On formal limitations of causal ecological networks
Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the re...
Saved in:
| Published in | Philosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 379; no. 1909; p. 20230170 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
England
09.09.2024
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the relationship between formal logic methods used to describe causal networks and their inherent statistical and epistemological limitations. I argue that while these methods offer valuable insights, they are restricted by axiomatic assumptions, statistical constraints and the incompleteness of our knowledge. To prove that, I first consider causal networks as formal systems, define causality and formalize their axioms in terms of modal logic and use ecological counterexamples to question the axioms. I also highlight the statistical limitations when using multivariate time-series analysis and Granger causality to develop ecological networks, including the potential for spurious correlations among other data characteristics. Finally, I draw upon Gödel’s incompleteness theorems to highlight the inherent limits of fully understanding complex networks as formal systems and conclude that causal ecological networks are subject to initial rules and data characteristics and, as any formal system, will never fully capture the intricate complexities of the systems they represent.
This article is part of the theme issue ‘Connected interactions: enriching food web research by spatial and social interactions’. |
|---|---|
| AbstractList | Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the relationship between formal logic methods used to describe causal networks and their inherent statistical and epistemological limitations. I argue that while these methods offer valuable insights, they are restricted by axiomatic assumptions, statistical constraints and the incompleteness of our knowledge. To prove that, I first consider causal networks as formal systems, define causality and formalize their axioms in terms of modal logic and use ecological counterexamples to question the axioms. I also highlight the statistical limitations when using multivariate time-series analysis and Granger causality to develop ecological networks, including the potential for spurious correlations among other data characteristics. Finally, I draw upon Gödel's incompleteness theorems to highlight the inherent limits of fully understanding complex networks as formal systems and conclude that causal ecological networks are subject to initial rules and data characteristics and, as any formal system, will never fully capture the intricate complexities of the systems they represent. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the relationship between formal logic methods used to describe causal networks and their inherent statistical and epistemological limitations. I argue that while these methods offer valuable insights, they are restricted by axiomatic assumptions, statistical constraints and the incompleteness of our knowledge. To prove that, I first consider causal networks as formal systems, define causality and formalize their axioms in terms of modal logic and use ecological counterexamples to question the axioms. I also highlight the statistical limitations when using multivariate time-series analysis and Granger causality to develop ecological networks, including the potential for spurious correlations among other data characteristics. Finally, I draw upon Gödel's incompleteness theorems to highlight the inherent limits of fully understanding complex networks as formal systems and conclude that causal ecological networks are subject to initial rules and data characteristics and, as any formal system, will never fully capture the intricate complexities of the systems they represent. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'. Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the relationship between formal logic methods used to describe causal networks and their inherent statistical and epistemological limitations. I argue that while these methods offer valuable insights, they are restricted by axiomatic assumptions, statistical constraints and the incompleteness of our knowledge. To prove that, I first consider causal networks as formal systems, define causality and formalize their axioms in terms of modal logic and use ecological counterexamples to question the axioms. I also highlight the statistical limitations when using multivariate time-series analysis and Granger causality to develop ecological networks, including the potential for spurious correlations among other data characteristics. Finally, I draw upon Gödel's incompleteness theorems to highlight the inherent limits of fully understanding complex networks as formal systems and conclude that causal ecological networks are subject to initial rules and data characteristics and, as any formal system, will never fully capture the intricate complexities of the systems they represent. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'. Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the relationship between formal logic methods used to describe causal networks and their inherent statistical and epistemological limitations. I argue that while these methods offer valuable insights, they are restricted by axiomatic assumptions, statistical constraints and the incompleteness of our knowledge. To prove that, I first consider causal networks as formal systems, define causality and formalize their axioms in terms of modal logic and use ecological counterexamples to question the axioms. I also highlight the statistical limitations when using multivariate time-series analysis and Granger causality to develop ecological networks, including the potential for spurious correlations among other data characteristics. Finally, I draw upon Gödel’s incompleteness theorems to highlight the inherent limits of fully understanding complex networks as formal systems and conclude that causal ecological networks are subject to initial rules and data characteristics and, as any formal system, will never fully capture the intricate complexities of the systems they represent. This article is part of the theme issue ‘Connected interactions: enriching food web research by spatial and social interactions’. |
| Author | Damos, Petros T. |
| Author_xml | – sequence: 1 givenname: Petros T. orcidid: 0000-0002-4055-0977 surname: Damos fullname: Damos, Petros T. organization: Minstry of Education, Religious and Sports, Directorate of Secondary Education Veroia , Ergohori 59132, Greece, Department of Agriculture, School of Agricultural Studies, University of Western Macedonia , Florina, 53100, Greece, Department of Electrical and Computer Engineering, Faculty of Engineering, University of Western Macedonia , Kozani 50100, Greece |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39034692$$D View this record in MEDLINE/PubMed |
| BookMark | eNp1kE1LxDAQhoOsuN3Vq0fp0Uvr5KNNc5TFL1jYi55DmqQSbZs1aRH_vS27ehA8zfDyvAPzrNCi971F6BJDjkFUNyEOdU6A0BwwhxOUYMZxRgSHBUpAlCSrGC2XaBXjGwCIgrMztKQCKCsFSRDd9WnjQ6fatHWdG9TgfB9T36RajXFKrfatf3V6Wns7fPrwHs_RaaPaaC-Oc41e7u-eN4_ZdvfwtLndZpoV5ZBVleKaGEG4LQzGlVW4ritS40YLzA0YayznXHNiClObKTeGQ1Eyo0BoA3SNrg9398F_jDYOsnNR27ZVvfVjlBQqSjBnjE7o1REd684auQ-uU-FL_jw6AfkB0MHHGGzzi2CQs0k5m5SzSTmbnArsT0Ef7QxBufa_2jdsDXgj |
| CitedBy_id | crossref_primary_10_1098_rstb_2023_0163 |
| Cites_doi | 10.1038/srep14750 10.1046/j.1461-0248.2002.00354.x 10.1007/s12038-007-0040-1 10.1098/rsos.172092 10.1007/BF01063984 10.1016/j.ecolind.2020.107096 10.1016/j.ecolmodel.2017.11.021 10.1038/s41598-021-86476-9 10.1080/00031305.1996.10473563 10.1103/PhysRevE.97.042207 10.1017/9781316779651.015 10.1007/s12080-020-00482-7 10.1038/238413a0 10.1038/s41467-020-16238-0 10.1016/0165-1889(80)90069-X 10.1111/j.1558-5646.2007.00203.x 10.1016/j.ecoinf.2021.101216 10.1038/s41598-021-97741-2 10.1090/cbms/107 10.1371/journal.pone.0208078 10.1090/S0002-9904-1947-08785-1 10.1007/978-0-387-79711-3 10.1016/j.marpolbul.2009.09.029 10.1146/annurev.ecolsys.38.091206.095818 10.1016/j.conb.2012.11.010 10.1146/annurev-ecolsys-012220-120819 10.2307/1912791 10.1057/9780230280816_28 10.1016/j.tree.2022.03.008 10.1016/j.neuroimage.2014.07.045 10.1073/pnas.2204405119 10.1007/s10994-006-5833-1 10.1098/rspb.2013.2837 10.1007/s10144-018-0628-3 10.1093/bjps/axi147 10.2307/2270922 10.1016/j.physleta.2004.02.032 10.1016/j.ecolmodel.2022.109964 10.1016/0165-1889(88)90055-3 10.1007/BF01700692 10.1007/s13278-020-00708-w 10.1002/jae.2676 10.1146/annurev.es.04.110173.000245 10.2202/1557-4679.1203 10.1002/ecy.3040 10.2307/5678 10.1016/j.ijppaw.2013.09.001 10.2307/1912559 10.3390/bioengineering10030372 10.1016/0304-4076(74)90034-7 10.1209/0295-5075/119/18003 10.1016/j.envsoft.2022.105489 10.1111/j.1365-2656.2006.01070.x 10.1126/science.5.121.634 10.3389/fevo.2019.00293 10.1007/978-94-009-3997-4_6 10.1038/s41467-022-28761-3 10.1371/journal.pcbi.1007037 10.1038/s41559-020-01298-8 10.1093/biosci/biaa088 10.1016/j.tree.2020.01.004 10.1007/s00382-021-05944-0 10.1111/j.1467-8640.1995.tb00021.x 10.1146/annurev-statistics-040120-010930 10.1080/01621459.1982.10477803 10.1186/s12898-016-0087-7 10.1139/f98-104 10.1111/ele.12775 10.1007/978-3-030-34308-8_15 |
| ContentType | Journal Article |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 |
| DOI | 10.1098/rstb.2023.0170 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE CrossRef |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine Sciences (General) Biology |
| EISSN | 1471-2970 |
| ExternalDocumentID | 39034692 10_1098_rstb_2023_0170 |
| Genre | Journal Article |
| GroupedDBID | --- -~X 0R~ 2WC 4.4 53G AACGO AANCE AAYXX ABPLY ABTLG ACPRK ADBBV AFRAH ALMA_UNASSIGNED_HOLDINGS AOIJS BAWUL BTFSW CITATION E3Z EBS F5P GX1 H13 HZ~ JSG JST KQ8 MRS MV1 NSAHA O9- OK1 RPM RRY TN5 V1E YNT ~02 CGR CUY CVF ECM EIF NPM 7X8 |
| ID | FETCH-LOGICAL-c456t-88a7c2d927e5d118ea1bb82b1fc917d0dede777c72d5dbdb1fdd70564da09cd03 |
| ISSN | 0962-8436 1471-2970 |
| IngestDate | Fri Jul 11 07:42:58 EDT 2025 Thu Jul 10 06:23:10 EDT 2025 Thu Apr 24 22:54:38 EDT 2025 Tue Jul 01 03:25:41 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1909 |
| Keywords | web-ecology granger causality incompleteness complex systems modal logic ecological interactions |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c456t-88a7c2d927e5d118ea1bb82b1fc917d0dede777c72d5dbdb1fdd70564da09cd03 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ORCID | 0000-0002-4055-0977 |
| PMID | 39034692 |
| PQID | 3083217443 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_3083217443 pubmed_primary_39034692 crossref_primary_10_1098_rstb_2023_0170 crossref_citationtrail_10_1098_rstb_2023_0170 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2024-Sep-09 |
| PublicationDateYYYYMMDD | 2024-09-09 |
| PublicationDate_xml | – month: 09 year: 2024 text: 2024-Sep-09 day: 09 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England |
| PublicationTitle | Philosophical transactions of the Royal Society of London. Series B. Biological sciences |
| PublicationTitleAlternate | Philos Trans R Soc Lond B Biol Sci |
| PublicationYear | 2024 |
| References | e_1_3_9_4_2 e_1_3_9_31_2 e_1_3_9_54_2 e_1_3_9_77_2 e_1_3_9_6_2 Lewis DK (e_1_3_9_39_2) 1986 e_1_3_9_56_2 e_1_3_9_79_2 e_1_3_9_12_2 e_1_3_9_35_2 e_1_3_9_50_2 e_1_3_9_73_2 e_1_3_9_2_2 Russell B (e_1_3_9_49_2) 1912 e_1_3_9_52_2 e_1_3_9_75_2 e_1_3_9_71_2 Hume D (e_1_3_9_60_2) 1978 Runge J (e_1_3_9_10_2) 2017; 27 Pearl J (e_1_3_9_43_2) 2000 e_1_3_9_16_2 e_1_3_9_14_2 e_1_3_9_58_2 e_1_3_9_18_2 e_1_3_9_42_2 e_1_3_9_65_2 e_1_3_9_88_2 e_1_3_9_40_2 e_1_3_9_67_2 Suppes P (e_1_3_9_70_2) 1970; 24 Barbero F (e_1_3_9_33_2) e_1_3_9_23_2 e_1_3_9_46_2 e_1_3_9_61_2 e_1_3_9_84_2 e_1_3_9_21_2 e_1_3_9_63_2 e_1_3_9_86_2 e_1_3_9_82_2 e_1_3_9_25_2 e_1_3_9_48_2 e_1_3_9_69_2 e_1_3_9_29_2 e_1_3_9_3_2 e_1_3_9_30_2 e_1_3_9_55_2 e_1_3_9_76_2 e_1_3_9_5_2 Hughes GE (e_1_3_9_37_2) 1968 e_1_3_9_57_2 e_1_3_9_78_2 Maziarz M (e_1_3_9_44_2) 2015; 8 e_1_3_9_34_2 e_1_3_9_51_2 e_1_3_9_72_2 e_1_3_9_11_2 e_1_3_9_32_2 e_1_3_9_53_2 e_1_3_9_74_2 Levins R (e_1_3_9_27_2) 1988; 3 Solvang HK (e_1_3_9_8_2) 2019; 14 e_1_3_9_17_2 e_1_3_9_38_2 e_1_3_9_15_2 e_1_3_9_36_2 e_1_3_9_7_2 e_1_3_9_9_2 e_1_3_9_19_2 e_1_3_9_20_2 e_1_3_9_41_2 e_1_3_9_66_2 e_1_3_9_87_2 e_1_3_9_68_2 e_1_3_9_45_2 e_1_3_9_62_2 e_1_3_9_83_2 e_1_3_9_22_2 e_1_3_9_64_2 e_1_3_9_85_2 Raatikainen P (e_1_3_9_24_2) 2018 Wiener N (e_1_3_9_59_2) 1956 Yu L (e_1_3_9_81_2) 2021 e_1_3_9_28_2 e_1_3_9_26_2 e_1_3_9_47_2 Krabbe Borregaard M (e_1_3_9_13_2) 2010; 85 Holmes EE (e_1_3_9_80_2) 2023 |
| References_xml | – ident: e_1_3_9_68_2 doi: 10.1038/srep14750 – ident: e_1_3_9_6_2 doi: 10.1046/j.1461-0248.2002.00354.x – ident: e_1_3_9_62_2 doi: 10.1007/s12038-007-0040-1 – ident: e_1_3_9_74_2 doi: 10.1098/rsos.172092 – ident: e_1_3_9_35_2 doi: 10.1007/BF01063984 – ident: e_1_3_9_85_2 doi: 10.1016/j.ecolind.2020.107096 – volume: 27 year: 2017 ident: e_1_3_9_10_2 article-title: Detecting and quantifying causal associations in large nonlinear time series datasets publication-title: Sci. Adv. – ident: e_1_3_9_16_2 doi: 10.1016/j.ecolmodel.2017.11.021 – volume: 3 start-page: 149 year: 1988 ident: e_1_3_9_27_2 article-title: The controlling factor in biological communities publication-title: Coenoses – ident: e_1_3_9_31_2 – ident: e_1_3_9_17_2 doi: 10.1038/s41598-021-86476-9 – volume-title: British moralists, 1650–1800 year: 1978 ident: e_1_3_9_60_2 – ident: e_1_3_9_79_2 doi: 10.1080/00031305.1996.10473563 – ident: e_1_3_9_20_2 doi: 10.1103/PhysRevE.97.042207 – ident: e_1_3_9_36_2 doi: 10.1017/9781316779651.015 – start-page: 98 volume-title: Analysis of multivariate time series using the MARSS package, version 3.11.4 year: 2023 ident: e_1_3_9_80_2 – ident: e_1_3_9_57_2 doi: 10.1007/s12080-020-00482-7 – volume-title: The Stanford encyclopedia of philosophy (fall 2018 edition) year: 2018 ident: e_1_3_9_24_2 – ident: e_1_3_9_5_2 doi: 10.1038/238413a0 – volume-title: The problems of philosophy year: 1912 ident: e_1_3_9_49_2 – ident: e_1_3_9_69_2 doi: 10.1038/s41467-020-16238-0 – ident: e_1_3_9_61_2 doi: 10.1016/0165-1889(80)90069-X – ident: e_1_3_9_48_2 doi: 10.1111/j.1558-5646.2007.00203.x – ident: e_1_3_9_67_2 doi: 10.1016/j.ecoinf.2021.101216 – ident: e_1_3_9_19_2 doi: 10.1038/s41598-021-97741-2 – volume: 24 start-page: 130 year: 1970 ident: e_1_3_9_70_2 article-title: A probabilistic theory of causality publication-title: Acta Philos. Fenn. – ident: e_1_3_9_87_2 doi: 10.1090/cbms/107 – volume: 8 start-page: 86 year: 2015 ident: e_1_3_9_44_2 article-title: A review of the Granger-causality fallacy publication-title: J. Philos. Econ. – volume: 14 year: 2019 ident: e_1_3_9_8_2 article-title: An improved methodology for quantifying causality in complex ecological systems publication-title: PLoS One doi: 10.1371/journal.pone.0208078 – ident: e_1_3_9_86_2 doi: 10.1090/S0002-9904-1947-08785-1 – ident: e_1_3_9_88_2 doi: 10.1007/978-0-387-79711-3 – ident: e_1_3_9_32_2 doi: 10.1016/j.marpolbul.2009.09.029 – ident: e_1_3_9_65_2 doi: 10.1146/annurev.ecolsys.38.091206.095818 – ident: e_1_3_9_54_2 doi: 10.1016/j.conb.2012.11.010 – ident: e_1_3_9_3_2 doi: 10.1146/annurev-ecolsys-012220-120819 – volume: 85 start-page: 41 year: 2010 ident: e_1_3_9_13_2 article-title: Causality of the relationship between geographic distribution and species abundance publication-title: Q. Rev. Biol. – ident: e_1_3_9_21_2 doi: 10.2307/1912791 – ident: e_1_3_9_30_2 doi: 10.1057/9780230280816_28 – ident: e_1_3_9_45_2 doi: 10.1016/j.tree.2022.03.008 – ident: e_1_3_9_75_2 doi: 10.1016/j.neuroimage.2014.07.045 – ident: e_1_3_9_15_2 doi: 10.1073/pnas.2204405119 – ident: e_1_3_9_40_2 doi: 10.1007/s10994-006-5833-1 – ident: e_1_3_9_66_2 doi: 10.1098/rspb.2013.2837 – ident: e_1_3_9_2_2 doi: 10.1007/s10144-018-0628-3 – ident: e_1_3_9_28_2 doi: 10.1093/bjps/axi147 – ident: e_1_3_9_38_2 doi: 10.2307/2270922 – ident: e_1_3_9_77_2 doi: 10.1016/j.physleta.2004.02.032 – ident: e_1_3_9_82_2 doi: 10.1016/j.ecolmodel.2022.109964 – ident: e_1_3_9_22_2 doi: 10.1016/0165-1889(88)90055-3 – ident: e_1_3_9_23_2 doi: 10.1007/BF01700692 – ident: e_1_3_9_25_2 – start-page: 165 volume-title: Modern mathematics for engineers year: 1956 ident: e_1_3_9_59_2 – ident: e_1_3_9_41_2 doi: 10.1007/s13278-020-00708-w – ident: e_1_3_9_11_2 doi: 10.1002/jae.2676 – ident: e_1_3_9_50_2 doi: 10.1146/annurev.es.04.110173.000245 – ident: e_1_3_9_29_2 doi: 10.2202/1557-4679.1203 – ident: e_1_3_9_83_2 doi: 10.1002/ecy.3040 – ident: e_1_3_9_26_2 doi: 10.2307/5678 – ident: e_1_3_9_14_2 doi: 10.1016/j.ijppaw.2013.09.001 – start-page: 17 volume-title: Proc. 3rd Int. Worksh. Dynamic Logic (DaLí ’20) (eds MA Martins, I Sedl´ar) ident: e_1_3_9_33_2 – ident: e_1_3_9_53_2 doi: 10.2307/1912559 – ident: e_1_3_9_76_2 doi: 10.3390/bioengineering10030372 – ident: e_1_3_9_73_2 doi: 10.1016/0304-4076(74)90034-7 – volume-title: An introduction to modal logic year: 1968 ident: e_1_3_9_37_2 – ident: e_1_3_9_7_2 doi: 10.1209/0295-5075/119/18003 – ident: e_1_3_9_52_2 doi: 10.1016/j.envsoft.2022.105489 – ident: e_1_3_9_64_2 doi: 10.1111/j.1365-2656.2006.01070.x – ident: e_1_3_9_47_2 doi: 10.1126/science.5.121.634 – ident: e_1_3_9_51_2 doi: 10.3389/fevo.2019.00293 – ident: e_1_3_9_71_2 doi: 10.1007/978-94-009-3997-4_6 – ident: e_1_3_9_12_2 doi: 10.1038/s41467-022-28761-3 – volume-title: On the plurality of worlds year: 1986 ident: e_1_3_9_39_2 – ident: e_1_3_9_56_2 doi: 10.1371/journal.pcbi.1007037 – volume-title: Proc. 24th Int. Conf. Artificial Intelligence and Statistics (AISTATS) year: 2021 ident: e_1_3_9_81_2 – ident: e_1_3_9_9_2 doi: 10.1038/s41559-020-01298-8 – ident: e_1_3_9_46_2 doi: 10.1093/biosci/biaa088 – ident: e_1_3_9_4_2 doi: 10.1016/j.tree.2020.01.004 – ident: e_1_3_9_55_2 doi: 10.1007/s00382-021-05944-0 – ident: e_1_3_9_78_2 doi: 10.1111/j.1467-8640.1995.tb00021.x – ident: e_1_3_9_58_2 doi: 10.1146/annurev-statistics-040120-010930 – ident: e_1_3_9_34_2 – ident: e_1_3_9_72_2 doi: 10.1080/01621459.1982.10477803 – ident: e_1_3_9_18_2 doi: 10.1186/s12898-016-0087-7 – ident: e_1_3_9_84_2 doi: 10.1139/f98-104 – ident: e_1_3_9_63_2 doi: 10.1111/ele.12775 – ident: e_1_3_9_42_2 doi: 10.1007/978-3-030-34308-8_15 – volume-title: Correlation and causality: models, reasoning, and inference year: 2000 ident: e_1_3_9_43_2 |
| SSID | ssj0009574 |
| Score | 2.4669297 |
| Snippet | Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these... |
| SourceID | proquest pubmed crossref |
| SourceType | Aggregation Database Index Database Enrichment Source |
| StartPage | 20230170 |
| SubjectTerms | Causality Ecology - methods Ecosystem Models, Biological Multivariate Analysis |
| Title | On formal limitations of causal ecological networks |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/39034692 https://www.proquest.com/docview/3083217443 |
| Volume | 379 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3da9RAEB-0YumL2POj5xcrCColMbfZdLOPrShFqVVooW8h-3FP11xpcg_61zuT3U2u6oFKIITNbu6YGX6Zyc7MD-CVoSiDG5Wgby0TaoGelLUoMFRxheLOCdPTAZ18OTg-F58uiotICR-qSzqdmh9_rCv5H63iGOqVqmT_QbPDQ3EAr1G_eEYN4_mvdHza-OLDxf6C6pTGrDZTr1ocdWaAtsane7frzujXSGPQz-hG5vA2Zg74jwsxs5O2E3r2j5QgBkPs_aM0kFmOxZVmnar-0ifxEW3Xsg352OETAxd9DpUHMudhEV9hCVee4iPiZu5ZYKKBqLAiACHFNjO_4DeUzhRVHqB3q1Oal_46EaV8ddnrLFdZjgE8H99WQw5hvHUb7nAMEYi94vO3cq3hshRDk87y3c0f24HtuPymP7IhyOidjbP7cC9ECezQq3wXbrlmAne9qL9PYPskZERMYDeAc8vehA7ibx9AftowbxhszTDYcs68YbDRMFg0jIdw_vHD2fvjJLBjJAad3i4py1oabhWXrrAYJrp6pnXJ9WxuMAS3mXXWSSmN5Law2uK4tRLdXWHrTBmb5Y9gq1k2bg9YVgvajc30vECHTjkt9ewA0dxoPCxXU0iijCoT_jQxmCwqn8JQViTeisRbkXin8HqYf-Wbpmyc-TKKvEJco82qunHLVVvlGXFoSSHyKTz2uhieFXX3ZOOdp7AzGvIz2OquV-45eo-dftGbyU_G5G46 |
| linkProvider | Colorado Alliance of Research Libraries |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=On+formal+limitations+of+causal+ecological+networks&rft.jtitle=Philosophical+transactions+of+the+Royal+Society+of+London.+Series+B.+Biological+sciences&rft.au=Damos%2C+Petros+T&rft.date=2024-09-09&rft.eissn=1471-2970&rft.volume=379&rft.issue=1909&rft.spage=20230170&rft_id=info:doi/10.1098%2Frstb.2023.0170&rft_id=info%3Apmid%2F39034692&rft.externalDocID=39034692 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0962-8436&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0962-8436&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0962-8436&client=summon |