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Prediction of post-thinning stem volume in slash pine stands by means of state and transition models

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Abstract

Predicting growth and production is the key to effective forest management, especially in those stands where silvicultural treatments are more intensive, such as silvopastoral systems. The aim of this study was to fit a state and transition model (STM) to predict the stem volume of slash pine silvopastoral systems under different management strategies. Volume growth was modeled by using the dominant height and the Relative Density Index, which can be related to other density indices (such as the Height Factor) through a proportionality factor. This link between density indices is what makes it possible to develop the transition functions, which are used to predict post-thinning stem volume. The transitional functions were established through three different approaches. Although all of them are good predictors of the Relative Density Index pattern, the best results in volume prediction were obtained when fitting the Weibull model to predict the Relative Density Index as a response of the Height Factor. By using this transition function, the differences in the mean volume between the predicted and observed data were less than 7% for all cases. We conclude that the proposed models are valuable management tools to predict the stem volume accumulated in the post-thinning period, and therefore, this finding may improve the management planning of the plantations of the region.

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Notes

  1. Banchero, Plevich and Fiandino UNRC-undergraduate thesis: "Site curves for Pinus elliottii in the Sierra de Comechingones, Córdoba, Argentina”. Unpublished data.

References

  • Andenmatten E, Letourneau F (2003) Predicción y proyección del rendimiento de pino ponderosa en las provincias de Chubut y Río Negro, Argentina. Quebracho 10:14–25

    Google Scholar 

  • Andenmatten E, Letourneau F, Ortega A (1997) Vínculo entre Densidad Relativa y Factor de Espaciamiento y su relación con la Altura Dominante. In: actas IUFRO “Modelliging growth of fast-grown tree species”, Valdivia, Chile, pp 265–276

  • Assmann E (1970) The principles of forest yield study. Pergamon Press, Oxford

    Google Scholar 

  • Chauchard L, Andenmatten E (2009) Vínculos entre Índices de Densidad: una aproximación para la modelización en rodales de Pinus radiata. Acta XIII Cong Ftal Mundial, Buenos Aires, Argentina

  • Chauchard L, Andenmatten E, Letourneau F (2013) Modelización del crecimiento y la producción de los rodales a través de Índices de Densidad. In Aplicaciones de modelos ecológicos a la gestión de recursos naturales, 1ra ed. OmniaScience Monographs, pp 109–124

  • Chikumbo O, Mareels IM, Turner BJ (1999) Predicting stand basal area in thinned stands using a dynamical model. For Ecol Manag 116:175–187

    Article  Google Scholar 

  • Curtis RO (1982) A simple index of stand density for Douglas-fir. For Sci 27:92–94

    Google Scholar 

  • Del Río M, Calama R, Cañellas I et al (2008) Thinning intensity and growth response in SW-European scots pine stands. Ann For Sci 65:308. https://doi.org/10.1051/forest:2008009

    Article  Google Scholar 

  • Di Rienzo JA, Casanoves F, Balzarini MG et al (2013) InfoStat versión 2013. Grupo InfoStat, FCA, Universidad Nacional de Córdoba, Argentina. http://www.infostat.com.ar. Accessed 15 Jan 2018

  • Diéguez Aranda U, Castedo Dorado F, Alvarez González JG (2005) Funciones de crecimiento en área basimétrica para masas de Pinus sylvestris L. procedentes de repoblación en Galicia. Invest Agrar Sist Rec For 14:253–266

    Article  Google Scholar 

  • Fernández Corradi I (2017) Desarrollo de tablas de producción para rodales de Pinus elliottii implantados en la Sierra de Comechingones, Córdoba. FAV, UNRC, Tesis de grado, Río Cuarto

  • Fiandino SI, Plevich JO, Tarico JC et al (2018) Effects of low-density Pinus elliottii (Slash Pine) afforestation on environmental conditions and native plant diversity, in the mountains of central Argentina. App Veg Sci 21(3):442–450

    Article  Google Scholar 

  • García O (1994) The state-space approach in growth modelling. Can J For Res 24(9):1894–1903

    Article  Google Scholar 

  • Gyenge JE, Fernández ME, Schlichter TM (2010) Effect of stand density and pruning on growth of ponderosa pines in NW Patagonia, Argentina. Agrofor Syst 78(3):233–241

    Article  Google Scholar 

  • Henry M, Besnard A, Asante WA et al (2010) Wood density, phytomass variations within and among trees, and allometric equations in a tropical rainforest of Africa. For Ecol Manag 260:1375–1388

    Article  Google Scholar 

  • Jarsún B, Gorgas J, Zamora A et al (2006) Recursos naturales de la Provincia de Córdoba, Los Suelos. Publ. Téc. Agencia Córdoba Ambiente SE, Córdoba, Argentina

  • Juodvalkis A, Kairiukstis L, Vasiliauskas R (2005) Effects of thinning on growth of six tree species in north-temperate forests of Lithuania. Europ J For Res 124:187–192

    Article  Google Scholar 

  • Kiviste A, Alvarez González JG, Rojo Alboreca A et al (2002) Funciones de crecimiento de aplicación en el ámbito forestal. Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Madrid

  • Li S, Hao Q, Swift E et al (2011) A stand dynamic model for red pine plantations with different initial densities. New For 41(1):41–53

    Article  Google Scholar 

  • Mäkinen H, Isomäki A (2004a) Thinning intensity and growth of Norway spruce stands in Finland. Forestry 77:349–364

    Article  Google Scholar 

  • Mäkinen H, Isomäki A (2004b) Thinning intensity and long-term changes in increment and stem form of Norway spruce trees. For Ecol Manag 201:295–309

    Article  Google Scholar 

  • Mayer DG, Butler DG (1993) Statistical validation. Ecol Modell 68(1–2):21–32

    Article  Google Scholar 

  • Mitchell KJ, Cameron IR (1985) Managed Stand Yield Tables for Coastal Douglas-Fir: Initial density and precommercial thinning. land management report number 31. B.C. Information Services Branch, Ministry of Forests, Victoria. ISSN 0702-9861

  • Nord-Larsen T, Johannsen V (2007) A state-space approach to stand growth modelling of European beech. Ann For Sci 64:365–374. https://doi.org/10.1051/forest:2007013

    Article  Google Scholar 

  • Pesonen A, Eerikäinen K, Maltamo M et al (2009) Models for predicting tree and stand development on larch plantations in Hallormsstaður, Iceland. New For 37(1):63–83

    Article  Google Scholar 

  • Pienaar LV, Shiver BD (1986) Basal area prediction and projection equations for pine plantations. For Sci 32:626–633

    Google Scholar 

  • Premer MI, Chhin S, Zhang J (2017) Alternative approaches to mixed conifer forest restoration: partitioning the competitive neighborhood. New For 48(6):801–816

    Article  Google Scholar 

  • Prodan M, Peters C, Cox F et al (1997) Mensura forestal. Proyecto IICA BMZ/GTZ sobre Agricultura, Recursos Naturales y Desarrollo Sostenible, San José, Costa Rica

  • Tang X, Lu Y, Fehrmann L et al (2016) Estimation of stand-level aboveground biomass dynamics using tree ring analysis in a Chinese fir plantation in Shitai County, Anhui Province, China. New For 47(2):319–332

    Article  Google Scholar 

  • Westoby M (1984) The self-thinning rule. Adv Ecol Res 14(2):167–225

    Article  Google Scholar 

  • Zeide B (1987) Analysis of the 3/2 power law of self-thinning. For Sci 33(2):517–537

    Google Scholar 

Download references

Acknowledgements

This research was funded through a PPI (SECyT-UNRC) and CONICET (doctoral scholarship). The authors thank to the FAV-UNRC Agrometeorology research group for providing meteorological data of the study area. We also thank to the people in charge of “Las Guindas” rural establishment for their help and support.

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Correspondence to Santiago Fiandino.

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11056_2018_9688_MOESM1_ESM.pdf

Summary statistics obtained from the inventories, presented according to the stand density (150, 250 and 450 TPH) (PDF 16 kb)

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Fiandino, S., Plevich, J., Tarico, J. et al. Prediction of post-thinning stem volume in slash pine stands by means of state and transition models. New Forests 50, 663–676 (2019). https://doi.org/10.1007/s11056-018-9688-7

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