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.
131
datasets available to search
ShareScore release 0.9.0
Dataset results
131 results for “northern Andes”
FIGURE 7 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 7. Dorsal (top), ventral (middle), and lateral (bottom) views of specimens of closely related Myiopagis flycatchers of Andean cloud forests. From left to right: "Antioquia Myiopagis": ICN 38437, 35903 (males); Myiopagis olallai: MECN 7141 (male), 6902 (male holotype), 7142 (female), 6903 (female paratype), AMNH 819936 (male); "Perijá Myiopagis": COP 6733 (unsexed), Pons 3861 (male), 3860 (female).
FIGURE 8 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 8. Male (left) and female (right) specimens of differentiated lineages of the paraphyletic Myiopagis caniceps. From left to right: M. caniceps caniceps: LSUMZ 32295, 124630; M. c. aff. caniceps: LSUMZ 102674, 85215; M. c. cinerea: LSUMZ 110744, 115989; M. c. absita: USNM 483342, 483341 (types); M. c. parambae: AMNH 499606 (holotype), ANSP 147150 (female). For further information, see Appendix 1.
FIGURE 5 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 5. Gene trees of Myiopagis flycatchers inferred for the mitochondrial gene ND2 (A) and the autosomal intron FGB-5 (B). Topologies and branch lengths resulted from 50% majority-rule consensus calculations. Strong statistical support in both Bayesian and maximum likelihood analysis indicated as black dots or asterisks (>0.99 posterior probability and>95% bootstrap support, respectively), numerical support is reported otherwise.
FIGURE 6 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 6. Consensus species-tree from the BEST analysis based on ND2 and FGB-5 sequences indicating Bayesian posterior probabilities of the species relationships in Myiopagis flycatchers. Differentiated populations from disjunct geographic regions of M. caniceps were treated independently. The Andean taxa in this complex are represented only by the two samples of the "Antioquia Myiopagis", due to missing sequence data for one or both molecular markers for M. olallai and the "Perijá Myiopagis". Geographic regions for each taxon in the caniceps-olallai group are indicated.
FIGURE 4 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 4. Spectrograms of call vocalizations in Myiopagis olallai and its closest relatives. (A) Andean grayish form from Bosque Guayabito, Amalfi, Antioquia, Colombia (IAvH-BSA 19543 by AMC, 21 January 2002); (B) Andean grayish form from Bosque Las Ánimas, Amalfi, Antioquia, Colombia (IAvH-BSA 19218 by AMC, 11 February 2002); (C) M. olallai from type locality, Zamora-Chinchipe, Ecuador (ML60232 by P. Coopmans, 20 June 1992); (D) M. caniceps caniceps from Río Grande do Sul, Brazil (ML 19532 by W. Belton, November 1975); (E) M. caniceps cinerea from Napo, Ecuador (by N. Krabbe, October 1994); (F) M. caniceps parambae from Imbabura, Ecuador (XC71233 by D. F. Lane, 14 July 1997). Panels C, D, and E based on figure 2 in Coopmans & Krabbe (2000); reprinted with the written permission of the Wilson Ornithological Society, 3 February 2012.
FIGURE 1 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 1. Photograph of the "Antioquia Myiopagis" exhibiting some of the characteristics, including light gray underparts, mossy green back, dark gray head, immaculate white crown patch, and reddish-brown eyes, that distinguish it from other taxa. Collected in an Andean cloud forest (1825 m) at Bosque Guayabito, Amalfi, Department of Antioquia, Colombia (ICN 35903).
FIGURE 3 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 3. Box plots comparing the "Antioquia Myiopagis" and M. olallai in six song attributes. (A) song pace; (B) song duration; (C) number of notes in the trill part of the song; (D) maximum and (E) minimum frequency of the trill; (F) frequency range of the trill (non significant). Data points represent the average values per individual bird.
FIGURE 2 in Geographic variation and phylogenetic relationships of Myiopagis olallai (Aves: Passeriformes; Tyrannidae), with the description of two new taxa from the Northern Andes
FIGURE 2. Spectrograms of songs of selected Myiopagis flycatchers. (A) Andean grayish form from Bosque Guayabito, Amalfi, Antioquia, Colombia (IAvH-BSA 19580 by AMC, 24 January 2002); (B) Andean grayish form from Bosque Las Ánimas, Amalfi, Antioquia, Colombia (IAvH-BSA 19187 by AMC, 8 February 2002); (C and D) M. olallai from the type locality, Zamora-Chinchipe, Ecuador (ML 60232 by P. Coopmans, 20 June 1992); (E) M. caniceps caniceps from Río Grande do Sul, Brazil (ML 19532 by W. Belton, November 1975); (F) M. caniceps cinerea from Napo, Ecuador (by N. Krabbe, October 1994); (G) M. caniceps parambae from Pichincha, Ecuador (by P. Coopmans, February 1995). Panels C-G based on figure 1 in Coopmans & Krabbe (2000); reprinted with the written permission of the Wilson Ornithological Society, 3 February 2012.
FIGURE 1. Acrobolbus mashpianus. A in Acrobolbus mashpianus (Acrobolbaceae, Marchantiophyta) sp. nov. from the Northern Andes of Ecuador-Notes on the Bryophytes of Ecuador VII
FIGURE 1. Acrobolbus mashpianus. A. Part of shoot, dorsal view. B. Part of shoot, ventral view. C. Underleaf, in situ. D. Cells from center of ventral leaf lobe with oil bodies. E. Cells from center of ventral leaf lobe, leaf surface papillae indicated. F. Detail of Plagiochila- type branch, ventral view. G.-J. Leaves. K. Stem cross-section. All drawn from MB 11033 (QCNE).
The fate of páramo plant assemblages in the sky islands of the northern Andes - Appendix S1. Vegetation and occurrence data used in this study
Open the record for dataset details and reuse information.
Data from: Pennellia yalaensis (Brassicaceae: Halimolobeae), a new species from the Andes of Northern Argentina
Open the record for dataset details and reuse information.
Data from: New host and lineage diversity of avian haemosporidia in the Northern Andes
Open the record for dataset details and reuse information.
Climate vulnerability assessment of the Espeletia complex on Páramo sky islands in the northern Andes
<p>Some of the largest impacts of climate change are expected in the environmentally heterogeneous and species rich high mountain ecosystems. Among those, the Neotropical alpine grassland above the tree line (c. 2,800 m), known as Páramo, is the fastest evolving biodiversity hotspot on earth, and one of the most threatened. Yet, predicting climate responses of typically slow-growing, long-lived plant linages in this unique high mountain ecosystem remains challenging. Here we coupled climate sensitivity modeling and adaptive potential inferences to efficiently assess climate vulnerability of Espeletia, Páramo's most iconic, predominant and rapidly evolving plant complex. In order to estimate climate sensitivity, we first modeled the distribution of 28 Espeletia taxa under a niche conservatism scenario using altitude and five current (1970-2000) and future (2050 RCP 8.5) bioclimatic variables across 36 different Páramo complexes in the northern Andes (49 % of the world's Páramo area). As an alternative to range shifts via migration, we also computed the adaptive capacity of these Páramo complexes by considering three enhancing factors of the biodiversity's adaptive potential as well as three environmental limiting factors of the populations' plastic response. These predictors showed that diverse Páramos in the Eastern Cordillera were more vulnerable likely because the counteracting effects of the adaptive potential (r = -0.93 ± 0.01) were not sufficient to buffer higher distribution losses (r = 0.39 ± 0.01). Agriculture (r = -0.48 ± 0.01), mining (r = -0.36 ± 0.01), and rural population density (r = -0.23 ± 0.01) also weakened the adaptive capacity. These results speak for a limited persistence via migration in the short-term responses of Espeletia to climate change, even though the past population dynamics in concert with glacial cycling is indicative of a predominant role of range shifts. Furthermore, changing climate, together with a general inability to adapt, may eventually constrain the rapid diversification in the Espeletia complex. Our integrative modeling illustrates how future climate may impact plant populations in a mega diverse and highly threatened ecosystem such as the Páramo, and encourages carrying out similar estimates in diverse plant complexes across other high mountain and island-like ecosystems.</p>
FIGURE 4 in Two new species of Eleutherodactylus (Anura: Leptodactylidae) from the Andes of northern Peru
FIGURE 4. Holotype of Eleutherodactylus stictoboubonus, MHNSM 24446. Color pattern in groin.
FIGURE 17 in Six new species of Paraleia Tonnoir (Diptera, Mycetophilidae): amphinotic elements at the northern range of the Andes
FIGURE 17. Female terminalia of Paraleia fumosa sp. n., lateral view. Paratype. Scale 0.1 mm.
FIGURE 20 in Six new species of Paraleia Tonnoir (Diptera, Mycetophilidae): amphinotic elements at the northern range of the Andes
FIGURE 20. Male terminalia of Paraleia tonnoiri sp. n., ventral view. Holotype. Scale 0.1 mm.
FIGURE 16 in Six new species of Paraleia Tonnoir (Diptera, Mycetophilidae): amphinotic elements at the northern range of the Andes
FIGURE 16. Male terminalia of Paraleia fumosa sp. n., ventral view. Holotype. Scale 0.1 mm.
FIGURE 1 in Six new species of Paraleia Tonnoir (Diptera, Mycetophilidae): amphinotic elements at the northern range of the Andes
FIGURE 1. Habitus. Female paratype of Paraleia fumosa sp. n., lateral view. Scale 1 mm.
FIGURE 13 in Six new species of Paraleia Tonnoir (Diptera, Mycetophilidae): amphinotic elements at the northern range of the Andes
FIGURE 13. Male terminalia of Paraleia bolivari sp. n., ventral view. Paratype. Scale 0.1 mm.
FIGURE 23 in Six new species of Paraleia Tonnoir (Diptera, Mycetophilidae): amphinotic elements at the northern range of the Andes
FIGURE 23. Female terminalia of Paraleia sp., lateral view. Paratype. Scale 0.1 mm.
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.