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dc.contributor.authorPiirainen, Sirke
dc.contributor.authorLehikoinen, Aleksi
dc.contributor.authorHusby, Magne
dc.contributor.authorKålås, John Atle
dc.contributor.authorLindström, Åke
dc.contributor.authorOvaskainen, Otso
dc.date.accessioned2023-03-06T06:59:42Z
dc.date.available2023-03-06T06:59:42Z
dc.date.issued2023
dc.identifier.citationPiirainen, S., Lehikoinen, A., Husby, M., Kålås, J. A., Lindström, Å., & Ovaskainen, O. (2023). Species distributions models may predict accurately future distributions but poorly how distributions change : A critical perspective on model validation. <i>Diversity and Distributions</i>, <i>29</i>(5), 654-665. <a href="https://doi.org/10.1111/ddi.13687" target="_blank">https://doi.org/10.1111/ddi.13687</a>
dc.identifier.otherCONVID_177113461
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/85752
dc.description.abstractAim Species distribution models (SDMs) are widely used to make predictions on how species distributions may change as a response to climatic change. To assess the reliability of those predictions, they need to be critically validated with respect to what they are used for. While ecologists are typically interested in how and where distributions will change, we argue that SDMs have seldom been evaluated in terms of their capacity to predict such change. Instead, typical retrospective validation methods estimate model's ability to predict to only one static time in future. Here, we apply two validation methods, one that predicts and evaluates a static pattern, while the other measures change and compare their estimates of predictive performance. Location Fennoscandia. Methods We applied a joint SDM to model the distributions of 120 bird species in four model validation settings. We trained models with a dataset from 1975 to 1999 and predicted species' future occurrence and abundance in two ways: for one static time period (2013–2016, ‘static validation’) and for a change between two time periods (difference between 1996–1999 and 2013–2016, ‘change validation’). We then measured predictive performance using correlation between predicted and observed values. We also related predictive performance to species traits. Results Even though static validation method evaluated predictive performance as good, change method indicated very poor performance. Predictive performance was not strongly related to any trait. Main Conclusions Static validation method might overestimate predictive performance by not revealing the model's inability to predict change events. If species' distributions remain mostly stable, then even an unfit model can predict the near future well due to temporal autocorrelation. We urge caution when working with forecasts of changes in spatial patterns of species occupancy or abundance, even for SDMs that are based on time series datasets unless they are critically validated for forecasting such change.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherWiley
dc.relation.ispartofseriesDiversity and Distributions
dc.rightsCC BY 4.0
dc.subject.otherbirds
dc.subject.otherclimate change
dc.subject.otherFennoscandia
dc.subject.otherforecasting
dc.subject.otherland use
dc.subject.othermodel validation
dc.subject.otherprediction
dc.subject.otherspecies distribution modelling
dc.subject.otherspecies traits
dc.subject.othertemporal transferability
dc.titleSpecies distributions models may predict accurately future distributions but poorly how distributions change : A critical perspective on model validation
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202303062011
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange654-665
dc.relation.issn1366-9516
dc.relation.numberinseries5
dc.relation.volume29
dc.type.versionpublishedVersion
dc.rights.copyright© 2023 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber856506
dc.relation.grantnumber856506
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/856506/EU//LIFEPLAN
dc.subject.ysoennusteet
dc.subject.ysolinnut
dc.subject.ysoilmastonmuutokset
dc.subject.ysomallit (mallintaminen)
dc.subject.ysolevinneisyys
dc.subject.ysomallintaminen
dc.subject.ysovalidointi
dc.subject.ysolajit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p3297
jyx.subject.urihttp://www.yso.fi/onto/yso/p3363
jyx.subject.urihttp://www.yso.fi/onto/yso/p5729
jyx.subject.urihttp://www.yso.fi/onto/yso/p510
jyx.subject.urihttp://www.yso.fi/onto/yso/p7415
jyx.subject.urihttp://www.yso.fi/onto/yso/p3533
jyx.subject.urihttp://www.yso.fi/onto/yso/p20652
jyx.subject.urihttp://www.yso.fi/onto/yso/p2765
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.datasethttps://doi.org/10.5061/dryad.bzkh189br
dc.relation.doi10.1111/ddi.13687
dc.relation.funderEuropean Commissionen
dc.relation.funderEuroopan komissiofi
jyx.fundingprogramERC European Research Council, H2020en
jyx.fundingprogramERC European Research Council, H2020fi
jyx.fundinginformationWe acknowledge the tremendous fieldwork effort made by the volunteers. This research was partly funded through the 2017–2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND programme, and with the funding organizations Academy of Finland (Helsinki: 326338), Swedish Research Council (Lund: 2018-02441), the Research Council of Norway (RCN, NINA: 295767) and the National Science Foundation (CLO, ICER-1927646). The Swedish Bird Survey is supported by grants from the Swedish Environmental Protection Agency, with additional financial and logistic support from the Regional County Boards (Länsstyrelsen). The censuses were carried out within the framework of the Linnaeus-project Centre for Animal Movement Research (CAnMove) and the strategic research environment Biodiversity and Ecosystem Services in a Changing Climate (BECC). The Norwegian Climate and Environment Ministry and the Norwegian Environment Agency finance the Norwegian bird monitoring. Additionally, AL was funded by the Academy of Finland (project 275606). SP was funded by the Finnish Cultural Foundation and the Kone Foundation (grant number 201903886). OO was funded by Academy of Finland (grant no. 309581), Jane and Aatos Erkko Foundation, Research Council of Norway through its Centres of Excellence Funding Scheme (223257), and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 856506; ERC-synergy project LIFEPLAN). We acknowledge the E-OBS dataset from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://www.ecad.eu). We thank also the anonymous reviewers.
dc.type.okmA1


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