An Automated Image Analysis System to Measure and Count Organisms in Laboratory Microcosms

Mallard, François; Bourlot, Vincent Le; Tully, Thomas N.

doi:10.1371/journal.pone.0064387

Cited by 46 publications

(37 citation statements)

References 22 publications

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“…Such an 'every other day' food regime (Anson et al, 2005) enabled us to control and standardize the amount of food eaten by the groups of 10 individuals. The food restriction is moderate because the amount of food provided is sufficient to maintain on the long-term some populations composed of hundreds of individuals (Mallard et al, 2013;. Limiting the amount of food provided is also important to avoid the annoying growth of moulds that can occur if some uneaten food remains in the containers.…”

Section: Experimental Design and Life-history Trait Measurementsmentioning

confidence: 99%

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Within‐species variation in long‐term trajectories of growth, fecundity and mortality in the Collembola Folsomia candida

Mallard

Farina

Tully

2015

J of Evolutionary Biology

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Senescence--the progressive deterioration of organisms with age--affects many traits of which survival and reproduction are the most commonly studied. Recent comparative studies have revealed a remarkable amount of variation in the patterns of ageing across the tree of life. This between-species diversity raises many questions about the evolution of senescence and of the shapes of the life-history age trajectories. Here, we study how the different components of the shapes of these life-history age trajectories can vary within a single species to shed light on the possible constraints involved in their evolution. To do so, we closely followed in controlled laboratory conditions, and for more than 450 days, the mortality, body length and fecundity of small cohorts of two clonal lineages of the Collembola Folsomia candida. We studied three components of the adult mortality trajectory: the baseline mortality, onset and speed of senescence. We found that they can differ between strains of a single species in such a way that, remarkably, an increased life expectancy is not synonymous with a delayed senescence: the strain that grows bigger has the longest life expectancy but suffers from a precocious senescence. We observed marked differences between the strains in the asymptotic body length and reproductive investment. More generally, our results highlight the importance of finely describing the long-term trajectories of several life-history traits in order to better understand how the patterns of senescence have been shaped by natural selection.

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Section: Experimental Design and Life-history Trait Measurementsmentioning

confidence: 99%

“…We measured 1251 and 17 387 eggs from 36 and 242 clutches laid, respectively, by the HA and TO females. All the pictures were analysed using a dedicated IMAGEJ plugin (Mallard et al, 2013).…”

Section: Experimental Design and Life-history Trait Measurementsmentioning

confidence: 99%

Within‐species variation in long‐term trajectories of growth, fecundity and mortality in the Collembola Folsomia candida

Mallard

Farina

Tully

2015

J of Evolutionary Biology

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“…), in estimating sublethal effects of chemical agents in ecotoxicology (van Gestel ), in allometric studies (Mulder ) and in population growth modelling (Meli, Palmqvist & Forbes ). Techniques already exist to automatize these time‐consuming measurements in the laboratory (Mallard, Le Bourlot & Tully ; Bánszegi et al . ).…”

Section: Introductionmentioning

confidence: 99%

EDAPHOLOG monitoring system: automatic, real‐time detection of soil microarthropods

et al. 2016

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Summary Soil microarthropods as organic matter decomposers play an important role in soil functioning thus providing ecosystem services. However, ecosystem scale investigations on their abundance and dynamics are scarce because their high spatio‐temporal heterogeneity requires huge sample size. Processing and identifying large number of individuals are extremely labour‐intensive. We prototyped a device called EDAPHOLOG monitoring system that consists of (1) a probe that catches and detects microarthropods and estimates their body size; (2) a data logger transmitting data to a central data base; and (3) a Java application for retrieving data. We tested the device in three ways. First, we tested the precision and accuracy of detection and body size estimation of the device in the laboratory using microarthropods of five morphotypes: euedaphic Collembola, haired Collembola, scaled Collembola, Acari and Oribatida. Secondly, we compared the number of individuals collected by EDAPHOLOG traps, pitfall traps and soil extraction method in an alfalfa field. Thirdly, we deployed a total of 100 EDAPHOLOG probes in nine different habitats for over 3 months to demonstrate the applicability of the monitoring system. In the laboratory, EDAPHOLOG detected 95·6% of individuals; even the smallest morphotype (Oribatida, body size (mean ± SE): 0·58 ± 0·04 mm) was detected in 87·5% of cases. For body length estimation, we established a quadratic relationship between the estimated and measured body lengths; however, the R2 of the quadratic model was only 0·32. By comparing the three different sampling methods (EDAPHOLOG, pitfall traps and soil extraction), we concluded that EDAPHOLOG traps better select for soil microarthropods compared to classical pitfall traps, since the latter ones caught also many other arthropod species. Furthermore, the EDAPHOLOG traps caught more epigeic microarthropods and almost the same number of soil‐dwelling euedaphic microarthropods as the numbers collected by soil extraction. During the 3‐month‐long field test, the total numbers of detected and captured individuals agreed very well, although the device tended to overestimate the number probably due to counting also some soil particles falling into the probe. This trend was the same regardless of the total number caught. Surface‐dwelling epigeic and litter‐dwelling hemiedaphic microarthropods dominated the samples although soil‐dwelling euedaphic microarthropods were also caught. EDAPHOLOG is a novel device that consumes little power, rugged enough to operate in the field for extended periods of time, and can be remotely controlled. It detects surface‐ and soil‐dwelling microarthropods real‐time, and with high accuracy; however, it is less accurate to estimate body size. The system is especially suitable in field research focusing on temporal activity of microarthropods. Because it is non‐invasive, studies requiring long‐term monitoring, such as soil remediation or ecosystem restoration projects, will also find EDAPHOLOG useful.

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“…Studies that do use video analysis often either (1) lack the generality and flexibility needed for easy application across systems or set‐ups; (2) are not freely available or platform‐independent; (3) are cumbersome to install or use; (4) are not accurate enough to base demographic studies on, or (5) fail to provide measures of accuracy and robustness (e.g. Auclerc, Libourel, Salmon, Bels, & Ponge, ; Bánszegi, Kosztolányi, Bakonyi, Szabo, & Dombos, ; Færøvig, Andersen, & Hessen, ; Hooper et al., ; Mallard, Bourlot, & Tully, ; Noldus, Spink, & Tegelenbosch, ; Pennekamp et al., ; Pérez‐Escudero, Vicente‐Page, Hinz, Arganda, & De Polavieja, ). These drawbacks need to be addressed, before ecology can harness the full power and potential of automated image and video analysis.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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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.

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An Automated Image Analysis System to Measure and Count Organisms in Laboratory Microcosms

Cited by 46 publications

References 22 publications

Within‐species variation in long‐term trajectories of growth, fecundity and mortality in the Collembola Folsomia candida

Within‐species variation in long‐term trajectories of growth, fecundity and mortality in the Collembola Folsomia candida

EDAPHOLOG monitoring system: automatic, real‐time detection of soil microarthropods

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

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