2Many animal species are comprised of discrete phenotypic forms. Understanding the genetic mechanisms generating and maintaining such phenotypic variation within species is essential to comprehending morphological diversity. A common and conspicuous example of discrete phenotypic variation in natural populations of insects is the occurrence of different colour patterns, which has motivated a rich body of ecological and genetic research [1][2][3][4][5][6] . The occurrence of dark, i.e. melanic, forms, displaying discrete colour patterns, is found across multiple taxa, but the underlying genomic basis remains poorly characterized. In numerous ladybird species (Coccinellidae), the spatial arrangement of black and orange patches on adult elytra varies wildly within species, forming strikingly different complex colour patterns 7,8 (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/345942 doi: bioRxiv preprint first posted online Jun. 13, 2018; 3 wild has been attributed to a combination of allelic diversity, interactions between allelic forms, and plastic response to environmental factors 12,13 . Genetic crosses have demonstrated that the majority of H. axyridis melanic forms result from variation of multiple alleles segregating at a single, uncharacterised, autosomal locus 9,10 , hereafter referred to as the colour pattern locus.To identify this colour pattern locus, and the mechanisms underlying discrete colour pattern variation, we used a population genomics approach, taking advantage of the cooccurrence of multiple colour pattern forms in natural populations. To that end, we first performed a de novo genome assembly of the H. axyridis Red-nSpots form (HaxR) using long reads produced by a MinION sequencer (Oxford Nanopore) (see Extended Data Table 1).Then, to fine map the colour pattern locus on this assembly, DNA from 14 pools of individuals (from n=40 to n=100 individuals per pool) representative of the world-wide genetic diversity and the four main colour pattern forms of H. axyridis was sequenced on a HiSeq 2500 (Illumina, Inc.) (Extended Data Table 2). Our aim was to characterize genetic variation associated with phenotypic differences across pool samples, using the proportion of individuals of a given colour form in each pool as a covariate. To do so, we called 18,425,210autosomal SNPs, and we performed a population-based genome-wide association study accounting for the covariance of allele frequencies across pools 14 . Given the dominance hierarchy of colour morph alleles with Black-2Spots > Black-4Spots > Black-nSpots > RednSpots 9,12,13 , we first performed the association study using the proportion of Red-nSpots individuals, carrying two copies of the most recessive allele, in each DNA pool as a covariate.We found 710 SNPs strongly associated with the proportion of the Red-nSpots form (Bayes factor > 30 db), the vast majority (86%) of which are located within a s...

101. Understanding the decline in bee populations and their plant mutualists is of 11 paramount concern for ecosystem health, as well as our future food security. 12 Intensive farming practices are one of the major drivers behind such declines. 13Organic farming is one of the principal alternatives to conventional practices yet the 14 evidence for its effects are mixed, with some studies showing limited benefits. 15 2. We conducted bee and floral surveys on 10 paired organic and conventional farms 16 across Yorkshire, UK, to investigate how farming practice influenced the 17 abundance, richness and community composition of bees and flowering plants.18 3. Firstly, we found that species richness for flowering plants and bees was similar 19 across organic and conventional farms. Floral composition differed between organic 20 and conventional farms with the greatest differences seen in May and June, whereas 21 bee community composition was similar among farming practices.22 4. Secondly, both bee and floral abundance were higher in organic farms. Peaks in 23 floral abundance, and corresponding bee abundance, occurred in particular months, 24 most notably in July, with abundance during the rest of the season being similar 25 across both farming practices. 26 5. Synthesis and applications: Our results suggest that higher floral availability on 27 organic farms corresponds with increased bee abundance. Of particular importance 28 was the higher floral abundance during spring, in the pollinator 'hungry gap', where 29 floral resources are traditionally scarce. However, conventional farms performed 30 comparably to organic farms across the rest of the season, as well as showing 31 similar levels of species richness, diversity and species composition for both 32 flowering plants and bees. We suggest that targeted management on conventional 33 farms, aimed at boosting floral abundance in the spring, when floral abundance is 34 low, could allow conventional farms to make up the shortfall. Additionally, 35 focusing on increasing the diversity of flowering plants, in terms of both phenology 36 and nutritional composition, for both adult bees and their larvae, could improve bee 37 community diversity across both farming systems.38 39

We have recently developed and deployed methods for environmental DNA (eDNA) based monitoring of lake fish communities in the UK. This approach combines eDNA with modern High-Throughput-Sequencing technology, so-called eDNA metabarcoding. This non-invasive method has proven to be more effective at detecting elusive species than established invasive surveying techniques such as electro fishing or fyke netting and can provide meaningful semi-quantitative abundance estimates. The UK Environment Agencies have funded the collection of an eDNA meta-barcoding data set of vertebrates from 101 UK lakes covering a broad spectrum of environmental conditions Fig. 1. This dataset is based on analysing 20 water samples per lake and has successfully been used to develop a WFD compatible water quality assessment tool. In its current form this tool is suitable for reporting the status of fish in water bodies where eutrophication is the dominant pressure. DNA is not homogeneously distributed in lentic environments and hence the detection of species relies on the collection of an adequate number of samples from a water body to capture the eDNA signal. Previous analyses on a subset of lakes have indicated that the number of samples used for the 101 lake fish data set is more than sufficient to reliably estimate species richness of lakes, but it is unclear how exactly reduced sampling effort affects other biodiversity estimates and inferences made about water quality. As the number of samples determines the cost of monitoring programmes it is essential that the sampling effort is optimised for a specific monitoring objective. The objective of this study was to explore the effect a reduced sampling effort would have on various biological inferences using algorithmic and statistical resampling techniques. with a much lower number of samples. For example, almost 90% of lakes achieved a sample coverage of 95% with only 10 samples. However, rare species are more often missed with fewer samples, with implications for monitoring programs of invasive or endangered species. Estimates of community composition and the ecological quality ratio (EQR) responded slowly to decreasing sampling effort. For example, subsets of 10 samples were in most cases much more closely related to each other than to sample sets from other lakes and showed very similar Ecological Quality Ratios. These results are able to inform the design of eDNA sampling strategies, so that these can be optimised to achieve specific monitoring goals.

Early detection is paramount for attempts to remove invasive non-native species (INNS). Traditional methods rely on physical sampling and morphological identification, which can be problematic when species are in low densities and/or are cryptic. The use of environmental DNA (eDNA) as a monitoring tool in freshwater systems is becoming increasingly acceptable and widely used for the detection of single species. Here we demonstrate the development and application of standard PCR primers for the detection of four freshwater invasive species which are high priority for monitoring in the UK and elsewhere: Dreissenid mussels; Dreissena rostriformis bugensis (Andrusov, 1987) and D. polymorpha (Pallas, 1771), and Gammarid shrimps; Dikerogammarus villosus (Sowinsky, 1984) and D. haemobaphes (Eichwald, 1843). We carried out a rigorous validation process for testing the new primers, including DNA detection and degradation rate experiments in mesocosm, and a field comparison with traditional monitoring protocols. We successfully detected all four target species in mesocosms, but success was higher for mussels than shrimps. eDNA from single individuals of both mussel species could be detected within four hours of the start of the experiment. By contrast, shrimp were only consistently detected at higher densities (20 individuals). In field trials, the two mussel species and D. haemobaphes were detected at all sites where the species are known to be present, and eDNA consistently outperformed traditional kick sampling for species detection. However, D. villosus eDNA was only detected in one of five sites where the species was confirmed by kick sampling. These results demonstrate the applicability of standard PCR for eDNA detection of freshwater invasive species, but also highlight the importance of differences between taxa in terms of the detection ability.

Early detection is paramount for attempts to remove invasive non-native species (INNS). Traditional methods rely on physical sampling and morphological identification, which can be problematic when species are in low densities and/or are cryptic. The use of environmental DNA (eDNA) as a monitoring tool in freshwater systems is becoming increasingly acceptable and widely used for the detection of single species. Here we demonstrate the development and application of standard PCR primers for the detection of four freshwater invasive species which are high priority for monitoring in the UK and elsewhere: Dreissenid mussels; Dreissena rostriformis bugensis (Andrusov, 1987) and D. polymorpha (Pallas, 1771), and Gammarid shrimps; Dikerogammarus villosus (Sowinsky, 1984) and D. haemobaphes (Eichwald, 1843). We carried out a rigorous validation process for testing the new primers, including DNA detection and degradation rate experiments in mesocosm, and a field comparison with traditional monitoring protocols. We successfully detected all four target species in mesocosms, but success was higher for mussels than shrimps. eDNA from single individuals of both mussel species could be detected within four hours of the start of the experiment. By contrast, shrimp were only consistently detected at higher densities (20 individuals). In field trials, the two mussel species and D. haemobaphes were detected at all sites where the species are known to be present, and eDNA consistently outperformed traditional kick sampling for species detection. However, D. villosus eDNA was only detected in one of five sites where the species was confirmed by kick sampling. These results demonstrate the applicability of standard PCR for eDNA detection of freshwater invasive species, but also highlight the importance of differences between taxa in terms of the detection ability.