Vis enkel innførsel

dc.contributor.authorSimmonds, Emily Grace
dc.contributor.authorAdjei, Kwaku Peprah
dc.contributor.authorCretois, Benjamin
dc.contributor.authorDickel, Lisa
dc.contributor.authorGonzález-Gil, Ricardo
dc.contributor.authorLaverick, Jack H
dc.contributor.authorMandeville, Caitlin Marie
dc.contributor.authorMandeville, Elisabeth G.
dc.contributor.authorOvaskainen, Otso Tapio
dc.contributor.authorSicacha Parada, Jorge Armando
dc.contributor.authorSkarstein, Emma
dc.contributor.authorO'Hara, Robert
dc.description.abstractEcological and evolutionary studies are currently failing to achieve complete and consistent reporting of model-related uncertainty. We identify three key barriers – a focus on parameter-related uncertainty, obscure uncertainty metrics, and limited recognition of uncertainty propagation – which have led to gaps in uncertainty consideration. However, these gaps can be closed. We propose that uncertainty reporting in ecology and evolution can be improved through wider application of existing statistical solutions and by adopting good practice from other scientific fields. Our recommendations include greater consideration of input data and model structure uncertainties, field-specific uncertainty standards for methods and reporting, and increased uncertainty propagation through the use of hierarchical models.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleRecommendations for quantitative uncertainty consideration in ecology and evolutionen_US
dc.title.alternativeRecommendations for quantitative uncertainty consideration in ecology and evolutionen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.rights.holder© 2023 The Authorsen_US
dc.source.journalTrends in Ecology & Evolutionen_US
dc.relation.projectNorges forskningsråd:314952en_US
dc.relation.projectNorges forskningsråd: 223257en_US
dc.relation.projectAndre: Academy of Finland (grants 336212 and 345110)en_US
dc.relation.projectEuropean Research Council: 856506; ERC-synergy project LIFEPLANen_US
dc.relation.projectEuropean Research Council: HORIZON CL6-2021-BIODIV-01 project 101059492 (Biodiversity Genomics Europe)en_US
dc.relation.projectEuropean Research Council: HORIZON-INFRA-2021-TECH-01 project 101057437 (Biodiversity Digital Twin for Advanced Modelling, Simulation, and Prediction Capabilities)en_US

Tilhørende fil(er)


Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Navngivelse 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Navngivelse 4.0 Internasjonal