[{"intvolume":"        17","researchdata_availability":"yes","year":"2026","status":"public","PlanS_conform":"1","issue":"4","type":"journal_article","date_created":"2026-03-15T23:01:36Z","oa":1,"date_published":"2026-04-01T00:00:00Z","publication_status":"published","fulldoi":"https://doi.org/10.1111/2041-210x.70277","publication":"Methods in Ecology and Evolution","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"OA_type":"gold","article_type":"original","quality_controlled":"1","file":[{"success":1,"content_type":"application/pdf","file_id":"22422","creator":"dernst","file_size":7154332,"file_name":"2026_MethodsEcologyEvolution_Oh.pdf","date_created":"2026-07-27T11:30:53Z","access_level":"open_access","date_updated":"2026-07-27T11:30:53Z","relation":"main_file","checksum":"5f2a44daa57f757c8d5226bb3d80680b"}],"volume":17,"supplementarymaterial":"yes","ec_funded":1,"OA_place":"publisher","das_tickbox":"1","page":"1218-1234","author":[{"full_name":"Oh, Jinook","first_name":"Jinook","last_name":"Oh","orcid":"0000-0001-7425-2372","id":"403169A4-080F-11EA-9993-BF3F3DDC885E"},{"full_name":"Cremer, Sylvia","first_name":"Sylvia","orcid":"0000-0002-2193-3868","id":"2F64EC8C-F248-11E8-B48F-1D18A9856A87","last_name":"Cremer"}],"day":"01","publisher":"Wiley","_id":"21453","date_updated":"2026-07-27T11:31:10Z","ddc":["570"],"acknowledgement":"We thank Harikrishnan Rajendran for discussion. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement No. 771402; EPIDEMICSonCHIP to S.C.). Open Access funding provided by Institute of Science and Technology Austria/KEMÖ.","external_id":{"biorxivid":["10.1101/2025.08.11.669637"]},"biorxivid":1,"title":"ALTAA: Analysis of long-term activity patterns in ant colonies","DOAJ_listed":"1","article_processing_charge":"Yes","citation":{"chicago":"Oh, Jinook, and Sylvia Cremer. “ALTAA: Analysis of Long-Term Activity Patterns in Ant Colonies.” <i>Methods in Ecology and Evolution</i>. Wiley, 2026. <a href=\"https://doi.org/10.1111/2041-210x.70277\">https://doi.org/10.1111/2041-210x.70277</a>.","short":"J. Oh, S. Cremer, Methods in Ecology and Evolution 17 (2026) 1218–1234.","ama":"Oh J, Cremer S. ALTAA: Analysis of long-term activity patterns in ant colonies. <i>Methods in Ecology and Evolution</i>. 2026;17(4):1218-1234. doi:<a href=\"https://doi.org/10.1111/2041-210x.70277\">10.1111/2041-210x.70277</a>","ieee":"J. Oh and S. Cremer, “ALTAA: Analysis of long-term activity patterns in ant colonies,” <i>Methods in Ecology and Evolution</i>, vol. 17, no. 4. Wiley, pp. 1218–1234, 2026.","ista":"Oh J, Cremer S. 2026. ALTAA: Analysis of long-term activity patterns in ant colonies. Methods in Ecology and Evolution. 17(4), 1218–1234.","mla":"Oh, Jinook, and Sylvia Cremer. “ALTAA: Analysis of Long-Term Activity Patterns in Ant Colonies.” <i>Methods in Ecology and Evolution</i>, vol. 17, no. 4, Wiley, 2026, pp. 1218–34, doi:<a href=\"https://doi.org/10.1111/2041-210x.70277\">10.1111/2041-210x.70277</a>.","apa":"Oh, J., &#38; Cremer, S. (2026). ALTAA: Analysis of long-term activity patterns in ant colonies. <i>Methods in Ecology and Evolution</i>. Wiley. <a href=\"https://doi.org/10.1111/2041-210x.70277\">https://doi.org/10.1111/2041-210x.70277</a>"},"file_date_updated":"2026-07-27T11:30:53Z","doi":"10.1111/2041-210x.70277","abstract":[{"lang":"eng","text":"1. Collective behaviours are a fascinating study area due to the emergent properties that can only arise in groups of interacting individuals. However, their quantitative study is often impaired by technical difficulties, creating either low-quality and sparse data or impractical data amounts, particularly when capturing large groups over long periods of time. Common challenges arise from recording group members with as little obscuring of each other as possible, as well as in generating manageable data amounts with as high as possible information content.\r\n2. We here provide a multicomponent system that allows to record, analyse and simulate the long-term spatiotemporal activity patterns of insect collectives, especially ant colonies. Our Ant Observing System, ALTAA, comprises a flat-nest design to prevent occlusion of individuals, a recording system running on a low-power single-board-computer, and a set of computer programmes performing quantitative analyses to guide the formation and validation of rules underlying the observed collective patterns. Our system is scalable in that it allows parallel, continuous observation of a high number of colonies using low memory space, with colony maintenance requirements (e.g. feeding, nest humidity) being achieved at lowest possible disturbance by the experimenter.\r\n3. We showcase the potential of the system in a study using the black garden ant, Lasius niger, where we analyse the spatiotemporal effects of different group sizes (1, 6, 10 ants), brood (larvae) presence or absence, as well as of different nest geometries, over a period of 1 week. We show that the ants' motion activity has a weak periodicity in the range of 20 to 120 min promoted by larval presence, and that ants are spatially attracted to their larvae, the water source and the walls. We also find that the presence of nestmates lowers an individual ant's motion activity. Observed data are compared to simulations of the temporal activity of the ants.\r\n4. ALTAA provides a powerful toolkit to quantify and interpret spatial and temporal collective activity patterns in (social) insects over extended periods."}],"publication_identifier":{"eissn":["2041-210X"]},"corr_author":"1","has_accepted_license":"1","department":[{"_id":"SyCr"}],"project":[{"_id":"2649B4DE-B435-11E9-9278-68D0E5697425","name":"Epidemics in ant societies on a chip","call_identifier":"H2020","grant_number":"771402"}],"dataavailabilitystatement":"Data available via https://doi.org/10.5281/zenodo.16893940 (Oh, 2025), and the code is available at Github, https://github.com/jinook0707/CremerGroupApp.","oa_version":"Published Version","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"04","scopus_import":"1"},{"intvolume":"         6","extern":"1","year":"2015","status":"public","issue":"1","type":"journal_article","date_created":"2022-08-16T06:43:49Z","oa":1,"date_published":"2015-01-01T00:00:00Z","publication_status":"published","fulldoi":"https://doi.org/10.1111/2041-210x.12299","publication":"Methods in Ecology and Evolution","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"article_type":"original","pmid":1,"quality_controlled":"1","file":[{"creator":"asandaue","file_size":411415,"success":1,"content_type":"application/pdf","file_id":"11846","relation":"main_file","date_updated":"2022-08-16T06:52:53Z","checksum":"880e78f09f0ac99cb351c48dc97623b6","file_name":"2015_MethodsInEcologyAndEvolutionChernomor.pdf","date_created":"2022-08-16T06:52:53Z","access_level":"open_access"}],"volume":6,"page":"83-91","author":[{"last_name":"Chernomor","full_name":"Chernomor, Olga","first_name":"Olga"},{"first_name":"Bui Quang","full_name":"Minh, Bui Quang","last_name":"Minh"},{"last_name":"Forest","full_name":"Forest, Félix","first_name":"Félix"},{"last_name":"Klaere","first_name":"Steffen","full_name":"Klaere, Steffen"},{"last_name":"Ingram","full_name":"Ingram, Travis","first_name":"Travis"},{"first_name":"Monika H","full_name":"Henzinger, Monika H","orcid":"0000-0002-5008-6530","id":"540c9bbd-f2de-11ec-812d-d04a5be85630","last_name":"Henzinger"},{"last_name":"von Haeseler","first_name":"Arndt","full_name":"von Haeseler, Arndt"}],"day":"01","publisher":"Wiley","_id":"11845","date_updated":"2024-11-06T12:16:55Z","ddc":["570"],"external_id":{"pmid":["25893087"]},"title":"Split diversity in constrained conservation prioritization using integer linear programming","article_processing_charge":"No","citation":{"ista":"Chernomor O, Minh BQ, Forest F, Klaere S, Ingram T, Henzinger M, von Haeseler A. 2015. Split diversity in constrained conservation prioritization using integer linear programming. Methods in Ecology and Evolution. 6(1), 83–91.","ieee":"O. Chernomor <i>et al.</i>, “Split diversity in constrained conservation prioritization using integer linear programming,” <i>Methods in Ecology and Evolution</i>, vol. 6, no. 1. Wiley, pp. 83–91, 2015.","ama":"Chernomor O, Minh BQ, Forest F, et al. Split diversity in constrained conservation prioritization using integer linear programming. <i>Methods in Ecology and Evolution</i>. 2015;6(1):83-91. doi:<a href=\"https://doi.org/10.1111/2041-210x.12299\">10.1111/2041-210x.12299</a>","chicago":"Chernomor, Olga, Bui Quang Minh, Félix Forest, Steffen Klaere, Travis Ingram, Monika Henzinger, and Arndt von Haeseler. “Split Diversity in Constrained Conservation Prioritization Using Integer Linear Programming.” <i>Methods in Ecology and Evolution</i>. Wiley, 2015. <a href=\"https://doi.org/10.1111/2041-210x.12299\">https://doi.org/10.1111/2041-210x.12299</a>.","short":"O. Chernomor, B.Q. Minh, F. Forest, S. Klaere, T. Ingram, M. Henzinger, A. von Haeseler, Methods in Ecology and Evolution 6 (2015) 83–91.","apa":"Chernomor, O., Minh, B. Q., Forest, F., Klaere, S., Ingram, T., Henzinger, M., &#38; von Haeseler, A. (2015). Split diversity in constrained conservation prioritization using integer linear programming. <i>Methods in Ecology and Evolution</i>. Wiley. <a href=\"https://doi.org/10.1111/2041-210x.12299\">https://doi.org/10.1111/2041-210x.12299</a>","mla":"Chernomor, Olga, et al. “Split Diversity in Constrained Conservation Prioritization Using Integer Linear Programming.” <i>Methods in Ecology and Evolution</i>, vol. 6, no. 1, Wiley, 2015, pp. 83–91, doi:<a href=\"https://doi.org/10.1111/2041-210x.12299\">10.1111/2041-210x.12299</a>."},"doi":"10.1111/2041-210x.12299","file_date_updated":"2022-08-16T06:52:53Z","abstract":[{"lang":"eng","text":"Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.\r\nDepending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of species for conservation action. Specifically, we discuss the use of species' geographic distributions, the choice of candidates under economic pressure, and the use of predator–prey interactions between the species in a community to define viability constraints.\r\nDespite such optimization problems falling into the area of NP hard problems, it is possible to solve them in a reasonable amount of time using integer programming. We apply integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure.\r\nWe exemplarily show the results for two data sets: the Cape region of South Africa and a Caribbean coral reef community. Finally, we provide user-friendly software at http://www.cibiv.at/software/pda."}],"publication_identifier":{"eissn":["2041-210X"]},"has_accepted_license":"1","oa_version":"Published Version","language":[{"iso":"eng"}],"month":"01","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","scopus_import":"1"}]