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2111 2005. 2111 2005 Climate change mitigation related to Tanzanian forests Key factors for analysis and research prioritizing Ole Hofstad.

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Presentation on theme: "2111 2005. 2111 2005 Climate change mitigation related to Tanzanian forests Key factors for analysis and research prioritizing Ole Hofstad."— Presentation transcript:

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2 Climate change mitigation related to Tanzanian forests Key factors for analysis and research prioritizing Ole Hofstad

3 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Organisation of the presentation  Mitigating climate change through REDD  Monitoring  Carbon accounting  PES mechanisms  Land-use change modelling  Policy measures within the forest sector  Other policies Climate change mitigation and Tanzanian forests 3

4 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Carbon stocks Climate change mitigation and Tanzanian forests 4

5 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management GHG emissions Climate change mitigation and Tanzanian forests 5

6 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management The importance of degradation Climate change mitigation and Tanzanian forests 6

7 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 7  area and density  technologies  sampling  accuracy  frequency  costs Monitoring forest ecosystems

8 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 8 The monitoring problem may be considered as two separate components: 1. estimating areas of different vegetation types (e.g.: forest, woodland, savannah, cropland, etc.), and 2. estimating the average biomass density (tons/ha) in each vegetation type. Cropland and burned bush in Northern Mozambique (Photo: E. H. Hansen)

9 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 9 Area estimates  Areas may be measured on the ground, either by triangulation using surveying equipment, or GPS. These methods are both time consuming and expensive and best suited for small areas with very high precision requirements.  Areas may be measured on aerial photographs. This is expensive if aerial photography is ordered for this particular use alone.  Areas may be measured on satellite images based on reflected sunlight. Classification of vegetation types may be assisted by competent personnel, or be made unassisted by computer. Using satellite images is the preferred method in most modern applications for large areas of low unit value.

10 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 10

11 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 11 Biomass measurements  Biomass density may be measured on temporary or permanent sample plots in the field. Trees (and bushes) are measured in various ways, e.g. stem diameter, height, crown diameter, etc. These measurements are transformed by allometric functions into estimates of volume or weight of individual trees or bushes.  Biomass density may be estimated on the basis of crown cover measured on aerial photos.  Biomass estimates may be based on data collected by the use of light emitted from an airborne or satellite laser, or  from an airborne or satellite radar. The three latter methods (photo, laser, radar) require some sample plots on the ground where trees are measured manually. Such data is necessary in order to calibrate the remote sensing data.

12 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Combining area estimates with estiamated biomass density Climate change mitigation and Tanzanian forests 12

13 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Air-borne laser Climate change mitigation and Tanzanian forests 13

14 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Remote sensing of biomass density in forests Climate change mitigation and Tanzanian forests 14 Points of reflection distributed in space

15 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 15 Sampling  Stratified sampling  Sampling percentage  Permanent plots  Temporary plots Stratification:  Forest types [rain forest (flooded or not), montane forest, seasonal green forest, open forest, shrub, savanna, etc.], cropland, grazing land  Agro-ecological zones, regions, districts  Biomass density  The smaller the reporting unit, the larger sampling percentage is required to give precise estimates

16 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Proposed laser project  1. If FRA2010/NFI decides to measure ground plots either from FRA2010 tiles or along the lines formed by FRA2010 tiles (see map), we should consider offering to fly LiDAR along these lines of FRA2010 tiles in all, or parts of, Tanzania. If we fly all over Tanzania, it will imply flying a total distance of ca 9000 stripe-km, which will give a systematic sample of laser data for all of Tanzania. Calibrated with field data from below the flight corridors, one would be able to give a national biomass estimate for the whole of Tanzania in less than one year (given that field data are measured during the same period). We may even be able to break the estimate down into regional partial estimates.  2. In addition we should select one of the three "ecosystems" as an object for detailed studies, where we either fly wall-to-wall with LiDAR or fly stripes very close (as proposed in Brazil) in an area of 5-10,000 km 2. In this area we must establish a set of separate sample plots on the ground. Observations from these plots will be used to calibrate LiDAR measurements of biomass. This set of data will serve two purposes: –2a: GEO/FCT sites –2b: detailed studies of design of laser-mapping of biomass through sampling –2c: “ground” validation of SAR-study. If we choose tropical rain forest as a case, this will be complementary to Brazil since we may find higher biomass density than in Amazonia. Climate change mitigation and Tanzanian forests 16

17 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 17 Precision For the REDD-activities in Tanzania, where a lot of different inventories will be performed, it will be of crucial importance to gain basic knowledge on patterns of spatial variation for biomass ha -1 (or volume or basal area ha -1 ) under different forest conditions and plot designs. A research project to approach these challenges could be performed along the following lines; 1.Systematic review of previously performed inventories with respect to spatial variation 2.Undertake inventories in selected study areas covering important vegetation types and inventory designs 3.Perform theoretical inventory simulations in order to select optimal inventory strategies under different conditions and requirements Relationship between accuracy (S m ) and number of plots (n) according to different patterns of spatial variation S m = Standard error CV = Coefficient of variation

18 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 18 Frequency  How often will new area estimates be presented?  How often shall biomass estimates be updated?  Rotation on permanent sample plots  Repeated flights [airplane or satellite] (with camera, laser, or radar)  Higher frequency, higher costs

19 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 19  Living biomass –Trees, bushes, herbs and grass Above ground Roots  Ded wood –Logging residues –Ded branches, roots and more  Soil CARBON IN FOREST IPCC Guidelines: Three hierarchical tiers of methods that range from: 1.default data 2.simple equations 3.to the use of country-specific data and models to accommodate national circumstances. It is good practice to use methods that provide the highest levels of certainty, while using available resources as efficiently as possible. Combination of tiers can be used.

20 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 20 LIVING BIOMASS  Biomass expansion factor (BEF/BF) –E.g. IPCC default value = 0.44 tons Dry Matter / m 3 fresh volume  Biomass equation –Allometric functions for whole trees or fractions like stem, branches and roots. –E.g.: Biomass above ground B = dbh h 0.64 B = dbh 2  Field measurements and laboratory measurement of wood density are required.

21 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Land-use changes to achieve REDD Climate change mitigation and Tanzanian forests 21

22 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 22 Leakage

23 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 23 Global trade in forest products Main trade flows of tropical roundwood (million m 3 ) Buongiorno, J., D. Tomberlin, J. Turner, D. Zhang, S. Zhu The Global Forest Products Model: Structure, Estimation, and Applications.

24 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 24 Source: Jayant Sathaye, Lawrence Berkeley National Laboratory, California

25 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 25

26 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 26

27 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 27 Land-use model

28 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 28 Land-use models at village or watershed level  Namaalwa, J., P. L. Sankhayan & O. Hofstad A dynamic bio- economic model for analyzing deforestation and degradation: An application to woodlands in Uganda. Forest Policy and Economics, 9 (5):  Sankhayan, P. L., M. Gera & O. Hofstad Analysis of vegetative degradation at a village level in the Indian Himalayan state of Uttarkhand – a systems approach by using dynamic linear programming bio-economic model. Int. J. Ecology and Environmental Sciences 33(2-3):  Hofstad, O Review of biomass and volume functions for individual trees and shrubs in southeast Africa. J. Tropical Forest Science, 17(1):  Namaalwa, J., W. Gombya-Ssembajjwe & O. Hofstad The profitability of deforestation of private forests in Uganda. International Forestry Review 3:  Sankhayan, P. L. & O. Hofstad A village-level economic model of land clearing, grazing, and wood harvesting for sub-Saharan Africa: with a case study in southern Senegal. Ecological Economics 38:  Hofstad, O. & P. L. Sankhayan Prices of charcoal at various distances from Kampala and Dar es Salaam Southern African Forestry Journal, 186:  Hofstad, O Woodland deforestation by charcoal supply to Dar es Salaam. J.of Environmental Economics and Management, 33:17-32.

29 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 29 Tanzanian land-use and forest sector trade models  Kaoneka, A.R.S Land use Planning and quantitative modelling in Tanzania with particular reference to agriculture and deforestation: some theoretical aspects and a case study from the West Usambara mountains. Dr.Scient. Thesis, Agriculture University of Norway, Aas.  Monela, G. S Tropical rainforest deforestation, biodiversity benefits and sustainable land use: Analytical of economic and ecological aspects related to the Nguru Mountains, Tanzania. Dr. Scient. Thesis, Department of Forestry, Agricultural University of Norway.  Ngaga, Y.M Analysis of production and trade in forestry products of Tanzania. Dr.Scient. Thesis, Agriculture University of Norway, Aas.  Makundi, W. R Potential and Cost of Carbon Sequestration in the Tanzanian Forest Sector. Mitigation and Adaptation Strategies for Global Change, 6(3-4):  Ngaga, Y. M. & B. Solberg Assessing the Suitability of Partial Equilibrium Modelling in Analyzing the Forest Sector of Developing Countries: Methodological Aspects with Reference to Tanzania. Tanzania Journal of Forestry and Nature Conservation, 76:  Monela, G. C. & J. M. Abdallah External policy impacts on Miombo forest development in Tanzania. In: Dubé, Y. C. & F. Schmithüsen (eds.): Cross-sectoral policy developments in forestry.  Monela, G. C. & B. Solberg Deforestation and agricultural expansion in Mhonda area, Tanzania. In: Palo, M. & H. Vanhanen (eds.): World forests from deforestation to transition?

30 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 30 Policy measures  General policies –Good governance ( legal system, transparency, corruption ) –Energy –Agriculture –Transport  Sector specific measures –PES ( monitoring, verification ) –Projects ( administrative costs, foreign assistance ) –Land; ownership and user rights  Cost effectiveness and efficiency ( Cost-Benefit )

31 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 31 Schematic view of a REDD PES system Mgt. of forest reserves (Govt., FBD ) F u n d DC International funding: carbon market, global funds, bilateral donors, NGOs, … VC, NRC CBO, villager s Incentives (flow of money) Village forests P u b l i c f o r e s t sForest reserves Information processing (IRA, FBD) Flow of information National level Local level Participatory monitoring Internat. level Satellite based inf., plots

32 NORWEGIAN UNIVERSITY OF LIFE SCIENCES Department of Ecology and Natural Resource Management Climate change mitigation and Tanzanian forests 32


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