The effects of marking and capture on recapture frequencies of butterflies

Integrating high-speed videos in capture-mark-recapture studies of insects

Capture-mark-recapture (CMR) studies have been used extensively in ecology and evolution. While it is feasible to apply CMR in some animals, it is considerably more challenging in small fast-moving species such as insects. In these groups, low recapture rates can bias estimates of demographic parameters, thereby handicapping effective analysis and management of wild populations. Here, we use high-speed videos (HSV) to capture two large dragonfly species, Anax junius and Rhionaeschna multicolor, that rarely land and, thus, are particularly challenging for CMR studies. We test whether HSV, compared to conventional "eye" observations, increases the "resighting" rates and, consequently, improves estimates of both survival rates and the effects of demographic covariates on survival. We show that the use of HSV increases the number of resights by 64% in A. junius and 48% in R. multicolor. HSV improved our estimates of resighting and survival probability which were either under- or overestimated with the conventional observations. Including HSV improved credible intervals for resighting rate and survival probability by 190% and 130% in A. junius and R. multicolor, respectively. Hence, it has the potential to open the door to a wide range of research possibilities on species that are traditionally difficult to monitor with distance sampling, including within insects and birds.

Spot on: using camera traps to individually monitor one of the world’s largest lizards

Abstract ContextEstimating animal abundance often relies on being able to identify individuals; however, this can be challenging, especially when applied to large animals that are difficult to trap and handle. Camera traps have provided a non-invasive alternative by using natural markings to individually identify animals within image data. Although camera traps have been used to individually identify mammals, they are yet to be widely applied to other taxa, such as reptiles. AimsWe assessed the capacity of camera traps to provide images that allow for individual identification of the world’s fourth-largest lizard species, the perentie (Varanus giganteus), and demonstrate other basic morphological and behavioural data that can be gleaned from camera-trap images. MethodsVertically orientated cameras were deployed at 115 sites across a 10000km2 area in north-western Australia for an average of 216 days. We used spot patterning located on the dorsal surface of perenties to identify individuals from camera-trap imagery, with the assistance of freely available spot ID software. We also measured snout-to-vent length (SVL) by using image-analysis software, and collected image time-stamp data to analyse temporal activity patterns. ResultsNinety-two individuals were identified, and individuals were recorded moving distances of up to 1975m. Confidence in identification accuracy was generally high (91%), and estimated SVL measurements varied by an average of 6.7% (min=1.8%, max=21.3%) of individual SVL averages. Larger perenties (SVL of >45cm) were detected mostly between dawn and noon, and in the late afternoon and early evening, whereas small perenties (SVL of <30cm) were rarely recorded in the evening. ConclusionsCamera traps can be used to individually identify large reptiles with unique markings, and can also provide data on movement, morphology and temporal activity. Accounting for uneven substrates under cameras could improve the accuracy of morphological estimates. Given that camera traps struggle to detect small, nocturnal reptiles, further research is required to examine whether cameras miss smaller individuals in the late afternoon and evening. ImplicationsCamera traps are increasingly being used to monitor reptile species. The ability to individually identify animals provides another tool for herpetological research worldwide.

Monitoring butterfly abundance: beyond Pollard walks

Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.g., among sites) and time (e.g., among years), it remains unclear whether index counts truly reflect population sizes and trends. This study compares capture-mark-recapture (absolute abundance) and count-index (relative abundance) monitoring methods in three species (Maculinea nausithous and Iolana iolas: Lycaenidae; Minois dryas: Satyridae) in contrasted habitat types. We demonstrate that intraspecific variability in individual detectability under standard monitoring conditions is probably the rule rather than the exception, which questions the reliability of count-based indices to estimate and compare specific population abundance. Our results suggest that the accuracy of count-based methods depends heavily on the ecology and behavior of the target species, as well as on the type of habitat in which surveys take place. Monitoring programs designed to assess the abundance and trends in butterfly populations should incorporate a measure of detectability. We discuss the relative advantages and inconveniences of current monitoring methods and analytical approaches with respect to the characteristics of the species under scrutiny and resources availability.

A simulation study of how simple mark-recapture methods can be combined with destructive subsampling to facilitate surveys of flying insects

Mark-recapture techniques are used for studies of animal populations. With only three sampling occasions, both Bailey's triple-catch (BTC) and Jolly-Seber's (J-S) stochastic method can be applied. As marking and handling of fragile organisms may harm them, and thereby affect their chances of being recaptured, handling should be minimized. This can be achieved by taking a subsample before the main sample at the second sampling occasion. Individuals in the main sample are marked and released, whereas those in the subsample are only used for identifying recaptures. Monte-Carlo simulation was used to compare the subsampling method with the ordinary mark-recapture methods. Model-generated populations were sampled with and without subsampling to provide estimates of population size, loss, and dilution rates. The estimated parameters were compared with their true values to identify biases associated with the sampling methods, using 81 different combinations of population size, dilution rate, loss rate, and sampling effort. Each combination was replicated 1,000 times. In no cases did subsampling perform more poorly than the ordinary methods. J-S was slightly more accurate than BTC to estimate the population size, but only when sampling effort was high. The relative biases associated with estimates of dilution and loss rates were substantial, but declined with increasing population size and sampling effort. Confidence limits for the population parameters generally were reliable and tended to be conservative. We therefore conclude that ordinary mark-recapture methods can be supplemented with subsampling without sacrificing accuracy. Subsampling is especially advantageous in cases where marks are difficult to observe under field conditions.