Modeling the Potential of Forestation for Carbon Storage in Southern Africa ______

Modeling the potential of forestation for carbon storage in Southern Africa ______

Shakirudeen Lawal – LWLSHA002

Towards a Master of Science specializing in Climate Change and Sustainable Development, University of Cape Town

Supervisor: Dr. Babatunde J. Abiodun

Minor dissertation presented for the approval of Senate in partial fulfillment of the requirements for the M.Sc. specializing in Climate Change and Sustainable Development in approved courses and a minor dissertation. I hereby declare that I have read and understood the regulations governing the submission of the M.Sc. specializing in Climate Change and Sustainable Development dissertations, including those relating to length and plagiarism, as contained in the rules of this University, and that this minor dissertation conforms to those regulations.

Signature:

Date:

Abstract

The present study examines the carbon storage potential of forestation over southern Africa with focus on South Africa, Botswana and Namibia; to investigate how some local species may sequester carbon and thereby provide economic returns to these nations and landowners through the Clean Development Mechanisms (CDM). First, this study used the IPCC Tier 2 method to calculate the carbon stored and emitted from forestlands in these three southern Africa countries. The potential net and gross carbon storage values of these forestlands were then estimated using the emissions-storage statistical equations. Second, the CO2FIX V3.1 model which is an IPCC Tier 3 method was used to simulate the carbon storage potential of Acacia karoo, Eucalyptus grandis, E. smithii, E. nitens, Portulacaria afra, Searsia pendulina, Combretum apiculatum and

Pinus radiate over a 30-year period. The results show that carbon dioxide (CO2eq) emissions from forestlands were highest in Botswana from 1990-2000 (8000 CO2eq) and 2005-2010 (5800

CO2eq) while Namibia recorded the lowest emissions (2900 CO2eq) in this period. Among the species used for simulations in the CO2FIX model, A. karoo sequestered the highest amount of carbon in South Africa, 138.06 MgC/ha (506.23 MgCO2eq/ha and Euro 2328.65/ha), in

Botswana 138.71/ha MgC (508.59 MgCO2eq/ha and Euro 2339.51/ha) and in Namibia, 137.96

MgC/ha (505.59 MgCO2eq/ha and Euro 2326.92/ha) and thus, gave the highest economic value while P. afra has the least potential for carbon storage in the region, sequestering 5% of what A. karoo sequesters although it also showed some promising abilities for carbon storage. The simulations further reveal that a mixed plantation which comprises all these indigenous and exotic species sequestered much more carbon than that of A. karoo by a factor of 4.5 in South Africa (615.59 MgC/ha), 4.6 in Botswana (646.79 MgC/ha) and 5.0 in Namibia (709.99 MgC/ha) and therefore, gave far more economic value (5x higher) than the sum all the monoculture.

Key words: Carbon capture and storage, Forestation, Clean Development Mechanism, Afforestation

iii

Plagiarism Declaration

Name: Shakirudeen Lawal Student Number: LWLSHA002 Course: EGS5029H

Declaration

1. I know that plagiarism is wrong. Plagiarism is to use another’s work and pretend that it

is one’s own.

2. I have used the Harvard convention for citation and referencing. Each contribution and

quotation in this dissertation from the works of other people has been attributed and has

been cited and referenced.

3. This dissertation is my own work.

4. I have not allowed, and will not allow, anyone to copy this work with the intention of

passing it off as his or her own.

January 31, 2014

Shakirudeen Lawal

Dedication

This work is dedicated to my beloved mother – Mrs. Silifat Ayo Lawal, my siblings – Habib Lawal, Shakirat Lawal and Baasit Lawal, my cousin- Kashiro Rabiu and my fiancé- Tawakaltu Atinuke Adeleye.

Acknowledgements

First and foremost, I thank Almighty Allah who has kept me alive till this day and for making this journey a reality.

The success of this work calls for appropriate recognition of those that made diverse and great contributions towards this end. Paramount among who is my supervisor, Dr. Babatunde J. Abiodun who contributed immeasurably and wholesomely to the success of this study. I am eternally grateful for your financial as well as moral support; and most importantly your outstanding tutelage in the course of this work.

In the same vein, I appreciate the invaluable role of Dr. Bradley Rink as course convener who was not only a guardian but also a friend. Furthermore, I am also appreciative of the kind gestures I received from Professor Mark New, who despite his busy schedule always made time available to assist me. The large hearted and wholesome support which I received from the staff and students of the Climate System Analysis Group (among whom are Professor Bruce Hewitson, Sharon Bernard and Dr Joseph Daron) has also made this study worthwhile. To the all the staff of the African Climate and Development Initiative, particularly, Dr. Muhammad Rahiz, I am grateful for your support and accommodation.

I am in no small measure very grateful to my father, Professor Tola Atinmo for his financial and all-rounded support. This might not have been possible without my two best friends – Muideen Adebayo and Oscar Uzoma who encouraged me in every way to undertake this program. Friends in need are friends indeed. You will forever remain my friends and brother and I pray that I am able to fully repay your kindness and selflessness. Similarly, the priceless assistance of Messrs Victor Etokwu, Kazeem Durodoye, Tunde Ezichi, Chief John Edozien, Barrister Lateef Fagbemi (SAN), Messrs. Ayo Akinmade, Victor Eka, Ehima Abiodun, Drs. Gbolahan Elias (SAN), Yemi Ogunbiyi and Sola Adeduntan are highly appreciated. I am also grateful to Drs. Jimoh Saka, Ajewole Opeyemi and Yusuf Sulaimon for the encouragement.

A million thanks to all my Classmates, 2013/2014 ACDI Mphil/M.Sc. students for their indulgence and patience while we did this program. I cannot but acknowledge the conducive environment engendered by the cooperation and love from all members of staff of the vi

Department of Environmental and Geographical Science- among whom are Professor Mike Meadows (Head of Department), Shahieda Samsodien, Sharon Adams - just to mention a few, for giving me the opportunity to be a part of this department.

In like manner, I acknowledge greatly with joy camaraderie of my people: Temitope Egbeleye, AbdulRasheed Adeyemi, Goodnews, Daniel Chinenye Kalu, all members of the Muslim Students Society of Nigeria (MSSN) and the Sigma Club University of Ibadan, Nigeria.

My sincere appreciation also goes to the editors of this work – Kamoru Lawal, Myra Naik and Steve Arowolo.

The likes of Messrs. AbdRamon Dauda, Rildwan Olatoyinbo and Adepeju Salu rendered me invaluable support.

Once again, to my supervisor, Dr Babatunde J. Abiodun who played the role of an excellent teacher in all areas, I am forever indebted.

I am forever grateful to all my lecturers from various departments and institutions who at one time or the other have taught and imparted knowledge into me here in UCT or beyond. I am grateful to several others, who for one reason or the other cannot be mentioned or acknowledged appropriately.

To my siblings, Habib Lawal, Shakirat Lawal, Baasit Lawal and cousin Kashiro Rabiu, I specially acknowledge your support, perseverance, patience and trust. You are the most wonderful brothers and sister; To my fiancé – Atinuke Adeleye, I say thank you for your love. I am lucky to have you all. My deepest gratitude goes to my mother – Silifat Ayo Lawal.

Shakirudeen Abimbola, Lawal

January, 2014

vii

List of Figures

Figure 1a Acacia karoo...... 5

Figure 1b Eucalyptus nitens……………………………………………………………………6

Figure 1c Eucalyptus smithii…………………………………………………………………...6

Figure 1d Eucalyptus grandis …………………………………………………………………7

Figure 1e Pinus radiate………………………………………………………………………...7

Figure 1f Combretum apiculatum …………………………………………………………...... 8

Figure 1g Searsia pendulina…………………………………………………………………………….8

Figure 1h Portulacaria afra…………………………………………………………………….9

Figure 2 Southern African domain showing the topography and land cover pattern over the region…………………………………………………………………………………………...19

Figure 3 Stored carbon dioxide (CO2) equivalents in forestlands over 20 years in Botswana, Namibia and South Africa……………………………………………………………………...30

Figure 4 The long term average carbon stock (percentage) in soil and biomass for each of the monoculture and mixed plantation……………………………………………………………...36

Figure 5 The long term average carbon stock (MgC) in soil and biomass for each of the monoculture and mixed plant…………………………………………………………………...37

Figure 6 Total carbon stock (MgC) sequestered for the mixed plantation……………………...38

Figure 7 Advancing means of the net biomass carbon (MgC) balance of the mixed plantation..40

Figure 8 Temporal development of carbon stock (MgC) in the biomass component of the mixed plantation………………………………………………………………………………………..41

Figure 9 Advancing means of the net soil carbon balance of the mixed plantation: soil cohorts Mgc/ha ………………………………………………………………………………………….43 viii

Figure 10 Temporal development of the carbon stock (MgC) in the soil component of the mixed plantation………………………………………………………………………………………..44

List of Tables

Table 1 The dynamics of Rural vulnerability to Global change: Incidence of drought and cereal production in southern Africa…………………………………………………………………11

Table 2 Carbon stock in a tree…………………………………………………………………14

Table 3 Main characteristics of the forest types……………………………………………….22

Table 4 Parameter values of the soil component using Yasso model of the CO2FIX model....23

Table 5 Additional parameter values of the forest types………………………………………26

Table 6 Worksheets for estimating volume of forest species………………………………….27

Table 7 Estimated carbon storage, gross and net annual sequestration, number of trees and percent tree cover for the three regions in southern Africa using A. karoo…………………....33

Table 8 The carbon sequestration potential in a pure even-aged and mixed plantation over South Africa, Botswana and Namibia as simulated by CO2FIX model over 30 years……………….34

Table of Contents

Title page……………………………………………………..………………………….i

Abstract……………………………………………………..…………………………...ii

Declaration………………………………………………………………….…………..iii

Dedication………………………………………………………………….……………iv

Acknowledgements…………………………………………………………………...….v

List of Figures………………………………………………………………………...... vi

List of Tables…………………………………………………………………………....ix

Table of Contents…………………………………………………………………..…....x

Chapter 1: Introduction………………………………………………………………………………1

1.1 Forestation: Types and Components ...... …….….1

1.2 Forestation as a mitigation option for global warming in southern Africa ...... 1

1.3Study aim and objectives ...... 4

1.4 Species description…………………………………………………………………….5

1.4.1 Acacia karoo ...... 5 1.4.2 Eucalyptus nitens ...... 6 1.4.3 Eucalyptus smithii ...... 6 1.4.4 Eucalyptus grandis ...... 7 1.4.5 Pinus radiata ...... 7 1.4.6 Combretum apiculatum ...... 8 1.4.7 Searsia pendulina ...... 8 3.2.3 Portulacaria afra ...... 9 1.5Dissertation outline ...... 9

Chapter 2: Literature review ...... 10 xi

2.1 Climate Change: evidence and impacts ...... 10

2.2 Mitigation: Geoengineering mechanisms and carbon sequestration ...... 11

2.2.1 Afforestation and reforestation ...... 12

2.2.2 Carbon sequestration based on forest management ...... 12

2.2.3 Carbon sequestration based on tree based system ...... 13

2.2.4 Variation in species potential for carbon storage ...... 13

2.2.5 Carbon storage pool in forest ecosystem ...... 14

2.2.6 Agro forestry as an option for carbon sequestration and choice of species ...... 14

2.3 Cost-benefit analysis of carbon sequestration of forestation ...... 15

2.4 Modelling carbon storage potential of forestation ...... 16

2.5 Clean Development Mechanism (CDM) ...... 16

2.6 REDD+ (Reducing Emissions from deforestation and forest degradation) ...... 17

2.7 Bush encroachement and carbon sequestration ...... 17

Chapter 3: Methodology ...... 18

3.1 Study areas ...... 18

3.2 Calculation of forestland carbon storage in South Africa, Namibia and Botswana ... 19

3.3 Simulation of carbon sequestration: model description and set up ...... 20

3.4 Implementation of CO2FIX model ...... 24

3.5 Calculating the economic value of a metric ton of carbon sequestered in different plantations

...... 28 xii

Chapter 4: Results and Discusssion ...... 29

4.0 Results outline ...... 29

4.1 Potential carbon storage capacity of forestlands in Botswana, Namibia and South Africa

...... 29

4.2 Forestation carbon stock and their economic values ...... 31

4.3 The partitioning of sequestered carbon into biomass and soil ...... 35

4.4 Temporal variation of sequestered carbon in biomass ...... 39

4.5 Temporal variation of sequestered carbon in soil ...... 41

Chapter 5: Conclusion ...... 45

5.0 Conclusion ...... 45

4.3 Limitations and suggestions for further studies ...... 46

References ...... 48

Chapter 1: Introduction

1.1 Forestation: Types and Components

Forestation is the planting of trees on an area of land. It could be the establishment of a new forest or an entire replacement of forest trees. It is referred to as afforestation and/or reforestation activities. Afforestation is the process of establishing a forest on a land that is not a forest or has never been one for at least 50 years (Marrakech Accords, 2001; Andrea, 2002). Reforestation is the direct human-induced conversion of deforested land to a forestland through planting, seeding and/or human-induced promotion of natural seed sources, on land that was forested but has been converted to non-forested land over 50 years ago (Marrakech Accords, 2001; Hansen et al., 2007). A forest can be defined as land with tree crown cover of more than 10% and an area of more than 0.5 hectare; coupled with a minimum tree crown cover of between 10 and 30% and minimum tree height between 2 and 5 metres (FAO, 2000; USAID, 2009). A forest can either be natural forests comprising mainly indigenous trees not deliberately planted or plantations which are forest stands established by planting or seeding or both by afforestation or reforestation (FAO, 2000). In silvicultural systems, natural forests are mostly classified as uneven-aged mixed stands while plantations are usually considered to be even-aged pure stands (Kanninen, 2004). Pure and even-aged stands are characterized by one age class, uniform height, better diameter distribution and well developed canopy (Kanninen, 2004). Uneven-aged stands are characterized by species with different age classes, different heights, irregular canopy and diameter distribution. Uneven-aged stands are mostly found in mixed forests while even-aged are found in single-species plantations which are also referred to as monocultures (Kanninen, 2004).

1.2 Forestation as a mitigation option for global warming in southern Africa

Global warming is a complex and long-term problem that continues to threaten ecosystems and livelihood worldwide (Marshall, 2007; USAID, 2010). Impacts of global warming is severe in developing countries, where large numbers of rural people with low adaptive capacity depend on climatic resources and are highly vulnerable to climate variability and change (Downing et al., 1997; USAID, 2010). In southern Africa, for example, many rural dwellers have suffered losses (in agriculture, biodiversity, wildlife, and health) from severe droughts and flooding that were intensified by the global warming (Cane et al., 1997; Glantz et al., 1997; Phillips et al., 1998). 2

Over the last two decades, global warming has induced some unprecedented episodes of El Nino Southern Oscillation (ENSO), causing anomalously extreme or deficit of rainfall in the southern Africa sub-region. Furthermore, in biodiversity hot spot regions (like South Africa), global warming has led to regime change, extinction of valuable species, and disturbance in vital ecosystems (Desaker (WWF), 2002; Lovett, 2007). Consequently, other important species which depend on the ecosystem and biodiversity for survival have vanished (Keith et al., 2008). In addition, the warming has indirectly increased mortality and morbidity through climate related cardiovascular diseases; respiratory diseases due to heat waves; lack of access to safe drinking water which has also led to outbreak of diarrhea; and malnutrition associated with crop failures (Patz et al, 2005). The World Health Organization (WHO) has projected that global warming may increase the number of individuals prone to vector-borne diseases (such as malaria, schistosomiasis, onchocerciasis, leishmaniasis) by16-28% in future (Nabi and Qadar, 2009). Hence, there is a global interest on how to reduce the impacts of global warming.

Despite that global warming is human caused, however, several human interventions by the international communities have also been proposed as a solution to counterbalance the negative impacts of this warming (Wallace et al, 2010). These interventions include the geo-engineering mechanisms which are often defined as intentional, technological large-scale interventions in the climate system employed to mitigate the impacts of anthropogenic climate change (Galaz, 2012). All the geo-engineering approaches offer promising solutions because they are targeted to rectify the current imbalance in the earth’s radiative system (Lenton and Vaughen, 2009; Abiodun et al., 2012). The various types of geo-engineering mechanisms are (1) solar radiation management (SRM) techniques which aim to induce cooling. These include stratospheric aerosols injection or cloud seeding in the troposphere; (2) ocean based CO2 removal techniques such as ocean fertilization, alkalinity enhancement as well as upwelling in order to induce growth of phytoplanktons which in turn increase the intake of atmospheric carbon dioxide (CO2); (3) land– based CO2 removal such as biomass methods and forestation aimed at sequestering atmospheric

CO2 in natural or artificial trees (Royal Society, 2009).

In spite of the opportunities associated with the solar radiation management (SRM) and ocean- based CO2 removal techniques, several risks are also associated and these are yet to be properly understood (Royal Society, 2009; Abiodun et al., 2012). However, the land-based CO2 removal 3 technique (like forestation: afforestation or reforestation) remains the most promising option. It is cost-effective, efficient and offers realistic ways of sequestering carbon thereby mitigating the impact of climate change) and this has been recognized by the Intergovernmental Panel on Climate Change (IPCC) (Lenton and Vaughen, 2009; IPCC, 2000; Arora and Montenegro,

2011). These land-based CO2 removal techniques have potential to slow down the atmospheric and marine accumulation of greenhouse gases, which are released from burning fossil fuels (NAS, 1992), and alter the energy and moisture balances (IPCC, 2001). Furthermore, there are co-benefits associated with forestation activities. Brown et al., (1996) discussed the advantages of substituting wood products for fossil fuels. The expansion of land such as agro forestry also provide unique opportunities for mitigating greenhouse gases (GHGs) emissions while addressing other pertinent concern of the rural dwellers (Syampungani, 2010). It is estimated that about 60 Pg C is exchanged between terrestrial ecosystems and the atmosphere every year, with a net terrestrial uptake of 0.7 ±1.0 Pg C (Schimell et al., 1996 cited by Lasco et al., 1998). Thus, forest as a major component of the terrestrial ecosystems plays an important role in the global carbon cycle acting as both sources and sinks of carbon depending on the specific management regime and activities (IPCC, 2000).

In recognition of this, several efforts are currently being undertaken to harness the potential of the forest in curtailing the present warming and mitigating futures impacts. Thus, concepts such as carbon sequestration, carbon credit and trading, Clean Development Mechanism (CDM) are being discussed globally (Capoor and Ambrosi, 2008; Gillenwater and Seres, 2011). Carbon sequestration describes long-term storage of carbon dioxide or other forms of carbon to either mitigate or defer global warming (Sedjo and Sohngen, 2012). CDM was defined under the Kyoto Protocol (IPCC, 2007) to provide for emissions reduction projects through generation of Certified Emission Reduction (CER) units which may be traded in emissions trading schemes (ETS) (IPCC, 2007). It generates offsets through investments in greenhouse gas (GHG) reduction, avoidance and sequestration projects in developing countries (Gillenwater and Seres, 2011). Numerous sectors were proposed by the United Nations Framework Convention on Climate Change (UNFCCC) for CDM investments in the various sectors. These include rural electrification and wind projects (energy sector) in India and Maldives; United Nations Industrial Development Organization (UNIDO) industrial projects in Nigeria (built sector); as well as other initiatives in the forestry sector among numerous others (IPCC, 2007). Nevertheless, to achieve 4 emission reduction through forestation activities, Annex 1 countries who are signatories to the Kyoto Protocol must be willing to buy carbon credit from the developing nations. This requires that the buyers and sellers of carbon credit have knowledge of carbon sink with respect to different species (Nabuurs and Schelhaas, 2002). As a result, several studies on forestation have been initialized. Across Europe, carbon profile sink based on sites, locations, and tree species have been assessed (Nabuurs and Schelhaas, 2002). In South America and southern Africa, the cost-benefit analysis of establishing forests for carbon sequestration has been ascertained (Smith and Scott et al., 1992; Niles et al., 2002; Cornelis et al., 2004). The roles of forests on agricultural land (agroforestry) for sequestering carbon is being established around the world (Montagnini and Nair, 2004; Lin, 2011). In southern Africa, several studies have shown that the use of some species in forestation practice has effects on water yield and stream flow (Hewlett and Bosch, 1984; Smith and Scott, 1992 and Schulze et al., 2004), but no studies have shown or quantified the potential of forestation for sequestering carbon in this region. As a result, the economic potential of tree species that grow in the region for carbon capture and storage remains unknown. Meanwhile, there is need to quantify the net intake of carbon by a different species based on composition and area in the region. The quantification will help to identify species with large potential for carbon capture and know the viability of forestation practice based on areas and structure over southern Africa. 1.3 Study aim and objectives

The aim of this study is to quantify the potential of different tree species for carbon storage over reforestable areas in southern Africa using two IPCC methods (Tier 2 and Tier 3). The objectives of the study are as follows: • To identify target areas and calculate the extent of ‘forestable areas’ i.e. those areas which have potential for carbon-sink forestation practice • To identify the most suitable species for forestation and carbon sequestration in the target regions

• To analyze the carbon sequestration capacity of a pure and even-aged plantation of the identified species. • To investigate the carbon storage capacity of mixed plantation of all the species and compare the results with those of monoculture plantation. 5

• To analyze the soil-biomass carbon stock ratio in each of the plantations • To compare the different southern Africa regions with respect to the viability of the species and carbon sequestration

1.4 Species’ description

In this study, eight common southern African species were used for simulation in the CO2FIX model which is a IPCC Tier method for estimating the carbon storage potential of a plantations. The species are Acacia karoo, Eucalyptus nitens, E. smithii, E. grandis, Pinus radiate, Combretum apiculatum, Searsia pendulina and Portulacaria afra. The species characteristics and uses are described as follows: 1.4.1 Acacia karoo This is commonly referred to as Sweet Thorn. It is now known as ‘Vachellia karroo’. It is a South African native species (but can also be found in Angola and Zambia) with height which ranges from shrub to a tree, growing to a height of 1m – 15m but sometimes reaching 25m. It reproduces from seeds and has a life span of 30-40 years. It is used for raft making, fencing, fodder for livestock and game among other uses.

Figure 1a: A typical shape of a mature A. karoo tree (Source: Barnes R.D et al. 19996)

1.4.2 Eucalyptus nitens This is commonly known as Shining gum. It is an exotic species to South Africa originating from Australia. It is a fast growing species that can attain a height of 70 m and diameters of 1-2 m. It is poor at self-thinning and is mostly for timber, pulp and paper. It also exhibits possible toxicity and allelopathic effects when it produces ‘Eucalytus oil’

Figure 1b: A regenerating Eucalptus nitens with shoots from stem (Source: Bootle 2004)

1.4.3 Eucalyptus smithii E. smithii grows to about 40 m high. It is commercially planted in South Africa for pulp and paper, and various other forest products. Its oil is useful for respiratory purposes and pregnancy.

Figure 1c: A long needle-like leaf of Eucalyptus smithii (Source: Boland, 1991) 7

1.4.4 Eucalyptus grandis Originating from Australia, E. grandis is exotic to South Africa. It is commonly known as Rose gum. It grows to a height of 35-45m and sometimes 75 m with 1.2-2 m diameter. It is used as shelterbelt for food stock and as ornaments. It is not known to be toxic or weed

Figure 1d: A typical tree and leaves of Eucalyptus grandis (Source: FAO, 2000; Boland 2006)

1.4..5 Pinus radiata This is commonly known as Monterey Pine/Insignis Pine/ Radiata Pine. It is a rapidly growing species useful for lumber and pulp. It is also exotic to South Africa originating for Americas. It is a medium sized tree attaining a height of 40 to 50 m amd diameter of 1m.

Figure 1e: A mature standing Pinus radiate tree (Source: Moore et al. 2008) 8

1.4.6 Combretum apiculatum It is a native to southern Africa and it is commonly known as Red Bushwillow, it is a medium sized 4-10 m with density. It has a short, often curved stem and is usually multi-stemmed. Its leaves are eaten by animals and also planted in gardens by humans because of its antioxidants properties.

Figure 1f: A leaf bearing stem of Combretum apiculatum (Source: Schmidt et al. 2002)

1.4.7 Searsia pendulina Formerly referred to as Rhus, S. pendulina is commomly called White karee. It is a medium- sized tree which is native to South Africa. It grows to a height of 5-10 m and it is evergreen. It is is drought and wind resistant, and it is planted as a garden plant due to its non-invasive roots

Figure 1g: A field of Searsia pendulina trees (Source: Palgrave 1984)

1.4.8 Portulacaria afra This is commonly called Spekboom and mostly found in the Eastern Cape and some parts of Western Cape, South Africa. It is a fleshy, softly woody shrub or small tree up to 3m – 4 m. It is evergreen. It derives its English name ‘elephant Food’ because of elephants affinity for the top shoots of the trees.

Figure 1h: A pot of Portulacaria afra species (Source: Palgrave 1988)

1.5 Dissertation outline This dissertation is divided into four chapters. Chapter 2 provides a review of the literature on the evidence and the impacts of forestation in storing and capturing atmospheric carbon in other parts of the world. Chapter 3 presents the methodology used to calculate the carbon sequestration potential for the different plantation. Furthermore, it highlights the model used for simulating carbon storage by plants. Results and discussion on findings are presented in Chapter 4 while concluding remarks and study limitations are presented in Chapter 5.

Chapter 2: Literature Review

2.1 Climate change: evidence and impacts

Climate change model simulations for the African continent showed that land areas over the Sahara and semi-arid parts of southern Africa are warming by as much as 1.60C with a rise in mean sea level around the African coastline of about 25cm by 2050 (Hernes et al., 1995; Joubert et al., 1996; Ringius et al., 1996 in Hulme et al., 2001). Furthermore, a decrease of 5-15% has been projected during rainy season between November and May in southern Africa (Sivakumar et al., 2000) and a slightly extended later summer season over eastern South Africa (Hewitson and Crane, 1998). Ragab and Prudhomme (2002) reported that results from Global Climate Model for southern Africa (Angola, Namibia, Mozambique, Zimbabwe, Zambia, Botswana and South Africa) suggest an increase of annual temperature ranging between 1.5 - 2.50C in the south to between 2.5-30C in the north, with summer range between 1.75-2.250C in the south and increases towards the north to between 2.75-30C in the south and increases towards between 2.5- 2.750C and an annual average increase in some parts of South Africa by 5-20%. In addition, Collier et al. (2008) reported that Northern and southern Africa will become hotter (40C or more), and drier (with precipitation falling by 10-20% or more); rainfall increase in eastern and parts of central Africa (by 15% or more); the high drought incidence in southern Africa which is as a result of El-Nino phenomenon; rainfall decrease will affect the Limpopo province of South Africa most. The aforementioned changes in climate have potential impacts and implications on various sectors including agriculture, hydrology, health, biodiversity, wildlife and rangeland degradation (Hulme et al., 2001). These consequences on agriculture culminate in loss of income which further leads to impoverishments (Makonda and Gillah, 2007), biodiversity loss and increased deforestation (Geist et al., 1997), human displacement resulting from severe droughts and flooding(Cane et al., 1997; Glantz et al., 1997; Phillips et al., 1998). For instance, Table 1 below shows the loss of cereal crops in 1992 and 1995 as a result of severe droughts. Due to the high reliance on natural resources, vulnerability to these impacts is particularly high among rural populace which is mostly predominant in developing regions like southern Africa (World Bank, 2000a cited by Leichenko, et al, 2001). 11

TABLE 1: THE DYNAMICS OF RURAL VULNERABILITY TO GLOBAL CHANGE: INCIDENCE OF DROUGHT AND CEREAL PRODUCTION IN SOUTHERN AFRICA, 1989-1998 ______

Year Incidence of drought Cereal production (metric tons)

______

1989 N 28,589,437

1990 N 23,076,669

1991 N 22,847,797

1992 Y 12,554,607

1993 N 26,216,219

1994 N 27,837,978

1995 Y 19,191,821

1996 N 28,840,965

1997 N 25,711,546

1998 N 22,513,982

Source: WORLD BANK 2000a cited in Leichenko et al., 2001

2.2 Mitigation: Carbon sequestration

Climate change mitigation refers to efforts to reduce or prevent emission of greenhouse gases either by using new technologies, renewable energies, energy use efficiency, management practices or consumer behavior (UNEP, 2013). Carbon capture and storage (otherwise known as carbon sequestration) is one of the ways to mitigate climate change.

Carbon sequestration describes long-term storage of carbon dioxide or other forms of carbon to either mitigate or defer global warming and avoid dangerous climate change. It has been 12 proposed as a way to mitigate the atmospheric and marine accumulation of greenhouse gases, which are released as a direct result of fossil fuels combustion. It involves methods such as biological, chemical, geoengineering, physical processes, etc. (Sedjo and Sohngen, 2012).

2.2.1 Afforestation and reforestation

Afforestation and reforestation are of great importance because they can be used to improve the quality of life, regain and rebuild the natural ecosystem, biosequestration and production of timber (UNFCCC, 2001; IPCC, 2003). Forestation is now commonly used by scientists to indicate either afforestation or reforestation. Helms (1998) defined afforestation as the establishment of a forest or stand in an area where the preceding vegetation or land use was not forest.

There are different schools of thought on the real importance and impacts of afforestation. While some believe it has negative impact on biodiversity and that several species have been made extinct or threatened by it, especially ground species (Armstrong et al., 1998; Allan et al., 1997). Others believe it has numerous advantages such as water catchment, bioremediation, carbon sequestration (Lenton and Vaughen, 2009; Arora and Montenegro, 2011). Grainger (2012) reported that only one-fourth of the deforested lands are reforested while Geist et al (1999) noted that in countries like South Africa, deforestation is high to medium owing to tobacco farming.

2.2.2 Carbon sequestration based on forest management

Bass et al. (2000: 282) categorized activities through which forest management can help reduce atmospheric carbon into three. These are: “Carbon sequestration (through Afforestation, Reforestation, and restoration of degraded lands, improved silvicultural techniques to increase growth rates, and implementation of agro forestry practices on agricultural lands)”; “Carbon conservation (through conservation of biomass and soil carbon in existing forests, improved harvesting practices such as reduced impact logging, improved efficiency of wood processing, fire protection and more effective use of burning in both forest and agricultural systems)”; and “Carbon substitution (which involves increased conversion of forest biomass into durable wood products for use in place of energy-intensive materials, increased use of biofuels such as 13 introduction of bioenergy plantations, and enhanced utilization of harvesting waste as feedstock such as sawdust for biofuel)”. “It is noteworthy that among these three carbon sequestration techniques, carbon conservation is regarded as having the greatest potential for rapid mitigation of climate change, whereas carbon sequestration takes place over a much longer period of time” (Bass et al. 2000: 282; Smith et al. 2000).

Agro forestry has been recognized to be of special importance as a carbon sequestration strategy because of its applicability in agricultural lands as well as in reforestation programs (Cairns and Meganck 1994; Ruark et al. 2003). By including trees in agricultural production systems, agro forestry can, arguably, increase the amount of carbon stored in lands devoted to agriculture, while still allowing for the growing of food crops (Kursten 2000).

2.2.3 Carbon sequestration on tree based systems “Carbon sequestered is the difference between carbon ‘gained’ by photosynthesis and carbon ‘lost’ or ‘released’ by respiration of all components of the ecosystem, and this overall gain or loss of carbon is usually represented by net ecosystem productivity” (Montagnini and Nair, 2004: 283-285). Due to the their ability to soak up the carbon that would otherwise rise up and trap heat in the atmosphere, trees and plants are important players in efforts to stave off global warming (West, 2013)

“Most carbon enters the ecosystem via photosynthesis in the leaves, and carbon accumulation is most obvious when it occurs in above ground biomass. More than half of the assimilated carbon is eventually transported below ground via root growth and turnover, root exudates (of organic substances), and litter deposition, and therefore soils contain the major stock of carbon in the eco system. Inevitably, practices that increase net primary productivity (NPP) and/or return a greater portion of plant materials to the soil have the potential to increase soil carbon stock” (Montagnini and Nair, 2004: 283-285)

2.2.4 Variation in species potential for carbon storage Koskela et al. (2000: 64-70) reported that the main fast-growing, short-rotation species are of the genera Eucalyptus and Acacia. Pines and other coniferous species are the main medium-rotation utility species, primarily in the temperate and boreal zones. They also noted that there is strong 14 variation in the carbon sequestration potential among different plantation species, regions and management and variations in environmental conditions can affect carbon sequestration potential even within a relatively small geographic area.

2.2.5 Carbon storage pool in forest ecosystem Based on the IPCC (2003) estimation of carbon stock, the following are the carbon storage pools. Table 2 gives an overview of where carbon is stored and locked in plants and in the soil therefore telling how amount of carbon sequestered in a forest ecosystem can be estimated. TABLE 2: Carbon stock in a tree S/N Source Component 1 Aboveground biomass Includes all living biomass above the soil including stem, stump, branches, bark, seeds, and foliage. It also include the live understorey 2 Belowground biomass All living biomass of coarse living roots greater than 2mm diameter 3 Dead wood All living non woody biomass either standing or lying on the ground (but not including litter) or in the soil 4 Litter All the litter, fumic and humic layers and all non living biomass with a diameter less than 7.5 cm at transect intersection lying on the ground 5 Soil Organic Carbon (SOC) All organic material in soil to a depth of 1m but excluding the coarse roots of the above ground pools 6 Harvested wood These include harvested wood products (HWP) in use and HWP in solid waste disposal site (SWDS) Source: culled from IPCC (2003) source category 5A1 2.2.6 Agro forestry as an option for carbon sequestration and choice of species in carbon sequestration Albrecht and Kandji (2003) reported that large quantities of carbon can be absorbed in agricultural lands which are managed alongside trees and animals. However, caution has to be applied especially in areas of land use and land cover, choices of species of trees and crops which are managed together and the quality of soil and environment. An increase of 1 ton of soil carbon pool of degraded soils may increase crop yield by 20-40 kg/ha for wheat, 10-20 kg/ha for maize and 0.5-1 kg/ha for cowpeas and it also enhances food security. Furthermore, carbon sequestration on this land has the potential to offset fuel emissions by 0.4-1.2 gigatons of carbon/year or 5-15% of global fossil-fuel emissions (Lal, 2004). The Encyclopedia of Earth reported that a land use and land cover change (which is a term for human modification of 15 earth’s terrestrial surface) are driving changes in ecosystem and environmental processes such as climate change at local, regional and global scales; Land-use and land cover change (LULCC) can increase the release of carbon dioxide to the atmosphere by disturbances, terrestrial soil and vegetation; and the major driver of this change is deforestation especially when followed by agriculture, which causes the further release of soil carbon in response to disturbance by tillage accompanied by other greenhouse gases such as methane (which result from altered surface hydrology, wetland drainage, rice paddies, cattle rearing) and nitrous oxide (input of nitrogen fertilizers, irrigation, cultivation of nitrogen fixing plants, biomass combustion). These are also important drivers of land pollution.

Newly planted or regenerating forests, in the absence of major disturbance, will continue to uptake carbon for 20-50 years or more after establishments, depending on species and site conditions, IPCC (2000). To balance between the land use for agricultural purpose and land cover by vegetation, the concept of agro forestry was introduced. Lundgreen and Nair defined agro forestry as a collective name for land use system whereby woody perennials are deliberately used on the same land management with agricultural crops and/or animals in some form of spatial and temporal distribution (Nair, 1984). Nair (1985a) came up with three basic types of agro forestry systems which are: • Agrisilviculture system, where tree and livestock are combined • Silvopastoral system, incorporation of tree crops and animal component • Agrosilvopastoral system, food crops, tree crops and animal component Consideration of tree species for afforestation requires an in-depth approach. Factors such as tree deciduousness, height, biomass, its release or uptake of nutrients from the soil are good indicators for optimal carbon storage by trees. 2.3 Cost-benefit analysis of carbon sequestration of forestation Ruiz-Garvia (2008) analyzed the cost benefit analysis of carbon sequestration of forestry in Bolivia town. The study revealed that managing a land for timber plantations and carbon benefits bring higher income for landowners and encouraged afforestation option for carbon sequestration. To calculate the economic benefit of carbon sequestration, Pathak et al (2011) noted that this is done on the assumption that carbon sequestration can be used to offset carbon dioxide emissions from fossil fuel combustion and industrial productions in setting certain 16 emissions limit hoped to be achieved. Adopting a meta-analysis regression model, results suggested that for most regions where trees can be grown, there may be room to include carbon credits from forest sinks in meeting Kyoto-type target. The competitiveness of terrestrial sink project is enhanced if post harvesting uses of wood (either as a bio fuel or wood products) are included (Cornelis Van Kooten et al., 2004). Jindal et al (2008) reported that forestry-based carbon sequestration has the potential to provide opportunities for development, environmental protection and restoration for the livelihood of rural farmers especially if they are allowed to sell credits either individually or in groups from trees that provide multiple benefits beyond carbon income.

2.4 Modelling carbon storage potential for forestation

Several models exist for calculating carbon sequestration. Examples of such model are the abstract A model which was developed to calculate carbon fluxes from agricultural soils. It factors in the effects of crops, climate and soil on the carbon budget of agricultural land (Vleeshouwers and Verhagen, 2002). Several other methods have also been used for land use cover change in different countries. Such include the IPCC Tier 1, 2 and 3 methodologies designed to calculate the emissions and removals from land use and land use change. However, this does not discuss additionality, baselines or leakage. There is also the European Union (EU) Renewable energy directive, CDM and voluntary Carbon standard methodologies (Bird et al. 2010). In reforesting grassland to forest in South Africa on short-rotation forestry, the IPCC method gave more robust results as against those of EU Renewable energy directive conservative results which are not suitable in a developing economy CDM (Bird et al., 2010).

2.5 Clean development mechanism (CDM) The Kyoto protocol rolled out three flexible mechanisms for allowing the Annex 1 countries meet their emission target cuts. These are Emission Trading (ET), Joint Implementation (JI) and Clean Development Mechanism (CDM). The CDM concept involves trade of credit known as Certified Emission Reduction (CER) between Annex 1 parties and developing nations at a cost. This trade allows Annex 1 parties meet their target in emission cuts by investing in developing nations. For the developing countries, this facilitates biodiversity and ecosystem sustainability in addition to the economic returns (Winkler et al., 2001). 17

2.6 REDD+ (Reducing emissions from deforestation and forest degradation) Reducing emissions from deforestation and forest degradation (REDD+) is an international fund- or credit-based mechanism for reducing carbon emissions and protecting forest ecosystems introduced by the United Nations Framework Convention on Climate Change (UNFCCC) (Alexander et al. 2011). It uses policy approaches and positive incentives on issues relating to REDD in developing countries; and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (UNFCCC 2010).

Although the primary goals of REDD+ are to reduce emissions and sequester carbon in forest ecosystems, it is targeted to provide other beneﬁts such as enhancing ecosystem resilience, increasing ecosystem productivity and maintaining its perpetuity as well as long-term stability of biological diversity (SCBD cited in Alexander et al. 2011)

2.7 Bush encroachment and carbon sequestration

Range/regime shift is a common phenomenon in different biomes all over the world. It is the shift in elevation, latitude or change in specific vegetation to another. If there is an adjustment in the geography or elevation of an area, then the habitat of species is affected. This leads to habitat loss or habitat fragmentation. The consequence of this is decline in biodiversity. When there is range shift in vegetation, from grasses to shrubby or even woody vegetation, it is called bush encroachment. Bush encroachment is the suppression of palatable grasses and herbs by encroaching woody species often unpalatable to domestic livestock. This thereby undermines the carrying capacity for livestock. This is of great significance because savannas in southern and central Africa contain a large and rapidly growing proportion of the world’s human population, including many pastoralists whose livelihood is threatened by this process (Lamprey, 1983; Scholes, 1997). It also leads to the loss of biodiversity and alter the biogeochemical process of a biome. Soil carbon sequestration may initially increase with bush encroachment but then decline if bush densities become so high as to inhibit understorey grass growth (Hudak et al 2003). Scientists have postulated several hypotheses as to the cause of the range/shift. The different causes that scientists thought might be responsible for range shift and bush encroachment include increase in the atmospheric CO2, large and intensive grazing by animals and fire. However, the cause of bush encroachment is still poorly understood (Ward, 2005) 18

Chapter 3: Methodology

3.1 Study areas

This study used three forestation areas in different countries (South Africa, Botswana and Namibia) (Fig 2). The areas are located in the Eastern Cape Province (ECP) in South Africa, Southeast Botswana (SBT) and the Caprivi Strip of Namibia (CSN). The Eastern Cape, which lies on the south-eastern South African, is a region of rugged cliffs, rough seas and dense green bush of the stretch (Fig 2). The province has diverse landscapes, ranging from the dry and desolate Great Karoo to the lush forests of the Wild Coast and the Keiskamma Valley, the fertile Langkloof, renowned for its rich apple harvests, and the mountainous southern Drakensberg region around the town of Elliot. ECP has excellent potential for forestry because the coastal areas receive good summer rainfall and have a moderate climate, becoming more subtropical to the north-west (SouthAfrica.info, 2013). Botswana lies in the center of southern Africa, between latitudes 18° and 27°S of the equator and between longitudes 20° and 29°E of Greenwich with a total area of around 582,000 km2. Besides being limited in amount, rainfall in Botswana is also characterized by high variability. Botswana receives rainfall mainly during the summer months (October to March). These conditions result in a semiarid climate giving way to drought episodes whose occurrence is irregular but with an average periodicity of approximately 16–20 years (MoFDP 1997; Ringrose et al 2002). Namibia is located in southwestern Africa (17–27°S to13– 20°E). Namibia can be divided into three major physiographical regions based principally on its landforms and soils: the Namib Desert, the Central Highland, and the Mega Kalahari (Okitsu, 2004a). Namibia has a dry climate with extremely variable and unpredictable rainfall. The average annual potential evaporation varies between 3,700 mm in the central southern area to 2,600 mm in the north (Erkkilae & Siiskonen, 1992; Okitsu 2004b). The range of temperature fluctuations throughout the year varies according to region. Generally, the hottest month is October, during which the average daily maximum temperature is 34–36°C.

Fig 2: Southern African domain showing (a) the topography and (b) land cover pattern over the region. The areas used for forestation over South Africa (ECP), Botswana (SPT) and Namibia (CN) are indicated with rectangles.

3.2 Calculation of Forestland Carbon Storage and emissions in South Africa, Namibia and Botswana. To determine the carbon storage potential of various species in the forests located in our three study regions, this study used two different approaches. First, the IPCC Tier 2 method was used. This method uses gain-loss equation for calculating the emissions from biomass and drained organic soils in a forestland/plantation and thus, simulating the amount of carbon stored in those forestlands. In the simulations, the default parameters from IPCC Guidelines (2006) and FAO (2003) data were used as simulation inputs. These data include the areas of forests/plantations in the individual nations and specific species grown in those forests. These data were then used in ascertaining carbons stored (and emitted) in a forestland over 20 years (which are 1990-2000, 2000-2005 and 2005-2010). Secondly, the study also used the emissions-storage statistical equations to determine the gross and net carbon sequestration as well as emissions from a forestland. Note that the estimates of carbon emissions due to decomposition were based on the probability within the next year and the probability of tree being removed using the formula in equations (Eqns) 1, 2 and 3 (Nowak and Crane, 2002). For the individual tree, estimates of mortality probability and decomposition 20 rates were obtained from literature as given by FAO (1997). Note that the probability value of tree removal annually (used in our study) in Southeast Botswana, Eastern Cape and Caprivi Strip is 30% (Burgess, 2006).

Emission = � × �! × Ʃ�! ( �!"#$%" + �!"#$% )------Eqn 1

!!" ! !! !!" ! �!"#$%" = + ------Eqn 2 !! !! !! !! ! ! �!"#$% = �! − ------Eqn 3 !! !! where Emission = individual tree contribution to carbon emissions; C = carbon storage in the next year; Mc = probability of mortality based on condition class; i =decomposition class (based on number of years left standing before removal); pi = proportion of the land use tree population in decomposition class i; Pab = proportion of tree biomass above ground, pab = number of years left standing before removal (yi - infinity for dead trees that will never be cut down

(natural decomposition)); dm = decomposition rates for mulched above-ground biomass and dr = decomposition rate for standing trees and tree roots (30 years).

3.3 Simulation of carbon sequestration: Model description and set-up The study used IPCC Tier 3 method to quantify the carbon sequestration potential of eight tree species commonly found in Southern Africa. The species are: Portulacaria afra, Acacia karoo, Eucalyptus grandis, E. nitens, E. smithii, Searsia pendulina, Combretum apiculatum and Pinus radiate. The characteristics of the species are given in Table (3). For the Tier 3 method, the study used a stand level simulation model CO2FIX model (version 3.1). CO2FIX V3.1 is the latest version of CO2FIX model, developed as part of the “Carbon sequestration in afforestation and sustainable forest management” (CASFOR) project (Masera et al., 2003). It is freely available from the CASFOR website (http://www.efi.fi/projects/casfor/). A detailed description of CO2FIX model can be found in Schelhaas et al. (2004) and Maseera et al (2003). It has been applied and validated in many case studies on temperate and tropical forest, and in various Afforestation and agroforestry projects (Masera et al., 2008). The model comprises six compartments (or modules) which are biomass, soil, product, bioenergy, finance and carbon accounting (Nabuurs and Schelhaas, 2012). It can quantify the annual carbon stocks and fluxes in the forest biomass and soil organic matter, and simulate various management scenarios and approximate differences in carbon dynamics. The model evaluates all volume tree data in the 21 different modules (i.e. biomass and soil as used in this study) and produces an annual output of stocks and fluxes of carbon. For the soil module in the CO2FIX model, it is characterized by Yasso parameters which include woody and non woody litters, decomposition rates for these litter, humus stock, solubility of compounds, lignin as well as holocellulose compounds (Table 4).