Revisitation analysis uncovers spatio-temporal patterns in animal movement data

Ecography ◽  
2018 ◽  
Vol 41 (11) ◽  
pp. 1801-1811 ◽  
Author(s):  
Chloe Bracis ◽  
Keith L. Bildstein ◽  
Thomas Mueller
Keyword(s):  
Animal Movement ◽  
Temporal Patterns ◽  
Movement Data ◽  
Spatio Temporal

scholarly journals Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology

2010 ◽  
Vol 365 (1550) ◽  
pp. 2303-2312 ◽  
Author(s):  
Mark Hebblewhite ◽  
Daniel T. Haydon
Keyword(s):  
Animal Ecology ◽  
Animal Movement ◽  
Gps Telemetry ◽  
Long Distance ◽  
Location Data ◽  
The Past ◽  
Movement Data ◽  
Migratory Songbirds ◽  
Spatio Temporal ◽  
Gps Devices

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.

scholarly journals Behavioural valuation of landscapes using movement data

2019 ◽  
Vol 374 (1781) ◽  
pp. 20180046 ◽  
Author(s):  
George Wittemyer ◽  
Joseph M. Northrup ◽  
Guillaume Bastille-Rousseau
Keyword(s):  
Animal Movement ◽  
Temporal Dynamics ◽  
Economic Valuation ◽  
Movement Ecology ◽  
Optimization Theory ◽  
Population Level ◽  
Animal Behaviour ◽  
Tracking Data ◽  
Movement Data ◽  
Spatio Temporal

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’.

scholarly journals Facilitating insights with a user adaptable dashboard, illustrated by airport connectivity data

2018 ◽  
Vol 1 ◽  
pp. 1-6
Author(s):  
Ieva Dobraja ◽  
Menno-Jan Kraak ◽  
Yuri Engelhardt
Keyword(s):  
Temporal Patterns ◽  
Data Representation ◽  
Data Exploration ◽  
Temporal Data ◽  
Movement Data ◽  
Graphical Data ◽  
Multiple Data ◽  
Multi Temporal ◽  
Spatio Temporal ◽  
Heterogeneous Multiscale

Since the movement data exist, there have been approaches to collect and analyze them to get insights. This kind of data is often heterogeneous, multiscale and multi-temporal. Those interested in spatio-temporal patterns of movement data do not gain insights from textual descriptions. Therefore, visualization is required. As spatio-temporal movement data can be complex because size and characteristics, it is even challenging to create an overview of it. Plotting all the data on the screen will not be the solution as it likely will result into cluttered images where no data exploration is possible. To ensure that users will receive the information they are interested in, it is important to provide a graphical data representation environment where exploration to gain insights are possible not only in the overall level but at sub-levels as well. A dashboard would be a solution the representation of heterogeneous spatio- temporal data. It provides an overview and helps to unravel the complexity of data by splitting data in multiple data representation views. The adaptability of dashboard will help to reveal the information which cannot be seen in the overview.

Habitat selection by common brushtail possums in a patchy eucalypt-forestry environment.

2005 ◽  
Vol 27 (2) ◽  
pp. 119 ◽  
Author(s):  
Mar K le ◽  
C McArthur
Keyword(s):  
Habitat Selection ◽  
Population Density ◽  
Animal Movement ◽  
Brushtail Possum ◽  
Native Forest ◽  
Eucalyptus Nitens ◽  
North West ◽  
Movement Data ◽  
Selection Indices ◽  
Spatio Temporal

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.

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

2021 ◽  
Author(s):  
Mark Wilber ◽  
Anni Yang ◽  
Raoul Boughton ◽  
Kezia Manlove ◽  
Ryan Miller ◽  
...  
Keyword(s):  
Disease Ecology ◽  
Animal Movement ◽  
Disease Outbreaks ◽  
Transmission Risk ◽  
Indirect Contact ◽  
Pathogen Invasion ◽  
Movement Data ◽  
Spatio Temporal ◽  
Diverse Data ◽  
Fine Resolution

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.

SPATIO-TEMPORAL PATTERNS OF WORKFORCE IN INDIA DURING 1981-2011

2019 ◽  
Vol 38 (2) ◽  
pp. 239-254
Author(s):  
M.B. SINGH ◽  
◽  
NITIN KUMAR MISHRA ◽  
Keyword(s):  
Temporal Patterns ◽  
Spatio Temporal
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