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Data from: Comparative proteomics of stenotopic caddisfly Crunoecia irrorata identifies acclimation strategies to warming
Species' ecological preferences are often deduced from habitat characteristics thought to represent more or less optimal conditions for physiological functioning. Evolution has led to stenotopic and eurytopic species, the former having decreased niche breadths and lower tolerances to environmental variability. Species inhabiting freshwater springs are often described as being stenotopic specialists, adapted to the stable thermal conditions found in these habitats. Whether due to past local adaptation these species have evolved or have lost intra-generational adaptive mechanisms to cope with increasing thermal variability has, to our knowledge, never been investigated. By studying how the proteome of a stenotopic species changes as a result of increasing temperatures we investigate if the absence or attenuation of molecular mechanisms is indicative of local adaptation to freshwater springs. An understanding of compensatory mechanisms is especially relevant as spring-specialists will experience thermal conditions beyond their physiological limits due to climate change. In this study, the stenotopic species Crunoecia irrorata (Trichoptera: Lepidostomatidae, Curtis 1834) was acclimated to 10, 15 and 20 °C for 168 h. We constructed a homology-based database, and via liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based shotgun proteomics identified 1358 proteins. Differentially abundant proteins and protein norms of reaction revealed candidate proteins and molecular mechanisms facilitating compensatory responses such as trehalose metabolism, tracheal system alteration, and heat shock protein regulation. A species-specific understanding of compensatory physiologies challenges the characterization of species as having narrow tolerances to environmental variability if that characterization is based on occurrences and habitat characteristics alone.
Data from: Genome-wide SNPs identify limits to connectivity in the extreme freshwater disperser, spangled perch Leiopotherapon unicolor (Terapontidae)
The utility of restriction-site associated DNA sequencing (RADseq) to resolve fine-scale population structure was tested on an abundant and vagile fish species in a tropical river. Australia's most widespread freshwater fish, the "extreme disperser" Leiopotherapon unicolor was sampled from six locations in an unregulated system, the Daly River in Australia's Northern Territory. Despite an expectation of high connectivity based on life history knowledge of this species derived from arid zone habitats, L. unicolor was not a panmictic population in the tropical lower Daly. Using ~14,000 polymorphic RADseq loci, we found a pattern of upstream versus downstream population subdivision and evidence for differentiation among tributary populations. The magnitude of population structure was low with narrow confidence intervals (global FST = 0.014; 95% CI = 0.012, 0.016). Confidence intervals around pairwise FST estimates were all non-zero and consistent with the results of clustering analyses. This population structure was not explained by spatially heterogeneous selection acting on a subset of loci, or by sampling groups of closely related individuals (average within-site relatedness ≈ 0). One implication of the low but significant structure observed in the tropics is the possibility that L. unicolor may exhibit contrasting patterns of migratory biology in tropical versus arid zone habitats. We conclude that the RADseq revolution holds promise for delineating subtle patterns of population subdivision in species characterized by high within-population variation and low among-population differentiation.
Data from: From fine-scale foraging to home ranges: a semi-variance approach to identifying movement modes across spatiotemporal scales
Understanding animal movement is a key challenge in ecology and conservation biology. Relocation data often represent a complex mixture of different movement behaviors, and reliably decomposing this mix into its component parts is an unresolved problem in movement ecology. Traditional approaches, such as composite random walk models, require that the timescales characterizing the movement are all similar to the usually arbitrary data-sampling rate. Movement behaviors such as long-distance searching and fine-scale foraging, however, are often intermixed but operate on vastly different spatial and temporal scales. An approach that integrates the full sweep of movement behaviors across scales is currently lacking. Here we show how the semivariance function (SVF) of a stochastic movement process can both identify multiple movement modes and solve the sampling rate problem. We express a broad range of continuous-space, continuous-time stochastic movement models in terms of their SVFs, connect them to relocation data via variogram regression, and compare them using standard model selection techniques. We illustrate our approach using Mongolian gazelle relocation data and show that gazelle movement is characterized by ballistic foraging movements on a 6-h timescale, fast diffusive searching with a 10-week timescale, and asymptotic diffusion over longer timescales.
Data from: RADcap: sequence capture of dual-digest RADseq libraries with identifiable duplicates and reduced missing data
Molecular ecologists seek to genotype hundreds to thousands of loci from hundreds to thousands of individuals at minimal cost per sample. Current methods, such as restriction site associated DNA sequencing (RADseq) and sequence capture, are constrained by costs associated with inefficient use of sequencing data and sample preparation. Here, we introduce RADcap, an approach that combines the major benefits of RADseq (low cost with specific start positions) with those of sequence capture (repeatable sequencing of specific loci) to significantly increase efficiency and reduce costs relative to current approaches. RADcap uses a new version of dual-digest RADseq (3RAD) to identify candidate SNP loci for capture bait design, and subsequently uses custom sequence capture baits to consistently enrich candidate SNP loci across many individuals. We combined this approach with a new library preparation method for identifying and removing PCR duplicates from 3RAD libraries, which allows researchers to process RADseq data using traditional pipelines, and we tested the RADcap method by genotyping sets of 96 to 384 Wisteria plants. Our results demonstrate that our RADcap method: (1) methodologically reduces (to <5%) and allows computational removal of PCR duplicate reads from data; (2) achieves 80-90% reads-on-target in 11 of 12 enrichments; (3) returns consistent coverage (≥4x) across >90% of individuals at up to 99.8% of the targeted loci; (4) produces consistently high occupancy matrices of genotypes across hundreds of individuals; and (5) costs significantly less than current approaches.
Data from: Identifying signatures of sexual selection using genomewide selection components analysis
Sexual selection must affect the genome for it to have an evolutionary impact, yet signatures of selection remain elusive. Here we use an individual-based model to investigate the utility of genome-wide selection components analysis, which compares allele frequencies of individuals at different life history stages within a single population to detect selection without requiring a priori knowledge of traits under selection. We modeled a diploid, sexually reproducing population and introduced strong mate choice on a quantitative trait to simulate sexual selection. Genome-wide allele frequencies in adults and offspring were compared using weighted FST values. The average number of outlier peaks (i.e., those with significantly large FST values) with a quantitative trait locus in close proximity ("real" peaks) represented correct diagnoses of loci under selection, whereas peaks above the FST significance threshold without a quantitative trait locus reflected spurious peaks. We found that, even with moderate sample sizes, signatures of strong sexual selection were detectable, but larger sample sizes improved detection rates. The model was better able to detect selection with more neutral markers, and when quantitative trait loci and neutral markers were distributed across multiple chromosomes. Although environmental variation decreased detection rates, the identification of real peaks nevertheless remained feasible. We also found that detection rates can be improved by sampling multiple populations experiencing similar selection regimes. In short, genome-wide selection components analysis is a challenging but feasible approach for the identification of regions of the genome under selection.
Data from: Identifying the critical climatic time window that affects trait expression
Identifying the critical time window during which climatic drivers affect the expression of phenological, behavioral, and demographic traits is crucial for predicting the impact of climate change on trait and population dynamics. Two widely used associative methods exist to identify critical climatic periods: sliding-window models and recursive operators in which the memory of past weather fades over time. Both approaches have different strong points, which we combine here into a single method. Our method uses flexible functions to differentially weight past weather, which can reflect competing hypotheses about time lags and the relative importance of recent and past weather for trait expression. Using a 22-year data set, we illustrate that the climatic window identified by our new method explains more of the phenological variation in a sexually selected trait than existing approaches. Our new method thus helps to better identify the critical time window and the causes of trait response to environmental variability.
Data from: Identifying loci under selection against gene flow in isolation with migration models
When divergence occurs in the presence of gene flow, there can arise an interesting dynamic in which selection against gene flow, at sites associated with population-specific adaptations or genetic incompatibilities, can cause net gene flow to vary across the genome. Loci linked to sites under selection may experience reduced gene flow and may experience genetic bottlenecks by the action of nearby selective sweeps. Data from histories such as these may be poorly fitted by conventional neutral model approaches to demographic inference, which treat all loci as equally subject to forces of genetic drift and gene flow. To allow for demographic inference in the face of such histories, as well as the identification of loci affected by selection, we developed an isolation-with-migration model that explicitly provides for variation among genomic regions in migration rates and/or rates of genetic drift. The method allows for loci to fall into any of multiple groups, each characterized by a different set of parameters, thus relaxing the assumption that all loci share the same demography. By grouping loci, the method can be applied to data with multiple loci and still have tractable dimensionality and statistical power. We studied the performance of the method using simulated data, and we applied the method to study the divergence of two subspecies of European rabbits (Oryctolagus cuniculus).
Data from: Development of a simple, practice-based tool to assess quality of paediatric emergency care delivery in resource-limited settings: identifying critical actions via a Delphi study
Objective: Provision of timely, high-quality care for the initial management of critically ill children in African hospitals remains a challenge. Monitoring the completion of critical actions during resuscitations can inform efforts to reduce variability and improve outcomes. We sought to develop a practice-based tool based on contextually relevant actions identified via a Delphi process. Our goal was to develop a tool that could identify gaps in care, facilitate identification of training and standardized assessment to support quality improvement efforts. Design: Six sentinel conditions were selected based on disease epidemiology and mortality at rural and urban African emergency departments. Potential critical actions were identified through focused literature review. These actions were evaluated within a three-round modified Delphi process. A set of logistical filters was applied to the candidate list to derive a practice-based tool. Setting and participants: Attendees at an international emergency medicine conference comprised an expert panel of 25 participants, with 84% working primarily in African settings. Consensus rounds allowing novel responses were conducted via online and in-person surveys. Results: The expert panel generated 199 actions that apply to six conditions in emergently ill children. Application of appropriateness criteria refined this to 92 candidate actions across seven categories: core skills, active seizure, altered mental status, diarrheal illness, febrile illness, respiratory distress, polytrauma. From these, we identified 28 actions for inclusion in a practice-based tool contextually relevant to the initial management of critically ill children in Africa. Conclusions: A group consensus process identified critical actions for severely ill children with select sentinel conditions in emergency paediatric care in an African setting. Absence of these actions during resuscitation might reflect modifiable gaps in quality of care. The resulting practice-based tool is context-relevant and can serve as a foundation for training and quality improvement efforts in African hospitals and emergency departments.
Data from: From success to persistence: Identifying an evolutionary regime shift in the diverse Paleozoic aquatic arthropod group Eurypterida, driven by the Devonian biotic crisis
Mass extinctions have altered the trajectory of evolution a number of times over the Phanerozoic. During these periods of biotic upheaval a different selective regime appears to operate, although it is still unclear whether consistent survivorship rules apply across different extinction events. We compare variations in diversity and disparity across the evolutionary history of a major Paleozoic arthropod group, the Eurypterida. Using these data, we explore the group's transition from a successful, dynamic clade to a stagnant persistent lineage, pinpointing the Devonian as the period during which this evolutionary regime shift occurred. The late Devonian biotic crisis is potentially unique among the 'Big Five' mass extinctions in exhibiting a drop in speciation rates rather than an increase in extinction. Our study reveals eurypterids show depressed speciation rates throughout the Devonian but no abnormal peaks in extinction. Loss of morphospace occupation is random across all Paleozoic extinction events; however, differential origination during the Devonian results in a migration and subsequent stagnation of occupied morphospace. This shift appears linked to an ecological transition from euryhaline taxa to freshwater species with low morphological diversity alongside a decrease in endemism. These results demonstrate the importance of the Devonian biotic crisis in reshaping Paleozoic ecosystems.
Data from: Identifying management actions to increase foraging opportunities for shorebirds at semi-intensive shrimp farms
The expansion of aquaculture has resulted in widespread habitat conversion throughout the world. Identifying beneficial management measures may dramatically reduce negative impacts of aquaculture for migratory birds. We studied how densities of foraging shorebirds varied at ponds within a semi-intensive shrimp aquaculture farm on the north-western coast of Mexico, as related to timing of harvest and tidal cycles. Further, we estimated the total daily available area for each shorebird species throughout two entire harvesting seasons at the shrimp farm. High densities (average ca. 50 individuals per ha) of foraging shorebirds were found during the first days following pond harvest. The most abundant species were Willet Tringa semipalmata and Black-necked Stilt Himantopus mexicanus, followed by Marbled Godwit Limosa fedoa and American Avocet Recurvirostra americana. Other regular, but less abundant, species were whimbrel Numenius phaeopus and dowitchers Limnodromus spp. Densities of shorebirds sharply declined daily following harvest. In addition, the time-window availability of harvested ponds was related to each species' foraging behaviour: <2 days for godwits and dowitchers, 4 days for stilts, 5 days for willets and more than a week for avocets and whimbrels. However, birds continued to use harvested ponds that received a low, but continuous water influx. Our results demonstrate that a tropical shrimp farm represents a patchy environment that provides 4·3–12·7% (depending on species) of its total area as foraging opportunities for shorebirds. Synthesis and applications. Sequential harvesting of shrimp aquaculture farm ponds and increasing moisture of the substrate by providing some water supply to harvested ponds, at least throughout the harvesting period, could integrate shorebird conservation into shrimp-farm production. These low-cost and easy management procedures would not increase costs or affect shrimp production – thus representing a win-win opportunity – and would have potential applications for shorebird conservation throughout the world.
Data from: Return of a giant: DNA from archival museum samples helps to identify a unique cutthroat trout lineage formerly thought to be extinct
Currently one small, native population of the culturally and ecologically important Lahontan cutthroat trout (Oncorhynchus clarkii henshawi, LCT, Federally listed) remains in the Truckee River watershed of northwestern Nevada and northeastern California. The majority of populations in this watershed were extirpated in the 1940's due to invasive species, overharvest, anthropogenic water consumption and changing precipitation regimes. In 1977, a population of cutthroat trout discovered in the Pilot Peak Mountains in the Bonneville basin of Utah, was putatively identified as the extirpated LCT lacustrine lineage native to Pyramid Lake in the Truckee River basin based upon morphological and meristic characters. Our phylogenetic and Bayesian genotype clustering analyses of museum specimens collected from the large lakes (1872-1913) and contemporary samples collected from populations throughout the extant range provide evidence in support of a genetically distinct Truckee River basin origin for this population. Analysis of museum samples alone identified three distinct genotype clusters and historical connectivity among water bodies within the Truckee River basin. Baseline data from museum collections indicate that the extant Pilot Peak strain represents a remnant of the extirpated lacustrine lineage. Given the limitations on high quality data when working with a sparse number of preserved museum samples, we acknowledge that, in the end, this may be a more complicated story. However, the paucity of remnant populations in the Truckee River watershed in combination with data on the distribution of morphological, meristic and genetic data for Lahontan cutthroat trout, suggest that recovery strategies, particularly in the large lacustrine habitats should consider this lineage as an important part of the genetic legacy of this species.
Data from: A taxonomic revision of the African genus Desplatsia Bocq. (Malvaceae - Grewioideae) with identifiers
<p>A taxonomic revision of <i>Desplatsia</i> Bocq. (Malvaceae s.l., subfamily Grewioideae, tribe Grewieae) based on 810 herbarium specimens is presented. <i>Desplatsia</i> is a genus of trees and shrubs found in tropical West and Central Africa and is characterised by subulately divided stipules, the absence of an androgynophore, stamens that are fused to a tube at the base, and large and distinctive fruits that are dispersed by elephants. Four species are recognized (<i>D. subericarpa</i>, <i>D. chrysochlamys</i>, <i>D. dewevrei</i> and <i>D. mildbraedii</i>) and 12 species names are placed into synonymy, two of which have been put into synonymy for the first time: <i>D. floribunda</i> and <i>D. trillesiana</i>. All four species are locally abundant and their conservation status is assessed as Least Concern (LC). A key to the species, full species descriptions, illustrations, a specimen citation list and distribution maps are provided.</p>
Data from: Forensic genomics as a novel tool for identifying the causes of mass mortality events
Toxic spills, hypoxia, disease outbreaks and toxin-producing algal blooms are all possible causes of mass mortality events, but in many cases it can be difficult to pinpoint the cause of death. Here we present a new approach that we name 'forensic genomics', combining field surveys, toxin testing and genomic scans. Forensic genomics queries allele frequencies of surviving animals for signatures of agents causing mass mortality and, where genetic diversity is high, is uniquely suited to identify natural selection in action. As a proof of concept, we use this approach to investigate the causes of an invertebrate mass mortality event, and its genetic effects on an abalone population. Our results support that a harmful algal bloom producing a yessotoxin was a major causative agent to the event.
Data from: Community trees: identifying codiversification in the páramo dipteran community
Groups of codistributed species that responded in a concerted manner to environmental events are expected to share patterns of evolutionary diversification. However, the identification of such groups has largely been based on qualitative, post hoc analyses. We develop here two methods (PPS, K-F ANOVA) for the analysis of codistributed species that, given a group of species with a shared pattern of diversification, allow empiricists to identify those taxa that do not codiversify (i.e., "outlier" species). The identification of outlier species makes it possible to jointly estimate the evolutionary history of co-diversifying taxa. To evaluate the approaches presented here, we collected data from Páramo dipterans, identified outlier species, and estimated a "community tree" from species that are identified as having co-diversified. Our results demonstrate that dipteran communities from different Páramo habitats in the same mountain range are more closely related than communities in other ranges. We also conduct simulation testing to evaluate this approach. Results suggest that our approach provides a useful addition to comparative phylogeographic methods, while identifying aspects of the analysis that require careful interpretation. In particular, both the PPS and K-F ANOVA perform acceptably when there are one or two outlier species, but less so as the number of outliers increase. This is likely a function of the corresponding degradation of the signal of community divergence; without a strong signal from a co-diversifying community, there is no dominant pattern from which to detect and outlier species. For this reason, both the magnitude of K-F distance distribution and outside knowledge about the phylogeographic history of each putative member of the community should be considered when interpreting results.
Data from: Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants
Correlations among plant traits often reflect important trade‐offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to "spectra" or "leading dimensions," whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the "leaf economics spectrum," "biomass allocation dimension," "seed dimension," and carbon and nitrogen concentrations. This literature‐based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature‐based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below‐ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem‐specific length were "hub" traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature‐based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a "size" module, a "seed" module, two modules representing C and N concentrations in plant organs, and a "partitioning" module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole‐plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.
Replication Package: Towards Using Package Centrality Trend to Identify Packages in Decline
<p>Due to its increasing complexity, today’s software systems are frequently built by leveraging reusable code in the form of libraries and packages. Software ecosystems (e.g., npm) are the primary enablers of this code reuse, providing developers with a platform to share their own and use others’ code. These ecosystems evolve rapidly: developers add new packages every day to solve new problems or provide alternative solutions, causing obsolete packages to decline in their importance to the community. Developers should avoid depending on packages in decline, as these packages are reused less over time and may become less frequently maintained. However, current popularity metrics are not fit to provide this information to developers.</p> <p>In this paper, we propose a scalable approach that uses the package’s centrality in the ecosystem to identify packages in decline. We evaluate our approach with the npm ecosystem and show that the trends of centrality over time can correctly distinguish packages in decline with an ROC-AUC of 0.9. The approach can capture 87% of the packages in decline, on average 18 months before the trend is shown in currently used package popularity metrics. We implement this approach in a tool that can be used to augment npms metrics and help developers avoid packages in decline when reusing packages from npm.</p>
Data from: Integrated genome-scale analysis identifies novel genes and networks underlying senescence in maize
Premature senescence in annual crops reduces yield while delayed senescence, termed stay-green, is known to impose both positive and negative impact on yield and nutrition quality. Despite the importance, scant information is available on the genetic architecture of senescence in maize (Zea mays L.) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and co-expression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by GWAS, and 14 of these are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a co-expression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding cysteine protease in stay-green in Arabidopsis (Arabidopsis thaliana), and analysis of natural alleles suggest a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals.
Data from: Riverscape genetics identifies replicated ecological divergence across an Amazonian ecotone
Ecological speciation involves the evolution of reproductive isolation and niche divergence in the absence of a physical barrier to gene flow. The process is one of the most controversial topics of the speciation debate, particularly in tropical regions. Here, we investigate ecologically based divergence across an Amazonian ecotone in the electric fish, Steatogenys elegans. We combine phylogenetics, genome scans, and population genetics with a recently developed individual-based evolutionary landscape genetics approach that incorporates selection. This framework is used to assess the relative contributions of geography and divergent natural selection between environments as biodiversity drivers. We report on two closely related and sympatric lineages that exemplify how divergent selection across a major Amazonian aquatic ecotone (i.e., between rivers with markedly different hydrochemical properties) may result in replicated ecologically mediated speciation. The results link selection across an ecological gradient with reproductive isolation and we propose that assortative mating based on water color may be driving the divergence. Divergence resulting from ecologically driven selection highlights the importance of considering environmental heterogeneity in studies of speciation in tropical regions. Furthermore, we show that framing ecological speciation in a spatially explicit evolutionary landscape genetics framework provides an important first step in exploring a wide range of the potential effects of spatial dependence in natural selection.
Data from: Identifying drivers of breeding success in a long-distance migrant using structural equation modelling
In migrant animals, conditions encountered at various times and places throughout their annual cycle may affect breeding success. Yet, most studies so far have only investigated the effect of specific parts of the annual cycle, despite the importance to understand how different stages can interact and how these stages compare to intrinsic quality to properly modulate breeding success. Using a structural equation modelling approach, we investigated drivers of breeding success (migration cycle, individual quality, breeding conditions) in hoopoes (Upupa epops), a long-distant migrant. Our causal framework explained 75% of the variation in breeding success. The effect of the migration schedule was negligible, whereas the previous breeding attempt strongly influenced current breeding success. We suggest that the interplay of individual quality and environmental conditions during both previous and current breeding season may be more important drivers of breeding success than migration schedules, even in a long-distance migrant. We conclude that structural equation modeling is a promising tool to investigate causal relationships. Applied to hoopoes, we demonstrated that current breeding success is strongly linked to previous breeding success. Complementary analysis integrating weather and climate conditions during migration and the breeding season may provide a deeper and wider overview of the annual cycle of hoopoes and additional insights into the existence of carry-over effects in breeding success.
Data from: Identifying future zoonotic disease threats: where are the gaps in our understanding of primate infectious diseases?
Background and objectives: Emerging infectious diseases often originate in wildlife, making it important to identify infectious agents in wild populations. It is widely acknowledged that wild animals are incompletely sampled for infectious agents, especially in developing countries, but it is unclear how much more sampling is needed, and where that effort should focus in terms of host species and geographic locations. Here we identify these gaps in primate parasites, many of which have already emerged as threats to human health. Methodology: We obtained primate host-parasite records and other variables from existing databases. We then investigated sampling effort within primates relative to their geographic range size, and within countries relative to their primate species richness. We used generalized linear models, controlling for phylogenetic or spatial autocorrelation, to model variation in sampling effort across primates and countries. Finally, we used species richness estimators to extrapolate parasite species richness. Results: We found uneven sampling effort within all primate groups and continents. Sampling effort among primates was influenced by their geographic range size and substrate use, with terrestrial species receiving more sampling. Our parasite species richness estimates suggested that, among the best-sampled primates and countries, almost half of primate parasites remain to be sampled; for most primate hosts, the situation is much worse. Conclusions and implications: Sampling effort for primate parasites is uneven and low. The sobering message is that we know little about even the best studied primates, and even less regarding the spatial and temporal distribution of parasitism within species.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.