Skip to main content
Kent Academic Repository

Estimating insect population density from trap counts

Petrovskii, Sergei, Bearup, Daniel, Ahmed, Danish Ali, Blackshaw, Rod (2011) Estimating insect population density from trap counts. Ecological Complexity, 10 . pp. 69-82. ISSN 1476-945X. (doi:10.1016/j.ecocom.2011.10.002) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:64322)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/https://doi.org/10.1016/j.ecocom...

Abstract

Trapping is commonly used in various pest insect monitoring programs as well as in many ecological field studies. Despite this, the interpretation of trap counts is challenging. Traps are effective at providing relative counts that enable comparisons but are poor at delivering information on the absolute population size. Making better use of trap data is impeded by the lack of a consistent underlying theoretical model. In this paper, we aim to overcome current limitations of trapping methods used in ecological studies through developing a theoretical and methodological framework that enables a direct estimate of populations from trap counts. We regard insect movement as stochastic Brownian motion and use two different mathematical approaches accordingly. We first use individual-based modelling to reproduce trap catch patterns and study the effect of individual movement on observed catch patterns. We then consider a ‘mean-field’ diffusion model and show that it is capable of revealing the generic relationship between trap catches and population density.

Item Type: Article
DOI/Identification number: 10.1016/j.ecocom.2011.10.002
Uncontrolled keywords: Insect monitoring, Trapping, Trap counts, Random walk, Diffusion
Subjects: Q Science
Q Science > QA Mathematics (inc Computing science) > QA377 Partial differential equations
Q Science > QH Natural history > QH541 Ecology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Daniel Bearup
Date Deposited: 08 Nov 2017 12:36 UTC
Last Modified: 16 Nov 2021 10:24 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/64322 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.