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Effects of climate change and deforestation on potential of carbon sequestration and its implication in forest landscape restoration

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Presentation by Mulugeta Mokria, Dr Aster Gebrekirstos, Dr Ermias Aynekakulu and Prof Dr Achim Brauning based on a study to investigate the current extent of forest degradation due to climate change in Ethiopia. The study also quantified the effects of tree dieback on aboveground carbon stock and the carbon sequestration potential. \

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Effects of climate change and deforestation on potential of carbon sequestration and its implication in forest landscape restoration

  1. 1. Effects of climate change and deforestation on potential carbon sequestration and its implication in forest landscape restoration World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 aWorld Agroforestry Centre (ICRAF), United Nations Avenue, P.O. Box 30677-00100, Nairobi, Kenya bInstitute of Geography, Friedrich-Alexander-University Erlangen-Nuremberg, Wetterkreuz 15, 91058 Erlangen, Germany Mulugeta Mokriaa,b, Dr. Aster Gebrekirstosa , Dr. Ermias Aynekulua, Prof. Dr. Achim Bräuningb
  2. 2. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 • Brief introduction (forests, drivers of deforestation and tree mortality) • Methodology (site description, field, laboratory and modeling analysis) • Results (carbon stock, sequestration, growth rate, impact, resilience and range of ecotone shift) • Management and restoration implications Outline
  3. 3. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 • Tropical forests and agroforests: an important biome, to stabilize atmospheric carbon cycle and to minimize climate change impact • Continued to be degrade due to livelihood related issues and climate change • Become major carbon sources and accelerating global climate change • There is a need to understand the drivers, processes and impacts to suggest possible policy and management options Introduction
  4. 4. Drivers of deforestation Picture source: https://www.google.de/search?q=forest+clear+cutting+in+africa&biw=1600&bih=1089&tbm=isch&tbo=u&source=univ&sa=X&ei=6lxXVZ2JMoHaUsq_gbgL&sqi=2&ved=0CDcQ7Ak, https://www.google.de/search?q=drought+induced+tree+mortality+pictures&biw=1600&bih=1089&tbm=isch&tbo=u&source=univ&sa=X&ei=Ll5XVayOOqahyAP2tIDABw&ved=0CE4Q7Ak World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 anthropogenic ..since deforestation is the permanent destruction of trees and forests, it is considered to be one of the contributing factors to global climate change. (Adams et al. 2010).
  5. 5. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 climate (drought /temperature) https://www.google.com/search?q=drought+induced+tree+mortality+picture
  6. 6.  drought induced tree/forest mortality: Across the globe Australia Europe Africa Asia World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 America
  7. 7.  drought induced forest mortality is projected to increase World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Allen et al., 2010,2015
  8. 8. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Ethiopia ALLEN et al., 2015 Since 1970 Before 2010 Between 2010-2015
  9. 9. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 …forms a climatic buffer zone between…… Study area
  10. 10. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016  disaggregate anthropogenic and climate related effects  estimate the extent of the impact of tree dieback on ecosystem services (C-sequestration potential)  assess resilience/adaptation of foundation species in their natural environment  recommend policy and restoration options
  11. 11. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 https://www.google.com/search Dendrochronology: "reading history books of trees" Methodology
  12. 12. - Greenhouse effect - Heavy metals - Air pollution - Forest diseases GLACIO- LOGY ENVIRONMENTAL RESEARCH CLIMATOLOGY GEOMORPHOLOGY HYDROLOGY TEKTONICS/ VOLCANISM DENDRO- ECOLOGY - Ground water- fluctuations - Peat bog growth - Flood reconstruction - River history - Dating of moraines - glacier- fluctuations - Climate and wood formation - climate reconstruction - wind-/ fire-/ snow impact - Erosion rates - Debris flow frequency - Slope movement - Permafrost dynamics - Volcanic eruptions - earthquakes © Bräuning, Insitut für Geographie, Univ. Stuttgart, 24.04.2002 World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016
  13. 13. Interview with local people and experts in the area:  Their local knowledge about the forest and their perception  Drivers of deforestation  Change in climate and its impacts  When the tree dieback started and its trend World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Method- field data collection
  14. 14. Biometric data • Five transects (1km) • 57 plots • 50m X 50m size • Tree height and DBH> 5cm were measured World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016
  15. 15. Sample collection for tree-ring analysis World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016  20 disks (dead and living)  DBH range 20- 48 cm
  16. 16. Wood characteristics and growth ring identification Bark  J. procera forms distnict growth-rings DRP DRP World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Methods- laboratory analysis double staining with Safranin-Astra blue
  17. 17. Radioactive carbon analysis World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Methods- laboratory analysis Year 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 F 14 C_NH_zone3 1.0 1.2 1.4 1.6 1.8 F14C-NH zone 3 Tree ring (14C) Ethiopia Hua et al., 2013. Atmospheric radiocarbon for the period 1950–2010. RADIOCARBON , Vol 55, Nr 4, 2013, p 2059– 2072Mokria et al., in preparation
  18. 18. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 GRB Wider rings Narrow ring Wider rings Tree ring width measurement r1 r2 r3 r4 pith
  19. 19. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Density measurement Water displacement method - Fresh volume - Oven dry for 72h under 105 oC - Density = dry weight/ fresh volume (g/cm3)
  20. 20. Two biomass estimation allometric equations  improved pan-tropical allometric model by Chave et al., 2014 • where, coefficient a = 0.0673 and b = 0.976 and parameter AGB (kg), ρ = specific wood density (g/cm3), D (cm) and H (m).  the flexible tropical mixed-species biomass estimation model by Ketterings et al. (2001): • where, with coefficients D in centimeter, ρ in gram per cubic centimeter, AGBest, in kilogram, ϒ is a constant parameter over a range of sites calculated as ϒ = a/ρ(wood specific gravity), where a = 0.066, is the constant parameter, b is a scaling exponent derived from species-specific height-diameter allometry (this study). World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 b HDaAGB )( 2 1   b DAGB   2 2  Biomass estimation
  21. 21. ….. Propagation of measurement errors in σD, σH , σρ and σr , to estimated AGB: (Chave 2004, Schöngart et al., 2011) Eq.1 Eq.2 total uncertainty per plotuncertainty in each trees … then, the mean AGB and new variance form Eq. (1) and (2) to consider errors due to model selection Wood Science Underpinning Tropical Forest Ecology and Management, Tervuren, May 26-29, 2015 Mokria et al.; Tree dieback affects carbon sequestration potential of a dry afromontane forest    2bH)(ρDσ1b)2(Dba 2b)2D(ρHσ1bHba 2 b)2D(Hpσ1bρba)AGB( 2 σ       1 50 1 2 1 . )( )( ))( AGB AGB        2 Dbr 2 Dr 2 D)AGB( 2 σ b D bb r 1 2    )(  50 2 2 2 . )()( ))( AGBAGB     2502 2 1 22 .)()()(  AGBAGBmeanAGB 
  22. 22. Species Status No. of trees Mean [SE] DBH (cm) Mean [± SE] H (m) Range of DBH (cm) Range of H (m) Proportion of trees (%) under diff. diameter class (cm) 5-15 15-30 30-50 >50 Juniperus alive 1069 16.5 [0.96] 6.1 [0.29] 5-88 2-17.5 60.6 33.8 4.8 0.8 snag 607 17.2 [1.17] 5.9 [0.29] 5-90 2-20 48.4 44.2 5.6 1.8 Olea alive 1313 18.5 [0.83] 5.5 [0.16] 5 - 90 2-17 39.2 52.7 7.0 1.1 snag 802 19.6 [1.23] 4.7 [0.16] 5-114 2-13.5 48.3 46.4 3.7 1.6 Co-occurring alive 1747 11.4 [0.43] 4.2 [0.09] 5-85 2-17 78.1 20.8 1.0 0.1 snag 120 10.5 [0.73] 3.6 [0.20] 5-27 2-8.4 74.2 22.5 0.0 3.3 Summary of plot inventory data: DBH, H, and SE, refer to diameter at breast height, tree height, and standard error, respectively…..  92.2% of snags are from foundation tree species (i.e. juniperus and olea) World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Total= 5658 Results From inventory  25% were dead trees
  23. 23. Total estimated - aboveground C-stock At landscape level, 34.5% C-stock is going to be a source of carbon… World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Mean aboveground C-stock (Kg C tree-1) Total aboveground C-stock (Mg C ha-1) Species Living trees Snags Eq. 2 Eq. 3 Mean Proportion of C-stock estimated from snags (%) J. procera 41.0 (±7.7) 57.8 (±10.9) 8.3 (±1.5) 10.6 (±1.8) 9.4 (±1.6) 44.5 % O. europaea 80.7 (±17.6) 72.9 (±15.9) 11.0 (±2.2) 13.9 (±2.6) 12.4 (±2.4) 35.6 % Co-occurring 22.1 (±6.6) 12.2 (±3.6) 2.0 (±0.5) 2.4 (±0.7) 2.2 (±0.6) 3.7 % All species 43.6 (±9.9) 62.0 (±14.1) 17.2 (±3.5) 21.4 (±4.3) 19.3 (±3.9) 34.5 % Total above ground C-stock/ha -19.3 Mg C/ha ,
  24. 24. Diameter class (cm) 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 >50 Carbonstock(Mg) 0 2 4 6 8 10 12 Living trees Snags (a) J. procera Diameter class (cm) 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 >50 Carbonstock(Mg) 0 4 8 12 16 20 24 28 Living trees Snags (b) O. europaea Diameter class (cm) 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 >50 Carbonstock(Mg) 0 2 4 6 8 Living trees Snags (C) Other species Total aboveground carbon-stock - under different diameter classes Note: C-stock in snags increase with increasing diameter class World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016
  25. 25. Total aboveground carbon-stock - along an elevation gradient Elevation (m.a.s.l) 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 Carbonstock(Mg) 0 5 10 15 20 Living trees Snags (b) O. europaea Elevation (m.a.s.l) 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 Carbonstock(Mg) 0 2 4 6 8 10 12 14 16 Living trees Snags (a) J. procera Elevation (m.a.s.l) 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 Carbonstock(Mg) 0 2 4 6 Living trees Snags (C) Other species World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016  the trees at lower elevation are vulnerable due to increase in temperature and heat wave from Dallol  shifting ecotone by 500m what is the implication of this change when we consider restoration of degraded landscapes?
  26. 26. Tree age and diameter increment  tree age ranges from 106 to 248 years  the radial increment range: 0.25 to 2.1 mm year-1  the overall mean of 0.91 (± 0.02) mm year-1 World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 C-sequestration determination Year (Age) 50 100 150 200 250 Cumulativediameter(cm) 0 10 20 30 40 50
  27. 27. Age and C-stock in AGB relationship • From the above model we drive the annual carbon sequestration (kg year-1 tree-1): C-sequestration = CC-stock (t + 1) – CC-stock (t), where CC–stock is cumulative carbon stock over the entire life span of tree growth World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Year(Age) 100 125 150 175 200 225 250 C-stockinAGB(KgC) 0 100 200 300 400 500 Eq. 2 Eq. 3 Sigmoidal (Eq.2) Sigmoidal (Eq. 3) Eq.2 a = 577.8 b = 40.3 c =207.4 r2 = 0.81, p < 0.001 n = 20 Eq.3 a = 479.4 b = 36.4 c = 186.9 r2 = 0.8, P < 0.001 n = 20
  28. 28. Mean annual C-sequestration rate per tree  The mean annual C-sequestration rate: 1.12 (± 0.05) kg C tree-1 yr-1. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Years(age) 0 25 50 75 100 125 150 175 200 225 250 C-sequestrationinAGB(KgCyr-1) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 C-sequestration[M2] C-sequestration[M3] Mean C-sequestration
  29. 29. Carbon-sequestration potential- at landscape level Mean annual C-sequestration potential (Mg C ha-1 year-1) Species Pre-tree-dieback Post-tree dieback Lost CS-potential (%) J. procera 0.22 (± 0.03) 0.14 (± 0.03) 36.4 O. europaea 0.18 (± 0.02) 0.11 (± 0.02) 39.0 Co-occurring species 0.15 (± 0.01) 0.14 (± 0.01) 6.7 All species 0.45 (± 0.03) 0.33 (± 0.03) 27.0 • Pre and Post-tree dieback carbon-sequestration • Lost carbon-sequestration potential due to dieback World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Note: Annual C-sequestration per hectare = 1.12 (± 0.05) kg C tree-1 year-1 X stem density per ha
  30. 30. It is an indication of required period of time to reach optimum harvestable size under natural condition World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Other ecological implications Years (Age) 0 50 100 150 200 250 CGW(cm) 0 10 20 30 40 50 MAI(cm) 0.06 0.12 0.18 0.24 CGW MAI J. procera require more than 100 years to reach… the impact is long lasting impact
  31. 31. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 What is the implication if we consider to restore this degraded landscapes?
  32. 32.  trees at lower elevation are more vulnerable due to increase in temperature and heat wave from Dallol  dieback caused upward ecotone shift by about 500m,  ecotone shift Indicates changing environmental conditions  the impact of tree dieback on the ecosystem is long-lasting  It is costly to curb the situation after major vegetation loss  conservation is cheaper than restoration  restoration should consider a micros site conditions and climate resilient species  Dendrochronology is very useful tool to determine annual carbon sequestration (temporal and spatial), to asses resilience of species , understand landscape history and population dynamics World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Conclusion and recommendation
  33. 33. World Agroforestry Centre (ICRAF) Nairobi, March 14, 2016 Thank you! Acknowledgement CRP 6.4 for co-funding Mekele University for support during field work Edith Anyango for assisting laboratory work

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