{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T19:11:51Z","timestamp":1775502711239,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:00:00Z","timestamp":1643846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["PTDC\/ASP-PLA\/30650\/2017"],"award-info":[{"award-number":["PTDC\/ASP-PLA\/30650\/2017"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Forests"],"abstract":"<jats:p>Over the past few decades, species distribution modelling has been increasingly used to monitor invasive species. Studies herein propose to use Cellular Automata (CA), not only to model the distribution of a potentially invasive species but also to infer the potential of the method in risk prediction of Reticulitermes grassei infestation. The test area was mainland Portugal, for which an available presence-only dataset was used. This is a typical dataset type, resulting from either distribution studies or infestation reports. Subterranean termite urban distributions in Portugal from 1970 to 2001 were simulated, and the results were compared with known records from both 2001 (the publication date of the distribution models for R. grassei in Portugal) and 2020. The reported model was able to predict the widespread presence of R. grassei, showing its potential as a viable prediction tool for R. grassei infestation risk in wooden structures, providing the collection of appropriate variables. Such a robust simulation tool can prove to be highly valuable in the decision-making process concerning pest management.<\/jats:p>","DOI":"10.3390\/f13020237","type":"journal-article","created":{"date-parts":[[2022,2,4]],"date-time":"2022-02-04T11:35:17Z","timestamp":1643974517000},"page":"237","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Proof-of-Principle That Cellular Automata Can Be Used to Predict Infestation Risk by Reticulitermes grassei (Blattodea: Isoptera)"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3246-5964","authenticated-orcid":false,"given":"Jo\u00e3o G. N.","family":"Sequeira","sequence":"first","affiliation":[{"name":"BioISI-Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisbon, Campo Grande, C8 bdg, 1749-016 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1855-7451","authenticated-orcid":false,"given":"T\u00e2nia","family":"Nobre","sequence":"additional","affiliation":[{"name":"MED-Mediterranean Institute for Agriculture, Environment and Development, Instituto de Investiga\u00e7\u00e3o e Forma\u00e7\u00e3o Avan\u00e7ada, Universidade de \u00c9vora, P\u00f3lo da Mitra, Ap. 94, 7006-554 Evora, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7309-5440","authenticated-orcid":false,"given":"S\u00f3nia","family":"Duarte","sequence":"additional","affiliation":[{"name":"Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal"},{"name":"LEAF-Linking Landscape, Environment, Agriculture and Food, Tapada da Ajuda, 1349-017 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5565-6651","authenticated-orcid":false,"given":"Dennis","family":"Jones","sequence":"additional","affiliation":[{"name":"Department Wood Science and Engineering, Lule\u00e5 University of Technology, Forskargatan 1, S-93197 Skelleftea, Sweden"},{"name":"Department of Wood Processing and Biomaterials, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kam\u00fdck\u00e1 1176, Praha 6-Suchdol, 16521 Prague, Czech Republic"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6660-3128","authenticated-orcid":false,"given":"Bruno","family":"Esteves","sequence":"additional","affiliation":[{"name":"Department of Wood Engineering, Polytechnic Institute of Viseu, Av. Cor. Jos\u00e9 Maria Vale de Andrade, 3504-510 Viseu, Portugal"},{"name":"Centre for Natural Resources, Environment and Society-CERNAS-IPV Research Centre, Av. Cor. Jos\u00e9 Maria Vale de Andrade, 3504-510 Viseu, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6849-3241","authenticated-orcid":false,"given":"Lina","family":"Nunes","sequence":"additional","affiliation":[{"name":"Structures Department, National Laboratory for Civil Engineering, Av. do Brasil, 101, 1700-066 Lisbon, Portugal"},{"name":"cE3c, Centre for Ecology, Evolution and Environmental Changes, Azorean Biodiversity Group, University of Azores, 9700-042 Angra do Hero\u00edsmo, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1111\/j.1461-0248.2005.00792.x","article-title":"Predicting species distribution: Offering more than simple habitat models","volume":"8","author":"Guisan","year":"2005","journal-title":"Ecol. 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