scholarly journals A framework for leveraging animal movement to understand spatio-temporal disease dynamics

Author(s):  
Mark Wilber ◽  
Anni Yang ◽  
Raoul Boughton ◽  
Kezia Manlove ◽  
Ryan Miller ◽  
...  

The ongoing explosion of fine-resolution movement data in animal systems provides a unique opportunity to empirically quantify spatial, temporal, and individual variation in transmission risk and improve our ability to forecast disease outbreaks. However, we lack a generalizable framework that can leverage movement data to quantify transmission risk and how it affects pathogen invasion and persistence on heterogeneous landscapes. We developed a flexible framework “Movement-driven modeling of spatio-temporal infection risk” (MoveSTIR) that leverages diverse data on animal movement to derive metrics of direct and indirect contact by decomposing transmission into constituent processes of contact formation and duration and pathogen deposition and acquisition. We use MoveSTIR to demonstrate that ignoring fine-scale animal movements on actual landscapes can mis-characterize transmission risk and epidemiological dynamics. MoveSTIR unifies previous work on epidemiological contact networks and can address applied and theoretical questions at the nexus of movement and disease ecology.

2010 ◽  
Vol 365 (1550) ◽  
pp. 2303-2312 ◽  
Author(s):  
Mark Hebblewhite ◽  
Daniel T. Haydon

In the past decade, ecologists have witnessed vast improvements in our ability to collect animal movement data through animal-borne technology, such as through GPS or ARGOS systems. However, more data does not necessarily yield greater knowledge in understanding animal ecology and conservation. In this paper, we provide a review of the major benefits, problems and potential misuses of GPS/Argos technology to animal ecology and conservation. Benefits are obvious, and include the ability to collect fine-scale spatio-temporal location data on many previously impossible to study animals, such as ocean-going fish, migratory songbirds and long-distance migratory mammals. These benefits come with significant problems, however, imposed by frequent collar failures and high cost, which often results in weaker study design, reduced sample sizes and poorer statistical inference. In addition, we see the divorcing of biologists from a field-based understanding of animal ecology to be a growing problem. Despite these difficulties, GPS devices have provided significant benefits, particularly in the conservation and ecology of wide-ranging species. We conclude by offering suggestions for ecologists on which kinds of ecological questions would currently benefit the most from GPS/Argos technology, and where the technology has been potentially misused. Significant conceptual challenges remain, however, including the links between movement and behaviour, and movement and population dynamics.


Ecography ◽  
2018 ◽  
Vol 41 (11) ◽  
pp. 1801-1811 ◽  
Author(s):  
Chloe Bracis ◽  
Keith L. Bildstein ◽  
Thomas Mueller

2019 ◽  
Vol 374 (1781) ◽  
pp. 20180046 ◽  
Author(s):  
George Wittemyer ◽  
Joseph M. Northrup ◽  
Guillaume Bastille-Rousseau

Wildlife tracking is one of the most frequently employed approaches to monitor and study wildlife populations. To date, the application of tracking data to applied objectives has focused largely on the intensity of use by an animal in a location or the type of habitat. While this has provided valuable insights and advanced spatial wildlife management, such interpretation of tracking data does not capture the complexity of spatio-temporal processes inherent to animal behaviour and represented in the movement path. Here, we discuss current and emerging approaches to estimate the behavioural value of spatial locations using movement data, focusing on the nexus of conservation behaviour and movement ecology that can amplify the application of animal tracking research to contemporary conservation challenges. We highlight the importance of applying behavioural ecological approaches to the analysis of tracking data and discuss the utility of comparative approaches, optimization theory and economic valuation to gain understanding of movement strategies and gauge population-level processes. First, we discuss innovations in the most fundamental movement-based valuation of landscapes, the intensity of use of a location, namely dissecting temporal dynamics in and means by which to weight the intensity of use. We then expand our discussion to three less common currencies for behavioural valuation of landscapes, namely the assessment of the functional (i.e. what an individual is doing at a location), structural (i.e. how a location relates to use of the broader landscape) and fitness (i.e. the return from using a location) value of a location. Strengthening the behavioural theoretical underpinnings of movement ecology research promises to provide a deeper, mechanistic understanding of animal movement that can lead to unprecedented insights into the interaction between landscapes and animal behaviour and advance the application of movement research to conservation challenges. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.


2020 ◽  
Vol 9 (12) ◽  
pp. 732
Author(s):  
Hongjie Yu ◽  
Lin Liu ◽  
Bo Yang ◽  
Minxuan Lan

Crime prediction using machine learning and data fusion assimilation has become a hot topic. Most of the models rely on historical crime data and related environment variables. The activity of potential offenders affects the crime patterns, but the data with fine resolution have not been applied in the crime prediction. The goal of this study is to test the effect of the activity of potential offenders in the crime prediction by combining this data in the prediction models and assessing the prediction accuracies. This study uses the movement data of past offenders collected in routine police stop-and-question operations to infer the movement of future offenders. The offender movement data compensates historical crime data in a Spatio-Temporal Cokriging (ST-Cokriging) model for crime prediction. The models are implemented for weekly, biweekly, and quad-weekly prediction in the XT police district of ZG city, China. Results with the incorporation of the offender movement data are consistently better than those without it. The improvement is most pronounced for the weekly model, followed by the biweekly model, and the quad-weekly model. In sum, the addition of offender movement data enhances crime prediction, especially for short periods.


2005 ◽  
Vol 27 (2) ◽  
pp. 119 ◽  
Author(s):  
Mar K le ◽  
C McArthur

We investigated population density and patterns of habitat selection by the common brushtail possum (Trichosurus vulpecula fuliginosus) within a patchy forestry environment in north-west Tasmania. Population density was extremely low overall (0.04 animals.ha-1) and varied between habitats (0.01 ? 0.13 animals.ha-1). Selection indices from population surveys and animal movement data showed clear patterns for two closed habitats across two spatio-temporal scales: native forest was selected for, while 5 - 7 year old Eucalyptus nitens plantation was selected against, for both home range placement within the study area and habitats selectively used while foraging at night. Daytime habitat selection also showed the same pattern. We argue that native forest represented high quality habitat, offering both food and shelter (tree-hollows), while older plantation represented low quality habitat, lacking both of these resources. Results for open habitats (young Eucalyptus nitens plantation and grassland) were less clear. These patterns are discussed in relation to potential effects of a changing forestry landscape on this species.


2017 ◽  
Author(s):  
Mariëlle L. van Toor ◽  
Bart Kranstauber ◽  
Scott H. Newman ◽  
Diann J. Prosser ◽  
John Y. Takekawa ◽  
...  

AbstractContextHigh-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.ObjectivesWe introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.MethodsWe used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.ResultsSimulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corresponding to previous findings for this species.ConclusionsWe show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Shenglai Yin ◽  
Yanjie Xu ◽  
Nyambyar Batbayar ◽  
John Y. Takekawa ◽  
Yali Si ◽  
...  

Long-distance migrations influence the dynamics of hostpathogen interactions and understanding the role of migratory waterfowl in the spread of the highly pathogenic avian influenza viruses (HPAIV) is important. While wild geese have been associated with outbreak events, disease ecology of closely related species has not been studied to the same extent. The swan goose (Anser cygnoides) and the bar-headed goose (Anser indicus) are congeneric species with distinctly different HPAIV infection records; the former with few and the latter with numerous records. We compared movements of these species, as well as the more distantly related whooper swan (Cygnus cygnus) through their annual migratory cycle to better understand exposure to HPAIV events and how this compares within and between congeneric and noncongeneric species. In spite of their record of fewer infections, swan geese were more likely to come in contact with disease outbreaks than bar-headed geese. We propose two possible explanations: i) frequent prolonged contact with domestic ducks increases innate immunity in swan geese, and/or ii) the stress of high-elevation migration reduces immunity of bar-headed geese. Continued efforts to improve our understanding of species-level pathogen response is critical to assessing disease transmission risk.


Author(s):  
Heike Otten ◽  
Lennart Hildebrand ◽  
Till Nagel ◽  
Marian Dork ◽  
Boris Muller

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Patricia Kerches-Rogeri ◽  
Danielle Leal Ramos ◽  
Jukka Siren ◽  
Beatriz de Oliveira Teles ◽  
Rafael Souza Cruz Alves ◽  
...  

Abstract Background There is growing evidence that individuals within populations can vary in both habitat use and movement behavior, but it is still not clear how these two relate to each other. The aim of this study was to test if and how individual bats in a Stunira lilium population differ in their movement activity and preferences for landscape features in a correlated manner. Methods We collected data on movements of 27 individuals using radio telemetry. We fitted a heterogeneous-space diffusion model to the movement data in order to evaluate signals of movement variation among individuals. Results S. lilium individuals generally preferred open habitat with Solanum fruits, regularly switched between forest and open areas, and showed high site fidelity. Movement variation among individuals could be summarized in four movement syndromes: (1) average individuals, (2) forest specialists, (3) explorers which prefer Piper, and (4) open area specialists which prefer Solanum and Cecropia. Conclusions Individual preferences for landscape features plus food resource and movement activity were correlated, resulting in different movement syndromes. Individual variation in preferences for landscape elements and food resources highlight the importance of incorporating explicitly the interaction between landscape structure and individual heterogeneity in descriptions of animal movement.


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