SYMP 13 - Methods for occurrence data from natural history collections and community science data

Organizer(s)

• LG

  Laura Guzman, n/a

  University of Southern California, Canada

Co-organizer(s)

• VS

  Vaughn Shirey

  PhD Candidate
  Georgetown University, United States
• RK

  Rassim Khelifa

  University of British Columbia, United States

Moderator(s)

• RK

  Rassim Khelifa

  University of British Columbia, United States

Species’ occurrence data is becoming more widely available through digitization of museum collections (Hedrick et al., 2020) and citizen science platforms (Dickinson et al., 2012) At the time of writing, the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) contain over 1.5-billion records of species occurrences across the planet. Occurrence data is rich with metadata that includes a species name, location, date of collection, and sometimes even photographs of specimens or individuals. The richness of this data allows us to ask questions about changes in biodiversity through time, particularly in taxonomic groups that have not been consistently monitored.The use of occurrence data from museum collections is becoming more common in ecological analyses over the last several years. Importantly, however, improper treatment of these data can lead to misleading inferences (Guzman et al. 2021, Larsen et al. 2021). In this symposium we will present recent advances in methodological approaches that allow us to leverage digitized museum collections. Specifically, we will address how to make inferences about changes in species distributions using occurrence data (Laura Melissa Guzman), how these inferences can be linked to changes in climate (Vaughn Shirey), how we can infer phenology and changes in phenology through time (Michael Belitz), and how we can integrate multiple data sources, such as structured diversity surveys and occurrence data, to make inferences about populations through time (Courtney Davis). Together we tackle methods that ecologists want to use to answer questions about how biodiversity has changed in the anthropocene.




References:



Hedrick, B. P., J. M. Heberling, E. K. Meineke, K. G. Turner, C. J. Grassa, D. S. Park,

J. Kennedy, J. A. Clarke, J. A. Cook, D. C. Blackburn, et al., 2020. Digitization and the

future of natural history collections. BioScience 70:243–251.



Dickinson, J. L., J. Shirk, D. Bonter, R. Bonney, R. L. Crain, J. Martin, T. Phillips, and

K. Purcell, 2012. The current state of citizen science as a tool for ecological research

and public engagement. Frontiers in Ecology and the Environment 10:291–297.



Guzman, L. M., S. A. Johnson, A. O. Mooers, and L. K. M’Gonigle, 2021. Using historical

data to estimate bumble bee occurrence: Variable trends across species provide little

support for community-level declines. Biological Conservation 257:109141



Larsen, E. A. and V. Shirey, 2021. Method matters: pitfalls in analysing phenology from

occurrence records. Ecol. Lett. P. Early View.

Presentations:

• 3:30 PM – 3:50 PM EDT

  Using historical data to estimate changes in species occurrences
  

  Presenting Author: Laura M. Guzman, n/a – University of Southern California

  Co-author: Vaughn Shirey – Georgetown University

  Co-author: Leithen K. M'Gonigle, PhD – Simon Fraser University

  Co-author: Rassim Khelifa – University of British Columbia
• 3:50 PM – 4:10 PM EDT

  Utilizing occupancy-detection models with opportunistic data to detect climate-driven changes in communities
  

  Presenting Author: Vaughn Shirey – Georgetown University

  Co-author: Naresh Neupane – Georgetown University

  Co-author: Leslie Ries – Georgetown University
• 4:10 PM – 4:30 PM EDT

  Phenological research based on natural history collections: practical guidelines and a Lepidopteran case study
  

  Presenting Author: Michael W. Belitz – University of Florida

  Co-author: Elise A. Larsen – Georgetown University

  Co-author: Vaughn Shirey – Georgetown University

  Co-author: Daijiang Li – Louisiana State University

  Co-author: Robert P. Guralnick – University of Florida
• 4:30 PM – 4:50 PM EDT

  CANCELLED - Data Integration Methods For Estimating Long-Term Population Trends Using Opportunistic Data
  

  Presenting Author: Courtney Davis – Michigan State University

  Co-author: Robert P. Guralnick – University of Florida

  Co-author: Elise Zipkin – Michigan State University
• 4:50 PM – 5:00 PM EDT

  Discussion