Resource communicationNew forestry tools for natural beech forests in northwestern Spain

  1. Castaño-Santamaría, Javier
  2. Obeso, Jose R.
  3. Barrio-Anta, Marcos 1
  1. 1 SMartForest Group, Oviedo University, Mieres (Asturias), Spain
Revista:
Forest systems

ISSN: 2171-5068

Año de publicación: 2022

Volumen: 31

Número: 2

Tipo: Artículo

DOI: 10.5424/FS/2022312-19199 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Forest systems

Objetivos de desarrollo sostenible

Resumen

Aim of study: Although beech (Fagus sylvatica L.) forests in north-western Spain constitute c.a. 40% of the total area occupied by the species in the whole country, no growth or yield studies have been carried out regarding these forests. The specific objective of this study was to elaborate yield tables and stand density management diagrams for the beech forests. Area of study: Asturias and León provinces (NW Spain). Material and methods: Sample plots (n=112) were established in natural beech forests, and 60 dominant trees were felled for sampling. The Asturias Government Forest Service provided data on another 351 felled trees. Yield tables and stand density management diagrams (SDMDs) were elaborated to estimate tree volume and biomass in the study area for the first time. Main results: These forests are more productive than expected. Although they are currently not managed for forestry purposes, they could be managed again in the future and the tools are now available for this purpose. Research highlights: The study generates new user-friendly tools to manage beech forests in northwestern Spain. These tools will also enable simulations to be conducted to determine the potential carbon storage or the capacity of the stands to sequester atmospheric carbon.

Referencias bibliográficas

  • Arévalo C, 1954. Proyecto de Ordenación del M.U.P. nº 118 denominado "Pedroso" de la pertenencia a los pueblos de Viego, Casielles y San Ignacio. Concejo de Ponga. Dirección General de Montes, Caza y Pesca Fluvial. Ministerio de Agricultura.
  • Arévalo C, 1956. Proyecto de Ordenación del M.U.P. nº 253 denominado "Valgrande" de la pertenencia del Ayuntamiento de Lena y pueblo de Pajares. Concejo de Lena. Dirección General de Montes, Caza y Pesca Fluvial. Ministerio de Agricultura.
  • Arévalo C, 1960. Proyecto de Ordenación del M.U.P. nº 48 denominado "El Grande". Concejo de Teverga. Dirección General de Montes, Caza y Pesca Fluvial. Ministerio de Agricultura.
  • Barrio M, 2003. Crecimiento y producción de masas naturales de Quercus robur L. en Galicia. Doctoral thesis. Universidad de Santiago de Compostela.
  • Barrio-Anta M, Álvarez-González JG, 2005. Development of a stand density management diagram for even-aged pedunculate oak stands and its use in designing thinning schedules. Forestry 78: 209-216. https://doi.org/10.1093/forestry/cpi033
  • Barrio-Anta M, Balboa-Murias MA, Castedo-Dorado F, Diéguez-Aranda U, Álvarez-González JG, 2006. An ecoregional model for estimating volume, biomass and carbon pools in maritime pine stands in Galicia (northwestern Spain). For Ecol Manage 223: 24-34. https://doi.org/10.1016/j.foreco.2005.10.073
  • Baskerville GL, 1972. Use of logarithmic regression in the estimation of plant biomass. Can J For Res 2: 49-53. https://doi.org/10.1139/x72-009
  • Castaño-Santamaría J, Barrio-Anta M, Álvarez-Álvarez P, 2013. Potential above ground biomass production and total tree carbon sequestration in the major forest species in NW Spain. Int For Rev 15: 273-289. https://doi.org/10.1505/146554813807700083
  • Castaño-Santamaría J, López-Sánchez CA, Obeso JR, Barrio-Anta M, 2019. Modelling and mapping beech forest distribution and site productivity under different climate change scenarios in the Cantabrian Range (North-western Spain). For Ecol Manage 450: 117488. https://doi.org/10.1016/j.foreco.2019.117488
  • Costa M, Morla C, Sainz H, 1998. Los bosques ibéricos. Ed. Planeta, Barcelona. 572 pp.
  • Cunia T, 1965. Some theories on reliability of volume estimates in a forest inventory sample. For Sci 11: 115-127.
  • DGCN, 2006. III Inventario Forestal Nacional (1997-2006). Dirección General de Conservación de la Naturaleza, Ministerio de Medio Ambiente, Madrid.
  • Draper NR, Smith H, 1998. Applied regression analysis. Wiley, New York. 706 pp. https://doi.org/10.1002/9781118625590
  • Field CB, Campbell JE, Lobell DB, 2008. Biomass energy: the scale of the potential resource. Trends Ecol Evol 23: 65-72. https://doi.org/10.1016/j.tree.2007.12.001
  • García D, Quevedo M, Obeso JR, Abajo A, 2005. Fragmentation patterns and protection of montane forest in the Cantabrian range (NW Spain). For Ecol Manage 208: 29-43. https://doi.org/10.1016/j.foreco.2004.10.071
  • Gertner GZ, 1986. Postcalibration sensitivity procedure for regressor variable errors. Can J For Res 16: 1120-1123. https://doi.org/10.1139/x86-195
  • Gertner GZ, 1990. The sensitivity of measurement error in stand volume estimation. Can J For Res 20: 800-804. https://doi.org/10.1139/x90-105
  • Ibáñez JI, 1989. El haya (Fagus sylvatica L.) en La Rioja. Selvicultura y ordenación. Doctoral thesis. Universidad Politécnica de Madrid, Madrid.
  • Keeton WS, Whitman AA, McGee GC, Goodale CL, 2011. Late-successional biomass development in northern hardwood-conifer forests of the northeastern United States. For Sci 57: 489-505.
  • Long JN, 1985. A practical approach to density Management. For Chron 23: 23-26. https://doi.org/10.5558/tfc61023-1
  • Madrigal A, Puertas F, Martínez Millán J, 1992. Tablas de producción para "Fagus sylvatica L." en Navarra. Ed. Gobierno de Navarra, Ser. Agr. 3, Pamplona. 141 pp.
  • Matthews RW, Jenkins TAR, Mackie ED, Dick EC, 2016. Forest yield: A handbook on forest growth and yield tables for British forestry. Forestry Commision, Edinburgh.
  • McKinley DC, Ryan MF, Birdsey RA, Giardina CP, Harmon ME, Heath LS et al., 2011. A synthesis of current knowledge on forests and carbon storage in the United States. Ecol Appl 21: 1902-1924. https://doi.org/10.1890/10-0697.1
  • Meyer HA, 1944. A correction for systematic error occurring in the application of the logarithmic volume equation. Pennsylvania State University. Forest Research Paper nº 7.
  • Montero G, Ruiz-Peinado R, Muñoz M, 2005. Producción de biomasa y fijación de CO2 por los bosques españoles. Monografías INIA: Serie Forestal, no 13. INIA, Madrid. 270 pp. https://libros.inia.es/libros/product_info.php?cPath=12&products_id=64
  • Mund M, 2004. Carbon pools of European beech forests under different silvicultural management. Doctoral thesis. Georg-August-Universität Göttingen.
  • Návar J, Domínguez P, 1997. Ajuste de modelos de volumen y funciones que describen el perfil diamétrico de cuatro especies de pino plantadas en el Nordeste de México. Invest Agrar: Sist Recur For 6: 147-163.
  • Newton PF, 1997. Stand density management diagrams: review of their development and utility in stand-level management planning. For Ecol Manage 209: 181-192.
  • Parresol B, 1999. Assessing tree and stand biomass: A review with examples and critical comparisons. For Sci 45: 573-593.
  • Ramos M, 1969. Primera Revisión del Proyecto de Ordenación del M.U.P. nº 119 denominado "Peloño". Concejo de Ponga. Dirección General de Montes, Caza y Pesca Fluvial. Ministerio de Agricultura.
  • Ruiz-Peinado R, Montero G, Del Río M, 2012. Biomass models to estimate carbon stocks for hardwood tree species. For Syst 21: 42-52. https://doi.org/10.5424/fs/2112211-02193
  • Sánchez A, Ayuga E, Grande MA, García-Abril A, 2008. Forestry alternatives to Navarran yield tables for beech (Fagus sylvatica L.). Allg Forst- u J -Ztg 179: 225-231.
  • SAS, 2004. SAS/ETS 9.1: user's guide. SAS Inst. Inc., Cary, NC, USA.
  • Vanclay JK, 1994. Modelling forest growth and yield: Applications to mixed tropical forests. CAB Int., Wallingford (UK). 329 pp.
  • Wilcox R, Peterson TJ, McNitt-gray JL, 2018. Data analyses when sample sizes are small: Modern advances for dealing with outliers, skewed distributions, and heteroscedasticity. J App Biomech 34: 258-261. https://doi.org/10.1123/jab.2017-0269
  • Zellner A, 1962. An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. J Am Stat Assoc 57: 348-368. https://doi.org/10.1080/01621459.1962.10480664
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