Inferring the rules of social interaction in migrating caribou

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’

Optimal nitrogen application rates for three intensively-managed hardwood tree species in the southeastern USA

Forest production can be limited by nutrient and water availability, and tree species are expected to respond differently to fertilization and irrigation. Despite these common expectations, multi-species comparisons are rare, especially ones implementing a range of fertilization rates crossed with irrigation. This study compares the response of three forest hardwood species to numerous nitrogen (N) fertilization levels and water availability using a novel non-replicated technique. A range of N levels was included to determine how N affected the growth response curve, and statistical procedures for comparing these non-linear response functions are presented. We used growth and yield data to calculate the Land Expectation Value (LEV) for these intensive management treatments, and to determine the optimal growing conditions (accounting for tree productivity and grower expenses). To accomplish these objectives, we used a series of cottonwood, sycamore, and sweetgum plots that received a range of N fertilization with or without irrigation. Regression is an economical approach to define treatment responses in large-scale experiments, and we recommend >3 treatment levels so the response of any single plot does not disproportionally influence the line. The non-replicated plots showed a strong positive N response below 150 kg N ha -1 yr -1, beyond which little response was observed. However, different amounts of fertilization were required for the greatest biomass accumulation rate in each tree species. Cottonwood and sycamore growth was optimized with less than 150 kg N ha -1 yr -1 while sweetgum growth was optimized with less than 100 kg N ha -1 yr -1. Results from this experiment should be representative of many of the nutrient-poor soils in the Coastal Plain in the southeastern USA. The LEVs were not positive for any treatment x genotype combination tested when using irrigation or liquid fertilizer, but our analysis showed that several non-irrigated treatments in sycamore and sweetgum did result in positive LEVs when fertilized with granular urea

The Lancet Psychiatry Commission : a blueprint for protecting physical health in people with mental illness

No abstract available

Tracking fine-scale structural changes in coastal dune morphology using kite aerial photography and uncertainty-assessed Structure-from-Motion photogrammetry (dataset)

The data includes aerial photos of a section of St. Gothian Dunes sand dune system (North Cornwall, UK) at 6 different periods of time. Six of the datasets are obtained with kite aerial photography and one has been captured with a lightweight drone. Photos are processed and ready to be used with Agisoft Photoscan to produce dense point clouds. Also included are the positions of Ground Control Points for each survey as well as vector data indicating the areas investigated. Lastly, change clouds (processed data) from the M3C2-PM process are included.The article associated with this dataset is located in ORE at: http://hdl.handle.net/10871/34019This is the dataset used for the Duffy et al. (2018) article "Tracking fine-scale structural changes in coastal dune morphology using kite aerial photography and uncertainty-assessed structure-from-motion photogrammetry" published in Remote Sensing.This research was funded by [Natural Environment Research Council] grant number [570009815

Supporting Information from Inferring the rules of social interaction in migrating caribou

Information; Tables S1-S4; Figures S1-S

Assessing climate change associated sea level rise impacts on sea turtle nesting beaches using drones, photogrammetry and a novel GPS system

Climate change associated sea level rise (SLR) is expected to have profound impacts on coastal areas, affecting many species including sea turtles which depend on these habitats for egg incubation. Being able to accurately model beach topography using digital terrain models (DTMs) is therefore crucial to project SLR impacts and develop effective conservation strategies. Traditional survey methods are typically low-cost with low accuracy or high-cost with high accuracy. We present a novel combination of drone-based photogrammetry and a low-cost and portable real-time kinematic (RTK) GPS to create DTMs which are highly accurate (<10 cm error) and visually realistic. This methodology is ideal for surveying coastal sites, can be broadly applied to other species and habitats, and is a relevant tool in supporting the development of Specially Protected Areas. Here we applied this method as a case-study to project three SLR scenarios (0.48, 0.63 and 1.20 m) and assess the future vulnerability and viability of a key nesting habitat for sympatric loggerhead (Caretta caretta) and green turtle (Chelonia mydas) at a key rookery in the Mediterranean. We combined the DTM with 5 years of nest survey data describing location and clutch depth, to identify (1) regions with highest nest densities, (2) nest elevation by species and beach, and (3) estimated proportion of nests inundated under each SLR scenario. On average, green turtles nested at higher elevations than loggerheads (1.8 m vs. 1.32 m, respectively). However, because green turtles dig deeper nests than loggerheads (0.76 m vs. 0.50 m, respectively), these were at similar risk of inundation. For a SLR of 1.2 m, we estimated a loss of 67.3% for loggerhead turtle nests and 59.1% for green turtle nests. Existing natural and artificial barriers may affect the ability of these nesting habitats to remain suitable for nesting through beach migration. This article is protected by copyright. All rights reserved.info:eu-repo/semantics/acceptedVersio