UN CO RR EC TE D PR OO F Chapter 7 1 Modelling Continuous Cover Forests 2 Jerome

Continuous cover forestry (CCF) is desirable for many reasons, but this silvicultural 5 approach does add to the complexity of predicting forest growth and timber yield. 6 Many well established techniques such as yield tables and age-based growth 7 models – techniques that are well-established and known to be useful and reliable – 8 are not applicable in the all-aged forests that develop with continuous cover forestry. 9 Thus CCF requires the use of alternative techniques that do not require knowledge 10 of the age of trees, and admit the possibility of trees of all sizes and of many species. 11 While this is not problematic conceptually, it poses some practical challenges 12 in gathering data and calibrating the model, especially if the model deals with 13 interspecific competition and other species interactions. 14 A further complexity is the need to predict regeneration. Most models for 15 plantations and even-aged stands accept initial stocking as an input, and regeneration 16 does not need to be predicted. However, prediction of regeneration is central to 17 CCF, and a CCF model used for long-term simulations must be able to predict the 18 amount and species of regeneration. This can be a complicated undertaking, and 19 the complexity increases with the number and diversity of species (Vanclay 1992; 20 Weiskittel et al. 2011). Because the nature of regeneration is usually dependent on 21 stand conditions in the immediate vicinity, long-term simulations in CCF require a 22 modelling approach that utilizes spatial data (e.g., Newnham and Smith 1964) or 23 simulated small gaps (e.g., JABOWA, Botkin et al. 1972; Sortie, Pacala et al. 1993). 24 The many examples of models for CCF make a comprehensive review with 25 case studies a daunting exercise that this chapter does not attempt, as recent 26 comprehensive reviews are offered elsewhere (Hasenauer 2006; Pukkala 2009; 27 Weiskittel et al. 2011).