Natural history collections (NHC) provide a wealth of information that can be used to understand the impacts of global change on biodiversity. There is growing interest in using NHC data to estimate changes in species’ distributions and abundance trends over historic time horizons when contemporary survey data are limited or unavailable.
The problem is that museum specimens were not collected with the purpose of estimations population trends. NHC data can exhibit several spatiotemporal and collector-specific biases that can limit the utility of NHC data for evaluating population trajectories.
The main objective of this project was to explore one possible solution for estimating long-term insect trends - the integration of NHC data with other types of observational data, including structured survey data and opportunistic observations from iNaturalist.
Our paper is the Journal of Animal Ecology 1) reviews the challenges associated with using museum records to track long-term population trends; 2) highlights recent methodological advancements that aim to overcome these challenges; and 3) examines the potential of analyzing multiple sources of observational data in a unified analytical framework that accounts for the sampling biases of each data source.
Time series of available data on monarch butterflies in the Midwestern breeding population from 1900 to 2018, including preserved museum specimens (black), opportunistic iNaturalist observations (red), and structured monitoring surveys (blue). Integrating these data sources in a single analytical framework will require a thorough understanding of (1) the relative length of each time series of data, (2) the length of overlap in temporal coverage, and (3) how far back in time we can hindcast population trends when only NHC data are available.
This work was supported by an NSF Postdoctoral Research Fellowship in Biological Collections (DBI-2010698).