Find research datasets worth reusing

Fig. 2 in New sibling species and new occurrences of squat lobsters (Crustacea, Decapoda) from the western Indian Ocean

Fig. 2. Munida austrina sp. nov., holotype, ♀, 4.6 mm (MNHN-IU-2014-13478), Mozambique. A. Carapace and abdomen, dorsal view. B. Sternal plastron. C. Cephalic region, showing antennular and antennal peduncles, ventral view. D. Right Mxp3, lateral view. E. Right P1, dorsal view. F. Right P2, lateral view. G. Dactylus of right P2, lateral view. H. Right P3, lateral view. I. Right P4, lateral view. Scale bar: A, E–F, H–I = 1.0 mm; B–D, G = 0.5 mm.

Fig. 1 in New sibling species and new occurrences of squat lobsters (Crustacea, Decapoda) from the western Indian Ocean

Fig. 1. Eumunida spiridonovi sp. nov., holotype, ♀, 11.0 mm (MNHN-IU-2016-8715), East of Somalia. A. Carapace, dorsal view. B. Abdomen, dorsal view. C. Sternal plastron, sternites 3 and 4. D. Left antenna and antennula, ventral view. E. Right Mxp3. F. Right P1 merus, dorsal view. G. Right P1 carpus and distal part of merus, ventral view. H. Right P1 palm and fingers, dorsal view. I. Right P1 distal part of palm and fingers, ventral view. J. Right P2. Scale bar: A–C, G, I–J = 2.0 mm; D–E = 1 m; F, H = 0.5 mm.

Fig. 7 in New sibling species and new occurrences of squat lobsters (Crustacea, Decapoda) from the western Indian Ocean

Fig. 7. Munida micra sp. nov., holotype, ♂, 3.7 mm (MNHN-IU-2008-10229), Mozambique. A. Carapace and abdomen, dorsal view. B. Sternal plastron. C. Cephalic region, showing antennular and antennal peduncles, ventral view. D. Right Mxp3, lateral view. E. Left P1, dorsal view. F. Left P2, lateral view. G. Dactylus of left P2, lateral view. H. Left P3, lateral view. I. Right P4, lateral view. Scale bar: A–B, E–F, H–I = 1.0 mm; C–D, G = 0.5 mm.

Fig. 3 in New sibling species and new occurrences of squat lobsters (Crustacea, Decapoda) from the western Indian Ocean

Fig. 3. Munida cristulata sp. nov., holotype, ♂, 6.1 mm (MNHN-IU-2014-13480), Glorieuses Islands, N of Mayotte Island. A. Carapace and abdomen, dorsal view. B. Sternal plastron. C. Cephalic region, showing antennular and antennal peduncles, ventral view. D. Right Mxp3, lateral view. E. Right P1, dorsal view. F. Right P2, lateral view. G. Right P3, lateral view. H. Right P4, lateral view. Scale bar: A–B, E–H = 1.0 mm; C–D = 0.5 mm.

Fig. 6 in New sibling species and new occurrences of squat lobsters (Crustacea, Decapoda) from the western Indian Ocean

Fig. 6. Munida mesembria sp. nov., holotype, ♂, 7.7 mm (MNHN-IU-2014-13477), Mozambique. A. Carapace and abdomen, dorsal view. B. Sternal plastron. C. Cephalic region, showing antennular and antennal peduncles, ventral view. D. Right Mxp3, lateral view. E. Right P1, dorsal view. F. Right P2, lateral view. G. Dactylus of right P2, lateral view. H. Left P3, lateral view. I. Right P4, lateral view. Scale bar: A, E–F, H–I = 2.0 mm; B–D, G = 1.0 mm.

Fig. 9 in New sibling species and new occurrences of squat lobsters (Crustacea, Decapoda) from the western Indian Ocean

Fig. 9. Munida tetracantha sp. nov., holotype, ♂, 6.6 mm (MNHN-IU-2014-13474), Madagascar. A. Carapace and abdomen, dorsal view. B. Sternal plastron. C. Cephalic region, showing antennular and antennal peduncles, ventral view. D. Right Mxp3, lateral view. E. Right P1, dorsal view. F. Right P2, lateral view. G. Dactylus of right P2, lateral view. H. Right P4, lateral view. Scale bar: A, E–F, H = 2.0 mm; B–D, G = 1.0 mm.

opencc-zeroJun 2020View details →

Species occurrence and occupancy in protected areas of the Natura2000 network in Belgium

Context Invasive alien species have been pointed out as an important driver of biodiversity loss. Many policy responses are being developed to address this threat. Protected areas often represent and preserve hotspots of biological diversity and ensure the maintenance of ecosystem services crucial to human livelihoods. The impact of biological invasions can be particularly severe in protected areas and their occurrence and impact in such areas is an important element of the risk they pose. To address this, there is a need for data on the occurrence and extent of alien species invasions in protected areas. Description This dataset contains species occurrence and occupancy in protected areas of the Natura2000 network in Belgium (Special Conservation Areas sensu Habitat Directive and Special Protection Areas sensu Bird Directive). The dataset was generated using the <a href="https://doi.org/10.5281/zenodo.3637911">Belgian occurrence cube at species level</a> and the <a href="https://doi.org/10.5281/zenodo.3635510">Belgian occurrence cube for non-native taxa</a> (both containing GBIF data aggregated using Oldoni et al. 2020), the 1x1km <a href="https://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2">EEA reference grid</a> and the <a href="https://www.eea.europa.eu/data-and-maps/data/natura-11/natura-2000-spatial-data/natura-2000-shapefile-1">Natura2000 protected areas shapefiles</a> from the European Environment Agency. Data are grouped by protected area (<code>SITECODE</code>), year (<code>year</code>) and (infra)species (<code>taxonKey</code>, <code>speciesKey</code>). For each group, it provides the number of occurrences found in GBIF (<code>n</code>), the area of occupancy (<code>aoo</code>: number of 1 km2 squares), the coverage (<code>coverage</code>: % of 1 km2 squares), the minimum <a href="http://rs.tdwg.org/dwc/terms/coordinateUncertaintyInMeters">coordinateUncertaintyInMeters</a> (<code>min_coord_uncertainty</code>), and the alien status (<code>is_alien</code>) based on the <a href="https://doi.org/10.15468/xoidmd">Global Register of Introduced and Invasive Species - Belgium</a>. For infraspecific taxa in the latter, the <a href="https://github.com/trias-project/indicators/blob/00e1ae72df3fb98b2a215c3af8769e53fbcd0182/reference/species_of_infraspecific_alien_taxa.tsv">alien status of the species</a> is looked up and included. The dataset is built on open science principles and intended to be completely reproducible: <ul> <li>The input data are publicly available on Zenodo, with the download DOIs listed in the related identifiers of this dataset package.</li> <li>The <a href="https://trias-project.github.io/indicators/10_species_observations_occupancy_in_protected_areas.html">code</a> to process the data is publicly available and documented on GitHub.</li> </ul> Files <ul> <li>protected_areas_species_occurrence.csv: number of occurrences (<code>n</code>), area of occupancy (<code>aoo</code>) and <code>coverage</code> of taxa (<code>taxonKey</code>) in Natura2000 areas of Belgium (<code>SITECODE</code>). Other columns included: <code>speciesKey</code> (for species is <code>speciesKey</code> = <code>taxonKey</code>), <code>SITETYPE</code> containing the site type of the Natura2000 area (one of <code>A</code>, <code>B</code> or <code>C</code>), <code>min_coord_uncertainty</code> with the lowest coordinate uncertainty in meters, <code>is_alien</code> containing the alien status (<code>TRUE</code> or <code>FALSE</code>) and <code>remarks</code> containing, if present, the infraspecific alien taxa whose occurrences contribute to the calculated <code>aoo</code> (only for species).</li> <li>protected_areas_species_info.csv: taxonomic information of taxa in <code>protected_areas_species_occurrence.csv</code> as retrieved from <a href="https://www.gbif.org/dataset/d7dddbf4-2cf0-4f39-9b2a-bb099caae36c">GBIF Backbone Taxonomy</a>. Columns: <code>taxonKey</code>, <code>speciesKey</code>, <code>scientificName</code>, <code>kingdom</code>, <code>phylum</code>, <code>order</code>, <code>class</code>, <code>genus</code>, <code>family</code>, <code>species</code>, <code>rank</code> and <code>includes</code>. The latter contains the infraspecific taxa and synonyms whose occurrences contribute to the number of occurrences at species level.</li> <li>protected_areas_metadata.csv: protected area information for areas included in <code>protected_areas_species_occurrence.csv</code>. Columns: <code>SITECODE</code> as in <code>protected_areas_species_occurrence.csv</code> (<code>BE*******</code>), <code>SITENAME</code> containing the name of the protected area, <code>SITETYPE</code> as in <code>protected_areas_species_occurrence.csv</code>, <code>flanders</code>, <code>wallonia</code> and <code>brussels</code> containing whether the area is situated respectively in Flanders, Wallonia or Brussels-Capital Region (<code>TRUE</code> or <code>FALSE</code>). Field codes are in line with <a href="https://www.eea.europa.eu/data-and-maps/data/natura-11/natura-2000-tabular-data-12-tables">EEA element definitions</a> for Natura 2000 sites.</li> </ul> Potential use of the dataset Currently, there is no comprehensive reporting system for invasive alien species in Natura 2000 sites. This dataset provides a baseline as to which species occur in which protected area. We envisage this dataset can be an interesting starting point for various types of analyses on alien species in protected areas in Belgium, but that it can also be used in complement to other data on alien species in protected areas to study more general patterns. Some examples of research questions: <ul> <li>Which protected areas are most invaded by alien species</li> <li>Which alien species are most distributed in protected areas and which traits do they have</li> <li>How does the proportion of alien species in protected areas change in time</li> <li>How does the occurrence/occupancy of alien species in protected areas match lists of regulated species (e.g. Union List, EPPO lists)</li> <li>To what extent can the network of protected areas contribute to providing safe refuge to native species from the impacts of invasive alien species</li> <li>How widespread are the impacts of certain alien species on protected areas</li> </ul> <h2>Acknowledgements</h2> This work has been funded under the Belgian Science Policies Brain program (BelSPO BR/165/A1/TrIAS), the European Union's LIFE program (LIFE19 NAT/BE/000953 - LIFE RIPARIAS).

opencc-by-4.0Nov 2020View details →

Data and code for the manuscript: "Varying richness need not imply non-random species co-occurrence: implications for specifying null models"

Data and R code for the manuscript "Varying richness need not imply non-random species co-occurrence: implications for specifying null models".

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SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes

The accurate quantification of eukaryotic species abundances from bulk samples remains a key challenge for community ecology and environmental biomonitoring. We resolve this challenge by combining shotgun sequencing, mapping to reference DNA barcodes or to mitogenomes, and three correction factors: (a) a percent‐coverage threshold to filter out false positives, (b) an internal‐standard DNA spike‐in to correct for stochasticity during sequencing, and (c) technical replicates to correct for stochasticity across sequencing runs. The SPIKEPIPE pipeline achieves a strikingly high accuracy of intraspecific abundance estimates (in terms of DNA mass) from samples of known composition (mapping to barcodes R2 = .93, mitogenomes R2 = .95) and a high repeatability across environmental‐sample replicates (barcodes R2 = .94, mitogenomes R2 = .93). As proof of concept, we sequence arthropod samples from the High Arctic, systematically collected over 17 years, detecting changes in species richness, species‐specific abundances, and phenology. SPIKEPIPE provides cost‐efficient and reliable quantification of eukaryotic communities.

opencc-zeroAug 2019View details →

opencc-by-4.0Aug 2017View details →

Species co-occurrences from EuPMC articles related to pines

A dataset containing info on matches from full text searches by ContentMine tools, that can be mapped to Wikidata. See README.md.

Fig.ç4.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, leg 2, dorsal view; B, leg 3, dorsal view; C, leg 4, dorsal view; D, leg 5, ventral view. Scale bars: 0.1 mm. in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species

Fig.ç4.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, leg 2, dorsal view; B, leg 3, dorsal view; C, leg 4, dorsal view; D, leg 5, ventral view. Scale bars: 0.1 mm.

Fig.ç3.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, maxilla, dorsal view; B, maxilliped, dorsal view; C, sternal furca, dorsal view; D, leg 1, ventral view; E, exopod of leg 1 enlarged, ventral view. Scale bars: 0.1 mm. in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species

Fig.ç3.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, maxilla, dorsal view; B, maxilliped, dorsal view; C, sternal furca, dorsal view; D, leg 1, ventral view; E, exopod of leg 1 enlarged, ventral view. Scale bars: 0.1 mm.

Fig.ç2.A, Caligus latigenitalis Shiino, 1954, male (KMNH IvR 500, 510), habitus, dorsal view; B–F. Caligus longiramus sp. nov., holotype, female (KMNH IvR 500, 511): B, habitus, dorsal view; C, caudal rami, dorsal view; D, antennule, ventral view; E, antenna, postantennal process, and maxillule, ventral view; F, mandible. Scale bars: 1 mm (A, B); 0.1 mm (C–F). in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species

Fig.ç2.A, Caligus latigenitalis Shiino, 1954, male (KMNH IvR 500, 510), habitus, dorsal view; B–F. Caligus longiramus sp. nov., holotype, female (KMNH IvR 500, 511): B, habitus, dorsal view; C, caudal rami, dorsal view; D, antennule, ventral view; E, antenna, postantennal process, and maxillule, ventral view; F, mandible. Scale bars: 1 mm (A, B); 0.1 mm (C–F).

Fig.ç1.C ollection sites of pelagic caligids including 3 stations in Japanese waters (St. 2–4, 2010) and 1 station in the Gulf of ffiailand (St. 1, 2006). in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species

Fig.ç1.C ollection sites of pelagic caligids including 3 stations in Japanese waters (St. 2–4, 2010) and 1 station in the Gulf of ffiailand (St. 1, 2006).

opencc-zeroNov 2023View details →

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Data from: Integrated species distribution models to account for sampling biases and improve range wide occurrence predictions

Aim Species distribution models (SDMs) that integrate presence-only and presence-absence data offer a promising avenue to improve information on species' geographic distributions. The use of such 'integrated SDMs' on a species range-wide extent has been constrained by the often-limited presence-absence data and by the heterogeneous sampling of the presence-only data. Here, we evaluate integrated SDMs for studying species ranges with a novel expert range map-based evaluation. We build a new understanding about how integrated SDMs address issues of estimation accuracy and data deficiency and thereby offer advantages over traditional SDMs. Location South and Central America. Time period 1979-2017. Major taxa studied Hummingbirds. Methods We build integrated SDMs by linking two observation models – one for each data type – to the same underlying spatial process. We validate SDMs with two schemes: i) cross-validation with presence-absence data and ii) comparison with respect to the species' whole range as defined with IUCN range maps. We also compare models relative to the estimated response curves and compute the association between the benefit of the data integration and the number of presence records in each data set. Results The integrated SDM accounting for the spatially varying sampling intensity of the presence-only data was one of the top-performing models in both model validation schemes. Presence-only data alleviated overly large niche estimates, and data integration was beneficial compared to modelling solely presence-only data for species that had few presence points when predicting the species' whole range. On the community level, integrated models improved the species richness prediction. Main conclusions Integrated SDMs combining presence-only and presence-absence data are successfully able to borrow strengths from both data types and offer improved predictions of species' ranges. Integrated SDMs can potentially alleviate the impacts of taxonomically and geographically uneven sampling and to leverage the detailed sampling information in presence-absence data.

opencc-by-4.0Jan 2023View details →

Figure 1 in The first occurrence of the subgenus Premicrodispus (Premicrodispulus) (Acari: Heterostigmata: Microdispidae) from Russia, with description of a new species

Figure 1. Premicrodispus (Premicrodispulus) kurganiensis sp. nov. (female) – A. Dorsum of body; B. Venter of body. Legs omitted.

opencc-by-4.0Jan 2023View details →

Figure 3 in The first occurrence of the subgenus Premicrodispus (Premicrodispulus) (Acari: Heterostigmata: Microdispidae) from Russia, with description of a new species

Figure 3. DIC micrographs of Premicrodispus (Premicrodispulus) kurganiensis sp. nov. (female) – A. Dorsum of body; B. Venter of body.

opencc-by-4.0Jan 2023View details →

Figure 2 in The first occurrence of the subgenus Premicrodispus (Premicrodispulus) (Acari: Heterostigmata: Microdispidae) from Russia, with description of a new species

Figure 2. Premicrodispus (Premicrodispulus) kurganiensis sp. nov. (female) – A–D. Left legs I-IV, respectively, dorsal aspect.

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Costa Rica mosquito community species occurrence and site environmental data, July - August 2017

Land use change is an important driver of both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting biodiversity, public health, and livelihoods in working landscapes requires understanding the spatial scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. A growing body of evidence shows that species richness for many taxa correlates with tree cover at small spatial scales of <100 m, indicating that local tree cover management is a promising conservation tool. To investigate whether mosquito species richness, community composition, and presence of specific disease vector species respond to tree cover—and if so, whether at spatial scales similar to other taxa—we surveyed mosquito communities along a tree cover gradient and across agricultural, residential, and forested land uses in rural southern Costa Rica. We found that tree cover was both positively correlated with mosquito species richness and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus, particularly at small spatial scales of 80 – 200m. Beyond tree cover, land use type predicted community composition and Ae. albopictus presence, but not species richness. The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa and also confer protection against disease vector occurrence.

opencc-zeroDec 2023View details →