Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
134
datasets available to search
ShareScore release 0.9.0
Dataset results
134 results for “Yucatan Peninsula”
Ecological Impacts of Hurricanes Across the Yucatan Peninsula 1851-2000
This study used computer modeling to study the impacts of hurricanes across the Yucatan Peninsula since 1851. For details on methods and results please see the published paper (Boose, E. R., D. R. Foster, A. Barker Plotkin and B. Hall. 2003. Geographical and historical variation in hurricanes across the Yucatan Peninsula. In Lowland Maya Area: Three Millennia at the Human-Wildland Interface. A. Gomez-Pompa, M. F. Allen, S. Fedick and J. J. Jimenez-Osornio, eds. Haworth Press, New York, NY. In press). The Abstract from the paper is reproduced below. "The ecological impacts of hurricanes across the Yucatan Peninsula over the last 150 years were investigated using a simple meteorological model (HURRECON) developed at Harvard Forest as well as a database of historical hurricane data (HURDAT) maintained by the U. S. National Hurricane Center. All hurricanes over the period 1851-2000 with sustained winds of hurricane force (33 meters/sec) within 300 kilometers of the study region were analyzed (n = 105). Each storm was reconstructed to produce estimates of wind damage on the Fujita scale across the region. Individual reconstructions were then compiled to study cumulative impacts of all 105 storms. "Results showed considerable variation in hurricane activity from year to year, and from decade to decade, while at the half-century scale there was an increase in hurricane intensity since the mid-nineteenth century. Ninety percent of the hurricanes causing F1 damage or higher (on the Fujita scale) occurred in the months of August, September, and October. A strong spatial gradient in hurricane frequency and intensity extended across the region from northeast to southwest, resulting from (1) the greater number of hurricanes to the north, (2) the east to west movement of most hurricanes across the area, and (3) the tendency for most hurricanes to weaken significantly after landfall. For example, during the study period, northeastern parts of the peninsula experienced a minimum of
Assessment of vulnerability to climate change of coastal communities in the Gulf of California and the Yucatan Peninsula: vulnerability outputs
<p>The dataset includes the outputs of the project: "Assessment of vulnerability to climate change of coastal communities in the Gulf of California and the Yucatan Peninsula: vulnerability outputs" funded by the David and Lucille Packard Foundation and awarded to H. Reyes-Bonilla (UABCS). </p> <p>This study analyzed vulnerability of fisheries-dependent coastal communities based on three components: a) adaptive capacity (84 indicators), which reflect the ability of a community to respond and recover after adverse events; b) susceptibility (11 indicators) which was determined based on fishing dependence; and c) exposure (31 indicators) that was evaluated with current environmental data. Future vulnerability was determined for a 2050 horizon and based on two climate change scenarios: SSP126, which represents low emissions, and SSP585, which takes into consideration that the amount of greenhouse gases will continue to increase. These data come from the Coupled Model Intercomparison Project 6 (CMIP6), which serves as the basis for the 6th IPCC report. We evaluated vulnerability using indicators what were available at the local scale.</p>
Fig. 2 in Fish functional groups in a tropical wetland of the Yucatan Peninsula, Mexico
Fig. 2. Cluster analyses of the functional traits data. Dendrograms show groups for food acquisition (A, B, C, and D) and locomotion (E, F, G, and H). Species identities (IDs) correspond to the first letter of the genus and species names.
Fig. 3 in Fish diet composition in permanent and semi-permanent pools in tropical wetlands of the Yucatan Peninsula
Fig. 3. Percentage composition of main items consumed by fish in Permanent (A) and Semi-permanent (B) pools in BPR during the dry (black bars) and rainy season (dash bars) of 2010. FR = fish remains, TI = terrestrial invertebrates, AI = aquatic insects, PR = plant remains, CR = crustaceans (mainly amphipods), AR = arachnid, AL = algae, GA = gastropod and DE = detritus.
Fig. 2 in Fish diet composition in permanent and semi-permanent pools in tropical wetlands of the Yucatan Peninsula
Fig. 2. Fish feeding spectrum of aquatic insects and terrestrial invertebrates (proportions of different orders in the diet of all stomachs analyzed) between Permanent (A) and Semi-permanent (B) pools in the PBR during 2010. Species codes: Aa = Astyanax aeneus, Cu = Cichlasoma urophthalmus, Tm = Thorichthys meeki, Gy = Gambusia yucatana, Pv = Poecilia velifera, Pm = P. mexicana, Bb = Belonesox belizanus, Ro = Rocio octofasciata, Cs = Cichlasoma urophthalmus, Ps = Petenia splendida, On = Oreochromis niloticus, Pm = Paraneetroplus melanurus, Gp = Garmanella pulchra.
Fig. 1 in Fish diet composition in permanent and semi-permanent pools in tropical wetlands of the Yucatan Peninsula
Fig. 1. Geographic location of studied pools, permanent and semi-permanent in PBR, Campeche, Mexico during 2010.
Fig. 6 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 6. Phylogenetic tree based on the Maximum Likelihood analysis of the species of the Order Onchoproteocephalidea found in Octopus maya constructed on partial large subunit ribosomal gene (28S) (likelihood = – 9067.566753). Bootstrap support values for ML are provided at the nodes; ex = host; the stage of development of the cestode in parentheses.
Fig. 4 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 4. Phylogenetic tree based on the Maximum Likelihood (ML) analysis of the species of the Order Trypanorhyncha found in Octopus maya constructed on partial large subunit ribosomal gene (28S) (likelihood = – 15209.189111). Bootstrap support values for ML are provided at the nodes; ex = host; the stage of development of the cestode in parentheses.
Fig. 3 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 3. Scanning electron microscopy of whole specimens and the detail of scolecis of the cestodes found as parasites of Octopus maya. Trypanorhyncha (A–L): A-C Eutetrarhynchus sp.; D-F Kotorella pronosoma; G-I Nybelinia sp.; J-L Prochristianella sp. Onchoproteocephalidea (M–R): M-N Acanthobothrium sp. O–P Phoreiobothrium sp.; Q-R Prosobothrium sp.
Fig. 2 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 2. Schematic drawings and photographs of the stained specimens of cestode parasitizing Octopus maya. Trypanorhyncha (A–D): A- Eutetrarhynchus sp.; B. Kotorella pronosoma; C- Nybelinia sp.; D- Prochristianella sp. Onchoproteocephalidea (E–G): E- Acanthobothrium sp.; F- Phoreiobothrium sp.; G- Prosobothrium sp.- Abbreviations: as = apical sucker; bot = bothridia cc = calcareous corpuscles; lo = loculi; pb = pars bulbosa; pbo = pars bothrialis; ppb = pars postbulbosa; ps = pedunculus scolecis; pv = pars vaginalis; sc = scolex; sp = septa; st = strobilo; vel = velum.
Fig. 5 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 5. Phylogenetic tree based on the Maximum Likelihood analysis of the species of the Order Trypanorhyncha found in Octopus maya constructed on partial small subunit ribosomal gene (18S) (likelihood = – 7987.787948). Bootstrap support values for ML are provided at the nodes; ex = host; the stage of development of the cestode in parentheses.
Linked collectors and determiners for: Coleccion Regional de Moluscos de la Peninsula de Yucatan.
Natural history specimen data linked to collectors and determiners held within, "Coleccion Regional de Moluscos de la Peninsula de Yucatan". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/4900fa23-93ef-41ae-80bb-e58119b7ba0d">https://bionomia.net/dataset/4900fa23-93ef-41ae-80bb-e58119b7ba0d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/4900fa23-93ef-41ae-80bb-e58119b7ba0d">https://gbif.org/dataset/4900fa23-93ef-41ae-80bb-e58119b7ba0d</a>. Formatted as a Frictionless Data package.
Fig. 3 in Fish functional groups in a tropical wetland of the Yucatan Peninsula, Mexico
Fig. 3. Relative biomass abundance of functional groups among habitats and seasons.
Fig. 1 in Fish functional groups in a tropical wetland of the Yucatan Peninsula, Mexico
Fig. 1. Geographic location of the study site (white star) in Sian Ka'an Biosphere Reserve, Mexico.
Fig. 1 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 1. Sampling localities where specimens of Octopus maya were collected in Yucatan, Mexico.
FIGURE 3 in Updated checklist and identification key of benthic tanaidaceans (Crustacea Peracarida) of the sublittoral zone of the northern Yucatan Peninsula, Mexico
FIGURE 3. Tanaidaceans species of the sublittoral zone of the northern Yucatan Peninsula, suborder Apseudomorpha. (A) Mesokalliapseudes macsweenyi ♂; (B) M. macsweenyi ♀; (C) Psammokalliapseudes granulosus ♂; (D) P. granulosus ♀; (E) Calozodion wadei ♂; (F) C. wadei ♀; (G) Pagurotanais largoensis ♂; (H) Shells that P. largoensis inhabits: upper left, Eulithidium affine; upper right, Zebina browniana; lower left, Cerithium eburneum; lower right, Stellatoma stellata.
FIGURE 2 in Updated checklist and identification key of benthic tanaidaceans (Crustacea Peracarida) of the sublittoral zone of the northern Yucatan Peninsula, Mexico
FIGURE 2. Diversity, abundance, and distribution of tanaidaceans of the sublittoral zone of the northern Yucatan Peninsula.
FIGURE 11. A–D, Cypretta campechensis n in On three new species of Cypretta Vávra, 1895 (Crustacea: Ostracoda) from the Yucatan Peninsula, Mexico
FIGURE 11. A–D, Cypretta campechensis n. sp. SEM. Female. A, ventral view; B, RV external view; C, LV internal view. D, detail of nodes on postero-ventral inner calcified lamella. E–H, Cypretta spinosa n. sp. Female. E, Ventral view; F, LV External view; G, RV internal view; H, Detail of hinge.
FIGURE 10. Cypretta maya n in On three new species of Cypretta Vávra, 1895 (Crustacea: Ostracoda) from the Yucatan Peninsula, Mexico
FIGURE 10. Cypretta maya n. sp. A–F, Holotype female. A, mandible and mandibular palp; B, T1; C,T2; D, T3; E, UR; F, attachment of UR.
FIGURE 9. Cypretta maya n in On three new species of Cypretta Vávra, 1895 (Crustacea: Ostracoda) from the Yucatan Peninsula, Mexico
FIGURE 9. Cypretta maya n. sp. A–D, Holotype female. A, A1; B, A2; C, Mx1p; D, rake like organ and upper lip.
ScienceDex guides
Understand access before you commit
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.