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CO and CO2 mixing ratios and flux measurements from the Amazon tropical rainforest
<p>CO and CO2 mixing ratio and flux measurements from the Amazon tropical rainforest</p><p>This dataset belongs to the manuscript 'The emission of CO from tropical rain forest soils', submitted to the journal Biogeosciences in December 2023.</p><p>More details on this dataset can be found in this manuscript:</p><p>https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2746/egusphere-2023-2746.pdf</p><p> For questions, please reach out to Hella van Asperen: hasperen@bgc.mpg-jena.de</p><p>########################################</p><p>Plateau tower CO and CO2 mixing ratio measurements</p><p>Plateau tower CO and CO2 mixing ratio measurements took place in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021) at the K34 tower at field site ZF2 in the Amazon rain forest (-2.60898, -60.209106). Due to a problem in the beginning of the dry season campaign, the measurements at the tower were continued until outside the campaign period, until 18 October 2020. Measurements were performed by a Spectronus FTIR analyzer. Concentrations were measured at 3 heights (5,15 and 36m) every half hour. Canopy height is ~28m.</p><p>########################################</p><p>Valley CO and CO2 mixing ratio measurements</p><p>Valley CO and CO2 mixing ratio measurements took place in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021) at a valley close to the K34 tower at field site ZF2 (-2.600026, -60.217079). Since no electricity was available, automatic battery-driven bag sampling was performed during the night at 3h time intervals, with 4 measurements per night from a 1m height inlet (~18:00, ~21:00, ~0:00, ~3:00). Bag samples were measured the following morning by a Spectronus FTIR-analyzer. </p><p>########################################</p><p>Plateau and valley chamber CO and CO2 fluxes</p><p>Flux chamber measurements were performed over soil and litter together on the plateau and in the valley at field site ZF2, in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021). Five soil collars were installed in the valley, and five on the plateau. Each collar was measured 3 times during each campaign week (on different days). Measurements from the same collar are indicated as (for example) V1A, V1B, V1C. After each flux chamber measurement, soil moisture and soil temperature was measured.</p>
Figures 15-18 in New species of Sycorax (Diptera: Psychodidae) from the Brazilian Amazon
Figures 15-18. Sycorax manauara sp. nov., female. (15) Head, anterior view. (16) Wing. (17) Apex of abdomen, ventral view. (18) Genital fork (white arrow) and sphermathecal ducts (black arrow).
Figures 10-14 in New species of Sycorax (Diptera: Psychodidae) from the Brazilian Amazon
Figures 10-14. Sycorax manauara sp. nov., male Terminalia. (10) Lateral view. (11) Dorsal view. (12) Ventral view. (13) Detailed drawing of lateral view. (14) Detail of aedeagal complex. Abbreviations: ae = aedeagus; ce = cercus; ea = ejaculatory apodeme; ep = epandrium; gc = gonocoxite; gn = gonostyle; ipr = internal branch of paramere; pb = parameral bridge; pr = paramere.
Figures 1-5 in New species of Sycorax (Diptera: Psychodidae) from the Brazilian Amazon
Figures 1-5. Sycorax manauara sp. nov., male head. (1) Anterior view. (2) Posterior view. (3) Head and complete antennae. (4) Detail of flagellomeres 1-3 with ascoids. (5) Detail of apical flagellomeres.
Centennial deforestation impacts on soil phosphorus cycling in the Amazon rainforest
<p>Deforestation of tropical rainforests is a major land use change that alters terrestrial biogeochemical cycling at local to global scales. Deforestation and subsequent reforestation are likely to impact soil phosphorus (P) cycling, which in P-limited ecosystems such as in the Amazon basin has implications for long-term land use change and productivity. We used a 100-year observational chronosequence of primary forest conversion to pasture, as well as a 13-year-old secondary forest, to test land use change and duration effects on soil P dynamics in the Amazon basin. By combining sequential extraction and P K-edge X-ray absorption near edge structure (XANES) spectroscopy with soil phosphatase assays, we assessed pools and process rates of P cycling in surface soils. Deforestation caused increases in total P (135-398 mg kg<sup>-1</sup>), total organic P (Po) (19-168 mg kg<sup>-1</sup>), and total inorganic P (Pi) (30-113 mg kg<sup>-1</sup>) fractions in surface soils with pasture age, with concomitant increases in Pi fractions corroborated by sequential fractionation and XANES spectroscopy. Soil non-labile Po (10-148 mg kg<sup>-1</sup>) increased disproportionately compared to labile Po (from 4-5 to 7-13 mg kg<sup>-1</sup>). Soil phosphomonoesterase and phosphodiesterase binding affinity (Km) decreased while the specificity constant (Ka) increased by 83-159% in 39–100y pastures. Soil P pools and process rates reverted to magnitudes similar to primary forests within 13 years of pasture abandonment, though the relatively short but representative pre-abandonment pasture duration of our secondary forest may not enable significant deforestation effects on soil P cycling, highlighting the need to consider both pasture duration and reforestation age in evaluations of Amazon land use legacies. Although the space-for-time substitution design can entail variation in the initial soil P pools due to atmospheric P deposition, soil properties, and/or primary forest growth, the trend of P pools and process rates with pasture age still provides valuable insights.</p>
Spatial data of Synthesis of the land carbon fluxes of the Amazon region between 2010 and 2020
<p>Spatial data used in the main figures of the manuscript Synthesis of the land carbon fluxes of the Amazon region between 2010 and 2020. </p> <p>To reproduce Figure 4b sum the maps of Figure 2c+2e and Figure 4c sum the maps of Figure 2d+2e. </p> <p>To reproduce Figure 5b sum the maps of Figure 3c+3d. </p> <p>The shapefiles with the Brazilian Amazon and biogeographical Amazon are also provided. </p>
Dura Europos Amazon Scutum
The roman shield based on the roman shield "Dura-Europos Amazon scutum". Dura Europos was the roman city/fort in Syria and it was abandoned in 256 AD The references: https://romanrecruit.weebly.com/shield.html https://www.culturalheritage.org/docs/default-source/annualmeeting/2014am_poster14_an_investigation_of_painted.pdf?sfvrsn=2 Source: Objaverse 1.0 / Sketchfab
Czech Musicians - Amazon River
One of the four "Czech Musicians" statues by Anna Chromy' at Senovážné square, Prague, Czechia. The dancing statues all play different instruments and are blindfolded. They represent the major rivers of the world. The statue with a flute represents the Amazon river.  Source: Objaverse 1.0 / Sketchfab
Supplementary material data for: Unstable environmental conditions constrain the fine-tune between opsin sensitivity and underwater light in an Amazon forest stream fish
<p>Visual adaptations can stem from variations in amino acid composition, chromophore utilization, and differential opsin gene expression levels, enabling individuals to adjust their light sensitivity to environmental lighting conditions. In stable environments, adaptations often involve amino acid substitutions, whereas in unstable conditions, differential gene expression may be a more relevant mechanism. Amazon forest streams present diverse underwater lighting conditions and experience short-term water colour fluctuations. In these environments, it is less likely for genetic and amino acid sequences to undergo modifications that tailor opsin proteins to the prevailing lighting conditions, particularly in species having several copies of the same gene. The sailfin tetra, <em>Crenuchus spilurus</em>, inhabits black and clear water Amazon forest streams. The long wavelength sensitivity (LWS) is an important component for foraging and courtship. Here, we investigated LWS opsin genes in the <em>sailfin tetra</em>. Three copies of LWS1 and two copies of LWS2 genes were found. The maximum absorbance wavelength (λmax) estimated from the amino acid sequences of LWS1 genes exhibited variation among the different copies. In contrast, the copies of LWS2 genes showed identical expected λmax values. Although the amino acid positions affecting λmax varied among LWS genes, they remained consistent among populations living in different water colours. The relative expression levels of LWS genes differed between gene copies. While not formally tested, our results suggest that in fluctuating environments, visual adaptations may primarily stem from alterations in gene expression profiles and/or chromophore usage rather than precise genetic tuning of protein light sensitivity to environmental lighting conditions.</p>
Figure 2 in A new species of Pinndorama Domahovski (Hemiptera: Cicadellidae: Hyalojassini) from the Amazon Rain Forest, Brazil
Figure 2. Pinndorama dilatata sp. nov., male holotype. (A) Habitus, dorsal view. (B) Habitus, lateral view. (C) Head, ventral view. (D) Sternite VIII, ventral view. (E) Genital capsule, lateral view. (F) Pygofer and subgenital plate, lateral view. (G) Pygofer and subgenital plate, ventral view. (H) Subgenital plate, lateral view. (I) Style, dorsal view. (J) Style, lateral view. (K) Aedeagus, lateral view. (L) Aedeagus, ventral view. Scale bars in mm.
Figure 3 in A new species of Pinndorama Domahovski (Hemiptera: Cicadellidae: Hyalojassini) from the Amazon Rain Forest, Brazil
Figure 3. Pinndorama dilatata sp. nov., female paratype. (A) Sternite VII, ventral view. (B) Distal portion of abdomen, ventral view. (C) Distal portion of abdomen, lateral view. (D) First valvifer and first valvula, lateral view. (E) Apical portion of first valvula. (F) Second valvula, lateral view. (G) Apical portion of second valvula. (H) Second valvifer and gonoplac, lateral view. Scale bars in mm.
High-resolution mapping of soil carbon stocks in the western Amazon
<h2>Dear Researchers and Interested Parties,</h2> <p> It is with great enthusiasm that we share our page on Zenodo, where we provide <strong>detailed maps</strong> (30 m resolution) of <strong>soil carbon stocks in Rondônia, Brazil</strong>. These maps were generated using machine learning techniques, using the Random Forest model implemented in the caret package. This initiative aims to provide a deeper and more accurate understanding of the spatial distribution of carbon in the soil, contributing significantly to environmental studies and climate change mitigation strategies in the region.</p> <h2>Available resources:</h2> <h3>High Resolution Maps:</h3> <p>We provide detailed maps of the estimates and uncertainties of soil carbon stocks at different depths (0-5; 5-15; 15-30; 30-60 and 60-100 cm). The maps include mean values (Mg ha<sup>-1</sup>), quantiles (Mg ha<sup>-1</sup>) and coefficients of variation (%), all in "tif" format, with a spatial resolution of 30 m and SAD 1969 Lambert South America projection system (<a href="https://epsg.io/102015">EPSG :102015</a>).</p> <p>The entire process was conducted in open source (R Language). The codes and database used <strong>can be found in the <a href="https://github.com/moquedace/ro_soil_carbon_stock" target="_blank" rel="noopener">GitHub repository</a></strong>, and more information about the methodology is available in the following publication:</p> <p>Moquedace, C. M., Baldi, C. G. O., Siqueira, R. G., Cardoso I. M., Souza, E. F. M., Fontes, R. L. F., Francelino, M. R., Gomes, L. C., Fernandes-Filho, E. I. High-resolution mapping of soil carbon stocks in the Western Amazon. <em>Geoderma Regional</em>, v. 36, p. e00773, 2024. DOI: <a href="https://doi.org/10.1016/j.geodrs.2024.e00773">10.1016/j.geodrs.2024.e00773</a></p> <h2>Availability objectives:</h2> <h3>Promote scientific collaborations:</h3> <p>We encourage researchers, scientists, and organizations to explore and use this data to enrich their own research and projects related to soil carbon and climate change.</p> <h3>Enhance environmental understanding:</h3> <p>By providing open access to these maps, we aim to contribute to a deeper understanding of environmental processes in Rondônia, Brazil and, by extension, enable the implementation of sustainable strategies.</p> <h3>Stimulating innovation:</h3> <p>We believe that sharing this data will stimulate innovation in modeling and spatial analysis methods, driving advances in the prediction of soil carbon stocks, especially in the Amazon.</p> <h2>Thank you in advance for your interest and collaboration. Together, we can advance knowledge and the search for sustainable solutions to important environmental challenges.</h2> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Data from: The latest freshwater giants: a new Peltocephalus (Pleurodira: Podocnemididae) turtle from the Late Pleistocene of the Brazilian Amazon
<p>Overkill of large mammals is recognised as a key driver of Pleistocene megafaunal extinctions in the Americas and Australia. While this phenomenon primarily affected mega-mammals, its impact on large Quaternary reptiles has been debated. Freshwater turtles, due to the scarcity of giant forms in the Quaternary record, have been largely neglected in such discussions. Here we present a new giant podocnemidid turtle, <em>Peltocephalus maturin</em> sp. nov., from the Late Pleistocene Rio Madeira Formation in the Brazilian Amazon, that challenges this assumption. Morphological and phylogenetic analyses of the holotype, a massive partial lower jaw, reveal close affinities to extant Amazonian species and suggests an omnivorous diet. Body size regressions indicate <em>Pe. maturin</em> possibly reached about 180 cm in carapace length and is amongst the largest freshwater turtles ever found. This finding presents the latest known occurrence of giant freshwater turtles, hinting at coexistence with early human inhabitants in the Amazon.</p>
Repeat LiDAR canopy height models for Borneo, eastern Amazon and Guiana Shield
<p>This repository contains LiDAR canopy height models (CHMS) for six tropical forest sites, derived from repeat LiDAR data. The data were used for analysis of canopy disturbance and recovery dynamics. The years of the data collection differ between sites, so the files are named 'a' for the first scan 'b' for the second scan and 'd' for the difference between scans. The 'dtm' files contain terrain models for these areas. Permanent plots and non-forest areas were masked out prior to analysis. </p>
Data from: Dung beetles from three primary forest sites in the Brazilian Amazon
<p><em>Scarabaeinae</em> beetles (Coleoptera: Scarabaeidae) is a high performance indicator group used in biodiversity assessment of tropical forests. As most species are coprophagous they are commonly known as dung beetles although few species may be necrophagous or saprophagous. Allied to the feeding habitat dung beetles display a complex reproductive behaviour with nests underground, and therefore act in many ecossistem services as nutrient cycling, bioturbation and secondary seed dispersal. Dung beetles display specific forraging methods, as they detect food odors through the antennas and fly towards the food resource. They are therefore captured by baited pitfall and flight interception traps, and studies have shown the complementary between these methods. However, the use of attractants can introduce additional sources of variation in trap performance. In our paper we aimed to assess the effect of bait attractiveness on assemblages metrics when sampled by baited pitfall traps. We identified species less and highly attracted to the baits in use, and that assemblages sampled with baited traps tend to lower diversity and higher dominance.</p>
Similar looking sisters: A new sibling species in the Pristimantis danae group from the southwestern Amazon basin (Anura, Strabomantidae)
<p><strong>Supplementary data <br></strong></p> <p>Köhler et al. (2024): Similar looking sisters: A new sibling species in the <em>Pristimantis danae</em> group from the southwestern Amazon basin (Anura, Strabomantidae). Zoosystematics and Evolution 100 (2): 565-582.</p> <p>Recordings of anuran advertisement calls:</p> <p><strong><em>Pristimantis asimus: </em></strong>recorded 29 November 2008 (18:15 h) by Frank Glaw, air temperature not recorded.<br>Locality: Peru: Departamento Huánuco: Provincia Puerto Inca, ACP Panguana, 9.6166°S, 74.9333°W.<br>Call voucher: MUSM 29028</p> <p><strong><em>Pristimantis reichlei</em></strong>: recorded 18 December 1998 by Jörn Köhler, air temperature 16.7 °C.<br>Locality: Bolivia: Departamento Cochabamba: Provincia Chapare: "old Chapare road", 17°07'S, 65°34'W.<br>Recording band-pass filtered at 900-3600 Hz.</p> <p> </p>
Final products from "3D MODELING AS A CONSERVATION TOOL TO CHARACTERIZE ENDANGERED SEASONALLY FLOODED ECOSYSTEMS IN THE VOLTA GRANDE DO XINGU, AMAZON FOREST, PARÁ, BRAZIL"
<p>In these .zip folders, you will find the products generated from flight missions carried out between November 7th to 14th, 2021, in the Volta Grande do Xingu, Pará, Brazil. <br>These results are presented as an integral part of the article titled '3D MODELING AS A CONSERVATION TOOL TO CHARACTERIZE ENDANGERED SEASONALLY FLOODED ECOSYSTEMS IN THE VOLTA GRANDE DO XINGU, AMAZON FOREST, PARÁ, BRAZIL' published on the doctoral thesis "Characterization and monitoring of the flooding dynamics and seasonally flooded environments of the Volta Grande do Xingu through remote sensing", available at <a href="https://doi.org/10.11606/T.106.2023.tde-02022024-211517">https://doi.org/10.11606/T.106.2023.tde-02022024-211517</a>. To understand the data processing methodology that led to these results, please refer to the thesis.<br>Each folder represents a flight mission. They are named by date and flight number (DD_MM_YYYY_FLIGHT#).<br>Within each folder, there are six files resulting from the processed flights: The georeferenced orthophoto and Digital Surface Model, which are raster files (.TIFs), the dense point cloud (.las), and the files composing the 3D Model generated by Agisoft Metashape (extensions .OBJ, .MTL, and .JPEG).<br>The .OBJ file is the primary file for visualizing the model, including the three-dimensional mesh formed by the points of the point cloud and containing geometry, texture, and color information. <br>The .MTL file contains the material description associated with the OBJ file and includes information about the visual properties of the model, such as texture, reflections, and materials. <br>The .JPEG files are the texture images used on the Digital Surface Model to generate the 3D model. This information provides the model with its realistic properties.<br>The .OBJ, .MTL and .JPEG files need to be together in the same folder for a complete 3D Model visualization (i.e., shape, color, and texture).<br>When using this data, please cite Affonso, A. A. (2023). <em>Caracterização e monitoramento da dinâmica de alagamento e dos ambientes sazonalmente alagáveis da Volta Grande do Xingu através de sensoriamento remoto</em>. Tese de Doutorado, Instituto de Energia e Ambiente, Universidade de São Paulo, São Paulo. doi:10.11606/T.106.2023.tde-02022024-211517. Recuperado em 2024-04-14, de www.teses.usp.br</p>
Dataset on Spatial Analysis and Clustering of Deforestation in the Amazon Biome: Spatio-Temporal Patterns and Priority Areas
<p>The dataset was developed with the aim of facilitating the development of a methodology to identify and evaluate deforestation patterns and trends in the Amazon. This innovative method combines deforestation alerts from the Real-Time Deforestation Detection System (DETER) with detailed information on various land categories, including environmental protection areas, settlements, rural properties, undesignated public forests, indigenous lands, and conservation units. The integration of this robust data allowed for the precise identification of areas at risk of deforestation, significantly strengthening monitoring and control activities aimed at combating deforestation in the Amazon region.</p> <p> </p> <p><strong>Spatial resolution</strong></p> <p>The data are available with a spatial resolution of 25 x 25 km (625 km²) and cover the Amazon biome.</p> <p> </p> <p><strong>Temporal resolution </strong></p> <p>Period of observed data: 2017 and 2021</p> <p> </p> <p><strong>Coordinate reference system</strong> </p> <p>Geographic Coordinate System with Datum SIRGAS 2000 (EPSG:5880)</p> <p> </p> <p><strong>Data format</strong></p> <p>Data is provided as Shapefile.</p> <p> </p> <p><strong>Dataset usage</strong> </p> <p>It is free to use, but please make sure to cite the repository and our paper properly if you use this dataset.</p> <p> </p> <p><strong>Publication & further information</strong></p> <p>For additional scenario information, please contact Francisco Gilney Silva Bezerra (franciscogilney@gmail.com).</p>
Checklist and distribution of Pitcairnia species in the Brazilian Amazon
<p>We present here the checklist of Pitcairnia (Bromeliaceae) species in the Brazilian Amazon. It contains 24 species that occur in the Amazon basin and 211 distribution points. These two files contain information on the taxonomy, collection and geographic references of these taxa.</p>
Carbon content of Amazon trees
<p>Original data for Romero et al. "Carbon Content of Amazonian Commercial Tree Boles: Implications for Carbon Stocks" (Submitted)</p>
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