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(Lihkl' :H'V WWHIWWII/Will”MM/WT“ 0064 5451 u ’5 - ‘ ~. £FW 0'4 smart-ve- '1 This is to certify that the dissertation entitled Undisturbed Short-term Growth of an in the Brazilian Tropical Moist Forest Amazon presented by Niro Higuchi has been accepted towards fulfillment of the requirements for PhD degreein Forestry 55/ Major professor Date {/1 31/6? 042771 Institution MS U i: an Alfmmm‘n Action/Equal Opportunity RETURNING MATERIALS: MSU Place in book drop to remove this checkout from LIBRARIES FINES will All-(gulls. your record. if book is be charged returned after the date stamped below. ”UN 1 1 19.0.0. ‘ 17:1" '~¢’ , 1'- r- } J I. v 1 I ‘l I 55. f ' l f‘rfi E-‘k’. “Anya “ mt! 21 “3“}? E . 2%55 SHORT-TERM GROWTH OF AN UNDISTURBED TROPICAL MOIST FOREST IN THE BRAZILIAN AMAZON BY Niro Higuchi A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Forestry 1987 IHEHRACT SHORT-TERM GROWTH or AN uuoxsruaaeo TROPICAL uorsr FOREST IN THE BRAZILIAN amazon. by NIRO HIGUCHI The main objective of this study is to provide basic information for sustained yield management of the tropical moist forest in the Brazilian Amazon. This was done by quantification of diameter distributions, projections of Idiameter distributions and of tree mortality, and by development of short-term growth and yield models. The data for this study were collected from an undisturbed stand located some 90 kilometers north of Manaus, the capital of Amazonas State - Brazil. Three permanent plots were established in 1980 and remeasured in 1985. They are the control plots of a forest management experiment randomly replicated within an area of about 2,000 hectares of pristine Amazonian forest. In each 4-hectare plot (200 by 200 meters), all trees with dbh 25 cm or greater were tagged and their dbhfls were recorded in 1980. In 1985. all tagged trees were remeasured with special attention to ingrowth and mortalityu The number of trees, dbh and basal area of the study area averaged 158 trees/ha. ii 38 cm, and 20 mZ/ha, respectively - in 1980. Among three different hypothesized diameter distribution functions, the Weibull using the percentile approach best fit the observed data. 3 Since age and successive records from long-term permanent plots were not available, the first-order Markov chain approach was used to project diameter distribution and tree mortality and proved to be a realistic alternative. The exponential Lotka growth model was adapted to predict future volume as an alternative for the traditional growth and yield models, and it behaved satisfactorily. The volume for 1990 was also predicted by models based upon the volume estimated in 1985 in relation to the dbh measured in 1980. There was a strong correlation between actual volume and past dbh, but not between past diameter and diameter growth. iii To Inezita and Chico, and Maria my children, my wife - my friends iv ACKNOWLEDGEMENTS I wish to express my gratitudetto Dr. Carl W. Ramm. Chairman of my dissertation committee, for his insight, support, and guidance in the preparation of this work. I also wish to extend my gratitude to Dr. Lee M. James, Dr. Kurt S. Pregitzer and Dr. Peter G. Murphy for serving on my guidance committee and assisting throughout my doctoral program. I would like to extend my acknowledgements to Dr. Phu Nguyen, Mr. T. W. W. Wood, Dr. Jurandyr C. Alencar, Dr. Kurt S. Pregitzer, Dr. Lee M. James, and Dr. Carl W. Ramm. They provided helpful suggestions on an earlier version of specific chapters of this manuscript . I would like to pay special tribute to my wife, my kids and my "pessoal" from Chavantes and Chapeco for their encouragement, patience and supportive "rezas". I am indebted to many people whose friendship was important during the course of this voluntary exile. Thank- you to Antonio & Lucia, Josmar & Fernanda, Carlos, Steve Westin, Robert De Geus, Bill Cole, Don Zak and George Host. I would like to express my sincere gratitude to Luis Maurc>& Fatima Magalhaes for being my proxy in Brazil and for their patient support during this time. Special thanks are due to the "peaozada" of DST (Departamento de Silvicultura Tropical)-Aluizhm5Cabore, Jesus, Barrao, Caroco, Paulista, Armando and other anonymous helpers - who have been my great masters in the forest and particularly for their help during field data collection. I also wish to thank the group of DST's "pica-pan" - Fernando, Antenor, Jurandyr, Magalhaes, Benedito, Noeli and Joaquim - who played an important role during the preparation of this research project. I am also indebted to many people from other departments of INPA for their support. Thank-you to "turma" of administration and to Nakamura. I gratefully acknowledge the support of many staff members of the Department of Forestry of Michigan State University. Finally, my sincere appreciation to my country - Brasil - through CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologi'co) for financial and administrative support, and INPA (Instituto Nacional de Pesquisas da Amazonia) for inspiration. THANK YOU GOD ! vi TABLE OF CONTENTS page TITLE . ABSTRACT ii DEDICATION iv ACKNOWLEDG EMENT S O O O C TABLE OF C ONTENTS O O O 0 vii LIST OF TABLES . LIST OF FI GURES O O O O xiii CHAPTERS 1. INTRODU CTION O O O O O Scepe of the Problem Statement of the Problem . 2. LITERATURE REVIEW ON THE MANAGEMENT OF NATURAL REGENERATION IN THE TROPICAL MOIST FORESTS 2.1. Overview . 2.2. Introduction . 2.3. Tropical America 03010101 2.4. Tropical Africa 12 2.5. Tropical Asia . 13 2.5. Tropical South Pacific . 16 2.7. Conclusion . 16 vii 3. THE BRAZILIAN AMAZON . 20 3.1. Introduction . 20 3.2. Climate . 21 3.3. Soils . 23 3.4. Vegetation . 25 Tropical moist forest on "terra firme" 27 Inundated forests . 30 "Campina" and "Campinarana" . 32 Tropical semi-evergreen forest . 34 "Cerrado" (Savannas) . 35 4. DESCRIPTION OF THE STUDY AREA . 39 5. MODELLING THE DIAMETER DISTRIBUTION OF AN UNDISTURBED FOREST STAND IN THE BRAZILIAN AMAZON TROPICAL MOIST FOREST: WEIBULL VERSUS EXPONENTIAL DISTRIBUTION . 47 5.1. Introduction . 47 5.2. Procedures . 48 The data . 48 The diameter distribution functions 49 The application of the functions . 52 5.3. Discussion of Results . S3 5.4. Conclusion . 55 6. A MARKOV CHAIN APPROACH TO PREDICT MORTALITY AND DIAMETER DISTRIBUTION IN THE BRAZILIAN AMAZON . 6.1. Introduction . 68 6. 2. PrOCEdures O O O O O O O O O O O O 71 The Data . 71 The Markov model . 71 The application of the model . 73 6.3. Discussion of Results . 75 6.4. Conclusion . 76 7. SHORT-TERM GROWTH OF UNDISTURBED BRAZILIAN AMAZON TROPICAL MOIST FOREST OF "TERRA FIRME" . 92 7.1. Introduction . 92 7.2. Procedures . 93 The Data . 94 Model Development . 95 7.3. Discussion of Results . 97 7.4. Conclusion . 102 8 0 CONCLUSIONS 0 O O O O O O O O O O O O O O I O O O 110 APPENDIX 0 O O O O O O O O O O O O O O O O O I O O O 113 L I ST OF REFERENCES 0 O O O C O O O O O O O O O O O 1 2 2 ix LIST OF TABLES Page 2.1. 1961 version of TSS - summary of operations . 18 2.2. Malayan Uniform System (MUS) - summary of activities . 19 4.1. Listed species for the NR management project . 44 5.1. Diameter (cm) descriptive statistics for the study area . 56 5.2. Parameter estimates used for diameter distribution - hectare basis . 57 5.3. Diameter distribution for all 3 sample plots together (Bacia 3) derived from 3 different methods . 58 5.4. Diameter distribution for Bloco 1 derived from 3 different methods . 59 5.5. Diameter distribution for Bloco 2 derived from 3 different methods . 60 5.6. Diameter distribution for Bloco 4 derived from 3 different methods . 61 6.1. Bloco 1 - Transition between states during a 5-year period . 78 6.2. Bloco 2 - Transition between states during a 5-year period . .'. 79 6.3. Bloco 4 - Transition between states during a 5-year period . 80 6.4. Bloco 1 - Transition probability matrix from one state to another during a 5-year period . 81 6.5. Bloco 2 - Transition probability matrix from one state to another during a S-year period . 82 6.6. Bloco 4 - Transition probability matrix from one state to another during a 5-year period . 83 6.7. Bloco 1 Two-step transition probability matrix . 84 6.8. Bloco 2 - Two-step transition probability matrix . 85 6.9. Bloco 4 - Two-step transition probability matrix . 86 6.10.
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