Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry

Being dynamic in time and space, seasonal snow represents a difficult target for ongoing in situ measurement and characterisation. Improved understanding and modelling of the seasonal snowpack requires mapping snow depth at fine spatial resolution. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial variability of snow depth is evaluated within an alpine catchment of the Pisa Range, New Zealand. Digital surface models (DSMs) at 0.15&thinsp;m spatial resolution in autumn (snow-free reference) winter (2 August 2016) and spring (10 September 2016) allowed mapping of snow depth via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by the propagation of check point residuals from the aero-triangulation of constituent DSMs and via comparison of snow-free regions of the spring and autumn DSMs. The accuracy of RPAS-derived snow depth was validated with in situ snow probe measurements. Results for snow-free areas between DSMs acquired in autumn and spring demonstrate repeatability yet also reveal that elevation errors follow a distribution that substantially departs from a normal distribution, symptomatic of the influence of DSM co-registration and terrain characteristics on vertical uncertainty. Error propagation saw snow depth mapped with an accuracy of ±0.08&thinsp;m (90&thinsp;% c.l.). This is lower than the characterization of uncertainties on snow-free areas (±0.14&thinsp;m). Comparisons between RPAS and in situ snow depth measurements confirm this level of performance of RPAS photogrammetry while also highlighting the influence of vegetation on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine-scale spatial variability. Despite limitations accompanying RPAS photogrammetry, which are relevant to similar applications of surface and volume change analysis, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological catchment ( ∼ 0.4&thinsp;km2) at very high resolution. Resolving snowpack features associated with redistribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data will enhance understanding of physical processes controlling spatial distributions of seasonal snow and their relative importance on varying spatial and temporal scales.</p

New European Union fisheries regulations could benefit conservation of marine animals

Peer Reviewe

Patterns of satellite tagged hen harrier disappearances suggest widespread illegal killing on British grouse moors

Natural England commenced a Hen Harrier Recovery Project in 2002. This tracking study was funded exclusively by Natural England and is part of their on-going work on hen harrier conservation. We thank Hamish Smith and staff at the Hawk and Owl Trust for contributing data from four hen harriers they have tracked. We are grateful for the time of many volunteers in the field who monitored and searched for harriers: Pat Martin, Gavin Craggs, Pete Davies, Derek Hayward, Martin Davison, Mick Carroll, Paul Howarth, Ian Thomson, and Elsie Ashworth. We thank Judith Smith and Phil Skinner for sponsoring tags. Also we would like to thank the Wildlife Crime Officers in Lancashire, Yorkshire, Co Durham and Northumberland for their assistance. Thanks also to Jeremy Wilson and Pat Thompson for useful comments on this manuscript. We are grateful to staff at Microwave Telemetry Inc. and CLS France for data archiving. The complete data sets analysed in this study are not publicly available due to the sensitivity of the locational data but are available from the corresponding author on reasonable request and with permission of Natural England. The source data for Figs. 1 and 2 have been provided as a Source Data file.Peer reviewedPublisher PD

Serum Concentrations of Myostatin and Myostatin-Interacting Proteins do not differ between young and Scarcopenic elderly men

Peer reviewedPostprin

Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management

Effective wildlife management is needed for conservation, economic and human well-being objectives. However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement. New methods which address these issues and offer effective wildlife management are required. We used an individual-based model to predict the efficacy of a sacrificial feeding area in preventing grazing damage by mute swans (Cygnus olor) to adjacent river vegetation of high conservation and economic value. The accuracy of model predictions was assessed by a comparison with observed field data, whilst prediction robustness was evaluated using a sensitivity analysis. We used repeated simulations to evaluate how the efficacy of the sacrificial feeding area was regulated by (i) food quantity, (ii) food quality, and (iii) the functional response of the forager. Our model gave accurate predictions of aquatic plant biomass, carrying capacity, swan mortality, swan foraging effort, and river use. Our model predicted that increased sacrificial feeding area food quantity and quality would prevent the depletion of aquatic plant biomass by swans. When the functional response for vegetation in the sacrificial feeding area was increased, the food quantity and quality in the sacrificial feeding area required to protect adjacent aquatic plants were reduced. Our study demonstrates how the insights of behavioural ecology can be used to inform wildlife management. The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems