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USE OF A LINE INTERCEPT SNOW TRACK INDEX AND PLOT SAMPLING FOR ESTIMATING DENSITIES OF WILD UNGULATES IN SOUTHWESTERN POLAND
B.Bobek, D.Merta, J.Furtek
Department of Ecology, Wildlife Research and Ecotourism, Institute of Biology, Pedagogical University of Cracow, Krakow, Poland, b.bobek@o2.pl
I. Introduction
Credible estimates of population numbers provide a basis for sustainable game management and for the protection of endangered animal species. At present, there are many different methods of estimating population numbers of wild animals available, (Mayle et al. 1999; Lancia et al. 2005) but only a few can be widely applied in practice. From 2005-2010, in a large forest complex called 'Bory Dolnosl^s-kie' in southwestern Poland, the usefulness of the snow track density index for estimating the absolute population numbers of red deer, roe deer, and wild boars was tested. Therefore, the objective of this paper is to present the method which was positively verified through practice, as a tool to inventory populations of wild ungulates and help plan their harvests.
II. Study area, material, and methods
The field work was carried out in January and February 2005 within
69.000 hectares of forest constituting a part of the large 'Bory Dolnosl^skie’ forest complex covering a total of
174.000 hectares. The study area is occupied chiefly by coniferous forest habitats with common pine Pinus sil-vestris as the dominant tree species in the stands. A total of 12 large and 12 small sampling plots were selected. The area size of each of the larger sampling plots ranged from 400-500 hectares, roughly square in shape, whereas small sampling plots were elongated rectangular shapes, covering a block of 5-6 forest compartments joined along their length. The smaller sampling plots ranged in size from 100-120 hectares.
The relationships between the snow track density index per kilometre of line transect (T/km) and the population density per 1000 hectares of forest (N/1000 hectares), were studied for red deer and wild boars using large sampling plots, whereas the same relationship for roe deer was determined on the smaller sampling plots.
The first stage of work on large sampling plots was to delineate two line transects within each plot, crossing at the right angle in the central point of the plot. All tracks of red deer and wild boars encountered were erased. On the second day, all the
tracks of these animals on the outline of the plot were again erased, and the number of animals which crossed line transects was determined on the basis of snow tracks left. Thus, the index of snow track density (tracks per km) was obtained, i.e., index of relative population density. Then, 40-50 persons (observers) with 2-3 dogs entered the plots prepared in the above-described manner. The observers were distributed regularly throughout the sampling plot, and their task was to penetrate the area allocated to them and to record all red deer and wild boars spotted, as well as the number and social composition of groups of animals encountered, the time of observation and the direction in which the animals escaped. Dogs were used to drive animals out of young stands. After the observers had left sampling plot, its outline was checked in order to record the number of animals that have left the plot. The space-time analysis enabled the elimination of multiple records of the animals which left or stayed within the plots. The final stage of calculations yielded the absolute density of animals (N/1000 hectares) for each sampling plot.
On small sampling plots, the first stage had involved delineating line transects along forest compartment dividing lines within each plot and erasing the snow tracks of roe deer on these, one day before the population census was conducted. On the next day each sampling plot was surrounded by a dense line of census drivers with head-on observers and observers on both flanks. The plot was then entered by persons recording, on the basis of tracks left, the number of roe deer which had crossed the line transects in the previous 24 hours. The next stage included estimating the number of roe deer in the sample plot using the driving census method (Pucek et al., 1975).
For each sampling plot, the index of track density per unit of length (km) and the population density per unit of area (1000 hectares) were thus obtained. The pairs of data pertaining to the track density index (T/km) and population density (N/1000 hectares) were used to calculate relationships between these variables using a non - linear regression.
III. Results and Discussion
In 12 large sampling plots (total area of 5 404 ha) the presence of 165 red deer and 109 wild boars was detected, and the corresponding population density index (N/1000 hectares) ranged from 2.4-67.1 and from 2.3-52.9 individuals per 1000 hectares of forest, respectively. However, in two large sampling plots red deer and wild boar were not present. The line transects within large sampling plots (total length of 54 km) were crossed by 171 tracks of red deer and 113 wild boars, whereas the track density index (T/km) for these two species in particular sampling plots ranged from 0.227.33 red deer tracks/km, and 0.0-6.67 wild boar tracks/km of transect. For red deer, the relationship between the population density per 1000 hectares of forest (Y1) and the density of tracks per 1 km of transect (X1) is described by the following formula:
Y1 = (83,85) arctan [(0,125) X1], R=0,72 (Fig. 1)
The same relationship for wild boars is described by the following formula:
Y2 = (20.55) arctan [(1.262) X2], R=0,70
where Y2 is the population density per 1000 hectares of forest, and X2 is the snow track density per km of transect.
Within small sampling plots (total area of 1696 ha) 175 roe deer were present, and the population density index in particular samples ranged from 43.4-225.3 individuals/1000 hectares of forest. On line transects within small sampling plots (total length of 15.2 km), 63 tracks of roe deer crossed the transects were recorded. In particular samples, this index ranged from 1.33.-9.33 tracks/km. Both these variables were correlated with each other (R=0.86), and the relationship was expressed by the following formula:
Y3 = (198.88) arctan [(0.154) X3], R=0.86
where Y3 is the population density per 1000 hectares of forest, and X3 is the snow track density per km of transect.
In the past, the relationship between the track density index and population density was used in the studies estimating the population numbers of moos (Alces alces) in a large (110,000 hectares) forest complex in the Augustowska Forest in south-eastern Poland (Bobek et al., 2005). There were 50 km line transects marked per each 10 thousand hectares of forest. Tracking exercises were completed over 5 consecutive days, and the track density index calculated was used to compute the moos population density as well as the total population number for the whole forest complex. The accuracy of the average numbers calculated from the 5-day tracking exercise was high, and in four consecutive years fluctuated within ±5.8-11.2% of the average value at 95% confidence intervals. Similar technique to estimate number of wild boar in Poland was used by Fonseca et al., 2007.
The relationships derived in this study were then used to estimate the population numbers of red deer, roe deer, and wild boar, as well as for
planning the harvest of these species in this part of the Bory Dolnosl^skie forest complex where the material for this study was collected. These further considerations will be addressed as subjects for subsequent publications.
To sum up therefore, the relationship between the track density index (T/km) and the population density can be useful in estimating the numbers of wild ungulates, although this relationship should be derived for local conditions because the mobility of these animals is determined by the depth of snow cover, winter food supply as well as topography of particular area.
REFERENCES
Bobek, B., D. Merta, and P. Sulkowski. 2005. Moose recovery plan in Poland: main objectives and tasks. Alces 41: 129-138.
Fonseca, C., M. Kolecki, D. Merta and B. Bobek. 2007. Use of line intercept tracks index and plot samplings for estimating wild boar Sus scrofa (Sui-dae) in Poland. Folia Zoologica 57(4): 389-398.
Lancia R. A., W. L. Kendall, K. H. Pollock and J. D. Nichols. 2005. Estimating the number of animals in wildlife populations. Pages 106-153 in: C. E. Brown (ed.) Techniques for wildlife investigation and management. The Wildlife Society, Bethesola, Maryland, USA.
Mayle B. A., A. J. Peace and R. M. Gill. 1999. How many deer? A field quide to estimating deer population size. Edinburgh, Forestry Commission. Field Book 18.
Pucek, Z., B. Bobek, L. Labucki, L. Milkowski, K. Morow and A. Tomek. 1975. Estimates of density and numbers of ungulates . Pol. Ecol. Stud. 1: 121-136.
No. of tracks per km
Fig. 1. Relationship between snow track index (X1) and population density (Y1) of red deer in the Bory Dolnosl^skie Forest. Y1=(83.85)*arctan[(0.125)*X1], R=0.72, n=12.
