Abstract
Killer whales (Orcinus orca) are cosmopolitan apex predators that interact with numerous species, including sharks, skates, and rays (subclass Elasmobranchii). Interactions between killer whales and elasmobranchs have garnered attention from the scientific community, but the dynamics of these events are poorly understood, as interactions are often challenging to observe. In this study, we collated imagery of interactions between killer whales and elasmobranchs to create the first image-based repository of interspecific interactions between marine predators. A total of 320 photos and videos from 82 unique interactions were collected from 12 countries. A minimum of 18 elasmobranch species across 16 genera were identified from the imagery. Furthermore, 10 different interaction types were documented, encompassing both predatory and non-predatory behavior. This dataset can provide insight into various research topics, including killer whale predation techniques, elasmobranch behavior, and the identification of individual killer whales that specialize in elasmobranch prey. As a new and openly accessible resource, this dataset provides the foundation to support future ecological and behavioral research on killer whale and elasmobranch interactions.
Subject terms: Behavioural ecology, Animal behaviour
Background & Summary
Open-access ecological datasets are increasingly essential for understanding predator–prey dynamics across spatial and temporal scales. These resources provide structured, reusable data that underpin research on species distributions, abundance, and interactions1–3, as well as trophic ecology and dietary shifts4,5, morphometrics5–7, and life history traits8,9. Yet for many apex predators, including killer whales (Orcinus orca), detailed records of predation on certain prey groups, such as elasmobranchs, remain sparse and often anecdotal10–12. As visual technologies and citizen-sourced media expand, image-based datasets offer a novel way to systematically capture and verify rare or underreported predator–prey interactions in the marine environment.
While image-based media offers new opportunities to document elusive predator–prey events, particularly in marine systems, structured datasets capturing such interactions remain rare. Interspecific interactions, particularly among predators, play an important role in understanding ecosystem dynamics13. Apex marine predators, such as killer whales, can exert top-down pressures on local ecosystems through predation. For example, killer whale predation has been suggested to influence the presence of white sharks (Carcharodon carcharias) and broadnose sevengill sharks (Notorynchus cepedianus) in South Africa14–16. However, the relationships between killer whales and elasmobranchs (sharks and rays) may be more complex than previously thought, and studies have documented non-predatory interactions between these species17,18. Nevertheless, these interactions are often difficult to observe and are largely underrepresented in the scientific literature.
Here, we share a dataset of imagery of interactions between killer whales and elasmobranchs, creating the first image-based repository of interspecific interactions between marine predators. A total of 320 photographs and videos from 82 unique interactions were collected across 12 countries: Australia, Brazil, Ecuador, French Southern and Antarctic Territories, Japan, Mexico, New Zealand, Panama, Portugal, South Africa, the United Kingdom, and the United States. We identified a minimum of 18 elasmobranch species across 16 genera and described 10 different interaction types from the imagery. Cookiecutter sharks (Isistius spp.) were the most frequently reported in shark interactions (n = 13), followed by requiem sharks (Carcharhinus spp.) (n = 9). Mobula rays (Mobula spp.) were the most commonly documented ray genus within interactions (n = 10). This new, open-access dataset offers a basis for advancing future studies on interactions between killer whales and elasmobranchs.
Methods
Our primary objectives were to (1) compile a comprehensive dataset of available imagery detailing interactions between killer whales and elasmobranchs, supported by visual documentation, (2) identify the elasmobranch species involved in these interactions with killer whales, and (3) characterize the types of interactions occurring between the two groups. Consequently, we have developed a database that serves as a resource for future behavioral and ecological investigations.
We reached out to a broad contributor pool to collect the data through various methods. A call for contributions was shared to MARMAM – Marine Mammals Research and Conservation Discussion, a widely distributed public email list for researchers and other people working with marine mammals. Author EL posted additional calls for contributions on the social media platforms Instagram and Facebook, which co-authors reshared. As of 7/04/2025, the Instagram posts (n = 4) generated a minimum of 50,926 views, and the Facebook posts (n = 2) generated a minimum of 27,116 views. To ensure private-sector perspectives were included, we also conducted an international outreach campaign targeting marine tourism operators. We contacted 74 companies across 12 countries and 15 key coastal regions where killer whales occur, seeking records that met our study criteria, including operators based in Puerto Madryn and Peninsula Valdés (Argentina); Bremer Bay (Australia); Imbituba (Brazil); La Serena (Chile); Drake Bay (Costa Rica); the Galápagos Islands (Ecuador); Auckland (New Zealand); the Canary Islands (Spain); Cape Town (South Africa); Cabo San Lucas (Mexico); Ponta Delgada (Portugal); and Monterey Bay, San Diego, and San Francisco (USA). This effort spanned multiple ocean basins and complemented our outreach through social media and research networks, broadening the search for killer whale–elasmobranch interactions.
Contributors included individual researchers specializing in killer whales or elasmobranchs, as well as whale watching and other sightseeing tour operators and employees, and citizen scientists reached through social media posts. Contributors were asked to provide the following data for their imagery: (1) the date the photo/video was taken, (2) the location of the photo/video, and (3) the identity of the killer whales involved, if known.
After receiving the imagery, we identified the elasmobranchs present in the imagery to the lowest taxonomic level possible. Confidence levels were assigned to taxonomic identifications based on the following criteria: 1 – Taxonomic ID assigned with complete confidence; identified from photo or video with identifying features of the elasmobranch(s) completely or mostly visible; 2 – Taxonomic ID assigned with medium confidence; identified from photo or video with identifying features of the elasmobranch(s) partially visible; 3 – Taxonomic ID assigned with low confidence; identified from photo or video with identifying features of the elasmobranch(s) not visible or absent, and NA – Unidentified shark or ray. Photographs of scarring caused by cookiecutter sharks (Isistius spp.) were automatically assigned confidence levels of 2 or 3 due to indirect inference of interactions based on scar sizes and shapes.
Exact coordinates were provided when possible. In cases where the exact coordinates of the photo or video location were not available, we approximated general coordinates for the interaction area based on discussions with the contributors and/or information contained within the provided imagery files. Each location was assigned a precision type (exact or estimated). We developed a set of interaction types (Table 1), and each encounter was assigned an interaction type based on details from interaction descriptions provided by contributors and the behaviors documented in the imagery.
Table 1.
Interaction type definitions.
| Interaction Type | Interaction Code | Behavior Description |
|---|---|---|
| attack | ATT | physical harm is caused but no kill is confirmed |
| avoidance | AVO | altering a path of travel to circumvent an encounter with another individual |
| depredation | DEP | full or partial removal of catch, bycatch, or bait from fishing gear |
| facilitation | FAC | the actions of one species benefit another |
| harassment | HAR | organism is followed or interfered with but no physical contact is made |
| killing | KIL | organism is killed but consumption is not confirmed |
| killing with consumption | KWC | organism is killed and consumed |
| kleptoparasitism | KPR | an organism steals food from another |
| parasitism | PAR | one organism (parasite) benefits at the expense of another (host) |
| other | OTH | any interaction that does not fit into previously defined interaction types |
Data Record
Metadata
The metadata (kw_elasmobranch_interaction_data.xls) is available in the repository figshare under the following link: 10.6084/m9.figshare.30170305. The dataset is structured as a single.xls file with nineteen columns that describe the encounter data (Tables 2–4). If no information is available for a particular component of the interaction data, “NA” is used. The dataset comprises 82 individual records corresponding to 320 imagery items19.
Table 3.
Description of elasmobranch genus codes.
| Genus Code | Genus |
|---|---|
| ALO | Alopias |
| CAR | Carcharhinus |
| CIR | Cirrhigaleus |
| CRD | Carcharodon |
| DAL | Dalatias |
| DAS | Dasyatis |
| GAL | Galeocerdo |
| GLH | Galeorhinus |
| GYM | Gymnura |
| ISI | Isistius |
| MOB | Mobula |
| MYL | Myliobatis |
| NOT | Notorynchus |
| PRI | Prionace |
| PTE | Pteroplatytrygon |
| RHI | Rhincodon |
| UNK | Unknown |
Table 2.
Description of columns in the.xls file.
| kw_elasmobranch_interaction_data.xls | |
|---|---|
| Interaction_Number | Unique identifier for each interaction |
| File_Name | File name given to each photo or video associated with an encounter [ElasmobranchGenusCode]_[LocationCode]_[YYYYMMDD]_[InteractionType]_[MediaType].[file extension] |
| Date (DDMMYY) | Date that the interaction occurred (DD-MM-YY). If no precise date is available, year (YYYY) or year range (YYYY-YYYY) is used |
| Interaction_Type | 3-digit interaction type code (see Table 1) |
| Actor | The individual or group that performs the focal behavioral action that defines the interaction type |
| Elasmobranch_Type | Type of elasmobranch involved in the interaction (shark or ray) |
| Elasmobranch_Genus | Elasmobranch genus identified in an interaction |
| Elasmobranch_Species | Elasmobranch species identified in an interaction |
| ID_Confidence | Confidence level (1–3) of the taxonomic identification assigned to elasmobranchs within an interaction |
| Location_Region | Locality where an interaction was documented |
| Location_Country | Country where an interaction was documented |
| Latitude (DD) | Latitude of an interaction |
| Longitude (DD) | Longitude of an interaction |
| Location_Precision | Precision of location coordinates (exact or estimated) |
| Media_Type | Media type associated with an interaction (photo or video) |
| KW_ID | Identity of the killer whale(s) involved in an interaction, if known |
| Interaction_Description | Description of the interaction |
| Contributor_Name | Name of the photographer, videographer, and/or organization associated with the interaction imagery |
| Photo_ID_Catalog | Reference or link to the photo-identification catalog associated with the killer whale ID for each record, when available. Entries are marked “NA” when no IDs are available or when IDs originate from informal/local naming systems. |
Table 4.
Description of country codes.
| Country Code | Country |
|---|---|
| AUS | Australia |
| ATF | French Southern and Antarctic Territories |
| ECU | Ecuador |
| BRA | Brazil |
| GBR | United Kingdom |
| JPN | Japan |
| MEX | Mexico |
| NZL | New Zealand |
| PAN | Panama |
| PRT | Portugal |
| USA | United States |
| ZAF | South Africa |
Imagery dataset
All accompanying imagery files are available as a separate dataset on figshare, accessible via the following link: 10.6084/m9.figshare.29607845. All photos and videos are watermarked to ensure attribution to their respective contributor20.
Technical Validation
To ensure the accuracy and consistency of the data, we cross-checked all entries against the original notes and materials provided by contributors. This included verifying species identifications, interaction categorizations, dates, and geographic coordinates wherever available. Any discrepancies between submitted notes and the compiled datasets were reviewed and resolved in consultation with the contributors. These checks helped confirm that each record accurately reflects the information documented at the time of observation.
Acknowledgements
We are grateful to the Playford Trust Foundation and the Australian Government for their scholarship and stipend support for IMR. LM was funded by the Australian Research Council Discovery Early Career Researcher Award DE220101409. We thank Anthony Pere, Christophe Baillout, Leigh de Necker, David Glennie, Nick Ingersole, and Adam Slattery for their contributions of images to this work.
Author contributions
Conceptualization: Emma Luck, Isabella M. Reeves, Lauren Meyer. Investigation: Emma Luck, Isabella M. Reeves, Lauren Meyer. Data curation: Emma Luck. Validation: Emma Luck, Isabella M. Reeves, Stephanie K. Venables, Alison A. Kock, Lauren Meyer. Writing – original draft: Emma Luck, Isabella M. Reeves, Lauren Meyer. Writing – review and editing: Emma Luck, Isabella M. Reeves, Maeva Terrapon, Rebecca Wellard, Stephanie K. Venables, Alison V. Towner, Alison A. Kock, Charlotte Hussain, Molly Altschwager, Rosie Ballard, Evans Baudin, Nancy Black, Evan Brodsky, Jade Cantrall, Julio Cardoso, Matt I. D. Carter, Oliver Clarke, Santiago Diaz-Pazmino, David Donnelly, Georgina Cabayol Ferraz, Arlaine Francisco, Laura González García, Mark Jackman, Aimee Jan, Eric Martin, Dane McDermott, James Moskito, Blair Ranford, Jesús Erick Higuera Rivas, Jasmin O’Brien, Anton Oleynik, Hernán Orellana-Vásquez, Daniela Alarcón Ruales, Gemma Sharp, Jade Sharp, Alisa Schulman-Janiger, Colleen M. Talty, Paul Tixier, John A. Totterdell, Steve Truluck, Jennah Tucker, Tara Weberg, M. Fernanda Urrutia-Osorio, Machi Yoshida, Jochen R. Zaeschmar, Lauren Meyer. Image contribution: Emma Luck, Alison A. Kock, Molly Altschwager, Rosie Ballard, Evans Baudin, Nancy Black, Evan Brodsky, Jade Cantrall, Julio Cardoso, Matt I. D. Carter, Oliver Clarke, Santiago Diaz-Pazmino, David Donnelly, Georgina Cabayol Ferraz, Arlaine Francisco, Laura González García, Mark Jackman, Aimee Jan, Eric Martin, Dane McDermott, James Moskito, Blair Ranford, Jesús Erick Higuera Rivas, Jasmin O’Brien, Anton Oleynik, Hernán Orellana-Vásquez, Daniela Alarcón Ruales, Gemma Sharp, Jade Sharp, Alisa Schulman-Janiger, Colleen M. Talty, Paul Tixier, John A. Totterdell, Steve Truluck, Jennah Tucker, Tara Weberg, M. Fernanda Urrutia-Osorio, Jochen R. Zaeschmar. Supervision: Lauren Meyer. Funding acquisition: Lauren Meyer, Isabella M. Reeves.
Data availability
The metadata can be accessed in the repository figshare under the following: 10.6084/m9.figshare.30170305. The corresponding imagery files can also be accessed in figshare at: 10.6084/m9.figshare.29607845.
Code availability
No custom code was used in the preparation of this dataset.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Citations
- Luck, E. et al. A global image-based data repository of killer whale interactions with elasmobranchs - Metadata. figshare10.6084/m9.figshare.30170305 (2025). [DOI] [PMC free article] [PubMed]
- Luck, E. et al. A global image-based data repository of killer whale interactions with elasmobranchs - Imagery Dataset. figshare10.6084/m9.figshare.29607845 (2025). [DOI] [PMC free article] [PubMed]
Data Availability Statement
The metadata can be accessed in the repository figshare under the following: 10.6084/m9.figshare.30170305. The corresponding imagery files can also be accessed in figshare at: 10.6084/m9.figshare.29607845.
No custom code was used in the preparation of this dataset.