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Record W4220995887 · doi:10.1016/j.tree.2021.11.011

Biological Earth observation with animal sensors

2022· article· en· W4220995887 on OpenAlexafffund
Walter Jetz, Grigori Tertitski, Roland Kays, U. Mueller, Martin Wikelski, Susanne Åkesson, Yury Anisimov, Aleksey Antonov, Walter Arnold, Franz Bairlein, Oriol Baltà, Diane Baum, Mario Beck, Olga Belonovich, Mikhail Belyaev, Matthias Berger, Peter Berthold, Steffen Bittner, Stephen Blake, Barbara A. Block, Daniel A. F. Bloche, Katrin Boehning‐Gaese, Gil Bohrer, Julia Bojarinova, G. Bommas, O. V. Bourski, Albert Bragin, Alexandr Bragin, Rachel Bristol, Vojtěch Brlík, Victor N. Bulyuk, Francesca Cagnacci, Taylor K. Chapple, Kalkidan F. Chefira, Yachang Cheng, Nikita Chernetsov, Grzegorz Cierlik, Simon S. Christiansen, Oriol Clarabuch, William D. Cochran, Jamie M. Cornelius, Iain D. Couzin, Margret C. Crofoot, Sebastián Cruz, Alexander A. Davydov, Sarah C. Davidson, Stefan Dech, Dina K. N. Dechmann, E. Yu. Demidova, Jan Dettmann, Sven Dittmar, Dmitry Dorofeev, Detlev Drenckhahn, V. M. Dubyanskiy, Н. В. Егоров, Sophie Ehnbom, Diego Ellis‐Soto, R. Ewald, C. J. Feare, Igor Fefelov, Péter Fehérvári, Wolfgang Fiedler, Andrea Flack, Magnus Froböse, Ivan Fufachev, Pavel A. Futoran, Vyachaslav Gabyshev, Anna Gagliardo, Stefan Garthe, Sergey I. Gashkov, Luke Gibson, Wolfgang Goymann, Gerd Gruppe, Chris Guglielmo, Phil Hartl, Anders Hedenström, Arne Hegemann, Georg Heine, Mäggi Hieber Ruiz, Heribert Hofer, Felix Huber, Edward Hurme, Fabiola Iannarilli, Marc Illa, Arkadiy Isaev, Bent K. Jakobsen, Lukas Jenni, Brett R. Jesmer, Frédéric Jiguet, Tatiana Karimova, N. Jeremy Kasdin, Fedor Kazansky, Ruslan Kirillin, Thomas Klinner, Andreas Knopp, Andrea Kölzsch, Alexander Kondratyev, Marco Krondorf, Pavel Ktitorov, Olga V. Kulikova, Rahul Kumar, Claudia Künzer, Anatoliy Larionov, C. Larose, Félix Liechti, Nils Linek, Ashley Lohr, А. А. Лущекина, Kate Mansfield, Maria Matantseva, Mikhail Markovets, Peter P. Marra, Juan F. Masello, Jörg Melzheimer, Myles H. M. Menz, Stephen Menzie, Swetlana Meshcheryagina, Dale G. Miquelle, Vladimir A. Morozov, Andrey Mukhin, Inge Müller, Thomas Mueller, Juan G. Navedo, Ran Nathan, L.S. Nelson, Zoltán Németh, Scott Newman, Ryan W. Norris, Olivier Nsengimana, И. М. Охлопков, Wioleta Oleś, Ruth Y. Oliver, Teague M. O'Mara, Péter Palatitz, Jesko Partecke, Ryan Pavlick, Anastasia Pedenko, Alys Perry, Julie Pham, Daniel Piechowski, Allison Pierce, Theunis Piersma, Wolfgang Pitz, Dirk Plettemeier, Irina D. Pokrovskaya, Liya Pokrovskaya, Ivan Pokrovsky, Morrison T. Pot, Petr Procházka, Petra Quillfeldt, Eldar Rakhimberdiev, Marilyn Ramenofsky, Ajay Ranipeta, Jan Rapczyński, Magdalena Remisiewicz, В. В. Рожнов, Froukje Rienks, Christian Rutz, В. В. Сахвон, Nir Sapir, Kamran Safi, Friedrich Schäuffelhut, David Schimel, Andreas Schmidt, Judy Shamoun‐Baranes, Alexander Sharikov, Laura Shearer, Evgeny Shemyakin, Sherub Sherub, Yanina V. Sica, Thomas B. Smith, Sergey Simonov, Katherine R. S. Snell, Aleksandr Sokolov, Vasiliy Sokolov, Olga N Solomina, Mikhail Soloviev, Fernando Spina, Kamiel Spoelstra, Martin Storhas, Т. А. Свиридова, George W. Swenson, Phil Taylor, Kasper Thorup, Arseny Tsvey, Marlee A. Tucker, Sophie Tuppen, Woody Turner, Innocent Twizeyimana, Henk P. van der Jeugd, Louis van Schalkwyk, Mariëlle L. van Toor, Pauli Viljoen, Marcel E. Visser, Tamara Volkmer, А А Волков, С. В. Волков, O. N. Volkov, Jan A. C. von Rönn, Bernd Vorneweg, Bettina Wachter, Jonas Waldenström, Natalie Weber, Martin Wegmann, Aloysius Wehr, Rolf Weinzierl, Johannes Weppler, David S. Wilcove, Timm A. Wild, Hannah J. Williams, John H. Wilshire, John C. Wingfield, Michael B. Wunder, A. A. Yachmennikova, Scott W. Yanco, Elisabeth Yohannes, Amelie Zeller, Christian Ziegler, Anna Zięcik, Cheryl Zook

Bibliographic record

VenueTrends in Ecology & Evolution · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsAcadia UniversityUniversity of GuelphWestern University
FundersCenter for Makroøkologi, Evolution og KlimaRussian Academy of SciencesLeibniz-GemeinschaftCalifornia Department of Fish and WildlifeUniversity of Illinois at Urbana-ChampaignPrinceton UniversitySorbonne UniversitéUniversität KonstanzSouthern University of Science and TechnologyDirectorate for Biological SciencesUniversidad Austral de ChileSenckenberg Biodiversität und Klima ForschungszentrumUniversität StuttgartFar East Branch, Russian Academy of SciencesDebreceni EgyetemJulius-Maximilians-Universität WürzburgKoninklijke Nederlandse Akademie van WetenschappenRadboud UniversiteitLomonosov Moscow State UniversityTomsk State UniversityNational Aeronautics and Space AdministrationGeorgetown UniversityWildlife Conservation SocietyMuséum National d'Histoire NaturelleUniversità di PisaJustus Liebig Universität GießenLeibniz-Institut für Zoo- und WildtierforschungUral Branch, Russian Academy of SciencesDeutsches Zentrum für Luft- und RaumfahrtCentre National de la Recherche ScientifiqueUniversity of Central FloridaTechnische Universität DresdenHebrew University of JerusalemLunds UniversitetNederlands Instituut voor EcologieYale UniversityChristian-Albrechts-Universität zu KielUniversity of PretoriaSmithsonian Tropical Research InstituteNederlandse Organisatie voor Wetenschappelijk OnderzoekNASA HeadquartersIrkutsk State UniversityEuropean Space AgencyRijksuniversiteit GroningenNorth Carolina Museum of Natural SciencesAcadia UniversityJet Propulsion LaboratoryLinnéuniversitetetCalifornia Institute of TechnologyUniversity of California, DavisSmithsonian Institution
KeywordsScale (ratio)Earth observationHuman animalRemote sensingEnvironmental scienceBiological motionTracking (education)Animal behaviorAnimal healthEnvironmental resource managementComputer scienceGeographyEcologyEngineeringCartographyArtificial intelligenceBiologyAerospace engineeringSatellite

Abstract

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Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmental change. Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmental change. In September 2020, a tag on the back of a Eurasian blackbird (Turdus merula) tagged in Belarus, that had migrated to its wintering grounds in Albania, switched on its transmitter as the International Space Station (ISS) passed 410 km above. The tag sent global positioning system (GPS) location data on the bird´s recent whereabouts as well as onboard sensor data, which the International Cooperation for Animal Research Using Space (ICARUS) receiver aboard the Russian Zvezda Module of the ISS picked up and returned to scientists back on Earth [1.Belyaev M. et al.Development of technology for monitoring animal migration on Earth using scientific equipment on the ISS RS.in: Proceedings of the 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS), St. Petersburg, Russia. 2020Crossref Scopus (6) Google Scholar] (Figure 1). While only 223 bytes in size, this transmission rang in a new epoch for space-based Earth observations and biological sensing. The new system, based on digital Internet of Things (IoT) technology, will allow the relay of position and behavior from myriad low-cost, miniaturized tracking tags (now 4g, soon 3g, optionally solar powered) at almost global scale and in near-real time. A connected global system of thousands of mobile ‘animal sensors’ has the potential to provide a quantum leap for the biological understanding and monitoring of our planet. The environmental associations of animals that drive their movements, finely tuned by evolution, offer an unrivalled biological lens into these habitats themselves. This concept flips the traditional satellite-based Earth observation paradigm: rather than globe-orbiting sensors capturing images of the planet’s surface for subsequent interpretation, animals, through countless individual movement decisions, seek out their preferred conditions, sensing the quality and health of ecosystems in real time (Figure 2). Realizing this capability, however, requires engagement from agencies and scientists worldwide to support decentralized coordinated data collection and, to catalyze this engagement, a global demonstration campaign. The blackbird’s data transmission was a long-anticipated milestone (https://www.icarus.mpg.de) [1.Belyaev M. et al.Development of technology for monitoring animal migration on Earth using scientific equipment on the ISS RS.in: Proceedings of the 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS), St. Petersburg, Russia. 2020Crossref Scopus (6) Google Scholar]. With a new transmission scheme, two-way communication, and mass-produced hardware, ICARUS has not only reduced the size and cost of tracking tags but also increased the number that can be monitored concurrently. Through the ability to simultaneously return data from millions of ‘wearables for wildlife’, ICARUS complements existing satellite (Argos, Iridium) and ground-based (e.g., GSM, IoT) networks to dramatically expand the number and diversity of animals that can be tracked. The initial drive for animal tracking has come from animal behavior and migration research. Earlier generations of GPS tags revealed previously unknown migration paths and seasonal gatherings, identified vital corridors and refugia in conservation, and documented important epidemiological links [2.Kays R. et al.Terrestrial animal tracking as an eye on life and planet.Science. 2015; 348: eaaa2478Crossref Scopus (721) Google Scholar,3.Hussey N.E. et al.Aquatic animal telemetry: a panoramic window into the underwater world.Science. 2015; 348: 1255642Crossref PubMed Scopus (715) Google Scholar,10.Tian H. et al.Avian influenza H5N1 viral and bird migration networks in Asia.Proc. Natl. Acad. Sci. U. S. A. 2015; 112: 172-177Crossref PubMed Scopus (123) Google Scholar]. Data growth and collaboration have enabled some of the first comparative studies discovering behavioral adjustments to human land use [4.Tucker M.A. et al.Moving in the Anthropocene: global reductions in terrestrial mammalian movements.Science. 2018; 359: 466-469Crossref PubMed Scopus (487) Google Scholar] and changes of movements across the Arctic due to climate change [5.Davidson S.C. et al.Ecological insights from three decades of animal movement tracking across a changing Arctic.Science. 2020; 370: 712-715Crossref PubMed Scopus (35) Google Scholar]. In addition, they have stimulated excitement about the emergence of an entirely new type of animal sentinel-based evidence supporting biodiversity conservation in a rapidly changing world [6.Rutz C. et al.COVID-19 lockdown allows researchers to quantify the effects of human activity on wildlife.Nat. Ecol. Evol. 2020; 4: 1156-1159Crossref PubMed Scopus (219) Google Scholar,7.Jetz W. et al.Essential biodiversity variables for mapping and monitoring species populations.Nat. Ecol. Evol. 2019; 3: 539-551Crossref PubMed Scopus (150) Google Scholar,11.Turner W. Sensing biodiversity.Science. 2014; 346: 301-302Crossref PubMed Scopus (148) Google Scholar]. Unlike the caged canary in the coal mine, free-ranging animals pick their own paths and are thus naturally intelligent sensors, fine-tuned by evolution. They actively seek out, or avoid, a set of environmental conditions and show distinct reactions to unusual weather, storms, and some natural disasters [8.Wikelski M. Tertitski G. Living sentinels for climate change effects.Science. 2016; 352: 775-776Crossref PubMed Scopus (23) Google Scholar]. When linked to concurrently remotely sensed data from satellites, and through sensors’ onboard tags, their movement tracks record individually encountered environmental conditions. This enables an unprecedented quantification of the habitat use, environmental niches and ecological boundaries of animals and, with baseline data in place, real-time monitoring of change. Thereby, tracked animals can add essential biological meaning to the vast, ongoing remote-sensing data collection and act as canaries in the coal mine set free: signalers and sentinels of environmental conditions through their selection, avoidance, or death. The satellite–animal interlink could extend to active digital handholding: satellites could be tasked with following particular individuals for extra information or, in real time, tune into those showing abnormal behavior or sudden avoidance of places expected to be suitable. Agencies or conservation groups could receive alerts if typically used habitats or conservation areas are suddenly avoided or cause death (e.g., due to illegal encroachment or hunting). Such a system would substantially enhance ecological-change detection from remotely sensed signals, complementing existing data and approaches, for example, for remotely sensed deforestation alerts or spatially fixed conservation technology, such as camera traps. Imagine a representative set of 100 000 animals from 500 species equipped with space-based GPS tracking tags that deliver half-hourly data. At a 3g tag size, such a system is able to address around 40% of birds and over 50% of mammals (i.e., a total of ca 7000 potential species) and hundreds of species of crocodiles, turtles, and large lizards (for a 5% weight limit). This expanded hyper-speciose taxonomic (and geographic) scope opens an entirely new phase of animal-based Earth observation. Deploying this many tags is certainly a challenge, but remember, the ISS-tracked blackbird was preceded by tens of thousands of blackbirds equipped with leg bands instead. Thanks to a vast international network of volunteers, ca 3.5 million individual birds have been captured and marked every year since 1960, globally [9.Kestenholz M. et al.Bird Ringing for Science and Conservation. EURING, 2011Google Scholar] (with <1% ever resighted or recovered to provide a second data point), and probably hundreds of thousands of mammals. While not all species will be straightforward or justifiable targets for GPS tags, the potential set is large enough to enable ecologically representative and global coverage. Past experience and initial ICARUS interest suggest that wildlife agencies, non-governmental organizations, scientists, and bird banders would carry the large majority of deployments, with coordination and targeted campaigns needed to ensure coverage. The International Bio-Logging Society (https://www.bio-logging.net) could play a role in supporting such a global coordination. With a receiver in place, tag hardware cost at scale decreasing to US$100 or less each, and a yearly redeployment of 50 000 new tags, this results in a US$10–15 million annual cost, tremendous value added to environmental satellite missions at a small fraction of their typical cost. We expect that, combined with other data on traits and behaviors, space–time–environment information from thousands of species will enable a more functional interpretation of the ecosystem consequences of biodiversity. Across scales of organismal organization, but also across space and time, these measurements will allow pinning down of the plasticity and adaptive potential around realized change in animal niches and space use. The detailed capture of individual lifetime tracks, when linked with environmental and individual phenotypic and genomic data, provides an unprecedented tool for evolutionary study and offers new life-history, geospatial, and environmental niche dimensions for specimens archived or exhibited in museums. For potential animal reservoirs of infectious diseases, Earth observation with animal sensors can help to identify potential hotspots of disease transmission and map and monitor the potential for long-distance and cross-border transmissions [10.Tian H. et al.Avian influenza H5N1 viral and bird migration networks in Asia.Proc. Natl. Acad. Sci. U. S. A. 2015; 112: 172-177Crossref PubMed Scopus (123) Google Scholar]. Tracking of individuals with antibodies offers epidemiologists the potential to pinpoint the location of the true hosts of zoonotics such as Ebola and coronavirus disease 2019 (COVID-19). With so many animals tracked, many intriguing stories will emerge about individual animals that will have the potential to capture the imagination of people worldwide. The tracked animals provide the daily drama that can be part of digitally-rich media campaigns around tagged individuals that support education and discovery, and can engage citizen scientists to collect ancillary observations, enriching the data record even further. The potential to adopt and follow single individuals and their fates can connect people to biodiversity issues, both at their doorstep and far away, and support educational uses and conservation funding. Realizing these opportunities will require the engagement of and contributions from government agencies, the science community, and beyond. At agency level, a shift in traditional perceptions and approaches to Earth observation and monitoring will be required, together with interagency collaboration among and within nations. The ICARUS ground-to-space IoT is designed to be an open system for any organization to join and augment the global readout capacity or leverage for an improved system. The success of the presented vision will also rely on global collaboration and coordination of biodiversity monitoring among sovereign territories. With the GEO Biodiversity Observation Network (https://geobon.org) and its associated research community, international platforms and scientific principles for globally coordinated and integrated biodiversity monitoring are in place. Through model-based integration with other biodiversity data in platforms such as Map of Life (https://mol.org), the envisioned animal-based Earth observation can inform Essential Biodiversity Variables and indicators for the tracking of progress toward international goals on maintaining ecological integrity and connectivity or provide management-relevant short-term forecasting [7.Jetz W. et al.Essential biodiversity variables for mapping and monitoring species populations.Nat. Ecol. Evol. 2019; 3: 539-551Crossref PubMed Scopus (150) Google Scholar]. As tag deployments will rely on individual scientist’s participation, a willingness to follow agreed data standards and share data is vital. Effective Earth observation via animals will thus require development and openness around new data-sharing and -use models, including the near-immediate sharing of limited anonymized information that near-real time monitoring and model-based short-term forecasting depend on. Community engagement is needed to develop effective approaches for the citation of tracking data to support appropriate attribution and recognition. As one scales this vision to a truly global endeavor, challenges certainly remain, including sufficient capacity to support best scientific practice, benefit sharing, and the engagement of regional and local stakeholders. With the ICARUS system now online, a globally coordinated ‘100 000 animal sentinels’ campaign is possible and would establish an unrivalled bioenvironmental baseline record. With the larger community engaged, it would be the start of ongoing real-time sensing of living conditions on Earth by animals themselves. Akin to hyperspectral remote sensing systems [12.Schimel D. et al.Prospects and pitfalls for spectroscopic remote sensing of biodiversity at the global scale.in: Remote Sensing of Plant Biodiversity. Springer, 2020: 503-518Crossref Scopus (9) Google Scholar], it would realize hyper-speciose, and thus multifaceted, in situ biological Earth observation. No interests are declared. Biological Earth observation with animal sensors: (Trends in Ecology and Evolution , 293–298; 2022)Jetz et al.Trends in Ecology & EvolutionMay 21, 2022In BriefSix supporting authors were omitted from the article ‘ Biological Earth observation with animal sensors ´ when it was published. The corrected supporting author list appears below. We apologise for this oversight. Full-Text PDF Open Access

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0970.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.251
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations131
Published2022
Admission routes2
Has abstractyes

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