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opencc-zeroDec 2016View details →

Data from: Metabarcoding for the parallel identification of several hundred predators and their preys: application to bat species diet analysis

Assessing diet variability is of main importance to better understand the biology of bats and design conservation strategies. Although the advent of metabarcoding has facilitated such analyses, this approach does not come without challenges. Biases may occur throughout the whole experiment, from fieldwork to biostatistics, resulting in the detection of false negatives, false positives or low taxonomic resolution. We detail a rigorous metabarcoding approach based on a short COI minibarcode and two-step PCR protocol enabling the 'all at once' taxonomic identification of bats and their arthropod preys for several hundreds of samples. Our study includes faecal pellets collected in France from 357 bats representing 16 species, as well as insect mock communities that mimic bat meals of known composition, negative and positive controls. All samples were analysed using three replicates. We compare the efficiency of DNA extraction methods and we evaluate the effectiveness of our protocol using identification success, taxonomic resolution, sensitivity, and amplification biases. Our parallel identification strategy of predators and preys reduces the risk of mis-assigning preys to wrong predators and decreases the number of molecular steps. Controls and replicates enable to filter the data and limit the risk of false positives, hence guaranteeing high confidence results for both prey occurrence and bat species identification. We validate 551 COI variants from arthropod including 18 orders, 117 family, 282 genus and 290 species. Our method therefore provides a rapid, resolutive and cost-effective screening tool for addressing evolutionary ecological issues or developing 'chirosurveillance' and conservation strategies.

Data from: A study of applicability of SNP chips developed for bovine and ovine species to whole-genome analysis of reindeer Rangifer tarandus

Two sets of commercially available single nucleotide polymorphisms (SNPs) developed for cattle (BovineSNP50 BeadChip) and sheep (OvineSNP50 BeadChip) have been trialed for whole-genome analysis of 4 female samples of Rangifer tarandus inhabiting Russia. We found out that 43.0% of bovine and 47.0% of Ovine SNPs could be genotyped, while only 5.3% and 2.03% of them were respectively polymorphic. The scored and the polymorphic SNPs were identified on each bovine and each ovine chromosome, but their distribution was not unique. The maximal value of runs of homozygosity (ROH) was 30.93Mb (for SNPs corresponding to bovine chromosome 8) and 80.32Mb (for SNPs corresponding to ovine chromosome 7). Thus, the SNP chips developed for bovine and ovine species can be used as a powerful tool for genome analysis in reindeer R. tarandus.

opencc-zeroDec 2019View details →

Data from: Microbial functional diversity: from concepts to applications

Functional diversity is increasingly recognized by microbial ecologists as the essential link between biodiversity patterns and ecosystem functioning, determining the trophic relationships and interactions between microorganisms, their participation in biogeochemical cycles and their responses to environmental changes. Consequently, its definition and quantification have practical and theoretical implications. In this opinion paper, we present a synthesis on the concept of microbial functional diversity from its definition to its application. Initially, we revisit to the original definition of functional diversity, highlighting two fundamental aspects, the ecological unit under study and the functional traits used to characterize it. Then, we discuss how the particularities of the microbial world disallow the direct application of the concepts and tools developed for macroorganisms. Next, we provide a synthesis of the literature on the types of ecological units and functional traits available in microbial functional ecology. We also provide a list of more than 400 traits covering a wide array of environmentally relevant functions. Lastly, we provide examples of the use of functional diversity in microbial systems based on the different units and traits discussed herein. It is our hope that this paper will stimulate discussions and help the growing field of microbial functional ecology to realize a potential that thus far has only been attained in macrobial ecology.

Data from: Effect of ecological momentary assessment, goal-setting and personalized phone-calls on adherence to interval walking training using the InterWalk application among patients with type 2 diabetes – a pilot randomized controlled trial

Objectives: The objective was to investigate the feasibility and usability of structured text-messages, goal-setting and phone-calls on adherence to a 12-week self-conducted interval walking training (IWT) program, delivered by the InterWalk smartphone among patients with type 2 diabetes (T2D). Methods: In a two-arm pilot randomized controlled trial (Denmark, March 2014 to February 2015), patients with T2D (18-80 years with a Body Mass Index of 18 and 40 kg/m2) were randomly allocated to 12 weeks of IWT with (intervention) or without additional support (control). The primary outcome was the difference between groups in accumulated time of interval walking training across 12 weeks. All patients were encouraged to use the InterWalk application to perform IWT for ≥90 minute/week. Patients in the intervention group made individual goals regarding lifestyle change, received automated text-messages once a week, inquiring about exercise adherence. In case of consistent non-adherence, the patients would receive a phone-call inquiring about the reason for non-adherence. The control group did not receive additional support. Information about training adherence was assessed objectively. Usability of structured text-messages was assessed based on response rates and self-reported satisfaction after 12-weeks. Results: Thirty-seven patients with T2D (66 years, 65% female, hemoglobin 1Ac 50.3 mmol/mol) where included (n=18 and n=19 in intervention and control group, respectively). The retention rate was 83%. The intervention group accumulated [95%CI] 345 -7, 698 minutes of IWT more than the control group. The response rate for the text-messages was 83% (68% for males and 90% for females). Forty-one percent of the intervention and 25% of the control group were very satisfied with their participation. Conclusion: The combination of structured text-messages, goal-setting with the possibility of follow-up phone calls are considered feasible interventions to attain training adherence when using the InterWalk app during a 12-week period in patients with T2D. Some uncertainty about the effect size of adherence remains.

opencc-zeroJun 2019View details →

Data from: Through the eye of a Gobi khulan – application of camera collars for ecological research of far-ranging species in remote and highly variable ecosystems

The Mongolian Gobi-Eastern Steppe Ecosystem is one of the largest remaining natural drylands and home to a unique assemblage of migratory ungulates. Connectivity and integrity of this ecosystem are at risk if increasing human activities are not carefully planned and regulated. The Gobi part supports the largest remaining population of the Asiatic wild ass (Equus hemionus; locally called "khulan"). Individual khulan roam over areas of thousands of square kilometers and the scale of their movements is among the largest described for terrestrial mammals, making them particularly difficult to monitor. Although GPS satellite telemetry makes it possible to track animals in near-real time and remote sensing provides environmental data at the landscape scale, remotely collected data also harbors the risk of missing important abiotic or biotic environmental variables or life history events. We tested the potential of animal born camera systems ("camera collars") to improve our understanding of the drivers and limitations of khulan movements. Deployment of a camera collar on an adult khulan mare resulted in 7,881 images over a one-year period. Over half of the images showed other khulan and 1,630 images showed enough of the collared khulan to classify the behaviour of the animals seen into several main categories. These khulan images provided us with: i) new insights into important life history events and grouping dynamics, ii) allowed us to calculate time budgets for many more animals than the collared khulan alone, and iii) provided us with a training dataset for calibrating data from accelerometer and tilt sensors in the collar. The images also allowed to document khulan behaviour near infrastructure and to obtain a day-time encounter rate between a specific khulan with semi-nomadic herders and their livestock. Lastly, the images allowed us to ground truth the availability of water by: i) confirming waterpoints predicted from other analyses, ii) detecting new waterpoints, and iii) compare precipitation records for rain and snow from landscape scale climate products with those documented by the camera collar. We discuss the added value of deploying camera collars on a subset of animals in remote, highly variable ecosystems for research and conservation.

Data from: Value of information in natural resource management: technical developments and application to pink-footed geese

The "value of information" (VOI) is a generic term for the increase in value resulting from better information to guide management, or alternatively, the value foregone under uncertainty about the impacts of management (Yokota and Thompson, Medical Decision Making 2004; 24: 287). The value of information can be characterized in terms of several metrics, including the expected value of perfect information and the expected value of partial information. We extend the technical framework for the value of information by further developing the relationship between value metrics for partial and perfect information and describing patterns of their performance. We use two different expressions for the expected value of partial information to highlight its relationship to the expected value of perfect information. We also develop the expected value of partial information for hierarchical uncertainties. We highlight patterns in the value of information for the Svalbard population of the pink-footed goose (Anser brachyrhynchus), a population that is subject to uncertainty in both reproduction and survival functions. The framework for valuing information is seen as having widespread potential in resource decision making, and serves as a motivation for resource monitoring, assessment, and collaboration.

opencc-zeroDec 2012View details →

Data from: A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents

Introduction: The PCR-based analysis of homologous genes has become one of the most powerful approaches for species detection and identification, particularly with the recent availability of Next Generation Sequencing platforms (NGS) making it possible to identify species composition from a broad range of environmental samples. Identifying species from these samples relies on the ability to match sequences with reference barcodes for taxonomic identification. Unfortunately, most studies of environmental samples have targeted ribosomal markers, despite the fact that the mitochondrial Cytochrome c Oxidase subunit I gene (COI) is by far the most widely available sequence region in public reference libraries. This is largely because the available versatile ("universal") COI primers target the 658 barcoding region, whose size is considered too large for many NGS applications. Moreover, traditional barcoding primers are known to be poorly conserved across some taxonomic groups. Results: We first design a new PCR primer within the highly variable mitochondrial COI region, the "mlCOIintF" primer. We then show that this newly designed forward primer combined with the "jgHCO2198" reverse primer to target a 313 bp fragment performs well across metazoan diversity, with higher success rates than versatile primer sets traditionally used for DNA barcoding (i.e. LCO1490/HCO2198). Finally, we demonstrate how the shorter COI fragment coupled with an efficient bioinformatics pipeline can be used to characterize species diversity from environmental samples by pyrosequencing. We examine the gut contents of three species of planktivorous and benthivorous coral reef fish (family: Apogonidae and Holocentridae). After the removal of dubious COI sequences, we obtained a total of 334 prey Operational Taxonomic Units (OTUs) belonging to 14 phyla from 16 fish guts. Of these, 52.5% matched a reference barcode (>98% sequence similarity) and an additional 32% could be assigned to a higher taxonomic level using Bayesian assignment. Conclusions: The molecular analysis of gut contents targeting the 313 COI fragment using the newly designed mlCOIintF primer in combination with the jgHCO2198 primer offers enormous promise for metazoan metabarcoding studies. We believe that this primer set will be a valuable asset for a range of applications from large-scale biodiversity assessments to food web studies.

opencc-zeroDec 2018View details →

Data from: Use of hidden Markov capture-recapture models to estimate abundance in presence of uncertainty: application to estimating the prevalence of hybrids in animal populations

Estimating the relative abundance (prevalence) of different population segments is a key step in addressing fundamental research questions in ecology, evolution, and conservation. The raw percentage of individuals in the sample (naive prevalence) is generally used for this purpose, but it is likely to be subject to two main sources of bias. First, the detectability of individuals is ignored; second, classification errors may occur due to some inherent limits of the diagnostic methods. We developed a hidden Markov (also known as multievent) capture–recapture model to estimate prevalence in free‐ranging populations accounting for imperfect detectability and uncertainty in individual's classification. We carried out a simulation study to compare naive and model‐based estimates of prevalence and assess the performance of our model under different sampling scenarios. We then illustrate our method with a real‐world case study of estimating the prevalence of wolf (Canis lupus) and dog (Canis lupus familiaris) hybrids in a wolf population in northern Italy. We showed that the prevalence of hybrids could be estimated while accounting for both detectability and classification uncertainty. Model‐based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. We also showed that ignoring detectability and uncertainty in the wolf case study would lead to underestimating the prevalence of hybrids. Our results underline the importance of a model‐based approach to obtain unbiased estimates of prevalence of different population segments. Our model can be adapted to any taxa, and it can be used to estimate absolute abundance and prevalence in a variety of cases involving imperfect detection and uncertainty in classification of individuals (e.g., sex ratio, proportion of breeders, and prevalence of infected individuals).

opencc-zeroDec 2015View details →

Data from: Statistical evidence for common ancestry: application to primates

Since Darwin, biologists have come to recognize that the theory of descent from common ancestry is very well supported by diverse lines of evidence. However, while the qualitative evidence is overwhelming, we also need formal methods for quantifying the evidential support for common ancestry (CA) over the alternative hypothesis of separate ancestry (SA). In this paper we explore a diversity of statistical methods, using data from the primates. We focus on two alternatives to CA, species SA (the separate origin of each named species) and family SA (the separate origin of each family). We implemented statistical tests based on morphological, molecular, and biogeographic data and developed two new methods: one that tests for phylogenetic autocorrelation while correcting for variation due to confounding ecological traits and a method for examining whether fossil taxa have fewer derived differences than living taxa. We overwhelmingly rejected both species and family SA, with infinitesimal p-values. We compare these results with those from two companion papers, which also found tremendously strong support for the CA of all primates, and discuss future directions and general philosophical issues that pertain to statistical testing of historical hypotheses such as CA.

Data from: Heritability estimates from genome wide relatedness matrices in wild populations: application to a passerine, using a small sample size

Genomic developments have empowered the investigation of heritability in wild populations directly from genome wide relatedness matrices (GRM). Such GRM based approaches can in particular be used to improve or substitute approaches based on social pedigree (PED-social). However, measuring heritability from GRM in the wild has not been widely applied yet, especially using small samples and in non-model species. Here, we estimated heritability for four quantitative traits (tarsus length, wing length, bill length and body mass), using PED-social and a pedigree corrected by genetic data (PED-corrected) and GRM from a small sample (n = 494) of blue tits from natural populations in Corsica genotyped at nearly 50,000 filtered SNPs derived from RAD-seq. We also measured genetic correlations among traits and we performed chromosome partitioning. Heritability estimates were slightly higher when using GRM compared to PED-social, and PED-corrected yielded intermediate values, suggesting a minor underestimation of heritability in PED-social due to incorrect pedigree links, including extra-pair paternity, and to lower information content than the GRM. Genetic correlations among traits were similar between PED-social and GRM but credible intervals were very large in both cases, suggesting a lack of power for this small dataset. Although a positive linear relationship was found between the number of genes per chromosomes and the chromosome heritability for tarsus length, chromosome partitioning similarly showed a lack of power for the three other traits. We discuss the usefulness and limitations of the quantitative genetic inferences based on genomic data in small samples from wild populations.

opencc-zeroDec 2011View details →

Data from: De novo assembly of the transcriptome of an invasive snail and its multiple ecological applications

Studying how invasive species respond to environmental stress at the molecular level can help us assess their impact and predict their range expansion. Development of markers of genetic polymorphism can help us reconstruct their invasive route. However, to conduct such studies requires the presence of substantial amount of genomic resources. This study aimed to generate and characterize genomic resources using high throughput transcriptome sequencing for Pomacea canaliculata, a non-model gastropod indigenous to Argentina that has invaded Asia, Hawaii and southern United States. De novo assembly of the transcriptome resulted in 128,436 unigenes with an average length of 419 bp (range: 150 to 8,556 bp). Many of the unigenes (2,439) contained transposable elements, showing the existence of a source of genetic variability in response to stressful conditions. A total of 3,196 microsatellites were detected in the transcriptome; among 20 of the randomly tested microsatellites, 10 were validated to exhibit polymorphism. A total of 15,412 single-nucleotide polymorphisms (SNPs) were detected in the ORFs. LC-MS/MS analysis of the proteome of juveniles revealed 878 proteins, of which many are stress-related. This study has demonstrated the great potential of high throughput DNA sequencing for rapid development of genomic resources for a non-model organism. Such resources can facilitate various molecular ecological studies, such as stress physiology and range expansion.

Data from: Markov switching autoregressive models for interpreting vertical movement data with application to an endangered marine apex predator

1.Time series of animal movement obtained from bio-loggers are becoming widely used across all taxa. These data are nowadays of high quality, combining high resolution with precision, as the tags are able to collect for longer times and store larger quantities of data. Due to their nature, high-frequency data sequences often pose non-trivial problems in time series analysis: non-linearity, non-Normality, non-stationarity, and long memory. These issues can be tackled by modelling the data sequence as a realization of a stochastic regime switching process. 2. We suggest a novel Markov switching autoregressive model where the hidden Markov chain is non-homogeneous, with time-varying transition probabilities, whose dynamics depend on the dynamics of some contemporary categorical covariates. 3. To illustrate the use of the method, we apply it to the depth profiles of four individuals of flapper skate (Dipturus cf. intermedia) in order to identify swimming behaviours. Individual time series were obtained from data storage tags that recorded pressure every two minutes. The environmental covariates used were lunar phase (a proxy for the spring-neap tidal cycle), lunar cycle, and diel cycle. For all individuals two states (or regimes) were always selected (the autoregressive order was either three or four), representing different regimes of animal activity, i.e., state 1 for resting or horizontal swimming or slow vertical movement; state 2 for fast ascending and descending. The cycle of the four lunar phases was the only environmental covariate that explained the hidden state dynamics in all individuals, whereas lunar cycle was selected for two individuals and diel cycle for one only. 4. The method is an efficient approach to fit one-dimensional tag data using categorical environmental covariates, and to classify the observations into a small number of states representing individual behaviours of tagged individuals.

opencc-zeroDec 2016View details →

Data from: A two-state model of tree evolution and its applications to alu retrotransposition

Models of tree evolution have mostly focused on capturing the cladogenesis processes behind speciation. Processes that derive the evolution of genomic elements, such as repeats, are not necessarily captured by these existing models. In this paper, we design a model of tree evolution that we call the dual-birth model, and we show how it can be useful in studying the evolution of short Alu repeats found in the human genome in abundance. The dual-birth model extends the traditional birth-only model to have two rates of propagation, one for active nodes that propagate often, and another for inactive nodes, that with a lower rate, activate and start propagating. Adjusting the ratio of the rates controls the expected tree balance. We present several theoretical results under the dual-birth model, introduce parameter estimation techniques, and study the properties of the model in simulations. We then use the dual-birth model to estimate the number of active Alu elements and their rates of propagation and activation in the human genome based on a large phylogenetic tree that we build from close to one million Alu sequences.

Data from: A basin-scale application of environmental DNA assessment for rare endemic species and closely related exotic species in rivers: a case study of giant salamanders in Japan

1. To prevent the invasion of exotic species causing a decline in an endangered endemic species, it is important to determine the distribution of both species at an early stage, when the density of the exotic species is still low, and to manage the invasion immediately. However, distinguishing between closely related species is difficult because they share similar characteristics. 2. The identification of DNA fragments sampled from a body of water (environmental DNA) has become a popular technique for rapidly determining the distribution of a target species. In this study, we analysed environmental DNA in water samples from 37 sites across the Katsura River basin in Japan. We used TaqMan real-time PCR to distinguish the Japanese giant salamander Andrias japonicus from the closely related Chinese giant salamander Andrias davidianus, which is known to invade Japanese rivers and hybridize with the Japanese species. 3. In environmental samples, we detected mtDNA of the endemic species at 25 sites and mtDNA of the exotic species at nine sites. The DNA detection sites were concentrated in the upstream region. The exotic species DNA was found beyond the limits of an earlier capturing survey. 4. Synthesis and applications. Using environmental DNA to monitor the two salamander species requires less time and effort than traditional surveys, so a wide-ranging survey can be conducted rapidly. Our results showed that performing three environmental DNA surveys for each site between autumn and winter is desirable for giant salamanders. Further collection of environmental DNA, in combination with conventional population surveys, will provide valuable information that can help protect rare endemic species in a variety of aquatic ecosystems and can help monitor the invasion of exotic species.

opencc-zeroDec 2012View details →

Data from: DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet

Ecological understanding of the role of consumer-resource interactions in natural food webs is limited by the difficulty of accurately and efficiently determining the complex variety of food types animals have eaten in the field. We developed a method based on DNA metabarcoding multiplexing and next-generation sequencing to uncover different taxonomic groups of organisms from complex diet samples. We validated this approach on 91 faeces of a large omnivorous mammal, the brown bear, using DNA metabarcoding markers targeting the plant, vertebrate, and invertebrate components of the diet. We included internal controls in the experiments and performed PCR replication for accuracy validation in post-sequencing data analysis. Using our multiplexing strategy, we significantly simplified the experimental procedure and accurately and concurrently identified different prey DNA corresponding to the targeted taxonomic groups, with ≥60% of taxa of all diet components identified to genus/species level. The systematic application of internal controls and replication was a useful and simple way to evaluate the performance of our experimental procedure, standardize the selection of sequence filtering parameters for each marker data, and validate the accuracy of the results. Our general approach can be adapted to the analysis of dietary samples of various predator species in different ecosystems, for a number of conservation and ecological applications entailing large-scale population level diet assessment through cost effective screening of multiple DNA metabarcodes, and the detection of fine dietary variation among samples or individuals and of rare food items.

opencc-zeroDec 2016View details →

Data from: Applications of random forest feature selection for fine-scale genetic population assignment

Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest, and guided regularized random forest) compared with FST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP dataset for Atlantic salmon (Salmo salar) and a published SNP data set for Alaskan Chinook salmon (Oncorhynchus tshawytscha). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than FST-selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each dataset, respectively, a level of accuracy never reached for these species using FST-selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic datasets to improve assignment for management and conservation of exploited populations.

opencc-zeroDec 2013View details →

Data from: Application of ancient DNA to the reconstruction of past microbial assemblages and for the detection of toxic cyanobacteria in subtropical freshwater ecosystems

Ancient DNA (aDNA) analysis of lake sediments is a promising tool for detecting shifts in past microbial assemblages in response to changing environmental conditions. We examined sediment core samples from subtropical, freshwater Laguna Blanca (Uruguay), which has been severely affected by cultural eutrophication since 1960 and where cyanobacterial blooms, particularly those of the saxitoxin-producer Cylindrospermopsis raciborskii, have been reported since the 1990s. Samples corresponding to ~1846, 1852, 2000 and 2007 A.D. were selected to perform Denaturing Gradient Gel Electrophoresis (DGGE) analysis of the 16S-23S rRNA intergenic transcribed spacer (ribosomal ITS) to compare their prokaryotic assemblage composition. Each stratum showed different ITS patterns, but the composition of 21st Century samples was clearly different than those of mid-19th Century. This compositional change was correlated to shifts in sediment organic matter and chlorophyll a content, which were significantly higher in recent samples. The presence of saxitoxin-producing cyanobacteria was addressed by quantitative real time PCR of the sxtU gene involved in toxin biosynthesis. This gene was present only in recent samples, for which clone libraries and ITS sequencing indicated the presence of Cyanobacteria. Phylogenetic analyses identified C. raciborskii only in the 2000 sample, shortly after several years when blooms were recorded in the lake. These data suggest the utility of aDNA for the reconstruction of microbial assemblage shifts in subtropical lakes, at least on centennial scales. The application of aDNA analysis to genes involved in cyanotoxin synthesis extends the applicability of molecular techniques in paleolimnological studies to include key microbial community characteristics of great scientific and social interest.

Data from: A high density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour

High density SNP microarrays ('SNP chips') are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this paper we describe the development and application of a high density Affymetrix Axiom chip with around 500 000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation (CNVs). The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genome-wide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays, (ii) detecting SNPs by more than one pipeline, and in independent datasets, ensures a high proportion of working assays, (iii) allele frequency ascertainment bias is minimised by performing SNP discovery in individuals from multiple populations and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.

Data from: Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem

Premise of the study: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. Methods: Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in mid-spring and identified using microscopic methods and ITS2 metabarcoding. Results: Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. Discussion: For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.

Data from: Comparing convenience and probability sampling for urban ecology applications

1. Urban forest ecosystems confer multiple ecosystem services. There is thus a need to quantify ecological characteristics in terms of community structure and composition so that benefits can be better understood in ecosystem service models. Efficient sampling and monitoring methods are crucial in this process. 2. Full tree inventories are scarce due to time and financial constraints, thus a variety of sampling methods exist. Modern vegetation surveys increasingly use stratified-random plot-based sampling to reduce the bias associated with convenience sampling, even though the latter can save time and increase species richness scores. The urban landscape, with a high degree of conspecific clustering and high species diversity, provides a unique biogeographical case for comparing these two methodological approaches. 3. We use two spatially extensive convenience samples of the urban forest of Meran (Italy) and compare the community structure, tree characteristics and ecosystem service provision with 200 random circular plots. 4. The convenience sampling resulted in a higher species diversity, incorporating more rare species. This is a result of covering more area per unit sampling time. Pseudorandom sub-plots were compared to the random plots revealing similar Shannon diversity and sampling comparability indices. Measured tree variables (diameter at breast height, height, tree-crown width, height to crown base) were similar between the two methods, as were ecosystem service model outputs. 5. Synthesis and applications. The results suggest that convenience sampling may be a time and money saving alternative to random sampling as long as stratification by land-use type is incorporated into the design. The higher species richness can potentially improve the accuracy of urban ecological models, which rely on species-specific functional traits.