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opencc-by-4.0Jan 2019View details →

Fig 7. Capsicum piuranum Barboza & S in Four new species of Capsicum (Solanaceae) from the tropical Andes and an update on the phylogeny of the genus

Fig 7. Capsicum piuranum Barboza & S. Leiva. (A) Flowering branch. (B) Calyx. (C) Flower. (D) Opened corolla. (E, F, G). Anther, ventral, dorsal and lateral view, respectively. (H) Gynoecium. (I) Fruit. (J) Seed. Drawn by S. Leiva González.

opencc-by-4.0Mar 2023View details →

Spatiotemporal variability of stable isotopes in precipitation and stream water in a high elevation tropical catchment in the Central Andes of Colombia

Stable isotopes data set for the manuscript "Spatio-temporal variability of stable isotopes in precipitation and stream water of a high elevation tropical catchment in the Central Andes of Colombia". Data also used by Andrés Tangarife-Escobar for the thesis "Analysis of the spatial and temporal distribution of stable isotopes and their driving factors in the Upper Claro River Basin, Colombian Andes" to obtain the title of MSc in "Tropical Hydrogeology and Environmental Engineering" at the Technische Universität Darmstadt (Germany) in 2019.  Samples collected by Jorge Ceballos from IDEAM (Colombia) and analyzed by the Servicio Geologico Colombiano.

Fig. 7 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 7. Dibolostethus kattani Means, Bouzan, Martínez-Torres & Ivanov sp. nov., holotype, ♂ (ICN- MD-1317A), right gonopod. A. Mesal view. B. Anterior view. C. Lateral view. Red circles = cingulum. Dashed lines = prostatic groove. Abbreviations: Lb = lobe; PfP = prefemoral process; S = solenomere; Sh = shelf.

Fig. 5. Dibolostethus sicarius Hoffman, 2009 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 5. Dibolostethus sicarius Hoffman, 2009, holotype, ♂ (VMNH110810), left gonopod. A. Lateral view. B. Anterior view. C. Mesal view. Red circles = cingulum. Dashed lines = prostatic groove. Abbreviations: PfP = prefemoral process; S = solenomere.

Fig. 4. Body ring 4, sternal projections. A–B. Dibolostethus sicarius Hoffman, 2009 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 4. Body ring 4, sternal projections. A–B. Dibolostethus sicarius Hoffman, 2009, holotype, ♂ (VMNH110810). C–D. D. inopinatus Means, Bouzan & Ivanov sp. nov., holotype, ♂ (VMNH110813). A, C. Lateral views. B, D. Posterolateral views. Abbreviation: Cx = coxae.

Fig. 3. Dibolostethus Hoffman, 2009 somatic characters continued. A, E. Dibolostethus sicarius Hoffman, 2009 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 3. Dibolostethus Hoffman, 2009 somatic characters continued. A, E. Dibolostethus sicarius Hoffman, 2009, holotype, ♂ (VMNH110810). B–D. D. kattani Means, Bouzan, Martínez-Torres & Ivanov sp. nov., holotype, ♂ (ICN-MD-1317-1). A. Coxa 2, mesal view, red arrow = gonopore. B. Left leg 4, posterior view, red arrow = tibial ventro-apical projection. C. Left leg of 5th leg pair showing incrassate femur, red arrow = tibial ventro-apical projection. D. Body ring 5, lateral view, red circle = anterior pair of sternal projections. E. Prefemur 5, red arrow = basal pore. Abbreviations: Cx = coxa; Pf = prefemur.

Fig. 1 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 1. Dibolostethus kattani Means, Bouzan, Martínez-Torres & Ivanov sp. nov., ♂ (ICN-MD-1367), habitus. Scale bar = 5 mm.

Fig. 9 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 9. Distribution of Chelodesmidae spp. in the Tropical Andes Biodiversity Hotspot, by country. Note: the type locality of Dibolostethus sicarius Hoffman, 2009 is included for completeness although it falls just outside of the boundaries of the Tropical Andes Biodiversity Hotspot. For information on these taxa see Supp. file 1.

Fig. 2 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 2. Scanning electron microscope images of Dibolostethus Hoffman, 2009 showing somatic characters. Dibolostethus kattani Means, Bouzan, Martínez-Torres & Ivanov sp. nov., paratype, ♂ (ICN- MD-1317B). A. Body rings 9th and 10th, red rectangle = median metazonal sulcus. B. Venter of 4th body ring, showing paired sternal projections, red oval = stigma. C. Venter of head, showing narrow gnathochilarium. D. Tip of seventh antennomere, red arrow = narrow slit connecting pocket containing sensilla basiconica and sensory cone area.

Fig. 6 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 6. Dibolostethus inopinatus Means, Bouzan & Ivanov sp. nov., holotype, ♂ (VMNH110813), left gonopod. A. Lateral view, red circle = cingulum. B. Anterior view. C. Mesal view. Dashed lines = prostatic groove. Abbreviations: PfP = prefemoral process; S = solenomere.

Fig. 8. Dibolostethus sicarius Hoffman, 2009 in A review of the previously monotypic tribe Dibolostethini (Chelodesmidae: Chelodesminae) with description of two new species and a summary of the Chelodesmidae of the Tropical Andes Biodiversity Hotspot

Fig. 8. Dibolostethus sicarius Hoffman, 2009, paratype, ♀ (VMNH110811), vulvae. A. Left vulva, lateroventral view, with operculum at base. B. Vulvae in situ, held appressed to 2nd leg pair coxae with valve openings facing each other. C. Left vulva, lateral view.

publicMay 2020View details →

dryad40/100

Plant dispersal strategies of high tropical alpine communities across the Andes

Open the record for dataset details and reuse information.

opencc-by-4.0Jan 2019View details →

Fig 2 in Four new species of Capsicum (Solanaceae) from the tropical Andes and an update on the phylogeny of the genus

Fig 2. Distribution of Capsicum species. https://doi.org/10.1371/journal.pone.0209792.g002

opencc-zeroJun 2021View details →

Landslide age, elevation and residual vegetation determine tropical montane forest canopy recovery and biomass accumulation after landslide disturbances in the Peruvian Andes

Landslides are common natural disturbances in tropical montane forests. While the geomorphic drivers of landslides in the Andes have been studied, factors controlling post-landslide forest recovery across the steep climatic and topographic gradients characteristic of tropical mountains are poorly understood. Here we use a LiDAR-derived canopy height map coupled with a 25-year landslide time series map to examine how landslide, topographic, and biophysical factors, along with residual vegetation, affect canopy height and heterogeneity in regenerating landslides. We also calculate aboveground biomass accumulation rates and estimate the time for landslides to recover to mature forest biomass levels. We find that age and elevation are the biggest determinants of forest recovery, and that the jump-start in regeneration that residual vegetation provides lasts for at least 18 years. Our estimates of time to biomass recovery (31.6-37.1 years) are surprisingly rapid, and as a result we recommend that future research pair LiDAR with hyperspectral imagery to estimate forest aboveground biomass in frequently disturbed landscapes. Synthesis: Using a high-resolution LiDAR dataset and a time-series inventory of 608 landslides distributed across a wide elevational gradient in Andean montane forest, we show that age and elevation are the most influential predictors of forest canopy height and canopy variability. Other features of landslides, in particular the presence of residual vegetation, shape post-landslide regeneration trajectories. LiDAR allows for a detailed analysis of forest structural recovery across large landscapes and numbers of disturbances, and provides a reasonable upper bound on aboveground biomass accumulation rates. However, because this method does not capture the effect of compositional change through succession on aboveground biomass, wherein high-wood density species gradually replace light-wooded pioneer species, it overestimates aboveground biomass. Given previously estimated stem turnover rates along this elevational gradient, we posit that aboveground biomass recovery takes at least three times as long as our recovery time estimates based on LiDAR-derived structure alone.

opencc-zeroSep 2021View details →

Temporal stability in species richness but reordering in species abundances within avian assemblages of a Tropical Andes conservation hot spot

As the pace of environmental change increases, there is an urgent need for quantitative data revealing the temporal dynamics of local communities in tropical areas. Here we quantify the stability of avian assemblages in the highly threatened, but poorly studied, Andean biodiversity hot spot. We evaluated the temporal variation in species richness and community composition of local bird assemblages in three habitat types (native forest, introduced forest, native shrub) using a unique, relatively long-term data series from Cajas National Park and Mazán Reserve in the Southern Andes of Ecuador. We sampled birds with mist nets using a standardized protocol over 11 years, from 2006 to 2016. Species richness remained stable over time across habitats, but community composition changed in the native forest. In particular, we observed taxonomic reordering in the native forest, in which the evenness in the distribution of abundances of taxa decreased over time. This finding is consistent with other studies where species richness remained constant over time while community composition changed. Our study highlights the value of long-term studies in the tropical Andes as we show that species composition of birds in a montane forest is changing, consistent with global trends in biodiversity change.

opencc-by-4.0Nov 2022View details →

Data from: Mixed Signals from the Stable Isotope Composition of Precipitation and Plant Waxes in the Northern Tropical Andes

These files are the supplementary information for Pérez‐Angel, L. C., Sepúlveda, J., Montes, C., Smith, J. J., Molnar, P., González-Arango, C., Snell, K., Dildar, N., Mixed Signals from the Stable Isotope Composition of Precipitation and Plant Waxes in the Northern Tropical Andes. Journal of Geophysical Research: Biogeosciences (In Revision).    This work was funded by the National Science Foundation NSF | GEO | Division of Earth Sciences (EAR): 1929199

opencc-by-4.0Dec 2022View details →

Effects of the environmental conditions and seasonality on a population survey of the Andean Condor Vultur gryphus in the tropical Andes

Script, datasets, and other supplementary material in Márquez-Alvis et al. 2023 PeerJ. Background: Among the New World vultures, the Andean Condor is considered one of the most culturally and ecologically important species. However, their populations are declining over their entire distributional range. In response, conservation strategies have been implemented in many countries to reverse the increasing extinction risk of this species. The initiatives rely on extensive population surveys to gather basic information necessary to implement policies and to intervene efficiently. Still, there is a need to standardize the surveys based on seasonality and suitable environmental conditions throughout the species distribution.  Here, we provide the first assessment of how daily temperature, rainfall, and seasonality influence surveys of Andean Condors on a communal roost in the central Peruvian Andes. Methods: Using an autoregressive generalized linear model, we associated environmental variables with visual surveys of adult and young condors at three different times of the day and three times a week between June 2014 and March 2015. Results: We found that both adults and young Andean Condors showed a threefold reduction in the use of the communal roost after the beginning of the rainy season. Colder and drier days (dry season) are preferable for surveying, as we expect the total number of condors using communal roosts to reduce under rainy (rainfall = -0.53 ± 0.16) and warmer days (temperature= - 0.04 ± 0.02) days. Therefore, the significant variation in the use of roosts across seasons and hours should be carefully accounted for in national surveys, at the risk of undermining the full potential of the communal roost surveys. Moreover, we also found a strong bias towards immatures (about 76%) in the adult:immature ratio and a remarkable absence of Andean Condors during the wet season. These results suggest that the species might be using other unknown communal roosts hierarchically. Such results provide key information for selecting priority areas for conservation and selecting the best time to survey this species in the tropical Andes. Finally, it may open a fruitful avenue for further research on the protection of the Andean Condor.

openAug 2023View details →

Tropical Andes Land Cover Dataset (TALANDCOVER)

The Tropical Andes Land Cover Dataset (TALANDCOVER) was built for the department of Antioquia Colombia and consists of three folders for the three types of sampling.<ul><li>Random: 5000 images</li><li>Balanced of minimum 50% coverage per class: 1389 images</li><li>Balanced of minimum 70% coverage per class:731 images</li></ul>The coordinate system of each dataset is EPSG:3857 - WGS 84 / Pseudo-Mercator with spatial resolution of 4.77 meters and 128*128px.Example of image and corresponding label name:<ul><li>image_PNICFI_D2019-05_T586-1068_C1_N100.tif</li><li>label_PNICFI_D2019-05_T586-1068_C1_N100.tif</li></ul>Pixel values for label are:0 Bare-degraded lands 1 Grasslands 2 Heterogeneous agricultural areas 3 Dense forest 4 Water bodies 5 Built-up areasThere are multiple keywords intentionally inserted in each image name or label name that enable the split of the name in pieces of information about each image and label metadata.Spliting the image or label name by the keywords, would get 6 items:<ol><li>The item (image/label) describe if the file correspond to a patch image or a patch label.</li><li>The second item (Keyword "_P") gives the name of the product NICFI (<a href="https://assets.planet.com/docs/NICFI_User_Guide_v4_EN.pdf">https://assets.planet.com/docs/NICFI_User_Guide_v4_EN.pdf</a>)</li><li>The third item (keyword "_D") gives a date for the composite</li><li>The fourth (keyword "_T") gives the tile number, as stated in the planet scope visual base map documentation: "The name of each basemap quad within the Basemaps API is designed to represent the x and y position of the quad within the two dimensional grid which makes up the basemap. It is generally {X}-{Y}, where X and Y are the x and y position of the quad in the grid". <a href="https://developers.planet.com/docs/data/visual-basemaps/">https://developers.planet.com/docs/data/visual-basemaps/</a></li><li>The fifth (keyword "_C") when available gives the cover class used by the slidding windows to extract the patch, resulting in at least a minimum of 50% or 70% of the pixels within the image correspond to that specific cover class, depending on the selected sample dataset.</li></ol>Take into account that random samples dont have this keyword since the patches where collected at random from a 2d grid without regard of the cover classes present Article : "Land Cover Classification in the Antioquia Region of the Tropical Andes Using NICFI Satellite Data Program Imagery and Semantic Segmentation Techniques".

opencc-zeroDec 2023View details →

Data from: Elevational range sizes of woody plants increase with climate variability in the Tropical Andes

Aim: The climate variability hypothesis proposes that species subjected to wide variation in climatic conditions will evolve wider niches, resulting in larger distributions. We test this hypothesis in tropical plants across a broad elevational gradient; specifically, we use a species-level approach to evaluate whether elevational range sizes are explained by the levels of thermal variability experienced by species. Location: Central Andes Time period: Present day Taxon: Woody plants Methods: Combining data from 479 forest plots, we determined the elevational distributions of nearly 2300 species along an elevational gradient (~209 – 3800 m). For each species, we calculated the maximum annual variation in temperature experienced across its elevational distribution. We used phylogenetic generalized least square models to evaluate the effect of thermal variability on range size. Our models included additional covariates that might affect range size: body size, local abundance, mean temperature and total precipitation. We also considered interactions between thermal variability and mean temperature or precipitation. To account for geometric constraints, we repeated our analyses with a standardized measure of range size, calculated by comparing observed range sizes with values obtained from a null model. Results: Our results supported the main prediction of the climate variability hypothesis. Thermal variability had a strong positive effect on the range size, with species exposed to higher thermal variability having broader elevational distributions. Body size and local abundance also had positive, yet weak effects, on elevational range size. Furthermore, there was a strong positive interaction between thermal variability and mean annual temperature. Main conclusions: Thermal variability had an overriding importance in driving elevational range sizes of woody plants in the Central Andes. Moreover, the relationship between thermal variability and range size might be even stronger in warmer regions, underlining the potential vulnerability of tropical montane floras to the effects of global warming.