Life-style services and yield from south-Swedish forests adaptively managed against the risk of wind damage: a simulation study

We estimated the effect of adapting forest management to reduce the risk of wind damage under climate change on life-style services and forest yield in a south-Swedish forest using an integrated modelling approach. The ECHAM5/CCLM models had been used to produce a reference climate and a climate change scenario for the A1B emission scenario. Using the FinnFor model we estimated the effect of the climate change scenario on the site index for three common commercial tree species for the period 2001–2100. The adjusted site index was applied in projections of the forest using the Forest Time Machine model. The WINDA-GALES model was used to calculate the probability of wind damage in simulated future states of the forest. Effects of increasing forest owner motivation to take measures to adapt to climate change were simulated by comparing the effects of introducing adaptive measures in years 2001 and 2051, respectively. These adaptive measures had been identified in consultation with stakeholders. In the simulations, adaptive regimes resulted in generally increased yield, increased hunting potential and a higher number of forest management operations to be carried out, although other aspects of recreation services were reduced. The net return remained unaffected by most of the adaptive forest management regimes. The simulations were made without accounting for effects of predicted wind damage on the states of the forest. Forest owners perceiving increased risk of wind damage but also risk to their life-style would have to balance adaptive measures between these risks. We conclude that adapting forest management to reduce the risk of wind damage may impact on life-style services. Hence, this may affect the process of adaptation to an increasing risk of wind damage in southern Sweden.

[1]  B. Gardiner,et al.  The stability of different silvicultural systems: a wind-tunnel investigation , 2005 .

[2]  B. Gardiner,et al.  Field and wind tunnel assessments of the implications of respacing and thinning for tree stability , 1997 .

[3]  Magnus Mossberg,et al.  The Forest Time Machine-a multi-purpose forest management decision-support system , 2005 .

[4]  B. Gardiner,et al.  Comparison of two models for predicting the critical wind speeds required to damage coniferous trees , 2000 .

[5]  M. Nilsson,et al.  Countrywide Estimates of Forest Variables Using Satellite Data and Field Data from the National Forest Inventory , 2003, Ambio.

[6]  K. Blennow Adaptation of forest management to climate change among private individual forest owners in Sweden , 2012 .

[7]  Lars Landberg,et al.  Wind Atlas Analysis and Application Program (WASP) Vol. 1: Getting Started , 1998 .

[8]  Chris Hewitt,et al.  Ensembles-based predictions of climate changes and their impacts , 2004 .

[9]  Ulf Hansson,et al.  Evaluation and future projections of temperature, precipitation and wind extremes over Europe in an ensemble of regional climate simulations , 2011 .

[10]  Ola Sallnäs,et al.  Climate change and the probability of wind damage in two Swedish forests. , 2010 .

[11]  Barry Gardiner,et al.  Destructive storms in European forests: past and forthcoming impacts. , 2010 .

[12]  Ari Venäläinen,et al.  Influence of clear-cutting on the risk of wind damage at forest edges , 2004 .

[13]  H. Peltola,et al.  Effects of changing climate on water and nitrogen availability with implications on the productivity of Norway spruce stands in Southern Finland , 2010 .

[14]  D. E. Akin Histological and Physical Factors Affecting Digestibility of Forages , 1989 .

[15]  Mikko Kurttila,et al.  The performance of alternative spatial objective types in forest planning calculations: a case for flying squirrel and moose , 2002 .

[16]  T. Ahti,et al.  Vegetation zones and their sections in northwestern Europe , 1968 .

[17]  Risto Sievänen,et al.  Comparison of a physiological model and a statistical model for prediction of growth and yield in boreal forests , 2003 .

[18]  E. Gumbel,et al.  Statistics of extremes , 1960 .

[19]  Ola Sallnäs,et al.  Risk Perception Among Non-industrial Private Forest Owners , 2002 .

[20]  Sujalakshmy Vasudevan,et al.  Modelling the Dynamics , 2013 .

[21]  Margarida Tomé,et al.  Climate Change: Believing and Seeing Implies Adapting , 2012, PloS one.

[22]  Manfred Näslund,et al.  Skogsförsöksanstaltens gallringsförsök i tallskog , 1936 .

[23]  Gert-Jan Nabuurs,et al.  Natural disturbances in the European forests in the 19th and 20th centuries , 2003 .

[24]  A. Lindhagen,et al.  Forest recreation in 1977 and 1997 in Sweden: changes in public preferences and behaviour , 2000 .

[25]  Johannes Persson,et al.  Climate change: Motivation for taking measure to adapt , 2009 .

[26]  A. Hope A Simplified Monte Carlo Significance Test Procedure , 1968 .

[27]  B. Sæther,et al.  Ecological Correlates of Regional Variation in Life History of the Moose Alces Alces , 1998 .

[28]  Barry Gardiner,et al.  A review of mechanistic modelling of wind damage risk to forests , 2008 .

[29]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[30]  K. Blennow,et al.  Understanding risk in forest ecosystem services: implications for effective risk management, communication and planning , 2014 .

[31]  Ola Sallnäs,et al.  WINDA—a system of models for assessing the probability of wind damage to forest stands within a landscape , 2004 .

[32]  Leif Kristensen,et al.  Extreme winds in Denmark , 2000 .

[33]  Seppo Kellomäki,et al.  Modelling the dynamics of the forest ecosystem for climate change studies in the boreal conditions , 1997 .

[34]  Jean-Claude Ruel Understanding windthrow: Silvicultural implications , 1995 .

[35]  P. Linden,et al.  ENSEMBLES: Climate Change and its Impacts - Summary of research and results from the ENSEMBLES project , 2009 .

[36]  M. Boman,et al.  The hunting value of game in Sweden: Have changes occurred over recent decades? , 2012 .

[37]  K. Blennow,et al.  The probability of wind damage in forestry under a changed wind climate , 2008 .

[38]  K. Blennow,et al.  Potential climate change impacts on the probability of wind damage in a south Swedish forest , 2010 .