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403 results for “Occurrence Data”
Data from: Biological invasion modifies the co-occurrence patterns of insects along a stress gradient
Biological invasions have become one of the most important drivers of biodiversity loss and ecosystem change world-wide. However, it is still unclear how invasions may interact with local abiotic stressors, which are expected to increase as global change intensifies. Furthermore, we know little about the response to biological invasions of insects, despite their disproportionate contribution to global animal biodiversity. The aim of the present work is to investigate the impact of an invasive aquatic insect on the co-occurrence patterns of native species of insects along a salinity gradient, and determine which assembly rules are driving these patterns. First, we characterised the habitat specialisation and functional niches of each species from physiological and biological traits, respectively, and their degree of overlap. Second, we used field data to compare the co-occurrence patterns of native and invasive species in invaded and non-invaded areas of southern Iberia and northern Morocco. Finally, we tested if habitat filtering or niche differentiation assembly rules mediate their co-occurrence. In non-invaded areas, habitat filtering drives habitat segregation of species along the salinity gradient, with a lower contribution of niche differentiation. The presence of the invasive insect modifies the distribution and co-occurrence patterns of native species. In invaded areas, niche differentiation seems to be the main mechanism to avoid competition among the invasive and native species, enabling coexistence and resource partitioning. The combined study of functional niche similarity and abiotic stressor tolerance of invasive and native species can improve our understanding of the effects of invasive species along abiotic stress gradients. This approach may increase our capacity to predict the outcomes of biological invasion in a global change context.
Data from: Evolutionary relatedness does not predict competition and co-occurrence in natural or experimental communities of green algae
The competition-relatedness hypothesis (CRH) predicts that the strength of competition is the strongest among closely related species and decreases as species become less related. This hypothesis is based on the assumption that common ancestry causes close relatives to share biological traits that lead to greater ecological similarity. Although intuitively appealing, the extent to which phylogeny can predict competition and co-occurrence among species has only recently been rigorously tested, with mixed results. When studies have failed to support the CRH, critics have pointed out at least three limitations: (i) the use of data poor phylogenies that provide inaccurate estimates of species relatedness, (ii) the use of inappropriate statistical models that fail to detect relationships between relatedness and species interactions amidst nonlinearities and heteroskedastic variances, and (iii) overly simplified laboratory conditions that fail to allow eco-evolutionary relationships to emerge. Here, we address these limitations and find they do not explain why evolutionary relatedness fails to predict the strength of species interactions or probabilities of coexistence among freshwater green algae. First, we construct a new data-rich, transcriptome-based phylogeny of common freshwater green algae that are commonly cultured and used for laboratory experiments. Using this new phylogeny, we re-analyse ecological data from three previously published laboratory experiments. After accounting for the possibility of nonlinearities and heterogeneity of variances across levels of relatedness, we find no relationship between phylogenetic distance and ecological traits. In addition, we show that communities of North American green algae are randomly composed with respect to their evolutionary relationships in 99% of 1077 lakes spanning the continental United States. Together, these analyses result in one of the most comprehensive case studies of how evolutionary history influences species interactions and community assembly in both natural and experimental systems. Our results challenge the generality of the CRH and suggest it may be time to re-evaluate the validity and assumptions of this hypothesis.
Data from: Co-occurrence and hybridization of anther-smut pathogens specialized on Dianthus hosts
Host specialization has important consequences for the diversification and ecological interactions of obligate pathogens. The anther-smut disease of natural plant populations, caused by Microbotryum fungi, has been characterized by specialized host-pathogen interactions, which contribute in part to the isolation among these numerous fungal species. This study investigated the molecular variation of Microbotryum pathogens within the geographic and host-specific distributions on wild Dianthus species in southern European Alps. In contrast to prior studies on this pathogen genus, a range of overlapping host specificities was observed for four delineated Microbotryum lineages on Dianthus hosts, and their frequent co-occurrence within single-host populations was quantified at local and regional scales. In addition to potential consequences for direct pathogen competition, the sympatry of Microbotryum lineages led to hybridization between them in many populations, and these admixed genotypes suffered significant meiotic sterility. Therefore, this investigation of the anther-smut fungi reveals how variation in the degrees of host specificity can have major implications for ecological interactions and genetic integrity of differentiated pathogen lineages.
Data from: Survey completeness of a global citizen-science database of bird occurrence
<p>Measuring the completeness of survey inventories created by citizen-science initiatives can identify the strengths and shortfalls in our knowledge of where species occur geographically. Here, we use occurrence information from eBird to measure the survey completeness of the world's birds in this database at three temporal resolutions and four spatial resolutions across the annual cycle during the period 2002 to 2018. Approximately 84% of the earth's terrestrial surface contained bird occurrence information with the greatest concentrations occurring in North America, Europe, India, Australia, and New Zealand. The largest regions with low levels of survey completeness were located in central South America, northern and central Africa, and northern Asia. Across spatial and temporal resolutions, survey completeness in regions with occurrence information was 55–74% on average, with the highest values occurring at coarser temporal and coarser spatial resolutions and during spring migration within temperate and boreal regions. Across spatial and temporal resolutions, survey completeness exceeded 90% within <i>ca</i>. 4–14% of the earth's terrestrial surface. Survey completeness increased globally from 2002 to 2018 across all months of the year at a rate of <i>ca</i>. 3% per year. The slowest gains occurred in Africa and in montane regions, and the most rapid gains occurred in India and in tropical forests after 2012. Thus, occurrence information from a global citizen-science program for a charismatic and well-studied taxon was geographically broad but contained heterogeneous patterns of survey completeness that were strongly influenced by temporal and especially spatial resolution. Our results identify regions where the application of additional effort would address current knowledge shortfalls, and regions where the maintenance of existing effort would benefit long-term monitoring efforts. Our findings highlight the potential of citizen science initiatives to further our knowledge of where species occur across space and time, information whose applications under global change will likely increase.</p>
Data from: Disentangling biotic interactions, environmental filters, and dispersal limitation as drivers of species co-occurrence
A key focus in ecology is to search for community assembly rules. Here we compare two community modelling frameworks that integrate a combination of environmental and spatial data to identify positive and negative species associations from presence-absence matrices, and incorporate an additional comparison using joint species distribution models (JSDM). The frameworks use a dichotomous logic tree that distinguishes dispersal limitation, environmental requirements, and interspecific interactions as causes of segregated or aggregated species pairs. The first framework is based on a classical null model analysis complemented by tests of spatial arrangement and environmental characteristics of the sites occupied by the members of each species pair (Classic framework). The second framework, (SDM framework) implemented here for the first time, builds on the application of environmentally-constrained null models (or JSDMs) to partial out the influence of the environment, and includes an analysis of the geographical configuration of species ranges to account for dispersal effects. We applied these approaches to examine plot-level species co-occurrence in plant communities sampled along a wide elevation gradient in the Swiss Alps. According to the frameworks, the majority of species pairs were randomly associated, and most of the non-random positive and negative species associations could be attributed to environmental filtering and/or dispersal limitation. These patterns were partly detected also with JSDM. Biotic interactions were detected more frequently in the SDM framework, and by JSDM, than in the Classic framework. All approaches detected species aggregation more often than segregation, perhaps reflecting the important role of facilitation in stressful high-elevation environments. Differences between the frameworks may reflect the explicit incorporation of elevational segregation in the SDM framework and the sensitivity of JSDM to the environmental data. Nevertheless, all methods have the potential to reveal general patterns of species co-occurrence for different taxa, spatial scales, and environmental conditions.
Data from: Fine scale spatial variability in the influence of environmental cycles on the occurrence of dolphins at coastal sites
Environmental cycles often influence the presence of animals, creating patterns at different temporal scales, which may mean that their effects overlap and/or interact. Interactions between diel and seasonal cycles have been reported to influence fish behaviour but little is known about such interactions in marine top predators. Here, we studied the combined effect of seasonal, tidal and diel cycles on the occurrence of bottlenose dolphins (Tursiops truncatus) within a Marine Protected Area in Scotland. Our analyses were based on echolocation detections from passive acoustic devices (CPODs) deployed at three coastal sites between 2010 and 2016. We described patterns of dolphins' occurrence using circular statistics and then used generalised additive mixed models to explore the relative importance of each cycle and any interactions between them. We found site-specific cyclical patterns of presence that remained constant across years. There was a highly significant interaction between seasonal and diel cycles at two sites around deep channels, where occurrence was diurnal in summer but became nocturnal in autumn. The study demonstrates the highly plastic behaviour of bottlenose dolphins and shows a previously unreported behaviour that has management implications for this and other marine protected areas.
Data from: Optimising trait and source selection for explaining occurrence and abundance changes: a case study using British Butterflies
Functional traits that define the ecological role of an organism are increasingly being used to determine and predict responses to environmental change. Functional trait analyses of butterflies remain underexplored compared with other taxa, such as plants. Previous works using butterfly functional traits have not comprehensively addressed issues about the quality of trait data sets used and the relative predictive power of different trait types. We compare the consistency of trait descriptions between six widely used trait sources for the British butterfly fauna. We analysed consistency of trait sources using Fleiss's kappa and ICC. PCA was used to produce species ordinations, comparing outputs to examine which trait sets were better at explaining recent species range and abundance changes within the UK. There was a large range in congruence values for specific traits between sources. No single source can be relied upon to produce accurate trait information for British butterflies. Most trait sets are poor predictors of abundance and occurrence changes but are better at predicting current occurrence. An extensive trait set, supplementing biotope-related traits with explicit resource-based information recovers more informative ecological classifications and models than those primarily based on life-history traits or biotope descriptors. Smaller trait sets do, however, recover the specialist-generalist continuum. We conclude that analyses of distribution and abundance changes that rely on traits are highly dependent on trait source and trait type. For butterflies, traits that are based on measures of biotope occupancy should be avoided in explaining changes of abundance and distribution. Including trait information that describes their resource requirements is essential for such analyses.
Data from: A native parasitic plant and soil microorganisms facilitate a native plant co-occurrence with an invasive plant
Invasive plants often interact with antagonists that include native parasitic plants and pathogenic soil microbes, which may reduce fitness of the invaders. However, to date, most of the studies on the ecological consequences of antagonistic interactions between invasive plants and the resident biota focused only on pairwise interactions. A full understanding of invasion dynamics requires studies that test the effects of multiple antagonists on fitness of invasive plants and co-occurring native plants. Here, we used an invasive plant Mikania micrantha, a co-occurring native plant Coix lacryma-jobi, and a native holoparasitic plant Cuscuta campestris to test whether parasitism on M. micrantha interacts with soil fungi and bacteria to reduce fitness of the invader and promote growth of the co-occurring native plant. In a factorial set up, M. micrantha and C. lacryma-jobi were grown together in pots in the presence versus absence of parasitism on M. micrantha by C. campestris, and in the presence versus absence of full complements of soil bacteria and fungi. Fungicide and bactericide were used to suppress soil fungi and bacteria, respectively. Findings show that heavy parasitism by C. campestris caused the greatest reduction in M. micrantha biomass when soil fungi and bacteria were suppressed. In contrast, the co-occurring native plant C. lacryma-jobi experienced the greatest increase in biomass when grown with heavily parasitized M. micrantha and in the presence of a full complement of soil fungi and bacteria. Taken together, our results suggest that selective parasitism on susceptible invasive plants by native parasitic plants and soil microorganisms may diminish competitive ability of invasive plants and facilitate native plant co-existence with invasive plants.
Data from: Edaphic factors determining the occurrence of herbaceous legumes in Amazonian savannas
Edaphic factors have been indicated as a determinant of the distribution of plant communities in Amazonia. The aim of this study was to detect which edaphic factors determine the occurrence of herbaceous legumes in Amazonian savannas. Therefore, an inventory of herbaceous flora of the family Leguminosae was conducted in 34 permanent plots established in two savanna areas of Roraima, northern Brazilian Amazon. The importance value index was higher for Chamaecrista desvauxii (24.9%), Aeschynomene hystrix (15.7%) and Galactia jussiaeana (10.8%), all having high abundance and wide distribution. The results indicated low density or absence of individuals and species in plots established on poorly drained soils (hydromorphic). Diversity and species richness tended to be higher in habitats formed on well drained soils, greater fertility and lower concentrations of exchangeable aluminum. It is suggested that poor and seasonally flooded soils tend to reduce the chances of occurrence of herbaceous legumes in savanna areas of Roraima, adversely affecting its richness/diversity.
Data from: Occurrence and phylogenetic analysis of bovine respiratory syncytial virus in outbreaks of respiratory disease in Norway
Background: Bovine respiratory syncytial virus (BRSV) is one of the major pathogens involved in the bovine respiratory disease (BRD) complex. The seroprevalence to BRSV in Norwegian cattle herds is high, but its role in epidemics of respiratory disease is unclear. The aims of the study were to investigate the etiological role of BRSV and other respiratory viruses in epidemics of BRD and to perform phylogenetic analysis of Norwegian BRSV strains. Results: BRSV infection was detected either serologically and/or virologically in 18 (86%) of 21 outbreaks and in most cases as a single viral agent. When serology indicated that bovine coronavirus and/or bovine parainfluenza virus 3 were present, the number of BRSV positive animals in the herd was always higher, supporting the view of BRSV as the main pathogen. Sequencing of the G gene of BRSV positive samples showed that the current circulating Norwegian BRSVs belong to genetic subgroup II, along with other North European isolates. One isolate from an outbreak in Norway in 1976 was also investigated. This strain formed a separate branch in subgroup II, clearly different from the current Scandinavian sequences. The currently circulating BRSV could be divided into two different strains that were present in the same geographical area at the same time. The sequence variations between the two strains were in an antigenic important part of the G protein. Conclusion: The results demonstrated that BRSV is the most important etiological agent of epidemics of BRD in Norway and that it often acts as the only viral agent. The phylogenetic analysis of the Norwegian strains of BRSV and several previously published isolates supported the theory of geographical and temporal clustering of BRSV.
Data from: Plant-mycorrhizal fungus co-occurrence network lacks substantial structure
The interactions between plants and arbuscular mycorrhizal fungi (AMF) maintain a crucial link between macroscopic organisms and the soil microbial world. These interactions are of extreme importance for the diversity of plant communities and ecosystem functioning. Despite this importance, only recently has the structure of plant–AMF interaction networks been studied. These recent studies, which used genetic data, suggest that these networks are highly structured, very similar to plant–animal mutualistic networks. However, the assembly process of plant–AMF communities is still largely unknown, and an important feature of plant–AMF interactions has not been incorporated: they occur at an extremely localized scale. Studying plant–AMF networks in a spatial context seems therefore a crucial step. This paper studies a plant–AMF spatial co-occurrence network using novel methodology based on information theory and a unique set of spatially explicit species-level data. We apply three null models of which only one accounts for spatial effects. We find that the data show substantial departures from null expectations for the two non-spatial null models. However, for the null model considering spatial effects, there are few significant co-occurrences compared with the other two null models. Thus, plant–AMF spatial co-occurrences seem to be mostly explained by stochasticity, with a small role for other factors related to plant–AMF specialization. Furthermore, we find that the network is not significantly nested or modular. We conclude that this plant–AMF spatial co-occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem more important in the first step of the assembly of plant–AMF communities.
Data from: Dynamic species co-occurrence networks require dynamic biodiversity surrogates
In conservation it is inevitable that surrogates be selected to represent the occurrence of hard–to–find species and find priority locations for management. However, species co–occurrence can vary over time. Here we demonstrate how temporal dynamics in species co–occurrence influence the ability of managers to choose the best surrogate species. We develop an efficient optimisation formulation that selects the optimal set of complementary surrogate species from any co–occurrence network. We apply it to two Australian datasets on successional bird responses to disturbances of revegetation and fire. We discover that a surprisingly small number of species are required to represent the majority of species co–occurrences at any one time. Because co–occurrence patterns are temporally dynamic, the optimal set of surrogates, and the number of surrogates required to achieve a desired surrogacy power, depend on sampling effort and the successional state of a system. Overlap in optimal sets of surrogates for representing 70% of co–occurring species ranges from zero to 57% depending on when the surrogacy decision is made. Surrogate sets representing early successional communities over–estimate the power of surrogacy decisions at later times. Our results show that in dynamic systems, optimal surrogates might be selected in different ways: (1) use short–term monitoring to choose a larger number of static less–informative surrogates; (2) use long–term monitoring to choose a smaller number of static high–power surrogates that may poorly represent early successional co–occurrence; (3) develop adaptive surrogate selection frameworks with high short–term and long–term surrogacy power that update surrogate sets and capture temporal dynamics in species co–occurrence. Our results suggest vigilance is needed when selecting surrogates for other co–occurring species in dynamic landscapes, as selected surrogates from one time may have reduced effectiveness at a different time. Ultimately, decisions that fail to acknowledge dynamic species co–occurrence will lead to uninformative or redundant surrogates.
Data from: Fine scale waterbody data improve prediction of waterbird occurrence despite coarse species data
While modelling habitat suitability and species distribution, ecologists must deal with issues related to the spatial resolution of species occurrence and environmental data. Indeed, given that the spatial resolution of species and environmental datasets range from centimeters to hundreds of kilometers, it underlines the importance of choosing the optimal combination of resolutions to achieve the highest possible modelling prediction accuracy. We evaluated how the spatial resolution of land cover/waterbody datasets (meters to 1 km) affect waterbird habitat suitability models based on atlas data (grid cell of 12×11 km). We hypothesized that the area, perimeter and number of waterbodies computed from high resolution datasets would explain distributions of waterbirds better because coarse resolution datasets omit small waterbodies affecting species occurrence. Specifically, we investigated which spatial resolution of waterbodies better explain the distribution of seven waterbirds nesting on ponds/lakes with areas ranging from 0.1 ha to hundreds of hectares. Our results show that the area and perimeter of waterbodies derived from high resolution datasets (raster data with 30 m resolution, vector data corresponding with map scale 1:10,000) explain the distribution of the waterbirds better than those calculated using less accurate datasets despite the coarse grain of the species data. Taking into account the spatial extent (global vs regional) of the datasets, we found the Global Inland Waterbody Dataset to be the most suitable for modelling distribution of waterbirds. In general, we recommend using land cover data of a resolution sufficient to capture the smallest patches of the habitat suitable for a given species' presence for both fine and coarse grain habitat suitability and distribution modelling.
Data from: Community-wide changes in inter-taxonomic temporal co-occurrence resulting from phenological shifts
Global climate change is known to affect the assembly of ecological communities by altering species' spatial distribution patterns, but little is known about how climate change may affect community assembly by changing species' temporal co-occurrence patterns, which is highly likely given the widely observed phenological shifts associated with climate change. Here we analyzed a 29-year phenological data set comprising community-level information on the timing and span of temporal occurrence in 11 seasonally occurring animal taxon groups from 329 local meteorological observatories across China. We show that widespread shifts in phenology have resulted in community-wide changes in the temporal overlap between taxa that are dominated by extensions, and that these changes are largely due to taxa's altered span of temporal occurrence rather than the degree of synchrony in phenological shifts. Importantly, our findings also suggest that climate change may have led to less phenological mismatch than generally presumed, and that the context under which to discuss the ecological consequences of phenological shifts should be expanded beyond asynchronous shifts.
Data from: On the occurrence of three non-native cichlid species including the first record of a feral population of Pelmatolapia (Tilapia) mariae (Boulenger, 1899) in Europe
Thermally influenced freshwater systems provide suitable conditions for non-native species of tropical and subtropical origin to survive and form proliferating populations beyond their native ranges. In Germany, non-native convict cichlids (Amatitlania nigrofasciata) and tilapia (Oreochromis sp.) have established populations in the Gillbach, a small stream that receives warm water discharge from a local power plant. Here, we report on the discovery of spotted tilapia (Pelmatolapia mariae) in the Gillbach, the first record of a reproducing population of this species in Europe. It has been hypothesized that Oreochromis sp. in the Gillbach are descendants of aquaculture escapees and our mtDNA analysis found both O. mossambicus and O. niloticus maternal lineages, which are commonly used for hybrids in aquaculture. Convict cichlids and spotted tilapia were most probably introduced into the Gillbach by aquarium hobbyists. Despite their high invasiveness worldwide, we argue that all three cichlid species are unlikely to spread and persist permanently beyond the thermally influenced range of the Gillbach river system. However, convict cichlids from the Gillbach are known to host both native and non-native fish parasites and thus, non-native cichlids may constitute threats to the native fish fauna. We therefore strongly recommend continuous monitoring of the Gillbach and similar systems.
Data from: Wolbachia-induced meiotic drive and feminization is associated with an independent occurrence of selective mitochondrial sweep in a butterfly
Maternally inherited Wolbachia endosymbionts manipulate arthropod reproduction in various ways. In the butterfly Eurema mandarina, a cytoplasmic incompatibility-inducing Wolbachia strain wCI and the associated mtDNA haplotypes are known to originate from the sister species Eurema hecabe, which offered a good case study for microbe-mediated hybrid introgression. Besides wCI, some females with the Z0 karyotype harbour a distinct Wolbachia strain wFem, which causes all-female production by meiotic drive and feminization. We report that a considerable proportion of E. mandarina females (65.7%) were infected with both wCI and wFem (CF) on Tanegashima Island. While females singly infected with wCI (C) produced offspring at a 1 : 1 sex ratio, CF females produced only females. Although Z-linked sequence polymorphism showed no signs of divergence between C and CF females, mtDNA split into two discrete clades; one consisted of C females and the other CF females, both of which formed a clade with E. hecabe but not with uninfected E. mandarina. This suggests that CF matrilines also, but independently, experienced a selective sweep after hybrid introgression from E. hecabe. Distinct evolutionary forces were suggested to have caused C and CF matrilines to diverge, which would be irreversible because of the particular phenotype of wFem.
Data from: Wind farms affect the occurrence, abundance and population trends of small passerine birds: the case of the Dupont's lark
1.The assessment of the effects of wind farms on bird populations is commonly based on collision fatality records. This could undervalue the effect of wind farms on small-sized birds. We evaluate the effect of wind turbines on occurrence, abundance and population trends of a threatened small passerine species, the Dupont's lark Chersophilus duponti. To our knowledge, this is one of the first studies addressing the effect of wind farms on population trends using time series data from multiple wind farms. 2.We estimated population trends by fitting a switching linear trend model with the software TRIM (Trend & Indices for Monitoring data). We used multiannual data surveys of five populations in the presence of wind farms and nine in their absence (2008–2016 period). Furthermore, we fitted a logistic and a negative binomial regression model to test the effect of wind farm proximity on species occurrence and abundance in 2016, respectively. We incorporated local connectivity and habitat availability estimates in both models as predictors. 3.Results showed a negative trend overall, but that was significantly more regressive in the presence of wind farms: 21.0% versus 5.8% average annual decline in the absence of wind farms. 4.Dupont's lark occurrence and abundance in 2016 were negatively affected by measures of population isolation and positively affected by the distance to wind farms. 5.These results highlight the negative effect of isolation and wind farm proximity on Dupont's lark population parameters. Taking into account the metapopulation structure exhibited by the species in the study area, this work established a 4.5 km threshold distance from wind farms, beyond which Dupont's lark populations should be unaffected. 6.Synthesis and applications. This work highlights the negative impact of wind farms on small-sized birds and provides a 4.5 km threshold distance that should be taken into account in the design of future wind energy projects. Moreover, we suggest an analytical approach based on population trends, species abundance and occurrence variation in relation to wind farms, useful for the assessment of wind farm impacts on small-sized birds.
Data from: Seasonal dynamics and co-occurrence patterns of honey bee pathogens revealed by high-throughput RT-qPCR analysis
The health of the honey bee Apis mellifera is challenged by introduced parasites that interact with its inherent pathogens and cause elevated rates of colony losses. To elucidate co-occurrence, population dynamics and synergistic interactions of honey bee pathogens, we established an array of diagnostic assays for a high-throughput qPCR platform. Assuming that interaction of pathogens requires co-occurrence within the same individual, single worker bees were analyzed instead of collective samples. Eleven viruses, four parasites and three pathogenic bacteria were quantified in more than one thousand single bees sampled from sixteen disease-free apiaries in Southwest Germany. The most abundant viruses were Black Queen Cell Virus (84%), Lake Sinai Virus 1 (42%), and Deformed Wing Virus B (35%). Forager bees from asymptomatic colonies were infected with two different viruses in average, and simultaneous infection with four to six viruses was common (14%). Also the intestinal parasites Nosema ceranae (96%) and Crithidia mellificae/Lotmaria passim (52%) occurred very frequently. These results indicate that low-level infections in honey bees are more common than previously assumed. All viruses showed seasonal variation, while N. ceranae did not. The foulbrood bacteria Paenibacillus larvae and Melissococcus plutonius were regionally distributed. Spearman's correlations and multiple regression analysis indicated possible synergistic interactions between the common pathogens, particularly for Black Queen Cell Virus. Beyond its suitability for further studies on honey bees, this targeted approach may be, due to its precision, capacity and flexibility, a viable alternative to more expensive, sequencing-based approaches in non-model systems.
FIGURES 15–26. 15–19, Pagodula concepcionensis n in New data on recently described Chilean trophonines (Gastropoda: Muricidae), description of a new species and notes of their occurrence at a cold seep site
FIGURES 15–26. 15–19, Pagodula concepcionensis n.sp.; 15–16, Chile, off Concepción, 36°21.75'S, 73°43.55'W, 726–865m, holotype MNHNCL201648, 19mm; 17–18, Chile, off Concepción, 36°21.46'S, 73°44.08'W, 930m, paratype IRSNB IG 30559/565, 19.5mm; 19, Protoconch (holotype) Scale bar 0.5mm; 20–21, Pagodula cf. concepcionensis; Chile, off Concepción, 36°21.46'S, 73°44.08'W, 930m, RH, 21.13mm; 22–24, Trophon veronicae Pastorino, 1999, off southern Chile, 46°00'S, 83°59'W, 742m, holotype USNM 880195, 52.2mm (photo courtesy G. Pastorino). Scale bar: 200µm; 25, Protoconch of Pagodula aculeata (Watson, 1882) (RH). Scale bar: 0.5mm; 26, Protoconch of P. verrillii (Bush, 1893) (RH). Scale bar: 0.5mm.
FIGURES 36–37. 36 in New data on recently described Chilean trophonines (Gastropoda: Muricidae), description of a new species and notes of their occurrence at a cold seep site
FIGURES 36–37. 36, Radula of Boreotrophon cepula (Sowerby, 1880), Kuriles Islands (scale bar: 10µm); 37, Radula of Pagodula aculeata (Watson, 1883), Brazil (scale bar: 10µm).
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.