The Effect of Climate Parameters on Mean Growing Stock in Russian Forests

Abstract

Mean growing stock across different wood species and age groups of forests based on the State Forest Inventory 2013 data were correlated by means of regression analysis with climate variables averaged over 1981–2000. The following species categories were predefined: all species, conifers, hardwoods, softwoods, and others. The following age groups were predefined: all ages, young growth, middle-aged, pre-mature, with old-growth forests. The correlation and regression analyses were performed for each of the 20 age and species groups of forests. Mean annual temperature, difference between mean July and mean January temperatures, and annual precipitation were independent variables. Mean stock positively correlates with the mean annual temperature and humidity, and negatively correlates with the difference between mean July and mean January temperature. The correlation coefficient between the mean stock and mean annual temperature had a pronounced upward trend across the species groups, as follows by their value: other species, conifers, hardwoods, and softwoods. Multiple polynomial regression equations, which included all possible combinations of independent variables and their quadratic effects, were found for each species and age groups. Determination coefficients had the highest values (R2 > 0.7) for all species, hardwood species, and mature and middle-aged forests of all species and hardwood species. Other wood species and all young growth were the least predictable (R2 < 0.5). The regression equations could be used to forecast changes in the mean growing stock under changing climate for forests overall and their groups of different age and species composition.