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Cellphone picture-based, genus-level automated identification of Chagas disease vectors: Effects of picture orientation on the performance of five machine-learning algorithms

https://doi.org/10.1016/j.ecoinf.2023.102430

de Miranda, Vinícius Lima ; de Souza, Ewerton Pacheco ; Bambil, Deborah ; Khalighifar, Ali ; Peterson, A. Townsend ; de Oliveira Nascimento, Francisco Assis ; Gurgel-Gonçalves, Rodrigo ; Abad-Franch, Fernando ( March 2024 , Ecological Informatics)

Free, publicly-accessible full text available March 1, 2025
The effects of light pollution on migratory animal behavior

https://doi.org/10.1016/j.tree.2022.12.006

Burt, Carolyn S. ; Kelly, Jeffrey F. ; Trankina, Grace E. ; Silva, Carol L. ; Khalighifar, Ali ; Jenkins-Smith, Hank C. ; Fox, Andrew S. ; Fristrup, Kurt M. ; Horton, Kyle G. ( April 2023 , Trends in Ecology & Evolution)

Light pollution is a global threat to biodiversity, especially migratory organisms, some of which traverse hemispheric scales. Research on light pollution has grown significantly over the past decades, but our review of migratory organisms demonstrates gaps in our understanding, particularly beyond migratory birds. Research across spatial scales reveals the multifaceted effects of artificial light on migratory species, ranging from local and regional to macroscale impacts. These threats extend beyond species that are active at night – broadening the scope of this threat. Emerging tools for measuring light pollution and its impacts, as well as ecological forecasting techniques, present new pathways for conservation, including transdisciplinary approaches.
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Deep learning improves acoustic biodiversity monitoring and new candidate forest frog species identification (genus Platymantis) in the Philippines

https://doi.org/10.1007/s10531-020-02107-1

Khalighifar, Ali ; Brown, Rafe M. ; Goyes Vallejos, Johana ; Peterson, A. Townsend ( March 2021 , Biodiversity and Conservation)
null (Ed.)
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Can ecological forecasting lead to convergence on sustainable lighting policies?

https://doi.org/10.1111/csp2.12920

Burt, Carolyn S. ; Kelly, Jeffrey F. ; Fox, Andrew S. ; Jenkins‐Smith, Hank C. ; Leon‐Corwin, Maggie ; Khalighifar, Ali ; Trankina, Grace E. ; Silva, Carol L. ; Horton, Kyle G. ( March 2023 , Conservation Science and Practice)

Abstract
The overuse and expansion of artificial light at night (ALAN) has emerged from complex social, economic, and political factors, making it a societal problem that negatively impacts wildlife and people. We propose that a convergence research approach combining ecological forecasting with community engagement and public policy is needed to address this diverse societal problem. To begin this convergence research approach, we hosted a workshop to strengthen connections among key biodiversity‐oriented ALAN stakeholders and to better understand how stakeholder groups function across the United States through facilitated discussions. We have prioritized the input of stakeholders early in our research design by including them in the formulation of a national survey on public perceptions surrounding ALAN and received their input on existing ecological forecasting tools to improve those research products for their future use.

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