Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluatio...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Global change biology 2022-12, Vol.28 (23), p.6921-6943
Hauptverfasser: Mahnken, Mats, Cailleret, Maxime, Collalti, Alessio, Trotta, Carlo, Biondo, Corrado, D'Andrea, Ettore, Dalmonech, Daniela, Marano, Gina, Mäkelä, Annikki, Minunno, Francesco, Peltoniemi, Mikko, Trotsiuk, Volodymyr, Nadal‐Sala, Daniel, Sabaté, Santiago, Vallet, Patrick, Aussenac, Raphaël, Cameron, David R., Bohn, Friedrich J., Grote, Rüdiger, Augustynczik, Andrey L. D., Yousefpour, Rasoul, Huber, Nica, Bugmann, Harald, Merganičová, Katarina, Merganic, Jan, Valent, Peter, Lasch‐Born, Petra, Hartig, Florian, Vega del Valle, Iliusi D., Volkholz, Jan, Gutsch, Martin, Matteucci, Giorgio, Krejza, Jan, Ibrom, Andreas, Meesenburg, Henning, Rötzer, Thomas, Maaten‐Theunissen, Marieke, Maaten, Ernst, Reyer, Christopher P. O.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 6943
container_issue 23
container_start_page 6921
container_title Global change biology
container_volume 28
creator Mahnken, Mats
Cailleret, Maxime
Collalti, Alessio
Trotta, Carlo
Biondo, Corrado
D'Andrea, Ettore
Dalmonech, Daniela
Marano, Gina
Mäkelä, Annikki
Minunno, Francesco
Peltoniemi, Mikko
Trotsiuk, Volodymyr
Nadal‐Sala, Daniel
Sabaté, Santiago
Vallet, Patrick
Aussenac, Raphaël
Cameron, David R.
Bohn, Friedrich J.
Grote, Rüdiger
Augustynczik, Andrey L. D.
Yousefpour, Rasoul
Huber, Nica
Bugmann, Harald
Merganičová, Katarina
Merganic, Jan
Valent, Peter
Lasch‐Born, Petra
Hartig, Florian
Vega del Valle, Iliusi D.
Volkholz, Jan
Gutsch, Martin
Matteucci, Giorgio
Krejza, Jan
Ibrom, Andreas
Meesenburg, Henning
Rötzer, Thomas
Maaten‐Theunissen, Marieke
Maaten, Ernst
Reyer, Christopher P. O.
description Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi‐model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests. In this study, we evaluated 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. Multiple models are available that excel according to our three proposed dimensions of model performance. In addition, w
doi_str_mv 10.1111/gcb.16384
format Article
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_04066667v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2731292514</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3994-7c0973e319ae96554e56647bae25fbd487d6c6b515dd59ff04555cae8de8273f3</originalsourceid><addsrcrecordid>eNp10UtLxDAQB_Agiu-D36DgRcG6mebVHtdlfcCCFz2HNJ1qJdvUxCr77c26iwfBuSSEXzIT_oScAb2GVJMXW1-DZCXfIYfApMgLXsrd9V7wHCiwA3IU4xullBVU7pMDJgEUh-KQzKfWjsHY1VUW0LguLjPTN9kL9hiMy8wwuM6aunPdxyrzbTYfgx_Q9FnrA8aPbOkbdPGE7LXGRTzdrsfk-Xb-NLvPF493D7PpIresqniuLK0UQwaVwUoKwVFIyVVtsBBt3fBSNdLKWoBoGlG1LeVCCGuwbLAsFGvZMbncvPtqnB5CtzRhpb3p9P10oddnlFOZSn1CshcbOwT_PqZZ9bKLFp0zPfox6kKBUBVw4Ime_6Fvfgx9-klSDIqqED9q29wGH2PA9ncCoHqdg0456J8ckp1s7FfncPU_1Hezm82NbzqVhQg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2731292514</pqid></control><display><type>article</type><title>Accuracy, realism and general applicability of European forest models</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Mahnken, Mats ; Cailleret, Maxime ; Collalti, Alessio ; Trotta, Carlo ; Biondo, Corrado ; D'Andrea, Ettore ; Dalmonech, Daniela ; Marano, Gina ; Mäkelä, Annikki ; Minunno, Francesco ; Peltoniemi, Mikko ; Trotsiuk, Volodymyr ; Nadal‐Sala, Daniel ; Sabaté, Santiago ; Vallet, Patrick ; Aussenac, Raphaël ; Cameron, David R. ; Bohn, Friedrich J. ; Grote, Rüdiger ; Augustynczik, Andrey L. D. ; Yousefpour, Rasoul ; Huber, Nica ; Bugmann, Harald ; Merganičová, Katarina ; Merganic, Jan ; Valent, Peter ; Lasch‐Born, Petra ; Hartig, Florian ; Vega del Valle, Iliusi D. ; Volkholz, Jan ; Gutsch, Martin ; Matteucci, Giorgio ; Krejza, Jan ; Ibrom, Andreas ; Meesenburg, Henning ; Rötzer, Thomas ; Maaten‐Theunissen, Marieke ; Maaten, Ernst ; Reyer, Christopher P. O.</creator><creatorcontrib>Mahnken, Mats ; Cailleret, Maxime ; Collalti, Alessio ; Trotta, Carlo ; Biondo, Corrado ; D'Andrea, Ettore ; Dalmonech, Daniela ; Marano, Gina ; Mäkelä, Annikki ; Minunno, Francesco ; Peltoniemi, Mikko ; Trotsiuk, Volodymyr ; Nadal‐Sala, Daniel ; Sabaté, Santiago ; Vallet, Patrick ; Aussenac, Raphaël ; Cameron, David R. ; Bohn, Friedrich J. ; Grote, Rüdiger ; Augustynczik, Andrey L. D. ; Yousefpour, Rasoul ; Huber, Nica ; Bugmann, Harald ; Merganičová, Katarina ; Merganic, Jan ; Valent, Peter ; Lasch‐Born, Petra ; Hartig, Florian ; Vega del Valle, Iliusi D. ; Volkholz, Jan ; Gutsch, Martin ; Matteucci, Giorgio ; Krejza, Jan ; Ibrom, Andreas ; Meesenburg, Henning ; Rötzer, Thomas ; Maaten‐Theunissen, Marieke ; Maaten, Ernst ; Reyer, Christopher P. O.</creatorcontrib><description>Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi‐model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests. In this study, we evaluated 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. Multiple models are available that excel according to our three proposed dimensions of model performance. In addition, we find that structural properties are modelled more accurately than carbon fluxes, more complex models are not necessarily more accurate, the model ensemble produces realistic results on average and model applicability is currently high.</description><identifier>ISSN: 1354-1013</identifier><identifier>EISSN: 1365-2486</identifier><identifier>DOI: 10.1111/gcb.16384</identifier><identifier>PMID: 36117412</identifier><language>eng</language><publisher>Oxford: Blackwell Publishing Ltd</publisher><subject>Accuracy ; Biodiversity and Ecology ; Carbon ; Climate change ; Climate change mitigation ; Climate models ; Climate prediction ; Dimensions ; eddy‐covariance ; Environmental gradient ; Environmental impact ; Environmental Sciences ; Fluxes ; Forests ; gap model ; Impact prediction ; Mitigation ; model ensemble ; model evaluation ; Plant species ; Primary production ; process‐based modeling ; Productivity ; Radiation ; Realism ; Systematic errors ; terrestrial carbon dynamics ; Vapor pressure ; Vapour pressure</subject><ispartof>Global change biology, 2022-12, Vol.28 (23), p.6921-6943</ispartof><rights>2022 The Authors. published by John Wiley &amp; Sons Ltd.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Attribution</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3994-7c0973e319ae96554e56647bae25fbd487d6c6b515dd59ff04555cae8de8273f3</citedby><cites>FETCH-LOGICAL-c3994-7c0973e319ae96554e56647bae25fbd487d6c6b515dd59ff04555cae8de8273f3</cites><orcidid>0000-0001-9633-7350 ; 0000-0001-6893-6890 ; 0000-0002-7328-1187 ; 0000-0002-9755-8814 ; 0000-0002-4980-8487 ; 0000-0001-7109-273X ; 0000-0003-2600-984X ; 0000-0003-1067-1492 ; 0000-0001-8938-0908 ; 0000-0002-1341-921X ; 0000-0001-7017-6640 ; 0000-0002-3035-4737 ; 0000-0003-3780-7206 ; 0000-0002-1932-5011 ; 0000-0003-3604-8279 ; 0000-0001-6377-0262 ; 0000-0003-1191-4716 ; 0000-0001-6902-2257 ; 0000-0003-4380-7472 ; 0000-0002-5218-6682 ; 0000-0003-2649-9447 ; 0000-0002-2942-9180 ; 0000-0001-6561-1943 ; 0000-0002-5884-210X ; 0000-0002-7658-6402 ; 0000-0002-0935-6201 ; 0000-0003-2028-6969 ; 0000-0002-8363-656X ; 0000-0003-4233-0094 ; 0000-0001-6468-4411 ; 0000-0001-6905-8356 ; 0000-0002-6255-9059 ; 0000-0001-5513-5496 ; 0000-0001-5427-6836 ; 0000-0002-2533-3739 ; 0000-0003-1854-0761 ; 0000-0003-2475-2111</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fgcb.16384$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fgcb.16384$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://hal.inrae.fr/hal-04066667$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Mahnken, Mats</creatorcontrib><creatorcontrib>Cailleret, Maxime</creatorcontrib><creatorcontrib>Collalti, Alessio</creatorcontrib><creatorcontrib>Trotta, Carlo</creatorcontrib><creatorcontrib>Biondo, Corrado</creatorcontrib><creatorcontrib>D'Andrea, Ettore</creatorcontrib><creatorcontrib>Dalmonech, Daniela</creatorcontrib><creatorcontrib>Marano, Gina</creatorcontrib><creatorcontrib>Mäkelä, Annikki</creatorcontrib><creatorcontrib>Minunno, Francesco</creatorcontrib><creatorcontrib>Peltoniemi, Mikko</creatorcontrib><creatorcontrib>Trotsiuk, Volodymyr</creatorcontrib><creatorcontrib>Nadal‐Sala, Daniel</creatorcontrib><creatorcontrib>Sabaté, Santiago</creatorcontrib><creatorcontrib>Vallet, Patrick</creatorcontrib><creatorcontrib>Aussenac, Raphaël</creatorcontrib><creatorcontrib>Cameron, David R.</creatorcontrib><creatorcontrib>Bohn, Friedrich J.</creatorcontrib><creatorcontrib>Grote, Rüdiger</creatorcontrib><creatorcontrib>Augustynczik, Andrey L. D.</creatorcontrib><creatorcontrib>Yousefpour, Rasoul</creatorcontrib><creatorcontrib>Huber, Nica</creatorcontrib><creatorcontrib>Bugmann, Harald</creatorcontrib><creatorcontrib>Merganičová, Katarina</creatorcontrib><creatorcontrib>Merganic, Jan</creatorcontrib><creatorcontrib>Valent, Peter</creatorcontrib><creatorcontrib>Lasch‐Born, Petra</creatorcontrib><creatorcontrib>Hartig, Florian</creatorcontrib><creatorcontrib>Vega del Valle, Iliusi D.</creatorcontrib><creatorcontrib>Volkholz, Jan</creatorcontrib><creatorcontrib>Gutsch, Martin</creatorcontrib><creatorcontrib>Matteucci, Giorgio</creatorcontrib><creatorcontrib>Krejza, Jan</creatorcontrib><creatorcontrib>Ibrom, Andreas</creatorcontrib><creatorcontrib>Meesenburg, Henning</creatorcontrib><creatorcontrib>Rötzer, Thomas</creatorcontrib><creatorcontrib>Maaten‐Theunissen, Marieke</creatorcontrib><creatorcontrib>Maaten, Ernst</creatorcontrib><creatorcontrib>Reyer, Christopher P. O.</creatorcontrib><title>Accuracy, realism and general applicability of European forest models</title><title>Global change biology</title><description>Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi‐model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests. In this study, we evaluated 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. Multiple models are available that excel according to our three proposed dimensions of model performance. In addition, we find that structural properties are modelled more accurately than carbon fluxes, more complex models are not necessarily more accurate, the model ensemble produces realistic results on average and model applicability is currently high.</description><subject>Accuracy</subject><subject>Biodiversity and Ecology</subject><subject>Carbon</subject><subject>Climate change</subject><subject>Climate change mitigation</subject><subject>Climate models</subject><subject>Climate prediction</subject><subject>Dimensions</subject><subject>eddy‐covariance</subject><subject>Environmental gradient</subject><subject>Environmental impact</subject><subject>Environmental Sciences</subject><subject>Fluxes</subject><subject>Forests</subject><subject>gap model</subject><subject>Impact prediction</subject><subject>Mitigation</subject><subject>model ensemble</subject><subject>model evaluation</subject><subject>Plant species</subject><subject>Primary production</subject><subject>process‐based modeling</subject><subject>Productivity</subject><subject>Radiation</subject><subject>Realism</subject><subject>Systematic errors</subject><subject>terrestrial carbon dynamics</subject><subject>Vapor pressure</subject><subject>Vapour pressure</subject><issn>1354-1013</issn><issn>1365-2486</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp10UtLxDAQB_Agiu-D36DgRcG6mebVHtdlfcCCFz2HNJ1qJdvUxCr77c26iwfBuSSEXzIT_oScAb2GVJMXW1-DZCXfIYfApMgLXsrd9V7wHCiwA3IU4xullBVU7pMDJgEUh-KQzKfWjsHY1VUW0LguLjPTN9kL9hiMy8wwuM6aunPdxyrzbTYfgx_Q9FnrA8aPbOkbdPGE7LXGRTzdrsfk-Xb-NLvPF493D7PpIresqniuLK0UQwaVwUoKwVFIyVVtsBBt3fBSNdLKWoBoGlG1LeVCCGuwbLAsFGvZMbncvPtqnB5CtzRhpb3p9P10oddnlFOZSn1CshcbOwT_PqZZ9bKLFp0zPfox6kKBUBVw4Ime_6Fvfgx9-klSDIqqED9q29wGH2PA9ncCoHqdg0456J8ckp1s7FfncPU_1Hezm82NbzqVhQg</recordid><startdate>202212</startdate><enddate>202212</enddate><creator>Mahnken, Mats</creator><creator>Cailleret, Maxime</creator><creator>Collalti, Alessio</creator><creator>Trotta, Carlo</creator><creator>Biondo, Corrado</creator><creator>D'Andrea, Ettore</creator><creator>Dalmonech, Daniela</creator><creator>Marano, Gina</creator><creator>Mäkelä, Annikki</creator><creator>Minunno, Francesco</creator><creator>Peltoniemi, Mikko</creator><creator>Trotsiuk, Volodymyr</creator><creator>Nadal‐Sala, Daniel</creator><creator>Sabaté, Santiago</creator><creator>Vallet, Patrick</creator><creator>Aussenac, Raphaël</creator><creator>Cameron, David R.</creator><creator>Bohn, Friedrich J.</creator><creator>Grote, Rüdiger</creator><creator>Augustynczik, Andrey L. D.</creator><creator>Yousefpour, Rasoul</creator><creator>Huber, Nica</creator><creator>Bugmann, Harald</creator><creator>Merganičová, Katarina</creator><creator>Merganic, Jan</creator><creator>Valent, Peter</creator><creator>Lasch‐Born, Petra</creator><creator>Hartig, Florian</creator><creator>Vega del Valle, Iliusi D.</creator><creator>Volkholz, Jan</creator><creator>Gutsch, Martin</creator><creator>Matteucci, Giorgio</creator><creator>Krejza, Jan</creator><creator>Ibrom, Andreas</creator><creator>Meesenburg, Henning</creator><creator>Rötzer, Thomas</creator><creator>Maaten‐Theunissen, Marieke</creator><creator>Maaten, Ernst</creator><creator>Reyer, Christopher P. O.</creator><general>Blackwell Publishing Ltd</general><general>Wiley</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope><scope>7X8</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-9633-7350</orcidid><orcidid>https://orcid.org/0000-0001-6893-6890</orcidid><orcidid>https://orcid.org/0000-0002-7328-1187</orcidid><orcidid>https://orcid.org/0000-0002-9755-8814</orcidid><orcidid>https://orcid.org/0000-0002-4980-8487</orcidid><orcidid>https://orcid.org/0000-0001-7109-273X</orcidid><orcidid>https://orcid.org/0000-0003-2600-984X</orcidid><orcidid>https://orcid.org/0000-0003-1067-1492</orcidid><orcidid>https://orcid.org/0000-0001-8938-0908</orcidid><orcidid>https://orcid.org/0000-0002-1341-921X</orcidid><orcidid>https://orcid.org/0000-0001-7017-6640</orcidid><orcidid>https://orcid.org/0000-0002-3035-4737</orcidid><orcidid>https://orcid.org/0000-0003-3780-7206</orcidid><orcidid>https://orcid.org/0000-0002-1932-5011</orcidid><orcidid>https://orcid.org/0000-0003-3604-8279</orcidid><orcidid>https://orcid.org/0000-0001-6377-0262</orcidid><orcidid>https://orcid.org/0000-0003-1191-4716</orcidid><orcidid>https://orcid.org/0000-0001-6902-2257</orcidid><orcidid>https://orcid.org/0000-0003-4380-7472</orcidid><orcidid>https://orcid.org/0000-0002-5218-6682</orcidid><orcidid>https://orcid.org/0000-0003-2649-9447</orcidid><orcidid>https://orcid.org/0000-0002-2942-9180</orcidid><orcidid>https://orcid.org/0000-0001-6561-1943</orcidid><orcidid>https://orcid.org/0000-0002-5884-210X</orcidid><orcidid>https://orcid.org/0000-0002-7658-6402</orcidid><orcidid>https://orcid.org/0000-0002-0935-6201</orcidid><orcidid>https://orcid.org/0000-0003-2028-6969</orcidid><orcidid>https://orcid.org/0000-0002-8363-656X</orcidid><orcidid>https://orcid.org/0000-0003-4233-0094</orcidid><orcidid>https://orcid.org/0000-0001-6468-4411</orcidid><orcidid>https://orcid.org/0000-0001-6905-8356</orcidid><orcidid>https://orcid.org/0000-0002-6255-9059</orcidid><orcidid>https://orcid.org/0000-0001-5513-5496</orcidid><orcidid>https://orcid.org/0000-0001-5427-6836</orcidid><orcidid>https://orcid.org/0000-0002-2533-3739</orcidid><orcidid>https://orcid.org/0000-0003-1854-0761</orcidid><orcidid>https://orcid.org/0000-0003-2475-2111</orcidid></search><sort><creationdate>202212</creationdate><title>Accuracy, realism and general applicability of European forest models</title><author>Mahnken, Mats ; Cailleret, Maxime ; Collalti, Alessio ; Trotta, Carlo ; Biondo, Corrado ; D'Andrea, Ettore ; Dalmonech, Daniela ; Marano, Gina ; Mäkelä, Annikki ; Minunno, Francesco ; Peltoniemi, Mikko ; Trotsiuk, Volodymyr ; Nadal‐Sala, Daniel ; Sabaté, Santiago ; Vallet, Patrick ; Aussenac, Raphaël ; Cameron, David R. ; Bohn, Friedrich J. ; Grote, Rüdiger ; Augustynczik, Andrey L. D. ; Yousefpour, Rasoul ; Huber, Nica ; Bugmann, Harald ; Merganičová, Katarina ; Merganic, Jan ; Valent, Peter ; Lasch‐Born, Petra ; Hartig, Florian ; Vega del Valle, Iliusi D. ; Volkholz, Jan ; Gutsch, Martin ; Matteucci, Giorgio ; Krejza, Jan ; Ibrom, Andreas ; Meesenburg, Henning ; Rötzer, Thomas ; Maaten‐Theunissen, Marieke ; Maaten, Ernst ; Reyer, Christopher P. O.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3994-7c0973e319ae96554e56647bae25fbd487d6c6b515dd59ff04555cae8de8273f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Biodiversity and Ecology</topic><topic>Carbon</topic><topic>Climate change</topic><topic>Climate change mitigation</topic><topic>Climate models</topic><topic>Climate prediction</topic><topic>Dimensions</topic><topic>eddy‐covariance</topic><topic>Environmental gradient</topic><topic>Environmental impact</topic><topic>Environmental Sciences</topic><topic>Fluxes</topic><topic>Forests</topic><topic>gap model</topic><topic>Impact prediction</topic><topic>Mitigation</topic><topic>model ensemble</topic><topic>model evaluation</topic><topic>Plant species</topic><topic>Primary production</topic><topic>process‐based modeling</topic><topic>Productivity</topic><topic>Radiation</topic><topic>Realism</topic><topic>Systematic errors</topic><topic>terrestrial carbon dynamics</topic><topic>Vapor pressure</topic><topic>Vapour pressure</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mahnken, Mats</creatorcontrib><creatorcontrib>Cailleret, Maxime</creatorcontrib><creatorcontrib>Collalti, Alessio</creatorcontrib><creatorcontrib>Trotta, Carlo</creatorcontrib><creatorcontrib>Biondo, Corrado</creatorcontrib><creatorcontrib>D'Andrea, Ettore</creatorcontrib><creatorcontrib>Dalmonech, Daniela</creatorcontrib><creatorcontrib>Marano, Gina</creatorcontrib><creatorcontrib>Mäkelä, Annikki</creatorcontrib><creatorcontrib>Minunno, Francesco</creatorcontrib><creatorcontrib>Peltoniemi, Mikko</creatorcontrib><creatorcontrib>Trotsiuk, Volodymyr</creatorcontrib><creatorcontrib>Nadal‐Sala, Daniel</creatorcontrib><creatorcontrib>Sabaté, Santiago</creatorcontrib><creatorcontrib>Vallet, Patrick</creatorcontrib><creatorcontrib>Aussenac, Raphaël</creatorcontrib><creatorcontrib>Cameron, David R.</creatorcontrib><creatorcontrib>Bohn, Friedrich J.</creatorcontrib><creatorcontrib>Grote, Rüdiger</creatorcontrib><creatorcontrib>Augustynczik, Andrey L. D.</creatorcontrib><creatorcontrib>Yousefpour, Rasoul</creatorcontrib><creatorcontrib>Huber, Nica</creatorcontrib><creatorcontrib>Bugmann, Harald</creatorcontrib><creatorcontrib>Merganičová, Katarina</creatorcontrib><creatorcontrib>Merganic, Jan</creatorcontrib><creatorcontrib>Valent, Peter</creatorcontrib><creatorcontrib>Lasch‐Born, Petra</creatorcontrib><creatorcontrib>Hartig, Florian</creatorcontrib><creatorcontrib>Vega del Valle, Iliusi D.</creatorcontrib><creatorcontrib>Volkholz, Jan</creatorcontrib><creatorcontrib>Gutsch, Martin</creatorcontrib><creatorcontrib>Matteucci, Giorgio</creatorcontrib><creatorcontrib>Krejza, Jan</creatorcontrib><creatorcontrib>Ibrom, Andreas</creatorcontrib><creatorcontrib>Meesenburg, Henning</creatorcontrib><creatorcontrib>Rötzer, Thomas</creatorcontrib><creatorcontrib>Maaten‐Theunissen, Marieke</creatorcontrib><creatorcontrib>Maaten, Ernst</creatorcontrib><creatorcontrib>Reyer, Christopher P. O.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 3: Aquatic Pollution &amp; Environmental Quality</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Global change biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mahnken, Mats</au><au>Cailleret, Maxime</au><au>Collalti, Alessio</au><au>Trotta, Carlo</au><au>Biondo, Corrado</au><au>D'Andrea, Ettore</au><au>Dalmonech, Daniela</au><au>Marano, Gina</au><au>Mäkelä, Annikki</au><au>Minunno, Francesco</au><au>Peltoniemi, Mikko</au><au>Trotsiuk, Volodymyr</au><au>Nadal‐Sala, Daniel</au><au>Sabaté, Santiago</au><au>Vallet, Patrick</au><au>Aussenac, Raphaël</au><au>Cameron, David R.</au><au>Bohn, Friedrich J.</au><au>Grote, Rüdiger</au><au>Augustynczik, Andrey L. D.</au><au>Yousefpour, Rasoul</au><au>Huber, Nica</au><au>Bugmann, Harald</au><au>Merganičová, Katarina</au><au>Merganic, Jan</au><au>Valent, Peter</au><au>Lasch‐Born, Petra</au><au>Hartig, Florian</au><au>Vega del Valle, Iliusi D.</au><au>Volkholz, Jan</au><au>Gutsch, Martin</au><au>Matteucci, Giorgio</au><au>Krejza, Jan</au><au>Ibrom, Andreas</au><au>Meesenburg, Henning</au><au>Rötzer, Thomas</au><au>Maaten‐Theunissen, Marieke</au><au>Maaten, Ernst</au><au>Reyer, Christopher P. O.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accuracy, realism and general applicability of European forest models</atitle><jtitle>Global change biology</jtitle><date>2022-12</date><risdate>2022</risdate><volume>28</volume><issue>23</issue><spage>6921</spage><epage>6943</epage><pages>6921-6943</pages><issn>1354-1013</issn><eissn>1365-2486</eissn><abstract>Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi‐model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests. In this study, we evaluated 13 widely used, state‐of‐the‐art, stand‐scale forest models against field measurements of forest structure and eddy‐covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. Multiple models are available that excel according to our three proposed dimensions of model performance. In addition, we find that structural properties are modelled more accurately than carbon fluxes, more complex models are not necessarily more accurate, the model ensemble produces realistic results on average and model applicability is currently high.</abstract><cop>Oxford</cop><pub>Blackwell Publishing Ltd</pub><pmid>36117412</pmid><doi>10.1111/gcb.16384</doi><tpages>23</tpages><orcidid>https://orcid.org/0000-0001-9633-7350</orcidid><orcidid>https://orcid.org/0000-0001-6893-6890</orcidid><orcidid>https://orcid.org/0000-0002-7328-1187</orcidid><orcidid>https://orcid.org/0000-0002-9755-8814</orcidid><orcidid>https://orcid.org/0000-0002-4980-8487</orcidid><orcidid>https://orcid.org/0000-0001-7109-273X</orcidid><orcidid>https://orcid.org/0000-0003-2600-984X</orcidid><orcidid>https://orcid.org/0000-0003-1067-1492</orcidid><orcidid>https://orcid.org/0000-0001-8938-0908</orcidid><orcidid>https://orcid.org/0000-0002-1341-921X</orcidid><orcidid>https://orcid.org/0000-0001-7017-6640</orcidid><orcidid>https://orcid.org/0000-0002-3035-4737</orcidid><orcidid>https://orcid.org/0000-0003-3780-7206</orcidid><orcidid>https://orcid.org/0000-0002-1932-5011</orcidid><orcidid>https://orcid.org/0000-0003-3604-8279</orcidid><orcidid>https://orcid.org/0000-0001-6377-0262</orcidid><orcidid>https://orcid.org/0000-0003-1191-4716</orcidid><orcidid>https://orcid.org/0000-0001-6902-2257</orcidid><orcidid>https://orcid.org/0000-0003-4380-7472</orcidid><orcidid>https://orcid.org/0000-0002-5218-6682</orcidid><orcidid>https://orcid.org/0000-0003-2649-9447</orcidid><orcidid>https://orcid.org/0000-0002-2942-9180</orcidid><orcidid>https://orcid.org/0000-0001-6561-1943</orcidid><orcidid>https://orcid.org/0000-0002-5884-210X</orcidid><orcidid>https://orcid.org/0000-0002-7658-6402</orcidid><orcidid>https://orcid.org/0000-0002-0935-6201</orcidid><orcidid>https://orcid.org/0000-0003-2028-6969</orcidid><orcidid>https://orcid.org/0000-0002-8363-656X</orcidid><orcidid>https://orcid.org/0000-0003-4233-0094</orcidid><orcidid>https://orcid.org/0000-0001-6468-4411</orcidid><orcidid>https://orcid.org/0000-0001-6905-8356</orcidid><orcidid>https://orcid.org/0000-0002-6255-9059</orcidid><orcidid>https://orcid.org/0000-0001-5513-5496</orcidid><orcidid>https://orcid.org/0000-0001-5427-6836</orcidid><orcidid>https://orcid.org/0000-0002-2533-3739</orcidid><orcidid>https://orcid.org/0000-0003-1854-0761</orcidid><orcidid>https://orcid.org/0000-0003-2475-2111</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1354-1013
ispartof Global change biology, 2022-12, Vol.28 (23), p.6921-6943
issn 1354-1013
1365-2486
language eng
recordid cdi_hal_primary_oai_HAL_hal_04066667v1
source Wiley Online Library Journals Frontfile Complete
subjects Accuracy
Biodiversity and Ecology
Carbon
Climate change
Climate change mitigation
Climate models
Climate prediction
Dimensions
eddy‐covariance
Environmental gradient
Environmental impact
Environmental Sciences
Fluxes
Forests
gap model
Impact prediction
Mitigation
model ensemble
model evaluation
Plant species
Primary production
process‐based modeling
Productivity
Radiation
Realism
Systematic errors
terrestrial carbon dynamics
Vapor pressure
Vapour pressure
title Accuracy, realism and general applicability of European forest models
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T22%3A45%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Accuracy,%20realism%20and%20general%20applicability%20of%20European%20forest%20models&rft.jtitle=Global%20change%20biology&rft.au=Mahnken,%20Mats&rft.date=2022-12&rft.volume=28&rft.issue=23&rft.spage=6921&rft.epage=6943&rft.pages=6921-6943&rft.issn=1354-1013&rft.eissn=1365-2486&rft_id=info:doi/10.1111/gcb.16384&rft_dat=%3Cproquest_hal_p%3E2731292514%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2731292514&rft_id=info:pmid/36117412&rfr_iscdi=true