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dc.contributor.authorRodríguez-Caro, Roberto Carlos-
dc.contributor.authorWiegand, Thorsten-
dc.contributor.authorWhite, Easton R.-
dc.contributor.authorSanz-Aguilar, Ana-
dc.contributor.authorGiménez, Andrés-
dc.contributor.authorGraciá, Eva-
dc.contributor.authorBenthem, Koen J. van-
dc.contributor.authorAnadón, José D.-
dc.date.accessioned2020-02-21T13:18:45Z-
dc.date.available2020-02-21T13:18:45Z-
dc.date.issued2019-09-
dc.identifier.citationBiological Conservation 237: 358-365 (2019)-
dc.identifier.issn0006-3207-
dc.identifier.urihttp://hdl.handle.net/10261/201573-
dc.description.abstractSurvival is a key parameter in species' management and conservation. Most methods for estimating survival require time series data, large sample sizes and, overall, costly monitoring efforts. Inverse modeling approaches can be less data hungry, however they are underused in conservation sciences. Here we present an inverse modeling approach for estimating relative survival rates of long-lived species that is mathematically straightforward and evaluate its performance under constraints common in conservation studies related to small sample sizes. Specifically, we (i) estimated the relative survival rates in a Testudo graeca population based on one-year monitoring, (ii) assessed the impact of sample size on the accuracy, and (iii) tested alternative hypotheses on the impact of fire on the survival rates. We then compared the results of our approach with capture-recapture (CRC) estimates based on long-term monitoring. Our approach (153 individuals within a single year) yielded estimates of survival rates overlapping those of CRC estimates (11 years of data and 1009 individuals) for adults and subadults, but not for juveniles. Simulation experiments showed that our method provides robust estimates if sample size is above 100 individuals. The best models describing the impact of fire on survival identified by our approach predicts a decrease in survival especially in hatchlings and juvenile individuals, similar to CRC estimates. Our work proves that inverse modeling can decrease the cost for estimating demographic rates, especially for long-lived species and as such, its use should be encouraged in conservation and management sciences.-
dc.description.sponsorshipThe Spanish Ministry of Science and European Regional Development Fund funded this work through Projects CGL2012-33536 and CGL2015-64144-R; MINECIO/FEDER). RCRC was supported by the Regional Government of the Community of Valencia (ACIF/2010/ 133). ASA was supported by a Ramón y Cajal contract (RYC-2017-22796) co-funded by the Spanish Ministry of Science, the Agencia Estatal de Investigación and the European Social Fund. KvB was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 316099922 - TRR 212.-
dc.languageeng-
dc.publisherElsevier-
dc.relationMINECO/ICTI2013-2016/CGL2015-64144-R-
dc.relationRYC-2017-22796/AEI/10.13039/501100011033-
dc.relationMICIU/ICTI2017-2020/RYC-2017-22796-
dc.relation.isversionofPostprint-
dc.rightsopenAccess-
dc.subjectPattern-oriented model-
dc.subjectSurvival rates-
dc.subjectDemography-
dc.subjectTortoise-
dc.subjectDisturbance-
dc.subjectFire-
dc.subjectTestudo graeca-
dc.titleA low cost approach to estimate demographic rates using inverse modeling-
dc.typeartículo-
dc.identifier.doi10.1016/j.biocon.2019.07.011-
dc.description.peerreviewedPeer reviewed-
dc.relation.publisherversionhttp://doi.org/10.1016/j.biocon.2019.07.011-
dc.date.updated2020-02-21T13:18:46Z-
dc.contributor.funderEuropean Commission-
dc.contributor.funderAgencia Estatal de Investigación (España)-
dc.contributor.funderMinisterio de Economía y Competitividad (España)-
dc.contributor.funderGeneralitat Valenciana-
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (España)-
dc.contributor.funderGerman Research Foundation-
dc.relation.csic-
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003359es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100001659es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100011033es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003329es_ES
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