Determining Browsing Capacity

Transcription

1 1 Module # 13 Component # 2 Objective Understand the purpose and methods for determining browsing capacity and to relate the browsing capacity to management decisions for a given area Expected Outcome Define browsing capacity Understand the factors that influence browsing capacity Understand the description and measuring of spatial volume of trees Understand the calculation of browsing capacity Giraffe: Giraffa camelopardalis

2 2 Introduction It is important to determine the browsing capacity of an area to make correct management decisions. The important functional characteristic of the woody component is the browsing potential of the trees and shrubs and the density and height of vegetation. The condition of woody plant communities determines the browsing capacity of an area. Browsing capacity is influenced by the following factors: Density of the woody plants Amount of leaf material within reach of the animal Species composition of the woody vegetation Palatability of the woody species Digestibility of the woody species Growth potential of the woody species Giraffe: Giraffa camelopardalis

3 3 What is Browse? Browse is generally described as being the current season s leaf and twig growth, while the following plant parts all form part of browse: Leaves Young twig material Bark Flowers Pods The browsing capacity of an area determines the amount of browsing animals it can support. Browsing animals can only utilize a certain portion of the browse due to several factors: Certain animals feed at certain heights and this restricts the amount of browse they can utilize. Plants have all adapted themselves to prevent animals from overutilizingia them. Mechanisms such as thorns, spines and secondary metabolites (tannins, phenols See Module # 6) have been developed. Nyala: Tragelaphus angasii Due to several factors such as rain and seasonal changes the palatability of the trees and shrubs fluctuates in such a way over the year that the selective feeding of the animals also varies. Browsing capacity is dynamic in nature and assessments only give an indication of the initial browsing stocking rate.

4 4 The Ecology of Trees If the ecological implications of trees are considered, there are three aspects which are important: Competition with herbaceous vegetation for moisture Food for browsers Creation of sub-habitats suitable for desirable grasses To describe a tree community all these factors must be considered, and suitable units are required. Bearing in mind the ecological effects of trees, the following three quantitative descriptive units are proposed: Evapo-transparation Tree Equivalent (ETTE): Defined as the leaf volume equivalent of a 1.5m (5 foot) single-stemmed Vachellia karroo tree. Browse Tree Equivalent (BTE): One BTE is defined as a single-stemmed Vachellia karroo with a height of 1.5m (5 foot). Canopied Sub-Habitat Index (CSI): Defined as the canopy spread area of those trees in a transect under which associated grasses like Panicum maximum are most likely to occur, expresses as a percentage of the total transect area. These describe the woody plant community condition in terms of potential water use, value of trees as food to browsers and suitability of a sub-habitat for grasses, respectively. The calculation of the ETTE and BTE rests upon the relationship between the spatial volume of a tree and its true leaf volume and leaf mass, respectively, considering differences in leaf densities.

5 5 The Ideal Tree A schematised ideal tree based on an Vachellia karroo is employed in the calculation of spatial volume for any tree. An ideal tree is regarded as a single stemmed tree with a canopy consisting of a dome-shaped crown and a cone-shaped base. The spatial canopy volume is calculated from measurement as follows: A = Tree height B = Height of maximum canopy diameter C = Height of first leaves or potential leaf bearing stems D = Maximum canopy diameter (D1 and D2) E = Base diameter of the total foliage at height C (E1 and E2) The tree is taken as the height of the main tree crown, ignoring any small stems protruding from the crown. Theoretically the canopy is considered as circular, the maximum canopy diameter is calculated as the average of the two measurements rectangular to each other (D1 and D2) whenever the tree is elliptic. The same principles apply to the base diameter E (E1 and E2). D1 and E1 are greater than D2 and E2 respectively. All measurements are based on live tree parts only. Schematic illustration of an ideal tree, its measurements and structure

6 6 Schematic illustration of two non-ideal trees, their measurements and structures

7 7 BECVOL The BECVOL (Biomass Estimates from Canopy Volume) computer program is a program that can be used effectively to derive: Estimates of leaf volume Leaf dry matter ETTE BTE from the association which exists between the spatial canopy volume and its true leaf volume and true leaf mass. The BECVOL program can also calculate stratified estimates of the leaf dry matter below certain specified heights. This is of great help in estimating the available browse for the different browse species considering each species has a limited height above which utilization is not possible. When determining the browsing capacity, the leaf volume that is not within reach of the animals is excluded by using the Maximum Browsing Height (MBH), the maximum height at which a certain animal can browse. The browsing capacity for each animal species will be different because every species utilizes browse at a different height. The mean MBH for three common browsers are: Impala (mixed feeder) < 1 ½ m (5 ft) Kudu < 2m (6 ½ ft) Giraffe < 5m (16 ½ ft) The data entered into the BECVOL program can also be used for structural classification of the vegetation. Of the potential leaf mass, the following should be deducted to determine the available browse: 50% of the browse is beyond the reach of browsers, 25% is deducted for the amount that is utilized by other animals 25% of the remaining mass is to allow for regrowth.

8 8 Example 1. If the total production was 100kg/ha it is first reduced by 50% to 50kg/ha. 2. This is then further reduced by 25% to 37.5kg. 3. Another 25 % deduction is applied (37.5 x 0.75) 4. The result is the available browse at 28.13kg/ha Browsing capacity can then be calculated by dividing the total by the leaf dry mass requirements of one Browsing Unit (BU) per year. One Browser Unit is defined as a kudu of 140 kg (308.6 lbs) that browses exclusively (100%). Small animals are equated to larger animals based on relative energy requirements using metabolic mass. The following equation is used: Animals per BU = (Animal body mass of species x) 0.75 x (% browse in diet) The table below indicates the replacement values for some browser species as well as the mass and average diet composition from which these values were derived. Species Mass (kg) %Graze: % Browse Animals / BU BU / Animal Elephant : Eland : Bushbuck 30 ± 100: Common duiker : Blue duiker 4.5 ± 0: The replacement values for various browsers in Browsing Units

9 9 Greater Kudu: Tragelaphus strepsiceros

10 10 Case Study: Msasa Nature Reserve The homogenous vegetation units that were identified during the Braun-Blanquet survey were used for the survey of the woody plant communities using the Quantitative Description Index Method. The survey is carried out in a 100 x 2m (330 x 6 ½ ft) belt transect. Within this transect every tree that is rooted is sampled. Measurement of the 2m wide belt transect and of the tree dimensions is estimated using a 2m range rod. At least three sample sites were surveyed in each homogenous vegetation unit. The BECVOL computer program was used to enter the data and provided the following estimates: Total leaf mass Canopy volume Leaf volume Total ETTE Browse equivalents at various height levels for the various species. Total leaf mass was calculated for the survey area and then extrapolated to a hectare to give the leaf biomass in kg/ha. To determine the total potential browse available, the leaf biomass was multiplied with the total area of the appropriate homogenous vegetation unit. Of the potential leaf mass, the following was deducted to determine the available browse: 50% of the browse is beyond the reach of browsers, 25% is deducted for the amount that is utilized by other animals 25% of the remaining mass is to allow for regrowth. To calculate the browsing capacity for the year, the actual leaf biomass (kg/ha) was divided by the amount of dry leaf material required to sustain a browse unit for one year. The daily food requirement for an adult kudu is approximately 3% of the animal s body mass. An adult kudu of 140kg would require an amount of 4.20kg (9.3 lbs) of dry leaf material per day or 1533kg/year (3424 lbs / year). The maximum browser height was taken as 2m (6 ½ ft). The reason for this is that the browser height for impala and kudu is 1.5m and 2m respectively and the browse material above this height is not available to these species and is therefore not considered.

11 11 The table below shows: Tree density potential and actual leaf biomass Potential and actual browse and browsing capacities for the respective plant communities. Community 6 had no browse since it is a grassland with no trees present. The total browsing capacity for the area is BU. The BU is very important in determining the stocking levels for browsers. The browsing capacity will be used together with the grazing capacity to determine the ecological capacity and subsequent stocking rates for the study area. Community Size (ha) Tree density (tree/ha) Leaf biomass (kg/ha) Available browse (kg) Potential Actual Potential Actual Browsing capacity (BU) The browsing capacity for Msasa Nature Reserve