Situating Ecology as a Big-Data Science: Current Advances, Challenges, and Solutions

The FAIR Guiding Principles for scientific data management and stewardship

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423

The NIST definition of cloud computing

Mell, P., & Grance, T. (2011) · doi:10.6028/nist.sp.800-145 · Cited by 12,637

High-Resolution Global Maps of 21st-Century Forest Cover Change

Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., et al. (2013) · Science · doi:10.1126/science.1244693 · Cited by 11,704

Novel methods improve prediction of species’ distributions from occurrence data

Elith*, J., H. Graham*, C., P. Anderson, R., Dudík, M., Ferrier, S., Guisan, A., J. Hijmans, R., Huettmann, F., R. Leathwick, J., Lehmann, A., et al. (2006) · Ecography · doi:10.1111/j.2006.0906-7590.04596.x · Cited by 9,088

Untitled work

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Jupyter Notebooks – a publishing format for reproducible computational workflows

Kluyver, T. A., Ragan-Kelley, B., Fernando, P., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J. B., Grout, J., Corlay, S., et al. (2016) · IOS Press eBooks · doi:10.3233/978-1-61499-649-1-87 · Cited by 3,407

XSEDE: Accelerating Scientific Discovery

Towns, J. W., Cockerill, T. M., Dahan, M., Foster, I. T., Gaither, K., Grimshaw, A. S., Hazlewood, V., Lathrop, S. A., Lifka, D. A., Peterson, G. D., et al. (2014) · Computing in Science & Engineering · doi:10.1109/mcse.2014.80 · Cited by 3,114

The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte CarloPreprint

Homan, M. D., & Gelman, A. (2014) · arXiv (Cornell University) · Cited by 3,078

Big data: A survey

Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913

The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte CarloPreprint

Hoffman, M. D., & Gelman, A. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1111.4246 · Cited by 2,815

Leveraging synthetic data produced from museum specimens to train adaptable species classification models

Blair, J. D., Khidas, K., & Marshall, K. E. (2025) · PLoS ONE · doi:10.1371/journal.pone.0329482 · Cited by 3

Comparing maximum likelihood and Bayesian methods for fitting hidden Markov models to multi-state capture-recapture data of invasive carp in the Illinois River

Labuzzetta, C. J., Coulter, A. A., & Erickson, R. A. (2024) · Movement Ecology · doi:10.1186/s40462-023-00434-w · Cited by 3

Advancing the understanding of coastal disturbances with a network‐of‐networks approach

Myers‐Pigg, A., Moanga, D. A., Bond‐Lamberty, B., Ward, N. D., Megonigal, J. P., White, E., Bailey, V., & Kirwan, M. L. (2025) · Ecosphere · doi:10.1002/ecs2.70156 · Cited by 4

How will we prepare for an uncertain future? The value of open data and code for unborn generations facing climate change

Gomes, D. G. E. (2025) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2024.1515 · Cited by 4

Addressing Biological Invasions in Agriculture with Big Data in an Informatics Age

Clement, R. A., Lee, H., Manoukis, N. C., Pacheco, Y. M., Ross, F., Sisterson, M. S., & Owen, C. L. (2025) · Agriculture · doi:10.3390/agriculture15111157 · Cited by 3

Understanding deer management dilemmas: A mixed methods approach to understand diverse stakeholder values in human-wildlife conflicts

Murphy, K. J., Kenny, U., Ciuti, S., & Byrne, A. W. (2025) · European Journal of Wildlife Research · doi:10.1007/s10344-025-01954-z · Cited by 4

A semi-automatic workflow to process camera trap images in RPreprint

Böhner, H., Kleiven, E. F., Ims, R. A., & Soininen, E. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.05.510927 · Cited by 3

Grand challenges in foraging behavior and predator-prey interactions: next generation ethology in the Anthropocene

Clark, R. W. (2023) · Frontiers in Ethology · doi:10.3389/fetho.2023.1304654 · Cited by 2

Parsimonious machine learning for the global mapping of aboveground biomass potential

Paz, D. B., Torres, A. M., Pompeu, J., Martin‐Ducup, O., Villa, F., Köhler, C., & Balbi, S. (2025) · Ecography · doi:10.1111/ecog.07587 · Cited by 2

Object detection‐assisted workflow facilitates cryptic snake monitoring

Miller, S., Kirkland, M., Hart, K. M., & McCleery, R. A. (2025) · Remote Sensing in Ecology and Conservation · doi:10.1002/rse2.70009 · Cited by 2

Fish community responses to habitat alteration: Interactions, biomass shifts, and the value of imperfect data

Bonk, E. A., Hanner, R., Bartlett, A. J., & Tetreault, G. R. (2025) · Environmental Biology of Fishes · doi:10.1007/s10641-025-01705-8 · Cited by 2

Transferring species distribution models to understudied systems: Does data integration help?

Patterson, C. R., Zheng, X., Foster, S. D., & Helmstedt, K. J. (2025) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.70178 · Cited by 2

Introducing fwtraits – an R package for obtaining freshwater biodiversity trait information

Basooma, A., Borgwardt, F., Domisch, S., Buurman, M., Bremerich, V., Brizuela, S. R., Tschikof, M., Hein, T. I. A., & Schmidt‐Kloiber, A. (2025) · Basic and Applied Ecology · doi:10.1016/j.baae.2025.10.010 · Cited by 2

A network simplification approach to ease topological studies about the food-web architecture

Gini, A., Re, S., & Facchini, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-17508-1 · Cited by 2

Application of artificial intelligence technologies in processing images from camera traps: principles, software, approaches

Ogurtsov, S. S., Efremov, V., & Владимирович, Л. А. (2024) · Principles of the Ecology · doi:10.15393/j1.art.2024.14662 · Cited by 3

Development of an IoT-Based Device for Data Collection on Sheep and Goat Herding in Silvopastoral Systems

Araujo, M., Leitão, P., de Castro, M. M. F., Castro, J., & Bernuy, M. A. C. (2024) · Sensors · doi:10.3390/s24175528 · Cited by 2

A modular curriculum to teach undergraduates ecological forecasting improves student and instructor confidence in their data science skills

Lofton, M. E., Moore, T. N., Woelmer, W. M., Thomas, R. Q., & Carey, C. C. (2024) · BioScience · doi:10.1093/biosci/biae089 · Cited by 2

Environmental response strategies for the spatial distribution of seed plants in Gansu

Li, Z., Wei, J., Du, W., Huang, R., Song, L., Tian, Q., & Zhou, X. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2025.1526269 · Cited by 2

Evaluating Empirical Dynamic Modeling for forecasting: The role of variation among time series replicates

Slegers, F., Bastiaansen, R., & Pos, E. (2025) · Ecological Informatics · doi:10.1016/j.ecoinf.2025.103139 · Cited by 2

Multi-modal, interrelated navigation in migratory birds: A data mining study

Moayedi, A., Long, J., Kölzsch, A., Kruckenberg, H., Benitez‐Paez, F., & Demšar, U. (2025) · Ecological Informatics · doi:10.1016/j.ecoinf.2025.103218 · Cited by 2

Comparing efficiency of literature-based estimation of general biomass using Length-Weight Relationships (LWRs) between freshwater and seawater fishes

Yeom, J., & Kim, S. D. (2025) · PLoS ONE · doi:10.1371/journal.pone.0321571 · Cited by 2

infinitylists: A Shiny application and R package for rapid generation of place‐based species checklists

Mesaglio, T., Kar, F., Sauquet, H., & Cornwell, W. K. (2025) · Applications in Plant Sciences · doi:10.1002/aps3.70012 · Cited by 2

Macrosystems ecology: A new engine and frontier in contemporary ecosystem science

Yu, G., Yu, Z., Chen, Z., & Wang, Q. (2025) · Geography and sustainability · doi:10.1016/j.geosus.2025.100334 · Cited by 2

A geospatial inventory dataset of study sites in a Korean Quaternary paleoecology database

Kim, S. H., & Byun, E. (2025) · Earth system science data · doi:10.5194/essd-17-4479-2025 · Cited by 2

Managing FAIR Research Products for Biodiversity and Ecosystems Within the LifeWatch Italy Infrastructure

Tarallo, A., Muri, C. D., Pulieri, M., Leo, F. D., Marra, M. L., Raho, D., Basset, A., & Rosati, I. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-06136-2_31 · Cited by 2

Ecoinformatics: A Review of Approach and Applications in Ecological Research

Lin, C. C. (2020) · doi:10.22920/pnie.2020.1.1.9 · Cited by 2

Integration and Implication of Machine Learning: Barriers to Aid Environmental Monitoring and Management

Ali, M. A., Mukarram, M. M. T., Chowdhury, M. A., Karin, S., & Faruq, A. N. (2021) · OALib · doi:10.4236/oalib.1107468 · Cited by 2

Asking nicely: Best practices for requesting data

Midway, S. R., Sievert, N. A., Lynch, A. J., Whittier, J. B., & Pope, K. L. (2022) · Ecological Informatics · doi:10.1016/j.ecoinf.2022.101729 · Cited by 2

Conflicts of Digital Development’s Sustainability and Resolving them Through the Balance of Social, Ecological and Economic Interests During Technological Progress

Cherepukhin, T. Y., Савельева, Н. К., Коваленко, А. М., & Ivanova, O. (2022) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1572-832320220000030008 · Cited by 2

Seguimiento de la biodiversidad en la era del Big Data

Hernández, L., Álvarez‐Martínez, J. M., Almaraz, C. G., de Dios, R. S., Jiménez‐Alfaro, B., & Taboada, M. F. Á. (2022) · Ecosistemas · doi:10.7818/ecos.2450 · Cited by 2

Development of Species-Specific Cichla Species eDNA Primers for Rapid Alien Invasive Species (AIS) Monitoring

Osman, N. F. N., Bakar, A. A., Rahman, R. A., Saidin, S., Ghani, I. F. A., & Ahmad, A. (2023) · Advances in biological sciences research/Advances in Biological Sciences Research · doi:10.2991/978-94-6463-166-1_7 · Cited by 2

Performance of five statistical methods to infer interactions among moving individuals in a predator–prey system

Fronville, T., Blaum, N., Kramer‐Schadt, S., Schlägel, U. E., & Radchuk, V. (2024) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.14323 · Cited by 2

Relational Systems Ecology: The Anticipatory Niche and Complex Model Coupling

Kineman, J. J., & Wessman, C. A. (2021) · Springer eBooks · doi:10.1007/978-981-15-0720-5_79 · Cited by 2

Publisher Correction: Open Science principles for accelerating trait-based science across the Tree of Life

Gallagher, R. V., Falster, D. S., Maitner, B., Salguero‐Gómez, R., Vandvik, V., Pearse, W. D., Schneider, F. D., Kattge, J., Poelen, J. H., Madin, J. S., et al. (2020) · Nature Ecology & Evolution · doi:10.1038/s41559-020-1167-9 · Cited by 2

Global and national trends in documenting and monitoring species distributionsPreprint

Oliver, R. Y., Meyer, C., Ranipeta, A., Winner, K., & Jetz, W. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.03.367011 · Cited by 2

A deep neural network for multi-species fish detection using multiple acoustic camerasPreprint

Garcia, G. F., Martignac, F., Nevoux, M., Beaulaton, L., & Corpetti, T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.10664 · Cited by 2

Operations Research and Cost-Effective Spatial Conservation Planning: Data, Models, Tools and Future DirectionsPreprint

Alagador, D., & Cerdeira, J. O. (2021) · Preprints.org · doi:10.20944/preprints202112.0035.v1 · Cited by 2

Standardized NEON organismal data for biodiversity researchPreprint

Li, D., Record, S., Sokol, E., Bitters, M. E., Chen, M. Y., Chung, A., Helmus, M. R., Jaimes, R., Jansen, L., & Jarzyna, M. A. (2021) · doi:10.32942/osf.io/8kun3 · Cited by 2

Can Blockchain Technology Incentivize Open Ecological Data?Preprint

Lewis, R. J., Marstein, K., & Grytnes, J. (2022) · doi:10.22541/au.165425582.25694240/v1 · Cited by 2

Guidance framework to apply good practices in ecological data analysis: Lessons learned from building Galaxy-EcologyPreprint

Royaux, C., Mihoub, J., Jossé, M., Pelletier, D., Norvez, O., Reecht, Y., Fouilloux, A., Rasche, H., Hiltemann, S., Batut, B., et al. (2024) · doi:10.32942/x2g033 · Cited by 2

Translational Edge and Cloud Computing to Advance Lake Water Quality Forecasting

Figueiredo, R., Carey, C. C., & Thomas, R. Q. (2024) · Computing in Science & Engineering · doi:10.1109/mcse.2024.3430148 · Cited by 1

Indigenous owned aquatic monitoring programs in the Inuvialuit Settlement Region work: an adaptive framework with example traditional and local knowledge quotes and coastal marine water quality data collected from 2019 to 2022 near Sachs Harbour and Ulukhaktok

Akhiatak, K. P., Akoaksion, J., Alanak, T., Drost, H., Esau, W., Haogak, C., Harry, J., Inuktalik, R., Johnston, P., Joss, C., et al. (2025) · Arctic Science · doi:10.1139/as-2024-0005 · Cited by 1

A novel approach to field data augmentation with remote sensing and machine learning in rangelands

Schmidt, H. E., Leyton, J. M. O., Noa-Yarasca, E., Popescu, S., Jones, J. J., Wied, J. P., & Wu, X. B. (2025) · Ecological Informatics · doi:10.1016/j.ecoinf.2025.103353 · Cited by 1

Development of ecocentric radiation protection: issues, challenges and approaches

Mothersill, C. E., Desai, R., Alonzo, F., Ariyoshi, K., Bonisoli‐Alquati, A., Bradshaw, C., Bréchignac, F., Byun, S. H., Chauhan, V., Cresswell, T., et al. (2025) · International Journal of Radiation Biology · doi:10.1080/09553002.2025.2595632 · Cited by 1

Design and Evaluation of an LLM-Based Knowledge Graph System for Photosynthesis Research

Yoon, S., & Ahn, T. K. (2026) · IEEE Access · doi:10.1109/access.2026.3654178 · Cited by 1

Putting FAIR into practice for ecologists: How to make ecological data more reusable

Jantzen, C., & Vriend, S. J. G. (2026) · Ecological Informatics · doi:10.1016/j.ecoinf.2026.103712 · Cited by 2

Classifying behaviors from animal-borne cameras using machine learning: automated identification of breathing events in sea turtles

Robinson, N. J., Mazumdar, P., Allan, B. F., Aguzzi, J., Chen, B., Hsieh, B.-Y., Millet, L., Tomás, J., Terstriep, J., & Soliman, A. (2026) · Journal of Experimental Biology · doi:10.1242/jeb.251688 · Cited by 1

How beech ecophysiology shapes temperate forest gross primary productivity – Part 2: Identifying critical timeframes across phenological stages

Bitton, J., Heinesch, B., Charles, C., & Longdoz, B. (2026) · Biogeosciences · doi:10.5194/bg-23-6491-2026 · Cited by 1

A survey review on individual perception of environmental awareness in Andhra Pradesh

Teja, K., Krishna, C. V. M., Rao, K. V. S., & Sai, P. C. (2023) · Environmental Progress & Sustainable Energy · doi:10.1002/ep.14229 · Cited by 1

Using a Cost-Distance Time-Geographic Approach to Identify Red Deer Habitat Use in Banff National Park, Alberta, Canada

Ho, K., & Loraamm, R. W. (2023) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi12080339 · Cited by 1

Two Open Access datasets from the digitization of 50,493 herbarium sheets from Pondicherry and Baroda collections with a focus on the Western Ghats

ANDRIEU, J., Ayyappan, N., Balachandran, N., Balasubramanian, D., Engineer, R., Chandrasegarane, P., Rajput, K., Kothandapani, R., Ramakrishnan, S., & Nagar, P. S. (2023) · Biogeographia – The Journal of Integrative Biogeography · doi:10.21426/b638262151 · Cited by 1

Christmas Bird Count data are a reliable harvest-independent index for Ruffed Grouse monitoring in the eastern United States

Geary, B., Williams, L., Long, C. R., Tyl, R. M., & Gagne, R. B. (2024) · Ornithological Applications · doi:10.1093/ornithapp/duae011 · Cited by 1

Uncovering the ecology in big-data by hierarchizing multi-scale environmental effects

Vercken, E. (2024) · Peer Community In Ecology · doi:10.24072/pci.ecology.100634 · Cited by 1

Newcomb-Benford number law and ecological processes

Davic, R. D. (2025) · PLoS ONE · doi:10.1371/journal.pone.0310205 · Cited by 1

Phantasms of a feminist ecology: interdisciplinarity across the generations

Simha, A., & Subramaniam, B. (2025) · Feminist Theory · doi:10.1177/14647001251340923 · Cited by 1

The most prevalent perceived barriers to sharing research data at the point of manuscript acceptance in health and life sciences: a survey at the University of Bristol

Bajraktari, R., Booth, F., Munafo, M. R., & Beazley‐Long, N. (2025) · F1000Research · doi:10.12688/f1000research.161819.2

Futuring: Trends in Fire Science and Management

Rego, F. C., Morgan, P., Fernandes, P. M., & Hoffman, C. M. (2021) · Springer textbooks in earth sciences, geography and environment · doi:10.1007/978-3-030-69815-7_14 · Cited by 2

Bayesian models for spatially explicit interactions between neighbouring plants

Barber, C., Zaiats, A., Applestein, C. V., Rosenthal, L. M., & Caughlin, T. T. (2022) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13998 · Cited by 1

Rapid Prototyping of Species Classifiers using Deep Learning: A Guide for Non-ExpertsPreprint

Chege, H. N. (2020) · doi:10.22541/au.159493450.09431478 · Cited by 1

EcoScape: A Model for Species-Specific Functional Habitat ConnectivityPreprint

Ocampo‐Peñuela, N., de Alfaro, L., Tai, J., Valett, N., Adler, C., & Nazarov, A. (2023) · Research Square · doi:10.21203/rs.3.rs-3650354/v1 · Cited by 4

From Competition to Collaboration: Fostering a Culture of Data Sharing in the NIH HEAL Data Ecosystem

Barnes, H. L., Farlow, B., Marshall, M. P., Gartland-Gray, A., Bradford, K., Engle, M. L., & Martin, B. L. (2025) · doi:10.3768/rtipress.2025.op.0095.2501 · Cited by 2

Hearing and Seeing Through the Soils: A Review of New Sensing Technologies to Monitor Soil Invertebrate ActivityPreprint

Belaud, E., Jourdan, C., Capowiez, Y., & Hedde, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5179879 · Cited by 1

Profiling plants to predict range dynamics under climate warming

Radny, J. (2019) · doi:10.53846/goediss-7636

Techniques for the Study of Long-Term Dynamics: Analyzing Time Series

Henderson, P. A. (2021) · doi:10.1093/oso/9780198862277.003.0015

¡Se puede entender cómo funcionan Git y GitHub!

Astigarraga, J., & Cruz‐Alonso, V. (2022) · Ecosistemas · doi:10.7818/ecos.2332

Relational Systems Ecology: The Anticipatory Niche and Complex Model Coupling

Kineman, J. J., & Wessman, C. A. (2020) · Springer eBooks · doi:10.1007/978-981-13-0370-8_79-1

Prototyping Artificial Intelligent Classifiers using Deep LearningPreprint

Chege, H. N. (2022) · doi:10.22541/au.159493450.09431478/v3

Rapid Prototyping of Species Classifiers using Deep Learning: A Guide for Non-ExpertsPreprint

Chege, H. N. (2022) · doi:10.22541/au.158316446.65534248/v2

Rapid Prototyping of Species Classifiers using Deep LearningPreprint

Chege, H. N. (2022) · doi:10.22541/au.158316446.65534248/v3

An Automated and Scalable ML Solution for Mapping Invasive Species: the Case of the Australian Tree Fern in Hawaiian Forests

Iancu, O. D., Yang, K., Man, H., & Menard, T. C. (2023) · IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw58289.2023.00019

Big data technologies: Application in ecology

Nazarov, D. M., Sulimin, V. V., & Shvedov, V. V. (2023) · AIP conference proceedings · doi:10.1063/5.0161803

The Future Developments in Biogeochemistry

Campbell, M. O. (2023) · Springer eBooks · doi:10.1007/978-3-031-47017-2_8

Standardized NEON Organismal Data for Biodiversity Research

Li, D., Record, S., Sokol, E., Bitters, M. E., Chen, M. Y., Chung, Y., Helmus, M. R., Jaimes, R., Jansen, L., Jarzyna, M. A., et al. (2024) · doi:10.21079/11681/48421

Harmonising distributed tree inventory datasets across India can fill critical gaps in tropical ecologyPreprint

Anujan, K., Mohanbabu, N., Gopal, A., Surendra, A., Krishnan, A., Jayanth, A., Nair, T., Ongole, S., & Sankaran, M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.18.594774

Trends in research approaches and gender in plant ecology dissertations over four decades

Poddar, U., Lam, K., & Gurevitch, J. (2024) · Ecology and Evolution · doi:10.1002/ece3.11554

Captive trials of a potential predator exclusion device for kea (Nestor notabilis) burrows and analysis of burrow monitoring footage.

Ireland, M. (2024) · doi:10.26686/wgtn.26046817

Tidyverse: colección de paquetes de R para la ciencia de datos

Lorente-Casalini, O., Rodes‐Blanco, M., Aguirre-Iglesias, S., Martín‐Ávila, J. A., Molina, D. S. S., Tijerín‐Triviño, J., & Astigarraga, J. (2024) · Ecosistemas · doi:10.7818/ecos.2745

Perspective Chapter: Insect Conservation, Machine Learning, and Citizen Science Take Flight

Prudic, K. L. (2024) · Environmental sciences · doi:10.5772/intechopen.115302 · Cited by 1

Digital Forensics in Cybersecurity: Roles, Responsibilities, and Strategies

Qurashi, M. A., & Alzahrani, E. (2024) · Algorithms for intelligent systems · doi:10.1007/978-981-97-5791-6_17

Ethologists assemble - macrobehaviour needs you

Keith, S. A. (2025) · acta ethologica · doi:10.1007/s10211-025-00458-y

Wasp‐Hive Candidate Site Search System Using a Small Drone

Kim, B., Pak, J., & Son, H. I. (2025) · Entomological Research · doi:10.1111/1748-5967.70034 · Cited by 1

Digitization and Sustainable Development

Bhanumathi, P., Hemavathi, G. P., Jeevitha, R., & Seema, S. (2025) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9789815305548125010006

Implementation for Lightweight Deep Learning for Anomaly Detection and Denoising on Gravitational Waves

Niranjen, R. K. M., Yogesh, C. K., Vinodh, A., Sureshkumar, T., & Vatchala, S. (2025) · IEEE Access · doi:10.1109/access.2025.3562595

Enabling data‐driven collaborative and reproducible environmental synthesis science

Brun, J., Lyon, N. J., Chen, A., Slette, I. J., Rosa, G. D. L., Caselle, J. E., Davis, F. W., & Downs, M. R. (2025) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.70036 · Cited by 2

The perceived barriers to data sharing in health and life sciences: a survey at the University of Bristol

Bajraktari, R., Booth, F., Munafo, M. R., & Beazley‐Long, N. (2025) · F1000Research · doi:10.12688/f1000research.161819.1

Citizen scientists for MoveApps : Innovations and insights from volunteer coders in wildlife conservation

Kölzsch, A., Safi, K., Armfield, M., Beaupre, C. J., Bennitt, E., Böck, M., Brown, W., Eichler, C., Fielder, W., Hahn, C., et al. (2025) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.70101

Occupancy Modeling for Rare Species Using Large Datasets: A Subsampling Approach

de Haan‐Ward, J., Bonner, S. J., & Woolford, D. G. (2025) · Environmetrics · doi:10.1002/env.70023

Environmental safety in the digital age: new methods and approaches

Shchekotin, E. V. (2025) · SOCIETY AND SECURITY INSIGHTS · doi:10.14258/ssi(2025)2-07

A Web App for the Animal Culture Database and a Template for Deploying Comparative Trait Databases With Shiny

Basava, K., & Román‐Palacios, C. (2025) · Ecology and Evolution · doi:10.1002/ece3.71913

Simple Bagged Movement Models for Telemetry Data

Whetten, A., Hefley, T. J., Haukos, D. A., & Brewer, D. E. (2025) · Ecology and Evolution · doi:10.1002/ece3.72060

Flexible Metadata Harvesting for Ecology Using Large Language Models

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