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Macgregor, C. J.

Publications and source records attributed to Macgregor, C. J..

4 recordsLinked to original sources

Unlocking the potential of historical abundance datasets to study biomass change in flying insects

O_LITrends in insect abundance are well-established in some datasets, but far less is known about how abundance measures translate into biomass trends. Moths (Lepidoptera) provide particularly good opportunities to study trends and drivers of biomass change at large spatial and temporal scales, given the existence of long-term abundance datasets. However, data on the body masses of moths are required for these analyses, but such data do not currently exist. C_LIO_LITo address this data gap, we collected empirical data in 2018 on the forewing length and dry mass of field-sampled moths, and used these to train and test a statistical model that predicts the body mass of moth species from their forewing lengths (with refined parameters for Crambidae, Erebidae, Geometridae and Noctuidae). C_LIO_LIModelled biomass was positively correlated, with high explanatory power, with measured biomass of moth species (R2 = 0.886 {+/-} 0.0006, across 10,000 bootstrapped replicates) and of mixed-species samples of moths (R2 = 0.873 {+/-} 0.0003), showing that it is possible to predict biomass to an informative level of accuracy, and prediction error was smaller with larger sample sizes. C_LIO_LIOur model allows biomass to be estimated for historical moth abundance datasets, and so our approach will create opportunities to investigate trends and drivers of insect biomass change over long timescales and broad geographic regions. C_LI

ecology↗

Environmental DNA (eDNA) metabarcoding of pond water as a tool to survey conservation and management priority mammals

O_LIEnvironmental DNA (eDNA) metabarcoding is largely used to survey aquatic communities, but can also provide data on terrestrial taxa utilising aquatic habitats. However, the entry, dispersal, and detection of terrestrial species DNA within waterbodies is understudied. C_LIO_LIWe evaluated eDNA metabarcoding of pond water for monitoring semi-aquatic, ground-dwelling, and arboreal mammals, and examined spatiotemporal variation in mammal eDNA signals using experiments in captive and wild conditions. C_LIO_LIWe selected nine focal species of conservation and management concern: European water vole, European otter, Eurasian beaver, European hedgehog, European badger, red deer, Eurasian lynx, red squirrel, and European pine marten. We hypothesised that eDNA signals (i.e. proportional read counts) would be stronger for semi-aquatic than terrestrial species, and at sites where mammals exhibited behaviours (e.g. swimming, urination). We tested this by sampling waterbodies in enclosures of captive focal species at specific sites where behaviours had been observed ( directed sampling) and at equidistant intervals along the shoreline ( stratified sampling). We then surveyed natural ponds (N = 6) where focal species were present using stratified water sampling, camera traps, and field signs. eDNA samples were metabarcoded using vertebrate-specific primers. C_LIO_LIAll focal species were detected in captivity. eDNA signal strength did not differ between directed and stratified samples across or within species, between species lifestyles (i.e. semi-aquatic, ground-dwelling, arboreal), or according to behaviours. Therefore, eDNA was evenly distributed within artificial waterbodies. Conversely, eDNA was unevenly distributed in natural ponds. eDNA metabarcoding, camera trapping, and field signs detected beaver, red deer, and roe deer. Badger and red fox were recorded with cameras and field signs, but not eDNA metabarcoding. However, eDNA metabarcoding detected small mammals missed by cameras and field signs, e.g. water vole. Terrestrial mammal eDNA signals were weaker and detected in fewer samples than semi-aquatic mammal eDNA signals. C_LIO_LIeDNA metabarcoding has potential for inclusion in mammal monitoring schemes by enabling large-scale, multi-species distribution assessment for priority and difficult to survey species, and could provide early indication of range expansions or contractions. However, eDNA surveys need high spatiotemporal resolution and metabarcoding biases require further investigation before this tool is routinely implemented. C_LI

molecular biology↗

Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using microscopy and DNA metabarcoding

O_LIMoths are globally relevant as pollinators but nocturnal pollination remains poorly understood. Plant-pollinator interaction networks are traditionally constructed using either flower-visitor observations or pollen-transport detection using microscopy. Recent studies have shown the potential of DNA metabarcoding for detecting and identifying pollen-transport interactions. However, no study has directly compared the realised observations of pollen-transport networks between DNA metabarcoding and conventional light microscopy.\nC_LIO_LIUsing matched samples of nocturnal moths, we construct pollen-transport networks using two methods: light microscopy and DNA metabarcoding. Focussing on the feeding mouthparts of moths, we develop and provide reproducible methods for merging DNA metabarcoding and ecological network analysis to better understand species-interactions.\nC_LIO_LIDNA metabarcoding detected pollen on more individual moths, and detected multiple pollen types on more individuals than microscopy, but the average number of pollen types per individual was unchanged. However, after aggregating individuals of each species, metabarcoding detected more interactions per moth species. Pollen-transport network metrics differed between methods, because of variation in the ability of each to detect multiple pollen types per moth and to separate morphologically-similar or related pollen. We detected unexpected but plausible moth-plant interactions with metabarcoding, revealing new detail about nocturnal pollination systems.\nC_LIO_LIThe nocturnal pollination networks observed using metabarcoding and microscopy were similar, yet distinct, with implications for network ecologists. Comparisons between networks constructed using metabarcoding and traditional methods should therefore be treated with caution. Nevertheless, the potential applications of metabarcoding for studying plant-pollinator interaction networks are encouraging, especially when investigating understudied pollinators such as moths.\nC_LI

ecology↗

Estimating sampling completeness of interactions in quantitative bipartite ecological networks: incorporating variation in species specialisation

BackgroundThe analysis of ecological networks can be affected by sampling effort, potentially leading to bias. Ecological network structure is often summarised by descriptive metrics but these metrics can vary according to the proportion of the total interactions that have been observed. Therefore, to know the likely degree of bias, it is valuable to estimate the total number of interactions in a network, and so calculate the proportion of interactions that have been observed (sampling completeness of interactions). Existing approaches to estimate sampling completeness of interactions use the Chao family of asymptotic species richness estimators to predict the total number of interactions, but do not fully utilise information about the relative specialisation of species within the network.\n\nResultsHere, we propose a modification of previously-used methods, that places equal weight on each interaction (whether or not it has been observed), rather than on each species. Our approach is therefore equivalent to weighting the interaction sampling completeness of each species in the network according to its relative specialisation. We demonstrate that, for the subset of species that are observed and when assuming that species richness estimators accurately project the number of unobserved interactions per observed species, our approach is mathematically more accurate. Our approach can be universally applied to any quantitative, bipartite network.\n\nWe propose two methods to estimation using our approach, using abundance-based and incidence-based species richness estimators respectively, and give recommendations when each should be applied. We discuss the effect of unobserved species and the potential use of a threshold of minimum abundance for species inclusion. Finally, we consider these advances in the context of some of the main issues surrounding estimation of interaction sampling completeness in network ecology.\n\nConclusionsWe recommend that future studies of bipartite networks utilise our approach and methods to estimate the sampling completeness of interactions, to assist with the quantitative and comparative analysis and interpretation of network properties.

ecology↗