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Caste-specific demography and phenology in bumblebees; modelling BeeWalk data

Matechou, Eleni, Freeman, Stephen N., Comont, Richard (2018) Caste-specific demography and phenology in bumblebees; modelling BeeWalk data. Journal of Agricultural, Biological, and Environmental Statistics, 23 (4). pp. 427-445. ISSN 1085-7117. (doi:10.1007/s13253-018-0332-y) (KAR id:67427)

Abstract

We present novel dynamic mixture models for the monitoring of bumblebee populations on an

unprecedented geographical scale, motivated by the UK citizen science scheme BeeWalk. The models

allow us for the First time to estimate bumblebee phenology and within-season productivity, defined as

the number of individuals in each caste per colony in the population in that year, from citizen science

data. All of these parameters are estimated separately for each caste, giving a means of considerable

ecological detail in examining temporal changes in the complex life-cycle of a social insect in the wild.

Due to the dynamic nature of the models, we are able to produce population trends for a number of

UK bumblebee species using the available time-series. Via an additional simulation exercise, we show

the extent to which useful information will increase if the survey continues, and expands in scale,

as expected. Bumblebees are extraordinarily important components of the ecosystem, providing

pollination services of vast economic impact and functioning as indicator species for changes in climate

or land-use. Our results demonstrate the changes in both phenology and productivity between years

and provide an invaluable tool for monitoring bumblebee populations, many of which are in decline,

in the UK and around the world.

Item Type: Article
DOI/Identification number: 10.1007/s13253-018-0332-y
Uncontrolled keywords: citizen science, mixture models, phenology, population trends, productivity, stopover models, SEAK
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Eleni Matechou
Date Deposited: 27 Jun 2018 11:54 UTC
Last Modified: 09 Jan 2024 11:21 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67427 (The current URI for this page, for reference purposes)

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