Sara Beery

2.1k total citations · 1 hit paper
18 papers, 471 citations indexed

About

Sara Beery is a scholar working on Ecology, Ecological Modeling and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sara Beery has authored 18 papers receiving a total of 471 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Ecology, 8 papers in Ecological Modeling and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sara Beery's work include Species Distribution and Climate Change (8 papers), Wildlife Ecology and Conservation (5 papers) and Video Surveillance and Tracking Methods (3 papers). Sara Beery is often cited by papers focused on Species Distribution and Climate Change (8 papers), Wildlife Ecology and Conservation (5 papers) and Video Surveillance and Tracking Methods (3 papers). Sara Beery collaborates with scholars based in United States, Canada and United Kingdom. Sara Beery's co-authors include Blair R. Costelloe, Devis Tuia, Tanya Berger‐Wolf, Grant Van Horn, Mackenzie Weygandt Mathis, Holger Klinck, Tilo Burghardt, Charles V. Stewart, Silvia Zuffi and Frank van Langevelde and has published in prestigious journals such as Nature Communications, Trends in Ecology & Evolution and Methods in Ecology and Evolution.

In The Last Decade

Sara Beery

14 papers receiving 454 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Perspectives in machine learning for wildlife conservation

2022 348 citations Devis Tuia, Benjamin Kellenberger et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sara Beery United States	7	191	159	88	54	50	18	471
Éric Hervet Canada	7	194 1.0×	123 0.8×	99 1.1×	56 1.0×	57 1.1×	17	510
Sylvain Christin Canada	4	194 1.0×	120 0.8×	35 0.4×	53 1.0×	40 0.8×	7	413
Christina Locke United States	7	188 1.0×	171 1.1×	41 0.5×	34 0.6×	20 0.4×	9	389
Marco Willi United States	4	136 0.7×	124 0.8×	42 0.5×	19 0.4×	18 0.4×	5	302
Mohammad Sadegh Norouzzadeh Iran	8	378 2.0×	283 1.8×	220 2.5×	72 1.3×	42 0.8×	12	896
Julie Linchant Belgium	8	361 1.9×	112 0.7×	86 1.0×	47 0.9×	24 0.5×	17	573
Zoë Jewell United States	11	373 2.0×	156 1.0×	38 0.4×	39 0.7×	31 0.6×	25	547
Shane M. Baylis Australia	8	504 2.6×	167 1.1×	70 0.8×	72 1.3×	43 0.9×	13	760
Anabelle W. Cardoso South Africa	11	301 1.6×	179 1.1×	53 0.6×	116 2.1×	27 0.5×	17	639
Jarrod C. Hodgson Australia	7	516 2.7×	167 1.1×	73 0.8×	69 1.3×	44 0.9×	11	797

Countries citing papers authored by Sara Beery

Since Specialization

Citations

This map shows the geographic impact of Sara Beery's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sara Beery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Beery more than expected).

Fields of papers citing papers by Sara Beery

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara Beery. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sara Beery. The network helps show where Sara Beery may publish in the future.

Co-authorship network of co-authors of Sara Beery

This figure shows the co-authorship network connecting the top 25 collaborators of Sara Beery. A scholar is included among the top collaborators of Sara Beery based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sara Beery. Sara Beery is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Sharma, Shubhi, Kevin Winner, Laura J. Pollock, et al.. (2025). No species left behind: borrowing strength to map data-deficient species. Trends in Ecology & Evolution. 40(7). 699–711.

Rafiq, Kasim, Sara Beery, Meredith S. Palmer, Zaïd Harchaoui, & Briana Abrahms. (2025). Generative AI as a tool to accelerate the field of ecology. Nature Ecology & Evolution. 9(3). 378–385. 9 indexed citations

Miao, Zhongqi, Yuanhan Zhang, Sara Beery, et al.. (2025). New frontiers in artificial intelligence for biodiversity research and conservation with multimodal language models. Methods in Ecology and Evolution. 17(2). 238–256. 1 indexed citations

Pollock, Laura J., Justin Kitzes, Sara Beery, et al.. (2025). Harnessing artificial intelligence to fill global shortfalls in biodiversity knowledge. Edinburgh Research Explorer. 1(3). 166–182. 9 indexed citations

Santoro, Simone, Javier Calzada, Nuria Selva, et al.. (2025). Essential tools but overlooked bias: Artificial intelligence and citizen science classification affect camera trap data. Methods in Ecology and Evolution. 16(11). 2638–2652.

Kim, HyungWon, et al.. (2024). To crop or not to crop: Comparing whole‐image and cropped classification on a large dataset of camera trap images. IET Computer Vision. 18(8). 1193–1208. 5 indexed citations

Beery, Sara, Gabriel Brostow, Kate E. Jones, et al.. (2024). INQUIRE: A Natural World Text-to-Image Retrieval Benchmark. 126500–126514.

Sharma, Tarun Kumar, et al.. (2024). Monitoring Social Insect Activity with Minimal Human Supervision. 1244–1253.

Chen, Jun, Ming Hu, Darren J. Coker, et al.. (2023). MammalNet: A Large-Scale Video Benchmark for Mammal Recognition and Behavior Understanding. 13052–13061. 16 indexed citations

10.

Tuia, Devis, Benjamin Kellenberger, Sara Beery, et al.. (2022). Perspectives in machine learning for wildlife conservation. Nature Communications. 13(1). 792–792. 348 indexed citations breakdown →

11.

Beery, Sara, Guanhang Wu, T.J. Edwards, et al.. (2022). The Auto Arborist Dataset: A Large-Scale Benchmark for Multiview Urban Forest Monitoring Under Domain Shift. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21262–21275. 25 indexed citations

12.

Beery, Sara, Elijah Cole, Joseph Parker, Pietro Perona, & Kevin Winner. (2021). Species Distribution Modeling for Machine Learning Practitioners: A Review. arXiv (Cornell University). 329–348. 4 indexed citations

13.

Beery, Sara. (2021). Scaling Biodiversity Monitoring for the Data Age. XRDS Crossroads The ACM Magazine for Students. 27(4). 14–18. 4 indexed citations

14.

Robertson, Tim, Serge Belongie, Hartwig Adam, et al.. (2019). Training Machines to Identify Species using GBIF-mediated Datasets. Biodiversity Information Science and Standards. 3. 4 indexed citations

15.

Beery, Sara, et al.. (2019). Long Term Temporal Context for Per-Camera Object Detection. arXiv (Cornell University). 2 indexed citations

16.

Copas, Kyle, Tim Robertson, Serge Belongie, et al.. (2019). Training machines to improve species identification using GBIF-mediated datasets. 2019. 1 indexed citations

17.

Beery, Sara, et al.. (2019). Efficient Pipeline for Automating Species ID in new Camera Trap Projects. Biodiversity Information Science and Standards. 3. 30 indexed citations

18.

Beery, Sara, et al.. (2016). Finding areas of motion in camera trap images. 1334–1338. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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