References:Huth, A., T. Ditzer, and H. Bossel, 1997: Rain Forest Growth Model FORMIX3. German Agency for Technical Cooperation, Eschborn, Germany. (available at http://www.gtz.de/toeb/ftp/formix.pdf)
Growth factor applied to diameter increment on sites of different quality
site qua lity
sp ecies group poor a verage good
em ergents -1 0 % ± 0 % + 1 0 %
m ain ca nopy species -1 3 % ± 0 % + 1 3 %
pioneers -2 5 % ± 0 % + 2 5 %
understorey sp ecies -1 1 % ± 0 % +11%
Growth & yield analysis in tropical rain forest:
applying a stand growth model in a GIS-framework
T. Ditzer
1, M. Förster
2, P. Köhler
1, R. Glauner
2, A. Huth
11Center for Environmental Systems Research, University of Kassel, D-34109 Kassel, Germany
2Institute for World Forestry, Federal Research Centre for Forestry and Forest Products, Leuschnerstr. 91, D-21031 Hamburg, Germany Center for
Environmental Systems Research
The calculation of tree growth is mainly based on light-response characteristics of net photo- synthesis and a simple model of tree physiognomy. Tree species are grouped into 4 functional species groups (emergents, main canopy species, pioneers, under- storey species) and the model is subsequently parametrized based on field data.
Site quality affects the typical physiognomy and average incre- ment of trees. We apply a growth factor ( ) derived from diameter increment measure- ments to reflect the effect on total increments. Height-dia- meter-curves and leaf area in its relation to diameter for differing
site qualities (
) can be derived from field data as well.
The effect of slope gradients on forest dynamics is more hypo- thetical. We assume higher propability of gap formation and less effective light attenuation on steeper slopes.
Parametrization
table below
figures below on the left
Introduction
Approach
Conclusion
Tropical forest management is at a crossroad. Long-term field data to determine timber growth, to fix An- nual Allowable Cuts (AACs), and to assess forest disturbance are widely not available. This problem can be bridged by growth models which provide a valuable tool supporting yield regulation.
Presently only few operational models exist for tropical rain forest.
Such models simulate forest dyna- mics in stands of approx. 1 ha. We use the model in a GIS- framework to support forest ma- nagement decisions on the larger scale of field operation. This poster presents our concept of how to apply for the 55.000 ha of Deramakot Forest Reserve in Sabah, Malaysia.
is a process-based model developed for ecological studies and management planning in the Dipterocarp forests of South-East Asia (Huth et al. 1997). Typical for Malaysia, the Forest Management Units (FMU) cover areas of commercial forest of approxi- mately 100,000 ha. Within the FMU site conditions, actual growing stock, and forest structure vary considerably, especially in heavily logged and partially degraded forests as found at Deramakot.
Our approach considers the FMU as composed of single and mutually independent 0.1-2 ha-stands differing in site conditions and forest structure. We classify site characteristics and actual growing stock to derive a set of s
and analyse their particular present stand structure.
is parametrized for the site conditions reflected in the SSSTs. In simulation, the range of site conditions given at Deramakot determines the . Based on the SSSTs, the regeneration of the
disturbed is
simulated.
In the
we compare different logging strate- gies to evaluate timber yields and the effects on forest structure.
Silvicultural decisionmaking needs support for planning the management of large, hetero- geneous areas. Evaluation of forest resource condition and forest growth for developing sustainable management strate- gies must account for this heterogeneity. The joint applica- tion of a detailed stand growth model and spatial data analysis in a GIS provides a suitable approach to this task.
FORMIX
FORMIX
FORMIX
ite-specific stand types (SSSTs)
The model
potential vegetation present vegetation exemplary simulation of potential timber harvests
FORMIX
Data analysis
We consider a site an area uniform in climate, topogra- phy, and soil conditions producing a specific vege- tation structure, species composition (forest type), and a particular yield.
The description of sites at Deramakot is based on topographic maps, aerial photo interpretation, soil data measured in the field, and a terrestrial forest inventory. These data are captured in a GIS (Geo- graphic Information System) and underly the deter- mination of site-specific stand types (SSSTs).
The SSSTs are based on an analysis of slope gradients (4 slope classes), growing stock (4 stocking strata), and of water and nutrient status of the soil (3 site quality classes). The combination of these geographic layers (
) results in 48 theoretical SSSTs out of which 44 are actually found at Deramakot.
From the terrestrial inven- tory data a representative tree diameter distribution is derived for each SSST.
maps on the left and flow- chart above
0 10 20 30 40 50
0 25 50 75 100 125
dbh [cm]
total height [m]
poor average good
leaf area [m]2
0 200 400 600 800
0 25 50 75 100 125
dbh [cm]
Physiognomic relations of trees on sites of different quality (height diameter curve for emergents)
Comparing logging strategies
Simulations as described on the left allow for comparing different logging strategies.
depicts results for different scenarios of RIL, applying damages of 15 % - 30 % and logging cycles of 20-100 years.
Such analysis helps to investigate the effects of silvicultural decisions on timber yields and forest structure. Once a logging strategy is selected, the respective AAC will (in future work) be determined in the GIS-framework.
The figure on the right
Potential vegetation The model F ORMIX
Present vegetation Site-specific stand types (SSSTs)
Exemplary simulation of potential timber harvests
Simulated forest regeneration of selected SSSTs representing the four strata of actual growing stock
0 50 100 150 200 250
0 20 40 60 80 100 120
time [yr]
standing volume (> 60 cm dbh)[mha]3-1
stratum 1 (SSST 212) stratum 2 (SSST 222) stratum 3 (SSST 232) stratum 4 (SSST 242) 0
50 100 150 200 250 300 350 400 450 500
0 20 40 60 80 100 120
time [yr]
total aboveground biomass[t ODM ha]-1
Simulated mature forest structure on sites of different quality and slope 5°-15°
site qua lity p oor a verage good total abovegr. b iom ass [t ODM h a-1-1] 2 3 2 4 5 1 51 6 basal area (> 1 0 cm dbh ) [m33ha-1-1] 2 1.1 3 0.5 3 5 .6 stem n um ber (> 1 0 cm dbh ) [h a- 1- 1] 7 6 6 7 5 3 81 9 stan din g vol. (> 1 0 cm dbh ) [m33ha-1-1] 2 0 6 3 8 5 43 8 stem n um ber (> 6 0 cm dbh ) [h a- 1- 1] 7 23 2 5 stan din g vol. (> 6 0 cm dbh ) [m33ha-1-1] 66 2 2 5 23 7
Simulated standing volume of harvested trees and the assumably 30 % smaller net timber yield at roadside for different RIL-scenarios on a site of average site quality and slope 5°-15°
harvested standing volume [mhayr3-1-1] net yielded volume [mha3-1yr]-1
0 0.5 1 1.5 2 2.5
20 30 40 50 60 70 80 90 100
logging cycle [yr]
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
15 % damage 20 % damage 25 % damage 30 % damage
Simulated standing volume and stem number of trees >
60 cm dbh in a RIL-scenario with 20 % damage and a 40 year cycle on a site of average site quality and slope 5°-15°
standing volume (> 60 cm dbh) [mha]
3-1
stem number (> 60 cm dbh) [ha]-1 0 5 10 15 20 25 30
0 40 80 120160200240280320360400
time [yr]
0 50 100 150 200 250 stem number 300 standing volume
Simulated mature forest structure dependent on site
Long term simulations of forest development are used to analyse the potential, mature forest structure. Based on the site classi- fication, the model predicts mature forest structure on sites of different slope and most important site quality.
The show simulated
1-ha mature forest stands on sites with diffe- ring qualities and slope of 5°-15°. The
summarizes several structural variables.
, ,
stand pictures on the right table below
stratum 1 (SSST 212)
stratum 2 (SSST 222)
stratum 4 (SSST 242) stratum 3 (SSST 232)
Simulated forest regeneration of SSSTs
An undisturbed develop- ment of the forest at Deramakot is simulated.
Simulations are performed for each of the SSSTs. The tree diameter distribution derived for each SSST initializes the simulation (examples in the
). The SSST’s site quality and slope charac- terize the site conditions.
The
show simulation results for the forest regeneration projected for the four strata on sites of average quality and slope 5°-15°.
pictures on the left
figures on the right
Reduced impact logging (RIL)
We simulate a RIL-technique: only com- mercial species > 60 cm dbh are harvested, 5 of these harvestable trees are left in the forest to foster natural regeneration, and low log- ging damages are assumed. A site with aver- age quality and slope of 5°-15° is simulated.
The shows the stem number
and standing volume (clear bole vol.) of trees of harvestable dimension in a stand logged every 40 years with a 20 % stand damage.
figure on the right
Acknowledgements:The work was supported by the Deutsche Forschungsgemeinschaft (Hu 741/1-1, -2, Kr 683/4-1, -2) and the Malaysian-German Sustainable Forest Management Project in Sandakan (Sabah, Malaysia).
10 km
Deramakot Forest Reserve
emergents main canopy species pioneers understorey species average site quality
good site quality poor site quality
0 25 50 75 100 m
site-specific stand types
inventory stratum
site quality slope
b
slope stratum
SSST
(site-specifc stand type) digital elevation model
(DEM) from 1:25.000 topographic map 4 slope classes (0°-5°, 5°-15°, 15°-25°, >25°)
from 1:25.000 b&w aerial photographs recording of big tree crowns minimum interpretation area of 25 ha 4 strata (0-4, 5-8, 8-16,
> 16 big crowns per ha)
defined by slope class, stratum, and site quality class specific species composition specific diameter distribution
site quality
plant available water and nutrient stock based on soil profile pit descriptions in 1x1 km grid system 3 quality classes (poor, average, good)
inventory
from terrestrial forest inventory 0.25 ha sample plots based on regular 1x1 km grid system recording of tree species and diameter (dbh)
(slope, strat., site qual.)
good midd poorvery S tratum
le poor
Site Quality poor average good
0246810 Kilometers
Sitequality poor average good
