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2011
"This chapter discusses how models, combined with modern data sources and statistical methods, can be used to test different hypotheses about the causes of migration. Mathematical formalisms for migration are presented. The ecological mechanisms that could spontaneously have given rise to migration-like patterns of space use from the interaction within and between groups of animals and their environment are discussed, showing that migration is best seen as to lie on a continuum from sedentary to nomadic movement patterns and not as a clearly distinct movement behaviour. Given the multitude of potential processes leading to migration, and the constraints imposed by data collection methods, it may be difficult to observe and identify the original cause. With this caveat in mind, the use of inferential methods to detect, quantify and identify the underlying mechanisms of migration is discussed and the links between models, data and inference are illustrated using three case studies. ##################################################### Updates: The book already sold out! A corrected reprint is available since Dec 2011."
Estimating migration parameters of individuals and populations is vital for their conservation and management. Studies on animal movements and migration often depend upon location data from tracked animals and it is important that such data are appropriately analyzed for reliable estimates of migration and effective management of moving animals. The Net Squared Displacement (NSD) approach for modelling animal movement is being increasingly used as it can objectively quantify migration characteristics and separate different types of movements from migration. However, the ability of NSD to properly classify the movement patterns of individuals has been criticized and issues related to study design arise with respect to starting locations of the data/animals, data sampling regime and extent of movement of species. We address the issues raised over NSD using tracking data from 319 moose (Alces alces) in Sweden. Moose is an ideal species to test this approach, as it can be sedentary, nomadic, dispersing or migratory and individuals vary in their extent, timing and duration of migration. We propose a two-step process of using the NSD approach by first classifying movement modes using mean squared displacement (MSD) instead of NSD and then estimating the extent, duration and timing of migration using NSD. We show that the NSD approach is robust to the choice of starting dates except when the start date occurs during the migratory phase. We also show that the starting location of the animal has a marginal influence on the correct quantification of migration characteristics. The number of locations per day (1-48) did not significantly affect the performance of non-linear mixed effects models, which correctly distinguished migration from other movement types, however, high-resolution data had a significant negative influence on estimates for the timing of migrations. The extent of movement, however, had an effect on the classification of movements, and individuals undertaking short- distance migrations can be misclassified as other movements such as sedentary or nomadic. Our study raises important considerations for designing, analysing and interpreting movement ecology studies, and how these should be determined by the biology of the species and the ecological and conservation questions in focus.
2011 •
1. Decreasing rate of migration in several species as a consequence of climate change and anthropic pressure, together with increasing evidence of space-use strategies intermediate between residency and complete migration, are very strong motivations to evaluate migration occurrence and features in animal populations. 2. The main goal of this paper was to perform a relative comparison between methods for identifying and characterising migration at the individual and population level on the basis of animal location data. 3. We classified 104 yearly individual trajectories from five populations of three deer species as migratory or non-migratory, by means of three methods: seasonal home range overlap, spatiotemporal separation of seasonal clusters, and the Net Squared Displacement (NSD) method. For migratory cases, we also measured timing and distance of migration and residence time on the summer range. Finally, we compared the classification in migration cases across methods and populations. 4. All methods consistently identified migration at the population level, i.e., they coherently distinguished between complete or almost complete migratory populations and partially migratory populations. However, in the latter case, methods coherently classified only about 50% of the single cases, i.e. they classified differently at the individual-animal level. We therefore infer that the comparison of methods may help point to ‘less-stereotyped’ cases in the residency-to-migration continuum. For cases consistently classified by all methods, no significant differences were found in migration distance, or residence time on summer ranges. Timing of migration estimated by NSD was earlier than by the other two methods, both for spring and autumn migrations.
Journal of Animal Ecology
A model-driven approach to quantify migration patterns: individual, regional and yearly differences2011 •
"Note: This is an extension of my squared displacement modelling approach, published in the book chapter Borger & Fryxell (2012, Oxford University Press), to include the case of migration. Beware, this publication on migration is somewhat preliminary in several aspects. Before using it on migration or other data I strongly suggest to refer to the original presentation of the method in Borger & Fryxell (2012, OUP), as it is considerably more rigorous and markedly improved. ### Abstract: 1. Animal migration has long intrigued scientists and wildlife managers alike, yet migratory species face increasing challenges because of habitat fragmentation, climate change and over-exploitation. Central to the understanding migratory species is the objective discrimination between migratory and nonmigratory individuals in a given population, quantifying the timing, duration and distance of migration and the ability to predict migratory movements. 2. Here, we propose a uniform statistical framework to (i) separate migration from other movement behaviours, (ii) quantify migration parameters without the need for arbitrary cut-off criteria and (iii) test predictability across individuals, time and space. 3. We first validated our novel approach by simulating data based on established theoretical movement patterns. We then formulated the expected shapes of squared displacement patterns as nonlinear models for a suite of movement behaviours to test the ability of our method to distinguish between migratory movement and other movement types. 4. We then tested our approached empirically using 108 wild Global Positioning System (GPS)-collared moose Alces alces in Scandinavia as a study system because they exhibit a wide range of movement behaviours, including resident, migrating and dispersing individuals, within the same population. Applying our approach showed that 87% and 67% of our Swedish and Norwegian subpopulations, respectively, can be classified as migratory. 5. Using nonlinear mixed effects models for all migratory individuals we showed that the distance, timing and duration of migration differed between the sexes and between years, with additional individual differences accounting for a large part of the variation in the distance of migration but not in the timing or duration. Overall, the model explained most of the variation (92%) and also had high predictive power for the same individuals over time (69%) as well as between study populations (74%). 6. The high predictive ability of the approach suggests that it can help increase our understanding of the drivers of migration and could provide key quantitative information for understanding and managing a broad range of migratory species."
Partial migration is a crucial mobility pattern in animal ecology. Unlike complete migrations that take place when all the individuals in a population migrate with a clear separation of ranges, partial migrations are migrations that often follow modalities and times that vary from animal to animal. As a result the distinction between migratory and nonmigratory behavior becomes less defined. In this paper, we present an interdisciplinary effort geared to evaluate whether a recent time-aware, density-based clustering technique, called SeqScan, relying on the novel concept of object’s presence can be effectively applied to the study of partial migrations. To that end, we propose an extended framework centered on SeqScan, comprising a noise model for the detection of fine-grained movement patterns, i.e. excursions and inter-cluster transitions, and an internal time-aware validity index, for clustering evaluation. Furthermore, we contrast SeqScan with a recent technique developed in the context of animal ecology and grounded on statistical methods. For the study, we use real trajectories from two large herbivorous species located in Bavaria. We argue that the classification capabilities of SeqScan are comparable to those of the reference method. Moreover, the SeqScan framework overcomes important limitations of more conventional techniques, offering, in particular, the opportunity of quantifying the mobility behavior of individuals.
2009 •
The Springer Series on Demographic Methods and Population Analysis
The Indirect Estimation of Migration2010 •
Studying multiple individuals from multiple populations would add knowledge about the proportion of different movement strategies (migratory vs. resident) and how space use patterns vary within and across populations. This allows for effective conservation or management of partially migratory animal populations by identifying the appropriate size of management units and temporal interventions. However, this knowledge is often lacking as only a few individuals from a single population are tracked in space and time. To understand the drivers of intraspecific variation in movement patterns across a broad scale, we analyzed the multiannual space use of 307 moose (Alces alces), containing 544 single-year trajectories, from 10 study areas that are spread over a 1500-km latitudinal gradient. Using a novel approach, we quantified within-and among-population variation in movement and space use patterns. We identified the movement strategy (migratory, sedentary, nomadic, or dispersal) of moose and computed annual and seasonal home ranges. Individuals demonstrated variable movement strategies from migration to year-round residence. Summer home ranges were larger in northern study areas, whereas no geographical trends were detected among populations in winter home ranges. Individual-level traits, such as sex and age, along with factors related to the landscape, such as land use and habitat, explained variation within populations, whereas climatic factors such as temperature and vegetative productivity explained variation among populations. Importantly, the variables that explained individual-level variation in space use within populations were different for all our populations. We demonstrate the intricate interplay between individual life history and landscape scale variables and how they may determine the observed movement patterns and influence the scale of management.
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2019 •
Global Ecology and …
How landscape dynamics link individual‐to population‐level movement patterns: a multispecies comparison of ungulate relocation data2011 •
Journal of Animal Ecology
Mechanistic models of animal migration behaviour - their diversity, structure and use2013 •
Ecological Monographs
Migration in geographic and ecological space by a large herbivorePhilosophical Transactions of the Royal Society B: Biological Sciences
Building the bridge between animal movement and population dynamics2010 •