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1. Established butterfly survey methods that are useful for monitoring species that are widely distributed and numerous may be less accurate for more rare species. We therefore need new monitoring approaches.2. We describe a plot-based survey method, where butterflies or larvae nests are counted within 1-ha grid cells. The aim was to compare this grid method with more traditional transect counts and evaluate both methods in relation to high-quality capture-mark-release (CMR) population estimates (reflecting the true population). We do this using data from a large population of the marsh fritillary butterfly in Sweden. Moreover, we followed the overall population trend from 2017 to 2021 for both adult butterflies and larvae.3. Results showed a higher detection probability using the grid method compared with transect counts, which for adult butterflies seem to be explained by time effort. Moreover, grid surveys of adult butterflies showed a clear significant relationship with the estimated true population size from CMR, while transect counts did not. For larvae, both methods showed significant relationships with the estimated adult population size, but the grid method found 5.7 times more larvae. The overall popu-lation fluctuated significantly across years. In years with low densities, the transect method largely failed to detect the species.4. The grid method seems more reliable for detecting the marsh fritillary and for estimating its population size, and thus, tracking the population trend. We propose this novel method to be integrated into surveys and monitoring of biodiversity, especially when focusing on rare habitat specialists that are normally underrepre-sented in monitoring based on volunteer counts., Funding Agencies|Cementa AB; Svenska Forskningsradet Formas

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 c 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 nuclear 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 procedures. 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.