinants of local-scale air quality (including four meteorological factors, distance to major roads, vegetation footprint, and building and vegetation height). The higher significance level of variables calculated using the wind wedge system as compared to the conventional circular buffer highlights the importance of incorporating the relative position of emission sources and receptors in modeling.

The association between spatial access to physical activity facilities within home and workplace neighborhoods and time spent on physical activities: evidence from Guangzhou, China

BackgroundUrban residents from the developing world have increasingly adopted a sedentary lifestyle and spend less time on physical activities (PA). Previous studies on the association between PA facilities and individuals’ PA levels are based on the assumption that individuals have opportunities to use PA facilities within neighborhoods all day long, ignoring the fact that their willingness and opportunities to use nearby facilities depend on how much discretionary time (any time when people have a choice what to do) they have. Further, scant attention has been paid to the influence of PA facilities within both residential and workplace neighborhoods in the dense urban context. To address the above research gaps, this study investigated the links between the spatial access to PA facilities within home/workplace neighborhoods and time spent on PA among working adults, focusing on whether results were different when different measures of accessibility were used and whether participants’ discretionary time over a week affected their time spent on PA.MethodThis study used data from a questionnaire survey (n = 1002) in Guangzhou between June and July 2017 and point of interest (POI) data from online mapping resources. Outcome variables included the amount of time spent on physical activity/moderate and vigorous intensity physical activity (PA/MVPA) over the past week. Home/workplace neighborhoods were measured as different distance buffers (500 m circular buffers, 1000 m circular buffers, and 1080 m network buffers) around each respondent’s home/workplace. Spatial access to PA facilities was measured using two indicators: the counts of PA facilities and proximity to PA facilities within home/workplace neighborhoods. The amount of discretionary time was calculated based on activity log data of working day/weekend day from the Guangzhou questionnaire survey, and regression models were used to examine relationships between the spatial access of PA facilities, the time spent on PA/MVPA, and the amount of discretionary time, adjusted for covariates. Associations were stratified by gender, age, education, and income.ResultsUsing different measures of accessibility (the counts of and proximity to PA facilities) generated different results. Specifically, participants spent more time on PA/MVPA when they lived in neighborhoods with more PA facilities and spent more time on MVPA when worked in closer proximity to PA facilities. A larger amount of discretionary time was associated with more time spent on PA/MVPA, but it did not strengthen the relationship between access to PA facilities and PA/MVPA time. In addition, relationships between access to PA facilities and PA levels varied by gender, age, education, and income.ConclusionThis study contributes to the knowledge of PA-promoting environments by considering both the home and workplace contexts and by taking into account the temporal attributes of contextual influences. Policymakers and urban planners are advised to take into account the workplace context and the temporal variability of neighborhood influences when allocating public PA facilities and public spaces.

Responses of anuran diversity to wetland characteristics and surrounding landscape in the Southern Andean Yungas, Argentina

AbstractModification and loss of natural habitats caused by human activities are among the main drivers of biodiversity decline worldwide. To evaluate how land‐use changes affect species diversity at different spatial scales, amphibians represent an excellent group given that their complex life cycle requires both aquatic and terrestrial habitats.In this study, the influence of wetland characteristics and surrounding landscape features on richness and functional diversity of anurans was investigated in 26 natural wetlands in a human‐modified landscape within the Southern Andean Yungas.The analysis was performed at two spatial scales: wetland scale (the breeding pond structure) and the surrounding landscape scale. The classification of the landscape was limited to land uses modified by human activities within concentric circular buffers (radius = 0.1, 0.2, 0.5, and 1 km) centred on each breeding pond.Generalized linear models were applied to investigate the relationship between environmental variables measured at different scales and anuran species richness and functional diversity, respectively.Pond area best explained the observed variation in both diversity measures, which is consistent with other studies on anuran diversity in disturbed landscapes. In contrast to regression models including landscape scale variables only, integrated models (which included variables on both scales) highly improved model fit.Conservation strategies for anuran species diversity in these altered Andean Yungas forests should include efforts to maintain or restore aquatic habitats (e.g. breeding ponds) placed within suitable landscapes.Successful long‐term management will require an understanding of relationships between habitat characteristics at different spatial scales to identify variables that relate to species diversity in such heterogeneous habitats.

DIFFERENTIAL RESPONSE OF EPIPHYTIC LICHEN TAXA TO AGRICULTURAL LAND USE IN A FRAGMENTED FOREST IN CENTRAL ARGENTINA

The seasonally dry subtropical forest, especially the Espinal forest in central Argentina (one of the most fragmented ecoregions), is affected by intensive agricultural activity. These activities are the main anthropogenic sources of atmospheric nitrogen compounds and their effects on lichens have been extensively studied, making them excellent ecological indicators. However, in the Espinal forest, the agricultural emissions are not monitored therefore analysis of the response of lichen diversity to these activities has a fundamental role in providing baseline data for monitoring. We analyzed changes in the frequency of families and genera of epiphytic lichen communities in 39 circular buffer areas at different scales comprising crop production, stock farming (feedlots), grazing and forest. Significant correlations at different taxonomic levels were detected in relation to land use. Frequency of Physciaceae increased with an increasing area of cropland to a distance of 600 m. Likewise a positive correlation was observed between the frequency of Collemataceae and the forest area. At genus level, Physcia presented a different response to livestock according to the intensity of production, since the frequency of these species increased in forest patches surrounded by grazing but decreased in areas with livestock farming where the stocking density is higher. This result could indicate an eutrophication process in the Espinal ecosystem, even for Physcia species. Our results can be used to start a list of indicator species to impact of agricultural in forest ecosystems.

Real-Time Adaptive Differential Feature-Based Protection Scheme for Isolated Microgrids Using Edge Computing

Inhabited isolated areas require independent power systems called isolated microgrids. Conventional protection schemes are not suitable for isolated microgrids due to their dependence on significant fault current. This article introduces an adaptive differential feature-based protection scheme for fault detection and faulty phase identification for isolated microgrids. Instead of differential currents, it proposes differential features, where edge computing is used to extract the features at point of measurement. The most informative one-dimensional feature is extracted from each phase at both ends of the line. The line differential feature is compared with an adaptive threshold to perform fault detection. The threshold is updated every second and is immune to system noises. Faulty phase identification is performed with a logical comparison. An in-memory circular buffer is proposed to store the local features in case of communication delay. Communication and synchronization are experimentally validated, and the worst-case latency is reported along with individual processing time for data acquisition, feature extraction, communication, and fault detection. Extensive validations are done with IEC-based and IEEE 13-node-based isolated microgrid. The test results are compared with state-of-the-art methods and proved that the proposed scheme is practical to be adopted in real- world isolated microgrids of different sizes and topologies.