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Articles by Clara Antón-Fernández

Category: Research article

article id 10627, category Research article
Christian Kuehne, J. Paul McLean, Kobra Maleki, Clara Antón-Fernández, Rasmus Astrup. (2022). A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway. Silva Fennica vol. 56 no. 1 article id 10627. https://doi.org/10.14214/sf.10627
Keywords: Pinus sylvestris; mortality; volume growth; seemingly unrelated regression; production forestry; system of equations
Highlights: The presented growth and yield model consists of component equations for dominant height, stem density, total basal area, and total stem volume; The component equations were fitted simultaneously using seemingly unrelated regression; The model is capable to forecast and compare outcomes of varying thinning regimes; The new component equations better represent the improved growing conditions for Scots pine in Norway.
Abstract | Full text in HTML | Full text in PDF | Author Info

Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment.

  • Kuehne, Norwegian Institute of Bioeconomy Research, Division of Forestry and Forest Resources, P.O. Box 115, NO-1431 Ås, Norway E-mail: christian.kuehne@nibio.no (email)
  • McLean, Norwegian Institute of Bioeconomy Research, Division of Forestry and Forest Resources, P.O. Box 115, NO-1431 Ås, Norway E-mail: paul.mclean@nibio.no
  • Maleki, Norwegian Institute of Bioeconomy Research, Division of Forestry and Forest Resources, P.O. Box 115, NO-1431 Ås, Norway E-mail: kobra.maleki@nibio.no
  • Antón-Fernández, Norwegian Institute of Bioeconomy Research, Division of Forestry and Forest Resources, P.O. Box 115, NO-1431 Ås, Norway E-mail: clara.anton.fernandez@nibio.no
  • Astrup, Norwegian Institute of Bioeconomy Research, Division of Forestry and Forest Resources, P.O. Box 115, NO-1431 Ås, Norway E-mail: rasmus.astrup@nibio.no
article id 10414, category Research article
Jouni Siipilehto, Micky Allen, Urban Nilsson, Andreas Brunner, Saija Huuskonen, Soili Haikarainen, Narayanan Subramanian, Clara Antón-Fernández, Emma Holmström, Kjell Andreassen, Jari Hynynen. (2020). Stand-level mortality models for Nordic boreal forests. Silva Fennica vol. 54 no. 5 article id 10414. https://doi.org/10.14214/sf.10414
Keywords: Norway spruce; Scots pine; simulation; broadleaved species; logistic function; period length; plot size
Highlights: Models were developed for predicting stand-level mortality from a large representative NFI data set; The logistic function was used for modelling the probability of no mortality and the proportion of basal area in surviving trees; The models take into account the variation in prediction period length and in plot size; The models showed good fit with respect to stand density, developmental stage and species structure, and showed satisfying fit in the independent data set of unmanaged spruce stands.
Abstract | Full text in HTML | Full text in PDF | Author Info

New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age.

  • Siipilehto, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi (email)
  • Allen, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway; Larson and McGowin Inc., Mobile, AL 36607, USA ORCID https://orcid.org/0000-0002-7824-2849 E-mail: micky.allen@nibio.no
  • Nilsson, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden ORCID https://orcid.org/0000-0002-7624-4031 E-mail: urban.nilsson@slu.se
  • Brunner, Norwegian University of Life Sciences (NMBU), Faculty of Environmental Sciences and Natural Resource Management, NO-1432 Ås, Norway ORCID https://orcid.org/0000-0003-1668-9714 E-mail: andreas.brunner@nmbu.no
  • Huuskonen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0001-8630-3982 E-mail: saija.huuskonen@luke.fi
  • Haikarainen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland ORCID https://orcid.org/0000-0001-8703-3689 E-mail: soili.haikarainen@luke.fi
  • Subramanian, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden ORCID https://orcid.org/0000-0003-2777-3241 E-mail: narayanan.subramanian@slu.se
  • Antón-Fernández, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway ORCID https://orcid.org/0000-0001-5545-3320 E-mail: clara.anton.fernandez@nibio.no
  • Holmström, Swedish University of Agricultural Sciences (SLU), Southern Swedish Forest Research Centre, SE-23053 Alnarp, Sweden ORCID https://orcid.org/0000-0003-2025-1942 E-mail: emma.holmstrom@slu.se
  • Andreassen, Norwegian Institute of Bioeconomy Research (NIBIO), Division of Forest and Forest Products, NO-1431 Ås, Norway ORCID https://orcid.org/0000-0003-4272-3744 E-mail: kjellandreassen@gmail.com
  • Hynynen, Natural Resources Institute Finland (Luke), Natural resources, P.O. Box 2, FI-00790 Helsinki, Finland E-mail: jari.hynynen@luke.fi

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