Meet our grantees
Wild Animal Initiative funds academic research on high-priority questions in wild animal welfare.
The goal of our grants program is to fund research that deepens scientific knowledge of the welfare of wild animals in order to better understand how to improve the welfare of as many wild animals as possible, regardless of what causes the threats to their well-being.
We showcase our grantees and their projects here and continuously update this page as new projects are added.
Harnessing machine learning for the non-invasive assessment of wild fish welfare
Grantee: Thomas Pike
Institution: University of Lincoln
Project summary
This project aims to develop an open-source aquatic camera system capable of automatically and non-invasively quantifying a suite of behavioural and cognitive welfare indicators in wild fish. Behavioural indicators include the degree of physical closeness between individuals within a group, the spatial arrangement of subgroups, movement behaviour, and agonistic interactions. The project will examine variation in these indicators along an urban–rural gradient to a range of putative stressors, before validating them using “challenge” tests involving ecologically relevant experimental interventions (e.g., acoustic disturbances such as boat noise). The overarching objective is to develop an open-source toolkit that integrates commercially available hardware with custom-designed software, allowing the methods to be readily used by others to assess wild fish welfare.
Grantee: Thomas Pike
Institution: University of Lincoln, UK
Grant amount: $81,927
Grant type: Challenge grants
Focal species: Fish
Conservation status: Least concern
Disciplines: Animal behavior, cognition, climate science, ichthyology
Research locations: United Kingdom
Project summary
Wild fish are facing unprecedented challenges from climate-change-induced alterations to natural environments and anthropogenic stressors. Yet assessing their welfare is extremely challenging. To address this, this project aims to develop an open-source aquatic camera system capable of automatically and non-invasively quantifying a suite of behavioural and cognitive welfare indicators. Behavioural indicators include the degree of physical closeness between individuals within a group, the spatial arrangement of subgroups, movement behaviour, and agonistic interactions. The project will examine variation in these indicators along an urban–rural gradient to a range of putative stressors, before validating them using “challenge” tests involving ecologically relevant experimental interventions (e.g., acoustic disturbances such as boat noise). The overarching objective is to develop an open-source toolkit that integrates commercially available hardware with custom-designed software, allowing the methods to be readily used by others to easily, cheaply, and repeatedly assess the welfare of wild fish.
Why we funded this project
This project will provide proof of concept for a novel approach to monitoring fish welfare at scale that is designed to be widely generalisable and translatable across species, habitats, and contexts. This project will improve current strategies for assessing the welfare of wild fish, most notably by avoiding the need for capture, handling, or restraint, and by being entirely non-invasive and non-disruptive.
Integrating individual-level juvenile welfare in dynamic habitats across time and space
Grantee: Tom Luhring
Institution: Wichita State University, Texas State University, and Stephen F. Austin University
Project summary
The project will track four populations of juvenile lesser sirens in Eastern Texas within and across years. Sirens’ health is directly affected by their environment through the impacts of resource availability on body condition and growth rates. Furthermore, sirens show strong size-dependent and seasonal shifts in antagonistic behaviors, which lead to acute injuries. This project will use water-borne corticosterone release rates to investigate changes in stress physiology as a function of changes in the environment experienced by the individual (population density, drought severity index, water temperature, pH, conductivity) across time and space to understand coping capacity. This data will also be used to investigate the welfare impact of an established marking technique compared to a novel machine-learning approach.
Grantee: Tom Luhring
Institutions: Wichita State University, Texas State University, and Stephen F. Austin University, United States
Grant amount: $162,604
Grant type: Challenge grants
Focal species: Sirens (Siren intermedia)
Conservation status: Least concern
Disciplines: Herpetology, physiology, climate science
Research location: United States
Project summary
The project will track individual juvenile lesser sirens (Siren intermedia) within and across years for four populations in Eastern Texas. The lack of a terrestrial life-stage and severely limited overland dispersal ability means that hydrologically isolated pools function as closed populations, facilitating recaptures and simplifying demographic estimates. Siren health is directly impacted by the effects of the environment (e.g., drought conditions) through the impacts of resource availability on body condition and growth rates. Furthermore, sirens show strong size-dependent and seasonal shifts in antagonistic behaviors such as biting which lead to acute injuries.
Aquatic amphibians are especially well-suited for the collection of water-borne stress hormones (corticosterone), which offer the least invasive method of evaluating an integrated measure of corticosterone levels that are passively being released through the skin, gills, feces, and urine. This project will use water-borne corticosterone release rates to investigate changes in stress physiology as a function of changes in the environment experienced by the individual (population density, drought severity index, water temperature, pH, conductivity) across time and space to understand coping capacity. These data will also be used to investigate the welfare impact of an established marking technique compared to a novel approach based on pattern recognition by a machine-learning algorithm.
Why we funded this project
Juvenile mortality is especially high in amphibians, and amphibian welfare in general is a neglected subject. This project should provide proof of concept for a cost-effective approach for assessing welfare at both an individual and population level. The waterborne measurements have the potential to integrate corticosterone over a longer period of time, increasing its reliability as a welfare indicator. Finally, this project will test a novel, non-invasive approach to mark-recapture studies, which could facilitate much better individual-level welfare research for amphibians and other (especially aquatic) animals in the future.
