Accounting for windthrow risk in forest management planning: a Romanian tailor-made solution

Marian Dragoi, Ionut Barnoaiea


Aim of study: To better estimate the annual allowable cut reserve (AACR), taking into consideration the endemic windthrows (EW), we combined a series of existing algorithms into a coherent methodology to use the data available at district level, without any additional fieldworks.

Area of study: The algorithm was tested on the EW occurred in the last 20 years in Brosteni FD (Eastern Carpathians, Romania) that covers 21,013 ha and we found that every year from an AAC of 37,000 m3 no more than 2,700 m3 shall be spared for EW that might occur next year.

Material and methods: We considered three EW enabling factors (stand slenderness, location on pits and mounds, and the vicinity of canopy gap) and three contingency tables of the EW produced between 1999 and 2008, one for each 40-year age group. Then we calculated a Bayesian model for all six permutations of enabling factors, each of them being tested on the data referring to 2008-2017 period

Results: Plugging the posterior EW likelihoods into a Markov chains (MC) model, we produced a formula that enables a better estimation of the optimal AACR that could be replaced with salvage cuttings every next year. Other options of using the EW likelihoods are also presented at length, such as the type of age-class structure that requires no AACR, that is a “U” shape age structure, as well as a rough assessment of the additional demand for seedlings needed to re-plant the stands affected by EW. The relatively short period of time the input data refer to, which is ten years, equals the time window of the forest planning and this parity allows a ten-year forecast period, enough for modeling the stationary age-structure of even-aged forests.

Research highlights: A new model for optimizing the annual allowable cut (AAC) in even-age forests in the context of endemic windthrows (EW) scenario has been developed and evaluated.

Keywords: Bayes’ rule, forest management planning, endemic windthrows.


Bayes’ rule, forest management planning, endemic windthrows

Full Text:



Anonymous, 2013: Summary of the Audit Report concerning "the patrimonial state of the Romanian Forest Fund between 1990 and 2012. Court of Accounts of Romania.

Bolte A, Ammer C, Löf M, Madsen P, Nabuurs G-J, Schall P, Spathelf P, Rock J, 2009. Adaptive forest management in central Europe: Climate change impacts, strategies and integrative concept. Scand J Forest Res 24(6): 473–482.

Boon S, 2012. Snow accumulation following forest disturbance. Ecohydrology 5(3): 279–285.

Bošela M, Konôpka B, Šebeň V, Vladovič J, Tobin B, 2014. Modelling height to diameter ratio – an opportunity to increase Norway spruce stand stability in the Western Carpathians. Forestry J 60: 71.

Buongiorno J, Zhou M, 2011. Further generalization of Faustmann's formula for stochastic interest rates. J Forest Econ 17(3): 248–257.

Bouriaud L, 2005. Causes of illegal logging in Central and Eastern Europe. Small-Scale For 4: 269–291.

de Filippi R, Palma J, Reisner Y, Herzog F, 2004. Spatial database for GIS for scaling up. Research Report. Swiss Federal Research Station for Agroecology and Agriculture. 9 pp.

Drăgoi M, 2010. Compensating the opportunity cost of forest functional zoning - two alternative options for the Romanian forest policy. Ann Forest Res 52(1): 81-92.

Gadow K Von, 2000. Evaluating Risk in Forest Planning Models. Silva Fenn 34: 181–191.

Hanewinkel M, Hummel S, Albrecht A, 2010. Assessing natural hazards in forestry for risk management: a review. Eur J Forest Res 130(3): 329–351.

Holecy J, Hanewinkel M, 2006. A forest management risk insurance model and its application to coniferous stands in southwest Germany. Forest Policy Econ 8(2): 161–174.

Holeksa J, Jaloviar P, Kucbel S, Saniga M, Szewczyk J, Szwagrzyk J, Zielonka T, Żywiec M, 2017, Models of disturbance driven dynamics in the West Carpathian spruce forests. Forest Ecol Manage 388: 79–89.

Keith M, Adams P, Bryant D, Mitchelson K, Cochran D, Lala G, 2003 Inferring an Original Sequence from Erroneous Copies: Two Approaches. J. Bioinform Comput Biol 6(3): 107-114.

Klaus M, Holsten A, Hostert P, Kropp J, 2011. Integrated methodology to assess windthrow impacts on forest stands under climate change. Forest Ecol Manage 261(11): 1799–1810.

Konopka J, Petras R, Toma R, 1987. Slenderness coefficient of the major tree species and its importance for static stability of stands. Lesnictvi 33: 887-904.

Kouba J, 2002. Das Leben des Waldes und seine Lebensunsicherheit, Forstwiss Centralbl (Hamb) 121(4): 211–228.

Lanquaye-Opoku N, Mitchell SJ, 2005. Portability of stand-level empirical windthrow risk models. Forest Ecol Manage 216(1–3): 134–148.

Lohmander P, Helles F, 1987. Windthrow probability as a function of stand characteristics and shelter. Scand J Forest Res 2(1–4): 227–238.

Mitchell SJ, 1995. The windthrow triangle : A relative windthrow hazard assessment procedure for forest managers windthrow Triangle Soils. Forest Chron 71(4): 446–450.

Mitchell SJ, 1998. A diagnostic framework for windthrow risk estimation. Forest Chron 74(1): 100–105.

Nilsson C, Stjernquist I, Bärring L, Schlyter P, Jönsson, AM, Samuelsson H, 2004. Recorded storm damage in Swedish forests 1901-2000. Forest Ecol Manage 199(1): 165–173.

Nolet P, 2012. Predicting Stem Windthrow Probability in a Northern Hardwood Forest Using a Wind Intensity Bio-Indicator Approach. Open J Forest 2(2): 77–87.

Nolet P, Béland M, 2017. Long-term susceptibility of even-and uneven-aged northern hardwood stands to partial windthrow, Forests 8(4).

Nöth M, Weber M, (2003). Information aggregation with random ordering: Cascades and overconfidence. Economic J 113(484): 166–189.

Olofsson E, Blennow K, 2005. Decision support for identifying spruce forest stand edges with high probability of wind damage. Forest Ecol Manag 207: 87–98.

Panferov O Sogachev A, 2008. Influence of gap size on wind damage variables in a forest. Agric Forest Meteorol 148(11): 1869-1881.

Popa I, 2005. Doborâturi produse de vânt-factor de risc în ecosistemele forestiere montane. (Windthrows – risk factors if mountainous forest ecosystems). Anale ICAS 48(4).

Popa I, 2008. Windthrow risk management: results from Romanian forests. Disturbi in foresta ed effetti sullo stock di carbonio: il problema della non permanenzai, Pubblicazione del Corso di Cultura in Ecologia, Atti del 44 corso, 77-88.

Schlyter P, Stjernquist I, Bärring L, Jönsson AM, Nilsson C, 2006. Assessment of the impacts of climate change and weather extremes on boreal forests in northern Europe, focusing on Norway spruce. Clim Res 31(1): 75–84.

Schindler D, Grebhan K, Albrecht A, Schönborn, J, 2009. Modelling the wind damage probability in forests in Southwestern Germany for the 1999 winter storm 'Lothar'. Int J Biometeorol 53(6): 543-554.

Schliemann SA, Bockheim JG, 2011. Methods for studying treefall gaps: A review. For Ecol Manage 261(7): 1143–1151.

Scott R.E, Mitchell SJ, 2005. Empirical modelling of windthrow risk in partially harvested stands using tree, neighbourhood, and stand attributes. Forest Ecol Manag 218(1-3): 193-209.

Senf C, Seidl R, 2017. Natural disturbances are spatially diverse but temporally synchronized across temperate forest landscapes in Europe. Glob Change Biol 3218–3221.

Strigul N, Florescu I, Welden AR, Michalczewski F, 2012. Modelling of forest stand dynamics using Markov chains. Environ Model Softw 31: 64–75.

Ulanova NG, 2000. The effects of windthrow on forest at different spatial scales: a review. Forest Ecol Manag 135: 155–167.

Waldron K, Ruel JC Gauthier S, 2013. Forest structural attributes after windthrow and consequences of salvage logging. Forest Ecol Manag 289: 28–37.

Wintle BA, Lindenmayer DB, 2008. Adaptive risk management for certifiably sustainable forestry. Forest Ecol Manage 256(6): 1311–1319.

Yousefpour R, Jacobsen JB, Thorsen BJ, Meilby H, Hanewinkel M, Oehler K, 2012. A review of decision-making approaches to handle uncertainty and risk in adaptive forest management under climate change. Ann Forest Sci 69(1): 1–15.

DOI: 10.5424/fs/2018273-13333