Management conservation of ecosystem services based on artificial intelligence: a analysis of citations in Scopus
DOI:
https://doi.org/10.56294/dm20251066Keywords:
ecosystem services, artificial intelligence, sustainable development, environmental managemenAbstract
Technological development has allowed a global advance of artificial intelligence (AI), which is used as an advanced tool for the conservation of ecosystem services in order to achieve planetary sustainability. The objective of the article was to analyze the conservation of ecosystem services focused on the application of artificial intelligence based on bibliometric research. The Scopus database was used as a direct source of research. Using the 2020 prism methodology, 69 articles were quantified, considered from the year 2020 to 2025, with a notable growth of study from the year 2022 to 2024, obtaining in 2024 the maximum point with a total of 31 publications, of which environmental science is the most studied with 24 % and the country in which more research is generated is the United States with 15,84 %, followed by Italy with 14,85 %. Most of the studies involving ecosystem services seek to generate a green solution for the preservation of natural resources that provide great benefits and contribute to human wellbeing.
References
1. Demarquet Q, Rapinel S, Dufour S, Hubert-Moy L. Long-Term Wetland Monitoring Using the Landsat Archive: A Review. Remote Sensing. enero de 2023;15(3):820.
2. Blobel B, Oemig F, Ruotsalainen P, Brochhausen M, Sexton KW, Giacomini M. The Representational Challenge of Integration and Interoperability in Transformed Health Ecosystems. J Pers Med [Internet]. 2025;15(1). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215781661&doi=10.3390%2fjpm15010004&partnerID=40&md5=8576055a28d226f7efe8f8db4f8ad107
3. Kirby MG, Scott AJ, Walsh CL. A greener Green Belt? Co-developing exploratory scenarios for contentious peri-urban landscapes. Landsc Urban Plann [Internet]. 2025;255. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210531715&doi=10.1016%2fj.landurbplan.2024.105268&partnerID=40&md5=920b1088ae69680181ded06b3b2aab9b
4. Evangelista V, Scariot A, Teixeira HM, Júnior IML. Local ecological knowledge and perception as a strategy in the management of ecosystem services. J Environ Manage [Internet]. 2024;368. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200824945&doi=10.1016%2fj.jenvman.2024.122095&partnerID=40&md5=39c06fbf456a0a5bd95622db95fd4c6e
5. Nabhani A, Mardaneh E, Sjølie HK. Multi-objective optimization of forest ecosystem services under uncertainty. Ecol Model [Internet]. 2024;494. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196426068&doi=10.1016%2fj.ecolmodel.2024.110777&partnerID=40&md5=3f3615786b9952b5b1b00fe7ce5fe6f0
6. Maňas J, Kabrhel J. Land use types at the boundaries between settlements and open landscape in suburbanised settlements on the example of the Czech Republic from the perspective of the potential for planting tall vegetation. Ecol Indic [Internet]. 2024;158. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180924232&doi=10.1016%2fj.ecolind.2023.111446&partnerID=40&md5=7a56b4e27ce1587471dd0b8143cd720e
7. Ruiz I, Pompeu J, Ruano A, Franco P, Balbi S, Sanz MJ. Combined artificial intelligence, sustainable land management, and stakeholder engagement for integrated landscape management in Mediterranean watersheds. Environ Sci Policy. 2023;145:217-27.
8. Chotisarn N, Phuthong T. Mapping the landscape of marketing technology: trends, theories and trajectories in ecosystem research. Cogent Bus Manag [Internet]. 2025;12(1). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214204935&doi=10.1080%2f23311975.2024.2448608&partnerID=40&md5=3ed7513306d45fe806b959146f23ca90
9. Rojas MP, Chiappe A. Artificial Intelligence and Digital Ecosystems in Education: A Review. Tech Knowl Learn. 2024;29(4):2153-70.
10. Deléglise H, Justeau-Allaire D, Mulligan M, Espinoza JC, Isasi-Catalá E, Alvarez C, et al. Integrating multi-objective optimization and ecological connectivity to strengthen Peru’s protected area system towards the 30*2030 target. Biol Conserv [Internet]. 2024;299. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204359447&doi=10.1016%2fj.biocon.2024.110799&partnerID=40&md5=2a4636463625f13224a07de530c0d594
11. Aznarez C, Kumar S, Marquez-Torres A, Pascual U, Baró F. Ecosystem service mismatches evidence inequalities in urban heat vulnerability. Sci Total Environ [Internet]. 2024;922. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187533093&doi=10.1016%2fj.scitotenv.2024.171215&partnerID=40&md5=6b6d97b401e094f6e2afb783b113e017
12. Wu C, Lu R, Zhang P, Dai E. Multilevel ecological compensation policy design based on ecosystem service flow: A case study of carbon sequestration services in the Qinghai-Tibet Plateau. Sci Total Environ [Internet]. 2024;921. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185531452&doi=10.1016%2fj.scitotenv.2024.171093&partnerID=40&md5=2492b90aa7ce61be51955cc7f3e30a9e
13. Başkent EZ, Kašpar J. Exploring the effects of various rotation lengths on the ecosystem services within a multiple-use management framework. For Ecol Manage [Internet]. 2023;538. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151781010&doi=10.1016%2fj.foreco.2023.120974&partnerID=40&md5=b47f9b27a78c2e59795392689f113029
14. Hahn T, Eggers J, Subramanian N, Toraño Caicoya A, Uhl E, Snäll T. Specified resilience value of alternative forest management adaptations to storms. Scand J For Res. 2021;36(7-8):585-97.
15. Capriolo A, Boschetto RG, Mascolo RA, Balbi S, Villa F. Biophysical and economic assessment of four ecosystem services for natural capital accounting in Italy. Ecosyst Serv [Internet]. 2020;46. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096711049&doi=10.1016%2fj.ecoser.2020.101207&partnerID=40&md5=56655bd7c2eb1078019b35e36c74916e
16. Baskent EZ. A framework for characterizing and regulating ecosystem services in a management planning context. Forests [Internet]. 2020;11(1). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078528866&doi=10.3390%2ff11010102&partnerID=40&md5=6e81186e03fbe84f56cd6418ae81d918
17. Bentley C, Rigley E, Krook J, Ramchurn SD. Transdisciplinary Skills for AI Ecosystems: Using Future Visioning to Collaboratively Unpack Skills in UK Health and Emergency Response Scenarios. Int J Semantic Computing. 2024;18(3):305-27.
18. Hirvonen N, Jylhä V, Lao Y, Larsson S. Artificial intelligence in the information ecosystem: Affordances for everyday information seeking. J Assoc Soc Inf Sci Technol. 2024;75(10):1152-65.
19. Megaro A, Carrubbo L, Polese F, Sirianni CA. Triggering a patient-driven service innovation to foster the service ecosystem well-being: a case study. TQM J. 2023;35(5):1256-74.
20. Pascual A, Giardina CP, Povak NA, Hessburg PF, Heider C, Salminen E, et al. Optimizing invasive species management using mathematical programming to support stewardship of water and carbon-based ecosystem services. J Environ Manage [Internet]. 2022;301. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116466548&doi=10.1016%2fj.jenvman.2021.113803&partnerID=40&md5=9e5b0bb1396ea625b986f9293a593368
21. Yadav N, Rakholia S, Yosef R. A Prototype Decision Support System for Tree Selection and Plantation with a Focus on Agroforestry and Ecosystem Services. Forests [Internet]. 2024;15(7). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199662392&doi=10.3390%2ff15071219&partnerID=40&md5=cf35ace8011b09f7ed572fe780722e2f
22. Mitra A, Alvarez CI, Abbasi AO, Harris NL, Shao G, Pijanowski BC, et al. Mapping Planted Forests in the Korean Peninsula Using Artificial Intelligence. Forests [Internet]. 2024;15(7). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199580600&doi=10.3390%2ff15071216&partnerID=40&md5=ea07628155f4a595be1735f2364b5c41
23. Coro G, Bove P, Baneschi I, Bertini A, Calvisi L, Provenzale A. Climate change effects on animal presence in the Massaciuccoli Lake basin. Ecol Informatics [Internet]. 2024;81. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193226427&doi=10.1016%2fj.ecoinf.2024.102644&partnerID=40&md5=de748c5e1779baab39209a6db4576558
24. Piazza N, Bebi P, Vacchiano G, Rigling A, Wohlgemuth T, Bottero A. Post-windthrow forest development in spruce-dominated mountain forests in Central Europe. For Ecol Manage [Internet]. 2024;561. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189935891&doi=10.1016%2fj.foreco.2024.121884&partnerID=40&md5=228ef7c2018280c45b5bc07417c320c1
25. Kowalkowski C, Wirtz J, Ehret M. Digital service innovation in B2B markets. J Serv Manage. 2024;35(2):280-305.
26. Valman SJ, Boyd DS, Carbonneau PE, Johnson MF, Dugdale SJ. An AI approach to operationalise global daily PlanetScope satellite imagery for river water masking. Remote Sens Environ [Internet]. 2024;301. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179014067&doi=10.1016%2fj.rse.2023.113932&partnerID=40&md5=4f41818fa020ddbfc816aee43b4dd41c
27. Müller M, Olsson PO, Eklundh L, Jamali S, Ardö J. Response and resilience to drought in northern forests revealed by Sentinel-2. Int J Remote Sens. 2024;45(15):5130-57.
28. Juvany L, Hedwall PO, Felton A, Öhman K, Wallgren M, Kalén C, et al. From simple metrics to cervid forage: Improving predictions of ericaceous shrub biomass. For Ecol Manage [Internet]. 2023;544. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163948674&doi=10.1016%2fj.foreco.2023.121120&partnerID=40&md5=60c06dbae5c21c64e54521f0e978b327
29. Katehakis DG, Filippidis D, Karamanis K, Kouroubali A, Farmaki A, Natsiavas P, et al. The smartHEALTH European Digital Innovation Hub experiences and challenges for accelerating the transformation of public and private organizations within the innovation ecosystem. Front Med [Internet]. 2024;11. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211924375&doi=10.3389%2ffmed.2024.1503235&partnerID=40&md5=998fc4f2282020e91ceec493cfba346a
30. Maass W, Agrawal A, Ciani A, Danz S, Delgadillo A, Ganser P, et al. QUASIM: Quantum Computing Enhanced Service Ecosystem for Simulation in Manufacturing. KI - Kunstl Intell [Internet]. 2024; Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208025154&doi=10.1007%2fs13218-024-00860-x&partnerID=40&md5=b8a779f1d37c7542e8986fb6e6085f3c
31. Kaartemo V, Helkkula A. Human–AI resource relations in value cocreation in service ecosystems. J Serv Manage [Internet]. 2024; Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194383036&doi=10.1108%2fJOSM-03-2023-0104&partnerID=40&md5=117eb898e2e6c771fbbd0e7a978542d2
32. Cai S. Trends and Prospects of Ecodesign in Urban Landscape Design in the Context of Artificial Intelligence. Appl Math Nonlinear Sci [Internet]. 2024;9(1). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186567869&doi=10.2478%2famns-2024-0414&partnerID=40&md5=20b0655dc144c2c30ba8b18b39d60cee
33. Jaung W. The need for human-centered design for AI robots in urban parks and forests. Urban For Urban Greening [Internet]. 2024;91. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180961888&doi=10.1016%2fj.ufug.2023.128186&partnerID=40&md5=91e1d74c2e4e247e791c8fd6ed3ed712
34. Ibn-Mohammed T, Mustapha KB, Abdulkareem M, Fuensanta AU, Pecunia V, Dancer CEJ. Toward artificial intelligence and machine learning-enabled frameworks for improved predictions of lifecycle environmental impacts of functional materials and devices. MRS Commun. 2023;13(5):795-811.
35. Velasquez-Camacho L, Etxegarai M, de-Miguel S. Implementing Deep Learning algorithms for urban tree detection and geolocation with high-resolution aerial, satellite, and ground-level images. Comput Environ Urban Syst [Internet]. 2023;105. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167972874&doi=10.1016%2fj.compenvurbsys.2023.102025&partnerID=40&md5=d47f2fc2bc7d286d3f2b28d259516931
36. Pashanejad E, Thierry H, Robinson BE, Parrott L. The application of semantic modelling to map pollination service provisioning at large landscape scales. Ecol Model [Internet]. 2023;484. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165477507&doi=10.1016%2fj.ecolmodel.2023.110452&partnerID=40&md5=b8e25444c49287fb4810d0f05a8c77ce
37. Lassalle G, Scafutto RDM, Lourenço RA, Mazzafera P, de Souza Filho CR. Remote sensing reveals unprecedented sublethal impacts of a 40-year-old oil spill on mangroves. Environ Pollut [Internet]. 2023;331. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160249163&doi=10.1016%2fj.envpol.2023.121859&partnerID=40&md5=b4e7adbbf3b2fe18d0c3c2385ae191b1
38. Gupta P, Bharat A. A hybrid scale to relate natural and built environments: a pragmatic approach to sustainable cities. Int J Sustainable Dev World Ecol. 2023;30(1):95-110.
39. Wei S, Cheng S. An artificial intelligence approach for identifying efficient urban forest indicators on ecosystem service assessment. Front Environ Sci [Internet]. 2022;10. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141042972&doi=10.3389%2ffenvs.2022.994389&partnerID=40&md5=87e44702909e973d20c34759bb2af195
40. Başkent EZ, Kašpar J. Exploring the effects of management intensification on multiple ecosystem services in an ecosystem management context. For Ecol Manage [Internet]. 2022;518. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133953193&doi=10.1016%2fj.foreco.2022.120299&partnerID=40&md5=87b267d68dbce7691d2d861f3761d974
41. Sivasankari M, Anandan R, Chamato FA. HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images. Comput Intell Neurosci [Internet]. 2022;2022. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133600471&doi=10.1155%2f2022%2f5081541&partnerID=40&md5=d10952b363e085532bdc2b8349a46bb9
42. Bindajam AA, Mallick J, Talukdar S, Islam ARMT, Alqadhi S. Integration of artificial intelligence–based LULC mapping and prediction for estimating ecosystem services for urban sustainability: past to future perspective. Arab J Geosci [Internet]. 2021;14(18). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113373959&doi=10.1007%2fs12517-021-08251-4&partnerID=40&md5=52650278d32caff03d34b6ed6891bf50
43. Mozgeris G, Mörtberg U, Pang XL, Trubins R, Treinys R. Future projection for forest management suggests a decrease in the availability of nesting habitats for a mature-forest-nesting raptor. For Ecol Manage [Internet]. 2021;491. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104940984&doi=10.1016%2fj.foreco.2021.119168&partnerID=40&md5=b436e5759a4d3ca86cf8039be58751fb
44. Durán-Vinet B, Araya-Castro K, Zaiko A, Pochon X, Wood SA, Stanton JAL, et al. CRISPR-Cas-Based Biomonitoring for Marine Environments: Toward CRISPR RNA Design Optimization Via Deep Learning. CRISPR J. 2023;6(4):316-24.
45. Spalding MD, Longley-Wood K, McNulty VP, Constantine S, Acosta-Morel M, Anthony V, et al. Nature dependent tourism – Combining big data and local knowledge. J Environ Manage [Internet]. 2023;337. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150384174&doi=10.1016%2fj.jenvman.2023.117696&partnerID=40&md5=007c6cb2f823d8050bc8119e69b08d57
46. Bruzzese S, Blanc S, Brun F. The Decision Trees Method to Support the Choice of Economic Evaluation Procedure: The Case of Protection Forests. For Sci. 2023;69(3):241-53.
47. Balan A, Gabriel Tan A, Kourtit K, Nijkamp P. Data-Driven Intelligent Platforms—Design of Self-Sovereign Data Trust Systems. Land [Internet]. 2023;12(6). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163828713&doi=10.3390%2fland12061224&partnerID=40&md5=df072cc33d7a45e9c85380be8d64d062
48. Mpatziakas A, Drosou A, Papadopoulos S, Tzovaras D. IoT threat mitigation engine empowered by artificial intelligence multi-objective optimization. J Network Comput Appl [Internet]. 2022;203. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129217028&doi=10.1016%2fj.jnca.2022.103398&partnerID=40&md5=7d04375388f47e7a3066010258f11f2e
49. Verma A, Bhattacharya P, Madhani N, Trivedi C, Bhushan B, Tanwar S, et al. Blockchain for Industry 5.0: Vision, Opportunities, Key Enablers, and Future Directions. IEEE Access. 2022;10:69160-99.
50. Bustinza OF, Molina LM, Vendrell-Herrero F, Opazo-Basaez M. AI-enabled smart manufacturing boosts ecosystem value capture: The importance of servitization pathways within digital-intensive industries. Int J Prod Econ [Internet]. 2024;277. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203828326&doi=10.1016%2fj.ijpe.2024.109411&partnerID=40&md5=9517ee4c4220f10e0a60b6add4e64e76
51. Li K, Kirkland S, Yeo BL, Tubbesing C, Bandaru V, Song L, et al. Integrated economic and environmental modeling of forest biomass for renewable energy in California: Part I - Model development. Biomass Bioenergy [Internet]. 2023;173. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151842101&doi=10.1016%2fj.biombioe.2023.106774&partnerID=40&md5=4a44766d5d297320bf16556b9e23385d
52. Mallick J, Alqadhi S, Talukdar S, Sarkar SK, Roy SK, Ahmed M. Modelling and mapping of landslide susceptibility regulating potential ecosystem service loss: an experimental research in Saudi Arabia. Geocarto Int. 2022;37(25):10170-98.
53. Shaw JA, Donia J. The Sociotechnical Ethics of Digital Health: A Critique and Extension of Approaches From Bioethics. Front Digit Health [Internet]. 2021;3. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129020558&doi=10.3389%2ffdgth.2021.725088&partnerID=40&md5=1ff10f7d2b1b4b470d9de59e1628e08c
54. Scopus - Búsqueda de documentos | Iniciar sesión [Internet]. [citado 4 de febrero de 2025]. Disponible en: https://www.scopus.com/search/form.uri?display=basic#basic
55. PRISMA statement [Internet]. [citado 4 de febrero de 2025]. PRISMA 2020 flow diagram. Disponible en: https://www.prisma-statement.org/prisma-2020-flow-diagram
56. Pilogallo A, Scorza F. Mapping Regulation Ecosystem Services Specialization in Italy. J Urban Plann Dev [Internet]. 2022;148(1). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121205329&doi=10.1061%2f%28ASCE%29UP.1943-5444.0000801&partnerID=40&md5=3501a0e5d3a0a0b0d1e2bbf7aafaceef
57. Bont LG, Fraefel M, Frutig F, Holm S, Ginzler C, Fischer C. Improving forest management by implementing best suitable timber harvesting methods. J Environ Manage [Internet]. 2022;302. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119302805&doi=10.1016%2fj.jenvman.2021.114099&partnerID=40&md5=17b8f0d84968819f44e973aa70ff3c4b
58. Yin X, Li J, Kadry SN, Sanz-Prieto I. Artificial intelligence assisted intelligent planning framework for environmental restoration of terrestrial ecosystems. Environ Impact Assess Rev [Internet]. 2021;86. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096675214&doi=10.1016%2fj.eiar.2020.106493&partnerID=40&md5=6879c4d55cc12b56af3f7c78ed8a37fd
59. Lal R. The role of industry and the private sector in promoting the “4 per 1000” initiative and other negative emission technologies. Geoderma [Internet]. 2020;378. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088820034&doi=10.1016%2fj.geoderma.2020.114613&partnerID=40&md5=4e9b871c17f18b380040ef1fcb823b76
60. Marta C, Maurizio C, Giacomo C, Marco B, Alessandro P. A social assessment of forest resource based on stakeholders’ perception: an application in three Balkans rural areas. J For Res. 2020;25(5):308-14.
61. Rinaldi F, Jonsson R. Accounting for uncertainty in forest management models. For Ecol Manage [Internet]. 2020;468. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091299635&doi=10.1016%2fj.foreco.2020.118186&partnerID=40&md5=7d47d5af49b934ace9f64f3f822379f9
62. Cavalari AA, Del Nero Velasco G, da Silva-Luz CL, Rosa AS, De Abreu Neder Waetge A, De Souza Barbosa E, et al. Predicting tree failure to define roles and guidelines in risk management, a case study in São Paulo / Brazil. Urban For Urban Greening [Internet]. 2024;91. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181023251&doi=10.1016%2fj.ufug.2023.128181&partnerID=40&md5=da23ad924312d3c49e4ca6ae6c24208e
63. Garlington B. CISE: Community Engagement of CEB Cloud Ecosystem in Box. Intl J Adv Comput Sci Appl. 2022;13(4):1-15.
64. Valeev DK, Nuriev AG, Makolkin NN. Using artificial intelligence algorithms in legal proceedings in the ecosystem services and digital economy. Caspian J Environ Sci. 2020;18(5):589-93.
65. Singh S, Sharma PK, Yoon B, Shojafar M, Cho GH, Ra IH. Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city. Sustainable Cities Soc [Internet]. 2020;63. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088643220&doi=10.1016%2fj.scs.2020.102364&partnerID=40&md5=9747810b5f9c5b2e22f58c8581e3ab06
66. Malde K, Handegard NO, Eikvil L, Salberg AB. Machine intelligence and the data-driven future of marine science. ICES J Mar Sci. 2020;77(4):1274-85.
67. Maydana G, Romagnoli M, Cunha M, Portapila M. Integrated valuation of alternative land use scenarios in the agricultural ecosystem of a watershed with limited available data, in the Pampas region of Argentina. Sci Total Environ [Internet]. 2020;714. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078654287&doi=10.1016%2fj.scitotenv.2019.136430&partnerID=40&md5=1d7276566e84add8e9518fb7fa51aad3
68. Grilli G, Fratini R, Marone E, Sacchelli S. A spatial-based tool for the analysis of payments for forest ecosystem services related to hydrogeological protection. For Policy Econ [Internet]. 2020;111. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074371037&doi=10.1016%2fj.forpol.2019.102039&partnerID=40&md5=d5375007d09ad37600c5313ec73a8448
69. Runge CA, Hausner VH, Daigle RM, Monz CA. Pan-arctic analysis of cultural ecosystem services using social media and automated content analysis. Environ Res Commun [Internet]. 2020;2(7). Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101466475&doi=10.1088%2f2515-7620%2fab9c33&partnerID=40&md5=5b2fe7b13f28c4f82531c91d8f05eba1
70. Cervelli E, Scotto di Perta E, Pindozzi S. Energy crops in marginal areas: Scenario-based assessment through ecosystem services, as support to sustainable development. Ecol Indic [Internet]. 2020;113. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079386512&doi=10.1016%2fj.ecolind.2020.106180&partnerID=40&md5=c2f6f46eae256800d84446d83b0aba02
71. Lin J. Developing a composite indicator to prioritize tree planting and protection locations. Sci Total Environ [Internet]. 2020;717. Disponible en: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079359317&doi=10.1016%2fj.scitotenv.2020.137269&partnerID=40&md5=7a3a7b1f3905002470469930c28efaab
72. Ahn S, Yim HJ, Lee Y, Park SI. Dynamic and Super-Personalized Media Ecosystem Driven by Generative AI: Unpredictable Plays Never Repeating the Same. IEEE Trans Broadcast. 2024;70(3):980-94.
Published
Issue
Section
License
Copyright (c) 2025 Juan Bladimir Aguilar-Poaquiza, Carla Sofía Arguello Guadalupe, William Patricio Cevallos-Silva, Jorge Daniel Córdova Lliquin, Carlos Eduardo Cevallos Hermida, Oscar Danilo Gavilánez Álvarez, Diego Cajamarca-Carrazco (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
