Temperate Grassland Afforestation Dynamics in the Aguapey Valuable Grassland Area between 1999 and 2020:Identifying the Need for Protection

Temperate grasslands are considered the most endangered terrestrial ecosystem worldwide; the existent areas play a key role in biodiversity conservation. The Aguapey Valuable Grassland Area (VGA), one of the most well-preserved temperate grassland areas within Argentina, is currently threatened by the anthropogenic expansion of exotic tree plantations. Little is known about the impacts of afforestation over temperate grassland landscape structures; therefore, the aim of this study is to characterize Aguapey VGA landscape structural changes between 1999 and 2020 based on remotely sensed data. This involves the generation of land cover maps for four annual periods based on unsupervised classification of Landsat 5 TM and 8 OLI images, the estimation of landscape metrics, and the transition analysis between land cover types and annual periods. The area covered by temperate grassland is shown to have decreased by almost 22% over the 20 year-period studied, due to the expansion of tree plantation cover. The afforestation process took place mainly between 1999 and 2007 in the northern region of the Aguapey VGA, which led first to grassland perforation and subsequently to grassland attrition; however, Aguapey’s cultural tradition of cattle ranching could have partially inhibited the expansion of exotic trees over the final years of the study. The evidence of grassland loss and fragmentation within the Aguapey VGA should be considered as an early warning to promote the development of sustainable land use policies, mainly focused towards the Aguapey VGA’s southern region where temperate grassland remains the predominant land cover type

Satellite-Based Monitoring of Primary Production in a Mediterranean Islet Post Black Rat Eradication

Invasive rodents have a detrimental impact on terrestrial ecosystem functioning, this is often exacerbated on small islands. Rat eradication campaigns are often used to deal with this environmental perturbation given their classification as invasive species. Studies assessing the effects of rodent control at ecosystem scale are scarce and thus little is known about the subsequent functional response of vegetation subsequent to rat control. In this work, we use remote sensing to assess the effects of black rat (Rattus rattus) eradication on Mediterranean vegetation productivity in the Sa Dragonera Islet, Mallorca (Spain). Rats feed on seeds, sprouts, and leaves of woody vegetation and hence we expect primary production to increase nine years after the rodenticide campaign. The Break Detection approach for additive season and trend (BFAST method) was adopted to examine changes in vegetation density before and after the eradication campaign in Sa Dragonera Islet (Balearic Islands), using a temporal series of monthly NDVI data extracted from Landsat imagery. The same temporal trends were examined for a control zone where no rat eradication took place, in order to control for weather-driven changes. The results of this study revealed changes across the 21-year monthly NDVI time series. However, the dates, magnitude, and trend of these changes could not be explicitly attributed to the action of rats, when compared to the historical changes on the islet and the changes found to co-occur within the control zone. These finding could, perhaps, be explained by the high resilience of Mediterranean shrubs to browsing including that of rat invasion. However, the results from the study appear to show that rat damage on specific plant species, with little contribution to global NDVI values, would be overshadowed by the effects of broader environmental factors in this remote sensing approach. The results suggest that the current passive restoration scheme imposed following eradication is not sufficient for effective ecosystem restoratio

Linking soils and human health: geospatial analysis of ground-sampled soil data in relation to community-level podoconiosis data in North West Cameroon

Background Podoconiosis is a form of leg swelling, which arises when individuals are exposed over time to red clay soil formed from alkaline volcanic rock. The exact causal agent of the disease is unknown. This study investigates associations between podoconiosis disease data and ground-sampled soil data from North West Cameroon. Methods The mineralogy and elemental concentrations were measured in the soil samples and the data were spatially interpolated. Mean soil values were calculated from a 3 km buffer region around the prevalence data points to perform statistical analysis. Analysis included Spearman's rho correlation, binary logistic regression and principal component analysis (PCA). Results Six elements, barium, beryllium, potassium, rubidium, strontium and thallium, as well as two minerals, potassium feldspar and quartz, were identified as statistically related to podoconiosis. PCA did not show distinct separation between the spatial locations with or without recorded cases of podoconiosis, indicating that other factors such as shoe-wearing behaviour and genetics may significantly influence podoconiosis occurrence and prevalence in North West Cameroon. Conclusion Several soil variables were statistically significantly related to podoconiosis. To further the current study, future investigations will look at the inflammatory pathway response of cells after exposure to these variables

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100

Understanding ‘saturation’ of radar signals over forests

There is an urgent need to quantify anthropogenic influence on forest carbon stocks. Using satellite-based radar imagery for such purposes has been challenged by the apparent loss of signal sensitivity to changes in forest aboveground volume (AGV) above a certain ‘saturation’ point. The causes of saturation are debated and often inadequately addressed, posing a major limitation to mapping AGV with the latest radar satellites. Using ground- and lidar-measurements across La Rioja province (Spain) and Denmark, we investigate how various properties of forest structure (average stem height, size and number density; proportion of canopy and understory cover) simultaneously influence radar backscatter. It is found that increases in backscatter due to changes in some properties (e.g. increasing stem sizes) are often compensated by equal magnitude decreases caused by other properties (e.g. decreasing stem numbers and increasing heights), contributing to the apparent saturation of the AGV-backscatter trend. Thus, knowledge of the impact of management practices and disturbances on forest structure may allow the use of radar imagery for forest biomass estimates beyond commonly reported saturation points

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

Raman spectroscopy as a tool to determine the thermal maturity of organic matter : application to sedimentary, metamorphic and structural geology

Raman spectrometry is a rapid, non-destructive alternative to conventional tools employed to assess the thermal alteration of organic matter (OM). Raman may be used to determine vitrinite reflectance equivalent OM maturity values for petroleum exploration, to provide temperature data for metamorphic studies, and to determine the maximum temperatures reached in fault zones. To achieve the wider utilisation of Raman, the spectrum processing method, and the positions and nomenclature of Raman bands and parameters, all need to be standardized. We assess the most widely used Raman parameters as well as the best analytical practices that have been proposed. Raman band separation and G-band full-width at half-maximum are the best parameters to estimate the maturity for rocks following diagenesis–metagenesis. For metamorphic studies, the ratios of band areas after performing deconvolution are generally used. Further work is needed on the second-order region, as well as assessing the potential of using integrated areas on the whole spectrum, to increase the calibrated temperature range of Raman parameters. Applying Raman spectroscopy on faults has potential to be able to infer both temperature and deformation processes. We propose a unified terminology for OM Raman bands and parameters that should be adopted in the future. The popular method of fitting several functions to a spectrum is generally unnecessary, as Raman parameters determined from an un-deconvoluted spectrum can track the maturity of OM. To progress the Raman application as a geothermometer a standardized approach must be developed and tested by means of an interlaboratory calibration exercise using reference materials

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website (https://osf.io/mhg94/).</p&gt

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts