Sensitivity of long-term productivity estimations in mixed forests to uncertain parameters related to fine roots.

Yeste Yeste, Antonio; Seely, Brad; Imbert Rodríguez, Bosco; Blanco Vaca, Juan Antonio

Sensitivity of long-term productivity estimations in mixed forests to uncertain parameters related to fine roots.

dc.contributor.author	Yeste Yeste, Antonio
dc.contributor.author	Seely, Brad
dc.contributor.author	Imbert Rodríguez, Bosco
dc.contributor.author	Blanco Vaca, Juan Antonio
dc.contributor.department	Ciencias	es_ES
dc.contributor.department	Zientziak	eu
dc.contributor.department	Institute for Multidisciplinary Research in Applied Biology - IMAB	en
dc.date.accessioned	2024-03-01T08:40:04Z
dc.date.available	2024-03-01T08:40:04Z
dc.date.issued	2024
dc.date.updated	2024-03-01T08:29:18Z
dc.description.abstract	Forest growth models are increasingly being used in forestry and ecology research as predictive tools to help developing practical guidelines and to improve understanding of the drivers of forest ecosystem functioning. Models are usually calibrated using parameters directly obtained or estimated from empirical field observation, and hence are subject to uncertainty. Thus, output accuracy depends on input parameters precision and on how influential is each parameter on model behaviour. Hence, it is important to analyse parameter-related uncertainty and its effects on model outputs. This can be done by performing sensitivity analyses, which allow to explore the influence of one or several calibration parameters on model outputs. As studies on tree root parameters are particularly scarce, the aim of the present work was to evaluate the influence of parameters related to fine roots on estimations of long-term forest growth patterns in pure and mixed forests, using FORECAST (a hybrid forest growth model) as a virtual lab. The fine root parameters assessed were biomass, turnover rate, and nitrogen content. The analysis was performed by simulating monospecific stands of two contrasting species (Pinus sylvestris L. and Fagus sylvatica L.), and mixed stands formed by both species. In all cases, FORECAST showed good capability to contain uncertainty propagation during the first and middle stages of stand development (<40 years). After that moment, model output uncertainty steadily increased, but it reached different maximum uncertainty levels depending on stand type. Simulations of the less nutrient demanding P. sylvestris manifested very little sensitivity when growing in monospecific stands. However, F. sylvatica monospecific stands showed intermediate sensitivity, but significant species interactions occurred in mixed stands that determined the biggest impact detected of uncertainty related to fine root parameters over model outputs. All things considered, FORECAST displayed an interesting capability to capture some of the interspecific interactions that are key in mixed forests functioning. Our results suggest an acceptable model performance under uncertain parameterization but also caution against expecting accurate quantitative estimations of forest growth, especially when considering long-term scenarios in complex mixed stands.	en
dc.description.sponsorship	This research was funded by the Spanish Ministry of Economy and Competitiveness (grant AGL2016-76463-P TIMENUTRIENT) and the Spanish Ministry of Science and Innovation (grant TED2021-131081BC21). A.Y. was funded through a Spanish Predoctoral Research Grant (BES-2017-080326).	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Yeste, A., Seely, B., Imbert, J. B., Blanco, J. A. (2024) Sensitivity of long-term productivity estimations in mixed forests to uncertain parameters related to fine roots. Ecological modelling International journal of ecological modelling and engineering and sustems ecology, 490, 1-12. https://doi.org/10.1016/j.ecolmodel.2024.110670.	es_ES
dc.identifier.doi	10.1016/j.ecolmodel.2024.110670
dc.identifier.issn	0304-3800
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/47604
dc.language.iso	eng	en
dc.publisher	Elsevier	en
dc.relation.ispartof	Ecological Modelling, 2024, vol. 490	es_ES
dc.relation.projectID	info:eu-repo/grantAgreement/MINECO//AGL2016-76463-P/
dc.relation.projectID	info:eu-repo/grantAgreement/MICINN//TED2021-131081B-C21/
dc.relation.projectID	info:eu-repo/grantAgreement///BES-2017-080326/
dc.relation.publisherversion	https://doi.org/10.1016/j.ecolmodel.2024.110670
dc.rights	© 2024 The Authors. This is an open access article under the CC BY-NC license.	en
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.rights.uri	https://creativecommons.org/licenses/by-nc/4.0/
dc.subject	Forest growth modelling	en
dc.subject	FORECAST	en
dc.subject	Mixed forests	en
dc.subject	Sensitivity analysis	en
dc.subject	Fine roots	en
dc.subject	Pinus sylvestris	en
dc.subject	Fagus sylvatica	en
dc.title	Sensitivity of long-term productivity estimations in mixed forests to uncertain parameters related to fine roots.	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
dspace.entity.type	Publication
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