Our March Issue is now online! Our third issue of the year contains 21 fantastic articles about the latest methods in ecology and evolution, including methods for recognition of taxonomic entities in literature, precipitating and purifying environmental and ancient DNA, estimating wildlife abundance in tropical forests and much more!

Read on to find out about this month’s featured articles.

Featured Articles

ubms (Application) Obtaining unbiased estimates of wildlife distribution and abundance is an important objective in research and management. Occupancy and N-mixture abundance models, which correct for imperfect detection, are commonly used for this purpose. Fitting these models in a Bayesian framework has advantages but doing so can be challenging and time-consuming for many researchers. Here, Kellner et al. developed ubms, an R package which provides an easy-to-use, formula-based interface for fitting occupancy, N-mixture abundance and other models in a Bayesian framework using Stan. The package also provides tools for visualising parameter effects, calculating residuals, assessing goodness-of-fit and comparing models.

Maintaining solitary bees in the lab (Practical Tools) Although solitary bees represent at least 70% of bee species, most ecotoxicological studies on bees focus on social species. One of the challenges in developing toxicological studies on solitary bees is the lack of protocols for maintaining these species under laboratory conditions. This article by Tadei et al. presents a new method to maintain adult individuals of the solitary bee Centris analis under controlled conditions.

TaxoNERD A prerequisite to extracting useful multi-taxa information from ecological texts is the ability to recognise mentions of taxa in text, a special case of named entity recognition (NER). In recent years, deep learning-based NER systems have become ubiquitous, yielding state-of-the-art results in the general and biomedical domains. However, no such tool is available to ecologists wishing to extract information from the biodiversity literature. Here, Le Guillarme & Thuiller propose a new tool called TaxoNERD that provides deep neural network models to recognise taxon mentions in ecological documents.

Precipitating and purifying environmental and ancient DNA Nucleic acid extraction from complex environmental and ancient tissue material is prone to co-extract inhibitory substances that make further molecular analysis difficult or impossible. Currently, the widely used method to overcome inhibition includes the addition of bovine serum albumin (BSA) to the downstream enzymatic reactions or the dilution of the nucleic acid extracts. BSA, however, seems to reduce the inhibitory effect of certain compounds only, and excessive dilution may change the original DNA composition. In this study, Maixner et al. introduce an innovative new method using linear polyacrylamide to efficiently precipitate and purify nucleic acids extracted from complex environmental and ancient tissue samples in one working step.

Estimating wildlife abundance in tropical forests Local ecological knowledge (LEK) methods (empirically acquired through the observation of ecological processes by local people) have only been recognised as valid for surveying fauna abundance in the last three decades. However, the agreement between LEK-based methods and diurnal line-transect surveys has not been extensively analysed. Here, Braga-Pereira et al. compared concomitant abundance data for 91 wild species from diurnal line transects and a LEK-based method, using biological and socioecological factors to assess the agreements and divergences between abundance indices obtained from both methods.

Practical Tools

Free to read for the next two months

BoomBox Camera traps (CTs) are a valuable tool in ecological research, amassing large quantities of information on the behaviour of diverse wildlife communities. Integrating CTs into experimental studies can enable rigorous testing of key hypotheses in animal behaviour and conservation biology that are otherwise difficult or impossible to evaluate. Here, Palmer et al. developed the ‘BoomBox’, an open-source Arduino-compatible board that attaches to commercially available CTs to form an Automated Behavioural Response system. The modular unit connects directly to the CT’s passive infrared motion sensor, playing audio files over external speakers when the sensor is triggered.


Free to read for the next month

KTU Amplicon sequencing is widely implemented in microbiome-associated studies. In recent years, microbial ecologists have switched to new algorithms for taxonomic identification and quantification. The amplicon sequence variant (ASV) denoising algorithm of unbiased sequence picking has replaced the OTU clustering methods. ASV can be used to detect and distinguish biological variations to the species OTU level (≥97% similarity). However, the ASV quantification among samples is sparse and less prevalent within the same batch. Here, Liu et al. present a k-mer based, alignment-free algorithm—‘KTU’ (K-mer Taxonomic Unit)—to iteratively re-cluster ASVs into optimal biological taxonomic units.

phenopype (open access) Digital images are an intuitive way to capture, store and analyse organismal phenotypes. Many biologists are taking images to collect high-dimensional phenotypic information from specimens to investigate complex ecological, evolutionary and developmental phenomena, such as relationships between trait diversity and ecosystem function, multivariate natural selection or developmental plasticity. As a consequence, images are being collected at ever-increasing rates, but extraction of the contained phenotypic information poses a veritable analytical bottleneck. Here, Moritz D. Lürig presents phenopype, a high-throughput phenotyping pipeline for the programming language Python that aims at alleviating this bottleneck.

Argos Recent advances in machine learning applied to video analysis have been helpful for animal tracking, but existing tools work well only in homogeneous environments with uniform illumination, features rarely found in natural settings. Moreover, available algorithms cannot effectively process discontinuities in animal motion such as sudden jumps, thus requiring laborious manual review. In answer to this, Ray & Stopfer present Argos, a software toolkit for tracking multiple animals in inhomogeneous environments.

The ZAX Herbivory Trainer (open access) There are many ways ecologists can measure leaf damage, with some methods being more time-consuming than others. Due to a high variance in herbivory, accurate quantification of damage at the population level requires sampling of many leaves. A simple yet effective solution to this problem is to estimate leaf damage visually – this may be less accurate than scanning methods, but visual estimates of leaf damage are much faster than digital measurements. Here, using simulations, Xirocostas et al. show that gathering larger quantities of data at a slightly higher level of inaccuracy gives a more accurate estimate of a population’s overall leaf damage than fewer, exact measurements. They then introduce the ZAX Herbivory Trainer, a free online application that teaches researchers to accurately visually estimate leaf damage.

GinJinn2 Modern machine learning approaches have the potential to automate a variety of tasks, which until recently could only be performed manually. Unfortunately, the application of such methods by researchers outside the field is hampered by technical difficulties. Here, Ott & Lautenschlager present GinJinn2, a user-friendly toolbox for deep learning-based object detection and instance segmentation on image data. Besides providing a convenient command-line interface to existing software libraries, it comprises several additional tools for data handling, pre- and postprocessing, and building advanced analysis pipelines.

The Otter on the Cover

The cover image shows a female Eurasian otter, Lutra lutra, taken on Christmas Eve 2019 on Loch Spelve, Scotland. The otter was with her young kit and brought the crab to shore before eating it. Direct observation of feeding like this takes a great deal of patience and skill – otters are elusive, typically ranging over tens of kilometres, and are mostly nocturnal. Finding an otter is the first challenge, observing feeding is the next, and to reliably identify the prey species is often impossible, especially when the prey is small. Yet finding out about trophic relationships remains one of the fundamental underpinnings of ecology. Metabarcoding now provides a powerful tool which can be applied (e.g. to faecal samples, or gut contents) to investigate cryptic trophic interactions, but its high sensitivity can make it vulnerable to errors. In this issue, Drake et al. discuss potential sources of error, and provide guidance for best practice filtering of metabarcoding data in order to produce conservative and accurate information about diet. Photo credit: ©Alan Seymour.