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opencc-by-4.0Dec 2023View details →

Supplementary Information and data for: "Quaternary and Pliocene sea-level changes at Camarones, central Patagonia, Argentina"

This repository contains the supplementary information and raw data annexed to the manuscript "Quaternary and Pliocene sea-level changes at Camarones, central Patagonia, Argentina", authored  by Karla Rubio-Sandoval et al. and submitted for consideration in the journal Quaternary Science Reviews. The folder contains the following items. 1. Raw_data.xlsx This is an excel file that includes all survey and analytical data in several sheets, briefly described hereafter. - GNSS data. Data surveyed with differential GNSS in the field. - Sea level index points. Datapoints used as sea-level index points, and associated calculations of paleo Relative Sea Level. - AAR Summary. Table summarising the main results of the AAR analyses. - AAR complete sheet. The complete set of analytical data done for the Amino Acid Racemization dating. - Radiocarbon data. The analytical results of radiocarbon dating. - Literature ages. A compilation of the Electron Spin Resonance and U-series ages published for the Camarones site. - Transects. Topographical transects extracted from the TanDEM-X Digital Elevation model and referred to the GEOIDEAR 16 geoid. - Distance plot. Data for plotting Relative Sea Level vs distance along the coast of the sea-level index points described in the manuscript. 2. Holocene (folder) This folder contains two excel files ("Area_Camarones_Accepted.xlsx" and "Area_Camarones_Rejected.xlsx") that include the Holocene data described in the paper compiled following the standard HOLSEA template. 3. Runup_modelling This folder contains three folders, each with a Jupyter notebook (.ipynb) and datasets to perform the runup calculations described in the manuscript.

opencc-by-4.0Sep 2022View details →

Ablation stake length record at Glaciar Perito Moreno, Patagonia

These are records of ablation stake length observed at Glaciar Perito Moreno in southern Patagonia.

opencc-by-4.0Apr 2024View details →

Model-based runoff in Northwestern Patagonia (41-46°S)

Dataset: The present dataset includes model-based runoff data for each of the 896 catchments with a surface area > 5 km2 draining into the coastal zone of Northwestern Patagonia (41-46°S). The data were generated using the Variable Infiltration Capacity (VIC) model. VIC is a semi-distributed, physically based hydrological model that simulates snow accumulation and melt, evapotranspiration, canopy interception, surface runoff, baseflow and other hydrological processes at sub-daily time steps. The model was forced with gridded meteorological data from PMET-sim and ERA5-Land for the period 1980-2020. The VIC model was calibrated (1985-2004) and validated (2005-2020) in 43 catchments using a split-sample approach. The calibration was performed using the Shuffled Complex Evolution algorithm included in the SPOTPY framework. The modelling approach achieved adequate performance of hydrological fluxes with modified Kling-Gupta efficiencies of 0.75 ± 0.12 and 0.64 ± 0.23  in the calibration and validation phases (daily timestep), respectively.  The file details are as follows - basins_NP_metadata.csv: basin attributes including basin ID, area (in km2), name, location, mean elevation and climate attributes. - basins_NP_shapefile.zip: Zip file containing the shp file of all basins in the study area () - basins_NP_historical_runoff.csv: Daily time series of runoff data (in m3/s). Each column in the .csv file represents a basin. Citation: A preprint is in preparation and will be added here. Version history: <ul> <li>v1.0: First public released</li> <li>v1.1: Corrected NAs in some basins + minor changes</li> </ul>

opencc-by-4.0Sep 2024View details →

Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020.

Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020. Our study aimed to evaluate the spatio-temporal variability of turbidity from Sentinel-2 (S2) images in the Reloncaví sound and fjord, in Northern Patagonia, Chile, a coastal ecosystem that is intensively used by finfish and shellfish aquaculture. To this end, we downloaded 123 S2 images and assembled a five-year time series (2016-2020) covering five study sites (R1 to R5) located along the axis of the fjord and seaward into the sound. We used Acolite to perform the atmospheric correction and estimate turbidity with two algorithms proposed by Nechad et al. (2009, 2016 Nv09 and Nv16, respectively). Columns (R) represent the spatial distribution of study sites (see Figure 2). Link: https://doi.org/10.1016/j.ecoinf.2024.102814 For more information see materials and methods. Nv2009 or Nv09 are the results obtained for the Nechad algorithm version 2009. Similar to Nv2016 or Nv16 are the results obtained for the Nechad algorithm version 2016.

opencc-by-4.0Feb 2023View details →

Ground Penetrating Radar survey of San Quintin glacier, Northern Patagonia Icefield

Measured ice thickness, Residual Bedrock Reflection Power (BRP) and Internal Reflection Power (IRP) of San Quitin glacier, Northern Patagonia Icefield.   Data for the preprint  "Frontal collapse of San Quintín glacier (Northern Patagonia Icefield), the last piedmont glacier lobe in the Andes" in review for The Cryosphere (https://doi.org/10.5194/tc-2023-10)

opencc-by-4.0May 2023View details →

Water depth observed in front of lake-terminating glaciers in Patagonia

This is the dataset of water depth observed in front of O'Higgins, Upsala, Viedma, and Tyndall glaciers in southern Patagonia.   Data format: Latitude [deg], Longitude [deg], Depth [m]

opencc-by-4.0May 2023View details →

PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia

PatagoniaMet v1.0 (PMET from here on) is a new dataset for Western Patagonia that consists of two datasets: i) PMET-obs, a compilation of quality-controlled ground-based hydrometeorological data, and ii) PMET-sim, a daily gridded product of precipitation, and maximum and minimum temperature. PMET-obs was developed using a 4-step quality control process applied to 523 hydro-meteorological time series (precipitation, air temperature, potential evaporation, streamflow and lake level stations) obtained from eight institutions in Chile and Argentina.  Based on this dataset and currently available uncorrected gridded products (in this case ERA5), PMET-sim was developed using statistical bias correction procedures (i.e. quantile mapping), spatial regression models (random forest) and hydrological methods (Budyko framework). Details are given below. - PMET-obs is a compilation of five hydrometeorological variables obtained from eight institutions in Chile and Argentina. The daily quality controlled data of each variable are stored in separate .csv files with the following naming convention: variable_PMETobs_timeperiod_version/timestep.csv. Each column represents a different gauge with its "gauge_id". Each variable has an additional .csv file containing the metadata for each station (variable_PMETobs_version_metadata.csv). In order to make transparent the possible erroneous data that were discarded from the quality-controlled version, a .zip file with the raw data of all variables is attached. The metadata file (final and raw versions) contains the station name (gauge_name), the institution, the station location (gauge_lat and gauge_lon), the NASADEM elevation (gauge_alt) and the total number of daily records (length). In addition, the precipitation and temperature metadata include the number of monthly outliers (step Nº3 in the methods) and the number of changepoints (step Nº4 in the methods). The streamflow metadata file (Q_PMETobs_version_metadata.csv) contains more than just the location data. Following current guidelines for hydrological datasets, the upstream area corresponding to each stream gauge was delimited (.shp file in Basins_PMETobs_version.zip), and several climatic and geographic attributes were derived. The details of the attributes can be found in the README file. For the basins that were part of the hydrological modelling (and that achieved a Kling-Gupta efficiency greater than 0.5), the file Q_PMETobs_version_water_balance.csv is attached, which contains the water balance for each basin estimated for the period 1985-2019.  - PMET-sim is a daily gridded product with a spatial resolution of 0.05° covering the period 1980-2020. The data for each variable (precipitation and maximum and minimum temperature) are stored in separate netcdf files with the following naming convention: variable_PMETsim_1980_2020_v10d.nc. Citation:   Aguayo, R., León-Muñoz, J., Aguayo, M., Baez-Villanueva, O., Fernandez, A. Zambrano-Bigiarini, M., and Jacques-Coper, M. (2023) PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia. Sci Data 11, 6 (2024). https://doi.org/10.1038/s41597-023-02828-2 Code repository: https://github.com/rodaguayo/PatagoniaMet

dryad40/100

Guanaco distribution modeling in the last 2500 years in Northwest Patagonia

Context: The guanaco is one of the four species of South American camels, and is the largest native mammal inhabiting arid and semi-arid environments in South America. Although guanaco was abundant and widely distributed in the past, currently its density and distribution range are substantially reduced, inhabiting mainly in Argentine Patagonia in small isolated groups. The decline in guanaco populations is most likely related to the Anthropocene defaunation process that is affecting large mammals in developing countries worldwide, but the extent and causes of these changes are not well understood. Aims: Explore both the changes in the distribution of guanaco populations in Northwest Patagonia and the environmental and anthropic factors that shaped the distribution patterns, employing a long-term perspective spanning from the end of the Late Holocene to present times (i.e., last 2500 years). Methods: We combine archaeological information, ethnohistorical records and current observations and apply Species Distribution Models using bioclimatic and anthropic factors as explanatory variables. Key results: Guanaco spatial distribution in Northwest Patagonia changed significantly throughout time. This change consisted in the displacement of the species towards the east of the region and its disappearance from northwest Neuquén and southwest Mendoza in the last 30 years. In particular, the high-density urban settlements and roads, and secondly, competition with ovicaprine livestock (goats and sheep) for forage are the main factors explaining the change in guanaco distribution. Conclusions: Guanaco and human populations co-existed in the same areas during the Late Holocene and historic times, but during the 20th century the modern anthropic impact generated a spatial dissociation between both species, pushing guanaco populations to drier and unproductive areas that were previously peripheral in its distribution. Implications: As with many other large mammal species in developing countries, Northwest Patagonia guanaco populations are undergoing significant changes in their range due to modern anthropic activities. Considering that these events are directly related to population declines and extirpations, together with the striking low density recorded for Northwest Patagonia guanaco populations, urgent management actions are needed to mitigate current human impacts.

opencc-zeroNov 2023View details →

Fig. 5 in Systematic revision of a Miocene sperm whale from Patagonia, Argentina, and the phylogenetic signal of tympano-periotic bones in Physeteroidea

Fig. 5. Schematic comparisons of the periotic of MLP 76-IX-5-1, "Preaulophyseter gualichensis" Caviglia and Jorge, 1980 (A) with "Aulophyseter" rionegrensis (B), Acrophyseter deinodon (C, modified from Lambert et al. 2016), Zygophyseter varolai (D, modified from Bianucci and Landini 2006), Aulophyseter morricei (E, modified from Kellogg 1927), Orycterocetus crocodilinus (F, modified from Kellogg 1965), and Physeter macrocephalus (G, modified from Kasuya 1973). In dorsal (A1–G1), ventral (A2–G2), medial (A3–G3), and lateral (A4–C4, E4–G4) views. Black areas indicate anatomical foramina. Not to scale.

Fig. 4 in Systematic revision of a Miocene sperm whale from Patagonia, Argentina, and the phylogenetic signal of tympano-periotic bones in Physeteroidea

Fig. 4. Isolated periotics of a sperm whale Physeteroidea indet. from the Miocene of Patagonia. A. MPEF-PV-605, right periotic. B. MPEF-PV-651, right periotic. C. MPEF-PV-6098, left periotic. D. MLP 80-VIII-30-133a, right periotic. E MLP 80-VIII-30-133b, left periotic. F. MLP 52-X-2-8, right periotic. In dorsal (A1–F1), ventral (A2–F2), medial (A3–F3), and lateral (A4–F4) views. G. MLP 56-IX-2-7, fragmentary periotic in dorsal (G1) and medial (G2) views.

Fig. 2 in Systematic revision of a Miocene sperm whale from Patagonia, Argentina, and the phylogenetic signal of tympano-periotic bones in Physeteroidea

Fig. 2. Teeth of a sperm whale Physeteroidea indet. previously described as "Preaulophyseter gualichensis" Caviglia and Jorge, 1980, MLP 76-IX5-1, from the Miocene of Gran Bajo del Gualicho Formation, Patagonia, Argentina; in labial (A1) and lingual (A2) views, and detailed view of the crown (A3) and enamel (A4). I and II refer to the two fragmentary teeth of the MLP 76-IX-5-1 (the best and worst preserved tooth, respectively).

Fig. 3. Sperm whale Physeteroidea indet. A in Systematic revision of a Miocene sperm whale from Patagonia, Argentina, and the phylogenetic signal of tympano-periotic bones in Physeteroidea

Fig. 3. Sperm whale Physeteroidea indet. A. Left periotic of nomen dubium "Preaulophyseter gualichensis" Caviglia and Jorge, 1980, MLP 76-IX-5-1, from the Miocene of Gran Bajo del Gualicho Formation, Patagonia, Argentina, in dorsal (A1, A2), ventral (A3, A4), medial (A5, A6), and lateral (A7, A8) views. B, C. Two isolated right periotics from the Miocene of Patagonia, MLP 76-IX-2-3 (B) and MLP 76-IX-2-4 (C), in dorsal (B1, C1), ventral (B2, C2), medial (B3, C3), and lateral (B4, C4) views. Photographs (A1, A3, A5, A7, B, C) and explanatory drawings (A2, A4, A6, A8). Abbreviations: abf, anterior bullar facet; aca, aperture for cochlear aqueduct; ai, anterior incisure; ao, accessory ossicle; ava, aperture for the vestibular aqueduct; eh, epitympanic hiatus; fasu, facial sulcus; fo, fenestra ovalis; fosi, foramen singulare; fr, fenestra rotunda; iam, internal acoustic meatus; lt, lateral tuberosity; mf, mallear fossa; pbf, posterior bulla facet; pofc, proximal opening of facial canal (VII); sct, spiral cribiform tract (VIII).

Fig. 1 in Systematic revision of a Miocene sperm whale from Patagonia, Argentina, and the phylogenetic signal of tympano-periotic bones in Physeteroidea

Fig. 1. Geographic location of studied area in Patagonia, southern Argentina (A) and location of the marine Miocene outcrops (B, stars) where the specimens included in this study were collected: Gran Bajo del Gualicho Formation (1) and Gaiman Formation (2).

Fig. 4 in Hamatospiculum flagellispiculosum (Nematoda: Diplotriaenidae) causing severe disease in a new host from Argentine Patagonia: Campephilus magellanicus (Aves: Picidae)

Fig. 4. Optical microscope micrograph of histopathological assessment of muscular tissues dissected from articulations affected by a parasitic infection in Campephilus magellanicus: (A) Sample from the right knee exhibiting loss of the skeletal muscle architecture and nematode eggs (dark dots at lower half), contiguous to muscle fibers with normal tissue architecture (upper half), Bar = 200 μm. (B) Sample from the left tibiotarsus mass showing myofibers of variable shape and size, diffuse mononuclear infiltration, and several eggs, Bar = 100 μm. (C) Two thin-shelled eggs with fully differentiated L1 at the centre of the image, surrounded by mononuclear cells, Bar = 20 μm.

Fig. 2 in Hamatospiculum flagellispiculosum (Nematoda: Diplotriaenidae) causing severe disease in a new host from Argentine Patagonia: Campephilus magellanicus (Aves: Picidae)

Fig. 2. Scanning electron micrograph (SEM) of female Hamatospiculum flagellispiculosum: (A) Detail of epaulette in anterior end (frontal view): a: amphid, b: cephalic papilla in inner circle, c: cephalic papilla in outer circle, d: tooth. (B) Anterior end with vulva (ventral view), Bar = 100 μm. (C) Anterior end (lateral view), Bar = 20 μm. (D) Detail of anal region (caudal view) with atrophied anus, Bar = 200 μm.

Fig. 1 in Hamatospiculum flagellispiculosum (Nematoda: Diplotriaenidae) causing severe disease in a new host from Argentine Patagonia: Campephilus magellanicus (Aves: Picidae)

Fig. 1. Parasitic infections at joints of a necropsied Magellanic woodpecker (Campephilus magellanicus) adult female from Argentine Patagonia: (A) Dissected distocranial extremity of the left tibiotarsus. (B) Urogygial gland area increased in size. Arrows show roundworms present in the tissues extracted from the affected locations.

opencc-by-4.0Apr 2018View details →

Fig. 3 in Helminth communities of two populations of Myotis chiloensis (Chiroptera: Vespertilionidae) from Argentinean Patagonia

Fig. 3. Intestinal location of the endoparasites of Myotis chiloensis, represented by the number of helminths found infecting each intestinal region from the bats from a. Manso, b. Luis Ruiz.

opencc-by-4.0Apr 2018View details →

Fig. 2 in Helminth communities of two populations of Myotis chiloensis (Chiroptera: Vespertilionidae) from Argentinean Patagonia

Fig. 2. Endoparasites of Myotis chiloensis. a. Ochoterenatrema sp. (ventral view), b. Paralecithodendrium sp. (ventral view), c. Parabascus limatulus (ventral view), d. Parabascus sp. (dorsal view), e. Postorchigenes cf. joannae (dorsal view), f. Vampirolepis sp. 1 (scolex), g. Vampirolepis sp. 2 (scolex), h. Allintoshius baudi (male's bursa), i. Physocephalus sp. (encysted larvae), j. Physaloptera sp. (anterior region). Scale bar = 100 μm.

Fig. 5 in Hamatospiculum flagellispiculosum (Nematoda: Diplotriaenidae) causing severe disease in a new host from Argentine Patagonia: Campephilus magellanicus (Aves: Picidae)

Fig. 5. Hamatospiculum flagellispiculosum, optical microscope micrograph of eggs: (A) Egg with first-stage larvae (L1), Bar = 15 μm. (B) Larvae hatching, Bar = 15 μm.