JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
Session 2.1 yield, carbon density & climate change bagras
1. Yield, Carbon Density and Climate Change
Impact on Bagras (Eucalyptus Deglupta Blume)
in Corn-Based Hedgerow Intercropping
Agroforestry System in Northern Mindanao,
Philippines
R.A. Palma, Ph.D* and W.M. Carandang, Ph.D**
*Assistant Professor, Misamis Oriental State College of Agriculture and
Technology, Claveria, Misamis Oriental, Philippines
**Professor, College of Forestry and Natural Resources, University of the
Philippines Los Banos, College, Laguna, Philippines
2. INTRODUCTION
• Yield estimation of standing
timber is crucial for a successful
agroforestry enterprise.
• Yield studies should be
undertaken to effectively
demonstrate the economic
feasibility of growing bagras in
an agroforestry system.
3. • Little has been published in the Philippines, or
elsewhere, about timber yields from corn-based
hedgerow intercropping agroforestry system.
• With suitable inventory and other resource data,
yield models provide a reliable way to examine
silvicultural options and to determine the
sustainable timber yield for different areas and
management strategies (Vanclay, 1994).
4. OBJECTIVES
1.Develop reliable yield model for management of
hedgerow intercropping agroforestry system
using Eucalyptus deglupta Blume (Bagras)
relative to soil - site index, age and stand
density, provenance, temperature and rainfall;
2. Compare the yield of Bagras in corn-based
hedgerow intercropping with various
agroforestry systems;
5. 3.Determine above ground carbon
density of bagras; and,
4. Assess the impact of future climate
change on the yield of Bagras.
10. Regression Diagnostics and Analysis
• unusual data
• influential data
• checking normality of residuals
• homocedasticity of residuals
• multicollinearity
• linearity
• model specification
11. Multiple Linear Regression
Analysis (STATA v. 10)
Development of Yield Model
Y = f[site index (SI), age (A),
spacing) (SP), basal area
(BA), provenance (P), rainfall
(RF), Temperature (T)]
12. AGB (ton per tree) = volume over bark (m3 per
tree) * wood density (g/ cc) * biomass
expansion factor (BEF)
Carbon Density
The above ground carbon density of bagras was
determined using the formula (Brown and Lugo,
1992):
13. Assessing Future Climate Change Impact
• The impact of future climate change on the yield
of bagras was assessed based on the projected
change in seasonal mean RF and T of the
Province of Bukidnon.
• The data was extracted from PAGASA PRECIS
Regional Climate Model (climate change scenario)
14. RESULTS AND DISCUSSION
LnYield = 1.4284 - 0.0251*SI + 0.0094*Age +
1.0128*LnBA + 0.0003*Rainfall
R2 = 0.9620
• The model had shown that for every unit increase
in independent variables (except SI), there was an
equivalent increase in volume.
15. • These predicted changes were logical in terms of
the physiological aspect of tree growth.
• Growth was reduced when planted at an
elevation close to 1000 masl.
16. • RF in this model also posed
considerable influence in volume
(2.8 % per 100 mm increase).
Precipitation is important to plant
growth, not only for photosynthesis
but also in nutrient dynamics.
17. • BA an expression of stand density, had
significant contribution to the changes in volume
amounting to approximately 48.9 %.
• It is a general knowledge that increasing SP up
to certain maximum will also result to the
increase in height and diameter and eventually
volume of wood harvested.
18. • The negative direction of the effect of SI with
yield is not expected.
• The negative coefficient could be due to
combined effects of physiographic and edaphic
factors.
• Negative direction of the effect of site index with
yield of Teak (Tectona grandis) and Ipil-ipil
(Leucaena leucocephala) were also found in the
study of Pinol (1990) and Pinol et al. (1985).
19. • The estimated mean annual increment (MAI) of
Bagras was 0.0016 m3 yr-1 or equivalent to 0.67 m3
ha-1 yr-1 (420 trees per ha).
Timber Yield in Corn-Based Hedgerow
Intercropping Agroforestry System
• Even though the value generated from the model is
quite low, it does not in any way reflect any
irregularity. The result had elucidated the intrinsic
nature of the data used in model construction.
20. • The average annual yield is only 7.43 m3 ha-1 yr-1
with an average of 0.0177 m3 per tree (SI = 18;
RF = 1700 mm).
• However, planting Bagras in an area with high RF
(2700 mm) was predicted to yield up to 9.73 m3
ha-1 yr-1 on 10 yr rotation.
21. Aboveground Carbon Density (AGCD)
basal area = 0.02 m2
site index = 14 m
mean annual rainfall = 1700 mm
0.2094
0.2209
0.233
0.195
0.2
0.205
0.21
0.215
0.22
0.225
0.23
0.235
6 12 18
ACDINMILLIONGRAMSPERTREE
AGE IN YR
24. Assessing Future Climate Change Impact
• The result had elucidated the findings of PAGASA
that RF will be decreasing by 2050.
• The yield was negatively affected by the changes
in seasonal mean RF.
• Yield will decrease linearly with seasonal mean RF
and in 2050 volume will be reduced to an
approximate amount of 0.0190 m3 (8 bd ft) per
tree.
25. • The predicted decrease in yield with decreasing
precipitation is logical especially if it is coupled
with increasing temperature.
• One possible reason for the decline in yield will be
reduced inputs of nutrients from the soil and the
atmosphere (Yang et al., 2004).
• Decreasing rainfall will also hinder transport and
availability of macronutrients by reducing soil
moisture.
26. SUMMARY AND CONCLUSIONS
1. Yield variation can be accounted by site index,
age, basal area and rainfall.
2. Site index showed inverse relationship with
volume.
27. • Yield relative to various stand and climatic
characteristics of the sites was in the order
woodlot > boundary > alley.
28. • Based on the result of the study, the AGCD per tree
was in the order woodlot > boundary > alley.
• In this study, the changed in future climate
scenario had negative effect on the yield. Yield will
decline with decline in seasonal mean rainfall.
29. RECOMMENDATIONS
1. The model for hedgerow intercropping offers an
essential aid in the selection of suitable
establishment in Northern Mindanao and for the
future management of these land-use.
2. There is limited consensus on which agroforestry
systems and industrial plantation are more
profitable. This study could shed vital information
that would explain the variability in superiority of
management regimes.
30. 3. Likewise, the result of the study could be an
essential aid in the preparation of feasibility
studies pertaining to Bagras establishment and
management in agroforestry systems.
4. Little has been published in the Philippines, or
elsewhere, about timber yields from smallholder
tree-based agroforestry systems using
indigenous fast-growing tree species. This
study could fill the information gap on timber
yield which is vital in assessing site productivity
using economic analysis.
31. ACKNOWLEDGMENT
The author would like to thank Science Education
Institute (SEI) – Department of Science and
Technology (DOST), Commission on Higher
Education (CHED) and Philippine Council for
Agriculture and Aquaculture Resources Research
and Development (PCAARRD) for their financial
support. Dr. Leuvy Tandug is thanked for her useful
suggestions in improving the manuscript.
Agroforestry Farmer’s of Misamis Oriental and
Bukidnon is thanked for providing access to their
farms.