Quantifying Resilience of Humans and Other Animals. Scheffer, M., Bolhuis, J. E., Borsboom, D., Buchman, T. G., Gijzel, S. M. W., Goulson, D., Kammenga, J. E., Kemp, B., van de Leemput , I. A., Levin, S., Martin, C. M., Melis, R. J. F., van Nes , E. H., Romero, L. M., & Olde Rikkert, M. G. M. Proceedings of the National Academy of Sciences, 115(47):11883–11890, November, 2018. doi abstract bibtex All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.
@article{schefferQuantifyingResilienceHumans2018,
title = {Quantifying Resilience of Humans and Other Animals},
author = {Scheffer, Marten and Bolhuis, J. Elizabeth and Borsboom, Denny and Buchman, Timothy G. and Gijzel, Sanne M. W. and Goulson, Dave and Kammenga, Jan E. and Kemp, Bas and {van de Leemput}, Ingrid A. and Levin, Simon and Martin, Carmel M. and Melis, Ren{\'e} J. F. and {van Nes}, Egbert H. and Romero, L. Michael and Olde Rikkert, Marcel G. M.},
year = {2018},
month = nov,
volume = {115},
pages = {11883--11890},
issn = {0027-8424},
doi = {10.1073/pnas.1810630115},
abstract = {All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.},
journal = {Proceedings of the National Academy of Sciences},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14657160,correlation-analysis,cross-disciplinary-perspective,ecosystem-resilience,feedback,human-health,memory,networks,resilience,society},
lccn = {INRMM-MiD:c-14657160},
number = {47}
}
Downloads: 0
{"_id":"Z79LYYNwnYYNxj9mr","bibbaseid":"scheffer-bolhuis-borsboom-buchman-gijzel-goulson-kammenga-kemp-etal-quantifyingresilienceofhumansandotheranimals-2018","authorIDs":[],"author_short":["Scheffer, M.","Bolhuis, J. E.","Borsboom, D.","Buchman, T. G.","Gijzel, S. M. W.","Goulson, D.","Kammenga, J. E.","Kemp, B.","van de Leemput , I. A.","Levin, S.","Martin, C. M.","Melis, R. J. F.","van Nes , E. H.","Romero, L. M.","Olde Rikkert, M. G. M."],"bibdata":{"bibtype":"article","type":"article","title":"Quantifying Resilience of Humans and Other Animals","author":[{"propositions":[],"lastnames":["Scheffer"],"firstnames":["Marten"],"suffixes":[]},{"propositions":[],"lastnames":["Bolhuis"],"firstnames":["J.","Elizabeth"],"suffixes":[]},{"propositions":[],"lastnames":["Borsboom"],"firstnames":["Denny"],"suffixes":[]},{"propositions":[],"lastnames":["Buchman"],"firstnames":["Timothy","G."],"suffixes":[]},{"propositions":[],"lastnames":["Gijzel"],"firstnames":["Sanne","M.","W."],"suffixes":[]},{"propositions":[],"lastnames":["Goulson"],"firstnames":["Dave"],"suffixes":[]},{"propositions":[],"lastnames":["Kammenga"],"firstnames":["Jan","E."],"suffixes":[]},{"propositions":[],"lastnames":["Kemp"],"firstnames":["Bas"],"suffixes":[]},{"propositions":["van de Leemput"],"lastnames":[],"firstnames":["Ingrid","A."],"suffixes":[]},{"propositions":[],"lastnames":["Levin"],"firstnames":["Simon"],"suffixes":[]},{"propositions":[],"lastnames":["Martin"],"firstnames":["Carmel","M."],"suffixes":[]},{"propositions":[],"lastnames":["Melis"],"firstnames":["René","J.","F."],"suffixes":[]},{"propositions":["van Nes"],"lastnames":[],"firstnames":["Egbert","H."],"suffixes":[]},{"propositions":[],"lastnames":["Romero"],"firstnames":["L.","Michael"],"suffixes":[]},{"propositions":[],"lastnames":["Olde","Rikkert"],"firstnames":["Marcel","G.","M."],"suffixes":[]}],"year":"2018","month":"November","volume":"115","pages":"11883–11890","issn":"0027-8424","doi":"10.1073/pnas.1810630115","abstract":"All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.","journal":"Proceedings of the National Academy of Sciences","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-14657160,correlation-analysis,cross-disciplinary-perspective,ecosystem-resilience,feedback,human-health,memory,networks,resilience,society","lccn":"INRMM-MiD:c-14657160","number":"47","bibtex":"@article{schefferQuantifyingResilienceHumans2018,\n title = {Quantifying Resilience of Humans and Other Animals},\n author = {Scheffer, Marten and Bolhuis, J. Elizabeth and Borsboom, Denny and Buchman, Timothy G. and Gijzel, Sanne M. W. and Goulson, Dave and Kammenga, Jan E. and Kemp, Bas and {van de Leemput}, Ingrid A. and Levin, Simon and Martin, Carmel M. and Melis, Ren{\\'e} J. F. and {van Nes}, Egbert H. and Romero, L. Michael and Olde Rikkert, Marcel G. M.},\n year = {2018},\n month = nov,\n volume = {115},\n pages = {11883--11890},\n issn = {0027-8424},\n doi = {10.1073/pnas.1810630115},\n abstract = {All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.},\n journal = {Proceedings of the National Academy of Sciences},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14657160,correlation-analysis,cross-disciplinary-perspective,ecosystem-resilience,feedback,human-health,memory,networks,resilience,society},\n lccn = {INRMM-MiD:c-14657160},\n number = {47}\n}\n\n","author_short":["Scheffer, M.","Bolhuis, J. E.","Borsboom, D.","Buchman, T. G.","Gijzel, S. M. W.","Goulson, D.","Kammenga, J. E.","Kemp, B.","van de Leemput , I. A.","Levin, S.","Martin, C. M.","Melis, R. J. F.","van Nes , E. H.","Romero, L. M.","Olde Rikkert, M. G. M."],"key":"schefferQuantifyingResilienceHumans2018","id":"schefferQuantifyingResilienceHumans2018","bibbaseid":"scheffer-bolhuis-borsboom-buchman-gijzel-goulson-kammenga-kemp-etal-quantifyingresilienceofhumansandotheranimals-2018","role":"author","urls":{},"keyword":["*imported-from-citeulike-INRMM","~INRMM-MiD:c-14657160","correlation-analysis","cross-disciplinary-perspective","ecosystem-resilience","feedback","human-health","memory","networks","resilience","society"],"downloads":0},"bibtype":"article","biburl":"https://sharefast.me/php/download.php?id=zOUKvA&token=29","creationDate":"2020-07-03T22:46:27.397Z","downloads":0,"keywords":["*imported-from-citeulike-inrmm","~inrmm-mid:c-14657160","correlation-analysis","cross-disciplinary-perspective","ecosystem-resilience","feedback","human-health","memory","networks","resilience","society"],"search_terms":["quantifying","resilience","humans","animals","scheffer","bolhuis","borsboom","buchman","gijzel","goulson","kammenga","kemp","van de leemput ","levin","martin","melis","van nes ","romero","olde rikkert"],"title":"Quantifying Resilience of Humans and Other Animals","year":2018,"dataSources":["5S2zj2hKW8TWTkuMq"]}