Natural regeneration density model developed for the purposes of the individual-tree growth simulator | Model hustoty prirodzeného zmladenia pre účely stromového rastového simulátora

Models of natural regeneration represent an important amendment to complex growth models. They allow making prognoses behind one production cycle of a forest, and simulating the development of natural and virgin forests. This work deals with modelling natural regeneration density, which is the first step towards the complex model of natural regeneration. The model will be a part of the individual-tree growth simulator SIBYLA. The model was developed using the data from National forest inventory and monitoring of the Slovak Republic (NFIM SR), and using the climatic rasters with the pixel of size of 90 x 90 m, which capture spatial distribution of all important climatic characteristics. The model itself consists of an empirical part, which simulates regeneration density (number per hectare) at a stand level, and of a process-based part, which simulates seed production and seedling germination at a tree level. The empirical part of the model is based on the data of NFIM SR and climatic rasters, and simulates regeneration density for individual tree species in relation to quadratic mean diarneter of the parent stand and its crown coverage. In addition, the model is site-specific. The process-based part of the model is based on seeding functions and fuzzy logic. It is based on the prediction of seed yield of individual trees in relation to such characteristics as seed purity, seed quality, germination capacity, absolute weight of seeds, seed production per an adult tree, etc. The production is further modified with regulators and reduction factors, which describe other conditions necessary for the germination, survival, and the establishment of the next generation. In the next step, empirically-derived regeneration density is reduced in relation to the ratio of individual tree species to the total production of all individuals estimated from the process-based model.