The data available on tally
sheets were entered manually into an MS Access database for further analysis.
Three different tables were created within MS Access. The Main table holds raw data
of the survey while the Dsdiv table contains data pertaining
to the geographical and climatic details of the study area. The Botname
table contains the local and botanical names, families and category of the
species. The database structure is shown in Table 6.
Table 6. Structure of the home garden database
Table name |
No. of
records |
Field name |
Description |
Main |
9 568 |
District |
Administrative district |
Srlno |
Identification number
of the DS division used in GIS |
||
Sppno |
Identification number
of the species |
||
Above 30 |
Number of trees in the
DS division above 30 cm girth |
||
Below 30 |
Number of trees in the
DS division below 30 cm girth |
||
Total |
Total number of
trees in both girth classes |
||
Dsdiv |
302 |
District |
Administrative district |
Ds_div |
Name of the DS division |
||
Srlno |
Identification of
the DS division used in the GIS |
||
Cli_zone |
Climatic zone of
the DS division (dry, intermediate, wet) |
||
Gnd |
Number of GN
divisions in the DS division |
||
Villages |
Number of villages
in the DS division |
||
Botname |
142 |
Sppno |
Identification
number of the species |
Lcl_name |
Local name of the
species |
||
Bot_name |
Botanical name of
the species |
||
Family |
Family of the
species |
||
Type |
Category of the
species (timber, timber & food, food) |
The data pertaining to all
the species, regardless of species frequency, were entered into the database for
dry and intermediate zones while only the most common 41 species were entered
into the database for the wet zone. The total number of species reported was
482 and only 76 species, based on the frequency of occurrence, were considered
in the final analysis. They represented 46 timber species, 17 timber and food
species, and 13 food species. Several tables and queries were used within MS
Access for data analysis. The tables and queries were exported subsequently to
MS Excel and DBF formats to generate maps, tables and charts.
A map of Sri Lanka was
produced by digitizing the boundaries of the 25 administrative districts and
302 DS divisions to facilitate the spatial data analysis using the Map Maker
Pro GIS package. The database was linked to the spatial data and several maps
were produced to illustrate the climatic zones, species distribution and
species density.