Biology subjects

Carvell, C.

Publications and source records attributed to Carvell, C..

3 recordsLinked to original sources

bioRxiv2026

Testing the efficacy of artificial flowers as a novel attractant for automated pollinator monitoring

Insect camera traps are a rapidly developing technology, enabling automated monitoring of insects. However, little has been reported on improving the attractants used for daytime flying insects on such cameras. This study compares the attractiveness of novel, 3D printed, artificial flowers with traditional methods of attracting insects (e.g. pan traps and solid coloured paper squares). We hypothesised that artificial flowers would attract a higher abundance and diversity of insects compared to traditional attractants by more accurately mimicking flowers. Additionally, we examined colour preference and average landing duration on the attractants. Artificial flowers, dry pan traps and paper squares, painted in yellow, white, or blue ultraviolet fluorescent paint, were filmed simultaneously to observe wild insect behavioural responses (landings and approaches). The results indicate overall preference for artificial flowers over the two traditional attractants when considering all insect groups together, and overall colour preferences for blue and yellow. When analysing insect groups separately, hoverflies preferred landing on artificial flowers over the other attractants. Bumblebees preferred approaching artificial flowers, and small insects preferred landing and approaching artificial flowers over the other attractants. Other flies preferred landing on pan traps and paper over artificial flowers. Hoverflies, small insects, wasps, and solitary bees responded more to yellow than the other colours, while bumblebees responded more to blue. Comparisons of landing durations revealed that hoverflies spent longer on the artificial flowers than paper. Other flies spent longer on the pan traps and paper. These results show that artificial flowers could offer an efficient attractant for insect camera traps as they attracted a higher abundance of key pollinating insects (hoverflies and bumblebees), and do not have worse attraction rates for the other insect groups (excluding other flies).

ecology↗

bioRxiv2021

occAssess: An R package for assessing potential biases in species occurrence data

Species occurrence records from a variety of sources are increasingly aggregated into heterogeneous databases and made available to ecologists for immediate analytical use. However, these data are typically biased, i.e. they are not a probability sample of the target population of interest, meaning that the information they provide may not be an accurate reflection of reality. It is therefore crucial that species occurrence data are properly scrutinised before they are used for research. In this article, we introduce occAssess, an R package that enables straightforward screening of species occurrence data for potential biases. The package contains a number of discrete functions, each of which returns a measure of the potential for bias in one or more of the taxonomic, temporal, spatial and environmental dimensions. Users can opt to provide a set of time periods into which the data will be split; in this case separate outputs will be provided for each period, making the package particularly useful for assessing the suitability of a dataset for estimating temporal trends in species distributions. The outputs are provided visually (as ggplot2 objects) and do not include a formal recommendation as to whether data are of sufficient quality for any given inferential use. Instead, they should be used as ancillary information and viewed in the context of the question that is being asked, and the methods that are being used to answer it. We demonstrate the utility of occAssess by applying it to data on two key pollinator taxa in South America: leaf-nosed bats (Phyllostomidae) and hoverflies (Syrphidae). In this worked example, we briefly assess the degree to which various aspects of data coverage appear to have changed over time. We then discuss additional applications of the package, highlight its limitations, and point to future development opportunities.

ecology↗

bioRxiv2019

A validated workflow for rapid taxonomic assignment and monitoring of a national fauna of bees (Apiformes) using high throughput barcoding

Improved taxonomic methods are needed to quantify declining populations of insect pollinators. This study devises a high-throughput DNA barcoding protocol for a regional fauna (United Kingdom) of bees (Apiformes), consisting of reference library construction, a proof-of-concept monitoring scheme, and the deep barcoding of individuals to assess potential artefacts and organismal associations. A reference database of Cytochrome Oxidase subunit 1 (cox1) sequences including 92.4% of 278 bee species known from the UK showed high congruence with morphological taxon concepts, but molecular species delimitations resulted in numerous split and (fewer) lumped entities within the Linnaean species. Double tagging permitted deep illumina sequencing of 762 separate individuals of bees from a UK-wide survey. Extracting the target barcode from the amplicon mix required a new protocol employing read abundance and phylogenetic position, which revealed 180 molecular entities of Apiformes identifiable to species. An additional 72 entities were ascribed to mitochondrial pseudogenes based on patterns of read abundance and phylogenetic relatedness to the reference set. Clustering of reads revealed a range of secondary Operational Taxonomic Units (OTUs) in almost all samples, resulting from traces of insect species caught in the same traps, organisms associated with the insects including a known mite parasite of bees, and the common detection of human DNA, besides evidence for low-level cross-contamination in pan traps and laboratory steps. Custom scripts were generated to conduct critical steps of the bioinformatics protocol. The resources built here will greatly aid DNA-based monitoring to inform management and conservation policies for the protection of pollinators.

molecular biology↗