Thursday, June 14, 2018

#BadStockPhotosOfMyJob

Ever seen anything in relation to the hashtag #BadStockPhotosOfMyJob? If not you should check out Twitter or search for it on Google because it really shows some ridiculously funny photos that exhibit some of the worst stereotypes people have when thinking about other's jobs. Especially the perception of what scientists do is almost tragic. I thought its a good idea to show a few examples including ironic comments by the real scientists. It's funny indeed but sometimes also just sad to see what others think we scientists do for a living.


 


  I have no words for those four.

Wednesday, June 13, 2018

Interview with a vampire

In this study, we show for the first time that it is possible to use DNA meta-barcoding to generate data on both diet and the predator's population structure. And we more or less get this additional information for free because the vampire bat's DNA is found in the DNA that we extract from blood meal and faecal samples

When the sun sets in South and Central America, the vampire bats wake up and fly out in search of prey. The vampire bat's diet consists of blood. It prefers to feed on domestic animals such as cows and pigs, but when it does so, there is a risk of transmitting pathogens such as rabies. In order to control rabies transmitted by vampire bats, it is crucial to have a method that allows large-scale assessment of vampire bat prey. A study published back in April led by researchers from Denmark and the UK, shows that metabarcoding can do just that.

The colleagues analysed vampire bat blood meal and faecal samples collected in Peru, along the coast, in the Andes and in the Amazon. In diet studies, the metabarcoding is normally only used to assess diet, but in this study, the researchers went one step further and gathered information on the vampire bat's population structure. The latter is an approach very similar to work my group has been doing in collaboration with researchers in Germany. This 'free of charge' data can help researchers understand how the landscape influences the connectivity of vampire bat populations, which could influence the spread of pathogens. 

We are slowly beginning to understand that all the metabarcoding data we generate to better understand community composition of a given environment contains several layers of information. It is perhaps much richer than an OTU table. That being said it is an entire different story on how to release let alone disentangle all that information.

It is great to gain insight into both predator and prey from DNA in droppings and blood meals. Apart from feeding on domestic animals, vampire bats occasionally took blood from wild tapirs, so the method may be useful for determining the distribution of elusive mammal prey. It is also of note that we found no evidence of vampire bats feeding on humans from the DNA left over from their dinners.





Tuesday, June 12, 2018

Citizen science vs giant slugs

Citizen science is a powerful tool to combat the challenges created by invasive species. Our study emphasizes the importance of collaborations between researchers, government administration, and citizen volunteers. 

The giant slug Limax maximus is an invasive species which made its way from northern Europe all the way to Japan and other regions of the world. It is a notorious pest of horticultural and agricultural crops. 

Recently a Japanese research team found that a certain set of weather conditions could be a reliable short-term indicator of how often giant slugs would appear on a set mountain path. The findings showed that the slugs were more likely to appear on days with higher humidity, lower windspeed and lower precipitation than the 20-year average. These observations can be used to predict future  outbreaks of the pest. 

This study was actually made possible by citizen science. In order to survey the number of slugs present on the mountain path chosen for the study (Mt. Maruyama route, in Sapporo, Japan), a volunteer naturalist hiked the path at 5:00 AM nearly every day for two years. The colleagues collected weather data obtained from a nearby meteorological station and combined them with observational data to calculate correlations between slug appearances and complex weather conditions.

Friday, June 8, 2018

Weekend readings

Need some readings for a sunny weekend? Not enough papers on the pile on your desk? Here is a solution for you. A couple of interesting journal articles I came across this week. Enjoy.

The genus Amara Bonelli, 1810 is a very speciose and taxonomically difficult genus of the Carabidae. The identification of many of the species is accomplished with considerable difficulty, in particular for females and immature stages. In this study the effectiveness of DNA barcoding, the most popular method for molecular species identification, was examined to discriminate various species of this genus from Central Europe. DNA barcodes from 690 individuals and 47 species were analysed, including sequences from previous studies and more than 350 newly generated DNA barcodes. Our analysis revealed unique BINs for 38 species (81%). Interspecific K2P distances below 2.2% were found for three species pairs and one species trio, including haplotype sharing between Amara alpina/Amara torrida and Amara communis/Amara convexior/Amara makolskii. This study represents another step in generating an extensive reference library of DNA barcodes for carabids, highly valuable bioindicators for characterizing disturbances in various habitats.

The correct identification of species in the highly divergent group of plants is crucial for several forensic investigations. Previous works had difficulties in the establishment of a rapid and robust method for the identification of plants. For instance, DNA barcoding requires the analysis of two or three different genomic regions to attain reasonable levels of discrimination. Therefore, new methods for the molecular identification of plants are clearly needed. Here we tested the utility of variable-length sequences in the chloroplast DNA (cpDNA) as a way to identify plant species. The SPInDel (Species Identification by Insertions/Deletions) approach targets hypervariable genomic regions that contain multiple insertions/deletions (indels) and length variability, which are found interspersed with highly conserved regions. The combination of fragment lengths defines a unique numeric profile for each species, allowing its identification. We analysed more than 44,000 sequences retrieved from public databases belonging to 206 different plant families. Four target regions were identified as suitable for the SPInDel concept: atpF-atpH, psbA-trnH, trnL CD and trnL GH. When considered alone, the discrimination power of each region was low, varying from 5.18% (trnL GH) to 42.54% (trnL CD). However, the discrimination power reached more than 90% when the length of some of these regions is combined. We also observed low diversity in intraspecific data sets for all target regions, suggesting they can be used for identification purposes. Our results demonstrate the utility of the SPInDel concept for the identification of plants.

Environmental DNA (eDNA) metabarcoding has been increasingly applied to biodiversity surveys in stream ecosystems. In stream networks, the accuracy of eDNA-based biodiversity assessment depends on whether the upstream eDNA influx affects downstream detection. Biodiversity assessment in low-discharge streams should be less influenced by eDNA transport than in high-discharge streams. We estimated α- and β-diversity of the fish community from eDNA samples collected in a small Michigan (USA) stream from its headwaters to its confluence with a larger river. We found that α-diversity increased from upstream to downstream and, as predicted, we found a significant positive correlation between β-diversity and physical distance (stream length) between locations indicating species turnover along the longitudinal stream gradient. Sample replicates and different genetic markers showed similar species composition, supporting the consistency of the eDNA metabarcoding approach to estimate α- and β-diversity of fishes in low-discharge streams.

The use of environmental DNA (eDNA) has become an applicable non-invasive tool with which to obtain information about biodiversity. A sub-discipline of eDNA is iDNA (invertebrate-derived DNA), where genetic material ingested by invertebrates is used to characterise the biodiversity of the species that served as hosts. While promising, these techniques are still in their infancy, as they have only been explored on limited numbers of samples from only a single or a few different locations. In this study, we investigate the suitability of iDNA extracted from more than 3,000 haematophagous terrestrial leeches as a tool for detecting a wide range of terrestrial vertebrates across five different geographical regions on three different continents. These regions cover almost the full geographical range of haematophagous terrestrial leeches, thus representing all parts of the world where this method might apply. We identify host taxa through metabarcoding coupled with high-throughput sequencing on Illumina and IonTorrent sequencing platforms to decrease economic costs and workload and thereby make the approach attractive for practitioners in conservation management. We identified hosts in four different taxonomic vertebrate classes: mammals, birds, reptiles, and amphibians, belonging to at least 42 different taxonomic families. We find that vertebrate blood ingested by haematophagous terrestrial leeches throughout their distribution is a viable source of DNA with which to examine a wide range of vertebrates. Thus, this study provides encouraging support for the potential of haematophagous terrestrial leeches as a tool for detecting and monitoring terrestrial vertebrate biodiversity.

Advances in DNA sequencing technology have revolutionised the field of molecular analysis of trophic interactions and it is now possible to recover counts of food DNA sequences from a wide range of dietary samples. But what do these counts mean? To obtain an accurate estimate of a consumer's diet should we work strictly with datasets summarising frequency of occurrence of different food taxa, or is it possible to use relative number of sequences? Both approaches are applied to obtain semi-quantitative diet summaries, but occurrence data is often promoted as a more conservative and reliable option due to taxa-specific biases in recovery of sequences. We explore representative dietary metabarcoding datasets and point out that diet summaries based on occurrence data often overestimate the importance of food consumed in small quantities (potentially including low-level contaminants) and are sensitive to the count threshold used to define an occurrence. Our simulations indicate that using relative read abundance (RRA) information often provide a more accurate view of population-level diet even with moderate recovery biases incorporated; however, RRA summaries are sensitive to recovery biases impacting common diet taxa. Both approaches are more accurate when the mean number of food taxa in samples is small. The ideas presented here highlight the need to consider all sources of bias and to justify the methods used to interpret count data in dietary metabarcoding studies. We encourage researchers to continue addressing methodological challenges, and acknowledge unanswered questions to help spur future investigations in this rapidly developing area of research.

DNA metabarcoding is a rapidly growing technique for obtaining detailed dietary information. Current metabarcoding methods for herbivory, using a single locus, can lack taxonomic resolution for some applications. We present novel primers for the second internal transcribed spacer of nuclear ribosomal DNA (ITS2) designed for dietary studies in Mauritius and the UK, which have the potential to give unrivalled taxonomic coverage and resolution from a short-amplicon barcode. In silico testing used three databases of plant ITS2 sequences from UK and Mauritian floras (native and introduced) totalling 6561 sequences from 1790 species across 174 families. Our primers were well-matched in silico to 88% of species, providing taxonomic resolution of 86.1%, 99.4% and 99.9% at the species, genus and family levels, respectively. In vitro, the primers amplified 99% of Mauritian (n = 169) and 100% of UK (n = 33) species, and co-amplified multiple plant species from degraded faecal DNA from reptiles and birds in two case studies. For the ITS2 region, we advocate taxonomic assignment based on best sequence match instead of a clustering approach. With short amplicons of 187-387 bp, these primers are suitable for metabarcoding plant DNA from faecal samples, across a broad geographic range, whilst delivering unparalleled taxonomic resolution.

The implementation of HTS (high-throughput sequencing) approaches is rapidly changing our understanding of the lichen symbiosis, by uncovering high bacterial and fungal diversity, which is often host-specific. Recently, HTS methods revealed the presence of multiple photobionts inside a single thallus in several lichen species. This differs from Sanger technology, which typically yields a single, unambiguous algal sequence per individual. Here we compared HTS and Sanger methods for estimating the diversity of green algal symbionts within lichen thalli using 240 lichen individuals belonging to two species of lichen-forming fungi. According to HTS data, Sanger technology consistently yielded the most abundant photobiont sequence in the sample. However, if the second most abundant photobiont exceeded 30% of the total HTS reads in a sample, Sanger sequencing generally failed. Our results suggest that most lichen individuals in the two analyzed species, Lasallia hispanica and L. pustulata, indeed contain a single, predominant green algal photobiont. We conclude that Sanger sequencing is a valid approach to detect the dominant photobionts in lichen individuals and populations. We discuss which research areas in lichen ecology and evolution will continue to benefit from Sanger sequencing, and which areas will profit from HTS approaches to assessing symbiont diversity.

Thursday, June 7, 2018

Who owns ocean biodiversity?

Within national jurisdiction, the Nagoya Protocol protects countries from exploitative bioprospecting, and is meant to foster greater equity. But there's a huge missing piece, because two-thirds of the ocean exists beyond national jurisdiction. That's roughly half the Earth's surface with no regulations on accessing or using genetic resources.

Marine organisms have evolved to thrive in various ocean environments, resulting in unique adaptations that make them the object of commercial interest, particularly for biomedical and industrial applications. Researchers from the Stockholm Resilience Centre and University of British Columbia have now identified 862 marine species, with a total of 12,998 genetic sequences that associated with a patent. They found that a single transnational corporation (BASF, the world's largest chemical manufacturer) has registered 47% of these sequences. Public and private universities accounted for another 12%, while entities such as governmental bodies, individuals, hospitals, and nonprofit research institutes registered the remaining 4%. Overall, entities located in only 10 countries accounted for 98% of the patents. 

A considerable portion of all patent sequences (11%) are derived from species associated with deep sea and hydrothermal vent ecosystems (91 species, 1650 sequences), many of which are found in unregulated areas beyond national jurisdiction.

Establishing a legal framework for marine genetic resources will be a core issue when international negotiations on a new UN treaty on the conservation and sustainable use of biodiversity in areas beyond national jurisdiction (BBNJ) begin in earnest in September 2018. By 2025, the global market for marine biotechnology is expected to reach $6.4 billion and span a broad range of commercial purposes for pharmaceutical, biofuel, and chemical industries. It is clear that these industry leaders must be involved in the upcoming BBNJ treaty negotiations, if only by virtue of their ownership of such a large share of the marine genetic sequence patents.

Wednesday, June 6, 2018

Deep learning to identify and count wild animals

This technology lets us accurately, unobtrusively and inexpensively collect wildlife data, which could help catalyze the transformation of many fields of ecology, wildlife biology, zoology, conservation biology and animal behavior into 'big data' sciences. This will dramatically improve our ability to both study and conserve wildlife and precious ecosystems.

Motion sensor camera trap' unobtrusively take pictures of animals in their natural environment, oftentimes yielding images not otherwise observable. The information in these photographs is only useful once it has been converted into numerical data. For years, the best method for extracting such information was to involve crowdsourced teams of human volunteers to label each image manually.

A team of researchers form the US and the UK has developed a system to automatically extract such information from images by using deep neural networks. The result is a system that can automate animal identification for up to 99.3 percent of images while still performing at the same 96.6 percent accuracy rate of crowdsourced teams of human volunteers. Deep neural networks are artificial neural networks with multiple hidden layers between the input and output layers. They require vast amounts of training data to work well, and the data must be accurately labeled (e.g., each image being correctly tagged with which species of animal is present, how many there are, etc.). For this study such data was available through Snapshot Serengeti, a citizen science project. Snapshot Serengeti has deployed a large number of camera traps in Tanzania that collect millions of images of animals in their natural habitat, such as lions, leopards, cheetahs and elephants. For this study 3.2 million labeled images tagged by more than 50,000 human volunteers over several years were used as training set.

Not only does the artificial intelligence system tell you which of 48 different species of animal is present, but it also tells you how many there are and what they are doing. It will tell you if they are eating, sleeping, if babies are present, etc. We estimate that the deep learning technology pipeline we describe would save more than eight years of human labeling effort for each additional 3 million images. That is a lot of valuable volunteer time that can be redeployed to help other projects.

Tuesday, June 5, 2018

What a few rabbits can do

Azorella selago
Understanding the full impact of an invasive species on an environment is very difficult as it involves many factors, one of which is generally a long timescale. A team of researchers from France, Italy and Norway has found a natural historical record of the impact of an invasive species of rabbit on a remote Indian Ocean island. They used an environment with few interacting variables and a natural historical record - DNA found in a lake bottom.

A type of rabbit was introduced to the Kerguelen Islands, situated in a remote southern part of the Indian Ocean. In 1874 a group of scientists that were studying the transit of Venus brought the animals with them as a food source and when they disembarked they left behind several rabbits that quickly multiplied because there were no natural predators. Since then, the rabbits spread across much of the main island of Grande Terre, wreaking havoc on a delicate ecosystem.

To learn more about the impact the rabbits had on the island, the colleagues collected samples from the bottom of a lake which contained samples of plant DNA. They found samples dating back several hundred years, and were able to reconstruct the events after the scientists left the island. The region had been relatively stable for hundreds of years prior to the arrival of the rabbits. Then, in the early 1940s, when the rabbits made their way to the part of the island were the lake is located, things changed. Prior to their arrival, the dominant plant was Azorella selago; after their arrival, plant diversity plummeted and Azorella selago disappeared quickly. They also noted that erosion dramatically increased, although it did eventually level off, but the ecosystem was left unstable, and remains until today in spite of efforts to eradicate the rabbits. Instead, as the result of increased human presence in the area, other invasive species have made their way to the islands. 

Monday, June 4, 2018

1000 posts


Wow - who would have thought back in 2012 that I will ever reach such a high number of posts. 

The prouder I am to have reached this milestone. The blog is still alive and kicking and I have all intentions to keep it that way. 

A big shoutout to all my readers. Without them there would be no blog. Thank you!

Off to the next thousand.

Measuring plant diversity using spectral imaging

We have known for decades that the chemical composition of plants can be estimated from reflectance spectra. What we found is that the spectral dissimilarity, or the overall differences in spectral reflectance, among plant species increases with their functional dissimilarity and evolutionary divergence time.

The value of ecological biodiversity for maintaining ecosystem stability and function is well established, but how do we measure it at larger scales. We need novel approaches that are rapid, repeatable and scalable in particular in ecosystems for which information about species identity and the number of species is difficult to acquire.

A group of US researchers is proposing to measure plant diversity using spectral data in an attempt to  improve efforts to predict how well ecosystems function. The colleagues measured the light reflectance of plants in 35 plots at a field station north of Minneapolis famous for long-term ecological experiments by using a field spectrometer. The spectrometer allows the researchers to evaluate how much light plants reflect at the leaf level across a range of wavelengths. By taking the leaf-level data the team found that the spectral diversity of a plant community predicted aboveground productivity, a critical ecosystem function, to a similar or higher degree than measures of species functional differences, their phylogenetic distances or species richness in a plant community.

Seeing that the ecosystem effect of plant diversity can be effectively evaluated using spectrometry, the team also wanted to know if their method could scale. They used an imaging spectrometer mounted three meters above ground at the same 35 plots at Cedar Creek. Their scans showed that the spectral diversity metric performed similarly when calculated from such spectral images.

The findings indicate that spectral diversity provides a powerful, integrative method of assessing several dimensions of biodiversity relevant to ecosystem function. The rapid changes in the Earth's biodiversity that are underway require novel means of continuous and global detection. This study demonstrates that we can detect plant biodiversity using spectral measurements from plant leaves or from the sky, which opens a whole new range of possibilities.

I guess all that needs to be shown is how well it really scales when it comes to remote sensing technology but this is really promising especially when taking into account the breadth of additional information the colleagues were able to obtain.

Friday, June 1, 2018

Weekend reads

This week a hopefully eclectic collection of reads. I  also hope I posted something for everyone.

Microeukaryotic plankton (0.2-200 μm) are critical components of aquatic ecosystems and key players in global ecological processes. High-throughput sequencing is currently revolutionizing their study on an unprecedented scale. However, it is currently unclear whether we can accurately, effectively and quantitatively depict the microeukaryotic plankton communities using traditional size-fractionated filtering combined with molecular methods. To address this, we analysed the eukaryotic plankton communities both with, and without, prefiltering with a 200 μm pore-size sieve -by using SSU rDNA-based high-throughput sequencing on 16 samples with three replicates in each sample from two subtropical reservoirs sampled from January to October in 2013. We found that ~25% reads were classified as metazoan in both size groups. The species richness, alpha and beta diversity of plankton community and relative abundance of reads in 99.2% eukaryotic OTUs showed no significant changes after prefiltering with a 200 μm pore-size sieve. We further found that both >0.2 μm and 0.2-200 μm eukaryotic plankton communities, especially the abundant plankton subcommunities, exhibited very similar, and synchronous, spatiotemporal patterns and processes associated with almost identical environmental drivers. The lack of an effect on community structure from prefiltering suggests that environmental DNA from larger metazoa is introduced into the smaller size class. Therefore, size-fractionated filtering with 200 μm is insufficient to discriminate between the eukaryotic plankton size groups in metabarcoding approaches. Our results also highlight the importance of sequencing depth, and strict quality filtering of reads, when designing studies to characterize microeukaryotic plankton communities.

Understanding the geographical distribution and community composition of species is crucial to monitor species persistence and define effective conservation strategies. Environmental DNA (eDNA) has emerged as a powerful noninvasive tool for species detection. However, most eDNA survey methods have been developed and applied in temperate zones. We tested the feasibility of using eDNA to survey anurans in tropical streams in the Brazilian Atlantic forest and compared the results with short-term visual and audio surveys. We detected all nine species known to inhabit our focal streams with one single visit for eDNA sampling. We found a higher proportion of sequence reads and larger number of positive PCR replicates for more common species and for those with life cycles closely associated with the streams, factors that may contribute to increased release of DNA in the water. However, less common species were also detected in eDNA samples, demonstrating the detection power of this method. Filtering larger volumes of water resulted in a higher probability of detection. Our data also show it is important to sample multiple sites along streams, particularly for detection of target species with lower population densities. For the three focal species in our study, the eDNA metabarcoding method had a greater capacity of detection per sampling event than our rapid field surveys, and thus, has the potential to circumvent some of the challenges associated with traditional approaches. Our results underscore the utility of eDNA metabarcoding as an efficient method to survey anuran species in tropical streams of the highly biodiverse Brazilian Atlantic forest.

Next-generation deep amplicon sequencing, or metabarcoding, has revolutionized the study of microbial communities in humans, animals and the environment. However, such approaches have yet to be applied to parasitic helminth communities. We recently described the first example of such a method - nemabiome sequencing - based on deep-amplicon sequencing of internal transcribed spacer 2 (ITS-2) rDNA, and validated its ability to quantitatively assess the species composition of cattle gastro-intestinal nematode (GIN) communities. Here, we present the first application of this approach to explore GIN species diversity and the impact of anthelmintic drug treatments. First, we investigated GIN species diversity in cow-calf beef cattle herds in several different regions, using coproculture derived L3s. A screen of 50 Canadian beef herds revealed parasite species diversity to be low overall. The majority of parasite communities were comprised of just two species; Ostertagia ostertagi and Cooperia oncophora. Cooperia punctata was present at much lower levels overall, but nevertheless comprised a substantive part of the parasite community of several herds in eastern Canada. In contrast, nemabiome sequencing revealed higher GIN species diversity in beef calves sampled from central/south-eastern USA and Sao Paulo State, Brazil. In these regions C. punctata predominated in most herds with Haemonchus placei predominating in a few cases. Ostertagia ostertagi and C. oncophora were relatively minor species in these regions in contrast to the Canadian herds. We also examined the impact of routine macrocyclic lactone pour-on treatments on GIN communities in the Canadian beef herds. Low treatment effectiveness was observed in many cases, and nemabiome sequencing revealed an overall increase in the proportion of Cooperia spp. relative to O. ostertagi post-treatment. This work demonstrates the power of nemabiome metabarcoding to provide a detailed picture of GIN parasite community structure in large sample sets and illustrates its potential use in research, diagnostics and surveillance.

DNA metabarcoding is an increasingly popular method to characterize and quantify biodiversity in environmental samples. Metabarcoding approaches simultaneously amplify a short, variable genomic region, or "barcode," from a broad taxonomic group via the polymerase chain reaction (PCR), using universal primers that anneal to flanking conserved regions. Results of these experiments are reported as occurrence data, which provide a list of taxa amplified from the sample, or relative abundance data, which measure the relative contribution of each taxon to the overall composition of amplified product. The accuracy of both occurrence and relative abundance estimates can be affected by a variety of biological and technical biases. For example, taxa with larger biomass may be better represented in environmental samples than those with smaller biomass. Here, we explore how polymerase choice, a potential source of technical bias, might influence results in metabarcoding experiments. We compared potential biases of six commercially available polymerases using a combination of mixtures of amplifiable synthetic sequences and real sedimentary DNA extracts. We find that polymerase choice can affect both occurrence and relative abundance estimates and that the main source of this bias appears to be polymerase preference for sequences with specific GC contents. We further recommend an experimental approach for metabarcoding based on results of our synthetic experiments.

Molecular gut-content analysis has revolutionized the study of food webs and feeding interactions, allowing the detection of prey DNA within the gut of many organisms. However, successful prey detection is a challenging procedure in which many factors affect every step, starting from the DNA extraction process. Spiders are liquid feeders with branched gut diverticula extending into their legs and throughout the prosoma, thus digestion takes places in different parts of the body and simple gut dissection is not possible. In this study, we investigated differences in prey detectability in DNA extracts from different parts of the spider´s body: legs, prosoma and opisthosoma, using prey-specific PCR and metabarcoding approaches. We performed feeding trials with the woodlouse hunter spider Dysdera verneaui Simon, 1883 (Dysderidae) to estimate the time at which prey DNA is detectable within the predator after feeding. Although we found that all parts of the spider body are suitable for gut-content analysis when using prey-specific PCR approach, results based on metabarcoding suggested the opisthosoma is optimal for detection of predation in spiders because it contained the highest concentration of prey DNA for longer post feeding periods. Other spiders may show different results compared to D. verneaui, but given similarities in the physiology and digestion in different families, it is reasonable to assume this to be common across species and this approach having broad utility across spiders.

Tropical animals and plants are known to have high alpha diversity within forests, but low beta diversity between forests. By contrast, it is unknown if microbes inhabiting the same ecosystems exhibit similar biogeographic patterns. To evaluate the biogeographies of tropical protists, we used metabarcoding data of species sampled in the soils of three lowland Neotropical rainforests. Taxa-area and distance-decay relationships for three of the dominant protist taxa and their subtaxa were estimated at both the OTU- and phylogenetic-levels, with presence-absence and abundance based measures. These estimates were compared to null models. High local alpha and low regional beta diversity patterns were consistently found for both the parasitic Apicomplexa and the largely free-living Cercozoa and Ciliophora. Similar to animals and plants, the protists showed spatial structures between forests at the OTU- and phylogenetic-levels, and only at the phylogenetic level within forests. These results suggest that the biogeographies of macro- and micro-organismal eukaryotes in lowland Neotropical rainforests are partially structured by the same general processes. However, and unlike the animals and plants, the protist OTUs did not exhibit spatial structures within forests, which hinders our ability to estimate local and regional diversity of protists in tropical forests.

Maximizing the delivery of key ecosystem services such as biological control through the management of natural enemy communities is one of the major challenges for modern agriculture. The main obstacle lies in our yet limited capacity of identifying the factors that drive the dynamics of trophic interactions within multi-species assemblages. Invertebrate generalist predators like carabid beetles are known for their dynamic feeding behaviour. Yet, at what extent different carabid species contribute to the regulation of animal and plant pests within agroecosystems is currently unknown. Here, we developed a DNA metabarcoding approach for characterizing the full diet spectrum of a community of fourteen very common carabid species inhabiting an intensively managed Western-European agroecosystem. We then investigated how diet and biological control potential within the carabid community varies with the sampling field location and the crop type (wheat vs oilseed rape). DNA metabarcoding diet analysis allowed to detect a wide variety of animal and plant taxa from carabid gut contents thus confirming their generalist feeding behaviour. The most common prey categories detected were arachnids, insects, earthworms and several plant families potentially including many weed species. Our results also show that the field location and the crop type are much stronger determinants then the species regarding carabid dietary choice: significantly more trophic links involving dipteran prey were observed in wheat, whereas more collembolan and plant prey was consumed in oilseed rape by the same carabid community. We speculate that structural differences in the habitats provided by these two crop types drive differences in resource availability cascading up the trophic chain, and we assume that specific carabid taxa could hardly be used to infer levels of ecosystem services (biological control) or disservices (e.g. intraguild predation). However, as this is the first study to report the use of DNA metabarcoding diet analysis in predatory carabid beetles we urge caution over the interpretation of our results. For instance, overall detection rates were rather low (31% of the individuals analysed tested positive for at least one prey category) most likely due to the overwhelming amplification of the carabid host DNA. Therefore, we acknowledge that more studies are required in order to confirm our observations and conclude with few recommendations for further improvements of the community-level DNA metabarcoding analysis of carabid diet.