Testing alternative methods for estimation of bird migration phenology from GPS tracking data

Soriano‐Redondo, Andrea; Acácio, Marta; Franco, Aldina M. A.; Martins, Bruno; Moreira, Francisco; Rogerson, Katharine F; Catry, Inês

doi:10.1111/ibi.12809

Cited by 32 publications

(35 citation statements)

References 28 publications

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“…The Bhote Koshi catchment, northeast of Kathmandu (red square in inset in Fig. 1), was also identified as one of the most affected areas, showing the greatest density of land-slides (Roback et al, 2018;Guo et al, 2017;Tanoli et al, 2017;Kargel et al, 2016;Collins and Jibson, 2015). The areal distribution of landslides away from the main shock epicentre appears to have been controlled by a combination of peak ground acceleration, slope, and fault rupture propagation (Roback et al, 2018;Martha et al, 2017;Regmi et al, 2016).…”

Section: Hazards and Their Interactions In The Area Of Studymentioning

confidence: 96%

“…Some authors pointed out that many coseismic landslides occurred at high elevations (e.g. Tanoli et al, 2017), and it was observed that after the earthquake, a large number of landslides remained disconnected from the channels, with significant amounts of material stored on the hillslopes (Cook et al, 2016;Collins and Jibson, 2015), including boulders that are still visible today on valley flanks. During the 2015 monsoon, new landslides were triggered along with the expansion of coseismic landslides, but loose material remained stored on the hillslopes by the end of the monsoon (Cook et al, 2016).…”

Section: Hazards and Their Interactions In The Area Of Studymentioning

confidence: 99%

“…Landslides and debris flows can also occur as a consequence of heavy and persistent rainfall during the monsoon. Every year the area receives up to 4100 mm of rainfall between June and September (Tanoli et al, 2017). Active monsoons can trigger or reactivate landslides; an example is the Jure landslide (roughly 15 km southwest of our study sites) that occurred in August 2014 (Acharya et al, 2016).…”

Section: Hazards and Their Interactions In The Area Of Studymentioning

confidence: 99%

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Development of smart boulders to monitor mass movements via the Internet of Things: a pilot study in Nepal

et al. 2021

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Abstract. Boulder movement can be observed not only in rockfall activity, but also in association with other landslide types such as rockslides, soil slides in colluvium originating from previous rockslides, and debris flows. Large boulders pose a direct threat to life and key infrastructure in terms of amplifying landslide and flood hazards as they move from the slopes to the river network. Despite the hazard they pose, boulders have not been directly targeted as a mean to detect landslide movement or used in dedicated early warning systems. We use an innovative monitoring system to observe boulder movement occurring in different geomorphological settings before reaching the river system. Our study focuses on an area in the upper Bhote Koshi catchment northeast of Kathmandu, where the Araniko highway is subjected to periodic landsliding and floods during the monsoons and was heavily affected by coseismic landslides during the 2015 Gorkha earthquake. In the area, damage by boulders to properties, roads, and other key infrastructure, such as hydropower plants, is observed every year. We embedded trackers in 23 boulders spread between a landslide body and two debris flow channels before the monsoon season of 2019. The trackers, equipped with accelerometers, can detect small angular changes in the orientation of boulders and large forces acting on them. The data can be transmitted in real time via a long-range wide-area network (LoRaWAN®) gateway to a server. Nine of the tagged boulders registered patterns in the accelerometer data compatible with downslope movements. Of these, six lying within the landslide body show small angular changes, indicating a reactivation during the rainfall period and a movement of the landslide mass. Three boulders located in a debris flow channel show sharp changes in orientation, likely corresponding to larger free movements and sudden rotations. This study highlights the fact that this innovative, cost-effective technology can be used to monitor boulders in hazard-prone sites by identifying the onset of potentially hazardous movement in real time and may thus establish the basis for early warning systems, particularly in developing countries where expensive hazard mitigation strategies may be unfeasible.

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Section: Hazards and Their Interactions In The Area Of Studymentioning

confidence: 96%

Section: Hazards and Their Interactions In The Area Of Studymentioning

confidence: 99%

Section: Hazards and Their Interactions In The Area Of Studymentioning

confidence: 99%

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Development of smart boulders to monitor mass movements via the Internet of Things: a pilot study in Nepal

et al. 2021

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“…Despite the importance of understanding migration phenology and common reporting of phenological information in movement-related wildlife analyses, a consistent methodology for determining departure and arrival dates has not yet emerged (Cerritelli et al, 2020; Soriano-Redondo et al, 2020). Often, there is no straightforward reproducible methodology, and authors provide vague descriptions of methods used to assign migration phenology to each individual (Shephard et al, 2015; Shimada et al, 2014).…”

Section: Example Applicationsmentioning

confidence: 99%

Using Piecewise Regression to Identify Biological Phenomena in Biotelemetry Datasets

Wolfson

Fieberg

Andersen

2021

Preprint

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Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal’s location, movement characteristics, external environmental conditions, and internal physiological status. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. We provide five example applications highlighting a variety of taxonomic species, data streams, timescales, and biological phenomena. These examples include a short-term behavioral response (flee and return) by a trumpeter swan (Cygnus buccinator) immediately following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose (Alces alces); a physiological response (spike in heart-rate) in a black bear (Ursus americanus) to a stressful stimulus (presence of a drone); a mortality event of a trumpeter swan signaled by changes in collar temperature and Overall Dynamic Body Acceleration; and an unsupervised method for identifying the onset, return, duration, and staging use of sandhill crane (Antigone canadensis) migration. We implement analyses using the mcp package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criterion and cross-validation measures. This approach uses simple modeling approaches that are accessible to a wide audience and is a straightforward means of assessing a variety of biologically relevant changes in animal behavior.

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“…feeding behaviours among other things (e.g. Soriano-Redondo et al, 2020;Panicker et al, 2019;Gilbert et al, 2016). Whilst some trackers store the data internally and transmit it to a server via GSM when a network becomes available, the trackers used for this study have been developed to allow for a network of nodes that communicate wireless and in real time through an Internet of Things (IoT) system (e.g.…”

Section: Introductionmentioning

confidence: 99%

Development of smart boulders to monitor mass movements via the Internet of Things: A pilot study in Nepal

Dini¹,

Bennett²,

Franco³

et al. 2020

Preprint

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Abstract. Boulder movement can be observed not only in rock fall activity, but also in association with other landslide types such as rock slides, soil slides in colluvium originated from previous rock slides and debris flows. Large boulders pose a direct threat to life and key infrastructure, amplifying landslide and flood hazards, as they move from the slopes to the river network. Despite the hazard they pose, boulders have not been directly targeted as a mean to detect landslide movement or used in dedicated early warning systems. We use an innovative monitoring system to observe boulder movement occurring in different geomorphological settings, before reaching the river system. Our study focuses on an area in the upper Bhote Koshi catchment northeast of Kathmandu, where the Araniko highway is subjected to periodic landsliding and floods during the monsoons and was heavily affected by coseismic landslides during the 2015 Gorkha earthquake. In the area, damage by boulders to properties, roads and other key infrastructure, such as hydropower plants, is observed every year. We embedded trackers in 23 boulders spread between a landslide body and two debris flow channels, before the monsoon season of 2019. The trackers, equipped with accelerometers, can detect small angular changes in boulders orientation and large forces acting on them. The data can be transmitted in real time, via a long-range wide area network (LoRaWAN®) gateway to a server. Nine of the tagged boulders registered patterns in the accelerometer data compatible with downslope movements. Of these, six lying within the landslide body show small angular changes, indicating a reactivation during the rainfall period and a movement consistent with the landslide mass. Three boulders, located in a debris flow channel, show sharp changes in orientation, likely corresponding to larger free movements and sudden rotations. This study highlights that this innovative, cost-effective technology can be used to monitor boulders in hazard prone sites, identifying in real time the onset of movement, and may thus set the basis for early warning systems, particularly in developing countries, where expensive hazard mitigation strategies may be unfeasible.

show abstract

Testing alternative methods for estimation of bird migration phenology from GPS tracking data

Cited by 32 publications

References 28 publications

Development of smart boulders to monitor mass movements via the Internet of Things: a pilot study in Nepal

Development of smart boulders to monitor mass movements via the Internet of Things: a pilot study in Nepal

Using Piecewise Regression to Identify Biological Phenomena in Biotelemetry Datasets

Development of smart boulders to monitor mass movements via the Internet of Things: A pilot study in Nepal

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