Modelling the sound production of narwhals using a point process framework with memory effects
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Modelling the sound production of narwhals using a point process framework with memory effects. / Søltoft-Jensen, Aleksander; Heide-Jørgensen, Mads Peter; Ditlevsen, Susanne.
In: Annals of Applied Statistics, Vol. 14, No. 4, 2020, p. 2037-2052.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Modelling the sound production of narwhals using a point process framework with memory effects
AU - Søltoft-Jensen, Aleksander
AU - Heide-Jørgensen, Mads Peter
AU - Ditlevsen, Susanne
PY - 2020
Y1 - 2020
N2 - Obtaining an adequate description of the behaviour of narwhals in a pristine environment is important to understand natural behaviour as well as providing the means to determine potential changes in behaviour directly or indirectly caused by human activity. Based on Acousonde™ data from five narwhals in Scoresby Sound, this paper aims at modelling buzzing and calling rates of East Greenland narwhals as functions of time, space and, possibly, autoregressive memory. Both buzzing and calling are sounds produced by narwhals. Buzzing is a way for the whale to navigate and locate prey using echolocation, while calling is associated with social communication between whales. Logistic regression models without and with autoregressive components are compared based on AIC and comparatively assessed using diagnostics from point process theory. Adding an autoregressive component appears to improve the models, and further improvements for the buzzing model are made with a non-GLM extension. Effects of extrinsic covariates and memory are presented and interpreted. Buzzing occurs at deeper depths, and initiations of buzzes are separated by refractory periods. A possible feeding area is identified. Calling occurs closer to the surface, and, while the probability of calling in general is lower than buzzing, it is more likely that calls are clustered together rather than spread randomly.
AB - Obtaining an adequate description of the behaviour of narwhals in a pristine environment is important to understand natural behaviour as well as providing the means to determine potential changes in behaviour directly or indirectly caused by human activity. Based on Acousonde™ data from five narwhals in Scoresby Sound, this paper aims at modelling buzzing and calling rates of East Greenland narwhals as functions of time, space and, possibly, autoregressive memory. Both buzzing and calling are sounds produced by narwhals. Buzzing is a way for the whale to navigate and locate prey using echolocation, while calling is associated with social communication between whales. Logistic regression models without and with autoregressive components are compared based on AIC and comparatively assessed using diagnostics from point process theory. Adding an autoregressive component appears to improve the models, and further improvements for the buzzing model are made with a non-GLM extension. Effects of extrinsic covariates and memory are presented and interpreted. Buzzing occurs at deeper depths, and initiations of buzzes are separated by refractory periods. A possible feeding area is identified. Calling occurs closer to the surface, and, while the probability of calling in general is lower than buzzing, it is more likely that calls are clustered together rather than spread randomly.
KW - Autoregressive process
KW - Behavioural data of marine mammals
KW - Buzz and call
KW - Ecology
KW - Logistic regression with memory
KW - Narwhal
KW - Point process
UR - http://www.scopus.com/inward/record.url?scp=85098279965&partnerID=8YFLogxK
U2 - 10.1214/20-AOAS1379
DO - 10.1214/20-AOAS1379
M3 - Journal article
AN - SCOPUS:85098279965
VL - 14
SP - 2037
EP - 2052
JO - Annals of Applied Statistics
JF - Annals of Applied Statistics
SN - 1932-6157
IS - 4
ER -
ID: 254663911