Remote mapping of foodscapes using sUAS and a low cost BG-NIR sensor.

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, R2 = 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.

The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index.

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.

The effects of run-of-river hydroelectric power schemes on invertebrate community composition in temperate streams and rivers.

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.

The Effects of Run-of-River Hydroelectric Power Schemes on Fish Community Composition in Temperate Streams and Rivers.

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.