DIGITALNA ARHIVA ŠUMARSKOG LISTA
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ŠUMARSKI LIST 9-10/2021 str. 21     <-- 21 -->        PDF

In the 1992–2001 period, 294 stags over one year of age were shot. The antlers were processed so that a trophy may be completely evaluated pursuant to the CIC methods. In addition to a trophy, the mandibles were also processed. The age of the head shot was estimated by the number of dental cementum deposits on the first lower molar (M1) according to the Almasan and Rieck’s method (Almǎsan and Rieck 1970) under a Leica Wild M28 binocular microscope, at a 6.3 to 50x magnification). A deer’s age in years was subtracted from the year of shooting, so that a head’s calving year, i.e., a cohort was obtained that way. Only the cohorts that were represented by more than four head, with an age range of at least three years, were taken into analysis. Therefore, a part of the cohorts was dropped out of the analysis, and 11 cohorts entered the analysis: 1986, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996 and 1997, i.e., a total of 225 trophies.
Pursuant to the CIC rules, the following was measured on the trophies (antlers variables): main beam length, length of brow tines, length of tray tines, circumference of coronets, lower beam circumference (circumference of beam between brow and tray tine), upper beam circumference (circumference of beam between the tray tine and the crown), weight of dry antlers, inside spread, number of tines, qualitative elements (antler colour, pearling, tine tops, bay tines, crowns, and deductions) and trophy value (Hromas et al. 2008).
A distribution normality testing was performed by the Kolmogorov–Smirnov and the Shapiro–Wilk tests. According to these tests, there is no significant difference in data distribution in relation to normality. Comparation of the antler variables was performed by analysis of covariance (ANCOVA), with age as a covariate to control for age-related variation in antler size and cohorts as groups (categorical factors). In case of manifestation of an interaction between equivalence lines, for the calculation of significant difference intervals between the trends, Potthoff’s modification of the Johnson–Neyman method was applied (White 2003; Kim 2010).
Testing among cohorts was performed for each of 9 trophy variables (main beam length, length of brow tines, length of tray tines, circumference of coronets, lower beam circumference, upper beam circumference, weight of dry antlers, number of tines and trophy value among 11 cohorts which values according to the cohorts are given in table 1.
A number of groups and subgroups was determined according to the number of significant difference cases between the mutual comparisons of cohorts for each trophy variable (ANCOVA or Johnson–Neyman method). The groups were classified according to the number of significant differences per column, and the subgroups were classified according to the number of significant differences per row in tables 1 to 9. For example, concerning the antler mass, the number of significant differences per column amounted to 0, 1, 2, 3, 4, 5, 6 and 9 (table 2). Eight groups were obtained that way (table 11). The number of significant differences per row served to rank a variable magnitude within a group. The 1995, 1996, and 1997 cohorts, for example, have not demonstrated a statistically significant mutual difference (the number of significant differences per columns amounted to 0), but various differences were detected between the rows. Thus, the 1997 cohort had a significantly higher antler mass in 3 cases, the 1995 cohort in 6 cases, and the 1996 cohort in 8 cases. Regarding the antler mass variable, all three cohorts are affiliated with the strongest group (Group 1), but the 1996 cohort is the strongest one within the group, followed by the 1995 cohort and ultimately by the 1997 cohort.
Data analysis was performed in Statistica 13.5.0.17 program package (TIBCO Software, 2018).
RESULTS
REZULTATI
The results of ANCOVA and Johnson–Neyman method have demonstrated that the number of differences identified between the cohorts varies (tables 2 to 10) in view of a variable (indicator). Most significant differences between the cohorts are possible to be detected by a trophy value (35 out of 55, 64%), upper beam circumference (35 differences, 64%), circumference of coronets (34 differences, 62%), weight of dry antlers (31 out of 55, 56%) and by lower beam circumference (30 out of 55, 55%). Slightly lesser differences are possible to be detected by length variables. A minimum of difference was detected by the length of tray tines (15 out 55, 27%), slightly more by a length of the beam and length of the brow tine (29 out of 55, 53%), while the number of differences detected was minimal by the number of tines – only 16 (29%).
Most comparisons (351 out of 495) were made by a common covariance analysis, whereby a significant difference between the cohorts was found in 142 cases. In 144 out of 495 comparisons, an interaction was manifested, out of which a significant difference was found in 113 cases. Additionally, a number of interaction cases were increasing along with the number of differences found. In three variables (of main beam length, number of tines, and overall trophy value), more significant differences were found in the interaction comparisons (18, 10, and 21) than in the cases when there is no interaction (11, seven, and 15, respectively).
An interaction phenomenon means that there is no significant difference between two cohorts from or up to certain age, and then a significant difference appears or disappears