Determining diet from faeces: Selection of metabarcoding primers for the insectivore Pyrenean desman (Galemys pyrenaicus)

Evaluation of Oxford Nanopore Technologies MinION Sequencer as a Novel Short Amplicon Metabarcoding Tool Using Arthropod Mock Sample and Irish Bat Diet Characterisation

Biodiversity monitoring using metabarcoding is now widely used as a routine environmental management tool. However, despite the rapid advancement of third-generation high-throughput sequencing platforms, there are limited studies assessing the most suitable tools and approaches for environmental metabarcoding studies. We tested the utility of Oxford Nanopore Technologies MinION sequencing for short-read amplicon sequencing of mitochondrial COI mini-barcodes from a known composition of arthropod species and compared its performance with more commonly used Illumina NovaSeq sequencing. The mock arthropod species assemblage allowed us to optimise a bioinformatic filtering pipeline to identify arthropod species using MinION long reads. Using this pipeline, we identified host species and diet composition by sequencing droppings collected from five individual Irish brown long-eared bats (Plecotus auritus) roosts. We showed that MinION data provided a similar taxonomic assignment to NovaSeq but only if the reference species barcode database was accurate and comprehensive. The P. auritus diet inferred was as expected based on previous morphological and Illumina metabarcoding studies. We showed that less sequencing depth, but a higher number of biological samples were necessary for complete species composition detection by MinION. A relatively simple bioinformatic filtering tool such as NanoPipe could adequately retrieve both host species and diet composition. The biggest standing challenge was the reference database format transferability and comprehensiveness. This pipeline can be used to guide future metabarcoding studies using nanopore sequencing to minimise the cost and effort while optimising results.

Data-driven evolution of water quality models: An in-depth investigation of innovative outlier detection approaches-A case study of Irish Water Quality Index (IEWQI) model

Recently, there has been a significant advancement in the water quality index (WQI) models utilizing data-driven approaches, especially those integrating machine learning and artificial intelligence (ML/AI) technology. Although, several recent studies have revealed that the data-driven model has produced inconsistent results due to the data outliers, which significantly impact model reliability and accuracy. The present study was carried out to assess the impact of data outliers on a recently developed Irish Water Quality Index (IEWQI) model, which relies on data-driven techniques. To the author's best knowledge, there has been no systematic framework for evaluating the influence of data outliers on such models. For the purposes of assessing the outlier impact of the data outliers on the water quality (WQ) model, this was the first initiative in research to introduce a comprehensive approach that combines machine learning with advanced statistical techniques. The proposed framework was implemented in Cork Harbour, Ireland, to evaluate the IEWQI model's sensitivity to outliers in input indicators to assess the water quality. In order to detect the data outlier, the study utilized two widely used ML techniques, including Isolation Forest (IF) and Kernel Density Estimation (KDE) within the dataset, for predicting WQ with and without these outliers. For validating the ML results, the study used five commonly used statistical measures. The performance metric (R2) indicates that the model performance improved slightly (R2 increased from 0.92 to 0.95) in predicting WQ after removing the data outlier from the input. But the IEWQI scores revealed that there were no statistically significant differences among the actual values, predictions with outliers, and predictions without outliers, with a 95 % confidence interval at p < 0.05. The results of model uncertainty also revealed that the model contributed <1 % uncertainty to the final assessment results for using both datasets (with and without outliers). In addition, all statistical measures indicated that the ML techniques provided reliable results that can be utilized for detecting outliers and their impacts on the IEWQI model. The findings of the research reveal that although the data outliers had no significant impact on the IEWQI model architecture, they had moderate impacts on the rating schemes' of the model. This finding indicated that detecting the data outliers could improve the accuracy of the IEWQI model in rating WQ as well as be helpful in mitigating the model eclipsing problem. In addition, the results of the research provide evidence of how the data outliers influenced the data-driven model in predicting WQ and reliability, particularly since the study confirmed that the IEWQI model's could be effective for accurately rating WQ despite the presence of the data outliers in the input. It could occur due to the spatio-temporal variability inherent in WQ indicators. However, the research assesses the influence of data input outliers on the IEWQI model and underscores important areas for future investigation. These areas include expanding temporal analysis using multi-year data, examining spatial outlier patterns, and evaluating detection methods. Moreover, it is essential to explore the real-world impacts of revised rating categories, involve stakeholders in outlier management, and fine-tune model parameters. Analysing model performance across varying temporal and spatial resolutions and incorporating additional environmental data can significantly enhance the accuracy of WQ assessment. Consequently, this study offers valuable insights to strengthen the IEWQI model's robustness and provides avenues for enhancing its utility in broader WQ assessment applications. Moreover, the study successfully adopted the framework for evaluating how data input outliers affect the data-driven model, such as the IEWQI model. The current study has been carried out in Cork Harbour for only a single year of WQ data. The framework should be tested across various domains for evaluating the response of the IEWQI model's in terms of the spatio-temporal resolution of the domain. Nevertheless, the study recommended that future research should be conducted to adjust or revise the IEWQI model's rating schemes and investigate the practical effects of data outliers on updated rating categories. However, the study provides potential recommendations for enhancing the IEWQI model's adaptability and reveals its effectiveness in expanding its applicability in more general WQ assessment scenarios.

Using biological traits to assess diet selection: the case of the Pyrenean Desman

Traditionally, researchers have assessed diet selection by comparing consumed versus available taxa. However, taxonomic assignment is probably irrelevant for predators, who likely base their selection on characteristics including prey size, habitat, or behavior. Here, we use an aquatic insectivore, the threatened Pyrenean Desman (Galemys pyrenaicus), as a model species to assess whether biological traits help unravel the criteria driving food and habitat preferences. We reanalyzed data from a previous taxonomy-based study of prey selection in two contrasting streams, one with excellent conservation status and the other affected by diversion for hydropower and forestry. Available and consumed prey were characterized according to nine biological traits, and diet selection was estimated by comparing availability-measured from Surber net samples, and consumption-analyzed by metabarcoding desman feces. Traits offered a biologically coherent image of diet and almost identical selection patterns in both streams, depicting a highly specialized rheophilic predator. Desmans positively selected prey with a preference for fast flow and boulder substrate, indicating their preferred riffle habitat. On the other hand, they positively selected prey with larger but not the largest potential size, living in the water column or the litter, and not inside sediments. They also chose agile prey, swimmers or prey attached to the substrate, prey with high body flexibility, and prey living exposed and clustered in groups. Overall, our results offer a picture of desman diet preference and point to biological traits as being better than taxonomic identity to describe the diet preference of consumers.

Aerospace-foraging bats eat seasonably across varying habitats

Recent research has confirmed the efficiency of insectivorous bats as pest suppressors, underlining the ecological services they offer in agroecosystems. Therefore, some efforts try to enhance bat foraging in agricultural landscapes by acting upon environmental factors favouring them. In this study, we monitored a Miniopterus schreibersii colony, in the southern Iberian Peninsula. We intensively sampled their faeces and analysed them by metabarcoding to describe how the bent-winged bat diet would change with time, and to test whether their most-consumed prey would seasonally depend on different landscapes or habitats. Our results confirm that M. schreibersii are selective opportunist predators of moths, dipterans, mayflies, and other fluttering insects, shifting their diet to temporary peaks of prey availability in their foraging range, including both pest and non-pest insects. Supporting our hypothesis, throughout the year, M. schreibersii consume insects linked to diverse open habitats, including wetlands, grassland, diverse croplands, and woodland. The importance of each prey habitat varies seasonally, depending on their insect phenology, making bats indirectly dependent on a diverse landscape as their primary prey source. Bats' predation upon pest insects is quantitatively high, consuming around 1610 kg in 5 months, of which 1467 kg correspond to ten species. So, their suppression effect may be relevant, mainly in patchy heterogeneous landscapes, where bats' foraging may concentrate in successive outbursts of pests, affecting different crops or woodlands. Our results stress that to take advantage of the ecosystem services of bats or other generalist insectivores, keeping the environmental conditions they require to thrive, particularly a heterogeneous landscape within the colony's foraging area, is crucial.

Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations

Extensive research in well-studied animal models underscores the importance of commensal gastrointestinal (gut) microbes to animal physiology. Gut microbes have been shown to impact dietary digestion, mediate infection, and even modify behavior and cognition. Given the large physiological and pathophysiological contribution microbes provide their host, it is reasonable to assume that the vertebrate gut microbiome may also impact the fitness, health and ecology of wildlife. In accordance with this expectation, an increasing number of investigations have considered the role of the gut microbiome in wildlife ecology, health, and conservation. To help promote the development of this nascent field, we need to dissolve the technical barriers prohibitive to performing wildlife microbiome research. The present review discusses the 16S rRNA gene microbiome research landscape, clarifying best practices in microbiome data generation and analysis, with particular emphasis on unique situations that arise during wildlife investigations. Special consideration is given to topics relevant for microbiome wildlife research from sample collection to molecular techniques for data generation, to data analysis strategies. Our hope is that this article not only calls for greater integration of microbiome analyses into wildlife ecology and health studies but provides researchers with the technical framework needed to successfully conduct such investigations.

DNA metabarcoding suggests adaptive seasonal variation of individual trophic traits in a critically endangered fish

Dietary studies are critical for understanding foraging strategies and have important applications in conservation and habitat management. We applied a robust metabarcoding protocol to characterize the diet of the critically endangered freshwater fish Zingel asper (the Rhone streber). We conducted modelling and simulation analyses to identify and characterize some of the drivers of individual trophic trait variation in this species. We found that population density and ontogeny had minor effects on the trophic niche of Z. asper. Instead, our results suggest that the majority of trophic niche variation was driven by seasonal variation in ecological opportunity. The total trophic niche width of Z. asper seasonally expanded to include a broader range of prey. Furthermore, null model simulations revealed that the increase of between-individual variation in autumn indicates that Z. asper become more opportunistic relative to summer and spring, rather than being associated with a seasonal specialization of individuals. Overall, our results suggest an adaptive variation of individual trophic traits in Z. asper: the species mainly consumes a few ephemeropteran taxa (Baetis fuscatus and Ecdyonurus) but seems to be capable of adapting its foraging strategy to maintain its body condition. This study illustrates how metabarcoding data obtained from faeces can be validated and combined with individual-based modelling and simulation approaches to explore inter- and intrapopulational individual trophic traits variation and to test hypotheses in the conventional analytic framework of trophic ecology.

Dietary preferences and feeding strategies of Colombian highland woolly monkeys

Primates are very selective in the foods they include in their diets with foraging strategies that respond to spatial and temporal changes in resource availability, distribution and quality. Colombian woolly monkeys (Lagothrix lagotricha lugens), one of the largest primate species in the Americas, feed mainly on fruits, but they also eat a high percentage of arthropods. This differs from closely related Atelid species that supplement their diet with leaves. In an 11 month study, we investigated the foraging strategies of this endemic monkey and assessed how resource availability affects dietary selection. Using behavioural, phenological, arthropod sampling and metabarcoding methods, we recorded respectively foraging time, forest productivity, arthropod availability in the forest and arthropod consumption. Scat samples and capturing canopy substrates (i.e. moss, bromeliads, aerial insects) were used for assigning arthropod taxonomy. The most important resource in the diet was fruits (54%), followed by arthropods (28%). Resource availability predicted feeding time for arthropods but not for fruits. Further, there was a positive relationship between feeding time on fruits and arthropods, suggesting that eating both resources during the same periods might work as an optimal strategy to maximize nutrient intake. Woolly monkeys preferred and avoided some fruit and arthropod items available in their home range, choosing a wide variety of arthropods. Geometrid moths (Lepidoptera) were the most important and consistent insects eaten over time. We found no differences in the type of arthropods adults and juveniles ate, but adults invested more time foraging for this resource, especially in moss. Although woolly monkeys are generalist foragers, they do not select their food items randomly or opportunistically.

Trophic competition in a guild of insectivorous semi-aquatic vertebrates in a Pyrenean headwater stream: diet specialisation in the endangered Galemys pyrenaicus

Conservation of vulnerable species in headwater streams requires good knowledge of their resource use and how they interact with competitors. In this study, we characterised the macroinvertebrate community of a Pyrenean headwater stream and assessed how it was used as a food resource—above all, in terms of prey electivity and diet overlap—by three semi-aquatic insectivorous vertebrates (Galemys pyrenaicus, Neomys fodiens and Cinclus cinclus). With this information, we examined the diet specialisation of the vulnerable Pyrenean desman (G. pyrenaicus) in the stream and analysed its implications for its conservation. There was a clear dietary overlap between these three predators, which resulted in interspecific trophic competition. G. pyrenaicus tended to avoid terrestrial prey and focused on abundant and energetically profitable rheophile species, for which it is well adapted. This diet specialisation makes it vulnerable to any decrease in food availability resulting from anthropogenic stressors such as damming, which can reduce habitat quality and prey availability. More research is needed to fully understand prey electivity in G. pyrenaicus and so be able to suggest effective conservation measures for this species.

Trophic resource partitioning drives fine-scale coexistence in cryptic bat species

Understanding the processes that enable species coexistence has important implications for assessing how ecological systems will respond to global change. Morphology and functional similarity increase the potential for competition, and therefore, co-occurring morphologically similar but genetically unique species are a good model system for testing coexistence mechanisms. We used DNA metabarcoding and high-throughput sequencing to characterize for the first time the trophic ecology of two recently described cryptic bat species with parapatric ranges, Myotis escalerai and Myotis crypticus. We collected fecal samples from allopatric and sympatric regions and from syntopic and allotopic locations within the sympatric region to describe the diets both taxonomically and functionally and compare prey consumption with prey availability. The two bat species had highly similar diets characterized by high arthropod diversity, particularly Lepidoptera, Diptera and Araneae, and a high proportion of prey that is not volant at night, which points to extensive use of gleaning. Diet overlap at the prey item level was lower in syntopic populations, supporting trophic shift under fine-scale co-occurrence. Furthermore, the diet of M. escalerai had a marginally lower proportion of not nocturnally volant prey in syntopic populations, suggesting that the shift in diet may be driven by a change in foraging mode. Our findings suggest that fine-scale coexistence mechanisms can have implications for maintaining broad-scale diversity patterns. This study highlights the importance of including both allopatric and sympatric populations and choosing meaningful spatial scales for detecting ecological patterns. We conclude that a combination of high taxonomic resolution with a functional approach helps identify patterns of niche shift.

A powerful long metabarcoding method for the determination of complex diets from faecal analysis of the European pond turtle (Emys orbicularis, L. 1758)

High‐throughput sequencing has become an accurate method for the identification of species present in soil, water, faeces, gut or stomach contents. However, information at the species level is limited due to the choice of short barcodes and based on the idea that DNA is too degraded to allow longer sequences to be amplified. We have therefore developed a long DNA metabarcoding method based on the sequencing of short reads followed by de novo assembly, which can precisely identify the taxonomic groups of organisms associated with complex diets, such as omnivorous individuals. The procedure includes 11 different primer pairs targeting the COI gene, the large subunit of the ribulose‐1,5‐bisphosphate carboxylase gene, the maturase K gene, the 28S rRNA and the trnL‐trnF chloroplastic region. We validated this approach using 32 faeces samples from an omnivorous reptile, the European pond turtle (Emys orbicularis, L. 1758). This metabarcoding approach was assessed using controlled experiments including mock communities and faecal samples from captive feeding trials. The method allowed us to accurately identify prey DNA present in the diet of the European pond turtles to the species level in most of the cases (82.4%), based on the amplicon lengths of multiple markers (168–1,379 bp, average 546 bp), and produced by de novo assembly. The proposed approach can be adapted to analyse various diets, in numerous conservation and ecological applications. It is consequently appropriate for detecting fine dietary variations among individuals, populations and species as well as for the identification of rare food items.

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo-mock community (33 arthropod taxa from 16 orders), and guano-based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano-based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one-third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.

Food from faeces: Evaluating the efficacy of scat DNA metabarcoding in dietary analyses

Scat DNA metabarcoding is increasingly being used to track the feeding ecology of elusive wildlife species. This approach has greatly increased the resolution and detection success of prey items contained in scats when compared with other classical methods. However, there have been few studies that have systematically tested the applicability and reliability of this approach to study the diet of large felids species in the wild. Here we assessed the effectiveness of this approach in the cheetah Acinonyx jubatus. We tested how scat degradation, meal size, prey species consumed and feeding day (the day a particular prey was consumed) influenced prey DNA detection success in captive cheetahs. We demonstrated that it is possible to obtain diet information from 60-day old scats using genetic approaches, but the efficiency decreased over time. Probability of species-identification was highest for food items consumed one day prior to scat collection and the probability of being able to identify the species consumed increased with the proportion of the prey consumed. Detection success varied among prey species but not by individual cheetah. Identification of prey species using DNA detection methods from a single consumption event worked for samples collected between 8 and 72 hours post-feeding. Our approach confirms the utility of genetic approaches to identify prey species in scats and highlight the need to account for the systematic bias in results to control for possible scat degradation, feeding day, meal size and prey species consumed especially in the wild-collected scats.

Gaining ecological insight on dietary allocation among horseshoe bats through molecular primer combination

Knowledge on the trophic interactions among predators and their prey is important in order to understand ecology and behaviour of animals. Traditionally studies on the diet composition of insectivorous bats have been based on the morphological identification of prey remains, but the accuracy of the results has been hampered due to methodological limitations. Lately, the DNA metabarcoding and High Throughput Sequencing (HTS) techniques have changed the scene since they allows prey identification to the species level, ultimately giving more precision to the results. Nevertheless, the use of one single primer set to amplify faecal DNA produces biases in the assessed dietary composition. Three horseshoe bats overlap extensively in their distribution range in Europe: Rhinolophus euryale, R. hipposideros and R. ferrumequinum. In order to achieve the deepest insight on their prey list we combined two different primers. Results showed that the used primers were complementary at the order and species levels, only 22 out of 135 prey species being amplified by both. The most frequent prey of R. hipposideros belonged to Diptera and Lepidoptera, to Lepidoptera in R. euryale, and Lepidoptera, Diptera and Coleoptera in R. ferrumequinum. The three bats show significant resource partitioning, since their trophic niche overlap is not higher than 34%. Our results confirm the importance of combining complementary primers to describe the diet of generalist insectivorous bats with amplicon metabarcoding techniques. Overall, each primer set showed a subset of the prey composition, with a small portion of the total prey being identified by both of them. Therefore, each primer presented a different picture of the niche overlap among the three horseshoe bats due to their taxonomic affinity.

Pest consumption in a vineyard system by the lesser horseshoe bat (Rhinolophus hipposideros)

Herbivorous arthropods cause immense damage in crop production annually. Consumption of these pests by insectivorous animals is of significant importance to counteract their adverse effects. Insectivorous bats are considered amongst the most voracious predators of arthropods, some of which are known crop pests. In vineyard-dominated Mediterranean agroecosystems, several crops are damaged by the attack of insect pests. In this study we aimed 1) to explore the diet and pest consumption of the lesser horseshoe bat Rhinolophus hipposideros and 2) analyse whether the composition of pest species in its diet changes throughout the season. We employed a dual-primer DNA metabarcoding analysis of DNA extracted from faeces collected in three bat colonies of a wine region in Southwestern Europe during the whole active period of most pest species. Overall, 395 arthropod prey species belonging to 11 orders were detected; lepidopterans and dipterans were the most diverse orders in terms of species. Altogether, 55 pest species were identified, 25 of which are known to cause significant agricultural damage and 8 are regarded as pests affecting grapevines. The composition of pest species in faeces changed significantly with the season, thus suggesting several periods should be sampled to assess the pest consumption by bats. As a whole, the results imply that R. hipposideros acts as a suppressor of a wide array of agricultural pests in Mediterranean agroecosystems. Therefore, management measures favouring the growth of R. hipposideros populations should be considered.