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Biology subjects

Bourlat, S. J.

Publications and source records attributed to Bourlat, S. J..

2 recordsLinked to original sources

Charting the insect biodiversity of Crete: insights from a pilot metabarcoding survey

Among eukaryotes, insects are by far the most diverse organisms on Earth, yet their global decline threatens ecosystem stability. Understanding local and regional biodiversity patterns is critical for conservation planning, ecosystem management, and predicting responses to environmental change, but traditional surveys for assessing insect diversity (e.g., manual collection, morphological identification, and counting) are highly labor-intensive, time-consuming, and often require rare or simply unavailable dedicated taxonomic expertise. DNA metabarcoding offers an efficient, high-resolution alternative to assess insect communities. Here, we report on the first insect metabarcoding survey on Crete that spans two years of sample collection between 2021 and 2023 from a small area in Southern Central Crete in the context of a citizen science project. A total of 29 samples yielded 10,865 Exact Sequence Variants (ESVs), 10,516 of which were assigned to insects, covering 988 species, 900 genera, and 227 families across 14 orders. A comparison with the existing observation records reveals 406 potential newly-observed species and an estimated 690 unclassified species, indicating substantial cryptic diversity. Our results demonstrate that even small-scale sampling can unravel substantial insect diversity and highlight critical gaps in barcode reference databases. Our study demonstrates how DNA metabarcoding can accelerate biodiversity discovery and monitoring in understudied regions.

ecology↗

Pooling size sorted malaise trap fractions to maximise taxon recovery with metabarcoding

O_LISmall and rare specimens can remain undetected when metabarcoding bulk samples with a high size heterogeneity of specimens. This is especially critical for malaise trap samples, where most of the biodiversity is often contributed by small specimens. How to size sort and in which proportions to pool these samples has not been widely explored. We set out to find a size sorting strategy that maximizes taxonomic recovery but remains highly scalable and time efficient. C_LIO_LIThree 3 malaise trap samples where size sorted into 4 size classes using dry sieving. Each fraction was homogenized and lysed. The corresponding lysates were pooled to simulate samples never sorted, pooled in equal proportions and in 4 different proportions favoring the small size fractions. DNA from the pooled fractions as well as the individual size classes were extracted and metabarcoded using the FwhF2 and Fol-degen-rev primer set. Additionally wet sieving strategies were explored. C_LIO_LIThe small size fractions harbored the highest diversity, and were best represented when pooling in favor of small specimens. Not size sorting a sample leads to a 45-77% decrease in taxon recovery compared to size sorted samples. A size separation into only 2 fractions (below 4 mm and above) can already double taxon recovery compared to not sorting. However, increasing the sequencing depth 3-4 fold can also increase taxon recovery to comparable levels, but remains biased toward biomass rich taxa in the sample. C_LIO_LIWe demonstrate that size fractionizing bulk malaise samples can increase taxon recovery. The most practical approach is wet sieving into two size fractions, and proportional pooling of the lysates in favor of the small size fraction (80-90% volume). However, in large projects with time constraints, increasing sequencing depth can also be an alternative solution. C_LI

molecular biology↗