Analysing the impact of trap shape and movement behaviour of ground‐dwelling arthropods on trap efficiency

Abstract

The most reliable estimates of the population abundance of ground‐dwelling arthropods are obtained almost entirely through trap counts. Trap shape can be easily controlled by the researcher, commonly the same trap design is employed in all sites within a given study. Few researchers really try to compare abundances (numbers of collected individuals) between studies because these are heavily influenced by environmental conditions, e.g. temperature, habitat structure and food sources available, directly affecting insect movement activity. We propose that useful insights can be obtained from a theoretical‐based approach. We focus on the interplay between trap shape (circle, square, slot), the underlying movement behaviour and the subsequent effect on captures. We simulate trap counts within these different geometries whilst considering movement processes with clear distinct properties, such as Brownian motion (BM), the correlated random walk (CRW) and the Lévy walk (LW). (a) We find that slot shaped traps are far less efficient than circular or square traps assuming same perimeter length, with differences which can exceed more than two‐fold. Such impacts of trap geometry are only realized if insect mobility is sufficiently large, which is known to significantly vary depending on type of habitat. (b) If the movement pattern incorporates localized forward persistence then trap counts accumulate at a much slower rate, and this rate decreases further with higher persistency. (c) If the movement behaviour is of Lévy type, then fastest catch rates are recorded in the case of circular trap, and the slowest for the slot trap, indicating that trap counts can strongly depend on trap shape. Lévy walks exacerbate the impact of geometry while CRW make these differences more inconsequential. In this study we reveal trap efficiencies and how movement type can alter capture rates. Such information contributes towards improved trap count interpretations, as required in ecological studies which make use of trapping systems.

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

“…'activity-density paradigm' (Thomas et al, 1998). An absolute interpretation of trap counts relating them to the population density in the vicinity of the trap is possible (Petrovskii et al, 2012(Petrovskii et al, , 2014Ahmed and Petrovskii, 2019) but it requires a succession of several trap counts and some information about the movement pattern such as the frequency distribution of step sizes and turning angles along the path (also the distribution of different movement modes, rest time, etc., in case of more complicated movement behaviours) as well as a good understanding of the effect of trap geometry (Ahmed and Petrovskii, 2019).…”

Mechanistic Modelling of Coronavirus Infections and the Impact of Confined Neighbourhoods on a Short Time Scale

“…See [58] supplementary information for details of this result. [1] Figure 2 (a) illustrates the movement path of a LW, a specialised type of RW composed of clusters of multiple short steps with longer steps in between them [38].…”

Mechanistic modelling of coronavirus infections and the impact of confined neighbourhoods on a short time scale

“…See Ahmed and Petrovskii (2019) supplementary information for details of this result 1 . 12, so that these RWs are 'comparable' to those presented in Figure 1.…”

“…Ahmed and Petrovskii (2019) compute a relationship between distribution scale-parameters, but consider the probability ε that move lengths do not exceed L, i.e. P(l < L) = ε = 1 − δ .…”