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Projet PROTECT
Projet PROTECT logo
Oct 28, 2022UMI SOURCE
Le projet Protect étudie l’articulation des logiques multiples façonnant les formes de la protection sociale à Madagascar. Il a pour finalité de caractériser les formes de la protection sociale à Madagascar, d’analyser leur adéquation avec les besoins des populations (pauvreté, v...
Analyses of soils sampled on Madagascar Highlands following temperature and rainfall gradients in 2014
Oct 27, 2022 - UMR Eco&Sols
Bernard, Laetitia; Razanamalala, Kanto; Razafimbelo, Tantely M.; Maron, Pierre-Alain; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas; Lelièvre, Mélanie; Dequiedt, Samuel; Ramaroson, Volaniaina; Marsden, Claire; Becquer, Thierry; Trap, Jean; Blanchart, Eric, 2022, "Analyses of soils sampled on Madagascar Highlands following temperature and rainfall gradients in 2014", https://doi.org/10.23708/OMIROI, DataSuds, V2, UNF:6:E57hcLurg305IF1DoMg8+g== [fileUNF]
Priming effect (PE) in soil is proposed to be generated by two distinct mechanisms: “stoichiometric decomposition” and/or “nutrient mining” theories. Each mechanism gets its own dynamics, involves its own microbial actors and targets different soil organic matter (SOM) pools. The...
Analyses_soils_Madagascar_Highlands.tab
Oct 27, 2022 - Analyses of soils sampled on Madagascar Highlands following temperature and rainfall gradients in 2014
Tabular Data - 24.5 KB - 77 Variables, 49 Observations - UNF:6:WXQIKanIsaVN3Q5UmY676g==
DataGeospatial
Raw data of variables measured on soil sampled on climate gradient. EXCEL format
Analyses_soils_Madagascar_Highlands.tsv
Oct 27, 2022 - Analyses of soils sampled on Madagascar Highlands following temperature and rainfall gradients in 2014
Tabular Data - 24.6 KB - 77 Variables, 49 Observations - UNF:6:cp4p0R5en79tIfcFSh0N9A==
DataGeospatial
Raw data of variables measured on soil sampled on climate gradient. Tab-separated values (TSV) format.
africanRice_nrctgs_V1.fasta
Oct 26, 2022 - Supporting data and code for the African Rice Panreference produced by the frangiPANe software
Unknown - 504.0 MB - MD5: 9d5d44f42a84c20758347c6b96246c01
Data
Fasta file of the new sequences absent from the reference
africanRice_nrctgs_V1_placedOnGenome.tab
Oct 26, 2022 - Supporting data and code for the African Rice Panreference produced by the frangiPANe software
Tabular Data - 4.6 MB - 4 Variables, 152411 Observations - UNF:6:J8wm0efC8Lf7KQQ/txrx4Q==
Data
CSV file with the position of the new sequences on the genome reference. It contains one line per sequence, each containing 4 columns : (1) the sequence id, (2) its length (bp), (3) the chromosome name, (4) its position on the chromosome.
Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis
Oct 21, 2022 - UMR CEREGE
Garcin, Yannick; Schefuß, Enno; Dargie, Greta C.; Hawthorne, Donna; Lawson, Ian T.; Sebag, David; Biddulph, George E.; Crezee, Bart; Bocko, Yannick E.; Ifo, Suspense A.; Mampouya Wenina, Y. Emmanuel; Mbemba, Mackline; Ewango, Corneille E.N.; Emba, Ovide; Bola, Pierre; Kanyama Tabu, Joseph; Tyrrell, Genevieve; Young, Dylan M.; Gassier, Ghislain; Girkin, Nicholas T.; Vane, Christopher H.; Adatte, Thierry; Baird, Andy J.; Boom, Arnoud; Gulliver, Pauline; Morris, Paul J.; Page, Susan E.; Sjögersten, Sofie; Lewis, Simon L., 2022, "Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis", https://doi.org/10.23708/FO2HGM, DataSuds, V1, UNF:6:ewI8zj0Z/m4OMWGoSn0k3Q== [fileUNF]
This dataset includes two packages: 'Age_depth_models' and 'Tropical_Peats' for the creation of the age-depth models and the processing and analysis of the geospatial data, which are presented in the article "Hydroclimatic vulnerability of peat carbon in the central Congo Basin"....
1_Data_Import_Precipitation.ipynb
Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis
Jupyter Notebook - 8.6 KB - MD5: 48a731c69580534c9dc3435e2b0331f4
Code
This notebook will download raster data (monthly precipitation) in high-resolution (~1x1 km), clip the tropical region and downsample raster at low-resolution (~10x10 km).
1_Data_Import_Precipitation.py
Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis
Python Source Code - 5.3 KB - MD5: 7b4cb0723bfc35ab6251601c993a94e4
Code
This code will download raster data (monthly precipitation) in high-resolution (~1x1 km), clip the tropical region and downsample raster at low-resolution (~10x10 km).
2_Africa_Data_Import_Peat.ipynb
Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis
Jupyter Notebook - 11.5 KB - MD5: 40073efc9b96795aa894a027776558f3
Code
This notebook will download and process (reproject, rasterize, synchronize in HR or LR and encoding) Africa peat shapefiles
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