Gis based land use simulation of sustainable forest management and wood utilizat

GIS based Land use Simulation of Sustainable Forest Management and Wood Utilization in Thai Nguyen Province, Vietnam Dissertation With the aim of achieving a doctoral degree At the Faculty of Mathematics, Informatics and Natural Sciences Department of Biology Of Universität Hamburg Submitted by Dang Cuong Nguyen Hamburg, 2018 0 Day of oral defense: July, 5th 2018 The following evaluators recommended the admission of the dissertation Supervisor: Prof. Michael Köhl Co-supervisor: Prof. Gherardo Chirici Chairman of examination committee: Prof. Jörg Fromm I Declaration I hereby declare, under oath, that I have written the present dissertation on my own and have not used any resources and aids other than those acknowledged.

Hamburg, July 2018 Dang Cuong Nguyen II English review testimonial I certify that the English in the thesis: GIS based Land use Simulation of Sustainable Forest Management and Wood Utilization in Thai Nguyen Province, Vietnam written by Dang Cuong Nguyen was reviewed and is correct. Ortloff (US citizen), freelance translator and editor Susan J. Ortloff, July 10, 2017 III Acknowledgement During my doctoral studies at the Center for Wood Sciences, World Forestry and the Department of Biology at the Universtät Hamburg, I received a great deal of support from many people. I would like to express my deepest gratitude to my supervisor Prof.

Michael Köhl for his intellectual advice, encouragement and valuable guidance. His valuable comments have been the most helpful in improving this thesis. I am also thankful to Prof. Gherardo Chirici, Universita Degli Studi Firenze for being my second supervisor.

I would like to express my sincere gratitude to Dr. Volker Mues for discussions, suggestions and occasional technical support at various stages of this study from the course of my fieldwork to the final dissertation. I am indebted to Dr. Prem Neupane for introducing me to Prof.

Köhl and the World Forestry Center in Hamburg. Words are not sufficient to express my thanks to them. I would like to sincerely thank the Ministry of Education and training of VietNam (MoET) and Universtät Hamburg (Center for Wood Sciences, World Forestry) for providing me with a scholarship during my studies in Germany and financial support for fieldwork in Vietnam, respectively. Special thanks go to Konstantin Olschofsky, Daniel Kübler, Dr.Timo Schönfeld, Dr.Philip Mundhenk, Laura Prill, Vlad Strimbu and Giulio Di Lallo for their hospitality.

They always stood by my side and encouraged me. My sincere thanks to Prof. Do Dinh Sam, Prof. Ngo Dinh Que, Dr.

Nguyen Thi Thu Hoan, and MA. Bach Tuan Dinh for their support and evaluations. In the course of my fieldwork, I would like to thank Mr. Phan Trung Nghia and Mr.

Nguyen Anh Duc, key members of my research team, for their support during this time. My sincere thanks to Mr. Khuong Van Khai, working in center for Marine Hydro met research, Vietnam Institute of Meteorology, Hydrology and climate change, for providing climate data. It was impossible to conduct this study without contributions from Tran Ho who provided soil map and forest land cover map.

I am IV obliged to the province forest officers, forest owners, and mills in the study area for providing opportunities to collect useful information. Special thanks go to Mrs. Doris Wöbb and Mrs. Sybille Wöbb for their unconditional support in administrative issues and their caring assistance during my stay in Germany.

I am grateful to my wonderful colleagues at the Center for Wood Sciences, World Forestry. My loving thanks go to my wife Thi Thu Huong Nguyen and my son Dang Khoa Nguyen for their patience, understanding, encouragement, and support during my study abroad. V Research summary The concept of Sustainable Forest Management (SFM) is well established. Its principles of sustainable forest development and land use planning often require a compromise between socio-economic development and environmental interests.

Biophysical factors have a significant effect on the productivity of forest plantations, while socio-economical and economic factors impact profitability and management systems. To enhance profits from forest plantations, the tree species grown need to match the specific site conditions. At the same time, the efficiency of forest plantations depends not only on forest site productivity, but also on market driven factors such as timber price, timber demand and transportation cost. This study uses a combination of a land suitability assessments based on FAO framework for land suitability classification, multi-criteria, linear programming (LP) and a Geographic Information System (GIS) framework to identify suitable locations and achieve the highest profit for forest plantation management.

A suitability analysis and an optimization analysis were used. The suitability analysis with classes highly suitable, moderately suitable, marginally suitable, and unsuitable was conducted through a combination of land suitability assessments and multi- criteria decision analysis (Analytic Hierarchy Process, AHP). Three main criteria were used in the suitability analysis comprising soil properties, climate and topography. Maps presenting suitability classes were established in ArcGIS environment by Weighted Linear Combination (WLC).

To reflect growth of the studied species, volume growth was modeled using three models including Chapman Richard, Gompert and Koft models. All three models reflected growth well based on coefficient of determination (r2) and root mean square error (RMSE). However, the Koft model performed best and was selected in the optimization analysis to assign productivity on each suitability class. The results of the suitability analysis were used in the optimization analysis.

The optimization model was built by combining programming (visual basic application environment) and GIS (ArcGIS environment). The optimization model indicates VI that the optimal harvest age of a Acacia mangium plantation in the study area is 6 years, at which time the highest profits can be reached. The model used shows the tradeoff between timber demand and timber supply. When timber demand increases, profit obtained from forest plantations has a decreasing trend because of the assignment of areas having lower profit due to lower productivity and higher costs.

The optimization model also illustrates that even considerably small variations in timber price and costs have significant effects on the profit obtained and land area allocated to respective mills. The optimization model suggests the possibility of combining the needs of environmental conservation with socio-economic demands of stakeholders by establishing nature conservation areas. Shadow pricing can be used as a mean to derive compensation payment to assign and maintain forest areas for protective use. Additionally, the optimization model provides a tool to study the establishment of co-operated mills.

Three new mills could replace 215 existing mills and 3 new mills could be added with higher capacities. The findings of this study provide evidence for the need of a concurrent forest land utilization and mill development planning in order to maintain and enhance economic and ecological objectives and to improve local livelihoods. This holds especially true under extensive afforestation and reforestation activities, as recently promoted by the Bonn Challenge and the New York Declaration. VII Content Research summary VI Content VIII List of tables XII List of figures XIV List of abbreviations XIX 1 Introduction 1 1.1 The demand and supply wood from planted forest 1 1.2 The role of forestry in the Vietnam economy 6 1.3 Forest cover and plantations in Vietnam 8 1.4 The problem statement 12 1.5 Research question and objectives 16 1.6 The structure of thesis 17 2 Literature review 18 2.1 Application of the FAO framework and multi-criteria decision analysis in land suitability assessment 18 2.2 Multiple criteria decision making 21 2.2 Application of linear programming in land use suitability analysis 26 3 Material and methodology 31 3.2 Studied species 34 VIII 3.3 Data sources as basis for suitability mapping 38 3.1 Determination of ecological factors and classes for each ecological factor 43 3.2 Determination score assignment to suitability classes and weight for ecological factor 44 3.3 Land suitability integration by weighted linear combination 47 3.1 Technical equipment for execution of inventory on growth 48 3.2 Selection of stands for forest measurement 48 3.3 Design and location of sample plot 52 3.4 Calculation of stand variables 54 3.5 Adjustment of sample area at forest edges 55 3.6 Modelling volume growth for suitability classes 56 3.3 Determination of optimal rotation as maximum sustained yield 57 3.4 Assessment of socio-economic aspects of Acacia mangium plantations 58 3.5 Scenario simulation with geo-explicit optimization methods 61 3.1 Geo-explicit optimization model 61 3.2 Calculation of transportation cost in ArcGIS environment 67 3.6 Scenario analysis 69 4 Results 72 IX 4.1 Results of questionnaire 72 4.1 Result of questionnaires on forest activities of households 72 4.2 Results of questionnaires on sawmills 76 4.3 Assignment of suitability classes for Acacia mangium 78 4.2 Growth of Acacia mangium 83 4.1 Number of trees per hectare – diameter classes distribution according to suitability classes 83 4.2 Stand variables according to suitability classes 88 4.4 Mill_new and Mill_coop 136 4.5 Nature conservation area 144 5 Discussion 150 5.1 Discussion of suitability and growth model 150 5.1 Land suitability assessment 150 5.2 Forest growth model and productivity 152 5.2 Profitability maximization from growing forest plantations 153 X 5.1 Optimal rotation age 153 5.2 Profitability maximization from growing plantation 154 6 Conclusion 158 References 160 Appendix 175 XI List of tables Table 1.1 Area of planted forest by region from 1990 to 2010 .2 Predicted change in wood volume produced in planted forests between 2005 and 2030 (million m3 year-1) .3 The change in forest cover for the period 1995 -2014 .4 The planted forest area .1 Land suitability classes (FAO 1984) .2 Scale for pairwise comparison (The Saaty fundamental 9-point scale) .1 Forested area according to forest types .2 The information of soil properties.3 The weather stations in study area .4 The locations of 11 stations in which rainfall regime is collected .1 Descriptive statistics on the size and spatial situation of the household questionnaire (Exchange rate: 1 USD = 22000 VND) .2 Characteristics of mills derived from the questionnaires .3 Parameters for determining suitable classes by experts .4 Matrix of pair-wise comparison of all attributes by forestry experts .5 Weights of ecological parameters in land suitability assessment .6 Land suitability class for Acacia mangium .7 Summary results of calculation of stand variables .8 The fitted models for tested species .9 Value selected for attributes in the optimization model.10 The results for the Landscape Approach and the Current Forest Approach (PA: pallet mills, VE: veneer mills, WC: woodchip mills) .11 Land area allocated for the Landscape Approach and the Current Forest Approach for harvesting A.

mangium plantation at age 6 years.12 Total forested area allocated in different timber demand amount over 6 years in the Current Forest Approach (_FO) .13 Change of profit with various timber demands for specific mill types under the Landscape Approach, 6 – year rotation .14 Change of profit with various timber demands for specific mill types under the Current Forest Approach, 6 – year rotation.15 The timber price at mill types varied according sub-regions .16 Differences in cost, profit and land area allocated for growing plantations with variations in timber price on 6-year-rotation .17 Costs, profit and area varied by change of cost on 6 years rotation.18 Distribution of timber demand and timber price at mills .19 Different costs, profits and land area allocated for growing plantations by adding new mills on 6-year rotation .20 Distribution of timber demand and price at mills .21 Different costs, profits and land area needed by taking into consideration larger mills on 6-year-rotation.22 The difference of total profit obtained between the basic timber demand and increase of 20% .146 XIII List of figures Figure 1.1 Trend in area of planted forest between 1990 and 2010 (source: FAO 2010a) .2 Planted forest area by climate domain (Source: FAO 2015b) .3 The trend in planted forest area from 1990 to 2015 in 20 countries (Source: Payn et al.4 Wood production export turnover varied in the period 2004 - 2011 (MARD 2014b) .5 Wood production import turnover varied in the period 2006 - 2012 (MARD 2014b) .6 The distribution of planted forest areas by region in Vietnam .1 Location of study area.