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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., (© The Author(s) 2020. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)

The assessment of landscape condition for large herbivores, also known as foodscapes, is fast gaining interest in conservation and landscape management programs worldwide. Although traditional approaches are now being replaced by satellite imagery, several technical issues still need to be addressed before full standardization of remote sensing methods for these purposes. We present a low-cost method, based on the use of a modified blue/green/near-infrared (BG-NIR) camera housed on a small-Unmanned Aircraft System (sUAS), to create foodscapes for a generalist Mediterranean ungulate: the Iberian Ibex (Capra pyrenaica) in Northeast Spain. Faecal cuticle micro-histological analyses were used to assess the dietary preferences of ibexes and then individuals of the most common plant species (n = 19) were georeferenced to use as test samples. Because of the seasonal pattern in vegetation activity, based on the NDVI (Smooth term Month  = 21.5, p-value < .01, R 2  = 43%, from a GAM), images were recorded in winter and spring to represent contrasting vegetation phenology using two flight heights above ground level (30 and 60 m). Additionally, the range of image pixel sizes was 3.5-30 cm with the smallest pixel size representing the highest resolution. Boosted Trees were used to classify plant taxa based on spectral reflectance and create a foodscape of the study area. The number of target species, the sampling season, the height of flight and the image resolution were analysed to determine the accuracy of mapping the foodscape. The highest classification error (70.66%) was present when classifying all plant species using a 30 cm pixel size from acquisitions at 30 m height. The lowest error (18.7%), however, was present when predicting plants preferred by ibexes, at 3.5 cm pixel size acquired at 60 m height. This methodology can help to successfully monitor food availability and seasonality and to identify individual species., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The loss of unimproved grassland has led to species decline in a wide range of taxonomic groups. Agricultural intensification has resulted in fragmented patches of remnant grassland habitat both across Europe and internationally. The monitoring of remnant patches of this habitat is critically important, however, traditional surveying of large, remote landscapes is a notoriously costly and difficult task. The emergence of small-Unmanned Aircraft Systems (sUAS) equipped with low-cost multi-spectral cameras offer an alternative to traditional grassland survey methods, and have the potential to progress and innovate the monitoring and future conservation of this habitat globally. The aim of this article is to investigate the potential of sUAS for rapid detection of threatened unimproved grassland and to test the use of an Enhanced Normalized Difference Vegetation Index (ENDVI). A sUAS aerial survey is undertaken at a site nationally recognised as an important location for fragmented unimproved mesotrophic grassland, within the south east of England, UK. A multispectral camera is used to capture imagery in the visible and near-infrared spectrums, and the ENDVI calculated and its discrimination performance compared to a range of more traditional vegetation indices. In order to validate the results of analysis, ground quadrat surveys were carried out to determine the grassland communities present. Quadrat surveys identified three community types within the site; unimproved grassland, improved grassland and rush pasture. All six vegetation indices tested were able to distinguish between the broad habitat types of grassland and rush pasture; whilst only three could differentiate vegetation at a community level. The Enhanced Normalized Difference Vegetation Index (ENDVI) was the most effective index when differentiating grasslands at the community level. The mechanisms behind the improved performance of the ENDVI are discussed and recommendations are made for areas of future research and study.

Run-of-river (ROR) hydroelectric power (HEP) schemes are often presumed to be less ecologically damaging than large-scale storage HEP schemes. However, there is currently limited scientific evidence on their ecological impact. The aim of this article is to investigate the effects of ROR HEP schemes on communities of invertebrates in temperate streams and rivers, using a multi-site Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 22 systematically-selected ROR HEP schemes and 22 systematically-selected paired control sites. Five widely-used family-level invertebrate metrics (richness, evenness, LIFE, E-PSI, WHPT) were analysed using a linear mixed effects model. The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the evenness of the invertebrate community. However, no statistically significant effects were detected on the four other metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future invertebrate community impact studies., Competing Interests: This research was co-funded by the Natural Environment Research Council (http://www.nerc.ac.uk/) and the Environment Agency (https://www.gov.uk/government/organisations/environment-agency) under grant reference NE/M019810/1. Only GSB received the funding for this work. The Environment Agency had a role in the original collection of the routine surveillance monitoring data used in this study, though it was not collected specifically for the purposes of this study. The study was designed by GSB and it was his decision to publish the work. HGO (an employee of the Environment Agency funding body) did contribute towards the preparation of the manuscript. JCG is employed by Precima Inc. (https://www.precima.com/). The funder provided support in the form of salaries for authors [JCG], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This commercial affiliation does not alter our adherence to PLOS ONE policies on sharing data and materials(as detailed online in our guide for authors http://www.PLOSone.org/static/editorial.action#competing). The specific roles of these authors are articulated in the ‘author contributions’ section.

The potential environmental impacts of large-scale storage hydroelectric power (HEP) schemes have been well-documented in the literature. In Europe, awareness of these potential impacts and limited opportunities for politically-acceptable medium- to large-scale schemes, have caused attention to focus on smaller-scale HEP schemes, particularly run-of-river (ROR) schemes, to contribute to meeting renewable energy targets. Run-of-river HEP schemes are often presumed to be less environmentally damaging than large-scale storage HEP schemes. However, there is currently a lack of peer-reviewed studies on their physical and ecological impact. The aim of this article was to investigate the effects of ROR HEP schemes on communities of fish in temperate streams and rivers, using a Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 23 systematically-selected ROR HEP schemes and 23 systematically-selected paired control sites. Six area-normalised metrics of fish community composition were analysed using a linear mixed effects model (number of species, number of fish, number of Atlantic salmon-Salmo salar, number of >1 year old Atlantic salmon, number of brown trout-Salmo trutta, and number of >1 year old brown trout). The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the number of species. However, no statistically significant effects were detected on the other five metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future fish community impact studies.

It is generally well recognised that suspended particulate matter (SPM), from nano-scale particles to sand-sized sediments, can cause serious degradation of aquatic ecosystems. However, at present there is a poor understanding of the SPM conditions that water quality managers should aim to achieve in contrasting environments in order to support good ecological status. In this article, we analyse long-term SPM data collected from a wide range of reference-condition temperate environments in the UK (638 stream/river sites comprising 42 different ecosystem-types). One-way analysis of variance reveals that there is a statistically significant difference (p < 0.001) between the background SPM concentrations observed in contrasting ecosystems that are in reference condition (minimal anthropogenic disturbance). One of the 42 ecosystems studied had mean background concentrations of SPM in excess of the current European Union (EU) water quality guideline, despite being in reference condition. The implications of this finding are that the EU's current blanket water quality guideline (25 mg L(-1) for all environments) is inappropriate for this specific ecosystem-type which will be non-compliant with the guideline regardless of the intensity of land-use. The other 41 ecosystems studied had mean concentrations below the current EU water quality guideline. However, this does not necessarily mean that the guideline is appropriate for these ecosystems, as previous research has demonstrated that detrimental impacts can be experienced by some freshwater organisms, of all trophic levels, when exposed to concentrations below 25 mg L(-1). Therefore, it is suggested here that it is likely that some ecosystems, particularly those with mean concentrations in the 0.00-5.99 mg L(-1) range, require much lower guideline values in order to be effectively protected. We propose a model for predicting environment-specific water quality guidelines for SPM. In order to develop this model, the 638 reference condition sites were first classified into one of five mean background SPM ranges (0.00-5.99, 6.00-11.99, 12.00-17.99, 18.00-23.99 and >24.00 mg L(-1)). Stepwise Multiple Discriminant Analysis (MDA) of these ranges showed that a site's SPM range can be predicted as a function of: mean annual air temperature, mean annual precipitation, mean altitude of upstream catchment, distance from source, slope to source, channel width and depth, the percentage of catchment area comprised of clay, chalk, and hard rock solid geology, and the percentage of the catchment area comprised of blown sand as the surface (drift) material. The MDA technique, with cross-validation (Wilks-Lambda 0.358, p 0.000), can predict the correct or the next closest SPM range of a site in 90% of cases. This technique can also predict SPM range membership in a probabilistic manner, allowing for an estimate of uncertainty to be made in the allocation of a site to an environment-specific SPM range., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

The South Downs Area of Outstanding Natural Beauty, UK, is an internationally and nationally important landscape, which contains a significant proportion (28%) of the southeast of England's calcareous grassland resource. The traditional calcareous grassland habitats characteristic of the downland landscape have suffered significant losses since the Second World War, and the remaining sites are small, fragmented and confined to the more marginal areas, often steeper slopes. The re-creation and restoration of these species rich grasslands has become a central aim of national and regional conservation organisations, however, the methods and mechanism by which restoration sites could be identified has not been clarified. The purpose of this work was to study the landscape characteristics of the calcareous grassland systems, and by use of GIS-based modelling approaches identify those sites on the downland most suited to the re-establishment and expansion of calcareous grasslands. Using a weighted scoring approach, a GIS-based Habitat Suitability Model is developed for use as a tool to support strategic landscape evaluation and to provide a method of identifying sites for targeted restoration. The approach models the relationship between specific grassland communities and topographic variables, and is applied to the South Downs landscape in order to predict the nature of grassland communities likely to result from restoration efforts at specific sites.