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Forest Biodiversity and Timber Extraction

Forest Biodiversity and Timber Extraction. Kanchan Chopra Pushpam Kumar Institute of Economic Growth Delhi 110007 India Fourth Bio-Econ Workshop, Venice August 28-29, 2003. Forest Biodiversity and Use for human well-being.

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Forest Biodiversity and Timber Extraction

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  1. Forest Biodiversity and Timber Extraction Kanchan Chopra Pushpam Kumar Institute of Economic Growth Delhi 110007 India Fourth Bio-Econ Workshop, Venice August 28-29, 2003.

  2. Forest Biodiversity and Use for human well-being • Forests can provide a range of products and services for human use, primarly due to diversity inherent in them, thereby contributing to human wellbeing • The mix that is available depends on the demand and the nature of the economic regimes within which they are extracted • Often, market and non-market regimes operate together in provision e.g.of timber and non-timber forest products.

  3. Forest Biodiversity and Timber Extraction The interaction takes place in two ways: • through the effect of changed biodiversity on the extraction effort for the marketed product: timber • through policies that increase the supply of marketed product Combined impact over time is examined in this paper

  4. Organisation of the Paper • Characterisation and Measurement of Bio-diversity • Bio-economic indices as measures of biodiversity in use • The theoretical model • The reduced form equations and the econometric estimation • Results and Discussion

  5. Characterization and Measurement of Biodiversity Biodiversity: the variety and variability of life forms from the molecular to the biome level:Three disciplines characterize and measure biodiversity: • Taxonomy: provides the reference system and depicts patterns of diversity • Genetics: knowledge of gene variations within and between species • Ecology: provides knowledge of ecological systems in which diversity is based

  6. Eco-systems and Biodiversity Measurement of biodiversity can be made in alternative ways: • Number of species • Size of an area as a measure as in island biogeography theory • Functional diversity: Ecologists envisage functionality as relevant for the eco-system itself: ecological functionality • Social Scientists’ interest is in use value or functionality in relation to humans

  7. Diversity and Use by Humans • The study of forest products as timber and non-timber forest products provides a measure of diversity in use • Weighted index of Bioeconomic Diversity: Sigma (piyi/TR)**2 where TR= Sigma piyi • In finding values of timber: Market prices • For non-timber: non-market values

  8. The Biodiversity Index • The pi s stand for value, not market price only • For some commodities, market prices may measure value • For others, value may be measured by labour for extraction, non-market traded value etc. • The higher the index, the lower the functional biodiversity of the forest

  9. The Model • The Gordon Schaeffer model is the starting point for the present model • A multi-species natural forest is like a pool from which valuable species are being extracted: products are ranked by value and high value products extracted first

  10. The Model • Y = f(E, X) where Y: extraction of timber • E: effort : X: Stock of timber • Changes in stock are given by • X dot =rX(1-X/K)-qEX………..(1) • r:net rate of regeneration q: coefficient depicting availability of timber species and • qEX: Extraction (natural forest here: no rotation: extraction proportional to effort)

  11. The model ctd. • Forest departments manage parts of forests for sustainable extraction of timber (not for sustainable extraction of all goods and services) we put X dot = 0 • Hence we obtain, extraction Y=qEX (a function of effort and extraction as Y=qEK(1-qE/r), a function of E and K

  12. The modified model • Bio economic Diversity Index: Sigmai (Pi Yi /TR)**2 • and TR = SigmaiPiYi • Now, Y=qBEX…………….(4) • B, the biodiversity index is a shift parameter implying extraction per unit effort Y/E=F(B,X): model with biodiversity

  13. The modified model continued • Interest in timber extraction results in more plantation forests, growth function becomes: • Xdot = rX(1+eW-X/K)-qEX……..(5) • W: Ratio of plantation area to total forest area e: coefficient for impact of W on timber stock

  14. The modified model ctd: • However, B=f(W) with B increasing as W increases (less diversity with plantations) • New growth and sustainable yield functions for timber: • Xdot = rX(1+ eW-X/ K)-qBEX……..(6) • Y = qKBE(1+eW-qBE/r)………….(7)

  15. Reduced form of Equations • Define Extraction per unit effort, U • Without biodiversity index: U= Y/E • With bio-diversity effort: U = Y/BE • In both cases, X=U/q • Growth function(6) is expressed in terms of U • Udot =rU(1-U/qK +eW)-qBEU • U dot/U= r –qBE-(r/qK)U +reW…….(8)

  16. Methods of Estimation • The above is a recasting of the Schaefar model as a dynamic, discrete time, model • Leads to a differential equation in Ut(Schnute) • Adding time subscripts and integrating from t-1 to t, we get (with U defined with and without B as Ut and Ubt) • ln(Ut/Ut-1) =r-qEt-(r/qK)Ut+reWt+e’…….(9) • ln(Ubt/Ubt-1)= r-qEt-(r/qK) Ubt+reWt+e’..(10)

  17. Data Aspects: Forests in a north Indian State • The state of Uttar Pradesh in Northern India has an area of 29.441 million hectares with 17.29% as forest area • Seven types of forests: three tropical subtypes, one sub-tropical, sub Alpine and Alpine……..Many species natural forest with small managed patches • Another characterisation Dense: with more than 70% canopy cover Open: 30-70% canopy cover; scrub: 10-40 % canopy cover.

  18. Forest Characteristics and Data • No single dominating species: hence very diverse • Land use changes documented: plantations increasing over time • Output: Extraction of timber 1975 to 2000 • Extraction cost: Costs of felling and transportation to the forest gate, corrected for difference between monetary and real wage rate to approximate the “effort”variable

  19. Biodiversity Index • As stated above, it is a bioeconomic diversity index • Data on quantity of timber and NTFP extraction from forest department • Sales Value of timber and NTFP from UP Forest Corporation: market prices for timber: different kinds of values for NTFPs

  20. Three Selected Equations • I ln (Ut/Ut-1)=f( Et, Ut) • II ln (Ubt/Ubt-1) =f( Et*, Ut*) • III ln (Ubt/Ubt-1) = f(Et*, Ubt*, Wt) Ut and Ubt being defined as with and without the biodiversity index

  21. Data Sources • Output of timber in cubic metres per annum for 25 years: from Annual Reports of Forest Corporation of UP • Effort in Extraction: treated as costs of felling and transportation to the forest gate: deflated by an index of labour cost to arrive at the “effort” variable • Bioeconomic index of diversity: Timber and non-timber products and their value, market or otherwise.

  22. Results and Discussion • Equation III gives best results in terms of explanatory power, nature of fit and DW statistic: the dependent variable is in logarithmic form and a ratio of two years observations are taken, robustness of the results is ensured • III: Log (Ubt/Ubt-1)= r+ (0.4495)0.0853Et +(2.9636)00169*Ubt +(2.8354)8.7454** Wt

  23. Results and Discussion Ctd. • In this form of the equation,explanatory power increases and • Extraction Y is positively related to Effort E though not a significant determinant of trends in extraction over time • Extraction increases over time (significantly) as W increases (planted area increases ) • Extraction increases over time (significantly) as Ubt increases

  24. Results and Discussion Consider that Ubt is defined as Y/BE: It can increase • With increasing B if Y rises faster than B (with constant E). In other words, a decreasing biodiversity with extraction rising faster, pushes the system towards a state in which increases in extraction take place at an increasing rate • With falling B, (increasing biodiversity), Ubt coulddecrease if Y is not rising faster than B is decreasing. This could lead to a decreasing trend in extraction in following periods of time.

  25. Conclusions and Pointers • A decrease in biodiversity may imply a rise in extraction and at a rising rate • An increased biodiversity ingeneral means higher extraction may imply a decreasing trend in the rate of extraction in the future if present extraction does not rise faster than the rate of increase in biodiversity • Together, these two results point to a distinct trade-off between timber extraction levels in the short and long time periods in the scenarios studied.

  26. Conclusions and Pointers • Implies that a reduced biodiversity may or may not be good for timber extraction in the long run • The model attributes it to two kinds of effects : through increasing cost of extraction and policy encouraging monoculture • Plantation policies must balance timber extraction and biodiversity maintenance objectives

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