trackdem: Automated particle tracking to obtain population counts and size distributions from videos in r

Abstract

The possibilities for image analysis in scientific research are substantial: the costs of digital cameras and data storage are sharply decreasing, and automated image analyses greatly increase the scale, reproducibility and robustness of biological studies. However, automated image analysis in ecological and evolutionary studies is still in its infancy. There is a clear need for easy to use and accessible tools. Here, we provide a general purpose method to obtain estimates of population densities, individual body sizes and behavioural metrics from video material of moving organisms. The methods are supplied as a new r‐package trackdem, which provides a flexible, easy to install and use, generally applicable and accurate way to analyse ecological video data. The package can detect and track moving particles, count individuals and estimate individual sizes using background detection, particle identification and particle tracking algorithms. Machine learning is implemented to reduce the influence of noise in lower quality videos or to distinguish a single species in multi‐species systems. We show that trackdem provides accurate population counts and body size distributions. Using a series of simulations, we show that our estimates are robust against high levels of noise in videos. When applied to live populations of Daphnia magna, our methods obtained accurate and unbiased estimates of population counts, individual sizes and size distributions, as verified by manual counting and measuring. The package trackdem is also directly usable for movement analysis, for instance in behavioural ecology, as illustrated by the tracking of insects, fish, cars and humans. Within 24 hr, we obtained 192 accurate population counts and body sizes of 22,154 individuals. Such results underscore that automated analysis can improve robustness and reproducibility, and greatly increase the scope of studies in ecology and evolution.

Population‐level responses to temperature, density and clonal differences in Daphnia magna as revealed by integral projection modelling

“…A movie of approximately 4 s was made with a digital camera (Sony Handycam, HDR‐CX115). We used newly developed R‐package trackdem to obtain estimates of population counts (Bruijning, Visser, Hallmann, & Jongejans, 2018). In short, movies were converted into an image sequence and loaded in the R‐environment (R Core Team ).…”

“…The four kernels describing all daily transition probabilities were (a) survival S d (z) , (b) growth G d (z′|z) , describing probabilities for surviving individuals of size z at time t to obtain size z′ at day t + 1 , (c) reproduction R d (z) and (d) an offspring size distribution D d (z′|z) describing probabilities of obtaining offspring with size z’ at t + 1 given a maternal size z at Day t . We created a composite IPM, whereby the four kernels were functions of, in addition to z , temperature T , observed population density N as estimated using trackdem (Bruijning, Visser, et al., 2018) (except for survival) and lineage C : …”

Do genetic differences in growth thermal reaction norms maintain genetic variation in timing of diapause induction?

“…For the video, all animals of a population were transferred to a transparent glass baking dish, which was put on top of a light table to obtain a high contrast between animals and the background. These videos were later used to estimate population sizes and body size distributions over time using the R-package trackdem v. 0.3.1 (Bruijning et al, 2018). Videos made by us (N = 153) under the same conditions as described above were used by Bruijning et al (2018) to evaluate the accuracy of trackdem.…”

“…These videos were later used to estimate population sizes and body size distributions over time using the R-package trackdem v. 0.3.1 (Bruijning et al, 2018). Videos made by us (N = 153) under the same conditions as described above were used by Bruijning et al (2018) to evaluate the accuracy of trackdem. This analysis revealed highly accurate and unbiased estimates of the population size ( Fig.…”

“…This analysis revealed highly accurate and unbiased estimates of the population size ( Fig. 3 in Bruijning et al, 2018). Trackdem uses automated particle tracking to keep track of the number of moving particles (here: individual daphnids) of potentially different size, in addition to outputting the size of the particles (number of pixels).…”