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1,681 to 1,690 of 8,495 Results
Mar 26, 2024 - Data collected as part of M-TROPICS - UMR GET
Boithias, Laurie; Jarde, Emilie; Latsachack, Keooudone; Thammahacksa, Chanthamousone; Silvera, Norbert; Rochelle-Newall, Emma; Ribolzi, Olivier, 2024, "Escherichia coli, stanol, and total suspended sediment concentrations at the outlet of a ditch draining sewage and surface runoff out of a village, Northern Lao PDR (2016)", https://doi.org/10.23708/YAKLF6, DataSuds, V1, UNF:6:SrLP4yVKKBcrmHLNWFhXlg== [fileUNF]
This dataset has been collected thanks to the long-term partnership with Department of Agricultural Land Management (DALaM), Lao PDR, which granted the permission for field access, and to the financial, scientific, technical, and/or logistical support of the Multiscale TROPIcal C...
Tabular Data - 6.6 KB - 25 Variables, 67 Observations - UNF:6:HSxEScUjwYungyrHcg4SLA==
Data
Escherichia coli, stanol, and total suspended sediment concentrations at the outlet of the station BLS
Mar 22, 2024 - UMR LEMAR
Sané, Babacar; Diouf, Malick; Jean, Fréderic; Kerhervé, Malika; Flye-Sainte-Marie, Jonathan; Houmenou, Abdou Karim; Thomas, Yoann, 2024, "Gonad histological analysis of Senilia senilis sampled in the Sine Saloum inverse estuary in Senegal between march 2021 and march 2022", https://doi.org/10.23708/VQHAZB, DataSuds, V1, UNF:6:F8uDwbq/ISTm9wrdeI/tgg== [fileUNF]
Understanding the reproductive biology of a species is an important means of determining the renewal capacity of natural stocks, especially in the case of heavily exploited species. It is a fundamental element in supporting the implementation of management measures. Here, we stud...
Plain Text - 1.7 KB - MD5: b8581b9e3e22d8c19c11fe94458f8d8d
Documentation
ReadMe file - data citation, description and terms of use.
Tabular Data - 23.7 KB - 15 Variables, 200 Observations - UNF:6:MEN4Up4jbYyjPMDHIAKVKw==
Data
Histological analysis data for Senilia senilis in Senegal (2021-2022).
Mar 18, 2024 - UMR AMAP
Rodda, Suraj Reddy; Fararoda, Rakesh; Jha, Nidhi; Réjou-Méchain, Maxime; Couteron, Pierre; Gopalakrishnan, Rajashekar; Barbier, Nicolas; Alfonso, Alonso; Bako, Ousmane; Bassama, Patrick; Behera, Debabrata; Bissiengou, Pulcherie; Biyiha, Hervé; Brockelman Y., Warren; Chanthorn, Wirong; Chauhan, Prakash; Dadhwal, Vinay Kumar; Dauby, Gilles; Deblauwe, Vincent; Dongmo, Narcis; Droissart, Vincent; Jeyakumar, Selvaraj; Jha, Chandra Shekar; Kandem, Narcisse Guy; Katembo, John; Kougue, Ronald; Leblanc, Hugo; Lewis, Simon; Libalah, Moses; Manikandan, Maya; Martin-Ducup, Olivier; Mbock, Germain; Memiaghe, Hervé; Mofack, Gislain; Mutyala, Praveen; Narayanan, Ayyappan; Nathalang, Anuttara; Oum Ndjock, Gilbert; Ngoula, Fernandez; Nidamanuri, Rama Rao; Pélissier, Raphaël; Saatchi, Sassan; Sagang, Le Bienfaiteur; Salla, Patrick; Simo-Droissart, Murielle; B. Smith, Thomas; Sonké, Bonaventure; Stevart, Tariq; Tjomb, Danièle; Zebaze, Donatien; Zemagho, Lise; Ploton, Pierre, 2024, "South Asian and Central African maps from: LiDAR-based reference aboveground biomass maps for tropical forests of South Asia and Central Africa", https://doi.org/10.23708/H2MHXF, DataSuds, V2, UNF:6:pUYwyUIpsRWmCnpBju2KxQ== [fileUNF]
The dataset contains forest aboveground biomass prediction maps derived from field inventory plot and UAV or airborne LiDAR data over five sites in South Asia and eight sites in Central Africa, together with prediction uncertainty maps. Maps are provided at 100 x 100 m and 40 x 4...
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