Using time-series similarity measures to compare animal movement trajectories in ecology

Identifying and understanding patterns in movement data are amongst the principal aims of movement ecology. By quantifying the similarity of movement trajectories, inferences can be made about diverse processes, ranging from individual specialisation to the ontogeny of foraging strategies. Movement analysis is not unique to ecology however, and methods for estimating the similarity of movement trajectories have been developed in other fields but are currently under-utilised by ecologists. Here, we introduce five commonly used measures of trajectory similarity: dynamic time warping (DTW), longest common subsequence (LCSS), edit distance for real sequences (EDR), Fréchet distance and nearest neighbour distance (NND), of which only NND is routinely used by ecologists. We investigate the performance of each of these measures by simulating movement trajectories using an Ornstein-Uhlenbeck (OU) model in which we varied the following parameters: (1) the point of attraction, (2) the strength of attraction to this point and (3) the noise or volatility added to the movement process in order to determine which measures were most responsive to such changes. In addition, we demonstrate how these measures can be applied using movement trajectories of breeding northern gannets (Morus bassanus) by performing trajectory clustering on a large ecological dataset. Simulations showed that DTW and Fréchet distance were most responsive to changes in movement parameters and were able to distinguish between all the different parameter combinations we trialled. In contrast, NND was the least sensitive measure trialled. When applied to our gannet dataset, the five similarity measures were highly correlated despite differences in their underlying calculation. Clustering of trajectories within and across individuals allowed us to easily visualise and compare patterns of space use over time across a large dataset. Trajectory clusters reflected the bearing on which birds departed the colony and highlighted the use of well-known bathymetric features. As both the volume of movement data and the need to quantify similarity amongst animal trajectories grow, the measures described here and the bridge they provide to other fields of research will become increasingly useful in ecology

Habitat selection and habitat use of gray foxes (Urocyon cinereoargenteus) on trespass cannabis grows.

Trespass cannabis grow sites, otherwise known as illegal cultivation sites on public lands, are extremely hazardous to the environment and can severely impact wildlife movement and behavior. Trespass grow sites are dangerous to wildlife as they negatively impact the quality of habitat and wildlife behavior through habitat modification, pesticide use, discarding of trash, and poaching on national forests. I researched gray fox habitat selection and habitat use at six different grow sites in the Klamath National Forest and Shasta-Trinity National Forest in northwestern California. I deployed GPS collars on three gray foxes at two of those grow sites and three gray foxes at two reference sites between September 2020 and April 2021. I used autocorrelated kernel density estimates and resource-selection functions, using generalized linear models, to evaluate gray fox habitat selection and found that two of the three gray foxes selected trespass grow sites when grow sites were found within their home ranges. I evaluated the combined data of all six collared foxes in regard to environmental characteristics and found that foxes prefer areas with a greater aspect, specifically those facing south, southwest, and west. I deployed eighty-eight game cameras across six trespass grow sites to collect photo and video media for 22 months. I used the Shapiro Wilks Normality test and the Mann Whitney U test to compare gray fox behavior across different grow site features. There were a higher number of detections of gray foxes at process areas, camp sites, toxicant piles, and trash pits. Locomotion behavior was observed at similar levels across all site features. Vigilant behaviors were most observed at toxicant piles, camp sites, trails, and cultivation plots. Marking behaviors were most common at process areas, trash pits, and toxicant piles. The most recorded behavior was locomotion, followed by vigilance, scent marking, and then feeding, with no documented behaviors of resting. Proportionally more foxes were recorded at camp sites, toxicant piles, trash pits, and process areas than in cultivation plots or along trails, which signifies that gray foxes utilize areas hypothesized as more attractive within the grow site. This research shows that foxes use trespass grows, though future researchers are encouraged to include a larger sample size collared gray foxes and of the cultivation plot and trail locations. Resource agencies must prioritize elimination and reclamation of these sites. Otherwise, wildlife will continue to suffer direct and indirect effects as they utilize the trespass grow sites present in their home ranges

Reassessing the Ranging Behavior of Black-And-White Ruffed Lemurs (Varecia variegata) in Ranomafana National Park, Madagascar

This study investigates black-and-white ruffed lemur (Varecia variegata) space use and movement using autocorrelated kernel density estimation (AKDE), a new methodology available from the continuous-time movement model (ctmm) package in R. Data were collected from 24 adults and subadults (10 males, 11 females, 3 subadult males) living in two adjacent V. variegata communities at Mangevo bush camp in Ranomafana National Park, Madagascar (RNP) for 11 months (February – December 2008) to estimate annual and seasonal patterns of individual and community-level range use. Autocorrelated kernel density estimates generated in this study are compared to earlier kernel density estimates from Baden et al. (2021) to determine whether and to what extent the same patterns emerge. Patterns of annual and seasonal variation are also compared across i) age-sex class, ii) reproductive seasonality, iii) site topography and iv) resource availability and distribution. Results reveal that both annual and seasonal home range size and spatial use varied between males and females, as well as within subgroups. Females exhibited larger annual home ranges than males, though not significantly so, and ranging behaviors varied by reproductive season. The topography of Mangevo appears to be a significant driver of range use, as mountain ridges, community boundaries (i.e., territorial space use), and neighborhoods are all structured around the distribution of food resources which are situated primarily at lower elevations between ridgelines throughout the ruffed lemur community

Reinforcements of a Greater Sage-Grouse Population in Utah: Applications for Range-Wide and Local Conservation Translocation Efforts

In a small, isolated greater sage-grouse (Centrocercus urophasianus) population in the Sheeprock Mountain Sage-Grouse Management Area (SGMA) located in Utah\u27s West Desert, peak male lek counts declined from 190 males in 2006 to 23 males in 2015. A collaborative effort across all federal, state, and local partners yielded 146 (40 male, 106 female) sage-grouse captured, marked with either a very-high frequency or global positioning systems (GPS) transmitter, and translocated into the Sheeprock sage-grouse management area between 2016 and 2019, complete with radiotelemetry monitoring during the spring and summers of 2016-2020 translocated individuals in addition to radiotelemetry monitoring of 39 (12 male, 27 female) resident Sheeprock sage-grouse. Coincident management efforts included extensive habitat restoration, predator control, and monitoring off-highway vehicle (OHV) recreation. To evaluate the movements, habitat selection, demographics, and genetics of this population, I performed a behaviorally segmented, movement-based habitat selection analysis, an integrated population model (IPM) of the Sheeprock SGMA and the translocation source populations, and analyses quantifying allelic richness, allelic frequency, and genetic heterogeneity. Additionally, I evaluated the GPS transmitters\u27 performance to monitor the grouse, which is essential for quantifying and accounting for fix error for GPS-based spatial models. The probability of sage-grouse beginning in the exploratory phase at the time of release was marginally lower for adult males and females than yearlings. The analysis also suggested that to reduce post-release dispersal, practitioners should prioritize release sites to maximize the restricted state selection in areas closer to mesic habitat, higher elevation, and lower tree cover. The IPM predicted declining populations following translocations due to low recruitment, dictated by low chick survival, and estimated population abundance of 22 individuals (95% CI: 2 – 63) by 2027 by 2027. However, we also detected an increase in allelic richness and the potential for the increased admixture of the source population genetics in the reinforced population

Statistical modelling of collective animal movement: with an application to reindeer movement in northern Sweden

The ways in which animals move are a complex phenomena, from small scale interactions to larger migratory movement. Internal and external stimuli govern a variety of behavioural patterns whose processes are vital for species survival. Analysing these movement and behavioural processes can have significant applications for conservation and management. Although there are many statistical tools readily available for investigating animal movement, they are largely directed towards individual-level cases and do not consider the group movement present in collective species such as ungulates. This thesis aims to redress the shortcomings of statistical literature by providing a modelling framework for collective animal movement in continuous time. Our modelling approach builds upon general themes of group movement originally put forward by Langrock et al. (2014), where each individual in the group is at times attracted to an unobserved leading point. However, the behaviour of each individual can switch between ‘following the group’ and ‘moving independently’, modelled as an Ornstein Uhlenbeck process and Brownian motion respectively. The movement of the leading point is also modelled as an Ornstein-Uhlenbeck process or, if we forgo the leader’s drift term, as Brownian motion. An inhomogeneous Kalman filter Markov chain Monte Carlo algorithm is used to estimate the diffusion and switching parameters and the behavioural states of each individual at a given time point. We assess the model’s performance in a variety of simulated settings before providing a real world application using the location data of semi-domesticated reindeer (rangifer tarandus). We extend this methodology by allowing switching to depend explicitly on covariate information. We define a general auxiliary model for the inclusion of covariate data which accounts for a wide range of environmental heterogeneity. We give a simulated illustration where the animals switch behaviour sinusoidally depending on the time of day. Then, we revisit the reindeer application by including covariate data on insect harassment, which is thought to influence reindeer movement

Stochastic models of animal movement and habitat selection

The analysis of animal movement reveals important features of habitat preferences and behaviours, and informs environmental conservation decisions. In this thesis, we present new statistical methods, to tackle the problem of scale dependence in models of animal movement. The inferences obtained from most existing approaches are tied to a particular spatio-temporal scale, which makes the interpretation and comparison of results difficult. We first focus on models of habitat selection, which combine tracking data and environmental data, to understand the drivers of animal movement. The two most popular approaches describe habitat selection on two different scales, and their parameters have different interpretations. We propose a time series approach to integrate local and global habitat selection. We explain how stochastic processes with known stationary distributions can be used, to describe both the short-term transition density and the long-term equilibrium distribution of the movement. The proposed approach captures both the short-term and long-term habitat selection. We suggest using Markov chain Monte Carlo (MCMC) algorithms to model animal movement. A MCMC algorithm describes transition rules, which lead to a limiting distribution: its target distribution. We also suggest the Langevin diffusion process as a continuous-time model of movement with known stationary distribution. We describe methods of estimation, to obtain habitat selection and movement parameters from tracking data. We then turn to the problem of the time formulation in models of animal movement and behaviour. Most widely-used models describe movement in discrete time, and their results are tied to the time scale of the observed data. We extend a popular continuous-time model of movement, to include behavioural heterogeneity. The approach can be used to identify behavioural phases from movement data collected at irregular intervals, and with measurement error. We describe a framework of Bayesian inference, to estimate movement parameters and behavioural phases from tracking data

The influence of environmental variation on individual foraging and habitat selection behaviour of the European nightjar

Animals experience a variety of environmental stressors, for example climate and habitat change. These changes can alter the distribution and population dynamics of species indirectly through disruption of behavioural processes, including foraging. Collecting behavioural data, such as foraging tracks, from multiple individuals can help to identify how response to habitat change, is driven by factors such as resource distribution, intra-specific competition and intrinsic factors such as sex and age. This thesis combined behavioural and dietary information collected from individual European nightjars Caprimulgus europaeus, to analyse variation in behaviour amongst the population, in response to habitat change and the consequences this might have in terms of future change and for beneficial management. This population of nightjars showed significant individual variation in home range size and habitat selection therein. Home ranges sizes increased by 1% and decreased by 9% in wetland and newly cleared habitat respectively. This indicated that although birds possess individual preferences for specific habitat types, there are foraging constraints that affect multiple individuals. Foraging behaviour changed most strongly in relation to habitat type, NDVI and more weakly in relation to the lunar cycle and temperature. Time spent foraging increased in cleared habitat (β: 0.03, R2 0.08, p: 0.07), which became more available during the study. Males spent 33% of their time foraging compared to females which spent only 18.6% of their time foraging, representing differing breeding roles. However, strong methodological influence was clear, whereby an increase in the fix interval from 3 to 5 minutes caused a 39% increase in step length, unaccounted for by year or habitat change. Individual diet composition differed and changed between years, in response to prey availability, however common species occurred in 40-50% of samples. Overall nightjars selected for larger moths compared to local availability. Collectively, my results and demonstrated flexibility at the population level and the potential to respond positively to habitat. As a species specialising in a spatially- and temporally varying prey resource, maintenance of complex habitat mosaics that encourage a wide diversity of moth and other flying insect species, along with the diversity of habitat types to encourage breeding and survival of all individuals