Student award winner explores innovative methods of producing more reliable ecological niche models for highly mobile species

Novel modelling approaches proposed by Kate Ingenloff, PhD candidate at the University of Kansas, could improve accuracy of maps used to shape management and policy of imperilled and migratory species, vectors of human disease

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Kate Ingenloff, 2018 GBIF Young Researchers Award winner

Kate Ingenloff, a PhD candidate at the University of Kansas Biodiversity Institute in the United States, is one of the two recipients of the 2018 GBIF Young Researchers Award. Her research combines occurrence records from the GBIF network with time-specific environmental and behavioural data in ways that could improve the biological and predictive accuracy of models for migratory and other highly mobile species used in research, conservation and policy.

Species distribution maps have an influential role in planning and implementing on-the-ground conservation. But traditional methods for producing the ecological niche models on which such maps are based tend to flatten or average out biological, environmental and temporal variables. For species that migrate or cover large distances, treating this data as if it's static has the effect of obscuring key biological information, like age, sex and breeding status, and overgeneralizing estimates of species ranges over time.

Ingenloff's research takes up the challenge of modelling time-specific and behaviourally complex associations for two well-known, data-rich species: wood thrush (Hylocichla mustelina) and wandering albatross (Diomedia exulans). Knowledge of the wood thrush's widespread distribution across North and Central America is in effect complete, making it a prime candidate to test methods for introducing temporally explicit, step-by-step projections into the models.

One of the best-studied seabirds of the Southern Oceans, the wandering albatross is currently Red Listed as 'vulnerable'. But in a 2017 paper, Ingenloff highlighted the limitations of traditional models to account for the ecological patterns of the 'goonie' across time and space. The earlier study serves as a baseline for her current effort to develop better, more biologically informed models for D. exulans and species like it.

“Kate's approach for incorporating time-specific environmental information into ecological niche models is highly innovative,” said A. Townsend Peterson, University Distinguished Professor at the University of Kansas and supervisor of Ingenloff’s PhD research. “I expect that the approach that Kate is exploring will change methodologies in the field entirely, such that future ecological niche models will be very different from those in vogue today.”

“The aim of my research is two-fold,” said Ingenloff. “First, I want to improve our ability to generate models that are spatially and temporally explicit for use in adaptive conservation planning. And second, I hope to develop a method that derives critical biological information from open-access observation data and calibrates better, more biologically informed models,” said Ingenloff.

“Without the wealth of data available from the GBIF network—which essentially serves as biogeographic big data—my research would not possible.”

Ingenloff is already playing an active role and giving back to the GBIF community, transferring knowledge and skills through capacity enhancement mentoring and training activities around the world. She acts a project mentor for five different BID projects in Africa and, most recently, served as an ecological niche modelling trainer at the BID Pacific data use workshop.

Ingenloff is the first U.S. national to win the award and the second winner nominated by the U.S. delegation, who in 2010 (the award's first year) put forward the name of Andrés Lira-Noriega, a researcher from Mexico then studying in the U.S. Ingenloff is the third winnner from the University of Kansas, preceded by Lira-Noriega in 2010 and Vijay Barve in 2013.

The GBIF Science Committee selected Ingenloff and Raquel Gaião Silva, a Master’s student from Portugal, from a pool of 14 candidates nominated by heads of delegation from 11 GBIF Participant countries. Committee members note that Ingenloff's study "represents much more than one more case study but merely an avenue for using species occurrence data to answer many different questions of ecology, evolution and conservation of biodiversity."

About the Award

Since its inception in 2010, the annual GBIF Young Researchers Award has sought to promote and encourage innovation in biodiversity-related research using data shared through the GBIF network.

About the University of Kansas Biodiversity Institute

The KU Biodiversity Institute studies the life of the planet for the benefit of the Earth and its inhabitants. The institute, including the KU Natural History Museum, accomplishes this mission through the acquisition, curation and study of collections of plants, animals, fossil material and cultural artifacts for undergraduate, graduate and public education, as well as research and public and professional service. Learn more at

About GBIF

GBIF—the Global Biodiversity Information Facility—is an international network and research infrastructure funded by the world’s governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth. Learn more at