Bio

Juliana Vélez (she/her) is a postdoctoral researcher with the Natural Capital Project, studying land-use change and vector-borne disease risk. Her research applies quantitative ecological methods to understand interactions among species, their habitat, and anthropogenic disturbance. Juliana's work incorporates ecological experimentation and collaborations with decision makers to assess the effectiveness of conservation actions for improving ecosystems. She conducts her research under open science standards and has contributed to the development of online resources for reproducible research, including the publication of guides, datasets, and code related to statistical modeling and data processing using artificial intelligence. Juliana earned her Ph.D. in Conservation Sciences from the University of Minnesota.

Honors & Awards

  • Predoctoral fellowship, Smithsonian Institution (2021)
  • Doctoral scholarship, Fulbright (2017)

Boards, Advisory Committees, Professional Organizations

  • Deputy Chair, IUCN SSC Tapir Specialist Group (2024 - Present)

Stanford Advisors

Contact

  • Academic
    velez063@stanford.edu
    University - Scholar Department: Biology Position: Postdoctoral Scholar

Additional Info

All Publications

  • Modelling individual variability in habitat selection and movement using integrated step-selection analysis METHODS IN ECOLOGY AND EVOLUTION Chatterjee, N., Wolfson, D., Kim, D., Velez, J., Freeman, S., Bacheler, N. M., Shertzer, K., Taylor, J., Fieberg, J. 2024; 15 (6): 1034-1047

    View details for DOI 10.1111/2041-210X.14321

    View details for Web of Science ID 001202141500001

  • Implications of the scale of detection for inferring co-occurrence patterns from paired camera traps and acoustic recorders CONSERVATION BIOLOGY Velez, J., McShea, W., Pukazhenthi, B., Stevenson, P., Fieberg, J. 2024; 38 (3): e14218

    Abstract

    Multifunctional landscapes that support economic activities and conservation of biological diversity (e.g., cattle ranches with native forest) are becoming increasingly important because small remnants of native forest may comprise the only habitat left for some wildlife species. Understanding the co-occurrence between wildlife and disturbance factors, such as poaching activity and domesticated ungulates, is key to successful management of multifunctional landscapes. Tools to measure co-occurrence between wildlife and disturbance factors include camera traps and autonomous acoustic recording units. We paired 52 camera-trap stations with acoustic recorders to investigate the association between 2 measures of disturbance (poaching and cattle) and wild ungulates present in multifunctional landscapes of the Colombian Orinoquía. We used joint species distribution models to investigate species-habitat associations and species-disturbance correlations. One model was fitted using camera-trap data to detect wild ungulates and disturbance factors, and a second model was fitted after replacing camera-trap detections of disturbance factors with their corresponding acoustic detections. The direction, significance, and precision of the effect of covariates depended on the sampling method used for disturbance factors. Acoustic monitoring typically resulted in more precise estimates of the effects of covariates and of species-disturbance correlations. Association patterns between wildlife and disturbance factors were found only when disturbance was detected by acoustic recorders. Camera traps allowed us to detect nonvocalizing species, whereas audio recording devices increased detection of disturbance factors leading to more precise estimates of co-occurrence patterns. The collared peccary (Pecari tajacu), lowland tapir (Tapirus terrestris), and white-tailed deer (Odocoileus virginianus) co-occurred with disturbance factors and are conservation priorities due to the greater risk of poaching or disease transmission from cattle.

    View details for DOI 10.1111/cobi.14218

    View details for Web of Science ID 001185520000001

    View details for PubMedID 37937478

  • An evaluation of platforms for processing camera-trap data using artificial intelligence METHODS IN ECOLOGY AND EVOLUTION Velez, J., McShea, W., Shamon, H., Castiblanco-Camacho, P. J., Tabak, M. A., Chalmers, C., Fergus, P., Fieberg, J. 2023; 14 (2): 459-477

    View details for DOI 10.1111/2041-210X.14044

    View details for Web of Science ID 000905278100001

https://orcid.org/0000-0003-0412-2761