Human-Animal Interactions


Postdoctoral Researcher
Institute for Game and Wildlife Research (IREC, Spain)


Javi Fernandez Lopez

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ORCID: 0000-0003-4352-0252
Twitter: @javi_ferlop

Collaborators / supervisors

Data integration to guide wildlife conservation and management / Olivier Gimenez


Interested in statistical ecology and wildlife conservation. Currently working on mammal abundance and distribution modeling focusing on game species. I combine different data sources such as camera trap data, distance sampling or hunting yields by using integrated distribution models in a hierarchical framework. I’m also interested in designing wildlife monitoring programs and Bayesian Inference.


About me

Graduated in Biology Sciences and Ms in Conservation Biology (Universidad Complutense de Madrid, Madrid, Spain). I developed my PhD about filogeny, biogeography and distribution of the corticioid fungus genus Xylodon (Real Jardín Botánico, CSIC, Madrid, Spain). I worked during two years as researcher asistance at the Institute for Game and Wildlife Research (UCLM – CSIC, Ciudad Real, Spain) for the ENETWILD project about mammal distribution at European scale. I performed one year postdoc at University of Massachusetts (Boston, USA) and two year postdoc at Centre d’Ecologie Foncionnelle et Evolutive (Montpellier, France). I’m currentely a postdoctoral researcher at the Institute for Game and Wildlife Research (IREC, Spain), interested in animal abundance modeling and wildlife monitoring programs designing.


Project outline

During my time at CEFE I used different sources of evidence (opportunistic citizen science data, wildlife-vehicle collisions, telemetry, camera trap data, hunting yields, etc.) to create abundance maps at fine resolution and at European level for 5 mammal species: red deer Cervus elaphus, roe deer Capreolus capreolus, wild boar Sus scrofa, red fox Vulpex vulpex and European rabbit Oryctolagus cuniculus. Firstly, addressed the availability of each kind of data for each species, since the same data is usually not recorded for all species. Later, we studied the best observational model for each data source and we identified the covariates which affect the detectability of each observation. Then, we fitted integrated species distribution models by combining the different observational models with a general model for species abundance. As a last stage, the resulting abundance maps for the different species were used in different study cases to provide information about wildlife management and conservation.


Background, employment:

  • 2021-2023: Postdoc at CEFE
  • 2021-2022: Postdoc at UMASS
  • 2018-2020: Researcher Assistant IREC
  • 2014-2020: PhD Student at RJB
  • 2012-2013: Research Assistant at UCM
  • 2011-2012: Ms at UCM
  • 2006-2011: Biology Sciences degree at UCM


(Co) Supervision of students

  • PhD David Ferrer-Ferrando (2021-2024): Wildlife distribution and abundance patterns at local a regional scale.
  • Ms Thesis Joaquín Naranjo (2022): Impact of road on the habitat use of three wild ungulates: a test in central Spain.
  • Ms Thesis David Ferrer-Ferrando (2020): The method matters. A comparative study of biologging and camera traps as data sources with which to describe wildlife habitat selection.



  • Fernández-López, J, Lavandera, P. A., & Gimenez, O. (2023). La unión hace la fuerza: modelos de distribución de especies integrando diferentes fuentes de datos. Ecosistemas: Revista científica y técnica de ecología y medio ambiente, 32(1), 9.
  • Gochanour, B., Fernández‐López, J., & Contina, A. (2023). abmR: An R package for agent‐based model analysis of large‐scale movements across taxa. Methods in Ecology and Evolution, 14(1), 218-230.
  • Fernández‐López, J., Blanco‐Aguiar, J. A., Vicente, J., & Acevedo, P. (2022). Can we model distribution of population abundance from wildlife–vehicles collision data?. Ecography, 2022(5), e06113.
  • Palencia, P., Fernández‐López, J., Vicente, J., & Acevedo, P. (2021). Innovations in movement and behavioural ecology from camera traps: Day range as model parameter. Methods in Ecology and Evolution, 12(7), 1201-1212.
  • Fernández‐López, J., Telleria, M. T., Dueñas, M., May, T., & Martín, M. P. (2021). DNA barcode analyses improve accuracy in fungal species distribution models. Ecology and Evolution, 11(13), 8993-9009.

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