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Carlos Cerrejon Lozano  - GEE, Bryophytes, cartographie numérique

carlos.cerrejonlozano@uqat.ca

I am student of environmental sciences, so I am here to improve my knowledge about that as much as possible. I have been working with bryophytes the last years. I love the field and the landscapes.

Formation académique

  • 2017-2022 Doctorat en sciences de l’environnement. Université du Québec en Abitibi-Témiscamingue, Rouyn-Noranda (Québec)
  • 2014 - 2015 Maîtrise en Biodiversité et Biologie de la Conservation, Universidad Pablo de Olavide. Séville, Espagne
  • 2009 - 2014 Baccalauréat en sciences de l’environnement, Universidad Pablo de Olavide. Séville, Espagne

Projet de recherche

Remote sensing of bryophytes in remote boreal forests: development of a tool for landscape planning.

The economy of remote regions in Northern Canada depends on two conflicting business sectors: exploitation activities and tourism and recreation, both based in available ecosystem services. The development of exploitation activities leads to disturbances in the landscape negatively influencing biodiversity which is the main driver of ecosystem processes and functions on which depend ecosystem service provision. In remote boreal forests, where tree diversity is especially poor, bryophytes play a crucial role in the maintenance ecosystem functioning as they are the main ground vegetation cover layer and account for a significant fraction of biodiversity. Therefore, the acquisition and integration of knowledge about bryophyte spatial distribution and diversity hotspot location into ecological planning may greatly facilitate the conservation of biodiversity along with ecosystem service provision. To reach these objectives in the vast and often inaccessibility boreal forests, remote sensing appears as a powerful information source since it offers a non-expensive detection method for remotely assessing biodiversity over large areas. Medium (30 m) and high (3 m) resolution remote sensing data will be used to generate both habitat variables and disturbance variables (as proxies of fire dynamic processes) and integrate them into species distribution models with the aim of developing an ecological planning tool in remote areas to identify sites of high ecological value to exclude them from industrial development. This will improve the knowledge about bryophyte distribution and the factors influencing their distribution patterns in remote boreal forests.

Carlos Cerrejon Lozano, Osvaldo Valeria, Jesús Muñoz, Nicole J. Fenton. Small but visible: Predicting rare bryophyte distribution and richness patterns using remote sensing-based ensembles of small models. 2022. PlosOne 17(1):e0260543
DOI : 10.1371/journal.pone.0260543    

Carlos Cerrejon Lozano, Osvaldo Valeria, Maxence Martin. Complementary airborne LiDAR and satellite indices are reliable predictors of disturbance-induced structural diversity in mixed old-growth forest landscapes. 2021. Remote Sensing of Environment 267:112746
DOI : 10.1016/j.rse.2021.112746    

Carlos Cerrejon Lozano, Osvaldo Valeria, Nicole J. Fenton, Marion Barbé, Nicolas Mansuy. Predictive mapping of bryophyte richness patterns in boreal forests using species distribution models and remote sensing data. 2020. Ecological Indicator 119:106826
DOI : 10.1016/j.ecolind.2020.106826    

voir la liste complète

 Carlos Cerrejon Lozano Comprendre les patrons de biodiversité des cryptogames (bryophytes et lichens) dans les forêts boréales grâce à la télédétection
Soutenance thèse (2022-07-07)

 Carlos Cerrejon Lozano, Osvaldo Valeria, Jesús Muñoz, Nicole J. FentonPrédire la répartition des espèces rares de bryophytes dans les forêts boréales canadiennes avec les satellites.
22e colloque de la Chaire AFD. Université du Québec en Abitibi-Témiscamingue, complètement virtuel (2020-12-02)

 Carlos Cerrejon Lozano Télédétection de plantes rares : détection et prédiction
Synthèse environnementale (2019-05-27)

 Carlos Cerrejon Lozano, Nicole J. Fenton, Osvaldo Valeria. Affiche 3
Prédiction de la diversité alpha des bryophytes en forêt boréale par modélisation à partir de données de télédétection..
20e colloque de la Chaire AFD. Université du Québec en Abitibi-Témiscamingue, Lorrainville, Québec. (2018-11-30)