Lightweight drones have emerged recently as a remote sensing survey tool of choice for ecologists, conservation practitioners and environmental scientists. In published work, there are plentiful details on the parameters and settings used for successful data capture, but in contrast there is a dearth of information describing the operational complexity of drone deployment. Information about the practices of flying in the field, whilst currently lacking, would be useful for others embarking on new drone-based investigations. As a group of dronepiloting scientists, we have operated lightweight drones for research in over 25 projects, in over 10 countries, and in polar, desert, coastal and tropical ecosystems, with many hundreds of hours of flying experience between us. The purpose of this paper was to document the lesser-reported methodological pitfalls of drone deployments so that other scientists can understand the spectrum of considerations that need to be accounted for prior to, and during drone survey flights. Herein, we describe the most common challenges encountered, alongside mitigation and remediation actions that increase the chances of safe and successful data capture. Challenges are grouped into the following categories: (i) pre-flight planning, (ii) flight operations, (iii) weather, (iv) redundancy, (v) data quality, (vi) batteries. We also discuss the importance of scientists undertaking ethical assessment of their drone practices, to identify and mitigate potential conflicts associated with drone use in particular areas. By sharing our experience, our intention is that the paper will assist those embarking on new drone deployments, increasing the efficacy of acquiring high-quality data from this new proximal aerial viewpoint.

Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa.This article is part of the theme issue ‘Collective movement ecology’.

Quantifying the extent of soil erosion at a fine spatial resolution can be time consuming and costly; however, proximal remote sensing approaches to collect topographic data present an emerging alternative for quantifying soil volumes lost via erosion. Herein we compare terrestrial laser scanning (TLS), and both unmanned aerial vehicle (UAV) and ground photography (GP) structurefrom-motion (SfM) derived topography. We compare the cost-effectiveness and accuracy of both SfM techniques to TLS for erosion gully surveying in upland landscapes, treating TLS as a benchmark. Further, we quantify volumetric soil loss estimates from upland gullies using digital surface models derived by each technique and subtracted from an interpolated pre-erosion surface. Soil loss estimates from UAV and GP SfM reconstructions were comparable to those from TLS, whereby the slopes of the relationship between all three techniques were not significantly different from 1:1 line. Only for the TLS to GP comparison was the intercept significantly different from zero, showing that GP is more capable of measuring the volumes of very small erosion features. In terms of costeffectiveness in data collection and processing time, both UAV and GP were comparable with the TLS on a per-site basis (13.4 and 8.2 person-hours versus 13.4 for TLS); however, GP was less suitable for surveying larger areas (127 person-hours per ha À1 versus 4.5 for UAV and 3.9 for TLS). Annual repeat surveys using GP were capable of detecting mean vertical erosion change on peaty soils. These first published estimates of whole gully erosion rates (0.077 m a À1 ) suggest that combined erosion rates on gully floors and walls are around three times the value of previous estimates, which largely characterize wind and rainsplash erosion of gully walls.

Lightweight, portable unmanned aerial vehicles (UAVs) or ‘drones’ are set to become a key component of a water resource management (WRM) toolkit, but are currently not widely used in this context. In practical WRM there is a growing need for fine-scale responsive data, which cannot be delivered from satellites or aircraft in a cost-effective way. Such a capability is needed where water supplies are located in spatially heterogeneous dynamic catchments. In this review, we demonstrate the step change in hydrological process understanding that could be delivered if WRM employed UAVs. The paper discusses a range of pragmatic concepts in UAV science for cost-effective and practical WRM, from choosing the right sensor and platform combination through to practical deployment and data processing challenges. The paper highlights that multi-sensor approaches, such as combining thermal imaging with fine-scale structure-from-motion topographic models, are currently best placed to assist in WRM decision-making because they provide a means of monitoring the spatio-temporal distribution of sources, sinks, and flows of water through landscapes. The manuscript highlights areas where research is needed to support the integration of UAVs into practical WRM, for example, in improving positional accuracy through integration of differential global positioning system sensors, and developing intelligent control of UAV platforms to optimize the accuracy of spatial data capture.

The academic literature of late is rich with examples of lightweight drones being used to capture data to support scientific research. Drone science is a blossoming field, but alongside a long-standing public concern about drone safety, the research community and our collaborators are increasingly calling for a 'code of best practice' for researchers who fly drones (no matter how small). Researchers who have long enjoyed the freedom of operating separately from 'hobbyist' and 'commercial' operators are now finding that their institutions and collaborators are demanding evidence of operational competence. In the UK, such competence can be formally accredited by obtaining a UK Civil Aviation Authority (CAA) 'permission for aerial work' (PfAW). Part of this process requires that the operators produce an 'operations manual' (OM) -a lengthy document explaining protocols for safe drone deployment, alongside maintenance and flight records. This article provides the frontispiece to an OM produced as part of a successful PfAW accreditation process. We share our OM, which is available as supplemental material to this article, in the spirit of research as a collaborative endeavour, with the aim that it will assist others facing the same stringent checks as ourselves, whilst also serving as a guide to safe flying that can be adapted and adopted by others. ARTICLE HISTORY