All of my papers can be found on my Google Scholar page.

Summary of contributions

Papers Published

Megan Laxton, Oscar Rodriguez de Rivera,and Janine Illian.(2021).Using Complex Spatio‐temporal Structures to Account for Population Dynamics in Species Distribution Models. (In Press in Methods in Ecology and Evolution; Invited paper for special issue: Realising the promise of large data and complex models).

Rafaela Cobuci Cerqueira, Oscar Rodriguez de Rivera, Jochen A. G. Jaeger and, Clara Grilo. (2021). Directandindirecteffectsof roads on space use by jaguars in Brazil. Scientific Reports. https://doi.org/10.1038/s41598‐021‐01936‐6

Juncal Espinosa, Dario Martin‐Benito, Oscar Rodriguez de Rivera, Mercedes Guijarro, Carmen Hernando and,Javier Madrigal. (2021). Tree growth response to prescribed burning in mixed and pure Pinus nigra stands: effects of burn season and fire severity. Applied Sciences (Accepted August 2021). https://doi.org/10.3390/app11167462

Oscar Rodriguez de Rivera, Rachel McCrea. (2021). Removal modelling in ecology: A systematic review} Plos One (Accepted January 2021). https://doi.org/10.1371/journal.pone.0229965}

Juncal Espinosa, Oscar Rodriguez de Rivera, Javier Madrigal, Mercedes Guijarro and, Carmen Hernando. (2020). Use of Bayesian Modeling to Determine the Effects of Meteorological Conditions, Prescribed Burn Season, and Tree Characteristics on Litterfall of Pinus nigra and Pinus pinaster Stands. Forests (Accepted September 2020). https://doi.org/10.3390/f11091006}

Juncal Espinosa, Oscar Rodriguez de Rivera, Javier Madrigal, Mercedes Guijarro and, Carmen Hernando. (2020) Predicting potential cambium damage and fire resistance in Pinus nigra Arn. ssp. salzmannii.} Forest Ecology and Management (Accepted June 2020). https://doi.org/10.1007/s12080-018-0387-y

Oscar Rodriguez de Rivera, Marta Blangiardo, Antonio López-Quílez and, Ignacio Martín-Sanz. (2019). Species distribution modelling through Bayesian hierarchical approach. Theoretical Ecology. (Accepted June 2018). https://doi.org/10.1007/s12080-018-0387-y

Oscar Rodriguez de Rivera, Antonio López-Quílez and, Marta Blangiardo. (2018). Assessing the Spatial and Spatio-Temporal Distribution of Forest Species via Bayesian Hierarchical Modeling. Forests (Accepted September 2018). https://doi.org/10.3390/f9090573

Oscar Rodriguez de Rivera, and Antonio López-Quílez. (2017). Development and comparison of species distribution models for forest inventories. ISPRS International Journal of Geo-Information (Accepted June 2017). https://doi.org/10.3390/ijgi6060176
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Rodríguez de Rivera, Ó. (2019). Spacio temporal modeling of species distribution. PhD Thesis. University of Valencia.

Rodríguez de Rivera, Ó. (2010). Inventario entomológico del parque nacional marítimo-terrestre de las islas atlánticas de Galicia, Lepidópteros nocturnos (heteróceros). Proyecto fin de carrera/Escuela Universitaria de Ingeniería Técnica Forestal Proyecto fin de carrera (Universidad de Oviedo. Escuela Universitaria de Ingeniería Técnica Forestal).

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Books

Rodríguez de Rivera, Ó., Angulo, I., & Cobos, P. (2015). Lepidópteros Diurnos del Parque Nacional Marítimo Terrestre de las Islas Atlánticas de Galicia. Organismo Autónomo de Parques Nacionales. 151pp. ISBN: 9788480148825

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Forthcoming

—Submitted

Oscar Rodriguez de Rivera, Antonio López-Quílez, Marta Blangiardo and, Martyna Wasilewska. (2020). A spatio-temporal model to understand forest fires causality in Europe. arXiv preprint arXiv:2003.05227 (2020). 14 Pages (Submitted to International Journal of Wildland Fire).}

Oscar Rodriguez de Rivera, Juncal Espinosa, Javier Madrigal and, Marta Blangiardo. (2021). A point-process spatio temporal model to understand wildfires in the Mediterranean basin. (Submitted to JABES).

—In Preparation

Oscar Rodriguez de Rivera and, Marta Blangiardo. (2022). A spatio-temporal model to understand the effect of urban trees in pollution levels (PM10): a case study in London. (To be submitted to Journal of Applied Ecology).

Oscar Rodriguez de Rivera and, Rachel McCrea.(2022).Analysing dispersion of invasive species through joint spatio‐temporal approach.