Can Aquatic Invertebrates within Public Aquaria Fit the Five Domain Welfare Model?

Perkins, Kerry

doi:10.1163/25889567-bja10025

Cited by 3 publications

(2 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Non‐invasive tagging methods also represent an improvement in animal welfare. Previously used invasive methods of tagging animals will likely lose their social licence as standards of care and legal protections increase, particularly with the rising interest in invertebrate animal welfare (Horvath et al., 2013; Mather, 2019; Perkins, 2021).…”

Section: Discussionmentioning

confidence: 99%

An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning

Wahltinez,

Wahltinez

2024

Methods Ecol Evol

View full text Add to dashboard Cite

Animal re‐identification remains a challenging problem due to the cost of tagging systems and the difficulty of permanently attaching a physical marker to some animals, such as sea stars. Due to these challenges, photo identification is a good fit to solve this problem whether evaluated by humans or through machine learning. Accurate machine learning methods are an improvement over manual identification as they are capable of evaluating a large number of images automatically and recent advances have reduced the need for large training datasets. This study aimed to create an accurate, robust, general purpose machine learning framework for individual animal re‐identification using images both from publicly available data as well as two groups of sea stars of different species under human care. Open‐source code was provided to accelerate work in this space. Images of two species of sea star (Asterias rubens and Anthenea australiae) were taken using a consumer‐grade smartphone camera and used as original datasets to train a machine learning model to re‐identify an individual animal using few examples. The model's performance was evaluated on these original sea star datasets which contained between 39–54 individuals and 983–1204 images, as well as using six publicly available re‐identification datasets for tigers, beef cattle noses, chimpanzee faces, zebras, giraffes and ringed seals ranging between 45–2056 individuals and 829–6770 images. Using time aware‐splits, which are a data splitting technique ensuring that the model only sees an individual's images from a previous collection event during training to avoid information leaking, the model achieved high (>99%) individual re‐identification mean average precision for the top prediction (mAP@1) for the two species of sea stars. The re‐identification mAP@1 for the mammalian datasets was more variable, ranging from 83% to >99%. However, this model outperformed published state‐of‐the‐art re‐identification results for the publicly available datasets. The reported approach for animal re‐identification is generalizable, with the same machine learning framework achieving good performance in two distinct species of sea stars with different physical attributes, as well as seven different mammalian species. This demonstrates that this methodology can be applied to nearly any species where individual re‐identification is required. This study presents a precise, practical, non‐invasive approach to animal re‐identification using only basic image collection methods.

show abstract

Section: Discussionmentioning

confidence: 99%

An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning

Wahltinez,

Wahltinez

2024

Methods Ecol Evol

View full text Add to dashboard Cite

show abstract

“…Within the aquarium and zoo community, Mellor's five domain model is the most popular [1]. Although useful for terrestrial vertebrates, its suitability for other species is still yet to be fully investigated [18,19]. Another criticism is that, like similar models, it is often based around a single point in time rather than the lifetime of experiences of an animal [20].…”

Section: Introductionmentioning

confidence: 99%

Invisible Invertebrates: The Welfare of Invertebrates in Public Aquaria

Perkins

2023

Animals

Self Cite

View full text Add to dashboard Cite

Awareness of welfare issues within animal collections is increasing as information becomes more accessible for staff and the public. A knowledge gap remains when considering the welfare of invertebrates, particularly when housed in public aquaria. TripAdvisor comments were analyzed for 485 worldwide aquariums. The public focused on anthropogenic features or charismatic organisms within collections. Invertebrate welfare was only presented in 18% of negative welfare comments compared with the 51% of represented vertebrates and 31% of negative general welfare comments. The UK and USA reported a greater number of perceived invertebrate welfare issues. Greater dissemination of information between aquarists and scientists should be encouraged to drive welfare standards and improve husbandry. In addition, incorporating input from invertebrate aquarists while utilizing welfare toolkits are vital for improving overall standards if we are to have greater representation of invertebrate welfare in public aquaria.

show abstract

Considerations for implementing regulation of decapods in science

Powell,

Agnalt,

Heasman

et al. 2024

Anim. welf.

View full text Add to dashboard Cite

Decapod crustaceans, commonly utilised for pure or applied scientific research and commercial food production, have generally remained outside ethical debate. However, in the last decade many parts of the world have seen an increase in public interest in the welfare of decapod crustaceans and statutory legal protection has been introduced in several countries. Although still limited to a small number of countries and remaining relatively unharmonised, relevant legislation could be increasingly broadened to include decapods in further jurisdictions. Much existing legislation, originally intended for protecting terrestrial vertebrates during scientific study, might be unsuitable for aquatic invertebrates such as decapods. Indeed, precedence with many fish species and cephalopods suggests detail is lacking with respect to fundamental guidance. Therefore, similar inclusion of decapods into such legislation could make welfare or scientific goals more challenging to achieve unless relevant guidance is available, particularly to animal care practitioners. This horizon paper aims to summarise existing decapod legislation, and the considerations required should decapods be included in current conceptual frameworks and scientific legislation.

show abstract

Can Aquatic Invertebrates within Public Aquaria Fit the Five Domain Welfare Model?

Cited by 3 publications

References 56 publications

An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning

An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning

Invisible Invertebrates: The Welfare of Invertebrates in Public Aquaria

Considerations for implementing regulation of decapods in science

Contact Info

Product

Resources

About