Development and Testing of a Procedural Model for the Assessment of Human/Wetland Interaction in the Tobari System on the Sonoran Coast, Mexico

AN ABSTRACT OF THE THESIS OF

Carlos Valdes-Casillas for the degreeof Doctor of Philosophy in Geography presentedon June 28 1996.

Title:DEVELOPMENT AND TESTING OF APROCEDURAL MODEL FOR THE ASSESSMENT OF HUMAN/WETLANDINTERACTION IN THE TOBARI SYSTEM ON THE SONORANCOAST, MEXICO

Abstract approved: Dr. James R. Pease

Coastal wetlands provide basic linkagesbetween productive estuarine and freshwater ecosystems. Throughoutthe Mexican coast, rates of wetland loss andchange are unknown. This project developed wetlandinventories for 1973 and 1991, including ecological functions and values, andhuman activities in and around the wetlands.Data was integrated by use of a geographic informationsystem. Identification of changes in wetlands and human activitieswas completed, as well as analyses of relationships between

wetland change and changes in humanactivities. The model also identified andevaluated Mexican governmental policiesaffecting wetland changes. Results include descriptions,maps, and analyses of wetlands conditions and human activities, changes overan 18 year period, and interactions supported bycorrelation analyses Wetlands functionswere summarized for the Tobari system. Human activities showed an increase in aquaculture, salt mining, agriculture, and fisheries.Changes by spatial distribution are shown inan intensity map. The federal government haspromoted policies focusedon development of irrigation districts, including self-sufficiency in grains and openingagricultural land. Economic incentives includesubsidies, infrastructure financing,price controls, and compensation for international marketfluctuations. Federalgovernment policies did have important impactson wetland change.

The emphasis of this modelwas on correlation between changes in wetland functions and values, and changes in human activities. Whilewetland distribution, classes, and interactions are essential information, assigning valueto them requires knowledge of their functions. Since valuesoften depend upon local cultural andeconomic conditions, local perception of wetland valuesemerge from people's awareness of them. Some values are recognized by local people in the Tobari system, especially those related to their economic system. Others, such as those relatedto water quality and climatic regulation, are not recognized yet. Results indicate that statistical analysis resulted in moderateto high correlation between changes in wetland types and changes in landuse patterns. This research contributes to understanding wetland functions and their relationships with humanlife styles. ©Copyright by Carlos Valdes-Casillas June 28, 1996 All Rights Reserved DEVELOPMENT AND TESTING OF A PROCEDURAL MODEL FOR THE ASSESSMENT OF HUMAN/WETLAND INTERACTION IN THE TOBARI SYSTEM ON THE SONORAN COAST, MEXICO

Carlos Valdes-Casillas

A THESIS

submitted to

Oregon State University

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Completed June 28, 1996 Commencement June, 1997 Doctor of Philosophy thesis of Carlos Valdes-Casillas presented on June28, 1996

APPROVED:

Major Professor, representing Geography

Head of Department of Geo sciences

Dean of the Gradte School

I understand that my thesis will become part of the permanent collectionof Oregon State University libraries. My signature below authorizes release of my thesis to anyreader upon request.

Carlos Valdes-Casillas, Author ACKNOWLEDGMENTS

...It all began when my wife Elena and I discussed a dream while our first months of marriage, fifteen years ago. Then, a few months later, Dr. Enrique Carrillo Barrios- GOmez augured Elena and me a "very fulfilling life" while getting our Masters at Oregon State University. His suggestion led to fiveyears of much more than just studies at Corvallis, and now this thesis; and with it, a full array of opportunities. The initial encouragement and friendship of Enrique and his wife, Socorro, is unswerving. For guiding and criticizing my Ph.D.program and dissertation, I thank the Geography program in the Department of Geo sciences. I especially appreciate Dr. James R. Pease's assistance and friendship in cultivatingmy interests in Geography, sharing with me his valuable expertise, guiding me into the geography science, and helping me to structure a critical mind, always leading me into research perspective. Members of my committee, including Dr. Gordon E. Matzke, Dr. A. Jon Kimerling, Dr. Frederick Smith, and graduate representative Dr. Steven C. Rubert, each made contributionsto my program and thesis. The National Council of Science and Technology (CONACYT) for the full economic support through my studies. Thanks to Dr. Guillermo Soberon-Chavez, Director of the Instituto Tecnologicoy de Estudios Superiores de Monterrey-Campus Guaymas for hisencouragement, extending my employment, and providing continuous support for my research. The North American Wetland Conservation Council, for their support and assistance in the conservation efforts of Southern Sonora Wetlands. In Oregon, Ram6n and Carmen Simbeck who shared withme their experience and guided me to value each hour of work, they also provideus with day to day support and friendship since the first day we arrived to Oregon. Thanks to Jim and Janet Good,Peter and Kathryn Howd, Paul and Mary Richards, Jay and Bonnie Lorenz, Scott and Jane Splean, and Antonio Martinez Cob. Their interest and unconditionalsupport went beyond friendship. In Corvallis, Pat, Jocey and Murphy Pease, Alice Hackenshmith, Enrique, Dolores and Daphne Riquelme, and Gaby Rosales for helpingme in my last stage.. Jan Meranda's suggestions and company, Joanne and Theresa in the main office, and all the Geosciences friends, thanks..To Bob and Karen Streeter, for her friendship and intensive guidance. A number of individuals made special contributions toward assembling the database, and producing this thesis. In Guaymas, the Biogeographic Information Unit personnel, with friendship and patience,saw me through the process of getting my attention back to this research, thanks to Manuel and Gloria Murioz, who sendme the information from Mexico City since the development of the original proposal and lateron collaborated with me at ITESM. Thanks to Luis Bowillon and Maiisol Tordesillas, Jose Campoy and Jorge Sereno, for their contributions in getting materials ready, sharing their knowledge and the support while the development of research and fieldtrips for wetland assessment. To Ma. de Jests and Liliana for their help in digitizing and map editing. Mariana, Diana and Raquel, for all those little details in adjustment of thereport. For Assistance with research design and statistical analysis I thank Ernesto Bravo Nunez at the Metropolitan Autonomous University UAM-Ixtapalapa in Mexico City, and Gaby Rosales from Oregon State University. The Dr. Idelfonso de la Pena, form the National Water Commission in the State of Sonora, Dr. Christopher Watts at CIDESON, Pedro Rosales from ITMAR, The Prof. Hector Araiza form the Autonomous University of Sinaloa (UAS), andmany local institutions for facilitating reports and publications and share their experience in the field. To "El Coffee" for his help and hospitality during the field trips. To Hugo Rodriguez, that patiently asked me day by day if I finished, finally Hugo, yes I did. To Alberto Oriza and Irene Gamio, for being continuously editing maps and text, helping me in the GIS processing of the aerial photos, maps and databases, sure life in the last stage of this dissertation would havea different history if they had not been there. Because of the time it took me to finish this research, the list of individuals and organizations would be very long, in different stages and differentways many people made it possible, thanks to all of them. I was fortunate to have Bruce and Loren Bechtel, being lucky enough of having them in Oregon, then in Guaymas, then in Tucson and lateron, back in Oregon. They were beside me all along, thanks. Embarking on my Ph.D. program was made possible by encouragement frommy family to follow my dreams. To my parents, Rodrigo and Marcela, they helpme talking to government officials in Mexico City, sending me materials and always a warm confident support; my sisters: Maria Marcela, who was responsible for helping me several times in my trips to Corvallis, and also spending long nights getting the literature ready; La Chachineca, always ready to help; To Rodrigo, Anita, Rodri, Diego and Eduardo, always living in me. Adri, Claudia and Loren, andmy father-in-law, (Paco) Dionisio Chavarria and Marcela, thanks to all. To my wonderful Cachorros, el Carlitosy la Ita. Their cheerful smiles and love helped keep my work in perspective Lsaben?, thanks for all the time of absence and remainders of....iya acaba! Finally, to Elena my wife, who has always provided totalencouragement and support. She would never imagined how far an answer to: where is the classroom? might take; I am sure this thesis would finally be the only Birthday and Christmaspresent she has ever asked me. For her faith and patience, this is your dissertation, and the degree goes on to you, iGracias! trilyat. To Elena, Ma. Teresa, Rosa Estela, Tartaleta, Mirmicine

and Tat!

To Carlitos and Elenita

To my brother Rodrigo TABLE OF CONTENTS

INTRODUCTION 1 1.1. Need for the Project 3 1.2. Research Problem and Research Hypotheses 4 1.3. The Proposed Procedural Model for Wetland Assessment 6 1.4. Organization of the Document 8

LITERATURE REVIEW AND BACKGROUND 9 2.1. Assessment of Land Resources 9 2.1.1. Land Use 9 2.1.2. Land Use Change 10 2.1.3. Land Use Classification 11 2.1.4. Monitoring of Land Use Change and the Process of Land Use Planning 13 2.1.5. Changes of Coastal Wetlands in Sonora and Land Use 14 2.2. Wetland Assessment 15 2.2.1. Wetlands as Critical Habitat 15 2.2.2. International Importance 16 2.2.3. Wetlands' Functions and Values: from Inventories to Wetland Management 18 2.2.4. Wetlands in Mexico 20 2.3. The Sonoran Coastal Zone 22 2.3.1. Development of Southern Sonora Coast and the Water Dilemma 23 2.4. The Tobari System, a Geographic Setting 25 2.4.1. Climate 29 2.4.2 Hydrology 29 2.4.3. Geology, Geomorphology and Soils 31 2.4.4. Human Activities 31 2.4.4.1 Mining 32 2.4.4.2. Tourism and Hunting 32 2.4.4.3. Fishing 32 2.5. Environmental Issues in the Tobari System 34

RESEARCH DESIGN AND PROCEDURES 36 3.1. Procedural Model for Wetland Assessment 36 3.2, Wetland Inventory /2 Dates 38 3.3. Wetlands Functions and Values 38 3.4. Land Uses and Land Use Patterns / 2 Dates 38 3.5. Database Development and GIS Integration 42 3.6. Identification of Changes in Wetlands and in Land Uses 45 3.7. GIS Analysis, Statistical / Spatial Integration of Results 45 3.8. Correlation of Wetland Change / Land Uses and Land Use Patterns 46 3.9. Policy Related Causes for Wetland Change 47 3.10. Considerations for the Sustainable Use of Wetland Areas 47

RESULTS 48 4.1 Wetland classes 48 4.1.1. Estuarine / Subtidal / Unconsolidated Bottom (ESUB). 49 4.1.2. Estuarine / Intertidal / Rocky Shore (EIRS) 50 4.1.3. Estuarine / Intertidal / Unconsolidated Shore (ERJS) 50 4.1.4. Estuarine / Intertidal / Emergent Wetland (EIEW) 52 TABLE OF CONTENTS (Continued)

4.1.5. Estuarine / Intertidal / Scrub-Shrub Wetland (EISS) 52 4.1.6. Palustrine / Unconsolidated Bottom (PUB) 54 4.1.7. Palustrine / Emergent Wetland (PEW) 54 4.2. Wetlands in 1973 55 4.3. Wetlands in 1991 57 4.4.Wetland Functions and Values 59 4.5. Human Activities Adjacent to the wetlands- 1973 63 4.6. Human Activities Adjacent to the wetlands- 1991 64 4.7. Spatial Changes 1973-1991 64 4 8 Human / Wetland Interactions 69 4.8.1. Interrelations of Estuarine Subtidal Unconsolidated Bottom 70 4.8.2. Interrelations of Estuarine Intertidal Rocky Shore 71 4.8.3. Interrelations of Estuarine Intertidal Unconsolidated Shore 72 4.8.4. Interrelations of Palustrine Unconsolidated Bottom 73 4.8.5. Interrelations of Estuarine Intertidal Emergent Class 74 4.8.6. Interrelations of Estuarine Intertidal Scrub-Shrub Class 75 4.8.7. Interrelations of Palustrine Emergent Wetland 76 4.8.8. Interrelations of Bare Land Class 77 4.8.9. Interrelations of Natural Vegetation Class 78 4.8.10. Interrelations of Dunes Class 79 4.8.11. Interrelations of Irrigated Agriculture Class 80 4.8.12. Interrelations of Aquaculture Class 81 4.8.13. Interrelations of Salt Mine Class 82 4.8.14. Interrelations of Abandoned Land Class 83 4.8.15. Interrelations of Small Towns Class 84 4.8.16. Interrelations of Rural Settlements Class 85 4.8.17. Interrelations of Tourism Class 86 4.9. Spatial Correlation of Wetland Change and Land Use Patterns 87 4.10 Government Policies Related to Wetland changes 91 4.10.1. The National Development Plan 93 4.10.2. The Sonora Development Plan 96 4.11. Policy Issues in the Tobari System 97 4.11.1. Agriculture 97 4.11.2. Water 98 4.11.3. Aquaculture 100

5. DISCUSSION AND CONCLUSIONS 101 5.1. Problems in Wetland Classification and Identification 101 5.2. Advantages and Disadvantages of Materials Used for Analysis 102 5.3. Spatial Accuracy in Data Transformation and Methodological Problems 102 5.4. Tobari Wetlands in 1973 and 1991 103 5.5. Wetland Functions and Values 104 5.6. Human Activities Adjacent to the Wetlands 106 5.7. Changes of Wetlands and Human Activities 107 5.8. Statistical Correlation of Wetland Change and Patterns of Land Use 114 5.9. Government Policies 118 5.10. Model Efficiency in Explaining Changes in Wetland Functions 120 5.11. Conclusions 122 5.12. General Comments 123 TABLE OF CONTENTS (Continued)

BIBLIOGRAPHY 126

CARTOGRAPHIC MATERIALS 141

APPENDICES 143 Appendix 1 Overlay Database 73+91 144 Appendix 2 Estimated Costs for the Procedural Model 165 iv

LIST OF FIGURES

Figure Page

1.1. Geographic Location within the Southern Sonora Coast 2 1.2. Procedural Model for Wetlands Assessment 7

2.1. The Tobari System Base Map 27 2.2. Aerial View of Huivulai Island 28 2.3. Access Road to the Huivulai Island 28 2.4. Climogram of Villa Juarez Data 30 2.5. Human Activities in the Tobari System 33

3.1. Flow Chart of Methods (Procedural Model in Detail) 37 3.2. GIS Overlay Process to Obtain Change Data 46

4.1. Photography Showing an Example of an Area within the ESUB Class 50 4.2. Photography Showing a Portion of the Road and the EIRS Class 51 4.3. Photography Showing the Paredoncito Shoreas Example of EIUS Class 51 4.4. Photography Showing Intertidal Emergent Grassesas Example of ELEW Class 52 4.5. Photography Showing an Example of Areas of EISS Class 53 4.6. Photography Showing Red Mangrove Rhizophora mangle of the EISS Class 53 4.7. Photography Showing an Example of an Area within the PUB Class 54 4.8. Photography Showing an Example of an Area within the PEW Class 55 4.9. Tobari System in 1973 56 4.10. Percentages of Total Area for 1973 57 4.11. Tobari System in 1991 58 4.12. Percentages of Total Area for 1991 60 4.13. Change Map of the Tobari System 1973/1991 65 4.14. Total Area per Class for 1973 and 1991 66 4.15. Total Change from 1973 to 1991 67 4.16. Interrelations of Estuarine Subtidal Unconsolidated Bottom 70 4.17. Interrelations of Estuarine Intertidal Rocky Shore 71 4.18. Interrelations of Estuarine Intertidal Unconsolidated Shore 72 4.19. Interrelations of Palustrine Unconsolidated Bottom 73 4.20. Interrelations of Estuarine Intertidal Emergent Wetland 74 4.21. Interrelations of Estuarine Intertidal Scrub-Shrub 75 4.22. Interrelations of Palustrine Emergent Wetland 76 4.23. Interrelations of Bare Land 77 4.24. Interrelations of Natural Vegetation 78 4.25. Interrelations of Dunes 79 4.26. Interrelations of Irrigated Agriculture 80 4.27. Interrelations of Aquaculture 81 4.28. Interrelations of Salt Mine 82 4.29. Interrelations of Abandoned Land 83 4.30. Interrelations of Small Towns 84 4.31. Interrelations of Rural Settlements 85 4.32. Interrelations of Tourism 86

5.1. Changes in Areas, Functions, and Values for the Tobari System 112 LIST OF TABLES

Table Page

2.1. Summary of the Main Causes of Wetland Degradation 17

3.1. Classification of Wetlands and Deepwater Habitats 39 3.2. Classification of Coastal Wetlands for the Tobari System 39 3.3. Summary of Wetland Functions and Values 40 3.4. LUCID Classification for Land Use Patterns 41 3.5. Human Activities in the Tobari system 42 3.6. Class Equivalence for Human Activities, Land Use/Cover, and LUCID System for Uplands in the Tobari System 42 3.7. Codes for Labeling Land Uses and Wetland Classes 44 3.8. Database structure for Each Date of Aerial Photography 45

4.1 Summary of the Classification Applied to the Tobari System 49 4.2, Data Summary for the Classified Areas of 1973 55 4.3. Data Summary for the Classified Areas of 1991 59 4.4. Summary of Wetland Functions for the Wetland Classes of the Tobari System 61 4.5. A Summary of Wetland Values for the Tobari Wetland Classes 62 4.6. Wetland Group Categories According to their Functions and Values 63 4.7. Change from 73 to 91 66 4.8. Summary of Changes by Class 73 into Class 91 67 4.9. Interrelations of Estuarine Subtidal Unconsolidated Bottom 70 4.10. Interrelations of Estuarine Intertidal Rocky Shore 71 4.11. Interrelations of Estuarine Intertidal Unconsolidated Shore 72 4.12. Interrelations of Palustrine Unconsolidated Bottom 73 4.13. Interrelations of Estuarine Intertidal Emergent Wetland 74 4.14. Interrelations of Estuarine Intertidal Scrub-Shrub 75 4.15. Interrelations of Palustrine Emergent Wetland 76 4.16. Interrelations of Bare Land 77 4.17. Interrelations of Natural Vegetation 78 4.18. Interrelations of Dunes 79 4.19. Interrelations of Irrigated Agriculture 80 4.20. Interrelations of Aquaculture 81 4.21. Interrelations of Salt Mine 82 4.22. Interrelations of Abandoned Land 83 4.23. Interrelations of Small Towns 84 4.24.Interrelations of Rural Settlements 85 4.25. Interrelations of Tourism 86 4.26. Summary Data for Change and no Change Areas and Polygons 87 4.27. Pearson's Correlation Coefficient, Showing Total Child and Parent Polygons 90 4.28. Means (Instruments) of Accomplishing Environmental Policies in Mexico 95 4.29. Environmental Strategies, Projects and the Priority Action Program 95

5.1. Total Functions and Values for the Tobari Wetland Classes 110 5.2. Weighting Factor based on Wetland Functions and Values 111 5.3. Summary of Correlation Results for LUCID Classes 117 "Tiw management of land degradation istherefore an art, rvith a huge palette of responses or avoidanceprocedures, the application Of which involve.s. %wine judgments, wisdom andscientific skill." Barrow, 1994

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CHAPTER 1 INTRODUCTION

Discovering the rules of engagement for our human relationship to the environment has been a continuous challenge for geographers. From the planning perspective, a sustainable development approach to land andresource management seems to be generally accepted, but to date, there is no proof that it is achievable. Our capabilities to share and access informationon a global scale provide a limitless and formless structure for research; however, scientific paradigms suchas sustainable development still pose a major challenge. The emerging science of landscape ecology incorporates geographical knowledge and technology, and offers alternativescenarios for testing sustainable development models using meaningful environmentalindicators, including plant and animal species, patterns of landuse, and community environmental health.

One recently "discovered" landscape indicator is thepresence and health status of wetland ecosystems. In most parts of the world, wetlandsystems have been drastically altered from their original condition. The identification ofcauses for wetland change requires a methodology that can be appliedto conditions at regional system levels. The overall purpose of this research is to design and testa procedural model to identify and classify coastal wetlands withina wetland classification system, and to correlate changes of wetland types to human activities. A portion of theSonora coast in Northwestern Mexico (Figure 1) is used to demonstrate this model. 2

Figure 1.1. Geographic Location within the Southern Sonora Coast.

Coastal wetlands are among the most productive ecosystems, providing basic linkages between estuarine and freshwater food webs. The importanceof wetland systems is highlighted by their ecological functions, since they provide habitatfor survival of many endangered species, and are essentialareas for feeding, nesting, shelter and breeding of a vast variety of organisms (The Conservation Foundation, 1988; Contreras and Zabalegui, 3

1988). Wetlands offer human benefits, serving as filters for pollution, buffers for flood protection, sources of organic matter essential for fisheries, and criticalareas for the reproduction of economically important species such as shrimp and shellfish (PSWQA, 1991).

1.1. Need for the Project. Lack of knowledge about the status of wetlands has concerned interestedgroups at national and international levels. Recently, an international agreement among Canada, United States, and Mexico was established (Tripartite Commission) for the protection and management of wetlands (U.S.F.W.S., 1993). One of the first actions promoted by this agreement was developing a program that will increase the attention given to wetland management. However, projects undertaken in Mexico under this initiative were forced to focus on wetland inventory first, because required information for managementwas not available (U.S.F.W.S., 1993). These inventorieswere necessary in order to understand the current status of wetlands, and the significance of existingor potential threats to them. The materials being used in this research, suchas maps and aerial photography, are commonly available throughout Mexico. Therefore, as these methods prove successful, their applicability to other regionscan provide a way to better understand the causes of wetland change in the Mexican coastal zones. In addition, identification and assessment of human/wetland interaction can provide criteria for decision-making, thus establishing a rationale for land use planning,on both regional and national levels in Mexico. Geographers are concerned with the spatial interactions of earth's phenomena, the relationship of human activities to the environment, and the physical features and conditions of the area. Coastal wetlands and the surrounding landuses provide a practical framework for geographical analysis. This project contributesto the science of geography by:

Applying a combination of geographical techniques forresource inventory, spatial analysis, and statistical interpretation; Proposing a procedural model for the assessment of human/wetland interaction; and,

Testing the model's feasibility on regional conditions in Northwestern Mexico.

1.2. Research Problem and Research Hypotheses. Despite the development of a series of assessment techniques derived from landscape applications to policy issues (Bojorquez-Tapia, 1989), landuse monitoring and studies on land use change in Mexicoare fairly recent and information on causes, localities, and rates of change isscarce (Flores and Gerez, 1988). Throughout the Mexican coast, wetlands have not been adequately inventoriedto determine wetland types and their spatial distribution. Rates of wetland loss andextent of change are also unknown.

Lot et al (1993), when talking about vascular aquatic plants, pointedout the lack of comprehensive inventories: ...In general, there is a great need in Mexico for aprogram on a wide scale that would allow for greater exploration, especially in those states whose biological diversity is poorly known The incomplete knowledge of the biodiversity of these states underscores the importance of their study...." Although studies on certain marine and estuarine wetlands in Mexico have been published, Mexican wetlands asa whole have not been fully described (Olmsted, 1993). The conversion of wetlands to agricultural lands, with accompanying dredging andwater pollution, has reduced the extent of wetlands and changed the groundwater level and inundation cycles (Redzowsky, 1983).

Shifts in economic activities along the coast, changes in populationdistribution, and agricultural development,are the principal pressures that indicate the need to manage wetland resources properly. Throughout the world (Olsen, 1993)and for Mexico, integrated management programs have been proposedas the appropriate coastal management framework (Cervantes, 1994); however, the baseline information required for this integrated approach to planning and development is stillunavailable in most of Mexico. 5

In Mexico's centralized economy, with its strong emphasison sectoral planning, economic activities are to a large extent determined by governmental policies; which commonly influence the increase or decrease of certain human activities. Planned development in Mexico is outlined in the National Development Plan, and at the regional level, in the State Development Plan. These documentswere analyzed to determine to what extent governmental policiesare promoting wetland changes through subsidies to development activities. First, identification of coastal wetlands' current conditions is required, including wetland types and human activities related to them. Human activitiesare evaluated through the different land uses and the way theyare spatially distributed; such arrangements constitute patterns of land use. These human activities may be associated with wetland modifications. The primary hypothesis of this research is that: Changes of wetland types are associated with certain patterns of landuse and human activities. A secondary hypothesis is that government policies have influenced wetland change, by encouraging certain types of development. Government documents and programs are evaluated to test the secondary hypothesis. In order to test these hypotheses, the overall objective of this study is: To develop and test a procedural model for the assessment of human / wetland interaction, through wetland change detection and correlation to land use patterns for the Tobari system in Northwest Mexico.

More specifically, the objectivesare: To identify and map wetland types for two dates of aerial photography; To identify wetland functions and values reported in the literature for the wetland types found in the studyarea; To identify human activities adjacent to the wetlands for two dates of aerial photography; 6

To identify and map changes in wetlands and human activity types; To test whether wetland changes and land use patternsare statistically associated; To identify government policies that might have encouraged changes in land use patterns associated with wetland changes; and, To evaluate model efficiency in time and costs, and model validity in terms of explaining changes in wetland functions.

1.3. The Proposed Procedural Model for Wetland Assessment. The procedural model (Figure 2) considers firsta wetland inventory, by classifying and mapping wetland types for two dates. Changes in wetland distribution between these two dates are then tabulated and analyzed. Ecological functions of wetlands, suchas providing wildlife habitat, sources of primary production, and water retention,are well defined in published literature, as well as the "services" they provide for society; these services include flood protection, recreational areas, and fishing grounds. These servicesare recognized as wetland values. Therefore, after identifying wetland types, it is possibleto identify from published literature the wetland functions and values for those wetlandtypes. This allows identification of changes in wetland functions and values,to determine whether an increase or decrease has occurred for the period analyzed. A land use classification is then developed to providean understanding of how changes in human activities are related to wetland changes. This landuse classification is applied to the two dates. Maps for both dates show the association of wetlandtypes and land uses, and a wetland changemap is then spatially correlated with human activities. The need for an assessment procedurewas suggested by the lack of wetland inventories at the regional level in Mexico. At the end of 1991,as an effort to get funding for this dissertation research,a series of adjustments were made to the dissertation proposal to achieve a suitable method for wetlandassessment in Mexico. Emphasis in the procedural design was put on theuse of available materials and expertise commonly found in Mexico. 7

Wetland Inventory / 2 Dates I

1 Wetland Functions and Values I

4, Land Uses and Land Use Patterns /2 Dates

GIS Integration

Identification of Changes in Wetlands and in Land Uses

GS AnalysisI

Statistical- Correlation of Wetland Change / Land Uses; Spatial Integration of Results

Policy Related Causes

Considerations for the Sustainable Use of Wetlands

Figure 1.2. Procedural Model for Wetlands Assessment.

Thus the Procedural Modelwas adjusted while proposal writing and identification of potential fundingsources went on. During this process, the identification of an 8

appropriate area for model testing was a key to its successful development. In 1992-1993 the proposal grew into a larger proposal that includeda broader approach and participation of a multidisciplinary team. It considered the integration of informationon wetland resources, human activities, and the design and development of public involvement activities and environmental education materials. This projectwas entitled Evaluation and Management Requirements for Coastal Wetlands in Southern Sonora, Mexico: Resource Information, Assessment of Human Activities, and Environmental Education (see Valdes et al, 1994). As part of that project,a series of spatial and tabular databases were developed for a coastal area south of Guaymas (Figure 1). Materialswere gathered, maps were digitized, and several field tripswere carried out for groundtruth and preliminary assessment. These materialsare one of the data sources for this research, although this research focuseson one wetland system (from the eleven systems evaluated for that project). Some complementary activitieswere carried out during 1995 for field verification, data integration, and GIS analysis.

1.4. Organization of the Document. This document has been structured in five chapters. Chapterone is a general introduction and includes the research problem, the hypotheses and objectives. Chapter two presents a discussion of three topics that provide the background information,as well as discussion of related research. Chapter three contains the research procedures that allowed hypothesis testing and servesas one of the contributions of this research: the procedural model for evaluating coastal wetlands. Chapter fourpresents and discusses the results, as a synthesis of tabular data and supportingmaps, which are summarized in a map of change intensity and human/wetland statistical associations. This Chapter also identifies weaknesses and strengths of the procedures. Chapter five analyzes the effectiveness of the proposed model and elaborateson recommendations for model application to other coastal regions. Consulted references and appendix sectionsare also included at the end, showing the related literature, databases, and thecosts involved in development of procedures. 9

CHAPTER 2 LITERATURE REVIEW AND BACKGROUND

In order to introduce the reader to the issues related to this research, three main topics were chosen for the literature review. The first deals with landuse and land cover when assessing land resources; the second with the importance of wetlandresources and their evaluation; the third presents the most relevant characteristics of the Sonorancoast and the study area.

2.1. Assessment of Land Resources. Studies of land resources for planning and managementpurposes are abundant, and vary in purpose, scale and methods. While theyuse different data sources, they all include some kind of spatial information, suchas historical maps or remotely sensed imagery such as aerial photography, satellite imagery,or a magnetic media (i.e. videography).

2.1.1. Land use. A frequent approach to the assessment of landresources is to study the uses of land. Land use is determined by environmental factors suchas soil characteristics, climate, topography, and vegetation, and also reflects the importance of landas a fundamental factor of production. Thus, understandingpast changes in land use and projecting future land-use trajectories requires understanding the interactions of the basic human forcesthat motivate production and consumption. Certain landuses such as industrial development and residential areas, or commercialzones and open space areas, may present a conflict when their objectives are not compatible. Land use planning offers processes and techniques for the establishment of measures that allow different land uses to coexist by developing standards suchas buffer zones or regulating residential densities. Land use planning is being usedas the basis for the planning process in various countries; however, its degree ofeffectiveness is 10

dependent on various factors, suchas government commitment, comprehensive laws, enforcement means, and zoning standards. It is important to consider the environmental, geopolitical, and cultural characteristics of an area for its application to be successful (Sorensen et al, 1984). Land use is a resource base activity that is constantly experiencing change. The accurate monitoring of land use changes and trends is essential to meeting all levels of land resource management needs (Parker, 1979). Variations in population growth and consumer demand combine with varied land-tenure arrangements, degrees ofaccess to financial capital, shifts in international trading patterns, and local inheritance lawsand customs to produce unique land uses in different places and times. Evaluating thecauses and consequences of changes in landuse and land cover is becoming an urgent need to manage land resources (Turner et al, 1993).

2.1.2. Land Use Change. The strong interest in land use and landcover results from their direct relationship to many of the planet's fundamental characteristics andprocesses, including the productivity of the land, the diversity of plant and animal species, and thebiochemical and hydrological cycles. Land cover is continually molded and transformed byland use due to human cultural, social, and economic activities (CIESIN,1995). Although development activitiesare recognized as a dominant force in global environmental change (CIESIN, 1995),causes of land degradation can include natural hazards, population change, marginality,poverty, land ownership problems, political instability, economic and social issues, health problems, and inappropriateagriculture practices (Barrow, 1994). Thus, the destruction of forestedareas has been identified as a contributing factor to climate change anda leading factor in the loss of biological diversity, and overgrazing and other agricultural practicesare causes of land degradation and desertification in some developing countries (McNeeleyet al, 1990). This dual role of humanity in both contributing to thecauses and experiencing the effects of global changeprocesses emphasizes the need for better understanding of the interaction between humans and the environment. Thisunderstanding becomes more 11

imperative as changes in land use becomemore rapid, so emphasis should be made on the pursuit of knowledge of the driving forces behind land-use changes. The development of models to simulate these changesare essential to predicting the effects of global environmental change (CIE SIN, 1995). Considerable activity in programs to detect landuse change is underway in a number of countries such as Canada (Bryant and Russwurm, 1983) and the U.S. (Vesterby, 1987), but much of it relates to estimating land andresource distribution at a particular point in time, rather thanas support for monitoring programs. The focus of a particular monitoring program on landuse change itself, should include land use change detection in a periodical fashion (Bryant and Russwurm, 1983; Cochran, 1963). Turner et al (1993) pointed out that it is not possible to understand the significance of land-cover changes for climate, biogeochemistry,or ecological complexity, without additional information on landuse. They suggest that most land-cover change is now driven by human use and that landuse has major direct effects on environmental processes and systems. Changes in land use are assessed by comparison of different dates of aerial photographs, satellite imagery,or a combination of these information sources. However, change analysis is not limited to these visual datasources (Parker, 1979), other tabular data, such as census of agriculture for differentyears, can suggest regional changes. Use of different data sourcescan produce discrepancies that could affect interpretation and analysis (Monmonier, 1991). However,use of different times for comparison allows the identification of developmentpatterns that supports a better understanding of land use dynamics (L.U.M.D. 1980). Inany case, an important consideration is how land uses are assignedto a certain class, when working at certain scale. This is done through the application ofa land use classification system.

2.1.3. Land Use Classification. In practice, land classification assigns each land unitor tract of land in an area to a class in a system of classes. The classes in thesystem are defined in terms of the qualities, characteristics, or specific criteria with which the classification isconcerned. Two basic 12

classification approaches have been identified: the taxonomic approach, which establishes land units by grouping sites with similar properties; and the regional approach, which subdivides land into natural units on the basis of separate patterns that affectresource use and natural processes (Jackson, 1984). A useful land use classification approach would beone that considers the specific definition of the minimum parcel size for each category, with reasonableaccuracy, and at the same time, allows enough categories for identificationamong the major land use activities and the different phases of development (Jackson, 1984). For thispurpose, Bryant and Russwurm (1983) suggest the importance of classification methods that involve detailed descriptions of vegetation types, individual species, densityclasses, age classes, size classes, and complex plant associations. According to Jackson (1984), land classification activities have traditionally been grouped into five major categories in terms of: Inherent characteristics; Present use; Use capabilities; Recommended use; and, Program effectuation.

A classification of landscape basedon natural qualities, implies a more or less specific rating of quality or value. Assignment and discriminationare involved, rather than a mere list of facts. This deliberate effort to establish criteria upon which utilization of land depends, is at the level ofan inherent classification type, and is just the first step along a complex process of land planning andmanagement. A classification of land capabilities, will develop information that is importantto policy formulation and land management programs(Jackson, 1984). Land use classification systems have been designed to classify landuse through remote sensing techniques (Anderson et al, 1976). The landuse classification chosen is an important element in the evaluation of landuse change studies; classifications must be general enough to be applicable to largeareas, yet specific enough to recognize local variability. New classification systemsare needed to reflect more meaningfully the 13 dynamics of the patterns of land use change and the associated impacts on resource production and costs to society (Pease, 1991). Parker (1979) notes that land use classes are very important because they determine the amount of detail that is interpreted and compared, and therefore dictate the maximum amount of analysis that is undertaken. He mentions that two basic approaches are used when determining land classification; the first is to choose groupings or classes that are most useful to the local planner andresource manager needs, while the second is to base the classes upon sensor capabilities without regard to specific local utility. A combination of these two approaches constitutes a third approach. Studies can be focused at one point in time or they can look at changes through time, such as agricultural developmentor the loss of agricultural areas to urban expansion (Tiner, 1984; McCuaig and Manning, 1982). However,an inventory at a specific time may not provide full understanding of the resource and land use dynamics. Pease et al (1990), proposed as another approach, theuse of the Land Use Change Index (or LUCID method), which is basedon a classification of land use patterns instead of specific uses. They proposed that the identification of patterns will allow understanding of land use dynamics and its relatedprocesses.

2.1.4. Monitoring of Land Use Change and the Process of Land Use Planning. Monitoring land use change involves identification ofcauses, localities, and rates of change. These studies range from the simple classification of landuse cover to quantitative studies of estimated rates of landuse conversion. Land use change studies within the planning process have provided the basis for the establishmentof formal protective designations to prevent urban and industrial developments from encroaching into ecologically sensitiveareas (Bryant and Russwurm, 1983; Frazier and Shovic, 1980; Rosenfield, 1982).

The importance of land use change studies tosupport decisions on land use allocation and regulation, has been extensively documented (Bryant,1986). Bryant and Le Drew (1989) have divided these studies into threetypes: descriptive, explicative, and prescriptive. 14

Descriptive refers to studies involving land use/land cover inventories, sometimes including ecological and cultural conditions. Explicative refers to understanding the process of land use change. Analysis of cause-effect is emphasized, including cultural values and attitudes, regional elements, and ecological and related economic issues. The dynamics of land use change may then be defined. Prescriptivethe more complex, expensive, and, therefore, less frequently done type of land use change study. It involves the above considerations and suggests alternative scenarios, describing the land use policy changes required if certain objectives are to be attained. The compilation of comprehensive informationon land use change in qualitative and quantitative terms has been used topreserve ecologically sensitive areas, such as wetlands (Kiraly et al, 1990). These data allow fora more rational planning of uses in terms of location, densities, and development types. By focusing on which activitiesare compatible with sensitive habitats and their surroundings, local economic and social needs, such as identifying zones for expansion of residentialareas, and commercial or industrial development, can be planned while maintaining critical ecologicalprocesses (ONERN, 1992).

As stated before, in landuse change studies, the purpose is not necessarily to have an inventory of current land use, but to determine specific land use changes; therefore, two or more time periods rather than one are employed (Lee, 1979).

2.1.5. Changes of Coastal Wetlands in Sonora and Land Use. Land use mapping has a short history in Sonora; experience with information sources such as census, air photo, and field surveys, is relatively new (POET, 1994). The National Institute of Statistics, Geography and Computerized Data (INEGI) didland use surveys called SINFA (National System of Inventory by Aerial Photography) in 1991- 1993, for small portions of the coast (INEGI, 1995). Othersurveys with a special purpose have been developed; for example,a land use study for the Soldado estuary (CIDESON, 1994; Ecodesarrollo, 1993) and the coastal wetlandassessment of the Southern Sonoran 15

(Valdes et al, 1994) have been completed. Landuse / land cover maps are still available only in a small scale format (1:250,000); thereforea satisfactory land use inventory and monitoring program is still needed. Changes in coastal wetlands related to human activities, and how theyare represented in some classification system, would constitute only one approach to identify human / wetland interactions. Other meaningful considerationsare the nature of the processes underlying the wetland changes and the policies promoting human activities which may cause change (ONERN, 1992; Pease, 1991).

2.2. Wetland Assessment. "Wetlands are not wastelands, but wonderlands" (Wisconsin Coastal Management Council, undated) 2.2.1. Wetlands as Critical Habitat. Wetlands are shallow water systems, or areas where water is ator near the surface for some time. They contain plants adaptedto flooding as well as hydric soils, and can be found in diverse topographical settings. They arise in flat, tidally inundatedbut protected areas, such as salt marshes and mangrove swamps. Wetlands exist next to freshwater rivers, streams, and lakes. Some are formed in surface depressions; such wetlandsinclude freshwater marshes, potholes, meadows, and pools with woody andnon-woody vegetation. Wetlands can also flourish on slopes andat the base of slopes, supplied by springs, and as bogs and fens fed by precipitation and groundwater.They can occur in cold climates where permafrost retainswater and low evaporation rates prevail (Kusler et al, 1994).

The importance of wetlands is slowly comingto people's mind (Barrow, 1994). Wetland losses in the United States have been estimatedat more than 50% of the original wetland area (Dahl and Johnson, 1991). In Central and South America,development pressures along the coastal zone causing habitat losses have attracted attention to the need for effective management strategies (Bildsteinet al, 1991), although losses have not been quantified for most areas. 16

Diversion of upstream river waters for construction of dams for hydroelectric generation, flood control, or irrigation supply are increasingly altering natural river flows and threaten the viability of downstream wetlands (Barrow, 1994). According to Barrow (1994), the main cause for wetland loss in the USA andmost of the world has been, directly and indirectly, agricultural related activities: directloss from clearing and draining, and indirect loss because of contamination ofwetlands with agrochemicals such as pesticides and fertilizers, and highly mineralcontent surplus irrigation water. These pollutantscan affect wetlands at great distances from their points of release. Since wetlands tend to be at the lowest point they accumulatepolluted water from a drainage basins. On the other hand, extensiveuse of agrochemicals and competing uses of water, suggest the lost of potentially sustainable agricultural systems. This situation leads to a double degradation: the wetland would be degraded,and the potential for developing intensive, sustainable food and commodity productionstrategies would be wrecked (Barrow, 1994).

2.2.2. International Importance. There are many examples throughout the world of wetland degradation dueto agricultural practices and waste products. In Asia, the majority of wetlandshave been managed under rice cultivation. Inland, innumerable smaller freshwatermarshes and swamps have been filled, drained, or reduced in size as farmers have expanded their operations (Barbier, 1993).

Despite their extent and significance, wetlands have almost universallybeen regarded as wastelands. Only recently hasa wetland conservation movement arisen (World Wildlife Fund, 1992).

The total area and status of tropical wetlandsare still unknown, but the available evidence suggests that the pattern of wetland conversion indeveloping countries may be similar to that of the United States, and perhaps proceedingat even a faster rate in some regions (Barbier, 1993). In Latin America, conversion ofmangroves and other wetlands into cultivation and grasslands has been a common practice for centuries (Suman, 1994).However, these 17 changes have been accelerated in recentyears. In the Caribbean Islands (Puerto Rico, Dominican Republic, and Cuba) the agricultural frontier has been extended intomangrove areas, especially with cane plantations. In Mexico and Central America a great proportion of the conversion has been into grazing lands. In Ecuador,mangroves have been transformed into coconut palm plantations, and aquaculture ponds (Bodero, 1994); in Honduras, construction of shrimp farms and saltworks have increased in the last fifteen years (Oyuela, 1994). In general, wetlands can change rapidly if there isany alteration in input water, sediment, or outflow. It is estimated that, globally, there has beena 50% loss of wetlands since 1900 (Williams, 1993). Asummary of the main causes of damage to wetlands is presented in Table 2.1:

Table 2.1. Summary of the maincauses of wetland degradation (Barrow, 1994).

Disruption of water supply. Drainage of water saturated areas. Pollution by agrochetnicals, industrial effluent, andsewage. Acid deposition. Introduction of invasive plants and animals. Reduction of rainfall or river flows by climatic change. Sea level changes or tectonic movement. Disturbance of wetland environment by human exploitation.

Coastal wetlands are consideredone of the more productive ecosystems. They not only are important for the localecosystem where they occur, but also for ecosystems elsewhere through the migratory species theysupport (Field et al, 1991). In tropical and subtropical regions,mangroves represent an important component because of their ecological role of producing organicmatter, and as habitat for both aquatic and terrestrial fauna. Mangrovesare valuable for coastal protection against waves and storms and as areas where fish, shellfish, andcrustaceans feed and breed. They are 18 important refuges for other wildlife, and so have a valueas genetic reserves. Plants in mangrove swamps include salt-resistant species which may have economic values if domesticated as crops for areas where there is a poor fresh water supply. Mangrovesare traditionally exploited for charcoal, tan-bark, building timber, and other products (Hodgson and Dixon, 1988; Snedaker and Getter, 1984). Mangrove wood isvery resistant to insects and is popular for the construction of rural housing in central American countries, especially Honduras, Guatemala and El Salvador (Suman, 1994). However,so far, there has been little or no attempt to improveany mangrove species for timber or other production, and little deliberate planting; their importance is being undervalued (Barrow, 1994).

Other halophytes important for human uses are different species ofgrasses, including the salt grass (Distichlis spp.) and the Salicorniaspp., which although they have been shown to have economic benefits,are under-utilized because they are still seen as experimental farms (Clark, 1994; Araiza, 1988).

2.2.3. Wetlands' Functions and Values: from Inventories to Wetland Management.

"The real need in conservation is the protection of those commodities like solitude and sunsets which your assign machine may tell you are economically valueless but which your heart tells you are beyond price" Luna Leopold (Cited by Wisconsin Coastal Management Council, undated)

Detailed wetland inventories have increasedas wetland protection is included within environmental agendas in different countries. These actions have beeninfluenced by a wider recognition of wetlands' functions and values. Theyare important habitats and integral parts of the hydrologic systemnecessary for the maintenance of water supplies and water quality (Marsh, 1991). Knowledge of wetland functional attributes has been definedas a prerequisite for the establishment of wise management activities (Eargle, 1991).Assessing wetland functions and values is becominga formal procedure in establishing guidelines for 19

development; however, there is much to do yet, because there are no standard procedures for the assessment of wetland functions. Development of most assessment methods in the past fifteen years has resulted from adaptation of methods originally designed for uplandor aquatic ecosystems, although some were designed specifically for wetland ecosystems (Smith, 1993). Two

frequently used procedures in the United States are the Wetland Evaluation Technique- WET (Adamus et al, 1987a,b; Adamus and Stockwell, 1983), and the Habitat Evaluation Procedures- REP (U.S. Fish Wild. Serv, 1980). Smith (1993) points out that these procedures are still limited in their application for regulatoryprograms in United States, when considering the large number of permits reviewed nationallyevery year. There are other procedures that focus on different objectives at stateor regional levels (Wells, 1988), or on specific environmental indicators, suchas hydrological and geomorphic properties (Brinson, 1993). A consideration of which functional evaluation procedure should be used will benefit from a review of objectives, extent ofarea for evaluation, and budgetary and time constraints. Discussionon wetland assessment are presented in World Wildlife Fund (1992) and Smith (1993). "Assessing the functions of wetlands providesa means for comparing the ability of two wetlands, separate in space or time, to perform specific functions. However, it does not provide a means for comparing the value of the functions performed by the wetland with the value of other public interest factors considered during the public interest review." (Smith, 1993). The economic value of wetlands has been recently given recognition. Like other natural assets which yield a flow of services, theyare considered valuable by society. Economic evaluation methods include direct-use values suchas consumptive (recreational and commercial fishermen and wildlife hunters) and non-consumptive (photographyand wildlife viewing), and indirect-use values suchas non-use or passive-use values (option value, existence value, and bequest value) (Wellman, 1995; McNeely, 1990). Valuing a wetland essentially means valuing the characteristics ofa system. Barbier (1993) presents a complete discussionon economic applications when valuing wetlands. He establishes that too often the decisionas to whether to overexploit or 20

convert tropical wetlands is taken arbitrarily, without consideration of the loss of any benefits that they may provide. As a result, the costs of such decisions only become apparent after they are carried out, often with irreversible consequences; furthermore, they are borne by those in developing economies who can least afford it.Therefore, before decisions are made, appraisal methodologiesare required for evaluating the alternative options for development. Policies like the "No-Net-Loss" policy in the United States forced planners to include procedures to try to maintaina balanced equation of economic development and wetland conservation, allowing development in wetlands tooccur only if certain functions and values were "replaced." Apparently, there has not been sufficient time forproven results, as stated below: "It is commonly assumed that wetland lossescan be mitigated by restoring or creating wetlands of equal value. Some feel that replication is not always necessary if certain functionsare replaced; others, including most wetland scientists, recognize that duplication is impossible and simulation is improbable. All would agree that we need substantially more information about what functions are being lost and how to replace them." (Zedler and Weller, 1990). Other considerations to the "replacement" approach,are how to select a "natural wetland" to be used as a reference tomeasure gradual success, and the replacement costs, which often are under estimated because of our inabilityto assess all ecosystem functions (Barbier, 1993). Therefore we can only replace whatwe can measure, and even with this potential reduction of functions, the replacement costsare high, especially when those functions were basically "free" with natural wetlands.

2.2.4. Wetlands in Mexico. Protection of wetlands in Mexico is limited by the absence of statewide wetland inventories. Some of the few available inventories for Mexico include theNeotropical Region Wetland Inventory (Derek and Carbonell, 1986); the PriorityWetlands and Protected Natural Areas Map, developed by SEDESOL and ConservationInternational with the support of the North America Wetland Conservation Council (CI-NAWCC- 21

USFWS-SEDESOL, 1992); and a few other publications (Olmsted, 1993; Lot and Novelo, 1990; Lot et al, 1993). Lack of knowledge on wetland conditions and wetland loss in Mexicosuggests the need to establish methods to gather and organize data ina usable format, in order to define alternative management strategies, including policies relatedto the different land uses that might be related to wetland modifications. In this context, land use planning offers regulatory tools for guiding development (SEDUE, 1990). The distribution of wetlands in Mexico formsa mosaic of habitats because of diverse ecological regions, complex topography, and geographical location withintwo bioregions: the Nearctic and Neotropical (Conservation International, 1989).Mexico is among the ten countries in the world with largest biodiversity, containinga number of species that establishes the countryas the first in reptile species, the second in mammals, and the fourth in amphibians and in angiosperms (Mc Neelyet al, 1990). Wetlands in Mexico are the southernmost destination for winteringsome migratory birds in North America, and giveyear long support for resident fauna. Conservation International (McNeely et al, 1990) reported that Mexico has nearly30 percent more bird species (1010) than the U.S. and Canada together, and is by far the most important wintering area for many U.S. and Canadian migratory bird species. Mexico hosts 51 percent of all migratory bird species from NorthAmerica every year; these birds spend from six to nine months of their lives in Mexico. Although continental wetlands are important, they havemore limited distribution, being associated with lakes, reservoirs and riversystems (Olmsted, 1993). On the other hand, coastal wetlands are distributed throughout Mexican coastalplains, mainly in the central Pacific, South, East and Southeast coasts (Lotet al, 1993). Changes in economic development policy in the previous Presidentialperiod translated into growth of coastal tourism, oil andgas development, expansion of agricultural areas, and urban infrastructure. These changes have increasedthe development pressure on wetlands (Yariez-Arancibiaet al, 1994; Cervantes et al, 1992; Escofet et al, 1989). 22

Increasing urban, industrial, commercial, and tourist land requirementsmean that more land will be taken out of wetlands. In Mexico, development in and around wetlands as a result of larger numbers of people competing for wetland resources, gives way to social conflicts and resource depletion. In fact, with more developmentalpressures on the coastal zone of Mexico, incompatibilities will continue toemerge (Chavez, 1984; Merino, 1987; Tordesillas and Brener, 1993; Cervantes et al, 1992).

2.3. The Sonoran Coastal Zone. Many aspects of the Sonoran desert have fascinated researchers and have been described in the literature, including the native Seris, Yaquis and Mayos, the plant and animal communities in the ever changing seasonal colors of the desert, and the diversity of coastal waters in the Sea of Cortez (Felger and Moser, 1991; Shreve and Wiggins,1964; Gentry, 1942). This region has been suggestedas one of the richest marine and coastal ecosystems, both in terms of biomass and biodiversity (Case and Cody, 1983; Brusca, 1983; Bourillon et al, 1988).

"The Sonoran Desert Region is by far the richest in number of life formsand in variety and development of communities of all the north American deserts." (Shreve, cited by Walter, 1991).

The Sonoran coastal zone includes importantresources such as sand beaches, active sand dunes, and areas where dunesare stabilized by low scrubs and grasses (Johnson, 1982; Brown, 1982). The vegetationcover has a myriad of species including grasses, shrubs, low trees, and many kinds of Cacti, such as the tall columnar varieties,as well as several types of centurion plants,or agaves (Walter, 1991). A distinctive characteristic is thepresence of other groups of halophytes (plants tolerant to saline conditions), that includemangrove communities, saltgrasses, and seagrasses. Mangroves are an important component of the vegetation communities in the southern Sonora Coast (Rzedowsky, 1988). These communities havedecreased due to land use change, specifically openingmore areas for agriculture and grazing (COTECOCA, 1974). 23

'Mangroves of the Gulf of Californiaare always stunted, rarely attaining heights over 2.5m, in contrast to the 10m giants ofmore equatorward shores. This stunted growth form has been said (in other subtropical regions) to reflect local climatic and physical conditions. They have been referred to as scrub mangrove systems. The Gulf of Californiamangrove esteros appear to be extremely productive regions that serve as highly efficient detritus and nutrient traps." (Brusca, 1983).

Along the Southern coast of Sonora, there isa series of semi-enclosed bodies of water which are of substantial biological importance and geomorphic significance (Figure 1) (Valdes et al 1994). The Yaqui and Mayo rivers have built extensive deltasnear the coast, forming wide natural levees, once cultivated by aborigines in pre-Spanish times(Walter, 1991). Today Sonora's landscapes reflect the integration of the varied activities thathave evolved from local cultural development, withina framework of strong government incentives for agricultural production and market control. These lands havesuffered from change and intensified use by agriculture, aquaculture, extractive industry(mostly natural salt), and, in the last 10 years, by tourism. Although these landuse changes were responses to development needs, they are not always desirable froman ecological and sociocultural point of view.

Of all changes on the coast, river basins have shown themost alterations since the beginning of the twentieth century. Modern rivers in thelowlands of Sonora have been reshaped in the form of irrigation canals and drainage ditches (Walter, 1991).Agricultural programs of the state have received strong government support in the form of irrigation and extensive use of agrochemicals, with littleconcern about the environmental consequences, until recently (PEF, 1984).

2.3.1. Development of Southern Sonora Coast and the WaterDilemma.

"The history of Sonora under Mexican rule isone of caudillos, of technocrats, and of foreign investors, all grappling with the problems of economic modernization and political stability." (McGuire, 1986). 24

The Sonora coastal plain was inhabited by the Yaqui and Mayo Tribes since before the Spanish conquest, and, despitesome efforts for colonization and evangelization, for centuries it remained almost untouched by western civilization (Walter, 1991). Towards the end of the 19th century, land speculation and social conflicts, mainly withthe Yaqui community, set the stage for foreign investors to acquire land (McGuire, 1986). It was at the turn of the last century, in 1890, whena Mexican entrepreneur, Mr. Carlos Connat obtained a concession from the federal government to irrigate andcolonize 300,000 hectares (from now on: ha) of land distributedat both sides of the Fuerte, Mayo and Yaqui rivers. For that purpose the Sonora and Sinaloa Irrigation Companywas created in New York, mainly with American investment. Irrigation works begun,and within 10 years they constructed 40 km of the main canal, anda diversion dam, achieving 15,000 ha of irrigated land. Because ofa big flood, in 1902 the company declared bankruptcy and paid its creditors with land (Walter, 1991). In 1905 another company obtained the rights for development,Constructora Richardson S.A., continued work and constructedtwo more canals which added 40,000 ha suitable for agriculture. At thesame time, the government established a scientific commission to develop an irrigation system in the northern portion of the valley (Dela Pella, undated).

In 1928 the government forced the Constructora Richardsonto sell, and the land was turned over to the Banco Nacional de Credit() Agricola, S.A. (National Bank for Agricultural Credit). Later, Irrigadora del Yaqui, S.A., gained control ofland development (Walter, 1991).

In 1941, there was a second extension to the main canal and the LizaroCardenas Dam was constructed, resulting in 75,000 ha of arable land,and by 1943 another 35,000 ha were suitable for agriculture. During the 50's and60's the government constructed two more dams (Alvaro Obregon and Plutarco Elias Calles), and irrigation canalsto create what today is known as the largest agricultural valley in Sonora,and together with the Mayo valley, the most important in thecountry. This area came to be known as "the barn of Mexico" (Dabdoub, 1995; Walter, 1991). 25

The limiting factor for development in the southern Sonora coastal plains has always been the availability of water. Its allocation was centered on agriculture, which for a long time has been the main economic activity. Thus, the main use of water in Sonora is agricultural, claiming 97% of the total extraction. About 4.5 million cubic meters ofwater are used annually to irrigate the 11 districts (CNA, 1990). Efficiency of water transfer is around 69%, losing 2 million cubic meters of water which is either filtered into the ground water, evaporated, or discharged "unused" into coastal waters. This water loss is a consequence of the lack of maintenance of infrastructure, poorly laid out irrigated land, and lack of programs for reutilization (CNA, 1990). The loss represents real economic impacts because of the energy and structures needed to divert andstore water. As in other parts of the world, effects of water scarcity andover- exploitation are predictable and are already noticeable insome areas where excess of salt in soils because of strong evaporation rates, have forced them to be abandoned. Nevertheless, expansion of irrigated acreage is expected to continue. In other regions, suchas in the Guaymas valley, with over 85,000 ha of mostly irrigated agriculture (INEGI, 1993), land qualityand total agricultural area is decreasing because of overdraft of groundwater, uneconomical conditions, and loss of water supplies due to competingusers. Other activities, like residential development, tourism, and industrial development will continueto challenge agricultural activities for water demand,a situation that will require the identification of alternative techniques for water reutilization and efficiency inwater distribution.

2.4. The Tobari System, a Geographic Setting. The area selected for this research is the Tobarisystem, in the Yaqui and Mayo Valleys of the state of Sonora, Mexico. Itwas chosen because of the proximity of human activities to wetland systems (CNA, 1988). The Tobari System, sometimes called Bahia Tobari, Estero Huivulai,or Tobari- Siaric Complex, is one of the elevenmost important coastal wetlands in Southern Sonora because of its size and itsresources (Valdes et al, 1994). The Tobari System is located within a region called "the Central Gulf' (Bourillonet al, 1988) and it is within the physiographic region of the Gulf of California Coastal Plain (Garciay Falcon, 1993). It is 26 characterized by flat plains varying in width and originated from river discharges. It is located 40 kilometers south of Ciudad Obregon, within the municipalities of Cajeme and Etchojoa (SCT, 1994), with a geographicalrange of 26°54' to 27°10' North and 109°50' to 110°24' West (Figure 2.1). It is a complex coastal lagoon containing 15 small estuaries and little bays, among them, Jiamora, Pitahaya, Conchalito, Diablo, El Sian iy Cubuja, (INEGI, 1982). The System covers anarea of 8,274 ha. The main water body is approximately 20 kilometers long andan average width of 4 kilometers. The shallow estuarine waters supportan important year round fish and shrimp fishery. During the first two weeks of the shrimpseason, fishing intensity increases as commercial fishermen arrive from different parts of Sonora and Sinaloa, and nearlyclear out the shrimp within the estuary (Wood, 1995). These waters alsosupport two shrimp farms. Aquaculture projects formore shrimp and oyster farms are being developed. The Tobari system includes the outstanding Huivulai barrier island, with complex active sand dunes and related coastal plains. This islandprotects the wetland system, is 12 kilometers long and covers an area of approximately 900 ha. The island formstwo mouths: the south mouth (800 m) is themore dynamic and wider; the north mouth (600 m) has a sedimentation pattern, causing less water exchange withinthe tidal cycles. In 1963 a road was filled in, joining the island with land, for thepurpose of developing a tourism and recreational area inone part of the island. Weekend houses were to be built, and a cattle ranch operationwas to be established (Figures 2.2 and 2.3) (Anonymous, 1993).

The Government of Sonora issueda decree to establish the island as a wildlife refuge (B.O.S., 1983); however landowners appealed and won against the state government, by arguing that this area was one of federal jurisdiction. Thereare still legal debates among the group of owners that claim portions of the island and itsresources. As a result of road construction, with a bridge only 10 meters long and 4 kilometers of fill, lack of water and sediment exchange has causedsedimentation patterns to transform the system into two semi-independent subsystems (D.F.P. 1982). 27

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LT=

Figure 23. Access Road to Heivulai Island, 29

There are 13 ditches draining into the system. Some of themwere built using ancient river causeways from the Yaqui river, sometimes called river branches. These ditches are collectors of waste waters from the irrigated agricultural lands,and some carry waste water from industrial and urban discharges. Some of these canals contain freshwater wetland emergent vegetation, suchas cattail (Valdes et al, 1994). Marine effects are important to the system because of the tidal influence and upwelling events during winter and spring, providing thenecessary nutrients for a high biological productivity. Tides are semidiurnal providing flood tides in tidal channelsevery 12 hours, with a tidal range of 1.3 meters (Gilmartin and Revelante, 1978;D.F.P., 1982). The coast absorbs most of the tidalenergy, resulting in different geomorphic conditions along the coastline, with some modifications because of the irrigationpatterns and waste water discharges.

2.4.1. Climate. The Tobari system is considered part of the climaticzone of the Sonoran Desert, which includes the Baja California peninsula anda portion of the state of Sonora State and U.S. state of Arizona (Schmidt, 1989). The climate is dry desertic for themeteorological station at Villa Juarez, which is the locality centered East of thesystem. It has an average annual temperature of 23.6°C, ranging between 17.4°C (January)and 29.5°C (July- August), and extreme cold temperatures ranging between 7°C and14°C (Garcia, 1988) (Figure 2.4). The region has an annual precipitation of 259 millimeters(Figure 2.4). It has summer rains with 10.2% of winter rain (Garcia, 1988).

2.4.2 Hydrology. The Yaqui Valley is a coastal plain of approximately 400,000 ha.It takes its name from the Yaqui River, whichruns through the plain from the uplands in the mountain range of Sonora and Chihuahua.

"The Yaqui River Basin is the most important aquaticsystem for the economy of the State of Sonora. This watershed occupies 30 percent of the state. It is a complex system of sub-basins, of which the lower basin is 30

particularly important for irrigation of crops...The Yaqui River watershed has been transformed to accommodate human needs, including irrigation, electricity, diversion for mineral and cattle production, and sport fishing...in the region there are three major reservoirs: La Angostura in Northern Sonora, El Novillo in the center of the state, and Alvaro Obregon to the South." (Abarca et al, 1995).

0 May Jun Jul Aug Sep Oct Nor Dec Hindu

Figure 2.4. Climogram of Villa Juarez Data (Garcia, 1988).

The Tobari system received the fresh water from the Yaqui and Cocoraque rivers in the northern portion, where accordingto De Negri (1928), the flooded area was more extended. This are is now considered within the hydrologic region No.9 "South of Sonora," having the influence of the Mayo basin in the South. The Cocoraquestream (INEGI 1993) was a small basin between the Yaqui and Mayo basins,provided seasonal fresh water to the system. Today, this small basin is completely modifiedby the Irrigation District No. 41 "Yaqui Valley," because of construction of dams anddiversion canals (SARH, 1970; Gonzalez, 1993). Today, the freshwater sources to the systemare from the 13 ditches, which also carry waste water discharges from the other activities in the region, suchas aquaculture, 31

industry, urban centers, and residual waters from irrigated agricultural lands. Thewater thus contains fertilizers, herbicides, heavy metals, anda high content of organic matter and sediments (B.O.S., 1983). It has been estimated that theaverage annual discharge in millions of cubic meters from the largest ditchesare, 17,569 in the center, 26,048 in the south (Las Mayas), and 44,964 in the north (Celis, 1992).

2.4.3. Geology, Geomorphology, and Soils. The river deltas created the coastal lagoon, whichnow is shallower because of sedimentation patterns, and has anaverage depth of less than two meters (Figure 2.1).It is considered a coastal lagoon with two mouths, resulting from differentgeomorphic processes, such as tidal erosion and marine currents (Ortiz and Espinosa, 1991). Sediments are reported from the quaternary (INEGI, 1990). Lankford (1977) considered the Tobarias one of the 22 coastal lagoons in the state of Sonora. The Tobari is characterized by the barrier island and the river discharges. Sedimentation patterns are influencedmore at the mouths by coastal erosion from tides and currents, and in the more internalareas by ditch discharges (Cabrera, 1975). Soils within the study areaare characterized by their high fertility, especially those within the floodplains. However, with the transformation of land foryear-round irrigated agriculture and control of floods by dams, soil nutrientsare complemented with agrochemicals. Soils in the alluvial plains originate by river floods; thusgood soils are present in the delta areas of the Yaqui, Cocoraque and Mayo rivers, however salinity increases closer to the coast (SRH, 1970).

2.4.4. Human Activities. There are three main communitiesnear the Tobari wetland system: Pared6n Colorado, El Paredoncito, and Paredon Colorado Subey Baja, with 1,633, 1,328 and 299 inhabitants respectively. Within the system thereare two shrimp farms, occupying 95 ha and 88 ha (Figure 2.1). Bothare semi-intensive farms, taking their water from the wetland system using a main channel or "calling channel," to fill the different tanks,then discharging waste waters into the system using another canalor "exit canal." 32

2.4.4.1. Mining. Another important economic activity is salt mining. There are two active saltworks, one at the northwest of the Jiamora estuary, anda second one just north of the ParedOn Colorado Town. Before the government allowed private investorsto register and establish a business enterprise for shrimp production, therewas a plan to establish a chain of saltwork projects along the north portion of the coast. Therewere already six permits for that portion, and one on the other end (SEMIP, 1994). However,now the emphasis is for shrimp farming development,so not all the permits for saltwork operated.

2.4.4.2. Tourism and Hunting. Huivulai Island is the main area for tourism and outdoor recreation. It contains natural attractions such as a long beach with palapas (palm leaf coveredshade structures), the systems of sand dunes in the center, anda freshwater well in the northern portion of the island.

Hunting takes place in almost all of the system, but mainly in the smallestuaries, using small flat boats. Hunting clubs from Ciudad Obregon takeMexican and foreign duck hunters during the winterseason (December-February). Often, these groups hunt in the agricultural areas and ditches, especially closeto the wheat crops.

2.4.4.3. Fishing. Two fishing communitiesare established at the central portion of the system, Pared6n Colorado and Paredoncito (Figure 2.1). Seasonal shrimpand oyster camps are located near the north and south mouths.

The shrimp cooperatives, and overall fishing activitiesare controlled by the fishing agency at Federal government level, under the Fisheries Subsecretariat,now within the Secretariat of the Environment, Natural Resources and Fisheries(SEMARNAP). Both communities focus on shrimp during thevery short season; they also fish for scale fish, shark, snail, and blue crabs, inan effort to diversify their operation. They have an ice- making plant and modest fish processing facilities. Asummary of human activities in the Tobari System is presented in Figure 2.5. . -1\ N Human Actiities in the Tobari System 710.. IL I, fa IMp Area- (Sea of Cortez) ..nmx ,a10. et aJ. la/ PrelosaL Gulf of California Figure 2 5 Human Setlements Aquaculture Area Agriculture Area Paved Roads Rural Roads. Ditch of Septaabor 1990 Carl o. Valdeis Geosciences Department TObari System Hunting, Oyster Farm Saltworks. Recreation, Fisheries Human Activities Map 34

2.5. Environmental issues in the Tobari System.

In Sonora, water pollution comes from three main sources: urban run-off and sewage, drains from rural agricultural areas, and industrial and mining waste waters. The Tobari wetland system is situated in the highly productive and highly disturbed Yaqui, Cocoraque and Mayo agricultural valleys, and is the recipient of 13 ditches thatcarry urban, industrial, and agricultural waste waters (Figure 2.1) (SRH, 1970). The biggest discharges come from the rural drains, witha high concentration of agrochemicals and waste water from animal farms (hogs, cattle and chicken) (Rice, 1995). The ecological alterations caused by this waste water discharge remain unassessed and unquantified in

detail; however, several studies have shown high pollutant concentrations, in groundand surface waters, in ditches and estuaries (Gonzalez, 1993; Gonzalez and Cordova, 1993; ITSON, 1993), and, in migratory and resident fauna (Mora and Anderson, 1991; SEDUE- Appisa, 1989). Of greaterconcern are data on human communities, where presence of DDT and other agrochemicals in lactant mothers have been identified (Garciaand Meza, 1991; Reyes, 1990).

According to Celis (1992), El Tobari isone of the most polluted systems on the coast of Sonora, and therefore with an urgent need for attention. In her study,water quality in El Tobari was found with bacterial values fargreater than the maximum standard allowed by the Mexican law, and therewas a low concentration of dissolved oxygen due to the waste water discharges. Thirteen of the eighteen drains from the Cajeme District (Yaqui Valley) flow into the Tobari System, dischargingan annual average of 208 millions of cubic meters of waste waters (CNA, 1988). The environmental consequences from irrigating agricultural land fall intotwo broad categories: water pollution and conservation ofwater and land resources. Water pollution is a major concern in irrigatedcrop production because of the generally intensive use of fertilizers and pesticides. Studies (Reganold, cited by Barrow, 1994), have shown that organic farms (abandonment of pesticides, herbicides and fertilizers),can be used very effectively with little or no negative environmental impact;yet under some conditions, extensive use of fertilizers can severely degrade the environment(Brown, 1991). Nitrate 35 leaching into ground water supplies has been documented (Aldrich, 1980),as well as the movement of nutrients off the land (Villa and Gortares, 1993). For the state of Sonora, there are 26 treatment plants for industrial wastewaters and 21 for urban sewage. From those 21, 19are oxidation lagoons and 2 are intake tanks. Re-use of treated waters is limited, mainly for forage irrigation, andsome for open space recreational "green" areas (SEDUE-Appisa, 1989). Today, the Tobari system as wellas all the southern portion of the Sonoran coast, is characterized by extreme poverty conditions in ruralareas, and most population centers have fragile economies dependenton agricultural related activities and fishing (Bravo, 1994; Camberos, 1994). In fact, this regionwas considered as one of the 15 poorest areas of the country, with high environmental problems, mainly because of pollutionfrom agricultural and animal farm related activities (Rice, 1995; Wonget al,_1995). 36

CHAPTER 3 RESEARCH DESIGN AND PROCEDURES

As stated in the introduction, the purposes of this researchare to (1) identify, describe, and analyze wetland conditions and human activities in the Tobarisystem and the changes that have occurred overa 18 year period, and (2) evaluate government policies that are affecting and/or promoting changes in wetlands. In this research, human/wetland interaction is evaluated by usingan assessment approach to identify measured changes.Historical aerial photographs are used as the main source of informationon human activities in the wetlands. Wetlands are classified according to Cowardin et al, (1979), to suggest ecological functions and thepotential human values they provide. Government environmental policiesare analyzed to identify contributing factors to wetland conditions and changes.

3.1. Procedural Model for Wetland Assessment. In order to identify the human/wetland interactions in theTobari system, inventories of wetlands and human activitiesas land use types are used for the analysis of wetland changes. The procedural model (Figure 1.2,page 7, Chapter 1) includes a wetland inventory for two differentyears (1973 and 1991), with its associated ecological functions and human values;a human activities inventory for the same different years, considering land uses and land coveras indicators of human activities; the integration of data into a geographic informationsystem (GIS); an identification of changes in wetlands and human activities; GIS analysis and display; and integrationof data by overlay for statistical analysis and identification of relationships betweenwetland change and human activities. The last part of the model identifiesgovernmental policies influencing human activities that affect wetland changes, in order tosuggest considerations for the sustainable use of wetlands. A summary of the detailed methodology is presented in Figure 3.1. 3 7

IInformation Gathering I

Photos (5) Photos (4) 1973 1991

Wetland Inventory

Land Use / Land Use Patterns ib li o g rap hy Inventory jB

Digitizing Wetland (Autocad 10) Functions GIS and Values Integration GIS Integration (Terrasoft 10.03) Change Analysis of Functions Statistical and Values 4--Georeferencing Correlation Terrasoft 10.03) (Excel 5.0) GIS Integration of Change in Functions/Values Map Integration Map Integration Land Use Wetland/Land UseWetland/Land Use Change Map 1973 1991 Identification of Government Policies

Map Overlay 1973 / 1991 Considerations for Sustainable Use of Wetlands

Figure 3.1. Flow Chart of Methods (Procedural Model in Detail). 38

3.2. Wetland Inventory / two Dates. Wetlands were identified through aerial photography interpretation techniques, applying the Cowardin et al (1979) (Table 3.1) wetland classification fortwo dates of available aerial photography. For this research, wetland distributionwas mapped and tabulated based on the class level, and is presented in Table 3.2. This isa simplified classification based on the types of wetlands found in the studyarea. Although the marine system with subtidal and intertidal subsystems were present, theywere not included in the analysis because of their general distribution and lack of differentiation;however, both subsystems are all along the coastline outside the estuarinesystem.

3.3. Wetland Functions and Values. Ecological functions of wetlands are well defined in published literature (Adamus and Stockwell, 1983; Adamus et al, 1987),as well as wetland values, which are recognized as the "services" they provide for society (The ConservationFoundation, 1988). Wetlands provide important economic and aesthetic values. Theyare used as natural filters for sewage discharges, aquaculture farms,open space areas for recreation, commercial fishing and sport hunting, salt mining, grazingareas, environmental education, and scientific research (The Conservation Foundation, 1988)(Table 3.3). After identifying wetland types, the wetland functions and valuespublished in literature are selected for analysis. This allows identification ofchanges in terms of wetland functions and values, determining their increaseor decrease for the period analyzed.

3.4. Land Uses and Land Use Patterns /two Dates. Pease et al (1990) suggesteda Land Use Change Index (LUCID) classification which considers remote sensing techniques for the identificationand analysis of established categories of development patterns. Theysuggest using eight land use pattern categories shown in Table 3.4. 39

Table 3.1. Classification of Wetlands and Deepwater Habitats (Cowardin et al, 1979).

System Subsystem Class

Marine Subtidal Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Reef Intertidal Aquatic Bed; Reef; Rocky Shore; Unconsolidated Shore.

Estuarine Subtidal Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Reef Intertidal Aquatic Bed; Reef; Streambed; Rocky Shore; Unconsolidated Shore; Emergent Wetland; Scrub-Shrub Wetland; Forested Wetland.

Riverine Tidal Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Streambed; Rocky Shore; Unconsolidated Shore; Emergent Wetland; Lower Perennial Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Rocky Shore; Unconsolidated Shore; Emergent Wetland. Upper Perennial Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Rocky Shore; Unconsolidated Shore. Intermittent Streambed.

LacustrineLimnetic Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Littoral Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Rocky Shore; Unconsolidated Shore; Emergent Wetland

Palustrine Rock Bottom; Unconsolidated Bottom; Aquatic Bed; Unconsolidated Shore; Moss-Lichen Wetland; Emergent Wetland; Scrub-Shrub Wetland; Forested Wetland.

Table 3.2. Classification of Coastal Wetlands for the Tobari System.

System Subsystem Class

Marine Subtidal Unconsolidated Bottom. Intertidal Unconsolidated Shore. Estuarine Subtidal Unconsolidated Bottom. Intertidal Rocky Shore; Unconsolidated Shore; Emergent Wetland; Scrub-Shrub Wetland. Palustrine Unconsolidated Shore; Emergent Wetland. , 40

Table 3.3. Summary of Wetland Functions and Values for different wetland types (The Conservation Foundation, 1988).

Flood conveyance; Barriers to waves and erosion; Flood storage; Fish and shellfish spawning and nursery areas; Habitat for waterfowl and other wildlife; Habitat for rare and endangered species; Recreation; Water supply; Food production; Timber production; Education and Research; Open space and aesthetic values; Water quality.

This classification of patterns is adapted to the regional characteristics of the study area, to compare results with future studies. Classification of human activities includes both continuous and seasonal activities (Table 3.4). The study area was classified using human activities aggregated intoa land use type classification of land use / land cover classes. In thisway, they can be related both to human activities and to patterns of development, following the criteria of theLUCID method described in Table 3.5. This classification is used to providean understanding of how changes of human activities (interms of land uses and patterns) are related to wetland changes as shown in Table 3.6. The comparison time period used to evaluate therate of change is 18 years because of photo availability. Two sets of aerial photographywere used. The first set consisted of five black and white 9" by 9" 1:70,000 scale, dated September1973. The second set had four black and white 9" by 9" 1:75,000 scale, datedJune 1991, both available from the National Institute of Statistics, Geography andComputerized Data (CETENAL, 1973; INEGI, 1991). 41

Table 3.4. LUCID Classification for Land Use Patterns (Pease et al, 1990).

Type I. This type is in an essentially natural (undisturbed) wilderness condition. These areas may be forested, barren, wetlands, or other ecosystem types. They show no signs of roadway, railway, or air access. Human use is limited to non-mechanized uses. Type II. A type II area shows signs of human exploitation; however, it is not a fully developed area, as indicated by a relatively low housing density and road network. It may be in transition to a full resource production/exploitation area. Type III. This type is characterized by developed systems forresource production, including access networks and managed production units. Type IV. A type IV area is developing a human settlement pattern that indicatesa shift from resource production as the predominant uses to rural non- resource residential and commuter settlement. A mix of resource based uses and non-resource settlement will be present. The area may be in transition to type V. Type V. A type V is a rural (non-urban) area which is characterized by settlement that is non-resource based. Dwellings may be primarily used for rural residences or vacation homes for urban based employment or retirees. This type could be characterized as an outer urban fringe area, which includes exurbs, linear fringe areas, and fringe enclaves. Type VI. A type VI area is becoming settled ata density that exceeds a rural residential character and shows signs of commercial /industrial development. This type could be characterized as a middle urban fringe area. Type VII. A type VII area could be called suburban or semi-suburban in that the intensity of use is generally urban in character but below densities ofa central urban core. It may or may not be in transition to an urbanarea. This type could be characterized as an inner urban fringearea. Type VIII. The type VIII is a fully developed urban center.

Interpretation was done manually, using pocket and mirror stereoscopes, by overlaying a clear plastic sheet. Lines and labelswere drawn using .01 mm and .005 mm Pens. Registration points were included for later georeferencing. Thesame land use classification was applied to the two dates. 42

Table 3.5. Human Activities the in the Tobari system.

Year long activities: Seasonal Activities: Small Towns (Urban) Fishing Camps Rural Settlement (Rural) Hunting Aquaculture Outdoor Recreation Salt mining Research / Education Tourism Abandoned/Barren Lands Agriculture Grazing

Table 3.6. Class Equivalence for Human Activities, Land Use/Cover, and LUCID System for Uplands in the Tobari System.

Human Activity Land Use/land Cover LUCID Type Urban Small Town Settlements (III) Rural Rural Settlement Settlements (III) Aquaculture Aquaculture Resources (II) Salt mining Salt mine Resources (II) Tourism Tourism/Recreation Resources (II) Agriculture Irrigated agriculture Resource Production (II) Fishing Camps Natural Vegetation Natural Areas (Iu) Grazing Natural Vegetation Natural Areas (Iu) Abandoned Lands Natural Vegetation Natural Areas (Iu) Hunting Natural Vegetation Natural Areas (Iu) Outdoor RecreationNatural Vegetation Natural Areas (Iu) Research/EducationNatural Vegetation Natural Areas (Iu) No Activity Bare Lands Natural Areas (Iu)

3.5. Database Development and GIS Integration. This research integrated data from air photo interpretation,maps and data gathered in the field, tabular data, and writtenreports into an electronic database. This approach considered as its main source of data the interpreted aerial photography; therefore, of particular importance were the limitations in the interpretation and in the ground truth verification process. The ground truth verificationwas done through field trips using a GPS receiver Magellan 5000 Pro. Forareas where access was very difficult, a low 43

altitude flight (150 feet above ground level) was made to obtain oblique video and aerial photography for verification purposes (Oriza et al, 1994). A base map was digitized from 1:50,000 scale topographicmaps (INEGI various dates, topographic maps). Description of the studyarea and wetland zones was based on previously digitized 1:250,000 scale thematic maps, which include land use/landcover, soils, surface and ground water, geology, and climate (INEGI various dates, thematic maps).

Linework and labels from air photo interpretationwere digitized using Autocad Release 10c2 (Autodesk Inc., 1988). Two personal computers, IBM PS2 Model 70 386DX 25 Mhz with 120 MB in the hard drive with 2 and 8 MB of RAMmemory were used, connected with two digitizing tablets IBM 5084-1 with .0001" resolution anda 16 button cursor. The registration of each photowas done using two control points taken from the topographic maps (1:50,000), with UTM coordinates, all within UTMzone 12. To label each polygon, the wetland and landuse classes were coded as in Table 2.7. Each class used one letter followed bya sequential number, in order to have each polygon with a unique identifier (i.e.: F26, F27, L13). Codes are not sequential (letters) because they were adjusted while GIS integration and correction was undertaken;some classes were eliminated and others were grouped together. The wetland classes of marine subtidal unconsolidated bottom and marine intertidal unconsolidated shorewere not included, because they were not considered for the analysis. Once line work and labels were digitized using different layers for each photo, they were exported as WU' files and imported as spaghetti linework into Terrasoft 10.03 software, a PC-based GIS (Digital Resource Systems, 1991) installed ina Dell 486DX 50 Mhz PC, with 8 MB of RAMImemory and a 830 MB hard drive. Air photo rectification and georeferencingwere done using a procedure within Terrasoft called rubber sheeting, in which another layer (called in Terrasoft "feature"),the digitized topographic base map, was overlaidon top of the line work from the air photo interpretation. By using a rubber-sheeting procedure,a series of paired points, a control from the base map, and a photo point from interpretationwere used to perform an Affine 44

Coordinate Transformation used in the rubber sheeting procedure (Digital Resource Systems, 1991). Polygons were warped and shifted for georeferencing, theprocess being repeated until each photo was matchedas closely as possible to the base map.

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid Class B Estuarine Subtidal Unconsolidated Bottom Iw C Estuarine Intertidal Rocky Shore Iw Z Open Ocean Water Iw Estuarine Intertidal Unconsolidated Shore Iwn G Palustrine Unconsolidated Bottom Iwn Estuarine Intertidal Emergent Wetland Iwv F Estuarine Intertidal Scrub-Shrub Wetland Iwv H Palustrine Emergent Wetland Iwv R Bare Land Natural Vegetation Iu V Dunes Iu I Irrigated Agriculture II N Aquaculture II 0 Salt Mine II S Abandoned Land II K Small Towns III L Rural Settlements III P Tourism III

Once linework was georeferenced, line workwas used to create a polygon theme, with the associated label as polygon identifier. Polygonswere created and cleaned within Terrasoft, by checking them to be closed and then building their topology.Spatial tabular databases were created, including attribute fields forarea, perimeter, identifier, coordinates for polygon centroid, and polygonstatus. Databases were manipulated using Foxpro 2.5 (Microsoft, 1993) and DbaseIV (Ashton-Tate, 1991). The database structure is shown in Table 3.8Creation of maps for each date was done by classifying each polygon accordingto the wetland and land use classification. 45

Table 3.8. Database structure for each date of aerial photography.

Name Type Width Dec Description P LABEL Character 16 Polygon Id P_AREA Numeric 13 5 Polygon Area P PERIM Numeric 13 5 Polygon Perimeter P X Numeric 10 2 Centroid UTM X Position P Y Numeric 10 2 Centroid UTM Y Position P_STAT Character 2 Unique Id. of Land Use for 1973 CLASI 73 Character 1 Class of Land Use for 1973 AREA 73 Numeric 13 5 Area of polygon in 1973 TOBA 91 Character 16 Unique Id. of Land Use for 1991 CLASI_91 Character 1 Class of Land Use for 1973 AREA 91 Numeric 13 5 Area of polygon in 1973 CAMBIO Numeric 1 Boolean indicator of land change TIPO CHG Character 2 Add of CLASS 73 and CLASS 73 STAT Numeric 1 Boolean indicator of area>0.25 Ha TASA_CAMBIO Numeric 13 5 (AREA/AREA_73)*100 CATEGORIA Numeric 1 Intensity Range Number of data records:2296

3.6. Identification of Changes in Wetlandsand in Land Uses. Once the classified maps for each datewere created, they were overlaid to get the areas of change. By using this procedure, each polygon from 1973was covered by the corresponding polygons of 1991. Therefore, those polygons from 1973and 1991 are called parent polygons. The resultingmap from this overlay contains what in Terrasoft are called "child polygons;" each of these child polygons isa record in a new database, containing the selected data attributes from theparent polygons (Figure 3.2). The data from this overlay are the basis for the statisticalanalysis on wetland change.

3.7. GIS Analysis, Statistical / Spatial Integration ofResults. Data were exported into a spreadsheet format in MicrosoftExcel 5.0 to be sorted and organized. Descriptive statistics and graphicrepresentation for data analysis were obtained within Excel. Datawere then reclassified while still in spreadsheet format, to facilitate the querying procedurenecessary for the data to be imported again into Terrasoft. 46

1 973 1991 Parent Parent Polygons Polygons

1991 over 1973 Child Polygons in Change Map

Figure 3.2. GIS Overlay Process to obtain Change Data.

Using the geographic information system, changeswere mapped and tabulated. The nature of change and its spatial distributionwere also identified, including wetland and land use change and conversion. Changes were ranked by intensity level, usingpercentage of change as indicator, by considering the area of each polygon in 1973, and the changesin 1991. Using these data, a change intensity mapwas developed in order to identify spatial distribution of changes and their relative degree of change (i.e.: Very High, High,Moderate, Low, Very Low and No change).

3.8. Correlation of Wetland Change, Land Uses, and LandUse Patterns. To identify any possible statistical correlations of wetland change with landuse types, data were defined as databases within Excel for Windows. 47

Two approaches were used to check for correlation: Graphical displays; The Pearson's sample correlation coefficientr to check for linear relationships, following the criteria suggested by Devore and Peck (1986) to considera statistical correlation: Strong if r> .8 or < -.8 Moderate if r> .5 and < .8 or < -.5 and > -.8 Weak if r is < .5 and > -.5 These relationships were visualized by their scatterplots. It is important to note thatan association (through the statistical correlation) does not imply causation. Results were sent back into Terrasoft for result integrationand map representation. Change data were used to reclassify the overlaymap based on intensity of change.

3.9. Policy Related Causes for Wetland Change. In order to identify whether wetland changes have been influencedor caused by a governmental policy within the studyarea, land use types identified as being correlated to wetland changes, whether positivelyor negatively, were used as indicators. Then, the National Development Plan, the State of Sonora Development Plan andsectoral plans, were reviewed for identification of policies related to those changes in landuse, such as sectoral economic programs directed towards agricultural lands andwater resources management, and other government programs and expenditures.

3.10. Considerations for the Sustainable Use of WetlandAreas. Observations are made on theoretical requirementsto maintain human uses and economic development, without diminishing wetlands functions and values.Regional considerations for Mexican institutionalarrangements are also discussed, in order to establish a potential scenario for the sustainableuse of coastal wetlands in Sonora. 48

CHAPTER 4 RESULTS

Results include descriptions, maps and analyses of conditions of wetlands and human activities and their changesover a 18 year period, as well as the most relevant of their interactions. This chapter is organized accordingto the following structure: conditions of the Tobari system in 1973 and 1991; the most important characteristics of the changes in conditions, and highlights of human / wetland interactions throughthose wetlands functions and values thatwere affected by those changes. Interactions are supported by a correlation analysis. The chapter closes by presenting the results of national and state policies affecting wetlands and humanactivities for the Tobari system.

4.1 Wetland classes. Wetland classes in the Tobari system are determined by tidal influence, freshwater flow from canals and ditches, and runoffwater from rainfall events. The system was originally formed by the Yaqui, the Cocoraque, and the Mayo riverdeltas. However, river migration and human induced water diversion have resulted inpoint specific freshwater outputs. The patterns of sedimentation within the system are also determined bya lack of water mixing from tidal currents, because ofpoor linkages of the two parts of estuary separated by the dividing road (Figure 2.1). Wetlands of the Tobari system, for thepurpose of this analysis, included only the estuarine and palustrine wetland classes. While thereare intertidal and subtidal marine wetlands along all the coast, theywere not considered in the classified map, for reasons given in chapter 3. The classifications of the studyarea were applied to both dates of aerial photography. The results are shown for eachset of data. A summary of the classifications used is shown in Table 4.1. A brief description ofthe wetland classes in the Tobari system is presented here to facilitate data interpretation: 49

Table 4.1 Summary of the Classification Applied to the Tobari system.

UPLANDS WETLANDS SystemSubsystem SystemSubsystem Class Development (LUCID III) Marine Settlements (LUCID III) Subtidal (LUCID Iw) Urban Unconsolidated Bottom. (LUCID Iw) Rural Intertidal Fishing Camps Unconsolidated Shore. (LUCID Iw) Resources (LUCID II) Estuarine Aquaculture Subtidal Salt mining Unconsolidated Bottom. (LUCID Iwn) Tourism Intertidal Resource Production (LUCID II) Rocky Shore; (LUCID Iwn) Cropland Unconsolidated Shore; (LUCID Iwn) Grazing Emergent Wetland; (LUCID Iwv) Natural Areas* (LUCID Iu) Scrub-Shrub Wetland. (LUCID Iwv) Barren Lands Palustrine Abandoned Lands Unconsolidated Bottom (LUCID Iwn) Natural Vegetation Emergent Wetland (LUCID Iwv) Desert Shrub Spiny forest Grasses Natural Areas* Include land uses considered seasonal, such as fishing, recreational, hunting and research/education.

4.1.1. Estuarine / Subtidal / Unconsolidated Bottom(ESUB). The entire area covered by water within thesystem below the tidal range was considered as an ESUB. The system doesnot have rocky areas, and, although presence of birds (such as Brantas, Branta spp.) mightsuggest areas with seagrass, these were not identified in either date of aerial photography. Field workobservations of the bottom showed sediments withoutgrass. This wetland class then is mostly determined by deposition of sediments from ditches and the tidalcurrents influencing sediment movement (Figure 4.1). 50

Figure 4.1. Photography showing an example of an area within the ESUB class

4.1.2. Estuarine / Intertidal / Rocky Shore (EIRS). There is only one area of this class located along the road that was built by filling of a four kilometer strip of rocks and covered with a dirt road. Road maintenance has been achieved by accumulating rocks at both sides. Although this class was constructed, thus an artificial landscape has resulted, it still offers opportunities for recreational fishing, since rocks offer good shelter for fish. The EIRS represents a minimum portion of the system and it could have been identified only through field trip observations (Figure 4.2)

4.1.3. Estuarine / Intertidal / Unconsolidated Shore (EIUS). Tides in the Tobari system range from 50 -100 centimeters; however because of the high deposition rates from the canals and ditches, intertidal fluctuation has been reported to have a width of 400 meters (Figure 4.3) (Valdes et al, 1994) Low areas that are periodically flooded by the tidal influence with no vegetation were also included in this class (Figure 4 4) Figure 43 Figure 4.2 Photography showingaportionoftheroadandEIRSclass. Photography showingthe ParedoncitoshoreasexampleofEIUSclass

i L ( Li Cie i . iti. la..4.,:i .3; k I L.11.1 , s:' C t i .:j i I Jr Cora 4 ;/1111Ifit, S' 1' h14,1''.,1:4 j. tv.ra,, 4 L. 1/4 V.4: 44 .2. N -1 1..41* f,t ..iflicS:P. .1.1/2..n, ,,,,- le( il., 51 52

"44-54d1

,- aP

u...,_ . 6 II :1-.1145c4 .., 1 b ,A , '. r/r ,-4-;43: - 1,kr A 5, 1 , .44 , LI '. i- ' 1r2..1 C ' i'' $'' 4 rl'/ - i ,,. Iv '..et. i:*44 - t, ,, ',4 0 0 n..1.4'__1. Qt, % % I., A Y;kil 1` 0 f 4 .tp 2[J4 Al, It 1, 't , 14 u [ Zhest1 ., r. H 1 ' .7.1 .r 1 4't 11 - I. n'f2. L 1 . 19 I ' ,. z4,0 i ' , 6i-4,.: 1 -4 0 c . ... , t 4,; li , ,.-:. i L r., ,1 1 e r t A- ", .:.I. CI ,-, ,z r__Fal..kal 4, _44. V_ el ClKit' V, 1,1-

Figure 4.4. Photography showing intertidal emergent grasses as example of EIEW class

4.1.4. Estuarine / Intertidal / Emereent Wetland (EIEW). Intertidal areas that maintain conditions of water saturated soils are frequently flooded completely. Emergent halophyte grasses are always present (i.e.: Batis spp. Distlichis spp.; Salicornia spp. ). These areas are predominant where there are freshwater flows into the system, such as outfalls of ditches, mostly in the north and south portion of the system (Figure 4.4).

4.1.5. Estuarine / Intertidal / Scrub-Shrub Wetland (EISS). This class is distributed mostly in the protected zones north and south of the system, characterized by the presence of black mangrove (Avicenia germinans) and red mangrove (Rhizophora mangle) (Figure 4.6). 53

411141 6.'eAlj ermir.____ "_IPOIR"--,10211,0"4"effigtell,'Wessih- laii2;famwagyta,ambasserraert4Vrzeik, - - r *". -``' - «Awfrs.1 "Segt 447- _

Figure 4.5. Photography showing an example of areas of EISS class.

Figure 4.6 Photography showing red mangrove Rhizophora mangle of the EISS class 54

4.1.6. Palustrine / Unconsolidated Bottom (PUB). This wetland class is limited to flooded areas where outfall from ditches occurs far from tide influence, and sedimentation has blocked communication with the estuarine systemTherefore, PUB includes areas of alluvial sediments, poor permeability, and no apparent vegetation (Figure 4 7)

Figure 4 7 Photography showing an example of an area within the PUB class

4.1.7. Palustrine / Emerzent Wetland (PEW). Areas identified by the presence of emergent grasses, such as cattail (Typha spp ) and bulrushes (Scirpus spp )They are closely associated with nearby ditches and freshwater outfallsIn several cases, they are present as islands within the (PUB) class (Figure 4.8)

4.2. Wetlands in 1973. Wetland distribution for 1973 is presented in Figure 4 9 A summary of the classified areas is presented in Table 4 2 and Figure 4 10Notice the absence of aquaculture and the use of an open ocean that originally was classified as estuarine area 55

(because of estuarine water coming out of the system) to adjust the total estuarine/land area, by subtracting it within the database. Irrigated agriculture and estuarine subtidal unconsolidated bottom (ESUB) alone cover nearly 60% of the total adjusted area.

i i 4 . .4 il 4 .0 4 ..,..;

IJ LY.4:1644'... 6 . SI 14i2ciai'lliwi ...Ile e 4,..414..- .,. .r....,..._...... r. w . I ftli I 4.M* -. ''-'--'. " '- -...... 7"...... --..--- -...''' ..::' ,11,4 0 ''.....-.."'"" "°".'t-.Ps-.". ,...---!NI .., . e. - N 1 i\1

1 ,

_ _ Lgr Y.! ,

c 3.4 ..1.!*Ilta-rl(1,11 If CSlidPA 3 Figure 4.8. Photography showing an example of an area within the PEW class

Table 4.2 Data summary for the classified areas of 1973

Class Class Class Total # PolyAverage`)/0 Total %W/O ESUB Est Subt. Unc B 8835 96 2 4417 99 12 98 20 92 FIRS Est Int Rock C 11 89 2 5 94 0 017 0 03 E1US Est Int Unc I) 1682 97 33 51 247 415

HEW Est Int Einem 1 1013 45 25 40 54 1 49 250 EISS Est Int Scni Shru 1219 36 77 15 83 1 79 3 00 PUB Pains Unc Bottom G 2772.34 2 1386 17 407 683 PEW Pains Emerg Wet 208 03 2 104 02 0 31 0 51

Irriga ted 1 15072 18 5 3014 44 22 14 37 13 ST Small Towns 62 13 4 15 53 009 0 15 RS Rural Settlements 130 24 69 1 89 0 19 0 32 AQ Aquaculture N 0 0 0 0 0 00

SM Salt Mine () 892 I 8 92 00! 002

Tourism 62 25 I 622! 009 0 15 BL Bare Land R 2114 27 31 682 311 52! AL Abandoned Land S 929 6 28 33 2 1 37 2 29 NV Natural Vegetation T 5858 57 74 79 17 86! 14 43 DU Dunes V 952 64 13 73 2% 14 2 35

00 ()nen Ocean Z 27130 54 1 27130 5 39 86 TOTAL68065 3 370 36508 8 100 100 00 Area adiusted 40590 13 _ _ - ,A Ch-0,47, Nat.,- .aqrrcuIi,.rnI Land Abandon ad Vega a.,on L andWiIhri1 RcraLtonol lar40 Tour 1 Hq.oc, I p"- Sinai ArIcoiLc,coi Land To1:).3r Gu Iror I ii his Depor tMlan 5.'1.1, IamanL TOLOG V59141, y Cor Geasc ances ;e ' T.;gst.ehl 01 Veai 04 , 1:,n 1,15 I_ for Lea. or g El :::: I i Forn E5Luori- E=Wwl=i'd°' ,54LIg=TdItinkV!, Ditch Ocaon OpenwaLer WaLimnd Poll,sLcina Emergent. Gm,,,.;Lcina Scrub-inruo Eluor1.1.a SwUlidol Figure 4.9.TobaiiSystem in1973. 1 cr7 eotLow elagam.acw- 00 56 57

Figure 4.10. Percentages of Total Area for 1973.

Classification 1973 Without Marine Area

V 2%

R5%

C, K, L, 0, P < 0.5%; N-0

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid Class Code Class Lucid Class Estuarine Subtidal Unconsolidated Bottom lw Natural Vegetation lu

1Estuarine Intertidal Rocky Shore lw V Dunes lu Dpen Ocean Water Iw Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn Aquaculture

IPalustrine Unconsolidated Bottom Iwn 0 salt Mine II .stuarnie intertidal Emergent Wetland lwv Abandoned Land II Estuarine Intertidal Scrub-Shrub Wetland Iwv Tourism III ralustrine Emergent Wetland lwv 3ma1l Towns III Bare Land lwv RuralRural Settlements HI

4.3. Wetlands in 1991.

Wetland distribution in 1991 is presented in Figure 4.11. As for 1973,a summary of the total areas in 1991 is presented in Table 4.3 and Figure 4.12. Thetotal area was also adjusted without openocean. Important to notice is the presence of aquaculture and that percentages of ESUB and irrigated agriculture remainedas in 1973 (about 60%).

Table 4.3. Data summary for the classified areas of 1991.

Class Class Class Total Area # Poly Average % Total %W/0 Ocean ESUB Est. Subt. Unc. Bot. B 8300.67 2 4150.33 12.19 20.45 EIRS Est. Int.Rock. Shore C 23.9 1 23.89 0.03 0.06 EIUS Est. hit. Unc. Shore D 1800.55 26 69.25 2.64 4.44 E1EW Est. Int. Emerg. Wet. E 869.58 26 33.45 1.28 2.14 EISS Est. Int. Scru.Shru. F 1799.13 78 23.07 2.64 4.43 PUB Palus. Unc. Bottom G 2548.48 2 1274.24 3.74 6.28 PEW Palus. Emerg. Wet. H 360 2 180 0.53 0.89 IA Irrigarted Awiculture I 16231.55 2 8115.77 23.85 39.99 ST Small Towns K 108.97 5 21.79 0.16 0.27 RS Rural Settlements L 101.46 78 1.3 0.15 0.25 AO Aquaculture N 497.57 3 165.86 0.73 1.23 SM Salt Mine 0 68.13 5 13.63 0.1 0.17

TO Tourism P 83.99 1 83.99 0.12 0.21 BL Bare Land R 448.26 26 17.24 0.66 1.10 AL Abandoned Land S 682.74 27 25.29 1 1.68 NV Natural Vegetation T 6025.08 65 92.69 8.85 14.84 DU Dunes V 640.08 6 106.68 0.94 1.58

00 Open Ocean Z 27475.18 1 27475.17 40.37 TOTAL 68065.3 356 41873.64 100 100.00 Area adjusted 40590.12

4.4. Wetland functions and values. Wetland functions and values have been extensively documented for Canada and United States in the literature (Lewis, 1995; Brinson, 1993; Bond et al, 1993; WWF, 1992; Adamus et al, 1987a; Adamus, 1987b; Cowardin et al, 1979). Wetland functions are the physical, chemical, and biological processes that characterize wetland ecosystems, such as flooding, denitrification, provision of habitat for organisms, and support of aquatic life. Some of these functions have been identifiedas useful or important to society, and therefore have been considered as wetland values, suchas the improvement of water quality, prevention of flood damage and development of unique plant communities that contribute to the conservation of biodiversity (Lewis, 1995). Also, other valuesare more closely related to lifestyles and thus vary in type and magnitude dependingupon their location (Bond et al, 1993). For the Tobari system, wetland functions have been identified and summarized in Table 4.4, and wetland values are summarized in Table 4.5. These tables donot pretend 60

Figure 4.12. Percentages of Total Area for 1991.

Classification 1991 Without Marine Area V 2% 15%

S2% R I% N I% D4%

E 2%

F4% 40%

C, K, L, 0, P < 1 %

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid Class Code Class Lucid Class Estuarine Subtidal Unconsolidated Bottom lw Vatural Vegetation lu Estuarine Intertidal Rocky Shore Iw V Dunes Iu Open Ocean Water Iw Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn Aquaculture II Palustrine Unconsolidated Bottom Iwn 0 Salt Mine II Estuarine Intertidal Emergent Wetland Abandoned Land Estuarine Intertidal Scrub-Shrub Wetland Iwv Tourism III Palustrine Emergent Wetland Iwv Small Towns III Bare Land Iwv Rural Settlements III

to cover all the functions and values, but only to illustratesome of the most frequently mentioned in the literature.

By looking at these tables, itcan be determined that some of the functions and values are common to vegetated wetlands, whilenon-vegetated wetlands share others (Table 4.5). This difference allows the establishment of threegroups of wetlands 61

Table 4.4. Summary of wetland functions for the wetland classes of the TobariSystem.

WETLAND FUNCTIONS ESTUARINE PALUSTRINE SYSTEM SYSTEM Subtidal Intertidal Subsystem Subsystem Class Class Class ^ Uncons. Rocky Uncons, Emergent Scrub-Shrub UnconsolidatedEmergent Bottom Shore Shore Wetland Wetland Bottom Wetland PHYSICAL:

Reduction of coastal erosion X X X

Reduction of dragging of X X aquatic communities

Storm abatement X X X

Sediment trap X X X X X X - Climate regulation X X X X X

Biosphere processes X X X stabilization

Vegetated buffer X X X HYDROLOGICAL:

Nutrient retention and X X X removal - Flood mitigation X X X

Aquifer recharge X X X X X Water Storage X X CHEMICAL:

Pollution trapping X X X X

Removal of toxic residues X X

Waste processing X X X BIOLOGICAL:

Productivity X X X X X

Nourishment for local and X X X X X X migratory species

Habitat for plants and X X X X X X X animals

Migratory processes X X X

Biological corridors for X X X X X genetic exchange

Food chain support X X X X X X Sources: Modified from Lewis, 1995; Brinson, 1993; Bond et al, 1992; WWF, 1992; Adamus eta!, 1987a; Adamus, 1987b; Cowardin et al, 1979. 62

Table 4.5. A summary of wetland values for the Tobari wetland classes.

Wetland Values EstuarineSystem PalustrhieSystem Subtidal Intertidal Subsystem Subsystem Uncoils. Rocky UnconsEmergentScrub-ShrubUncons. S. Emergent Biological Population Mammal Food X X X Fur X X Reptiles Skin Products X X X X Food X X X X X Jewelry/Crafts X X X X

Waterfowl Bird watching X X X X X X

Hunting X X X

Fish/ShellfishFood X X X X X

Aquacuhure supplies X X

Jewelry/Crafts X X

Timber/Other Charcoal X X Construction X X Fiber X X X

Ecosystem Flood mitigation and X X X X control Storm abatement X X X Shoreline stability X X X Land formation X X X Shoreline anchoring X X Aquifer recharge X X X X X Water quality X X X X improvement

Natural agriculture X X X

Rearing Habitat X X X X X

Food chain support X X X X X Social Outdoor Recreation X X X X X X Aesthetic Scenarios X X X X X X Cultural Heritage X X X X

Education/ Living labs X X X X X X

Scientific research X X X X X X X

Global Water Quality X X X Air Quality X X X Climatic regulation X X X X X Sources: Modified from Lewis, 1995; Brinson, 1993; Bond et al, 1992; WWF, 1992; Adams eta!, 1987a; Adarnus, 1987b; Cowardin et al, 1979. 63

according to their functions and values. However, vegetated wetlands include most functions and values, highlighting the diversity and importance of vegetated systems in terms of human - wetland interactions, as well as interactions within the ecosystem (Table 4.6).

Table 4.6. Wetland Group Categories according to their functions and values. A) Non-Vegetated wetlands: Estuarine / Subtidal / Unconsolidated Bottom (ESUB) Estuarine / Intertidal / Unconsolidated Shore (EIUS) Palustrine / Unconsolidated Bottom (PUB). B) Rocky stratum Estuarine / Intertidal / Rocky Shore (EIRS) C) Vegetated wetlands: Estuarine / Intertidal / Emergent Wetland (EIEW) Estuarine / Intertidal / Scrub-Shrub Wetland (EISS). Palustrine / Emergent Wetland (PEW).

4.5. Human activities adjacent to the wetlands- 1973. Human activities within the Tobariwere classified on aerial photographs by applying the classification system shown in Table 4.1. Some of the activitiesare grouped into manageable mapping units. For example, naturalareas cover seasonal activities such as research, education, outdoor recreation, and hunting, and include a variety of vegetation. However, the primarypurpose of the classification is to classify adjacent land areas according to the intensity of human activities. In 1973, the two main human activities interacting with wetlandswere agriculture and fisheries, and their associated activities, suchas waste water disposal and access roads. Recreation and tourismwere confined to the north portion of Huivulai island, the fill road that joins the island with the land, and thesurrounding two main population 64 centers (Pared& Colorado and Parendoncito) (See Figure 2.1). Total area for each class is shown in Table 4.2.

4.6. Human activities adjacent to the wetlands- 1991. Activities in 1991 were similar to those in 1973. However,an increase can be noticed in wetland related activities, suchas aquaculture (absent in 1973) and salt mining. Agriculture and fisheries related activitieswere also important, covering 60% of the total area, since the entire body of water classified as ESUB is considered as a fishingarea. Hunting activities increased in amore structured form, with hunting clubs based in Ciudad Obregon, 40 kilometers north of the system. Recreation and tourism remainedon the northern portion of the Huivulai island. However,waste water from agricultural areas is related to high sedimentation levels around the outfall of drainage ditches, thusmaking the wetland system shallower; emergent and scrub-shrubareas can be seen in these areas (Figure 4.11). A summary of the classifiedareas is presented in Table 4.3.

4.7. Spatial Changes 1973-1991.

In order to screen the major changes from 1973 to 1991 in the Tobarisystem, a change map was developed classifying changes into six levels: Areas of no change.- All polygons that maintained theirsame identifier in 1973 and 1991; Areas with very low change.- All polygons that changed less than 10 % of their 1973 area; Areas with low change.- All polygons that changedmore than 10 % and less than 20% of their 1973area; Areas with moderate change.- All polygons that changedmore than 20 % and less than 80% of their 1973area; Areas with high change.- All polygons that changedmore than 80 % and less than 90% of their 1973area; Areas with very high change.- All polygons that changedmore than 90 % of their 1973 area.

The break points for these levelswere set according to their distribution. Because most polygons fell in the categories of low changeor high change, the moderate change category was set between 20 % and 80 % change. Polygonswere categorized with 65 respect to the level of change for eachindividual polygon since 1973 A map was developed to show how the intensity of change isspatially distributed (Figure 4 13.)

&''Np ftl. k.. 014"", + 4';;".2t14..,

I c,irorraoi Gur or , 15eoorCortez!

Inter,sitw or Lona use Crionoe T000rt Sysf.em

No chonge 0MoperateChange

FMVery Low Chnnge n High Change Low Change 11 Very High Change -__ Ditch

Departmentor 6e0sclences

04) [Or103 VO4147. goetowne 1/M5

re0

Figure 4 13. Change Map of the Tobari System 1973/1991 66

Change data are summarized in Table 4.7 and is illustrated as change in Figure 4.14. Detailed change data are presented in Table 4.8. Total area changeper class is shown in Figure 4.15.

18000

16000

14000

12000

10000

8000 .Area73 T 6000 Area9 I 4000 KLN op 2000 o

Figure 4.14. Total area (hectares)per class for 1973 and 1991.

Table 4.7. Change from 73 to 91 (area in hectares).

Class Code Area73 Area91 Change Absolute Yo CH from 73 % of Change Respect to Chame same class Total Chame Area Est. Subt. Unc. Bot. B 8491.328300.67-190.65 190.65 2.25 3.39 Est. Int.Rock. Shore C 11.89 23.9 12.01 12.01 101.01 0.21 Est. Int. Unc. Shore D 1682.971800.55 117.58 117.58 6.99 2.09 Est. hit. Emerg. Wet. E 1013.45 869.58 -143.87 143.87 14.20 2.56 Est. Int. Scru.Shru. F 1219.361799.13 579.77 579.77 47.55 10.31 Palus. Unc. Bottom G 2772.342548.48-223.86 223.86 8.07 3.98 Palus. Emerg. Wet. H 208.03 360 151.97 151.97 73.05 2.70 Irrigarted Agriculture I 15072.216231.61159.371159.37 7.69 20.61 Small Towns K 62.13 108.97 46.84 46.84 75.39 0.83 Rural Settlements L 130.24 101.46 -28.78 28.78 22.10 0.51 Aquaculture N 0 497.57 497.57 497.57 100.00 8.85 Salt Mine 0 8.92 68.13 59.21 59.21 663.79 1.05 Tourism P 62.25 83.99 21.74 21.74 34.92 0.39 Bare Land R 2114.27448.26-1666.011666.01 78.80 29.62 Abandoned Land S 929.6 682.74 -246.86 246.86 26.56 4.39 Natural Vegetation T 5858.576025.08 166.51 166.51 2.84 2.96 Dunes V 952.64 640.08 -312.56 312.56 32.81 5.56 Totals 40590 40590 0 5625 1298 100 6 7

1500

1000 F N 500 H 'Op 0 II_ 1 I L -500 V

-1000

-1500

-2000

Figure 4.15. Total Change from 1973 to 1991.

Table 4.8. Summary of Changes by Class 73 into Class 91 (area in hectares).

Class Area # PolyAverage %Total %W/0 0 Class Area #Poly Average%Total%W/00 BB 7,969.17 7 1,138.45 11.72 19.63 1K 18.52 1 18.52 0.03 0.05 BC 14.07 2 7.03 0.02 0.03 IL 61.31 69 0.89 0.09 0.15 BD 447.85 14 31.99 0.66 1.10 10 6.73 1 6.73 0.00 0.02 BE 11.08 6 1.85 0.02 0.03 IR 3.24 1 3.24 0.00 0.00 BF 272.13 90 3.02 0.40 0.67 IS 196.64 17 11.57 0.29 0.48 BK 5.32 1 5.32 0.00 0.01 IT 114.99 12 19.16 0.17 0.28 BP 8.03 2 4.02 0.01 0.02 KF 2.77 2 1.39 0.00 0.00 BR 7.35 6 1.23 0.01 0.02 ICK 33.88 3 11.29 0.05 0.08 BT 81.52 18 6.85 0.12 0.20 KS 9.02 1 9.02 0.01 0.02 BV 10.73 5 2.15 0.02 0.03 LI 102.86 65 1.58 0.15 0.25 CB 1.76 1 1.76 0.00 0.00 LL 22.38 2 11.19 0.03 0.06

CC 9.30 1 9.30 0.01 0.02 LS 4.32 1 4.32 0.00 0.01 CF 0.83 1 0.83 0.00 0.00 OD 2.53 2 1.27 0.00 0.00

DB 27.59 18 1.53 0.04 0.07 OF 3.72 1 3.72 0.00 0.00 DD 539.21 28 19.26 0.79 1.33 OT 2.66 2 1.33 0.00 0.00

DE 269.00 23 11.70 0.40 0.66 PC 0.31 1 0.31 0.00 0.00 DF 305.01 50 6.10 0.45 0.75 PD 2.52 1 2.52 0.00 0.00

DG 137.91 5 27.58 0.20 0.34 PP 43.79 1 43.79 0.06 0.11 DH 11.20 1 11.20 0.02 0.03 PT 13.28 4 3.32 0.02 0.03 DI 72.97 5 14.60 0.11 0.18 PV 1.55 1 1.55 0.00 0.00 DN 5.95 2 2.98 0.00 0.01 RB 1.26 2 0.63 0.00 0.00 DP 24.79 1 24.79 0.04 0.06 RD 381.59 18 21.20 0.56 0.94 6.8

Table 4.8. (Continued). Summary of Changes by Class 73 into Class 91. _ _._ NMIClacc Area MIMIii Pnlv Average V.Tntal 04W/(1(1 ri. Area ii PnIv Averacre %Total%W/0 - ...... :-....------DR 68.52 7 9.79 0.10 0.17 RE 55.31 16 3.46 0.08 0.14 DT 213.14 31 14.01 0.31 0.53 RF 133.14 29 4.59 0.20 0.33 DV 170.13 7 24.30 0.25 0.42 RH 45.69 5 9.14 0.07 0.11 EB 28.43 14 2.03 0.04 0.07 RI 591.50 20 29.58 0.87 1.46 ED 223.56 24 9.32 0.33 0.55 RK 27.58 2 13.79 0.04 0.07 _ EE 251.26 17 14.78 0.37 0.62 RL 11.12 4 2.78 0.02 0.03

EF 167.79 37 4.53 0.25 0.41 RN 110.58 1 110.58 0.16 0.27 EG 16.75 4 4.19 0_02 0.04 RO 16.36 16.36 0.02 EH 47.39 , 47.39 0.07 0.12 RR 137.06 10 13.71 0.20 0.34

EK 082 1 0.82 0.00 000 RS 36.25 , 7 5.18 0.05 009 EN 27.35 7 3.91 0.04 0.07 RI 563.98 34 1858 PO 20.84 2 10.42 0_01 0.05 SD 19.46 3 6.49 000.833 01:0395 , ER 57.00 12 4.75 0.08 0.14 SF 17_66 2 8.83 0.03 0.04 ET 152.33 14 22.02 0.22 0.38 SH 34.96 34.96 0_05 0.09

EV 14.22 1 14.22 0.02 0.04 51 488.82 23 21.25 0.72 1.20

FB 153.31 68 225 0.23 0.38 SL 0.60 1 0.60 -17: 0.00 0.00

FD 1851071 38 4.89 1 0.27 0.46 SR 7.12 4 1.78 0.01 0_02 FE 41.03 21 1.95 0.06 0.10 SS 16412 14 1.77 0.24 0.41 FF 577.10 89 6.48 0_115 ..._ 1.42 ST 196.13 I I __25.96_ 0_29 0.48 FG 3.39. 2 1.70, 0.00 0.00 T13 98.22 36 4.02 0.14 0.24 Fl 43_91 12 3.66 0.06 0.11 TD 242.35 26 15.93 0.36 060 FK 9.81 3 3.27 0.01 0.02 TE 139.40 22 12.62 0.20 0.34 F1.1 14.40 3 4.80 002 0.04 IF 246.27 57 _9.48 ...... 0.36 0.61 FR 42.12 8 5.26 0.06 010 TG 408.60 33 44.34 0.60 1.01 FS 12.05 5 241 0.02 0.03 TH 85.08 4 38.23 013 0.21 FT 123.96 33 7.64 0.18 (131 T1 322.19 31 210.788 0.47 0.79 FV 3.66 2 1_83 0.00 0.00 TIC 12/9 0.03 1 GD 153.80 3 51.27 0.23 0.38 TL 1.30 3 0.80 0.00 0_00 GE 58.33 3 _ 1944.. 0.09 0.14 TN -...... 5.96 I -596- 0.00 0.01 GF 16_99 16.99 0.02 TO 9.20 3 3.07 0_01 0.02 GO 1.756.95 5 351_19 2.58 4.33 TP 6_81 4 1.70 0.01 0.02 1 GH 22.47 4 5.62_ 0.03 0_06 TR 98.16 15 0_24 GN 332.66 2 166.33 0 .49 0.82 IS 227.1 16 2135 f4890 0.30.134 0.56 GO 14.80 3 4.93 0.02 0_04 TT 3.922.34 91 199.34 5.77 9.66 OR 19.39-- 3 -646 0.03 0.05 TV 27.23 12 2.74 0.04 0.07 GS 15_40 3 5.13 0.02 _004 VB 13.78 I I -__1.25 0_02 003

GI 381.24 31 __-21 50 0.56 0.94 Inl 77.73 In 7.77 0.11 00..0139 I-1-HI 112.88 6 -18.81 _-__ 0.17 0.28 VE 1.91 3 3.97 002 HI 1.53 1 1.53 0.00 0.00 VF 25.49 12 ---2.12 0.04 0.06 HR 2.86 3 0.95 0.00 _ 0.00 VG 224.24 4 -56_06- 013--- 0.55 HS 16.13 4 4.03 0.02 0.04 VL 3.96 1 3.96 0.00 0.00

Hi' 74.23 5 ----29.07 - 0.1I 0.18 VP 0.37. 1 017 0.00 0.00 ID 34.46 5 6.89 0.05 0.08____ VR 2.98 I 2.98 0.00 0.00 1E --29.38- 3 9.79 0.04 007 VT 179.05 22 1.55 016 044 IF 15.05 5 _3.01 002 004 VV 411A6 5 82.29 0.60 1.01

II 114,606.65[9 2,092.51 21.47 35.99 ZZ 26.962.34 I 26_96214 39.64 66.43 Total30,567.94849.00 4381.82 44.94 75.31 Total37.454.26 822 28084_ 55 25.85 69

4.8. Human / Wetland Interactions. The description of human /wetland interactions focusedon the polygons that changed. Using the GIS, data on polygons that changedwere selected for the analysis. A complete set of data for the overlay map of change is presented in Appendix A. However, in order to visualize the interactions, each individual class for wetlands,as well as for uplands, is compared in terms of change. Datawere aggregated for each class, and percentages were computed and graphed for visual interpretation. In the following pages, a series of graphs and tablesare presented to visualize how each class interacted with the others. The order in which theyare presented follows the grouping of wetlands according to their functions and values (Table 4.6). First, thenon- vegetated wetlands and rocky stratum are presented, then the vegetated wetlands. The upland classes are also presented. Each class is represented by a code; the first letter in the code indicates the class in 1973, and the second letter, the class in 1991. For instance,a code GN indicates that palustrine unconsolidated bottom area in 1973 changed toan aquaculture area in 1991. In order to easily identify interactions,a reference table was attached to each set of graphs and tables, that show how thearea in one class in 1973 changed into other classes in 1991, and how other classes in 1973 changed to that class in 1991. Tables 4.9 to 4.25 show the areas in hectares and percentages. At thetop of each table, the total area that changed is indicated. The pound symbol" #"represents all other classes. The areas that remained thesame class during the 18 year period, for instance their code would have shown thesame letter: "D=>D" or "V=>V", were not included in the interaction tables. The percentageswere also included because they indicate the relative contribution of each class to the totalarea in 1991 that changed from 1973 for that class. 70

4.8.1. Interrelations of Estuarine Subtidal Unconsolidated Bottom (Code B, ESUB) - LUCID).

Table 4.9. Interrelations of Estuarine Subtidal Unconsolidated Bottom.

Change B to # 158.07 Hectares Change # to B =324.35 Hectares 1973 to 1991Code %Change Area # Poly 1973 to 1991Code %Change Area # Poly

73B to 91C BC 1.64 14.07 2 73C to 91B CB 0.54 1.76 1 73B to 91D BD 52.19 447.85 14 73C to 91B DB 8.51 27.59 18 73B to 91E BE 1.29 11.08 6 73C to 91B EB 8.77 28.43 14 73B to 91F BF 31.71 272.13 90 73C to 91B FB 47.27 153.31 68 73B to 91K BK 0.62 5.32 1 73C to 91B RB 0.39 1.26 2 73B to 91P BP 0.94 8.03 2 73C to 91B TB 30.28 98.22 36 73B to 91R BR 0.86 7.35 6 73C to 91B VB 4.25 13.78 11 73B to 91T BT 9.50 81.52 18 Total 100 324.35 150 73B to 91V BV 1.25 10.73 5 Total 100 858.07 142

Figure 4.16. Interrelations of Estuarine Subtidal Unconsolidated Bottom.

Changes from B (ESUB) D BC Changes to B (ESUB) 1973-1991 1973-1991 BD EB 9% FB BC 2% BD 52% OBE 47% BV 1% O BF BT BK BR 1% BP BP 1% BK 1% BR BT BV

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class stuanne Subtidal Unconsolidated Bottom Iw SI aural Vegetation lu Estuarine Intertidal Rocky Shore lw V Dunes lu Den Ocean Water lw Irrigiited Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn eiguaculture II Palustrine Unconsolidated Bottom Iwn 0 Salt Mine II Estuarine Intertidal Emergent Wetland Iwv kbandoned Land II Estuarine Intertidal Scrub-Shrub Wetland Iwy Tourism III Palustrine Emergent Wetland Iwv Small Towns III Bare Land In L Rural SettlementsSettlements 71

4.8.2. Interrelations of Estuarine Intertidal Rocky Shore (Code C. EIRS) (Iw- LUCID).

Table 4.10. Interrelations of Estuarine Intertidal Rocky Shore.

Change C to=2.59 Hectares Change /I to C =14.3781 Hectares 1973 to 1991Code %Change Area # Poly 1973 to 1991Code %Change Area # Poly

73C to 91B CB 67.79 1.76 1 73B to 91C BC 97.85 14.07 2

73 to 91F CF 32.21 0.83 1 73P to IC PC 2.15 0.31 1 Total 100.00 2.59 2 Total 100.00 14.38 3

Figure 4.17. Interrelations of Estuarine Intertidal Rocky Shore.

Change from C (FIRS) 1973-1991 Change to C (FIRS) 73-91

PC IN BC 2% PC

Be 98%,

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class ILucid ClassCode Class Lucid Class ------, i----IiEstuarine Subtidal Unconsolidated Bottom Iw STatural Vegetation Iu C Estuarine Intertidal Rocky_ Shore Iw V Dunes Iu Z Dpen Ocean Water lw Irrigatedfrrigated Agriculture II - Estuarine Intertidal Unconsolidated__. Shore Iwn eiouaculture II alushine Unconsolidated Bottom Iwn 0 salt Mine ! Estuarine Intertidal Emergent Wetland Iwy Ikbandoned Land II F Estuarine Intertidal Scrub-Shrub Wetland .....Iwy Fourism Ill Palustrine- - Emergent Wetland Iwy tmau owns HI R Bare Land i --... Lu L 1Sirral Settlements HI 72

4.8.3. Interrelations of Estuarine Intertidal Unconsolidated Shore (Code D, EIUS) ( Iwn - LUCID).

Table 4.11. Interrelations of Estuarine Intertidal Unconsolidated Shore.

Change D to # =1,306.23Hectares Change # to D =1,771.55Hectares 1973 to 1991 Code %Change Area # Poly 1973 to 1991Code%Change Area #Poly 73D to 91B DB 2.11 27.59 18 73B to 91D BD 25.2801 447.85 14 73D to 91E DE 20.59 269.00 23 73E to 91D ED 12.6196 223.56 24 73D to 91F DF 23.35 305.01 50 73F to 91D FD 10.4825 185.70 38 73D to 91G DG 10.56 137.91 5 73G to 91D GD 8.68161 153.80 3 73D to 91H DH 0.86 11.20 1 731 to 91D ID 1.94499 34.46 5 731D to 911 DI 5.59 72.97 5 730 to 91D OD 0.14308 2.53 2 73D to 91N DN 0.46 5.95 2 73P to 91D PD 0.14205 2.52 1

73D to 91P DP 1.90 24.79 1 73R to 91D RD 21.5396 381.59 18 73D to 91R DR 5.25 68.52 7 73S to 91D SD 1.09873 19.46 3 73D to 91T DT 16.32 213.14 31 73T to 91D TD 13.68 242.3486 36 73D to 91V DV 13.02 170.13 7 73V to 91D VD 4.38765 77.73 10 100 1,306.23 150 100 1771.553 1540

Figure 4.18. Interrelations of Estuarine Intertidal Unconsolidated Shore.

Change from D (11US) 0 RD DR Change to D (BUS) 73-91 ED 73-91 DE VD 4% DT 4% BD o FD DV 13% o DF TD DOD DR 5% DO 1 SD 1% ID DP 2% DH OD DI RD DN 0% PD DN 22% 0 DP ED o RD DI 6% DR PD 0% 13% SD DH 1% OD 0% TD 0 DT 1 p 2 04 GE y 9% FD .1 e'o. DG 11% 0 DV 0 VD

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom Iw Natural Vegetation Iu Estuarine Intertidal Rocky Shore Iw V Dunes lu Dpen Ocean Water Iw Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn eiguaculture II F'alustrine Unconsolidated Bottom Iwn 0 Salt Mine II Estuarine Intertidal Emergent Wetland Ivry Abandoned Land II Estuarine Intertidal Scrub-Shrub Wetland Iwy Tourism Palustrine Emergent Wetland Iwy Small Towns III Bare Land Iu L Rural Settlements 73

4.8.4. Interrelations of Palustrine Unconsolidated Bottom (Code G, PUB) awn - LUCID).

Table 4.12. Interrelations of Palustrine Unconsolidated Bottom.

Change G to # =1,015.07Hectares Change # to G =790.89 Hectares 1973 to 1991 Code%Change Area # Poly 973 to 1991Code%Change Area #Poly 73G to 91D GD 15.15 153.80 3 73D to 91G DG 17.44 137.91 5 73G to 91E GE 5.75 58.33 3 73E to 91G EG 2.12 16.75 4 73G to 91F GF 1.67 16.99 1 73F to 91G FG 0.43 3.39 2 73G to 91H GH 2.21 22.47 4 73T to 91G TG 51.66 408.60 30 73G to 91N GN 32.77 332.66 2 73V to 91G VG 28.35 224.24 7 730 to 910 GO 1.46 14.80 3 Total 100 790.89 48 73G to 91R GR 1.91 19.39 3 73G to 91S GS 1.52 15.40 3 73G to 91T GT 37.56 381.24 31 Total 100 1,015.07 53

Figure 4.19. Interrelations of Palustrine Unconsolidated Bottom.

Change from G (PUB) 73/91 OD Change to G (PUB) 73/91

OT 38% GE GD 15% o OF DG Gil E02% FG 0% EG GE 6% ON 0F2% o FG GO GFI 2% TO OR TG 52% VG ON 33% El GS OT

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class B estuarine Subtidal Unconsolidated Bottom Iw Iatural Vegetation Iu C Estuarine Intertidal Rocky Shore lw V Dunes lu Z 0pen Ocean Water lw Irrigated AgricultureAgriculture II D 6.stuarine Intertidal Unconsolidated Shore Iwn eiquaculture II G Palustrine Unconsolidated Bottom Iwn 0 Salt Mine II Lam[wine Intertidal Emergent Wetland Iwv Abandoned Land II F Ystuarine Intertidal Scrub-ShrubWetland Iwy Tourism Ill H ?alustrine Emergent Wetland Iwy Small Towns UI R Bare Land lu Rural Settlements 7,e1

4.8.5. Interrelations of Estuarine Intertidal Emergent Class (Code E, EIEW) fIwv - LUCID).

Table 4.13. Interrelations of Estuarine Intertidal Emergent Wetland.

Change E to # =756.49 Hectares Change # to E =615.44Hectares 1973 to 1991 Code %Change Area # Poly 1973 to 1991Code %Change Area # Poly 73E to 91B EB 3.76 28.43 14 73B to 91E BE 1.80 11.08 6 73E to 91D ED 29.55 223.56 24 73D to 91E DE 43.71 269.00 23 73E to 91F EF 22.18 167.79 37 73F to 91E FE 6.67 41.03 21 73E to 91G EG 2.21 16.75 4 73G to 91E GE 9.48 58.33 3 73E to 91H EH 6.26 47.39 1 731 to 91E LE 4.77 29.38 3 73E to 91K EK 0.11 0.82 1 73R to 91E RE 8.99 55.31 16 73E to 91N EN 3.62 27.35 7 73T to 91E TE 22.65 139.40 22 73E to 910 E0 2.75 20.84 2 73V to 91E VE 1.94 11.91 3 73E to 91R ER 7.54 57.00 12 Total 100 61544 97 73E to 91T ET 20.14 152.33 14 73E to 91V EV 1.88 14.22 1 Total 100 756.49 117

Figure 4.20. Interrelations of Estuarine Intertidal Emergent Wetland.

Change from E(HEW) 73/91 Ed EIT Gunge to E(HEW)73/91 ED EV 2% EB 4% VE 2% BE.i%. 0 EF ET T E 22% 0 BE 20% El EG ,;:01,1 .-., ED DE EH 0% n' on C3 EK 0 "1.: '' ' :'' ' DE cia ER 89'0 s2 EN 0*.:11! : - 43% - . 4 g, * . IE E.0 3% ,,,c "'" .0.11 E3 EO :RE 9% ::::::.:ig C3 RE EN 4% .4i ';; :::::::]:K; . EK 0% fti...,±f2.2.':2/ 9.8. E2 T E EH 6% ET 'IE 5% - EF 22A., . p VE EG 2% D EV 0E9% FE 7%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom Iw Natural Vegetation Iu Estuarine Intertidal Rocky Shore lw V Dunes Iu Dpen Ocean Water Iw IrrigatedErrigated AgricultureAgriculture Estuarine Intertidal Unconsolidated Shore Iwn ekauaculture Palustrine Unconsolidated Bottom Iwn Salt Mine II Estuarine Intertidal Emergent Wetland Iwv kbandoned Land II Estuarine Intertidal Scrub-Shrub Wetland Iwv Fourism III Palustrine Emergent Wetland Iwv Small Towns III Bare Land Iu Rural Settlements III 75

4.8.6. Interrelations of Estuarine Intertidal Scrub-Shrub Class (F, EISS) (Iwv- LUCID).

Table 4.14. Interrelations of Estuarine Intertidal Scrub-Shrub.

Change F to # =633.34 Hectares Change # to F =1,206.86 Hectares 1973 to 1991 Code %Change Area # Poly 1973 to 1991Code %Change Area #Poly 73F to 91B FB 24.21 153.31 68.00 73B to 91F BF 22.55 272.13 90

73F to 91D FD 29.32 185.70 38.00 73C to 91F CF 0.07 0.83 1 73F to 91E FE 6.48 41.03 21.00 73D to 91F DF 25.27 305.01 50 73F to 91G FG 0.54 3.39 2.00 73E to 91F EF 13.90 167.79 37

73F to 911 Fl 6.93 43.91 12.00 73G to 91F GF 1.41 16.99 1 73F to 91K FK 1.55 9.81 3.00 731 to 91F IF 1.25 15.05 5 73F to 91N FN 2.27 14.40 3.00 73K to 91F KF 0.23 2.77 2

73F to 91R FR 6.65 42.12 8.00 730 to 91F OF 0.31 3.72 1 73F to 91S FS 1.90 12.05 5.00 73R to 91F RF 11.03 133.14 29 73F to 91T FT 19.57 123.96 33.00 73S to 91F SF 1.46 17.66 2 73F to 91V FV 0.58 3.66 2.00 73T to 91F TF 20.41 246.27 57 Total 100 633.34 195.00 73V to 91F VF 2.11 25.49 12 Total 100 1,206.86287

Figure 4.21. Interrelations of Estuarine Intertidal Scrub-Shrub.

Change from F (EISSW) 73/91 F13 Change to F (EISSW) 73/91 VF 2% FD TF BF O FE 20% 24% O FG

11111 SF O FK 1% FN RF O FR 11% FS IF 1% FD FT OF, KF <1% 1% 28% 0 EV EF 14%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom lw gatural Vegetation Iu Estuarine Intertidal Rocky Shore lw V Dunes Iu nen Ocean Water lw 1 brit,eated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn etnuaculture II Palustrine Unconsolidated Bottom Iwn 0 Salt Mine Estuarine Intertidal Emergent Wetland Iwv Abandoned Land II Estuarine Intertidal Scrub-Shrub Wetland lwv Tourism III Palustrine Emergent Wetland lwv Small Towns III Bare Land lu L Rural Settlements 76

4.8.7. Interrelations of Palustrine Emergent Wetland (Code H. PEW) (Iwv- LUCID).

Table 4.15. Interrelations of Palustrine Emergent Wetland.

Change H to # =94.74 Hectares Change # to H= =246.79 Hectares 1973 to 1991Code%Change Area #Poly 1973 to 1991 Code %Change Area # Poly

73H to 911 HE 1.62 1.53 1 73D to 91H DH 4.54 11.20 1 73H to 91R HR 3.02 2.86 3 73E to 91H EH 19.20 47.39 1 73H to 91S HS 17.02 16.13 4 73G to 91H GH 9.10 22.47 4 73H to 91T HT 78.35 74.23 5 73R to 91H RH 18.51 45.69 5 Total 100 94.74 13 73S to 91H SH 14.17 34.96 1 73T to 91H TH 34.47 85.08 4 Total 100 246.79 16

Figure 4.22. Interrelations of Palustrine Emergent Wetland.

Changes from H (PEW) 73/91 Change to H (PEW) 73/91 FE HR DH DH 2% 3% T41 5% 34% ER 'ER

:OH

TH 140/0 _19%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code . - _ Class 1 Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom lw Tatural Veeetation lu Estuarine Intertidal Rocky Shore lw V Dunes Iu to.Inen Ocean Water lw Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn 1._etauaculture II Palustrine Unconsolidated Bottom . Iwn 0 iah Mine II IEstuarine Intertidal Emereent Wetland Iwv ,kbandoned Land II 1Estuarine Intertidal Scrub-Shrub Wetland Iwv fourism Ill Palustrine_ Emergent Wetland lwv ;mall Towns III Bare Land_ lu L rRural Settlements Ill 77

4.8.8. Interrelations of Bare Land Class (Code R. BL) au- LUCID).

Table 4.16. Interrelations of Bare Land.

Change R to # =2,111.42Hectares Change # to R =308.75 Hectares 1973 to 1991Code%Change Area # Poly 1973 to 1991Code %Change Area # Poly 73R to 91B RB 0.06 1.26 2 73B to 91R BR 2.38 7.35 6 73R to 91D RD 18.07 381.59 18 73D to 91R DR 22.19 68.52 7 73R to 91E RE 2.62 55.31 16 73E to 91R ER 18.46 57.00 12 73R to 91F RF 6.31 133.14 29 73F to 91R FR 13.64 42.12 8 73R to 91H RH 2.16 45.69 5 73G to 91R GR 6.28 19.39 3 73R to 911 RI 28.01 591.50 20 73H to 91R HR 0.93 2.86 3

73R to 91K RK 1.31 27.58 2 731 to 91R IR 1.05 3.24 1 73R to 91L RL 0.53 11.12 4 73S to 91R SR 2.31 7.12 4 73R to 91N RN 5.24 110.58 1 73T to 91R TR 31.79 98.16 15

73R to 910 RO 0.77 16.36 1 73V to 91R VR 0.97 2.98 1 73R to 91R RR 6.49 137.06 10 100 308.75 60 73R to 91S RS 1.72 36.25 7 73R to 91T RT 26.71 563.98 34 Total 100 2,111.42 149

Figure 4.23. Interrelations of Bare Land.

RB Change from R (BL) 73/91 Change to R (BL) 73/91 BR RD DR RT 27% RB 0% RE ER 18% RD RF ER 18% RH ID FR RS 2% RI OR RK RR 6% RE 3% HR RL RO 1% RF 6% RN IR RN 5% SR RH 2% RR RL 1% TR RK 1% RI 28% RS RI VR

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class B rEstuarine Subtidal Unconsolidated Bottom lw Natural Vegetation Iu C Estuarine Intertidal Rocky Shore Iw V Dunes lu

Z DPC11 Ocean Water lw I 1Errigated Agriculture II D Estuarine Intertidal Unconsolidated Shore Iwn eiguaculture LI G Palustrine Unconsolidated Bottom Iwn gait Mine II E Estuarine Intertidal Emereent Wetland lwv eibandoned Land II F Estuarine Intertidal Scrub-Shrub Wetland Iwv fourism III -^ H Palustrine Emergent Wetland Iwv Smaii i owns III

R Bare Land Iu L Rural Settlements ILL 78

4.8.9. Interrelations of Natural VeEetation Class (Code T, N, au - LUCID).

Table 4.17. Interrelations of Natural Vegetation.

Change T to # =1,930.66Hectares Change # to T= 2,096.51Hectares 1973 to 1991 Code %Change Area #Poly 1973 to 1991Code %Change Area #Poly 73T to 91B TB 5.09 98.22 36 73B to 91T BT 3.89 81.52 18 73T to 91D ID 12.55 242.35 26 73D to 91T DT 10.17 213.14 31 73T to 91E TE 7.22 139.40 22 73E to 91T ET 7.27 152.33 14 73T to 91F TF 12.76 246.27 57 73F to 91T FT 5.91 123.96 33 73T to 91G TG 21.16 408.60 33 73G to 91T GT 18.18 381.24 31 73T to 91H TH 4.41 85.08 4 73H to 91T HT 3.54 74.23 5 73T to 911 TI 16.69 322.19 31 731 to 91T IT 5.48 114.99 12 73T to 91K TIC 0.66 12.79 1 730 to 91T OT 0.13 2.66 2 73T to 91L U 0.07 1.30 3 73P to 91T PT 0.63 13.28 4 73T to 91N TN 0.31 5.96 1 73R to 91T RT 26.90 563.98 34 73T to 910 TO 0.48 9.20 3 73S to 91T ST 9.35 196.13 11 73T to 91P TP 0.35 6.81 4 73V to 91T VT 8.54 179.05 22 73T to 91R TR 5.08 98.16 15 Total 100 2,096.51 217 73T to 91S TS 11.76 227.11 16 73T to 91V TV 1.41 27.23 12 Total 100 1,930.66264

Figure 4.24. Interrelations of Natural Vegetation.

Change from T (NV) 73/91 TB Change to T (NV) 73/91 BT TD TD 13% TE 7% DTE ET 7% FT 6% DT TB 5% DTF DT 10% o ET TV I% TG El FT DTH GT ffiTI TS 12% DTK sa HT TL HT 4% IT IT 5% TR 5% DIN OT DTO OT 0% PT TL, TN, TP PT 1% RT TO, TP TK TR ST 1% TH 4% TS RT 27% <1% TI 17% TV la VT

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom Iw Natural Vegetation lu Estuarine Intertidal Rocky Shore Iw V Dunes lu 0pen Ocean Water Iw Irrigatedlrrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn Aquaculture II Palustrine Unconsolidated Bottom Iwn 0 salt Mine II Estuarine Intertidal Emergent Wetland lwv Abandoned Land II Estuarine Intertidal Scrub-Shrub Wetland lwv Tourism III Palustrine Emergent Wetland lwv kmall Towns III Bare Land Iu RuralRural Settlements Settlements III 79

4.8.10. Interrelations of Dunes Class (Code V, DU) au- LUCID).

Table 4.18. Interrelations of Dunes.

Change V to # =539.52Hectares Change # to V =227.52Hectares 1973 to 1991Code %Change Area # Poly 1973 to 1991Code %Change Area # Poly 73V to 91B VB 2.55 13.78 11 73B to 9IV BV 4.72 10.73 5 73V to 91D VD 14.41 77.73 10 73D to 91V DV 74.77 170.13 7

73V to 91E VE 2.21 11.91 3 73E to 91V EV 6.25 14.22 1 73V to 91F VF 4.73 25.49 12 73F to 91V FV 1.61 3.66 2

73V to 91G VG 41.56 224.24 4 73P to 91V PV 0.68 1.55 1

73V to 91L VL 0.73 3.96 1 73T to 91V TV 11.97 27.23 12 73V to 91P VP 0.07 0.37 1 Total 100 227.52 28

73V to 91R VR 0.55 2.98 1 73V to 91T VT 33.19 179.05 22 Total 100 539.52 65

Figure 4.25. Interrelations of Dunes.

Change from V (D) 73/91 inVS Change to V (D) 73/91 VB BV BV 5% VT 3% DV 33% El VE I TV EV I r 1 1 VD 14% 0 W. 12% ri. tbs FV VG VR 1% 14 / PV I% VP 03i sim FV 2% /WV

-..:7 VE 2%0 VI- 1 VL 1% MTV VP EV 6% VF 5% DV VG4/% 0 VR n nen 75%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom lw Vatural Vegetation Iu Estuarine Intertidal Rocky Shore Iw V DunesDuna Iu 0Den Ocean Water Iw Irrigated Agriculture II 'Maned Astrieuhure Estuarine Intertidal Unconsolidated Shore Iwn 4auaculture II Palustrine Unconsolidated Bottom Iwn 0 kilt Mine II Estuarine Intertidal Emergent Wetland Iwv kbandoned Land II Estuarine Intertidal Scrub-Shrub Wetland Iwv fourism Ill Palustrine Emergent Wetland Iwy smaii" towns III Bare Land Iu L Zural Settlements III Ban Land 1 80

4:8.11: Interrelations of Irrigated Agriculture Class (Code I. IA) - LUCID).

Table 4.19. Interrelations of Irrigated Agriculture.

Change Ito # =480.32 Hectares Change # to I =1,623.80Hectares 1973 to 1991Code%Change Area # Poly 1973 to 1991 Code %Change Area # Poly 731 to 91D ID 7.17 34.46 5 73D to 911 DI 4.49 72.97 5 731 to 91E IE 6.12 29.38 3 73F to 911 Fl 2.70 43.91 12

731 to 91F IF 3.13 15.05 5 73H to 911 HE 0.09 1.53 1 731 to 91K IK 3.86 18.52 1 73L to 911 LI 6.33 102.86 65 731 to 91L IL 12.76 61.31 69 73R to 911 RI 36.43 591.50 20 731 to 910 10 1.40 6.73 1 73S to 911 SI 30.10 488.82 23 731 to 91R IR 0.68 3.24 1 73T to 911 TI 19.84 322.19 31 731 to 91S IS 40.94 196.64 17 Total 100 1,623.80 157 731 to 91T IT 23.94 114.99 12 Total 100 480.32 114

Figure 4.26. Interrelations of Irrigated Agriculture.

Change from I(IA) 73/91 Change to I (IA) 73/91 IT 1D7% FL 24% 1E6% DI 4% gi DI 5 ID 3%HI 0% 1F3% 1K4% FI ,0 IF HI 1K El LI IL IL R1 13% 010 E SI IR TI IS IT

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom Iw Natural Veeetation Iu Estuanne Intertidal Rocky Shore lw V Dunes lu Open Ocean Water Iw irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn kauaculture II Palustrine Unconsolidated Bottom Iwn 0 ialt Mine II Estuarine Intertidal Emergent Wetland Iwy kbandoned Land Estuarine Intertidal Scrub-Shrub Wetland lwv rourism III Palustrine Emergent Wetland Iwy Small towns III Bare Land lu L Rural Settlements III 81

4.8.12. Interrelations of Aquaculture Class (Code N, IA) (II- LUCID).

Table 4.20. Interrelations of Aquaculture.

Change # to N =496.90 Hectares 1973 to 1991 Code % Change Area # Poly 73 to 91N DN 1.20 5.95 2 73 to 91N EN 5.50 27.35 7 73 to 91N FN 2.90 14.40 3 73 to 91N GN 66.95 332.66 2 73 to 91N RN 22.25 110.58 1

73 to 91N TN 1.20 5.96 1 Total 100 496.90 16

Note: There was no Aquaculture in 73

Figure 4.27.. Interrelations of Aquaculture.

Change toN (A) 73791 ON

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class T ',ridel B Estuarine Subtidal Unconsolidated Bottom lw Natural VegetationVeeetation lu C Estuarine Intertidal Rocky Shore lw V Dunes lu Z Open Ocean Water lw Irrigated Agriculture II D Estuarine Intertidal Unconsolidated Shore Iwn Anuaculture II G Palustrine Unconsolidated Bottom Iwn 0 salt Mine E Estuarine Intertidal Emereent Wetland lwv Abandoned Land F Estuarine Intertidal Scrub-Shrub Wetland Iwv Tourism Ill H Palustrine Emergent Wetland lwv small Towns R Bare Land lu L RuralRural SettlementsSettlements 82

4.8.13. Interrelations of Salt Mine Class (Code 0, SM) (II- LUCID).

Table 4.21. Interrelations of Salt Mine.

Change 0 to=8.92 Hectares Change SI to 0 =67.93 Hectares 1973 to 1991Code %Change Area # Poly 1973 to 1991 Code %Change Area # Poly 730 to 91D OD 28.43 2.53 2 73E to 910 EO 30.68 20.84 2 730 to 91F OF 41.70 3.72 1 73G to 910 GO 21.79 14.80 3

730 to 91T OT 29.87 2.66 2 731 to 910 JO 9.91 6.73 1

Total 100 8.92 5 73R to 910 RO 24.08 16.36 1 73T to 910 TO 13.54 9.20 3 Total 100 67.93 10

Figure 4.28. Interrelations of Salt Mine.

Change from 0 (SM) 73/91 Change to 0 (SM) 73/91

TO 14% EO 31% RO 24%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class

1Estuarine Subtidal Unconsolidated Bottom Iw STatural Vegetation Iu C 1Estuarine Intertidal Rocky Shore lw V DunesDunes Iu

Z 3ven Ocean Water Iw 1 Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn kauaculture II Palustrine Unconsolidated Bottom Iwn 0 Salt Mine II Estuarine Intertidal Emergent Wetland Iwv Abandoned Land II F Estuarine Intertidal Scrub-Shrub Wetland Iwy Tourism III Palustrine Emergent Wetland Iwv Small Towns III R Bare Land Iu L Rural Settlements Ill 83

4.8.14. Interrelations of Abandoned Land Class (Code S. AL) (II- LUCID).

Table 4.22. Interrelations of Abandoned Land.

Change S to # =764.76 Hectares Change # to S =516.91 Hectares 1973 to 1991Code%Change Area #Poly 1973 to 1991Code %Change Area # Poly 73S to 91D SD 2.55 19.46 3 73F to 91S FS 2.33 12.05 5 73S to 91F SF 2.31 17.66 2 73G to 91S GS 2.98 15.40 3

73S to 91H SH 4.57 34.96 1 73H to 91S HS 3.12 16.13 4 73S to 911 SI 63.92 488.82 23 731 to 91S IS 38.04 196.64 17

73S to 91L SL 0.08 0.60 1 73K to 9IS KS 1.75 9.02 1

73S to 91R SR 0.93 7.12 4 73L to 91S LS 0.84 4.32 1 73S to 91T ST 25.65 196.13 11 73R to 91S RS 7.01 36.25 7 Total 100 764.76 45 73T to 91S TS 43.94 227.11 16 Total 100 516.91 54 -a

Figure 4.29. Interrelations of Abandoned Land.

Change from S (AL)73/91 Change to S (AL)73/91

ST 26% SD 3% SF 2% INSD IS 38% KS 2% SR I% SH 5% RF LS 1% oSH SL 0% RS 7% 0 SI

RI, SI 63%, coSR

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class B 'L'stuarine Subtidal Unconsolidated%nom Iw Natural Vegetation Iu C -2;stuarine Intertidal Rocky Shore lw V [DunesDunes lu Z )pen Ocean Water Iw IrrigatedIrrigated AgricultureAgriculture II D Estuarine Intertidal Unconsolidated Shore Iwn Aquaculture II G Palustrine Unconsolidated Bottom Iwn 0 Salt Mine II E Estuarine Intertidal Emergent Wetland I%w Abandoned Land II F Estuarine Intertidal Scrub-Slvub Wetland Iwv Tourism III H Palustrine Emergent Wetland Iwy Small Towns III R Bare Land lu L Rural Settlements III g4

4.8.15. Interrelations of Small Towns Class (Code K, Si') (III- LUCID).

Table 4.23. Interrelations of Small Towns.

Change K to # =11.80 Hectares Change # to K =74.84 Hectares 1973 to 1991 Code%Change Area # Poly 1973 to 1991 Code%Change Area # Poly

73K to 91 F KF 23.49 2.77 2 73B to 91K BK 7.11 5.32 1

73K to 91S KS 76.51 9.02 1 73E to 91K EK 1.10 0.82 1 Total 100 12 3 73F to 91K FK 13.11 9.81 3 73I to 91K IK 24.75 18.52 I 73R to 91K RK 36.85 27.58 2

73T to 91K TK 17.09 12.79 1 Total 100 74.84 9

Figure 4.30. Interrelations of Small Towns.

Change from K (ST) 73/91 Changes to K(ST) 73/91 TK BK 7% EK BK FK EK 13% FK 01K RK IK T K 25%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class I Lucid Class 1 Estuarine Subtidal Unconsolidated Bottom...... lw Natural VegetationVegetatinn hi . Estuarine Intertidal Rocky Shore lw V 1Dunes lu _ C.Den Ocean Water. _ Iw Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn etauaculture II rPalusttine - - Unconsolidated Bottom Iwn "Salt Mine

Estuarine Intertidal Ementent Wetland Iwy kbandoned Land II , Estuarine Intertidal Scrub-Shrub Wetland Iwv rourism . , Palustrine Emergent Wetland Ivey ;mall Towns III Bare Land Iu L Zural Settlements III _ _ _ - i 4.8.16. Interrelations of Rural Settlements Class (Code L. RS) (III- LUCID).

Table 4.24. Interrelations of Rural Settlements.

Change L to=107.19 Hectares Change to L =78.28 Hectares 1973 to 1991Code %Change Area # Poly 1973 to 1991Code %Change Area # Poly 73L to 911 LI 95.97 102.86 65 731 to 91L IL 78.32 61.31 69 73L to 91S LS 4.03 4.32 1 73R to 91L RL 14.20 11.12 4

Total 100 107.19 66 73S to 91L SL 0.76 0.60 1 73T to 91L U 1.66 1.30 3

73V to 91L VL 5.06 3.96 1 Total 100 78.28 78

Figure 4.31. Interrelations of Rural Settlements.

Change from L (RS) 73/91 Change to L (RS) 73/91

LS 4% VL 5% TL 2% SL 1%

RL 14%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class Lucid Class Estuarine Subtidal Unconsolidated Bottom Iw NaturalNatural VegetationVegetation lu Estuarine Intertidal Rocky Shore lw V Dunes Iu loen Ocean Water lw L_Irrigated Agriculture II Estuarine Intertidal Unconsolidated Shore Iwn giauaculture II Palustrine Unconsolidated Bottom Iwn 0 salt Mine II Estuarine Intertidal Emergent Wetland Iwy kbandoned Land II Estuarine Intertidal Scrub-Shrub Wetland lwv tourism LII Palustrine Emergent Wetland Iwv Small Towns III Bare Land lu L RuralRural SettlementsSettlements Ill 86

4.8.17. Interrelations of Tourism Class (Code P, TO) (III- LUCID).

Table 4.25. Interrelations of Tourism.

Change P to # =17.65 Hectares Change # to P =40.00 Hectares 1973 to 1991Code %Change Area # Poly 1973 to 1991Code %Change Area # Poly 73P to 91C PC 1.75 0.31 1 73B to 91P BP 20.08 8.03 2

73P to 91D PD 14.26 2.52 1 73D to 91P DP 61.98 24.79 1 73P to 91T PT 75.21 13.28 4 73T to 91P TP 17.01 6.81 4

73 to 91V PV 8.78 1.55 1 73V to 91P VP 0.93 0.37 1 Total 100 17.65 7 Total 100 40.00 8

Figure 4.32. Interrelations of Tourism.

Change from P (1)73/91 Change to P (7) 73/91

BP 20% P V 9%

PC VP 2% 1%

PD T P 17% 14%

Table 3.7. Codes for Labeling Land Uses and Wetland Classes.

Code Class Lucid ClassCode Class IEstuarine Subtidal Unconsolidated Bottom lw NaturalNatural VegetationVegetation C IEstuarine Intertidal Rocky Shore Iw V Dunes Z ten Ocean Water Iw I Irrigated[nitrated AgricultureAvricuhure IEstuarine Intertidal Unconsolidated Shore Iwn kauaculture IFalustrine- Unconsolidated Bottom Iwn 0 salt Mine- IEstuarine Intertidal Emergent Wetland Iwy .kbandoned Land F Estuarine Intertidal Scrub-Shrub Wetland lwv tourism Palustrine Emergent Wetland Iwy iSmall Towns

R IBare Land lu L RuralRural Settlements Settlements 87

4.9. Spatial Correlation of Wetland Change and Land Use Patterns. Changes in the Tobari system were assessed through the spatial analysis of individual polygons. As stated in the methodology, child polygonswere used for the statistical analysis. Change was consideredas change in class type. Because the overlay map resulted in 2295 child polygons, individual polygon change was not as significant to the total area, because 86% remainedas unchanged open ocean, irrigated agriculture, and estuarine subtidal unconsolidated Bottom (Table 26.a,b). Totalarea of change was only 15.44% if considered with the open ocean class, and 25.58% if only the land / estuarine area (Table 4.26.c) is considered.

Table 4.26. Summary data for change and no change areas and polygons. a) Total area in hectares) and polyrgons Area % Area # Poly % Poly%Area Without open ocean

1Nlo Chang( 57520.48 84.56 289 17.30 74.42 Change 10501.71 15.44 138282.70 25.58 Total 68022.20 100.00 1671 100.00 100.00

b) Area (in hectares) of irrigated agriculture (II), ESUB (BB) and o enocean (ZZ) with respect to total area. Area % Area Poly % Pol:s, II 14606.65 25.39 9 3.11 BB 7969.17 13.85 7 2.42

ZZ 26962.34 46.87 1 0.35 Total 49538.16 86.12 17 5.88

c) Area (in hectares) of irrigated agriculture (H) and ESUB (BB) with respect to totalarea,without considering openocean (L,4'Z) Area % Area Poly %Poly II 14606.65 25.39 9 3.11 BB 7969.17 13.85 7 2.42 Total 22575.82 39.25 16 5.54 Total Area 68022.20 Without open ocean (ZZ) 41059.

Child polygons were reclassified before the statistical correlation analysis by grouping into their corresponding LUCID class for both the 1973 and 1991 classes.This allowed testing of correlationamong the land use pattern classes of LUCID. 88

Data manipulation was carried out by: Dropping from the database all child polygons less than 0.25 ha because they were considered slivers from the overlay. Selecting of child polygons that changed; Grouping of all wetland and human activities into their corresponding LUCID class; Obtaining statistical correlations: Using parent information from total area of each LUCID class in 1973 (Area_73), considering first total change for that class (Chg LUCID_73), and the corresponding area of LUCID class for 1991 (LUCID_91), data were arranged for testing using percentages instead of hectares. The change (Chg_LUCID_73) was computed by considering only thearea that was in other LUCID classes that were different from the LUCID class in 1973 being analyzed;

Chg_LUCID_73 = Area_73 minus the sum of all LUCID 91 different from the LUCID class of 1973.

LUCID 91 = the total of all child polygons that belong to that LUCID class in 1973.

Percentages of change were obtained with respect to total area of LUCID 73 (for each class) and considering the Change in 1991 from 1973:

Chg _LUCID _73 % LUCID_Chg = Area _73

LUCID 91 % LUCID_91 = Area 73 89

The Pearson Correlation Coefficient r considering each LUCID class with respect to all the rest of classes:

XY)-(EA')-(E

Il[nEX2 (E PEY2 (E y)2]

Where: X = %LUCID_Chg Y = % LUCID_91

For each LUCID 73 class, a matrix of correlation was developed considering only the child polygons with change area in LUCID 91. Correlationsare shown in Table 4.27 (a-f). Also note that the table includes the number of parent and child polygons to visualize polygon fragmentation from the overlay. Table 4.27.a. LUCID class Iw showed consistently high correlation with LUCID classes I (1w, Iwn, Iwv, and Iu). In allcases, correlation was 1 or -1. However, there was no changed polygons for classes II and III. Polygon fragmentation was higher for class Iwv, which also resulted the only positive correlation. Changes in LUCID class Iwn, which included non-vegetated wetlands were moderately correlated with all LUCID classes except in thecase of non-vegetated wetlands class Iwn- Iwn, which resulted in an r = -1. For the other classes, the highest correlation was with Iu (upland natural areas), withan r = .64 (Table 4.27. b). Notice the higher number of parent and child polygons in relation to class Iw. In Table 4.27.c, as in all cases, correlation with thesame class resulted in -1 (Iwv - Iwv). These are the vegetated wetlands, which in general presented high correlations with all classes suggesting a high level of interaction with the other classes. In the case of uplands with natural vegetation, they presented the lowest correlations in the 30's, except in thecase of lu-lu. The second higher correlation (r=0.66), was with non-vegetated wetlands (Table 4.27.d). The LUCID class of development (II) that includes human activities suchas irrigated agriculture and aquaculture, also presented high correlations with all but the estuarine unconsolidated bottom (Iw). (Table 4.27.e). Human settlements and tourism 90 presented correlations only with classes Iwv, which it had very few child polygons, and against development classes II and III (Table 4.27.f). In all cases, correlation was -1 when LUCID class in 1973 was compared against the same class in 1991. However, correlationwas from moderate to high in most cases.

Table 4.27. Pearson's Correlation Coefficient, showing total child and parent polygons.

, a. LUCID Class 1973 = Iw b. LUCID Class 1973 = Iwn Chat 4 P(na) #11(chl r # P(pa) #P(ch) r

1w-Iw 3 15 -1.00 Iwn-Iw 20 56 , 0.39 Iw-Iwn 2 14 -1.00 Iwn-Iwn 14 44 ' -1.00 Iw-Iwv 3 125 1.00 Iwn-Iwv 29 122 ' 0.42 1w-Iu 2 33 -1.00 Iwn-Iu 19 88 0.64 1 3 Iwn-II 9 17 0.49 Iw-DI 1 1 Iwn-111 0 0 X

, C. LUCID Class 1973 = Iwv d.LUCID Class 1973 = Iu # P(pa) #P(ch) r ri e o,# P(pa) #P(ch) r Iwv-Iw 57 139 0.65 Iu-Iw 34 86 0.35 Iwv-Iwn 36 94 0.71 Iu-Iwn 53 98 0.66 Iwv-Iwv 87 256 -1.00 Iu-Iwv 77 190 0.56 Iwv-Iu 50 111 0.67 lu-lu 82 254 -1.00 Iwv-II 21 43 0.62 Iu-II 33 94 0.39 5 Iwv-III 6 0.68 , Iu-III 7 11 ' 036

e. LUCID Class 1973=11 1. LUCID Class 1973 = ChasitILIE#P a#P cll_LIL. r. i ' #P sa #P ch r II-Iw 00, X HI-1w 1 1 II-Iwn 5 18 0.68 III-Iwn 0 0 X II-Iwv 9 16 1.00 III-Iwv 2 2 1.00 II-Iu 16 36 0.92 III-Iu 0 0 X II-II 28 69 -1.00 III-II 68 70 0.98 II-III 4 75 1.00 III-M 6 6 -1.00

= Parent Polygons from 1973 # P (Ch) = Total Child Polygons considering only the ones that changed = Correlation Coefficient based on # P (ch) X = Without polygons = Invalid operation (Division by zero) 91

4.10. Government policies related to wetland changes. This research determined that changes of wetland types were correlated with certain patterns of land use and human activities in the Tobari system, with corresponding changes in wetland functions and values. A secondary hypothesis was that government policies have influenced human activities, encouraging certain types of development. Government documents and programs were identified and analyzed to test this secondary hypothesis at the policy level. The concept of "wetlands" is relatively new in Mexico, itsuse being limited to an elite of scientists. More recently, wetlands have been included in thenewer governmental programs, mostly related to wildlife and water management (Cervantes, 1994). While specific wetland policies are still lacking in Mexico, in recentyears environmental policies have broadened to include management of protected naturalareas, international agreements for migratory birds, protection of biodiversity, and the Convention on International Trade of Endangered Species- CITES (SEMARNAP, 1996), marine and coastal conservation (Chapter 17, Agenda 21- UNEP Report, SEMARNAP, 1996). Other efforts have been specifically related to wetlands (RAMSAR, 1971; the North America Tripartite Committee for Wetland Conservation- SEDUE, 1990), that have resulted in an effort to draft a National Wetland Program ([NE, 1994), which isnow in a design phase. Although Mexico currently lacks direct wetland policies, policies found in other sectoral programs, such as water, fishing, agriculture, and education, have indirect effects on wetlands. For instance, mangroves are considered critical habitat, because of their role in coastal productivity and support for biodiversity. The threemangrove species common in the Tobari system, Red (Rhyzophora mangle), Black (Avicennia genninans) andWhite (Laguncularia racemosa), are all considered species with status of "Special Protection" (Diario Oficial, 1994). Furthermore, itwas established that use of this habitat, which supports rare, threatened, or endangered species, should be conditioned in order to "guarantee" their conservation according to mandates of all related laws (Diario Oficial, 1994). 92

Mexico has three important governmental characteristics that have resulted in patterns of development: a strong centralized government, a planning system based on a sectoral approach, and an emphasis on promoting inland (non-coastal) oriented activities (Merino, 1987). Therefore, predominant control, major development policies, and economic support come from Mexico City. Even tax participation at the state level is limited. Revenue and sales taxes are sent to the federal government; then, basedon a previously defined annual budget, a certain percentage willcome back to the states. To understand the major governmental policies affecting wetlands, it is important to briefly summarize the evolution of environmental policy in Mexico, and how it has affected the regulation of development. Environmentalprograms are the responsibility of several agencies, representing the sectoral approach that has characterized Mexico's planning framework. These agencies correspond to the followingareas: forestry, fishing, wildlife, protected areas, water, and soils. At the beginning of the 70's, pollutionstarted to be a consideration within the government agenda, particularly pollution that could represent a health hazard. Thus, a branch within the Secretariat of Health was created: the Subsecretariat of Environmental Health in the Luis Echeverria administration (1971- 1976). After this period, there were minor modifications of environmental policies until the early 80's, although Jose Lopez Portillo's administration (1977-1982) did include some environmental issues in federal programs, modifying federal laws and administrative rules. A new agency, the Secretariat of Ecology and Urban Development (SEDUE)was created by Miguel De la Madrid (1983-1988), that included departments of ecology, protected areas, wildlife management, pollution control, and urban development. This agency had several problems, because of the way it was organized. A new budgetwas not assigned to it, but rather the agency obtained itsresources through transfer from other agencies that were losing responsibilities, personnel, budget, andpower. This situation, plus the overwhelming responsibilities assigned to the SEDUE, causeda very slow maturing time. SEDUE continued during the firstyears of Carlos Salinas administration (1989-1994). In 1992, SEDUE changed to the Secretariat of Social Development (SEDESOL), emphasizing sustainable development froma grass roots perspective. Nevertheless, it represented a setback from previous administrations, because wildlife 93 management was separated from protected areas, and rural development was still within the agriculture and forestry sector (Mumme and Sanchez. 1992; Munune et al,1988). In the current administration, President Ernesto Zedillo (1995-2000) has createda new agency: the Secretariat of the Environment, Natural Resources and Fishing (SEMARNAP). This agency represents an effort "to integrate environmentalmanagement and regulation efforts into one single agency" (SEMARNAP, 1996), with its subsequent shifts in budgets, personnel, and adjustment of administrative and legal responsibilities and procedures. A summary of major changes in the last four presidential administrationson development and environmental policies include:

Re-designing of government structures through institutional modifications; Stronger environmental policies through modernization of laws and procedures for their application; Decentralization of governmental responsibilities; Emphasis on promoting public participation in planning and decision making (SEMARNAP, 1996; Mumme and Sanchez. 1992; Murnme et

al,1988).

4.10.1. The National Development Plan. The National Development Plan is the overall document that establishes the governmental policies for each presidential administration. The Plan 1995 -2000 establishes five fundamental objectives:

National sovereignty; Justice and social harmony based on the law; A democratic economic development process with an emphasison public participation; 94

S Advancement in social development based on regional equity and justice; and,

CO Promotion of a strong and sustainable economic development (PLANADE, 1995).

The sustainable economic development objective considersa global and regional equilibrium among economic, social, and environmental objectives, by reducingor eliminating environmental deterioration, and by promotinga land use planning process to determine the best land uses in accordance with regional environmental capability. The document establishes full and sustainable utilization of naturalresources as a basic consideration to reduce poverty, while caring for the environment and naturalresources from a new perspective of changingconsumer patterns and stronger enforcement of laws (PLANADE, 1995). The plan also states that to promote the compliance of environmental regulation an incentive system will be created. Theuse of economic means will avoid externalities, and, at thesame time, favor those who protect the environment and natural resources (PLANADE, 1995). The National Development Plan is complemented by the National Program for the Environment. This is a more specific document that states clearly at the beginning that the big challenge is to achieve sustainable development, and underlines the importance of economic and social factors including market and non-market values,open access to natural resources, the use of environmental indicators that couldsuggest thresholds for sustainability, correcting failures in institutional arrangements, and developing better information to support objectives and internalizecosts (SEMARNAP, 1995). As a general objective, this program establishes that it willstop environmental, ecosystems, and natural resource deterioration through the establishment of guidelines to restore and rehabilitate ecological conditions to allow social and economic development within criteria for sustainability. Table 4.28 presentsa list of the means (instruments) to accomplish the environmental policiesas established in the program, and Table 4.29 shows a list of the strategies, projects and priority action programs. 95

Table 4.28. Means (Instruments) of Accomplishing Environmental Policies in Mexico.

Protected Natural Areas Direct Regulation of Wildlife; Land Use Planning Program; Environmental Impact Assessment; Risk Studies; Official Mexican Norms (administrative rules); Direct Regulation of Materials, Dangerous Wastes and Risk to Health; Direct Regulation of Industrial Activities; Self-Regulation (non-regulatory approach); Environmental Auditing; Economic Means (instruments); Ecological Criteria; Environmental Information; Education and Research; Agreements and Participation; and, Verification, Control, and Surveillance.

Table 4.29. Environmental Strategies, Projects and the Priority Action Program.

Conservation and Sustainable Utilization of Biodiversity and Protected Areas; Recuperation, Activation and Decentralization of National Parks; Productive Diversification and Wildlife in the Rural Sector; Environmental Protection of the Coastal Zone; Land Use Plan Program for Regional Development; Actualize the Environmental Regulation; Reduction and Management of Hazardous Wastes; Promotion of Environmental Infrastructure and Productive Diversification; Promotion of a Sustainable Urban Development; Development of a National System of Environmental Information; Federalism and Decentralization of Environmental Management; Education, Training, and Research; Promoting Public Participation; Active Presence and Efficient Participation in InternationalAgreements. 96

The environmental protection of the coastal zone is the strategy most closely related to wetland conservation and management; however, the word "wetlands" is mentioned just once as: "...Elaborate inventories that allow the establishment of point sources of ocean degradation, such as waste water treatment and industrial plants, municipal water discharges, power generating plants, tourism facilities, aquaculture, alteration of habitat (dredging, filling of wetlands, mangrove extraction), introduction of exotic species." (PLANADE, 1995)

Therefore, wetlands are consideredas an important part of the coastal zone, with policies of coastal zone management applied to them.

4.10.2. The Sonora Development Plan. If the National Development Plan is too general and lacks specific information pertaining to wetlands, the State Development Plan is centered in the idea of "increasing progress." Emphasis is on policies for regional development, urban planning, mineral

extraction, improvement of services and facilities, promoting industrial development,and recovering the economic participation of the agricultural and fishingsectors (Gobierno del Estado de Sonora, 1992). Environmental policies related to wetlandsare broad and oriented towards a balanced development considering protection of naturalresources, by promoting the development of a coastal land use plan that would identify theresources most sensitive to development and allocate the bestuses with minimum conflicts. On the other hand, aquaculture activitiesare emphasized as a feasible economic activity for the Sonoran coast, mentioningaspects of the high requirements in terms of techniques, funding, and encouragement of private andgovernment alliance. Emphasis of the State Development Plan is to achieveprogress in all economic development areas; however, it also establishes the needto accomplish this through the increase of social welfare, by reducing pollution andoveruse of pesticides and ground water (Gobierno del Estado de Sonora, 1992). 97

4.11. Policy Issues in the Tobari system. From the results of the change map, three human activities were the most important in terms of area and correlation to wetland changes: agriculture, water management, and aquaculture. Other documents were reviewed to complement the information on governmental policies specifically related to agriculture,water, and aquaculture, and their presence in the Tobari system.

4.11.1. Agriculture. Agriculture has been a major economic activity in Sonora, particularly in Southern Sonora, since the beginning of this century. Asa part of the "inland" oriented activities, agriculture was favored by the fertile soils of the Yaqui and Mayo river deltas, and the almost permanent availability of water. Since food production, especially for grains,was a priority for the government, agricultural development history has been markedby periodic governmental subsidies for acquiring technology and for compensation of market conditions and development priorities at national levels. The federal government promoteda series of activities guided by development policies related to agriculture, suchas self-sufficiency in grains, opening more agricultural land, and social justice, all focusedon the development of the Yaqui and Mayo valleys. Support from government came in differentways: establishing incentives for crop types and industrialization, financing of infrastructure for water reservoirs and irrigationcanals, control of prices, and compensation for international market fluctuations (Sotoet al, 1991). Extensive use of agrochemicals in the form of fertilizers and pesticideshas been a common practice. Meisner et al (1992) mentioned that farmers of the Yaqui Valley have been using chemical fertilizers since the 1960's in advanced, high input,high yield farming characteristic of Green Revolution technologies. Other regular government subsidieswere allocated for drought periods, in the form of insurance againstcrops loss and loans for farm operations with reduced interest rates (Rojas, 1991). More recently, an important government subsidy that has promoted 98 the use of agrochemicals and increased the demand for continued land labor is the Procampo program. Rice (1995) describes it as:

"a strategy from President Salinas, a Mexican plan to replace current supports which hold domestic grain and oilseed prices substantially above world prices. PROCAMPO will gradually realign domestic prices with the international market (PROCAMPO 1993). This strategy will represent a loss of income to farmers. To replace that income, PROCAMPO pays direct supports to farmers based on past number of hectares farmed in the target crops. For example, a subsistence corn and bean farmer receives the same amount per hectare as the highly intensive maize farmers of the Yaqui Valley who produce surplus grain for sale. PROCAMPO's direct payments allow farmers to change crops and let their planting decisions be determined by the marketplace as longas the land is in productive use or is dedicated to forestry or conservation (Bonilla and Viatte 1994)".

The Procampo program promotes agricultural lands to be active, thus farmers have to show that they are working the land in order to qualify for governmental compensation. Certain farmers have taken advantage of Procampo, by planting latecrops, even though they might not obtain good production,or even worse, knowing their crop will not have a market. Nevertheless, they will get government compensation. This policy has direct effects on land erosion, overuse of chemicals, and misuse of irrigationwater. Another important issue related to governmental policies affecting agriculture activities are the modifications of the law affecting the cooperative andcommon status of ejido lands (Art. 27 from the Mexican Constitution), these landswere regionally allocated for exclusive agricultural use and undera communal property regime. With the modifications at the federal level, ejido landscan be legally partitioned into individual parcels, with the possibility of changing the land ownership to privateproperty. This change in the law can lead to land speculation and facilitating landuse changes by loosening the protection of exclusive agriculturaluse.

4.11.2. Water. In relation to water, the National Water Law established the first definition of wetlands within a federal law: 99

"Wetlands are transition zones between terrestrial and aquatic systems, which constitute seasonal or permanent flooding zones, which are subject or not to the influence of tides, such as swamps, marshes and sloughs, delimited by hydric vegetation present permanently or seasonally. Soils are normally hydric. They also include areas such as lakes or soils permanently wet, by the discharge of a natural aquifers." (SARH, 1994)

This definition, although it might cover most wetland types in Mexico, does not provide a good field definition, nor will it help in terms of legal wetland delineation. Wetland has generally not been a problem in Mexico, because most issues with wetlands are related to land or resources under Federal control. An important consideration related to the inland orientation of government policies, is the idea of using all freshwater for different "land" purposes suchas urban development, industry, and agriculture. However, the environment has not been considered as another "user;" therefore,every drop of water coming into an estuary, represents water "lost" from the government perspective (Escamilla, 1991). With this point of view, the water going into the wetland systems isseen as waste water. Therefore, it is clear why 13 ditches dump waste water from industry, farms, agricultural uses and rural communities into the wetland system. Another aspect of water management has to do with the privatization of water management within the irrigation districts. Formerly, the National Water Commission had the responsibility for water control, from the rivers to the reservoirs to irrigation districts. Now, through a gradual release of responsibilities, the National Water Commission delivers the water into the district, from where water users, organizedas cooperatives, are in charge of administering water quotas and scheduling irrigationpatterns. This situation has interesting effects on wetland management, because itopens up the possibility for identifying externalities of responsibleusers, and thereby the possibility for internalization of the costs of cleaning up run-off water. 100

4.11.3. Aquaculture. An important activity for the government,as well as private enterprise, aquaculture is considered a feasible alternative for food production, labor opportunity, economic development, and a practical way to use marginal lands not appropriate for agriculture and housing (Secretaria de Pesca, 1990). Aquaculture has also been suggestedas a measure for conservation of marineresources, because it would reduce pressure from free market fishing (Secretaria de Pesca, 1990). A good proportion of the existing land-based aquaculture farms is locatedon converted wetlands (Pillay, 1992). Several global examples existon overuse of coastal areas, particularly for shrimp farming, such as the Ecuador experience (Perez, 1988). For the state of Sonora, it has been suggested in the National Program for Comprehensive Aquaculture Development, that around 400,000 hectares would have potential for shrimp farming, considering the potential of all thecoast. For the Tobaii system, there are two main aquaculture development projects, the Parque Camaronicola El Tobariin the north and Sian in the South. These developments have modified about500 hectares.In a personal interview with an engineering-constructioncompany, they reported to have 60 new projects varying in size, all of them on the Southern Sonora coast. Therefore,as Pillay (1992) explains, conflicts with otheruses and possible adverse consequences of converting wetlands into aquaculture farmsare major considerations that need to be addressed. 101

CHAPTER 5

DISCUSSION AND CONCLUSIONS

"Humans and wetlands are interdependent. The better we understand that interrelationship, the greater the possibility for a sustainable coexistence" Anonymous

This chapter analyzes results in terms of the effectiveness of the model in evaluating land use change. Human-wetland interactions in the Tobari systemare assessed through integration of the database. Integration of disparate datasources is an important research contribution of the science of Geography, by relating considerations ofspace and time and looking at the interconnectionsamong physical and biological sciences, culture, economics, and government policies.

5.1. Problems in wetland classification and identification. Classification of wetlands has been a major area of research, evolving during the 70's, 80's and 90's (Lyon, 1993; Lewis, 1995). It has responded to regional and national geographic differences, conflicts and compatibility, and management and legal considerations; thus, the research design varies according to thepurpose of each study and the resolution desired. In Mexico, this process has just begun; therefore, for this study, itwas decided to keep the classification as close as possible to the Cowardinet al (1979) wetland classification, because this system has been applied to most of the continental United Statesas well as other countries. The few previous classification studies in Mexicowere not conclusive in terms of which system to use. The use of Cowardin's classification also allows other wetlandmanagers to easily compare results. In applying Cowardin's classification,no problems were encountered down to the class level; however, further testing will be required for the subclass level and the use of modifiers to allow for regional differentiation. 102

5.2. Advantages and disadvantages of materials used for analysis. The selection of materials was an important consideration for the development of the procedural model. One of the original ideas for the contribution of this researchwas to establish a feasible method that would use materials and equipment widely available throughout Mexico. Therefore, conventional black and white aerial photography, simple stereoscopes and maps for georeferencing were selected as the basic materials. Topographic maps used for registering the photos and referencing of field data were made at the beginning of the 80's (INEGI topographic and thematic maps, various dates). Today those topo maps could have greateraccuracy in terms of data sources and a global positioning system support. However, theyare what is available. Data processing was the most demanding part of the project in terms of technology. Use of a PC-computer with specialized software suchas the Terrasoft GIS, is not common in Mexico; however, they are now becoming available in most of the state governments, research centers, and universities.

5.3. Spatial accuracy in data transformation and methodological problems. Error will exist while using different sources of data and available technology. Cartographic accuracy should be maximized at all times; however,accuracy can only be as good as the materials, equipment, and techniques used. There were different sources of error in this research, includingerrors in interpretation, digitizing, and processing. Photo georeferencing and rectificationwere lengthy procedures that needed to be repeated each timea correction was made when checking for data consistency. In an effort to estimate the magnitude of error, I conducted field work for ground truthing the classification; I also used comparisons with topographicmaps. Mendoza (1994) compared topographic maps with the interpreted and geocorrected photo information. He found that when themaps were overlaid, there were some registration errors; however, none of them was in error by more than 50 meters, and, in most cases, they were in error by less than 20 meters. Interpretationerrors were found in polygon misclassification. This occurred where ground truthingwas not possible. In those areas, 103

air photo interpretation was inferred from the areas where field visits for ground truth reinforced the classification. Some classes were easier to interpret because of similar characteristics. The prints of the 1991 photo series had less quality than theones from 1973, which were more uniform and higher contrast.

5.4. Tobari wetlands in 1973 and 1991. Water conditions and soil types are determinants for vegetationpresence; together, these three components are used for the identification and delineation of wetlands. Theyare used in this study as a basis for discussion of the Tobari system changes. Sources of water to the system include tides, rivers, ground water and runoff water, all of which have been affected by human activities. Although tidesoccur twice a day, their influence on wetlands is altered by sedimentation patterns. Water movement due to tidalrange in part of the study area was drastically changed bya dirt road over a dike, partially blocking water movement. The ten meter bridge to a barrier beach does not allow enough water flow to enter the system through the north and south mouths. Before the construction of the road, the water mixing, influenced by tides, served as a flush in- flush out system. Now this lack of mixing has reduced the system capacity for ocean/estuarine water exchange;water quality has also diminished because of residual waters from drain discharges, witha direct effect on estuary activities especially fishing and aquaculture. Modification of water quality has also reduced the system's ability to maintain its ecological roles for aquatic and terrestrial wildlife, namely reproductive and feeding activities, and nesting grounds. Rivers, which provided freshwater on a regular basis, have been reshaped by human construction, such as canals and ditches. Now, rather than havinga seasonal input related to the rainy season, their flow is continuously regulated by irrigation activities. All soils within the system and the surrounding areasare saline (Valenzuela and Esquer, undated). However, the salt content in the soils is influenced by the mixing of marine and freshwater, by seasonal floods, and by water evaporation. Inareas where water circulation and sedimentation patterns have changed, soil salinity has also changed and, as a result, plant distribution is affected. Increases in soil salinity also have caused agricultural parcels to be abandoned, at least for some time while freshwater is usedto 104

"wash" soils. Abandoned land changed from 929.6 ha in 1973 (Table 4.2) to 628.74 ha in 1991 (Table 4.3), indicating that some parcels were incorporated into irrigated agriculture. In other cases, salt tolerant natural vegetation recovered in those areas (Figures 4.9 and 4.11). Human - wetland interactions were more diverse in areas where changes in water, soil conditions and vegetation are taking place. These areas are best represented in the Tobari system by the estuarine intertidal (EIUS, EIEW and EISS) and Palustrine systems (PUB and PEW) which together in 1973 included 6,896.15 ha, and in 1991 7, 377.74 ha (Figure. 4.9 and 4.11). These wetland classesare distributed in two main zones; the north, with the influence of the north mouth andan extensive coastal plain with discharges from five drainage ditches, and the south portion of the system, with a wider and deeper mouth, containing a series of subsystems with inlets and outlets associated with the outfall of eight drainage ditches. Although the south portionwas not accessible by water because it was too shallow (Figure 2.1), from the oblique videography it could be seen that mangroves in this portion of the system were taller than in the north portion.

5.5. Wetland functions and values. Wetlands, being closely related to hydrologic systems and representing "islands" with high biodiversity and productivity, have been consideredas indicators of environmental health. In an effort to identify environmentally sound alternatives for development, a series of indicators (functions and values) have been proposed by various investigators to assess and monitor development (Environment Canada, 1991). Furthermore, an assessment of wetland functions and values, contributesto a fuller understanding of wetlands in nature and their relationships to human life styles. Because wetland functions have not been fully identified for Mexican wetlands, their value is underestimated. While wetland distribution, classes, and interactions with other ecological systems are essential information, assigning valueto them requires a knowledge of their functions. Often, wetlands are assessed in non-monetary terms, focusingon their contributions to society (Wellman, 1995; Barbier, 1993; Costanza et al 1989). However, 105

this is usually done as a part of an environmental impact assessment, individual or cumulative, and as part of a procedure to evaluate mitigation requirements. Much work is still needed to include these assessments within thescope of regional planning and development processes. Protection of wetland functions is often the most cost-effective way to assure wetland services. At the international level, wetland restoration and creation has recently been given some attention because development interests have promoted themas a means of compensatory mitigation (Kusler and Kentula, 1990). Several considerationsare involved in restoring or creating a wetland: regional differences, the functionor set of functions that are guiding the replacement project, and the conditions imposed for issuing the permit for development (Kentula et al, 1992). Because of its size and complexity, replacement of Tobari functions and values, would probably not bea reasonable economic alternative for development. There are limitations in any case; the complexity of wetland functions make full replacement a very difficult task, both as toscope of design and for monitoring the conditions imposed on the project. This suggests thata well designed development plan should include the benefits of maintaining wetlands in their natural conditionsversus the high costs of replacement.

As stated in previous chapters, wetland functions and valuesare not well defined in Mexico. For this analysis, functions and values for wetland classeswere obtained from the literature. Based on the assumption that general wetland classes perform certain ecological roles, generic functionswere used to infer services that the Tobari wetlands offer. These services are listed in Table 4.5. The social values associated with their services should be considered as "potential values," since valuesare dependent on cultural and economic conditions. "Actual" wetland valuesemerge from people's awareness of wetland functions. Some services and values alreadyare recognized by local people in the Tobari system, such as those related directly to their economicsystem (i.e.: commercial and sport fishing, and tourism). However, thereare other services and values related to water quality and climatic regulation that would takesome time to be recognized by wetland users and governmental agencies. 106

Identification of functions and values offer several advantages. They can be applied as criteria for classification systems, as shown in the summary tables of wetland functions and values (Tables 4.4 and 4.5). Given the need for standardized information related to wetlands in Mexico, a simple system for wetland classification based on functions and values could offer a suitable approach to accomplish an inventory and assessment procedure for evaluating wetland conservation priorities. Such a system would provide quantitative and qualitative information on wetlands. An example of this system is suggested in Table 4.6, where wetlands are classified as non-vegetated wetlands, vegetated wetlands, and wetlands with a rocky stratum. Although this classification requires a finer detail, it could be adapted for other wetland types and used for comparison purposes.

5.6. Human activities adjacent to the wetlands. During the first years of this century, river canalization and land subdivision took place in the Yaqui and Mayo valleys, delineating the spatial distribution of economic activities to the present day. Based on the fertility of soils, the mild climate, the availability of water and the potential markets, both within Mexico and with exports to the United States., the success of agricultural development was predicted early in this century.

".... By proper exploiting the Mexican markets, all the wheat, beans,corn, rice, butter, lard, cured meats, cotton and many other products can be sold.... The completion of the Panama Canal and the Southern Pacific Railroad into Mexico City will give an additional stimulus to West Coast Agriculture, and will put the Yaqui Valley in connection with the world's best markets." Mackie, 1911

Predominant human activities in 1973 were related to agriculture and fishing. While major infrastructure investment was related to agriculture,some tourism development was taking place on the Huivulai island although, because of lack of facilities, it was more a local recreational area thana tourist destination area. 107

Human activities diversified somewhat by 1991, although agriculture was still the major economic activity. Expansion of land for agriculture occurred in the southern portion of the system, affecting primarily upland natural vegetation in the conversion process. Fishing remained centered in the two human settlements of Pared6n Colorado and Paredoncito (Figures 2.1 and 4.11). Aquaculture was an important addition with the development of two shrimp farms (498 ha), occupying areas in which soil salinity would not allow agriculture to be developed. The two major modifications to the landscape were the construction of canals for obtaining estuarine water, and for water discharge into the estuary. In both cases, they were constructed next to mangrove areas and modified patterns of water circulation. Also, some areas were filled for roads and for aquaculture pool dividers. In personal interviews, several ejidogroups (communal structures of land tenure and administration) stated that they have plans to use their lands for building shrimp and oyster farms. Another change was the development of two sites for salt mining. The operations are located in the north portion of the system, just above the north mouth, and the second, near Pared6n Colorado, totaling 68 ha. Salt mining is expected to increase; however, some areas previously intended for salt development are now being considered for shrimp aquaculture.

5.7. Changes of wetlands and human activities. Since change analysis was an essential component of this research, its design provided the specifications for data structure and the spatial analysis methodto be used. For this study, individual polygonswere used to obtain change analysis. Changes perceived in the Tobari system include the modification and conversion of wetland and upland areas. However, changes in wetlandareas include the increase or decrease of wetland functions and values. Thearea of estuarine mangroves increased 45.5% over originally estuarine water coveredareas, bare land, emergent grasses and dune lands. Most of these modifications were identified at the north and southpart of the Tobari wetland system due to sedimentation, aquaculture,water discharges and agriculture drainage ditches. However,mangrove lands were also transformed by a small 108 percentage for aquaculture, agriculture and small towns development. In general, mangroves contributed more for the vegetated system between 1973 and 1991 in the Tobari system. Mangroves performed 19 functions and 27 values and expandedover a total area of 579.77 ha, mainly in the north and south areas of the system. Sedimentation caused by drainage outfall and aquaculture discharges, could have been a major factor within this process. Emergent grasses expanded to 151.97 ha. The total area of emergentgrasses increased 17.05%. Their hydrologic and chemical functions also increased. Their values within migratory processes, food chain support as well as air and water quality prevailed and increased in the north part of the system,as fresh water discharges from agricultural ditches could have promoted their development. The area of shore land (as non-vegetated intertidal areas) increased 6.99% during this period, representing a very small change in totalarea. Some shore land was transformed into dunes and bare lands that lost the influence from tides. A decrease in natural vegetation and bare landsareas was appreciated while such classes were converted into vegetated and non vegetated wetlands. In the north part of the system, shore land areas were taken bymangrove growth. Sedimentation and fresh water discharge from agricultural ditches in thisarea might have influenced this change. Aquaculture siteswere built in the north and in the center of the system. Topographic modifications to these sites could have affected water circulation patterns, thus increasing tidal influence over originally palustrine land and loosing other areas because water circulation was lost. In the south, sedimentation caused natural vegetation, emergent grasses and mangroves to developover intertidal shore and areas previously covered by estuarine water that became shallower. The presence of halophyte grasses decreased 14.20% reducing theirarea in 143.87 ha for 1991. The functions and values of halophyte grasslands also decreased.These vegetated areas were transformed into salt mines, aquaculture and modifications of the dirt road. The fill-in road itself, promoted sedimentation, particularly where it joinsto the mainland, and this allowed some mangrove growth. 109

The area of estuarine water areas decreased 2.25%, losing 190.65 ha, thus its functions and values were also modified, since major changes were into bare lands, tourism and small town development. Flooded areas (represented as palustrine areas) in the Tobari system decreased 8%, loosing a total of 223.86 ha. Moderate change in functions and values were perceived within this process from flooded areas into salt mines, bare lands and abandoned lands. However, some natural vegetation areas and emergent grasses and dunes were also transformed into flooded areas. To illustrate how the Tobari system was modified, a change map was designed to show the spatial distribution of changes and to differentiate the magnitude of change. The spatial distribution was identified by assigning a simple boolean field into the database,so that each polygon was reclassified as no change if it maintained thesame class as in 1973, and was marked as a changed polygon if the class changed. The magnitude of changewas determined by using the percentage of change with respect to the 1973 area; therefore, there was a tendency for smaller polygons to be marked with higher change than larger polygons, with the same number of hectares undergoing change. Nevertheless, thismap offers the opportunity to identify change in terms of spatial distribution with a relative measure of magnitude (Figure 4.13). By looking at the change map, data verification was a complementary activity. Some errors were identified, such as in the case of the northwestcorner, where a large polygon was identified as an area with very high change (red polygon near the mouth). This was verified as an interpretation error, because a sand area was confusedas an estuarine intertidal unconsolidated shore. However, for the most part, theerrors were not significant, and they were corrected. On the rest of the change map, major changes occurred in the more dynamic wetland classes estuarine intertidal and palustrine wetlands, the lands associated with drain discharges, and the areas of influence of the small towns (Figure 4.13). A total change for each class is shown in Table 4.7. and Figure 4.14. This provides the overall information on the total system change. In this study, there has been an emphasis on exploring changes in terms of wetland functions and values; therefore, the 110

total change tables are used to consider functions and values associated with each wetland class. In using the summary tables for functions and values (Tables 4.4 and 4.5), the analysis was done by adding the total functions and values for each wetland class as shown in Table 5.1. This number can be used as a weighting factor to getan estimate of the relative importance of changes, in terms of wetland functions and values, as shown in Table 5.2.

Table 5.1. Total functions and values for the Tobari wetland classes. Total Functions = 20; Total Values = 30

Class FunctionsValues Class Functions Values EISS 19 27 PUB 9 11 EIEW 19 24 EIRS 6 9 PEW 16 26 EIUS 4 16 ESUB 6 8

EISS-Estuarine intertidal scrub-shrub PUB - Palustrine unconsolidated bottom EIEW-Estuarine intertidal emergent wetland EMS- Estuarine intertidal rocky shore PEW - Palustrine emergent wetland EIUS - Estuarine intertidal unconsolidated shore ESUB - Estuarine subtidal unconsolidated bottom

The relative change to wetlands functions and values for the Tobarisystem is presented in Figure 5.1, by using the percentages of net change and those weighted by functions and values. The weighting procedure included several assumptions: The total number of wetland functions and valueswas taken from Tables 4.4 and 4.5; however, this was not an exhaustive list, and therefore should be modified with a specific list for the wetlands being analyzed; There is no distinction among different functions, andamong different values. In some cases a wetland function could bemore important within the hydrological system, or in filtering pollutants; however, in thiscase, all were counted equally.

Wetland values are "potential" values, since they dependon cultural, economic and technological conditions. 111

Functions and values may not be uniform throughout the system, but for this analysis they were considered homogeneous. These assumptions require caution in interpreting the data.

Table 5.2. Weighting Factor based on Wetland Functions and Values.

Vegetated Non Vegetated Rocky Stratum

Class EIEW EISS PEW ESUB EIUS PUB EIRS Totals I Code El F H B D G C. Area73 1013 1219 208 8491 1683 2772 12 15398 Area91 870 1799 360 8301 1801 2548 24 15702 Net Change -144 580 152 -191 118 -224 12 303 % Net Glum -47 191 50 -63 39 -74 4 100 Fun-Weight-73 19256 23168 3328 50948 6732 24951 71 128454 Fun-Weight-91 16522 34183 5760 49804 7202 22936 143 136551 Chng-Func -2734 11016 2432 -1144 470 -2015 72 8097

°A) Fun Cling -34 136 30 -14 6 -25 1 100 Val-Weight-73 24323 32923 5409 67931 26928 30496 107 188115

Val-Weight-91 i 20870 48577 9360 66405 28809 28033 215 202269 Cling-Value -3453 15658 3951 -1525 1881 -2462 108. 14154

% Val Cling -24 111 28 -11 13 -17 1 100 _ _

Guide for Table 5.2. Class The wetland class. Code Code used in database. Area73 Total area (ha) in 1973 (for that class). Area91 Total area (ha) in 1991 (for that class). Change The change in area (ha) for that class 91-73. % Ching Percentage of change respect to total Net change (for all classes). Fun-Wei-73 Total area (ha) in 1973 multiplied by total functions for that class. Fun-Wei-91 Total area (ha) in 1991 multiplied by total functions for that class. Cling-Func Fun-Weight 1991 minus Fun-Weight 1973 % Fun Chng Percentage of chng-fimc respect to total Chng-Func (for all classes). Val-Wei-73 Total area (ha) in 1973 multiplied by total values for that class. Val-Wei-91 Total area (ha) in 1991 multiplied by total values for that class. Chng-Value Val-Weight 1991 minus Val-Weight 1973 % Val Chng Percentage of Chng-Value respect to total Chng-Value (for all classes).

In Figure 5.1, three series of percentagesare presented to compare visually the relative importance of change by considering functions and values. The change for wetland area is 302 hectares; however, the total wetlandarea is composed of different classes. It is possible to identify individual participation by wetland classes, anduse a coefficient to define the relative importance of change in terms of functions and values. In 112

Figure 5.1. Changes in Areas, Functions, and Values for the Tobaii System.

200.00 o

150.00 ea to 0% Total Chug 1100.00 % Fun Cling C EISS 0 A% Val Chug ri 50.00 0 I II I 0.00 6 II PEW A EIUS El 6 6 -50.00 o o FEW o ESUB PUB -100.00 Wetland Types

Figure 5.1 the more the points are separated from the "0" line, whether positiveor negative, the more significant will be that class to the overall change. Since vegetated wetlands (EISS, EIEW and PEW) offer a higher number of functions and values, theyare more significant. Non-vegetated wetlands (ESUB, EIUS, PUB) are not as significant, because their functions and valuesare less, and the change area was also smaller (Table 5.2).

Interactions of human activities and wetlands were illustrated in the interrelation graphs and tables in chapter four, which show data in two letter codes, the first letter being the class in 1973, and the second, the class in 1991. These graphs show, interms of percentages, how the change occurred in both directions, from each class of wetland and human activity to all the other classes. A second graph shows results going theother way, that is, what percentages of other classes contributed to the totalarea of each individual class. The graphs also illustrate the dynamics of landuse change, since they present the data on the different class interactions. For instance,a net change for a class can be a gain of 100 hectares, that will be the result of all hectares gained minus all hectareslost; however, by looking at these graphs, the proportional change for each individualclass 113

indicates how the interaction is taking place considering all change related classes. A discussion of human- wetland interactions follows for each of the wetland classes. It is focused only on wetland classes; however, these graphsare also useful to check for data consistency both in wetland and uplands, particularly for classes where the spatial distribution suggests that there could be a mistake in the database. Estuarine subtidal unconsolidated bottom- ESUB (Figure 4.16), interacted with EIUS, EISS, and EIEW. All of these classes share several areas of the system. Natural Vegetation and Dunes areas also interacted with these classes. Estuarine intertidal rocky shore- EIRS (Figure 4.17) was very small, limited to the dirt road to the island. Therefore it interacts mostly with ESUB, and, in theareas that joins the road to the mainland, it interacts with EISS, and where the road joinsto the island, with Tourism. Estuarine intertidal unconsolidated shore- EIUS (Figure 4.18) presents interactions with 11 classes, showing more diversity in interactions, mostly with other wetland areas and bare land upland area. Palustrine unconsolidated bottom- PUB (4.19) presented less interactions. However, it was the wetland class most closely related to aquaculture development, and interacted with EIUS and natural vegetation. Estuarine intertidal emergent wetland- EIEW (Figure 4.20) also presented a diversity of interactions, especially with EIUS, EISS and PUB wetlands, and with natural vegetation and bare land upland areas. Estuarine intertidal scrub-shrub- EISS (Figure 4.21) had the most significant increase in area, with an extensive growth into ESUB, mostly attributed to high sedimentation rates that have been making the system shallower. Otherstrong interactions were with EIUS and natural vegetation areas. An interesting result was a change into aquaculture development, specially since the government requiresa certain distance to kept from mangrove areas, whichare within the EISS class. Palustrine emergent wetland- PEW (Figure 4.22) had less interactions, the most important being with natural vegetation. Other interactionswere with PUB and EIEW wetlands, bare land, and abandoned landareas. 114

5.8. Statistical correlation of wetland change and patterns of land use. Human activities such as aquaculture and tourism development could potentially degrade wetland areas and conditions, as has been suggested from looking at photos and data distribution. However, the association of land use patterns and wetland conditions needs to be statistically supported. To test whether wetland changes and human activities are statistically associated, data were structured based on changed polygons. Each polygonwas a record in the database. By considering the gravity law in geography, which basically states that the closer two things are, the higher the relationamong them is, it was decided to use 'parent' polygons as units of change, and to consider 'child' polygons (polygons resulting from the overlay of 1991 over 1973) as adjacent variables for the statistical analysis. Statistical spatial correlations are a powerful tool. They allow for testing of spatial variables and the way they interact through time. This research useda simple correlation analysis, which allowed for the identification of interrelations between changes in wetland conditions and adjacent land use patterns. The population used for the statistical analysiswas the polygons within the overlay map. By using this map, polygons from 1973 were subdivided by polygons in 1991, resulting in a composed change map 1991on top of 1973. Considering the polygons of the change map as the population for analysis,a number of variables can be used, such as size, shape, shared perimeter, distance, and neighborhood analysis. Since changewas the main focus of this research, rather than other considerations suchas ecological relationships among variables, databaseswere structured in a Parent/Child arrangement. In this way, each child polygon was tagged with the parent polygon, providing the information of where the child polygonwas coming from. These data were used to make the graphs and tables of interrelationships, and visually identify interactionsamong different classes. Correlation analysis was done using only polygons that changed, since, in orderto identify whether an association exists between two classes, polygons that didn'tchange would not offer information within the child polygon (that would be thesame class as the parent polygon). However, changed polygons are subdivided into a number of child 115

polygons, which then can be compared in terms of frequency of child polygon present for certain class, considering all parent polygons that changed. Correlation results suggest that statistical associations existamong different classes, some evident correlation exists among wetland classes, particularlyamong intertidal classes, because areas with no vegetationare usually present in areas with vegetation. For instance, mangrove areasare commonly surrounded by emergent grasses, and both are intermixed with sandor mud areas with no vegetation. These associations presented moderate to strong correlations when parent polygonswere within theLUCID classes of Iw, and Iwv; these are the estuarine water andto the rocky shore associated emergent grasses and mangroves. However, the non-vegetated shoreline within the Iwn, resulted in lower correlations. In fact, it presented stronger correlations with upland natural areas. These are sand dunes, bare lands, and natural vegetationareas which usually occurred in adjacent lands, andwere more present when parent polygons of non- vegetated shoreline changed, along the coastline of the island and the mainland. LUCIDclass II included agriculture and aquacultureareas, and salt mines. They were not as highly correlated with wetland areas, as they were withLUCID III.However, aquaculture development occurred within lowland periodically floodedareas (palustrine unconsolidated bottom), resulting ina moderate correlation. Aquaculture was also moderately correlated with emergentgrasses and mangrove areas. Human settlements(LUCID III)were moderately correlated only with vegetated wetlands, particularly in the areas nearby the two towns (Paredon Colorado and Paredoncito). These areas contain emergentgrasses that were modified by human settlements areas. Tourism(LUCID III)occurred only in Huivulai island, where some mangrove areas did change, and presented a moderate correlation. The hypothesis for this researchwas stated as: changes of wetland types are associated with land use patterns. Therefore, to test it,a series of graphs were done to see possible associations. However, in order to test the hypothesis statistically,a Pearson Correlation Coefficient was obtained for the different variables. It is importantto detail some of the data transformation performed to translate the human activities and wetland 116

classes into the land use change index (LUCID) system, so that this classification could be compared with other areas in the future. All records were reclassified so that statistical analysis could be performed using the LUCID system. From LUCID, only three classes were identified in the Tobari system. For differentiation purposes, the first was divided into four, since they represent about the same intensity of development. Iw: Includes the Estuarine Subtidal Unconsolidated Bottom, the Estuarine Intertidal Rocky Shore, and the Open Ocean Water classes, although the Open Ocean class was not considered for the analysis. Iwn: Includes the Estuarine Intertidal Unconsolidated Shore and the Palustrine Unconsolidated Bottom. Iwv: Includes the Estuarine Intertidal Emergent Wetland, the Estuarine Intertidal Scrub-Shrub Wetland, and the Palustrine Emergent Wetland. Iu: Includes the Bare Land, Natural Vegetation, and the Sand dunes. Includes Irrigated Agriculture, Aquaculture, Salt Mine, and Abandoned Land. HI: Includes Tourism, Small Towns and Rural Settlements

By reclassifying all polygons for the LUCID system,a potential 18 by 18 class matrix became a simpler 6 by 6 matrix that could be controlled easily, although this caused some of the information to be lost while being generalized. In Table 4.27(a-f), all the correlation coefficients are shown. Theyare presented in six individual tables that show which LUCID class in 1973 is compared to which LUCID class in 1991, the 'parent' polygons that undergo change from 1973, and the total 'child' polygons in 1991 thatwere used within the correlation analysis. These tables also providea general idea of the polygon fragmentation which occurred in the overlayprocess. In order to have a uniform scale, the correlationswere estimated using a percentage of change, because some polygons were either too largeor too small. In Table 5.3, only those r's estimated in any combination of wetland/LUCID class,or LUCID/wetland class are presented. 117

Table 5. 3. Summary of Correlation Results for LUCID Classes. Classes Correlation Intensity Classes Correlation Intensity Iw-Iu -1.00 Strong Iu-Iw .35 Weak Iwn-Iu .64 Moderate Iu-Iwn .66 Moderate Iwn-II .49 Weak II-Iwn .68 Moderate Iwv-Iu .67 Moderate Iu-Iwv .56 Moderate Iwv-II .62 Moderate H-Iwv 1.0 Strong Iwv-HI .68 Moderate III-Iwv 1.0 Strong

By using this Table 5.3, and following the correlation rules of: Strong if r is greater than .8 or smaller than -.8; Moderate if r is between .5 and .8 or between -.5 and -.8; and, Weak if r is less than .5 or greater than -.5. it can be stated that the hypothesis is not rejected because there is statisticalsupport for the association of wetland changes with landuse patterns. Moderate and strong correlations exist, particularly for the areas of 1w-Iu, which representnon vegetated wetlands associated with natural areas; II-Iwv, vegetated wetlands associated to irrigated agriculture and aquaculture, and III-Iwv, vegetated wetlands associated withtowns. The Pearson correlation coefficientcan be used to measure how homogeneous the variables or groups are within LUCID classes. By estimating the correlation coefficient against the same pattern, if the resultsare not close to 1 or -1, then, the classification is not using variables with close association. Other spatial analyses could complement these results, suchas neighborhood analysis, that would require that adjacent landuses be subdivided into individual parcels. For instance, individual agricultural parcels would be registered, instead of havingone large irrigated agriculture polygon. Patch analysis could be supported by canal distribution and levels of parcelization. Trend analysis coulduse distance, shape regularity, and pattern distribution. Together, they could complement the analysisand they would help in understanding the spatial relationships. 118

5.9. Government policies. Changes in Mexico's inland orientation toward development have emerged in the last few years, due to the availability of naturalresources on the coast, specifically oil, gas, and tourism development. Still, as pointed out in the previous chapter, the strong sectoral approach prevails over all planning programs. Although some recent emphasis has been put on decentralization and integrated management, this is still far in the future. In the Tobari system, wetland changewas associated with irrigated agriculture, shrimp aquaculture, salt mining, and small towns, which were included in the LUCID classes II and III. These three activities belong to the primary sector,a sector related to natural resources, namely: agricultural lands and fishery resources. Both have been historically controlled by government. Therefore, the hypothesis thatgovernment policies have influenced wetland change, by encouraging certain types of development, is supported by the type of activities promoted in the national and state development plans, and the strong governmental control over those activities At the national level, knowledge about wetlands is limited, and establishment of wetland policies is not yet accomplished. However, there isa number of government programs that have affected wetlands, such as incentive programs for extensive use of pesticides and herbicides and water diversion for agricultural, urban and industrialuses. Therefore, the combined effect of having strong development-oriented policies in other sectors, government reaction to market forces, and lack of wetland protection policies, have contributed to the changes in the Tobari system. A national wetland program is needed now, that could offer opportunities for integration of sound wetland policies, emphasizing state and local participation. The development of a national wetland inventory, using indicators of functions and values, and a wetland training program, is also urgently needed. The need for this program is supported by international pressures, such as availability of financingresources targeted exclusively toward the design and implementation of wetlandmanagement practices and international agreements for protection of migratory birds. Thisprogram would provide stronger support for other environmental policies, such as landuse planning and environmental impact assessments. 119

From the main human activities in the Tobari system, fishing has been part of the coast livelihood, as it has in other coastal lagoons. Activities from surroundingareas are impacting the system and they have not been understood, nor confronted. The search for economic development alternatives is motivating the development of other less traditional activities.

Changes from fishing and agriculture into aquaculture and tourism could create conflictareas, but as Pillay (1992) expressed:

"Many ecological disasters that have occurredas a result of unsustainable use, abuse and misuse of natural resources, have clearly demonstrated that long-term and sustainable developmentcan be achieved only through sound environmental management. Experience in aquaculture to date strongly reinforces this concept, and aquaculturists are becoming more and more aware of the need for a long-term perspective in development planning, and the incorporation of solutions to the socio-cultural and the aestheticconcerns of affected communities, in site selection, farm design, and operation." (Pillay, 1992).

In the National Development Plan, the lastone of the five general objectives establishes the promotion of a strong and sustainable economic development, thatcovers the whole spectrum of sustainability. The environmental policies fora sustainable development covers all matters of the environment in only four anda half pages (out of 177 that the plan consists), which mayserve as an indicator of the importance given to the environment by the government. Furthermore, although therecent creation of SEMARNAP (which combines naturalresources, fisheries, environmental planning and regulation, and wildlife and protected naturalareas management), indicates some degree of integration, this National Development Plan is directedtoward 32 sectoral programs, including the National Environment Program, the National FisheriesProgram, the National Forest and Renewable Natural Resources Program, the NationalWater Program, and the National Program to carry out the Sustainable DevelopmentAgenda. All of these have some effect on wetlands, suggestinga long way to go for integrated management. The Sonora Development Plan representsa broader perspective, highlighting a series of economic development strategies. Since surface andground waters, as well as 120 the shoreline exclusion zone, are regulated by the federal government, majorprograms affecting the coast are just received by the state from federal agencies. Statescan promote certain activities, but they lack participation in planning activities within federalprograms. However, the next state program, to cover the period of 1997-2002, will most likely follow the same overall objectives as defined in the National Development Plan; accordingly, strategies of decentralization, delegation of responsibilities, and empowerment of local governments should provide support for a larger state and local involvement. Emphasis on regional development planning, through a state land use planning program, and the requirement for environmental impact statements are preventive procedures to regulate unbalanced development. Theseprograms have motivated public participation, although often on an issue by issue procedure; however, it is going through a maturing process.

5.10. Model efficiency in explaining changes in wetland functions. The design phase for model development includedan identification of the most relevant issues, such as changes in perception of wetlandsas resource areas, the intensive transformation of wetlands in United States, the diminishment of migratory birds, and availability of large habitat areas along the Mexican coast. All of these factors increase the attention given to Mexican wetlands. However, therewas not much information related to wetland problems. The lack of wetland inventories and the absence of policies for their conservation and management, suggested the need for the identification and development of a set of procedures that could be implemented within the general conditions ofMexico. In the design of the procedural model, the needto use materials available for Mexico was emphasized. This defined the techniques used in this project. Model efficiency can be measured in terms of costs, validity of the wetland functions, and time required to be developed. Estimatedcosts are detailed in Appendix 2. If it is considered that equipment and softwarewere already available, the highest cost of this procedural model were field trips and processes of data verification. For the development and testing of this procedural model, several activities had already been 121

carried out as part of a larger coastal wetlands project; therefore, there were some advantages in terms of work previously done, if compared to other regions of Mexico. The estimated time for application of the full model to the Tobari systemwas one year. However, different techniques were tested before the final procedure was fully developed. Length of time was determined by the access to available materials, funding, and available data for the area. The breakdown of time would be: collecting all sources of information,maps, air photos, and census reports- three months; interpretation, digitizing and georeferencing - two months. Data verification through ground truth and corrections- one month. Development of GIS data sets for the analysis and GIS processing took two months; tabular reports and map production another two months, and, the final report abouttwo months. Costs depend on available materials. If no data are available, several field trips would be necessary. One factor that affects the length of time and thus increases costs in model development is the georeferencing. For large wetlandareas, this could be very time consuming, because frequently there will not be good georeferencing marks. Ground truth verification is required to check for data consistency within the GIS. Another important factor is the interpretation of the overlay results. This requiresa good knowledge of the wetland system and the human activities in thearea. The model should be considered as a qualitative measurement of wetland conditions and change, because it uses interpretations from aerial photographyas its primary source of data; then, percentages of wetland changes should be usedas change indicators. Surrounding land use patterns provide informationon development pressures as well as the prevailing conditions of human / wetland interactions. In a first assessment, a simpler classification system, both for wetlands and land use patterns, such as the vegetated and non-vegetated wetlands, and intensity of land use, could provide enough information for preliminary management decisions. A rasterizing routine for statistical analysis purposes could provide faster data formatting. This model could be applied to other coastal areas in Mexico; however, policies for sustainableuse will depend on a clear understanding of wetland issues by local citizens andgovernment. 122

5.11. Conclusions. The procedural model designed and tested for assessment of human- wetland interactions, integrates different tools commonly used in geographical research and links resource assessment with government policies. As a procedural model, it intends to serve as a set of guidelines that can be used and modified according to regional differences, technical expertise and economic conditions. Because of the lack of specific data, suchas good agrochemical measurements and sediments on water discharges, along with historic data for a longer period regarding wetland conditions and wildlife information, specificcauses of wetland change and degradation could not be identified in this research. This research suggests that there is an urgent need for a national wetland inventory program in Mexico that could identify regional differences in resources and that could serve as a basis for developing sustainable policies. This will require a definition and an official acceptance of a wetland classification system. Air photography, being available for the entire country, although not uniformly up-to-date, can provide enough information to cover all wetland areas. Important components would be the required training for air photo interpretation and the quality control procedures. Cowardin's classification is very complete but its fill application requires specialized training and complex procedures. A first approach toa national wetland classification and inventory could use a simpler classification basedon shared functions and values. Such classification would offera good alternative to prepare a rapid assessment at the national level for wetlands, information that could help in establishing priorities for funding and initial protection and remedial actions. This effort could be complemented with a finer classification suchas the Cowardin's, as a following phase. Error is inherent to the use of historic data and variation in scale and quality will offer registration problems. Therefore, theerror needs to be quantified and the use of the data needs to consider the error. However, thereare a number of different spatial measurements that can effectively be obtained from aerial photography. These measurements do provide information on resource distribution, such as wetland classes and land use patterns. From these measurements, the determination of wetlandattributes, 123 such as functions and values, and the way they interact among each other and with surrounding land uses, provides insights on human- wetland interactions. The use of classified wetlands for inference of functions and values reported in the literature should be viewed only as an indicator for wetland assessment. This should be complemented with actual functions and values within the wetland system being analyzed. Changes were identified using two dates; however, for other areas it would be recommended to look at a longer period if spatial information is available. The use of intermediate dates could provide a better approach for understanding the dynamics of land use change. Those dates can be selected according to major weather or economic events, such as the establishment of government incentiveprograms relevant to that area. Change in wetlands was correlated to landuse patterns; however, association identified in this research does not imply cause-effect. Therefore, in order to fully understand the land use dynamics, a cause-effect relationship needs to be incorporated. The use of materials available throughout Mexico, and the possibility of linking local/regional resource issues with national environmental policies, suggests that this procedure represents a feasible strategy that could bridge the gap between a strong centralized sectoral planning and an integrated coastalzone management approach.

5.12. General Comments.

Management decisions in Mexico have occurred with poor knowledge ofresources and, frequently, government sectoralprograms are contradictory and confusing. Decision making is done at a broad scale, losing informationon regional differences and with no considerations of cultural differences in localareas. Environmental legislation in Mexico is considered comprehensive in nature; however, it still requires a maturing time for being enforced. Success storieson wetland conservation are due to a combination of factors, suchas NGOs participation, academic interests, concerned citizens, anda receptive governmental official that just happens to be there at the right time. On the other hand, lack ofawareness of critical issues dealing with coastal wetlands has lead to an absence of authority and lack of confidence in government's ability to manage them. At the same time, absence of wetland conservation policies and 124

government emphasis on broad economic development policies will continue to maintain a potential scenario for wetland degradation. Changes of governmental policies during the last decade have set the framework for public participation and sustainability considerations, along with proposals for internalization of the impacts of economic development (SEMARNAP, 1996). Newer strategies for government expenditures include strategies that share expenses with private groups, with emphasis on public participation, that will encourage private investors,resource managers, and local communities to work together. Since public participation is not a tradition in Mexico, it requires the establishment of feasible means for people to participate and government procedures that first build credibility. If this is achieved, local communities will request proper attention be givento the resources they depend on and to the environmental issues affecting them. Although wetlands have functions, these currently represent little social value in Mexico. Function is a direct result of the role of wetlands in the ecosystem, while values are more of a social perception problem. Different cultures will assign different values, and unless there is an awareness process that compensates for the lack of visionamong local populations, people will place valueon the wetland services only when those services have disappeared. This situation iseven more complex, because wetlands may not completely disappear, but their functions, and thus their values,may slowly deteriorate. This suggests the potential use of wetland functions and valuesas indicators for ecosystem health. Understanding human- wetland interactions requires an identification of how ecosystem functions occur and how humans use and impact those functions, and also how those interactions change through time. By approaching theuse of wetlands at the community level, specific values can be identified, whichmay support a change in attitude and behavior that can result in positive feedback to the government. This positive feedback may be translated intomore active government participation and the inclusion of wetland management in the political agenda and state and local development plans. Information integrated in this research shows that spatial analysiscan be entered at enough resolution for general management practices, and that materialsare in fact, 125 available for most of the country at reasonable costs (Appendix 2), but lack of education and absence of environmental policies oriented toward wetland use within the government, have resulted in lack of formal procedures to monitor wetland change. Although some areas in the Tobari have increased their functional capability with respect to wetland extent, degradation of both functions and values could result in lowering the quality of life for local people and the loss of opportunities for their future use. To achieve sound conservation and management, there is an urgent need for better understanding of the role of wetlands on a local and regional basis. 126

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CARTOGRAPHIC MATERIALS

CETENAL (Comision de Estudios del territorio Nacional). 1973. Mosaic of 15 black and white photos from the Tobari wetland system. Sonora. September 1973. Scale 1:70,000.

De Negri, R. and P. Sanchez. 1924. Carta del Estado de Sonora. Secretaria de Comunicaciones. 1:500,000.

INEGI (Institut° Nacional de Estadistica Geografiae Infonnatica). 1982. Carta Topografica, Morelos Dos G12-B-43. Scale 1:50,000.

INEGI (Institut° Nacional de Estadistica Geografiae Informatica). 1992. Carta Topografica, Villa Juarez G12-B-44. Scale 1:50,000.

INEGI (Institut° Nacional de Estadistica Geografia e Informatica). 1984. Carta Topografica, Etchoropo G12-B-54. Scale 1:50,000.

1NEGI (Institut° Nacional de Estadistica Geografia e Infonnatica). 1991. Mosaic of 15 black and white photos form the Tobari wetland system. Sonora. Juni° de 1991 Scale 1: 75,000.

INEGI (Institut° Nacional de Estadistica Geografiae Informatica). 1985. Carta I-Edrologica de Aguas Superficiales, Huatabampo G12-6. Scale 1:250,000.

1NEGI (Institut° Nacional de Estadistica Geografiae Infonnatica). 1983. Carta I-EdrolOgica de Aguas Superficiales, Guaymas G12-2. Scale 1:250,000.

INEGI (Institut° Nacional de Estadistica Geografiae Informatica). 1983. Carta I-EdrolOgica de Aguas Superficiales, Ciudad Obregon G12-2. Scale 1:250,000.

INEGI (Institut° Nacional de Estadistica Geografiae Infonnatica). 1983. Carta Hidrologica de Aguas Subterrineas, Guaymas G12-2. Scale 1:250,000.

1NEGI (Institut° Nacional de Estadistica Geografiae Informatica). 1992. Carta HidrolOgica de Aguas Subterrineas, Huatabampo G12-6. Scale 1:250,000.

1NEGI (Institut° Nacional de Estadistica Geografiae Informatica). 1985 Carta HidrolOgica de Aguas Subterrineas, Ciudad Obregon H12-2. Scale 1:250,000.

INEGI (Institut° Nacional de Estadistica Geografiae Informatica). 1985. Carta Edafologica, Huatabampo G12-6. Scale 1:250,000. 142

INEGI (Institut° Nacional de Estadistica Geografia e Informatica). 1983. Carta Edafologica, Guaymas G12-2. Scale 1:250,000.

INEGI (Institut° Nacional de Estadistica Geografia e Informatica). 1988. Carta Topografica G12B44-Villa Juarez, G12B54-Etchoropo, Sonora

INEGI (Institut° Nacional de Estadistica Geografia e Infonnatica). 1988.Atlas Nacional del Medi° Fisico. 11 juegos de mapas. Scale 1:1'000,000,

Institut° de Geografia, UNAM. 1991. Atlas Nacional de Mexico, Carta de geomorfologia, geologia, tectonismo, uso del suelo, vegetacion potencial, actividad turistica, contaminacion y uso del agua, centros de poblaciOn, capacidad de uso de la tierra, deterioro ambiental, coeficiente de agostadero. Scale 1.4,000,000.

Secretaria de Asentamientos Humanosy Obras Publicas. 1981. Carta de Ordenamiento del Territorio del Estado de Sonora (Imagen tipo Landsaten color) Scale 1.500,000.

Secretaria de Recursos Ffidraulicos. 1970. Plano General Distrito de Riego Niunero 38, Rio Mayo, Sonora. Scale 1:100,000. Secretaria de Recursos fEdraulicos, Direccion General de Distritos de Riego, Direccion de Conservaciony Mejoramiento, Departamento de Conservacion, Navojoa, Sonora.

Secretaria de Recursos Flidraulicos. Plano General Distrito de Riego Milner° 38, Rio Yaqui, Sonora. Scale 1:100,000. Secretaria de Recursos Hidraulicos, Direccion General de Distritos de Riego, Direccion de Conservacion, Ciudad Obregon, Sonora.

Secretaria de la Refonna Agraria. 1993. Coordinacion del Registro Agrario Nacional. Secretaria de la Refonna Agraria G12B44- Villa Juarez, G12B54-Etchoropo. 143 144 r 4 -"eCr.i.;:-4 pa '4.4, "4 BK BR BT BT BV BV BR BV BR BT BT BR BR BT BT BT BT BT BT BP BR BV BT BT BT BT BV BP BT BT BT BT CB BC BC BD BD BD BD BD BD BD BZ BZ BF BF BF BE BF BF BF BF BF BF BF BF BD BD BD BD BD Type Intensity III lu Iu Iu Iu lu Iu lu Iu Iu Iu lu lu Iu lu lu 91 lu lu Iu lu Iu Iu Iu Iu lu Iu Iu lu Iu lu lu Iu lw lw lw Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn lwv Iwv Iwv Iwv lwv Iwv lwv lwv Iwv lwv Iwv Iwv Lucid 3.10 1.04 0.74 2.86 21.95 80.27 16.87 46.09 16.80 2.20 1.09 2.15 30.83 39.58 86.31 83.99 28.23 87.65 64.24 83.99 25.16 38.07 81.65 18.23 14.47 0.32 0.36 23.90 23.90 88.20 76.88 76.88 76.88 230.42 249.45 221.64 249.45 249.45 249.45 249.45 110.01 198.32 158.50 153.72 62.03 23.26 Area91 221.64 249.45 231.35 241.99 241.99 153.72 196.96 170.97 2266.96 279.10 308.05 279.10 279.10 27475.18 27475.18 91 R2 K1 V4 VI V3 R3 P1 P1 U9 U8 RI VI V2 B2 Cl Cl F9 T44 T16 R23 R14 T16 R19 D6 D9 D6 D4 F7 T16 T16 T30 T33 T16 T16 T15 114 T24 T29 T28 T11 T43 DIO D25 D26 D25 D16 D26 D25 D1 1 D24 D24 F77 F25 E27 F32 F19 F53 F75 F41 F77 F77 73 Iw lw Iw Iw lw Iw lw Iw lw lw lw Iw Iw Iw Iw lw Iw Iw lw lw lw lw Iw lw lw lw lw lw lw lw lw lw Iw Iw Iw lw lw Iw lw Iw lw Iw lw lw lw lw Iw Iw Iw Iw lw lw lw lw lw lw lw lw lw Iw Iw Lucid 11.05 Area73 6246.69 6246.69 6246.69 6246.69 2589.28 6246.69 6246.69 2589.28 6246.69 6246.69 6246.69 6246.69 2589.28 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 2589.28 6246.69 2589.28 6246.69 6246.69 2589.28 2589.28 2589.28 2589.28 6246.69 6246.69 2589.28 6246.69 2589.28 6246.69 2589.28 2589.28 2589.28 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 2589.28 2589.28 6246.69 6246.69 2589.28 6246.69 6246.69 2589.28 6246.69 2589.28 2589.28 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 73 B2 B2 B2 B2 B1 B2 B2 B1 B2 B2 B2 B2 B1 B2 B2 B2 B2 B2 B2 B1 B2 B2 B2 B1 B1 B1 B1 B1 B2 B2 B1 B2 C2 B1 B2 B1 B1 B1 B2 B2 B2 B2 B2 B2 B1 131 B2 B2 B1 B2 B2 B1 B2 B1 B1 B2 B2 B2 82 B2 B2 APPENDIX 1 APPENDIX 2993284.15 2986214.73 2987208.33 2993118.21 2995536.43 2987328.87 2985961.49 2995988.92 2984781.83 2993813.20 2991714.60 2992589.13 3000584.99 2990920.82 2988930.63 2988723.90 2997437.15 2986865.43 2988792.71 2995437.60 2986689.23 2987574.65 2993702.16 2995713.10 2996330.69 3000194.05 2995494.26 2996208.06 2990199.16 2991723.67 2998513.67 2985631.86 2997704.29 2995343.93 2996959.71 2997386.25 2999964.55 3000828.74 2984662.98 2983359.79 2984825.53 2998108.74 2981739.58 2985177.10 2998670.84 3000253.20 2986202.74 2987040.69 2995818.92 2980190.46 2985540.31 2998469.19 2979568.86 2998602.78 2998076.26 2982050.86 2987511.34 2984777.53 2984247.20 2979625.86 2983512.97 607659.32 607431.46 605154.42 602391.43 597639.08 605249.49 609107.63 597688.79 609545.86 607545.42 603788.51 603038.20 594119.01 604330.63 608150.82 608860.63 603194.48 608426.92 595746.65 597722.52 605279.95 609325.06 605070.40 601775.51 595147.63 594254.80 593153.37 594693.13 608096.86 608041.56 594651.92 606237.57 601771.68 599879.04 601227.60 594225.22 593381.02 596000.51 609881.72 610445.75 610679.61 602311.52 610416.75 609066.17 594300.36 593337.02 593968.37 594354.89 607655.21 604034.97 610528.44 609022.78 601661.64 611127.62 595295.68 609852.04 605123.29 609433.84 609933.58 611052.89 609648.86 845.62 1725.84 255.39 320.76 495.30 424.80 348.23 375.39 444.11 851.33 825.27 579.76 582.70 874.41 681.89 832.45 935.22 1031.39 1808.84 1154.12 1212.77 1261.93 1186.74 1043.64 1234.53 1338.38 1065.63 1748.50 296.98 354.25 525.46 833.06 886.59 703.49 920.73 471.91 225.79 218.20 212.76 476.04 266.38 238.50 535.71

I 2266.63 2352.18 3282.73 6207.24 3539.63 8272.98 1016.92 1526.09 1617.47 1103.93 1070.78 393.58 240.27 494.07 280.91 P Perim P_X (UTM) P_Y(UTM) P Perim P_X (UTM) 4631.85 5803.43 13063.70 5.32 0.35 0.36 0.49 0.64 0.72 0.74 0.83 1.00 1.29 1.50 1.51 1.56 1.59 1.60 1.95 Area 2.06 2.23 2.28 2.35 2.41 2.87 3.18 4.16 4.22 4.24 5.66 5.68 7.53 9.07 9.45 1.76 3.01 0.43 0.78 1.06 1.26 1.66 1.96 Overlay Database 73+91 for Change Polygons Greater than .25 hectares Greater for Change Polygons Database 73+91 Overlay 11.06 2.18 2.22 2.59 2.63 2.72 3.74 0.25 0.25 0.26 0.28 0.28 0.30 0.30 0.32 0.35 0.36 0.40 0.42 24.11 115.94 308.66 620 138 634 229 408 993 633 348 166 GIS- 1380 1355 1210 1031 1215 1600 1708 1368 1096 1063 1138 1453 1562 1489 260 299 230 934 825 831 258 455 226 146 124 1075 1212 1594 1186 1442 1432 1237 1750 1920 1918 994 267 382 Label 2037 1030 1585 1359 1178 1984 1584 2115 1810 1199 1675 1827 1738 2097 145 BF BF BF BF BF BF BF BF BF BF BF BE BF BF BF CF BF BE BF BF BF BF BF BF BF BF BF BF BF BE BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BF BE BF BF BF BF BF BF BF BF BF BF BF BF BF BE BF Type Intensity 91 Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Iwv Iwv lwv lwv Iwv Iwv lwv lwv lwv lwv lwv Iwv lwv Iwv Ivey lwv Iwv lwv lwv lwv lwv Iwv Ivrv Ivey Iwv lwv Iwv lwv Iwv Iwv Iwv lwv Iwv lwv lwv Iwv Iwv Iwv lwv Iwv Iwv lwv lwv Iwv Iwv lwv lwv lwv Iwv lwv Lucid 5.71 4.78 0.80 0.81 7.74 1.43 1.80 1.40 1.43 1.48 71.31 14.36 19.38 18.71 2.49 4.97 5.53 2.57 62.03 25.55 30.71 88.71 30.40 25.55 19.38 11.31 3.26 24.21 30.40 60.62 71.31 85.55 88.71 279.10 279.10 279.10 308.05 279.10 145.76 196.96 196.96 62.03 30.40 60.62 25.55 88.71 30.40 30.40 37.37 37.37 42.00 23.26 30.40 Area91 308.05 308.05 308.05 308.05 196.96 308.05 279.10 279.10 279.10 279.10 279.10 279.10 279.10 308.05 279.10 279.10 91 E6 E7 F9 F9 F3 F9 F14 F32 F27 F77 F13 F20 E10 F77 F77 F73 F35 F37 F57 F76 F25 F77 F13 F30 F16 F8 E7 F2 F39 F28 F76 F39 F25 F25 F74 F25 F24 F26 F68 F25 FIO F52 F25 F29 F77 F77 F77 F14 F17 F32 F77 F15 F76 F13 F37 F 1 1 F37 F76 F76 F77 F31 F31 F77 F77 F75 F76 F25 F77 F77 73 Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw lw lw Iw Iw lw Iw Iw Iw lw lw lw lw lw Iw Iw Iw Iw lw lw Iw Iw lw Iw lw lw lw lw lw lw Iw Iw lw Iw lw Iw lw Iw Iw Iw lw Iw Iw Iw Iw lw Iw Iw lw lw Iw Iw Iw lw Iw Iw Iw Lucid 0.83 Area73 2589.28 2589.28 2589.28 6246.69 2589.28 2589.28 2589.28 6246.69 6246.69 2589.28 2589.28 6246.69 6246.69 6246.69 2589.28 2589.28 2589.28 6246.69 6246.69 2589.28 6246.69 6246.69 6246.69 2589.28 6246.69 2589.28 2589.28 2589.28 2589.28 2589.28 2589.28 6246.69 6246.69 6246.69 2589.28 6246.69 6246.69 6246.69 2589.28 2589.28 6246.69 6246.69 6246.69 2589.28 2589.28 2589.28 6246.69 2589.28 6246.69 6246.69 2589.28 2589.28 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 6246.69 2589.28 6246.69 6246.69 73 B1 B1 B1 B2 B1 B1 B! B2 B2 BI B1 B2 B2 B2 B1 Cl B1 B1 B2 B2 B1 B2 B2 B2 B1 B2 B1 B1 B1 B1 B1 B1 B2 B2 B2 B1 B2 B2 B2 B1 B1 B2 B2 B2 B! B1 B1 B2 B1 B2 B2 B1 B1 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B2 B1 B2 B2 2999221.90 2998876.07 2995457.80 2979771.89 3000226.46 2996188.99 3000716.82 2979890.30 2980692.16 2995573.14 2995521.61 2986986.15 2984963.66 2984904.49 2999028.04 2981007.03 3000542.44 2999789.74 2998167.56 2983830.15 2999048.08 2994613.69 2984572.07 2983821.31 3000758.50 2985550.60 2998576.00 2999151.39 2995577.63 2998779.20 2999138.34 2996213.99 2986772.28 2989745.22 2980583.64 2998131.69 2987606.35 2982770.14 2986455.59 2999011.25 2999348.37 2981053.74 2983343.21 2983318.12 2999686.08 2999271.98 2998173.77 2979698.60 2999150.32 2984787.78 2986975.77 3000533.13 2999897.57 2987809.15 2985555.52 2987475.21 2984614.51 2983415.29 2980314.49 2995382.29 2996408.21 2981508.21 2991166.53 2984090.44 2984070.73 2983852.68 2998156.43 2983511.60 2981633.23 595460.38 594078.72 598696.31 609864.08 594076.59 593142.16 595794.31 611263.66 610008.98 593097.53 598522.93 608323.04 606431.97 610480.19 599931.52 610265.11 594089.19 594384.20 602254.17 595487.80 609383.05 606680.50 610367.97 609154.94 596091.35 609589.34 601818.66 598469.73 597634.37 601374.93 596887.50 594911.53 607514.04 608149.94 609533.59 598590.67 608082.63 609232.41 609879.90 598830.86 600267.59 610183.18 610065.72 609416.44 594514.71 596511.44 594921.41 610612.39 595038.18 605477.97 610624.03 596251.57 593880.04 608374.68 609263.49 608349.42 609915.40 610377.31 609789.55 605546.55 604320.65 610525.33 608098.85 609633.62 609175.41 610073.53 599007.63 609820.46 610269.59 579.41 682.17 792.66 637.05 366.42 370.40 788.31 796.92 675.78 465.98 357.81 389.46 485.67 468.62 557.29 359.32 511.05 681.46 757.71 573.93 692.82 913.07 582.62 517.68 822.24 556.93 537.42 814.23 996.38 407.31 520.75 889.96 850.71 502.41 705.71 618.18 473.73 484.91 940.94 481.43 933.08 674.68 655.18 825.90 982.14 959.10 757.14 790.26 927.08 880.90 1270.80 1145.70 1133.23 1612.71 1428.76 1080.53 1542.96 1308.81 1141.91 933.31 P_Perbn P_X (UTM) P Y(UTM) P_Perbn P_X 1789.90 1324.67 1377.73 1855.84 1505.99 2258.28 2152.35 2252.67 2242.72 0.46 0.50 0.54 0.55 0.59 0.63 0.64 0.64 0.74 0.77 0.80 1.01 1.01 1.06 1.06 1.07 1.09 1.09 1.12 1.12 1.14 1.14 1.15 Area 0.81 0.81 0.82 0.82 0.83 0.86 0.93 0.95 0.96 0.97 1.18 1.21 1.28 1.34 1.36 1.40 1.47 1.48 1.50 1.55 1.57 1.58 1.59 1.66 1.75 1.91 2.12 2.15 2.16 2.33 2.57 2.65 2.71 2.95 2.99 3.00 3.09 3.13 3.69 4.10 4.52 4.52 4.61 4.70 4.83 5.01 142 137 393 227 757 234 436 739 865 239 269 390 GIS- 1791 1844 1488 1291 1962 470 997 714 617 973 541 335 743 758 881 293 514 321 327 477 179 2121 1913 1027 1655 1296 1932 1595 1734 1363 1459 1681 1449 1644 1754 1849 1838 1659 1231 1610 1493 761 Label 2019 2001 1503 1730 1888 1786 1220 1118 1940 1437 1707 1606 1812 1768 1886

- 146 1 1 3 4 1 3 4 4 1 3 3 2 1 3 01 eJ BF BF BE BF BF BF BF BF BF BF BF BF BF BF BF BF DI DI DI DI DI GS GS GS GO DN GO DN GO GT DT GT DT DT DV DT DT GT DT DT GT GN GN DR GT DV OR DT GT GT DR GT DR DT GT DT GT ZT DT DT DT DT GT DT GT DT Type Intensity DR GT GT II II II II II II II II II II 91 II II II II II Iu Iu Iu lu Iu lu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu lu Iu Iu Iu Iu Iu Iii Iu Iu Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv 1wv Iwv Iu Iu Iu Iu Iu Iu Iu Lucid 8.26 4.09 1.14 1.44 21.59 88.71 19.38 88.71 85.55 52.71 19.11 13.12 12.94 0.52 2.26 1.62 62.03 24.21 10.36 13.15 17.13 13.15 2.09 2.40 196.96 196.96 145.76 54.16 59.17 39.58 59.17 71.30 25.53 13.21 11.10 11.10 19.85 18.27 279.10 308.05 308.05 308.05 208.84 114.55 208.84 114.55 174.50 64.24 64.24 62.17 43.37 21.35 74.27 Area91 208.84 231.35 157.10 231.35 120.56 249.45 198.32 6200.17 10031.38 3055.16 3055.16 10031.38 10031.38 10031.38 3055.16 3055.16 91 12 II II II Ii E5 F9 Fl F9 03 N3 01 N3 02 T6 T9 T2 F78 F77 F37 F25 F25 F32 F39 F37 F17 F28 F25 F30 S26 S25 S26 N2 N3 U8 V2 T5 R8 T9 V2 R5 U6 T8 T7 T25 T19 T19 T32 T4 Ul T18 U13 T20 T23 T10 R18 T24 R18 T24 T16 U13 U13 U13 T31 R13 T22 T12 Ti! T13 73 Iw Iw Iw Iw 1w Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iwn Iwn Iwn Iwn Ivm Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Ivm Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Ivm Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn 1wn Iwn Iwn Iwn Iwn 1wn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Lucid 4.41 6.64 17.86 5.30 5.30 6.64 55.63 54.51 44.90 54.51 14.55 54.51 55.63 81.46 12.63 4.41 45.72 81.46 55.63 21.41 Area73 279.47 373.82 119.70 373.82 373.82 279.47 287.04 6246.69 6246.69 2589.28 6246.69 2589.28 2589.28 2589.28 6246.69 6246.69 2589.28 6246.69 6246.69 6246.69 2589.28 6246.69 6246.69 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 287.04 373.82 373.82 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 2750.93 73 B2 B2 BI B2 B1 BI B1 B2 B2 B1 B2 B2 B2 B1 B2 B2 02 02 02 02 02 02 02 02 02 02 D2 D2 G2 02 D2 D20 D18 02 02 02 02 02 02 02 D7 27130.54 Dl Dl GI D2 02 02 D2 02 D29 D31 D26 D30 D32 D20 D1 1 D22 D34 D32 D16 D16 D22 D20 D29 2984151.65 2982476.78 3000083.16 2988625.81 2999601.07 2999734.32 2997456.33 2983549.37 2988764.70 2999119.53 2994030.85 2986687.64 2992283.40 3000061.94 2986041.23 2997431.74 2989173.48 2999272.04 3000128.57 2999522.26 2996495.30 3004492.14 3005448.50 3000326.09 D17 3005375.12 2999774.22 2999020.48 D30 2998749.74 2998398.87 D30 3002270.36 3001698.48 3005413.76 3001562.46 3000527.91 2998172.79 3001396.08 2996629.08 2988733.25 2998099.03 3002038.38 3000599.90 2983441.73 3000847.82 3001212.34 2998225.25 2996525.70 3000211.81 3002758.51 3002337.81 2999390.47 2999364.81 3004204.70 2999319.10 2999629.34 D I 9 2999889.28 3000491.24 D17 2999965.82 2988865.68 2978333.24 2981012.80 2982982.10 2988866.92 2996350.66 3003628.15 2997617.33 3000670.39 2999599.73 2997223.34 3001601.41 607086.43 609997.82 593423.68 608856.30 600202.62 598496.27 594684.44 609074.58 608239.16 595890.95 607383.05 609210.94 607907.84 597663.95 608891.61 603112.20 609326.93 593370.52 594840.62 592228.50 605507.27 595306.23 593892.69 594389.96 594228.41 592278.43 605429.07 602128.07 604125.65 593941.86 594769.56 594397.61 599337.99 591120.35 603302.86 599352.94 592712.92 608396.94 591630.73 590828.05 598523.39 611296.16 591349.59 597019.39 591170.98 592871.54 592864.67 599927.74 596627.03 592853.66 594773.34 593784.71 595031.81 591859.23 594275.16 591418.64 601014.58 604991.57 610972.17 611826.96 611193.16 608477.91 605591.47 596794.74 594229.21 590995.91 592721.81 594243.78 596160.87 1507.86 1824.96 237.38 980.81 624.20 525.56 805.50 771.59 281.95 309.26 261.13 2424.51 2127.49 1842.94 3549.37 2612.46 2450.47 1446.61 1171.95 1552.45 365.38 495.40 367.12 330.47 429.26 444.93 315.31 346.56 968.38 474.99 459.16 410.08 392.18 890.92 567.14 542.31 436.93 602.93 581.85 855.72 494.48 595.33 569.79 570.07 864.74 2611.91 3124.74 2754.03 3232.47 2058.09 5439.53 4595.89 4968.60 2263.99 2307.21 3773.13 4199.23 6828.82 8987.01 963.64 687.21 630.80 657.35 658.62 815.24 910.26 773.17 P Perim P_X (UTM) P_Y(UTM) P Perim P_X I 1011.51 1223.68 5.32 5.45 6.01 6.30 6.35 6.49 7.38 7.97 8.76 9.79 1.54 Area 10.93 11.32 11.51 12.34 15.71 0.31 0.80 0.93 2.18 3.38 3.92 5.02 8.10 0.26 0.27 0.28 0.31 0.36 0.48 0.52 0.52 0.59 0.63 0.68 0.81 0.82 1.04 1.06 1.08 1.11 1.22 1.33 1.40 1.44 1.62 1.62 1.71 1.85 1.85 1.98 28.26 12.46 16.94 0.82 0.87 0.92 2.09 2.13 2.21 2.30 2.33 2.48 2.50 2.88 25.53 28.01 152.16 180.49 141 72 70 12 872 23 53 32 26 667 266 453 595 150 319 368 210 283 180 102 61 55 22 89 GIS- 1314 1716 1544 1572 1444 1315 1525 1404 1412 1032 1662 217 280 287 804 808 725 562 114 112 859 531 110 318 188 349 928 1230 1200 1010 1085 1082 1526 263 539 244 233 469 Label 2145 1174 1540 1236 2081 2191 2135 147

GIS- Area P_Perim P X (UTM)P Y(UTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 93 2.88 1370.60 592751.52 3000401.3402 2750.93 Iwn Ti! 198.32 Iu GT 298 3.11 755.75 594577.17 3005174.57G2 2750.93 Iwn T21 44.74 Iu GT 2182 3.20 778.47 611589.59 2980367.12DI 287.04 Iwn U13 3055.16 Iu DT 535 3.29 1254.70 596989.49 3002359.05D34 119.70 Iwn U5 82.05 Iu DT 209 4.43 1071.17 594033.91 3005443.62 02 2750.93 Iwn T25 54.16 Iu GT 2 4.48 924.22 590151.65 3002752.58 02 2750.93 Iwn T45 4.48 Iu GT 143 4.58 1407.04 593291.93 2999620.78 G2 2750.93 Iwn R17 8.71 Iu GR 1577 5.17 1554.25 609056.38 2989151.37D20 55.63 Iwn U9 30.83 Iu DT 1285 5.19 3730.59 606901.60 2983184.90D7 27130.54 Iwn T44 230.42 Iu ZT 213 5.75 1053.14 594006.59 2998605.90 D2 373.82 Iwn T17 7.88 Iu DT 30 6.06 1235.15 591465.66 3000249.11 02 2750.93 Iwn T6 10.36 Iu GT 243 6.20 1143.15 594240.85 2998153.23 D2 373.82 Iwn T12 18.27 Iu DT 4 6.83 985.81 590314.44 3002019.17022750.93 Iwn Ti 6.83 Iu GT 41 6.88 1383.10 591611.91 3000476.74022750.93 Iwn T5 17.13 Iu GT 481 6.92 1780.22 596416.89 3001480.77D34 119.70 Iwn Ul 74.27 Iu DT 1451 7.17 1699.65 608228.80 2989017.57 D20 55.63 Iwn T30 16.80 Iu DT 2 1875 9.37 1606.59 610283.52 2983033.53D22 81.46 Iwn R24 9.37 Iu DR 2 186 9.62 2123.08 593954.25 2994511.59 D7 27130.54Iwn V6 9.62 Iu ZV 1 1144 10.09 2744.15 604754.99 2988945.98D7 27130.54 Iwn V5 96.16 Iu ZV 1 2185 10.20 2188.84 611767.19 2981273.02D23 12.29 Iwn U13 3055.16 Iu DT 4 790 10.43 7744.66 600819.76 2993601.99D7 27130.54 Iwn V5 96.16 Iu ZV 1 517 10.98 2486.40 596859.40 3002281.71D34 119.70 Iwn T23 13.21 Iu DT 1 94 11.32 3486.46 593228.96 2999353.0202 2750.93 Iwn T11 198.32 Iu GT 1 1531 11.50 1505.16 608745.65 2989032.12D20 55.63 Iwn U9 30.83 Iu DT 3 84 13.89 3586.46 592780.69 2999498.51 02 2750.93 Iwn R7 25.09 Iu OR 1

2190 15.00 2695.55 611924.03 2980086.50DI 287.04 Iwn U13 3055.16 lu DT 1 546 15.06 2247.58 596848.95 3002934.14GI 21.41 Iwn U5 82.05 Iu GT 4 27 15.23 1488.27 591273.79 3001677.54022750.93 Iwn T2 71.30 Iu GT 1 165 17.51 2498.16 593684.11 3005176.03 02 2750.93 Iwn T25 54.16 Iu OT 1 17 17.94 2205.32 591093.09 3002435.8802 2750.93 Iwn T2 71.30 Iu GT 1 527 19.87 3092.56 597005.01 3000405.13 D9 26.28 Iwn R8 157.10 Iu DR 4 549 20.55 2409.39 596964.32 3001443.37 D34 119.70 Iwn Ul 74.27 lu DT 2 52 20.90 1916.65 591689.90 3002291.47 G2 2750.93 Iwn T3 28.65 Iu GT 1 39 23.59 6322.89 592430.39 3000113.98022750.93 Iwn Ti! 198.32 Iu GT 1 461 24.79 7073.41 597480.57 2995067.76D7 27130.54 Iwn PI 83.99 Iu ZP 1 551 33.91 5262.20 597190.83 3001589.54D34 119.70 Iwn R8 157.10 Iu DR 3 311 35.19 4855.00 595388.19 3004273.06 G22750.93 Iwn T21 44.74 lu GT 1 228 37.16 7832.19 594411.16 3003601.62022750.93 Iwn T24 64.24 Iu GT 1 28 44.38 4066.47 591919.77 2997479.83 D2 373.82 Iwn V2 231.35 lu DV 2 2041 80.41 8078.28 611216.80 2981403.35 DI 287.04 Iwn U13 3055.16 Iu DT 3 1160 94.2523596.79 607354.29 2982695.38D7 27130.54Iwn VI 221.64 Iu ZV 8 133.589480.12 592342.38 3004926.17022750.93 Ivvn T46 244.27 Iu GT 944 0.27 291.26 601084.83 2998882.54 D13 40.08 Iwn B2 2266.96 Iw DB 849 0.29 268.22 599764.40 2998955.99D32279.47 Iwn B2 2266.96 Iw DB 1880 0.29 265.42 610166.90 2981834.81D14 7.23 Iwn B1 6033.70 lw DB 1996 0.36 273.25 610573.88 2981646.50 DI 287.04 Iwn B1 6033.70 Iw DB 1022 0.37 309.79 602054.23 2998120.44 1331 44.90 Iwn B2 2266.96 Iw DB 1541 0.46 371.19 608648.03 2988686.54 D20 55.63 Iwn B1 6033.70 Iw DB 696 0.47 724.50 598265.78 2999667.01D11 45.72 Iwn B2 2266.96 Iw DB 922 0.47 495.83 600896.23 2999007.27D13 40.08 Iwn B2 2266.96 Iw DB 792 0.49 414.11 599201.54 2998540.15D32 279.47 Ivm B2 2266.96 lw DB 426 0.54 404.82 595625.78 3000334.60 DIO 42.86 Iwn B2 2266.96 Iw DB 2060 0.66 1006.13 610989.14 2980111.18DI 287.04 Iwn BI 6033.70 Iw DB 1977 0.68 418.33 610506.40 2978978.47DI 287.04 Iwn B1 6033.70 Iw DB 2018 0.70 443.35 610705.82 2979893.47DI 287.04 Iwn B1 6033.70 Iw DB 1946 1.10 446.76 610372.97 2981256.68DI 287.04 Iwn BI 6033.70 Iw DB 799 1.12 492.84 599395.90 2998692.36D32 279.47 Iwn B2 2266.96 Iw DB 456 1.80 728.18 596031.88 2998647.36D25 1.95 Iwn B2 2266.96 Iw DB 1800 5.61 2671.04 610260.68 2982574.25D22 81.46 Iwn B1 6033.70 Iw DB 1168 11.90 1495.18 605007.71 2988489.76D7 27130.54 Iwn B1 6033.70 Iw ZB 215 0.41 287.79 593978.88 2997210.11 D2 373.82 Win GI 2336.36 lwn DG 79 0.66 617.56 592489.04 3000642.68022750.93 Iwn D6 153.72 Iwn GD 304 0.71 357.46 594606.55 2994836.90D15 0.71 Iwn D24 27475.18 Ivm DZ 5 162 2.93 1006.86 593306.38 2996456.84 D2 373.82 Iwn GI 2336.36 Iwn DG 1 169 3.01 907.14 593578.39 2995276.95 D5 3.01 Iwn D24 27475.18 Iwn DZ 5 184 3.18 956.08 593853.22 2996809.25 D2 373.82 Iwn GI 2336.36 Iwn DG 1 356 3.70 878.85 594845.22 2994644.54 D6 3.70 Iwn D24 27475.18 Iwn DZ 5 125 4.74 1027.90 593075.24 2994605.49 D3 4.74 Iwn D24 27475.18 Iwn DZ 5 207 6.55 1143.29 593945.83 2994988.96 D4 6.55 Iwn D24 27475.18 Iwn DZ 5 148

GIS- AreaP_Perim P_X (UTM)P_Y(UTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 121 13.57 2895.58 593516.01 2997805.66 D2 373.82 Iwn G1 2336.36 lwn DG 1 343 46.31 3468.19 595429.61 3001021.62 02 2750.93 Iwn D9 88.20 Iwn GD 1 36 106.83 7741.34 592410.33 3000953.22 02 2750.93 Iwn D6 153.72 Iwn GD 1 48 117.83 10645.13 591714.84 2998082.30 D2 373.82 Iwn GI 2336.36 Iwn DG 3 224 0.30 298.67 594051.28 2996805.90 D2 373.82 Iwn F12 2.38 Iwv DF 106 0.33 324.76 592763.59 3000724.96 G2 2750.93 Iwn ES 21.59 lwv GE 306 0.33 272.82 594627.35 2999912.76 D18 17.86 Iwn E6 7.74 Iwv DE 425 0.33 333.11 595614.04 3000260.57 DIO 42.86 Iwn F14 71.31 Iwv DF 350 0.38 280.66 595003.98 2999402.37 D16 5.30 Iwn F14 71.31 Iwv DF 464 0.40 288.61 596149.64 3001422.09 D34 119.70 Iwn E26 56.13 lwv DE 1908 0.41 452.25 610333.57 2981824.72 D14 7.23 Iwn F77 279.10 lwv DF 488 0.42 633.97 596243.72 3002978.89 D34 119.70 Iwn E26 56.13 Iwv DE 418 0.51 402.60 595556.93 3000133.11 D24 3.17 Iwn E 1 0 30.71 lwv DE 2 1998 0.51 349.65 610596.35 2982555.67 D22 81.46 Iwn F77 279.10 lwv DF 1 569 0.58 431.37 597142.16 3000290.69 D9 26.28 Iwn F25 308.05 lwv DF 1 1878 0.58 354.89 610176.59 2983325.84 D22 81.46 Iwn F76 30.40 lwv DF 1 1605 0.74 382.00 609127.39 2988878.98 D21 2.71 Iwn F37 88.71 Iwv DF 3 182 0.74 377.04 593756.04 2998785.38 D2 373.82 Iwn F32 62.03 lwv DF 947 0.74 646.71 601102.14 3000390.96 D12 103.38 Iwn F25 308.05 Iwv DF 806 0.77 645.83 599491.98 2999695.58 D32 279.47 Iwn F25 308.05 lwv DF 801 0.79 593.29 599402.13 2999548.44 D32 279.47 Iwn F25 308.05 lwv DF 1995 0.90 525.06 610608.33 2981667.37 DI 287.04 Iwn F77 279.10 hw DF 492 0.92 637.24 596251.69 3003231.19 02 2750.93 Iwn HI 325.04 Iwv OH 970 0.93 421.32 601353.64 2999027.47 D13 40.08 Iwn F25 308.05 lwv DF 2054 1.20 607.18 610762.50 2981504.32 DI 287.04 Iwn F77 279.10 Iwv DF 841 1.37 555.74 599679.60 2999325.89 D32 279.47 Iwn F25 308.05 lwv DF 751 1.40 492.80 598700.66 2998395.46 D33 1.41 Iwn F25 308.05 lwv DF 750 1.48 577.55 598732.08 2999717.86 D32 279.47 Iwn F25 308.05 lwv DF 948 1.76 795.08 601162.82 2999399.18 D13 40.08 Iwn F25 308.05 Iwv DF 815 1.76 717.70 599569.98 2999946.65 D32 279.47 Iwn F25 308.05 lwv DF 565 1.84 855.83 597103.41 3001914.36 D34 119.70 Iwn E 1 1 122.96 Iwv DE 683 1.91 710.51 598173.38 3000486.51 Dll 45.72 Iwn E19 20.93 Iwv DE 2189 2.09 665.65 611798.45 2980814.09 D23 12.29 Iwn E27 170.97 Iwv DE 2 1452 2.22 709.66 608100.56 2989200.68 D20 55.63 Iwn F37 88.71 lwv DF 1 274 2.31 778.47 594403.01 2999857.13 D18 17.86 Iwn E6 7.74 Iwv DE 2 328 2.48 725.25 594906.64 2999282.72 D16 5.30 Iva' F15 5.53 lwv DF 3 1078 2.51 942.29 603418.95 2998214.75 D30 54.51 Iwn F30 145.76 Iwv DF 1 421 2.53 1082.22 595668.86 2999902.04 D24 3.17 Iwn F14 71.31 lwv DF 4 982 2.53 1025.87 601529.81 2998893.37 D13 40.08 Iwn F25 308.05 lwv DF 1 837 2.70 850.25 599761.75 2999033.67 D32 279.47 Iwn F25 308.05 Iwv DF 1 847 2.98 852.62 599810.23 3002072.78 D26 14.55 Iwn E12 21.10 lwv DE 3 1776 3.11 955.31 609752.89 2983349.22 D22 81.46 Iwn F77 279.10 Iwv DF 1 1777 3.62 1666.16 609957.20 2982214.26 D14 7.23 Iwn F77 279.10 Iwv DF 4 104 3.64 1449.85 592844.96 3000500.88 G2 2750.93 Iwn ES 21.59 lwv GE 1 545 4.12 1261.03 596875.64 3003635.72 GI 21.41 Ival HI 325.04 lwv OH 2 222 4.40 1300.80 594187.57 2998608.98 D2 373.82 Iwn F32 62.03 Iwv DF 1 803 4.45 1106.24 599315.20 2999372.25 D32 279.47 Iwn E14 4.75 lwv DE 1 999 4.59 1132.54 601821.11 2999111.24 D31 44.90 Iwn F25 308.05 Iwv DF 2 292 4.66 1791.79 594591.59 2999842.63 D18 17.86 Iwn F14 71.31 lwv DF 3 496 4.81 1093.96 596502.40 3002410.14 02 2750.93 Iwn HI 325.04 lwv OH 1 591 4.86 1410.66 597558.99 3000479.49 D9 26.28 Iwn F25 308.05 lwv DF 2 423 5.19 1437.06 595671.56 3000693.49DIO 42.86 Iwn EIO 30.71 Iwv DE 2 923 5.33 1749.52 601013.06 2998980.97 D13 40.08 Iwn F25 308.05 lwv DF 2 2003 5.54 1226.30 610752.34 2987008.34D28 7.84 Iwn E4 25.53 lwv DE 4 616 6.04 1860.56 597414.23 3001362.71 D34 119.70 Iwn Eli 122.96 Iwv DE 1 1146 6.74 1809.85 604727.31 2998778.12 D30 54.51 Iwn F30 145.76 lwv DF 2 660 7.54 2648.34 598310.70 2999809.43 Dll 45.72 Iwn F25 308.05 lwv DF 2 236 8.11 1309.39 594117.58 2997735.70 D2 373.82 Iwn F18 8.97 Iwv DP 1 853 8.66 1939.33 599968.96 2999431.78 D32 279.47 Iwn F25 308.05 lwv DF 1 9.34 346 1945.76 595269.19 3000220.61 D18 17.86 Iwn EIO 30.71 Iviv DE 4 1847 9.94 2724.39 610403.65 2982576.38 D22 81.46 Iwn F77 279.10 lwv DF 2 1007 9.95 2238.15 602058.13 2998316.57 D31 44.90 Iwn F30 145.76 lwv DF 3 655 10.83 2734.03 598012.17 2999891.31 Dll 45.72 Iwn El9 20.93 lwv DE 3 1514 10.84 2884.68 608776.64 2989317.38 D20 55.63 Iwn F5 27.51 lwv DP 2 907 11.18 1745.37 600938.95 2999462.71 D19 12.63 Iwn F25 308.05 Iwv DF 4 487 11.20 2543.82 596350.89 3003105.59 D34 119.70 Iwn HI 325.04 lwv DH 1 316 11.24 2186.68 594819.70 2997929.51 D8 11.31 Iwn F32 62.03 lwv DP 5 969 12.62 3383.57 601584.72 2999483.22 D12 103.38 Iwn F25 308.05 lwv DP 2 400 12.62 3014.96 595781.13 3004202.01 02 2750.93 Iwn Hi 325.04 Iwv OH 1 149 1 1 1 1 1 1 1 1 1 1 2 3 3 2 4 2 2 3 1 1 1 2 2 3 1 4 1 2 1 2 3 1 2 1 4.4 2 3 4 2 2 3 3 3 Fl Fl Fl Fl DE DE DF DE DF DE DF GF DE DF DF DF DF FS HI FT Fl Fl Fl Fl Fl DE DE GE DE EN EN EN FN HS FN FS FS FS FS Fl Fl EN E0 EN HS EN HS HS FN FK FK FK FT FR FT FT FT FT FT FT FT Type Intensity - EN E0 EK HR ET FR ER II II II II II II II II II II II II II II II II 91 II II II II II II II II II II II II II II II II II II Iwv Iwv Iwv lwv lwv Iwv Iwv lwv lwv Iwv Iwv Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iwv Iwv Iwv Iwv Iwv lwv 111 III III III lu Iu Iu Iu Lucid 21.10 60.92 88.71 27.85 40.58 60.62 40.58 31.15 56.13 15.99 4.09 170.97 61.23 65.85 65.03 57.24 6.16 6.16 6.03 308.05 308.05 279.10 170.97 114.24 114.24 35.20 65.03 65.85 19.11 21.95 86.31 Area91 279.10 279.10 208.84 114.24 114.24 174.50 174.50 174.50 114.55 114.55 174.50 40.49 81.65 86.31 86.31 39.32 81.65 157.10 198.32 208.84 249.45 249.45 157.10 10031.38 10031.38 10031.38 10031.38 10031.38 6200.17 6200.17 6200.17 6200.17 6200.17 10031.38 10031.38 3055.16 3055.16 10031.38 91 E9 Ii Ii II Ii E7 S7 Ii S5 12 12 12 Ii Ii 12 12 II E12 E16 F25 E27 F37 F25 F21 F77 F21 F77 F77 N 1 N3 N 1 Ni NI N2 S5 S7 Si E23 EIS E26 E27 S20 01 N2 N2 N2 N3 03 K1 K5 K2 K5 S23 S26 S26 R8 R8 T33 R16 T43 T16 T16 133 T33 U13 U13 111 R26 143 73 Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Ivm him Iwn Iwn Iwn Iwn Iwn Iwn lwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv 1wv Iwv Iwv lwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Ii.vv Iwv Iwv Iwv Lucid 3.27 3.31 6.58 5.60 2.77 6.34 6.34 55.63 42.86 40.08 2.77 3.09 6.21 8.63 8.63 103.38 119.70 38.23 35.81 23.35 86.54 89.91 86.54 35.81 39.80 15.38 15.70 0.81 279.47 279.47 287.04 373.82 279.47 287.04 287.04 287.04 102.98 102.98 118.13 39.36 35.81 39.80 23.35 39.80 39.80 43.65 15.70 Area73 279.47 287.04 162.48 118.13 125.88 118.13 118.13 125.88 162.48 174.81 20.43 38.23 20.43 20.43 89.91 2750.93 174.81 174.81 162.48 174.81 2750.93 219.11 73 Dl D2 G2 Dl DI Di 02 DI E4 E4 HI F2 E6 F2 H2 HI E9 F2 F2 E9 E6 F7 D32 D12 D32 D20 D32 D10 D34 D13 D32 F48 F33 F34 E23 F42 F25 F22 F22 F54 F73 HI H1 Fl Fl H2 E6 F6 E23 F52 F53 E23 F53 F25 F75 F37 F74 F73 F74 F12 F49 E17 F33 F49 F49 F12 F12 F12 E25 3002078.70 3001412.06 2999220.68 2978455.32 2989183.73 2996588.36 2999368.94 3001820.76 3000740.65 2979782.62 3001662.81 2979239.23 2999224.02 2980957.24 3000202.90 3003085.72 2980378.86 2995062.81 2985422.66 2998354.57 2996411.41 3000657.36 2985372.32 2998715.20 2994558.96 2985382.96 3005099.70 3004276.20 2985878.25 2987530.75 2993731.67 3000338.11 2992274.78 2989072.88 2999413.59 2988168.06 3000721.37 2988480.27 3004672.29 2991055.16 3000835.01 2994776.53 2996516.62 3004955.53 2992146.91 3005480.82 2991313.85 3000733.90 2995946.15 3000193.37 2999130.14 2993681.98 2982546.06 2995546.55 2982707.51 2987751.40 2996977.86 2985394.20 2989523.54 2988947.93 2987982.64 2987452.32 3002676.35 2981801.71 2981964.91 2999113.76 2982058.35 2985055.36 3001798.81 599964.10 600733.75 599194.00 610806.51 608518.11 592891.65 598470.25 596393.82 596291.85 596663.14 611258.58 610716.25 601267.18 610386.12 599132.99 596129.08 611405.23 607297.61 610747.68 602372.48 604625.60 594346.02 610251.89 603813.85 607140.00 610102.04 595662.63 597588.28 610110.80 610976.05 608080.20 593961.81 592220.03 594027.46 608203.18 609434.49 611127.64 611046.50 596078.18 610015.96 594088.27 606747.33 604385.95 595391.17 608439.28 595145.41 593836.42 594567.95 593241.39 609256.97 606185.93 607863.54 611470.91 605917.93 611489.72 608653.28 603848.63 606527.59 604902.72 605150.09 608807.12 608692.43 597234.22 612015.49 610913.11 593749.94 610965.63 606496.61 597286.40 505.15 261.22 320.46 323.93 376.82 415.14 587.55 465.23 392.93 600.09 629.00 702.99 592.46 767.75 2365.67 2248.00 4434.94 2370.06 3159.45 4504.91 3594.54 2356.03 2840.86 2938.78 754.98 645.28 680.99 730.29 778.31 905.69 923.69 941.00 P_Perim P X (UTM) P Y(UTM) P_Perim P 4358.67 4836.85 2659.00 6526.72 3868.81 7338.68 1032.42 1068.30 1168.02 1618.67 1097.00 1421.57 1024.29 1913.74 400.09 375.73 1182.87 979.01 257.88 250.07 918.16 347.12 323.90 333.48 596.97 346.47 348.85 399.74 587.52 508.98 515.70 413.90 10083.84 2556.38 2208.43 2015.28 2669.05 Area 13.31 13.33 14.57 14.83 0.32 0.44 0.46 0.52 0.53 0.59 0.66 0.81 0.90 1.38 1.53 1.58 1.83 1.92 15.07 15.45 15.50 16.99 17.98 18.67 2.23 2.38 2.52 2.55 2.90 3.36 3.40 3.78 4.12 4.61 5.27 5.55 5.70 23.22 25.18 28.52 32.75 51.43 54.37 59.97 4.62 4.72 7.23 0.76 0.82 3.71 5.34 0.26 0.27 0.38 0.40 0.41 0.49 11.92 11.99 15.60 18.29 0.57 0.58 0.63 0.68 0.70 0.76 0.81 0.94 75 71 854 905 770 671 468 471 497 941 1959 1481 764 441 282 430 619 193 178 120 GIS- 2065 1949 1904 1341 1034 1153 1895 1108 1327 1858 1868 1427 208 457 221 383 371 281 578 173 Label 2044 2038 2084 1450 1661 1823 1300 1141 1482 580 2109 2086 1556 1270 1413 1257 1551 1112 1299 1185 1214 1560 1549 2170 2171 2202 2078 2088 1294 150

GIS- AreaP PerimP X (UTM) P_Y(ITTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 1588 0.96 437.94 609017.47 2986216.52Ell 53.20 Iwv R22 0.97 Iu ER 523 0.98 375.46 596512.34 3003566.93 HI 118.13 Iwv R20 0.98 Iu HR 669 1.00 1336.81 598027.32 3003341.22E25 219.11 Iwv U2 120.51 Iu ET 1921 1.05 517.94 610325.65 2987019.46 F22 86.54 Iwv 135 6.70 Iu FT 265 1.08 421.53 594269.90 3000791.41 E9 125.88 Iwv T24 64.24 Iu ET 2079 1.12 760.97 610961.29 2980972.69F61 8.57 Iwv U13 3055.16 Iu FT 2 1561 1.13 492.37 608872.00 2988840.22F52 39.36 Iwv U9 30.83 Iu FT 1 240 1.16 571.46 594146.66 3000626.16E23 35.81 Iwv R19 2.86 Iu ER 1 1156 1.19 494.27 604651.22 2996338.08F34 3.31 Iwv R13 62.17 Iu FR 3 963 1.19 637.89 601218.12 2999857.10F77 5.88 Iwv U6 19.85 Iu FT 3 1074 1.21 972.80 603257.06 2997434.78F33 38.23 Iwv U8 39.58 Iu FT 1 703 1.24 494.11 598306.17 3002453.04E25 219.11 Iwv RU 1.51 Iu ER 1 677 1.30 508.58 598102.71 3002686.16H2 89.91 Iwv R12 1.93 Iu HR 1 1193 1.33 612.61 605058.66 2989181.69Fl 8.63 Iwv T16 249.45 Iu FT 2 365 1.43 588.48 595200.02 2999260.38E13 2.03 Iwv R18 11.10 Iu ER 4 1559 1.48 808.81 608946.59 2986879.32F22 86.54 Iwv T33 86.31 Iu FT 1 2111 1.71 745.16 611232.86 2981890.59F63 14.03 Iwv U13 3055.16 Iu FT 2 615 1.76 790.98 597621.19 2995488.43 F76 5.33 lwv V4 80.27 Iu FV 3 262 1.79 594.92 594252.51 3000625.13 E23 35.81 Iwv T24 64.24 Iu ET 1 131 1.90 643.70 592921.84 2996347.97F35 4.70 Iwv V2 231.35 Iu FV 3 635 2.13 643.41 597725.39 3000805.29E25 219.11 Iwv R8 157.10 Iu ER 1 583 2.22 865.43 597289.69 3003012.60 El 5 6.33 Iwv U5 82.05 Iu ET 3 779 2.22 850.19 598962.89 2995208.90F26 16.43 1%w T15 87.65 Iu FT 2 2172 2.27 654.45 611472.39 2982448.32E17 3.09 INVV U13 3055.16 Iu ET 4 360 2.39 677.59 595154.66 2999352.73F40 5.07 Iwv R18 11.10 Iu FR 3 1809 2.49 971.74 610024.90 2985049.43 E4 102.98 Iwv R4 5.99 Iu ER 1 697 2.61 814.04 598344.68 3000624.72F31 135.58 1wv T18 25.53 Iu FT 1 773 2.77 1615.32 599051.72 2995316.57F26 16.43 lwv T15 87.65 Iu FT 2 1328 2.81 830.01 607184.59 2994920.59F48 3.27 Iwv T27 20.34 Iu FT 4 1603 2.82 1276.85 609325.75 2986729.90F22 86.54 Iwv RI 28.23 Iu FR 1 2192 2.85 692.79 611900.69 2981693.68F64 2.87 Iwv U13 3055.16 Iu FT 5 933 3.00 1016.15 601039.83 3000200.13E22 60.71 Iwv 1J6 19.85 Iu ET 1 646 3.17 1269.02 597793.78 2995806.86F76 5.33 Iwv T15 87.65 Iu FT 4 1068 3.66 901.56 603084.22 2998156.80F33 38.23 Iwv U8 39.58 Iu FT 1 1357 3.68 1167.31 607518.38 2993977.66F25 23.35 Iwv R14 46.09 Iu FR 2 636 3.70 1731.50 597782.03 3003817.73 H2 89.91 Iwv U2 120.51 Iu HT 1 902 3.96 1013.91 600767.22 2999508.52F45 82.88 Iwv U6 19.85 Iu FT 1 2181 4.00 842.06 611746.43 2980274.54F66 6.35 Iwv U13 3055.16 Iu FT 4 483 4.06 1161.29 596329.63 3001380.12 E9 125.88 Iwv Ul 74.27 Iu ET 1 592 4.08 925.32 597349.39 3002835.06 E15 6.33 Iwv R8 157.10 Iu ER 4 1310 4.24 1283.39 607064.75 2994640.07F25 23.35 Iwv T27 20.34 Iu FT 2 1576 4.32 1136.58 609128.26 2989036.44F52 39.36 Iwv U9 30.83 Iu FT 2 1248 4.47 1099.99 605808.23 2985407.18 F4 19.90 Iwv T44 230.42 Iu FT 3 2176 4.62 1052.45 611503.22 2981174.58 F65 4.62 Iwv U13 3055.16 Iu FT 5 312 4.72 1186.84 594781.22 2999480.54 E7 39.84 Iwv R18 11.10 Iu ER 2 2131 5.26 976.13 611309.59 2978191.43 MS 6.74 Iwv U13 3055.16 Iu ET 4 1036 6.11 1479.02 602688.36 2998392.70 F33 38.23 Iwv U7 35.92 Iu FT 2 83 8.69 1836.15 592682.51 2999366.12 E6 162.48 lwv R7 25.09 Iu ER 1 2040 8.72 1406.04 610725.21 2980720.73 F 1 1 31.60 lwv U13 3055.16 Iu FT 3 254 9.70 1293.11 594284.32 2997838.73E24 51.77 Iwv T12 18.27 Iu ET 2 2092 10.46 1692.66 611285.71 2982016.50F63 14.03 Iwv R26 39.32 Iu FR 4 370 10.94 2901.17 595392.45 3005389.38Hi 118.13 Iwv T22 43.37 Iu FIT 1 512 13.90 2120.29 596745.27 3000260.33 E9 125.88 lwv R8 157.10 lu ER 2 67 14.22 3814.56 592653.22 2996551.97E12 18.09 Iwv V2 231.35 Iu EV 4 454 15.02 3168.89 596388.20 3004308.16Hi 118.13 Iwv T22 43.37 Iu HT 2 698 15.09 2318.91 598400.36 3000839.67E25 219.11 Iwv T18 25.53 Iu ET 1 563 15.26 2821.50 597490.24 3002079.44E25 219.11 Iwv R8 157.10 Iu ER 1 2025 16.84 2061.78 610886.08 2977712.20E16 16.84 Iwv U13 3055.16 Iu ET 5 570 18.06 2682.99 597487.63 3004166.13 H2 89.91 Iwv U15 23.89 Iu HT 3 2132 20.55 2616.24 611619.09 2981999.26F12 174.81 Iwv R26 39.32 Iu FR 2 571 26.50 4801.71 597410.38 3003365.97 H2 89.91 Iwv U5 82.05 Iu HT 3 729 43.07 4966.73 598999.09 3001257.65E25 219.11 Iwv T19 59.17 Iu ET 2 2058 46.24 2891.07 611232.88 2984578.56 E4 102.98 Iwv U13 3055.16 Iu ET 3 2136 48.61 6708.68 611550.76 2982310.54F12 174.81 Iwv U13 3055.16 Iu FT 3 1283 0.26 628.26 606362.71 2994832.69F25 23.35 lwv B1 6033.70 Iw FB 2036 0.29 244.30 610707.53 2981477.12F61 8.57 Iwv B1 6033.70 Iw FB 247 0.29 429.47 594125.65 3000377.36E23 35.81 Iwv B2 2266.96 Iw EB 968 0.31 295.99 601265.83 2998752.66F45 82.88 lwv 82 2266.96 Iw FB 1936 0.32 263.44 610323.73 2979216.96F70 1.20 Iwv B1 6033.70 lw FB 151 1 1 1 1 1 1 3 2 4 5 2 2 4 2 5 4 5 1 1 1 1 1 1 1 1 1 2 3 2 3 4 2 2 3 3 1 1 , "r 2 FB FB FB ED FB EB EB FB ED FB FB FB FB FB FB FB FB FB EB FB FB FB FB FB FB FB FB FB FB FB FB ED FB FB FB EB EB FB FB FB FB FB FB FB FB FB EB FB FB EB FB FB FD FB FB FB FB FB FB FB EB FB FB FB Type Intensity EB FB FB FB FB 91 Iw Iw Iw Iw lw Iw Iw Iw Iw Iw lw Iw Iw lw lw lw Iw Iw lw lw Iw Iw lw Iw Iw Iw Iw lw Iw Iw Iw Iw Iw lw Iw lw Iw Iw lw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw lw Iw Iw Iw Iw lw lw Iw Iw lw Iw lw Iw Iw Iw Iw Iw lw Iw lw Lucid Arest91 2266.96 2266.96 2266.96 2266.96 6033.70 2266.96 6033.70 6033.70 6033.70 2266.96 6033.70 6033.70 6033.70 6033.70 2266.96 6033.70 6033.70 2266.96 2266.96 2266.96 6033.70 6033.70 2266.96 2266.96 2266.96 2266.96 2266.96 2266.96 2266.96 2266.96 6033.70 6033.70 6033.70 6033.70 6033.70 6033.70 2266.96 2266.96 6033.70 6033.70 6033.70 6033.70 6033.70 6033.70 6033.70 2266.96 2266.96 6033.70 2266.96 6033.70 6033.70 2266.96 2266.96 6033.70 6033.70 6033.70 2266.96 2266.96 6033.70 6033.70 6033.70 6033.70 6033.70 2266.96 6033.70 2266.96 6033.70 2266.96 6033.70 91 B2 82 B2 B2 B1 B2 B1 B1 B1 B2 B1 B1 B1 B1 B2 B1 B1 82 B2 B2 B1 B1 B2 B2 B2 B2 82 B2 B2 B2 B1 B1 B1 B1 B1 81 B2 B2 B1 B1 B1 B1 B1 B1 B1 B2 B2 B1 B2 81 B1 B2 B2 B1 B1 Bl B2 B2 Bl Bl B1 B1 B1 82 B1 B1 B2 B2 B1 73 Iwv lwv lwv Iwv Iwv Iwv Iwv I%w lwv I%w Iwv Iwv Iwv lwv Iwv Iwv Iwv lwv I%w Iwv Iwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Iwv lwv lwv lwv Ivry Iwv Iwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Lucid lwv lwv Iwv Iwv Iwv 4.73 1.77 1.08 1.06 1.43 3.22 0.63 4.73 4.74 0.84 1.34 1.74 34.54 14.85 12.55 11.73 3.96 7.96 1.35 1.44 8.63 125.88 34.54 35.21 39.84 24.55 34.54 35.21 39.84 11.73 34.54 82.88 11.73 12.55 4.97 4.38 3.77 7.96 135.58 82.88 53.20 24.55 53.20 39.84 82.88 86.54 17.49 16.43 14.85 Area73 135.58 174.81 174.81 35.81 35.21 82.88 35.21 82.88 20.43 35.21 57.86 24.55 53.20 10.18 39.36 174.81 135.58 135.58 135.58 135.58 73 E9 E7 F38 F30 E7 E7 F5 F30 F13 E21 F58 E19 F30 F13 F71 F24 F69 F38 F20 FIO F27 F31 F57 FIO F36 Fl E5 F5 F8 F31 F30 F28 F44 F45 F45 F43 FIO Eli F58 F20 F12 Eli F45 F12 F22 F50 F72 F51 F21 F26 F68 E23 E21 F13 F29 F45 F19 F13 F12 F31 F45 F49 F13 F58 Eli F31 F31 F31 F52 P Y(UTM) 2999002.27 2999680.72 3000279.55 2999773.49 2983096.54 2999292.48 2984616.19 2983742.96 2979639.85 2999902.08 2983889.78 2983228.01 2985659.72 2979717.34 2998976.71 2985501.37 2980692.35 2996834.30 2999537.21 2999352.86 2982899.56 2980820.99 2998236.63 2999991.25 2999913.64 2999608.22 2998579.77 2998285.28 2999403.82 2998285.71 2980917.03 2986214.10 2984629.88 2985508.22 2982729.41 2987156.89 2999401.93 2998430.08 2982459.57 2986659.65 2984022.45 2988326.90 2987072.50 2988158.89 2984805.04 3000069.87 2995298.76 2989416.22 3000162.12 2984374.11 2983438.38 2999584.93 2998686.85 2984482.23 2983099.30 2982620.77 2999809.28 2998991.25 2987672.63 2983723.01 2983676.14 2983625.65 2986342.28 2999241.68 2984343.01 2982658.21 2998952.52 3000330.21 2988076.15 595176.76 595770.65 597289.34 594879.36 609546.43 595656.94 609363.39 610049.92 609749.57 595130.98 608975.13 609977.26 609315.73 609677.40 595685.48 594183.00 595169.58 597779.14 609139.53 609881.00 609299.14 609467.78 595461.71 596031.63 595427.46 595516.84 601982.35 598738.96 600377.78 602004.04 609809.80 609257.57 610545.55 609491.53 610661.34 607697.61 594638.93 598641.64 610465.40 609954.65 607215.64 608236.46 605562.30 608259.68 610261.14 594136.75 598721.25 605130.82 595745.07 609420.30 609457.06 595302.65 601582.70 609409.55 609818.83 609374.50 598398.80 600864.93 608187.29 596901.73 609488.06 610149.07 610111.99 608725.15 607117.14 608077.39 596276.65 597422.97 608613.60 391.25 360.89 317.78 416.50 328.92 326.48 353.72 343.27 284.59 518.83 338.66 389.08 457.36 401.37 401.28 420.56 382.00 397.39 445.48 762.73 640.37 727.66 735.55 508.18 444.30 448.93 473.31 914.74 575.93 573.94 493.95 784.33 548.94 724.20 703.85 490.40 533.36 866.18 783.14 477.28 467.38 470.62 705.68 536.18 836.14 581.39 694.30 703.74 885.15 964.12 791.03 996.89 P Perim P_X (UTM) P Perim P_X 1139.51 1077.11 1443.00 1041.60 1804.19 1562.72 1559.42 1265.91 1698.82 2167.48 2003.59 1708.00 1963.93 1346.38 1858.77 1619.71 3019.70 0.36 0.37 0.40 0.41 0.43 0.44 0.45 0.45 0.47 Area 0.47 0.55 0.56 0.58 0.60 0.60 0.61 0.64 0.66 0.81 0.81 0.81 0.84 0.84 0.87 0.88 0.95 0.97 0.99 1.01 1.01 1.09 1.11 1.12 1.15 1.22 1.25 1.25 1.26 1.27 1.29 1.29 1.35 1.36 1.44 1.44 1.52 1.61 1.63 1.68 1.92 1.87 2.00 2.06 2.09 2.13 2.44 2.79 2.81 2.91 3.33 3.37 3.58 3.61 3.68 3.80 4.07 4.20 4.67 5.52 369 449 598 339 438 364 432 252 362 625 GIS- 1728 1668 1836 1772 1573 1834 1639 1746 415 462 403 414 762 887 313 746 1616 1799 1643 1680 1015 1021 1781 1623 1983 1663 1387 241 755 437 358 980 682 911 522 Label 2027 1939 1818 1339 1500 1233 1479 1879 1201 1664 1646 1665 1751 1674 459 575 1448 1696 1815 1788 1509 1319 1416 1502 152 5 1 4 4 3 3 2 4 1 2 2 5 4 5 4 1 1 2 4 1 3 1 3 1 1 1 1 1 C1 - ff) ... v... 2 3 2 4 2 3 4 FB FB FB FB FB EB FB FB EG FD FD EG FD EG ED ED FD FD FD FD FD FD ED FD FD FD FD FD FG FD FD ED ED FD FD ED ED FD FD FD FD ED FD ED ED FD ED FD FG FD FD FD FD ED ED ED FD FD FD FD ED ED FD Type Intensity ED ED ED FD FD EG 91 lw Iw Iw Iw Iw Iw Iw Iw Iwn Ivm Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn lvm Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Ivm Iwn Iwn Iwn Lucid Iwn Iwn Iwn Iwn Iwn 5.67 4.21 5.67 5.67 5.67 76.88 34.15 14.47 14.47 2.72 6.27 6.27 6.27 76.88 34.15 73.63 78.62 73.63 73.63 73.63 73.63 13.03 241.99 470.63 73.63 76.88 76.88 76.88 76.88 78.62 18.23 87.77 Area91 6033.70 6033.70 6033.70 6033.70 6033.70 2266.96 2266.96 470.63 470.63 241.99 470.63 158.50 241.99 470.63 241.99 241.99 153.72 158.50 470.63 117.20 153.72 153.72 117.20 117.20 102.66 158.50 6033.70 2336.36 2336.36 2336.36 2336.36 241.99 241.99 470.63 241.99 2336.36 2336.36 91 B1 B1 B! B1 B1 B2 B2 Bl 01 GI GI D3 D4 D4 D3 GI D3 D3 D25 D26 D8 D8 D6 D8 D5 GI D6 D6 D14 D13 D25 D19 D14 D13 D13 D18 D21 D18 D18 D5 DI D5 D2 01 D26 D20 D13 D18 D10 D26 D13 D26 D26 D18 DIO D13 D18 D26 D25 D26 D25 D25 D17 D25 D13 DIO D21 D1 1 D26 73 Iwv lwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv I%w Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv lwv lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv lwv Iwv lwv lwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Iwv Iwv lwv lwv Iwv Iwv Iwv Iwv lwv lwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Lucid Iwv 9.27 6.21 9.16 11.88 9.16 4.70 1.87 16.30 39.84 82.88 19.90 18.09 86.54 18.09 12.55 17.49 4.32 8.57 3.68 2.49 4.74 5.60 174.81 24.55 53.20 38.23 82.88 53.20 82.88 28.22 28.22 24.55 53.20 12.63 14.03 135.58 125.88 219.11 135.58 135.58 28.22 28.22 82.88 28.22 35.81 51.77 82.88 35.81 35.81 28.22 17.49 12.55 39.36 17.49 86.54 10.98 Area73 125.88 162.48 135.58 174.81 102.98 60.71 51.77 39.80 24.55 102.98 102.98 162.48 162.48 73 F9 F7 F3 F4 E7 E9 F12 F14 F45 E9 E6 E3 E8 E12 F22 E12 F58 F31 E25 Eli F16 F20 F33 F31 F16 F45 Eli F45 F31 F21 F46 F46 F35 F58 Eli F15 F46 F46 E4 E4 E4 E6 F2 E6 E14 F31 F61 F45 F63 F46 E23 E24 F45 F55 F27 E23 E23 F46 F54 F12 F21 F20 F52 F21 F22 E22 F47 E24 F58 2982005.70 2985221.40 2983192.95 2982072.07 2986905.16 2999682.51 2998115.73 2984603.54 2996275.18 2985323.10 2996452.10 2984196.59 3000532.78 3001329.05 3001117.08 2986973.90 2986255.92 2985273.08 2997260.06 3000635.81 2986331.57 2986839.33 3000028.00 2999848.40 2999680.35 2985159.11 2999607.73 2999817.05 2996350.22 2983849.10 2986640.21 2986692.49 2999727.58 2999924.87 3000038.47 2999642.49 2998889.30 2999398.01 2981110.47 2999950.28 2982236.93 2982644.88 2999239.62 3000873.14 2997454.68 3000074.44 2999494.39 2986706.19 2996703.21 3000561.51 3000336.61 2999626.86 2987384.86 2983391.29 2985030.76 2984336.62 2985334.56 2988814.59 2984835.72 2986634.16 3000814.84 2984873.55 3002222.92 2998168.87 2985147.74 2998972.15 2991136.39 2983685.66 2999601.80 608535.61 606601.11 607388.85 609925.51 608095.94 595337.01 599107.64 606408.62 593163.93 610110.43 593183.34 610148.59 598443.68 596035.31 599269.56 607613.22 607824.72 609549.61 603448.33 598274.86 608116.30 598521.66 600298.63 607587.91 600171.11 610763.26 599609.78 599618.88 593195.84 610123.95 607795.66 607680.26 597872.13 599911.23 599642.81 596279.52 592656.96 596104.84 610913.08 600439.45 611050.82 611051.47 599563.12 592620.79 594131.90 600576.58 596229.96 594077.19 592971.55 593368.34 599228.07 610984.84 610879.23 611199.11 610612.62 610922.85 609201.78 609311.85 610102.68 610493.43 600836.12 610854.68 599592.47 594421.10 610963.34 593487.12 609505.48 610710.83 591449.56 1812.96 223.93 254.31 230.89 395.16 271.50 292.02 560.81 492.07 542.31 386.86 453.15 505.57 377.41 368.36 535.00 344.37 549.06 418.42 550.46 807.39 2687.57 2660.85 2096.94 2327.51 3257.86 3809.32 4085.24 405.31 646.67 663.39 686.04 737.32 556.28 754.55 577.11 860.04 923.53 617.39 589.16 691.14 868.33 644.16 797.32 745.39 759.08 875.53 846.58 950.58 P Perim P_X (UTM) P_Y(UTM) P Perim P_X 1036.37 1058.85 1453.72 1075.66 984.62 1314.80 1320.63 1081.13 1394.43 1368.34 1765.25 1720.77 2154.66 2130.05 2052.75 2169.77 2082.73 2647.49 2159.59 3653.36 5.55 5.83 7.14 7.25 7.68 0.28 0.30 0.31 0.31 0.33 1.16 Area 11.60 12.69 14.50 0.40 0.42 0.45 0.47 0.53 0.57 0.59 0.60 0.63 0.64 0.68 0.68 0.69 0.70 0.73 0.81 0.88 0.97 1.25 1.26 1.27 1.39 1.40 1.52 1.58 1.82 1.87 1.87 1.91 2.01 2.08 2.22 2.44 2.49 2.58 2.83 2.96 2.99 3.22 3.31 4.65 4.95 5.45 7.08 8.04 8.12 8.39 8.43 9.37 10.15 10.17 10.43 10.75 13.30 15.76 337 744 151 154 87 97 718 458 793 699 886 874 722 827 816 152 GIS- 1486 1295 1324 1729 1403 1267 1859 1882 1381 1396 1710 653 860 824 479 467 891 823 237 901 475 204 116 147 47 1088 1436 1375 2047 1869 1397 1383 786 918 813 277 128 Label 2076 2093 2117 2094 2059 2134 1968 1597 1618 1761 1961 2056 2055 2048 1604 1985 153 2 3 2 3 4 4 3 1 1 I 1 2 4 1 3 3 3 1 2 1 1 2 1 1 1 5 1 1 1 I 1 1 1 1 1 --.1 V1 re', VI 2 3 2 5 5 4 3 4 4 3 EF FE FE EF EF EF ED FD ED ED ED ED FD EF EF EF EF EF FE EF FE EF FE FE EF EF EF FE EF EF FE FE EF EF FE EF FE EF FE FE EF EF FE EF FE EF FE EF FE FE EF EF EF EF EF FE FE EF FE EF EF EF EF EF EF IS RS EH TO Type Intensity 91 Iwn Iwn Win Iwn Iwn Iwn Iwn Iwv Iwv Iwv Iwv lwv II IL II Iwv lwv Iwv Iwv lwv Iwv lwv lwv lwv lwv Iwv lwv lwv lwv lwv lwv Iwv Iwv lwv lwv Iviv lwv lwv lwv lwv lwv lwv lwv Iwv Iwv lwv lwv lwv lwv lwv lwv lwv Iwv lwv Iwv lwv lwv Iwv Iwv lwv lwv lwv Iwv lwv lwv lwv Iwv Iwv Iwv Lucid 4.75 5.53 0.64 8.97 5.71 5.71 2.23 88.20 24.31 76.88 30.40 20.93 71.31 85.55 71.31 30.40 71.31 25.53 60.92 71.31 153.72 30.71 60.62 61.23 71.31 31.15 71.31 71.31 60.62 61.23 85.55 31.15 470.63 241.99 241.99 62.03 21.10 60.62 60.62 30.71 30.40 30.40 25.55 85.55 25.53 25.55 23.26 71.31 62.03 35.20 57.24 12.94 Area91 279.10 308.05 279.10 308.05 170.97 279.10 170.97 170.97 170.97 170.97 308.05 308.05 308.05 279.10 308.05 196.96 325.04 91 D9 E4 D6 E7 E7 F76 E19 E14 F14 F77 F17 F15 F34 F14 F76 F14 E7 E7 E4 F9 Si D12 D25 D13 D26 D26 F25 E16 F14 EIO F77 F18 F20 EIS F14 F25 E23 E27 F14 F14 F77 F17 HI 02 E 1 5 E23 E27 F20 F32 E12 F25 F25 F38 EIO E27 F25 F76 F76 F13 F17 E27 F13 E27 F77 F25 F75 F14 F32 S23 73 Iwv Iwv lwv lwv lwv lwv Iwv lwv lwv lwv lwv lwv lwv lwv Iwv hvv lwv Iwv Iwv lwv lwv lu Iu lu Iwv lwv Iwv Iwv lwv Iwv Iwv Iwv lwv lwv Iwv lwv lwv Iwv lwv lwv lwv lwv lwv lwv Iwv Ii.vv Iwv lwv lwv lwv lwv lwv Iwv Iwv lwv lwv lwv Iwv Iwv lwv lwv Iwv lwv Iwv Iwv Iwv lwv lwv lwv Lucid 0.42 2.03 1.77 0.74 6.35 3.68 5.88 6.35 43.65 60.71 57.86 28.22 39.84 39.84 39.84 39.84 86.54 12.63 82.88 34.54 51.77 18.09 12.63 18.09 10.98 2.42 8.19 125.88 162.48 102.98 174.81 102.98 135.58 125.88 102.98 125.88 135.58 39.84 82.88 28.22 12.63 53.20 34.54 60.71 57.86 57.86 35.81 86.54 14.79 10.19 14.85 135.58 125.88 125.88 135.58 162.48 135.58 135.58 35.81 39.84 51.77 53.20 38.54 45.17 Area73 219.11 125.88 125.88 219.11 207.92 73 E9 E6 E4 E5 E4 E7 E9 E7 E7 E4 E7 E9 El E7 E9 E9 E8 E6 F37 E22 F12 F31 F46 EIO E13 F22 E14 F45 F30 F31 E5 E5 E9 E2 E9 E7 R4 E24 El2 F31 E14 F45 F66 F31 E19 F46 F77 F66 E12 F47 E25 F31 E14 F31 F30 F67 Eli E22 E23 F22 F59 E23 F17 E21 E24 Eli E25 TIO T15 3001149.08 3000516.63 2999431.06 2985234.97 3001105.49 2984073.61 2982184.04 2984534.85 3000012.65 2999467.52 2999680.38 2980457.80 2999647.06 2999225.50 2999615.80 2999883.14 2984921.37 2999855.13 2986876.48 2999758.68 2999611.01 3000030.15 3000189.73 2999729.63 2980817.29 2997812.84 2996239.64 3000159.43 2999649.18 3000195.74 2999199.95 2980202.16 3000199.98 2999942.32 2999859.33 2979556.92 2999841.68 2999461.96 2999633.74 2980406.20 2996448.11 2998923.70 3002112.69 3000738.29 2999637.58 2999680.72 2999941.50 2986828.63 3000088.23 2980586.74 3000268.03 2984511.52 2983626.95 3000569.14 2999449.51 2986904.01 2978547.00 3000072.30 2979551.70 2980793.39 3000237.18 2984342.64 2999477.95 2998360.30 2986214.32 3002238.78 2992194.66 2991357.03 2999840.58 595897.90 593347.78 591472.93 610167.75 600387.30 610458.61 610317.39 610725.51 597935.81 599339.41 595176.74 596914.54 595130.72 595424.48 595336.18 610353.30 610301.31 594962.34 610694.24 597617.57 600834.00 594668.82 595512.06 596837.94 610202.10 594173.69 593086.67 598887.86 595566.45 598106.73 601645.25 611657.50 595597.66 594498.73 596497.62 609725.49 599099.39 596283.12 601330.23 611806.67 593093.40 593772.93 599658.84 597971.98 597038.74 597856.01 596263.25 595117.89 607648.69 611582.83 601086.56 610514.58 610356.18 593996.89 596318.41 610398.75 610969.17 593890.80 611446.50 610022.99 597195.66 609339.21 595179.81 594498.15 608773.55 598526.27 608174.79 609915.11 592382.31 386.38 354.00 239.50 342.72 734.99 269.69 424.70 350.51 338.72 482.95 596.83 476.67 582.77 5486.21 2749.17 8498.08 449.07 461.60 495.06 445.46 343.85 471.26 491.45 795.52 890.07 645.85 495.27 569.94 589.85 490.85 756.22 636.41 563.15 687.49 638.52 602.95 551.74 586.95 590.05 666.77 924.38 689.61 897.33 938.21 775.66 795.34 3480.23 4584.65 4126.15 3692.82 1097.18 252.48 460.03 548.95 P_Perim P X (UTM) P_Y(UTM) P_Perim P 1042.76 1386.42 1255.83 1307.73 1327.10 1285.23 2063.49 2251.97 3132.28 2823.92 2722.72 3216.54 4472.66 6832.28 6327.88 Area 19.25 0.27 0.27 0.30 0.31 0.38 0.41 0.43 0.51 0.53 0.54 0.57 0.61 0.62 0.64 0.67 0.69 0.74 0.74 0.80 0.88 0.92 0.98 1.00 1.00 1.01 1.08 1.12 1.14 1.20 1.20 1.23 1.33 1.34 1.35 1.36 1.61 1.78 1.85 1.88 21.67 22.71 28.69 31.62 48.05 61.96 2.00 2.16 2.22 2.41 2.62 2.64 3.33 4.09 4.98 5.23 6.32 6.79 8.19 9.63 10.41 0.26 0.29 0.30 12.28 17.77 28.76 41.67 47.39 46 344 139 880 662 802 374 555 363 410 398 548 134 130 80 1760 1881 1839 338 627 920 314 412 255 767 411 679 990 419 291 519 785 482 966 185 844 561 195 176 GIS- 2046 1909 1905 2015 1900 1756 652 631 484 347 940 480 553 305 248 675 Label 2183 2188 1373 1976 1877 1911 1784 1626 1393 1464 1820 2173 2064 2168 154

GIS- Area P_Perim P_X (UTM)P_Y(UTM) 73 Area73Lucid 91 Area9I LucidType Intensity Label 73 91 1742 0.50 360.38 609645.27 2990675.12 RI 506.29 Iu 12 6200.17 Ii RI 1097 0.57 473.27 603649.12 2998648.77U23 46.21 Iu 11 10031.38 II TI 259 0.62 364.48 594264.99 3005408.16T27 140.04 Iu S26 114.55 II TS 1162 0.66 566.71 604748.53 2996544.39R31 96.84 Iu 11 10031.38 II RI 1474 0.71 439.38 608298.90 2994503.93 U 1 1 193.41 lu 12 6200.17 II TI 2119 0.78 567.65 611221.97 2987661.93 RI 506.29 Iu S5 65.03 II RS 416 0.81 387.71 595547.74 3005568.89T26 165.18 Iu S26 114.55 II TS 1579 0.82 1135.00 609243.80 3001709.63T46 58.21 Iu Ii 10031.38 II TI 1512 0.96 531.83 608424.05 2992030.57RI 506.29 Iu 12 6200.17 II RI 1476 1.03 466.24 608303.39 2992138.49T10 38.54 lu 12 6200.17 II TI 946 1.14 970.08 601075.52 3003463.45T14 212.74 Iu II 10031.38 II TI 1094 1.35 577.56 603636.86 2997575.22U22 51.44 Iu Ii 10031.38 II TI 989 1.39 1064.88 601762.33 3004320.07T14 212.74 Iu 05 8.13 II TO 132 1.60 625.68 593141.20 3005708.69T28 87.59 1u S24 1.68 II TS 1807 1.72 644.48 609971.90 3001713.27146 58.21 Iu Ii 10031.38 II TI 1384 1.98 785.99 607843.61 2994495.54Ul 1 193.41 Iu 12 6200.17 II TI 1268 2.50 757.95 606005.89 2995985.54R31 96.84 Iu 11 10031.38 II RI 1516 2.76 1902.55 608638.09 3001456.02T46 58.21 1u Ii 10031.38 II TI 1524 2.87 750.73 608313.82 2993998.27 Ul 1 193.41 Iu S12 2.87 II TS 1420 2.98 1360.46 608188.49 2995847.13 R7 61.37 Iu Ii 10031.38 II RI 951 3.35 1153.45 601255.42 3003889.82T14 212.74 Iu I 1 10031.38 II TI 1127 3.39 1020.74 604028.13 2997271.93 R5 24.94 1u Ii 10031.38 II RI 1825 3.72 1042.67 609986.47 2990853.74 RI 506.29 Iu S 1 57.24 II RS 1916 3.90 1344.33 610342.21 2987698.17 RI 506.29 1u S5 65.03 II RS 1093 3.96 1034.56 603626.69 2997685.81 R5 24.94 Iu Ii 10031.38 II RI 1086 4.00 1271.90 603517.10 2997855.51U22 51.44 Iu Ii 10031.38 II TI 1131 4.01 2103.12 604530.50 2998903.90U23 46.21 1u Ii 10031.38 II TI 912 4.04 1036.61 600813.17 3004414.62114212.74 Iu Ii 10031.38 II TI 1037 4.11 1269.91 602645.61 2998876.75U14 33.08 Iu Ii 10031.38 II TI 1101 4.41 1796.28 603968.13 2998426.29U23 46.21 Iu II 10031.38 II Ti 2104 4.61 1111.73 611262.54 2987594.88R30 792.86 Iu S5 65.03 II RS 1004 4.97 898.67 602045.71 3004986.03TI4 212.74 Iu S9 22.33 II TS 1028 5.39 1728.50 602383.84 2998421.65T46 58.21 lu II 10031.38 II TI 1130 5.59 1252.66 604308.21 2997122.73T42 37.50 Iu Ii 10031.38 II TI 2 1062 5.88 1038.71 603020.22 3000939.24T43 5.88 Iu 11 10031.38 II TI 5 289 5.96 1102.30 594590.42 3003230.08T23 5.96 Iu N3 208.84 II TN 5 1963 5.97 1858.72 610612.61 2987514.80R30 792.86 Iu S5 65.03 II RS 1 1504 6.23 1118.40 608495.40 2994257.30 U 1 1 193.41 lu S13 7.33 II IS 2180 6.59 1512.42 611382.50 2993292.50 R8 6.59 Iu 12 6200.17 II RI 5 2284 7.22 1266.20 613904.71 2981699.13 T5 555.04 Iu S22 25.05 II TS 2124 7.30 1763.70 611249.33 2988399.57 RI 506.29 Iu 12 6200.17 II RI 1 1172 7.50 1298.92 604926.69 2996286.07Iii 7.68 Iu 04 23.87 II TO 5 1667 7.70 1432.84 609504.44 2989205.98 RI 506.29 Iu 12 6200.17 II RI 1 759 8.34 1374.70 598842.33 3003525.98T13 128.72 Iu Ii 10031.38 II TI 1 1316 8.48 1430.02 606902.00 2995061.44U9 15.17 Iu II 10031.38 II TI 4 175 9.20 1606.17 593815.68 3005635.88T27 140.04 Iu S25 13.12 II IS 1 1435 10.52 1499.46 608269.11 2995281.65U10 10.52 Iu 12 6200.17 II TI 5 431 11.89 1670.34 595958.76 3005433.13127 140.04 Iu S7 65.85 II TS 1 1334 13.57 2127.49 607545.39 2994462.50Ul 1 193.41 Iu S20 15.99 II TS 1 736 14.12 1708.63 598713.35 3003372.96113 128.72 Iu S6 28.33 II IS 2 1471 14.86 1770.62 608330.83 2990215.85 19 38.92 Iu 12 6200.17 II TI 3 1170 16.36 2714.58 605019.57 2996092.95 R31 96.84 Iu 04 23.87 II RO 2 1426 16.65 2617.11 608089.52 2992627.71Ull 193.41 Iu S23 35.20 II TS 1 1990 16.99 3154.07 611057.11 2988002.25 121 506.29 lu S5 65.03 II RS 1 1689 17.09 2050.31 609587.62 2987210.89 U7 20.69 Iu 12 6200.17 II TI 4 474 17.26 2153.24 596466.87 3004889.39T26 165.18 Iu Ii 10031.38 II TI 2 2283 17.82 1695.80 613815.39 2981434.27 Ii 123.82 Iu S22 25.05 II IS 2 1044 17.86 4044.69 603068.89 2999071.98U14 33.08 1u Ii 10031.38 II TI 4 1140 18.72 1781.35 604579.79 2996686.13142 37.50 Iu 11 10031.38 II TI 3 1366 22.69 3167.28 608035.16 2995508.74 R7 61.37 Iu 12 6200.17 II RI 3 1884 23.81 3287.39 610540.69 2988870.78R25 23.81 Iu 12 6200.17 II RI 5 1084 24.15 4004.80 603999.28 2998875.52T46 58.21 Iu 11 10031.38 II TI 3 1256 28.21 7293.92 606955.79 2999854.94146 58.21 Iu I I 10031.38 II TI 3 1698 29.24 3761.35 609781.03 2988933.69 U8 30.62 lu 12 6200.17 II TI 5 1333 29.70 2290.43 607324.29 2995334.10 R7 61.37 Iu Ii 10031.38 II RI 3 1490 34.77 2692.03 608650.40 2992163.09 U 1 I 193.41 Iu 12 6200.17 II TI 2 1423 39.82 4251.80 608376.97 2993647.78Ul 1 193.41 Iu 12 6200.17 II TI 3 1014 41.58 3672.04 602369.00 2999119.64R20 43.23 Iu II 10031.38 II RI 5 429 42.06 4497.61 596214.18 3004733.52T26 165.18 Iu S7 65.85 II TS 3 155 1 1 1 5 4 4 2 3 1 1 1 1 1 1 1 5 2 2 5 1 5 5 1 1 1 1 1 1 cy .. (.4 .. .s - ..1 2 2 2 3 3 2 1 1 RI RI RI RI RI RI TS TL RL TL TL RN RL VL RL RL RIC TK RIC TV RT TV VP VT VT TV VT TR TV VT RT VT RT VT VT RT TR PT VT RT VT TP PT TP PV PT TV VT TR RT TV RT RT TV VT RT TP RT VT TP RT Type Intensity TV RT TV TR TR TR TV TR II II II II II II II II 91 III III III Iu lu lu Iu Iu lu lu III III III III III III III III lu Iu Iu lu lu lu Iu Iu lu Iu Iu Iu Iu lu lu lu Iu lu lu lu lu lu lu lu Iu lu lu Iu lu lu lu Iu lu Iu Iu lu lu lu lu Iu lu lu lu Lucid 0.31 0.44 0.56 0.67 3.96 4.99 5.32 1.49 18.86 12.04 0.45 6.70 2.26 40.49 21.95 40.49 83.99 13.21 3.10 114.55 114.24 96.16 74.27 87.65 20.34 87.65 83.99 80.27 2.80 39.58 96.16 82.05 83.99 80.27 80.27 83.99 59.17 96.16 83.99 82.05 80.27 Area91 221.64 221.64 249.45 249.45 221.64 249.45 198.32 157.10 110.01 110.01 249.45 198.32 120.56 198.32 110.01 160.03 96.16 25.09 6200.17 6200.17 6200.17 6200.17 6200.17 198.32 120.51 157.10 10031.38 3055.16 91 12 12 12 12 11 12 Ni L2 Li PI S26 K2 K1 K2 VI VI VI V5 PI 121 L27 L13 L69 Ul R8 V4 R5 V5 U5 PI V4 V4 PI PI L28 L12 T34 T16 T16 T16 R10 U8 V5 U2 U5 V5 R7 R8 R2 V4 R6 U13 T15 T27 T11 T15 T35 T14 T14 T23 T42 T16 T11 T20 Ti! T14 T40 T19 T11 Iu lu Iu Iu lu Iu 73 lu Iu lu Iu lu Iu lu lu lu Iu Iu lu lu Iu Iu Iu Iu lu Iu lu lu lu lu Iu lu Iu Iu Iu lu Iu lu Iu Iu lu Iu Iu Iu lu Iu Iu lu lu Iu lu Iu lu Iu lu lu Iu lu Iu lu Iu lu Iu Iu Iu Iu lu Iu Iu Iu Lucid 3.96 4.66 0.33 0.43 5.54 4.66 1.40 45.17 96.34 58.21 61.37 61.37 96.34 96.84 83.46 13.31 13.61 4.86 7.69 506.29 792.86 792.86 140.04 792.86 506.29 193.41 193.41 193.41 136.73 136.73 136.73 34.00 64.76 83.46 61.37 83.46 62.20 83.46 28.69 62.20 24.94 10.98 62.20 84.33 13.61 11.66 58.37 16.82 Area73 792.86 792.86 208.16 233.17 106.03 106.03 106.03 62.20 58.37 58.72 1252.89 233.17 207.92 208.16 106.03 106.03 208.16 208.16 208.16 207.92 207.92 73 R4 RI R6 RI R7 V3 R7 R6 Ul V2 V2 V2 VI R7 PI PI P1 R30 R30 T27 R30 T46 Ull Ull R.30 R30 R31 T39 V7 VI V8 R5 V8 PI V9 Ull R26 V12 T40 U21 T33 R10 V12 V12 R26 T44 V12 R14 T48 U6 T48 T15 T33 R23 R19 T48 T49 R28 T48 R17 T33 T33 R17 R13 T33 T15 U18 T48 T15 2991590.08 2989934.50 2986991.53 2986497.13 3004943.64 2995443.03 2985735.71 2987490.38 3001686.52 2995608.99 2993845.75 2993824.89 2986900.78 3005182.39 2995537.01 2987041.54 2995186.57 2993518.90 2995865.47 2978138.66 2987252.70 2987196.29 2995226.77 2991161.20 2990616.09 2987030.94 2994448.97 3001705.44 2994436.86 2978289.91 3001068.01 2995383.44 2995049.95 2998998.05 2994942.38 2987067.20 3002710.42 2995736.42 2995537.95 3002557.88 2981587.26 2995606.94 2994447.89 2995363.68 2998841.42 3000128.46 2997589.95 2990359.92 3003515.26 3004360.79 2995872.64 2995018.60 2995315.33 2998633.66 2995512.62 2981324.69 2995370.27 3001847.14 2998902.71 2990869.86 2994658.45 3002607.60 3003226.62 2991334.50 2999673.35 3001692.81 2986374.38 2995873.71 2999843.81 609199.21 608719.73 611647.10 613707.87 595131.96 606543.44 610787.59 609960.15 609827.67 608308.05 608592.87 608196.36 611575.93 610224.39 607863.36 612051.43 605994.25 607803.82 605699.52 610625.21 610369.19 604947.11 597369.31 603884.21 604192.61 604863.02 599431.91 598548.43 599646.58 610530.83 597161.57 597820.35 607428.95 594805.82 598358.37 610292.91 597477.59 594961.95 596673.48 596596.30 608398.03 595354.83 599344.77 597090.60 595234.13 592869.03 597463.58 594810.61 603485.69 604235.75 600988.38 597893.86 598143.62 595451.25 596130.83 612091.13 596926.68 599192.25 595189.93 603995.13 599597.85 598509.11 597482.15 603852.98 592736.57 597381.74 607490.00 596635.60 592807.71 551.36 211.60 287.37 301.08 328.15 288.67 380.91 270.18 565.67 302.01 3392.54 3976.83 6629.97 3481.89 7201.88 1005.69 1018.67 1151.08 411.31 267.24 381.55 269.21 566.14 338.04 363.13 356.67 479.59 319.34 360.27 469.69 650.86 558.91 725.36 813.50 508.04 660.11 956.61 639.75 582.42 500.30 920.86 597.99 833.67 533.46 6112.23 4869.90 2140.61 2097.93 2233.38 1139.45 961.40 772.16 643.06 928.18 958.34 726.03 895.33 953.46 642.60 820.18 656.39 902.80 P_Perim P X (UTM) P Y(UTM) P_Perim P 13735.45 1589.61 1745.82 1571.89 1052.35 1067.34 1071.77 Area 0.30 0.31 0.44 0.56 0.67 3.96 4.82 5.32 0.30 0.31 0.33 0.37 0.38 0.43 0.43 0.45 0.45 0.50 0.52 0.54 0.56 0.62 1.05 1.09 1.14 1.19 1.22 1.25 1.32 1.34 1.35 1.40 1.40 1.40 1.50 1.55 1.68 1.73 42.34 44.76 58.30 65.92 77.23 81.77 10.62 12.79 16.96 0.62 0.62 0.68 0.91 0.91 1.79 1.84 1.93 1.96 2.02 2.05 2.19 2.26 2.30 110.58 144.09 2.49 2.51 2.64 2.71 2.72 2.74 257 809 GIS- 1546 1472 1265 1856 1637 1780 1495 1542 1468 600 730 818 567 656 322 707 612 342 521 516 375 795 554 361 113 95 98 2099 2277 2179 1860 1401 2205 1252 1390 1228 2008 1929 1190 1121 1135 1181 1988 1348 1919 1491 614 927 326 623 668 394 439 525 784 355 812 712 606 597 504 Label 1092 1137 1122 1109 2215 1352 156 1 1 1 5 3 5 2 1 1 1 1 1 1 1 1 1 1 3 3 3 3 3 1 1 3 1 2 1 1 1 4 2 3 3 4 3 3 3 2 3 1 1 1 ...... -. ei -.1 ..I .ml 4 2 3 1 4 1 RT RT VR VT TR VT TR VT VT RT RT TR TR TR RT RT RT RT VT VT RT RT RT RT TV RT RT RT RT PT TV VT TR RT VT RT TR RT TR RT RT RT PC VT VT TB TB TB VB TB TB TB TB RB TB TB VB VB TB TB Type Intensity TB TB TB VB RB VB TB VB TB Iu Iu Iu Iu Iu Iu lu Iu In Iu lu 91 Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu lu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iw Iw Iw Iw Iw Iw Iw Iw Iw lw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Lucid 4.14 7.06 3.58 5.99 7.06 8.71 6.70 5.07 8.78 39.32 21.35 59.17 25.53 17.63 12.04 12.04 16.80 9.26 39.32 59.17 30.83 82.05 16.87 230.42 249.45 160.03 38.07 87.65 27.08 74.27 46.09 62.68 86.31 23.90 Area91 249.45 231.35 221.64 110.01 157.10 120.56 249.45 230.42 3055.16 3055.16 3055.16 6033.70 6033.70 6033.70 2266.96 6033.70 6033.70 2266.96 6033.70 6033.70 6033.70 6033.70 2266.96 6033.70 6033.70 6033.70 6033.70 6033.70 2266.96 6033.70 6033.70 6033.70 6033.70 2266.96 6033.70 91 R4 U9 V2 VI T36 T44 R25 T16 R26 U14 T13 T19 T18 R25 R17 R26 U5 R8 R3 Ul BI C 1 B1 B1 B2 BI U13 U13 T35 U16 T40 T50 T16 T34 T19 T34 T30 T28 T14 T37 BI B2 BI B1 B1 B1 B2 B I B1 BI BI BI BI B2 B1 B1 B1 B2 B1 Ul 1 T15 T41 T20 R14 T16 U10 T44 T33 U13 73 Iu lu Iu Iu lu lu 1u Iu Iu Iu In Iu Iu Iu Iu 1u Iu Iu Iu Iu Iu Iu lu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu In Iu Iu Iu lu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu 1u Iu Iu Iu lu Iu Iu Iu lu Iu Iu Iu Iu lu Iu Lucid 2.96 3.83 15.35 41.20 27.49 18.10 11.66 11.66 1.63 1.65 1.66 136.73 27.49 23.29 83.46 13.31 0.63 4.86 506.29 233.17 233.17 233.17 219.84 207.92 140.06 792.86 506.29 136.73 28.69 62.20 58.37 41.20 64.76 62.20 39.60 10.48 Area73 233.17 792.86 506.29 506.29 247.36 506.29 506.29 792.86 792.86 193.41 136.73 39.60 83.46 233.17 792.86 233.17 506.29 792.86 208.16 208.16 247.36 106.03 247.36 247.36 208.16 233.17 208.16 208.16 247.36 247.36 233.17 247.36 208.16 73 RI R2 VI V2 U3 VI VI V4 T4 RI VI RI V2 RI RI R1 PI P1 T37 R12 R15 U12 T15 R28 R30 R28 R30 R15 T45 VI V2 VI RI R3 V9 VI T34 R14 R30 V12 T44 R30 R17 T37 R10 R30 T33 VI R30 T33 T34 VIO T35 T34 T48 T34 U25 T33 T33 T33 T34 T34 T35 V12 R33 T34 Vii T33 P Y(UTM) 2987787.84 2983628.37 2980284.56 2989269.66 2981788.39 2978505.50 2985134.22 2977712.73 2996880.90 3001351.65 3000754.19 2980368.99 2999498.60 2982059.62 2981130.82 2987160.95 2988219.67 2980743.95 2982080.31 2994207.73 2987405.48 3000843.20 2987401.73 2989364.11 2997949.46 2981213.81 2989285.68 2991208.01 3002854.03 2987110.31 2995765.82 3002431.28 2985588.55 2994659.77 2980856.67 3002277.24 2985022.86 3000856.02 2993976.76 U 1 1 2992969.01 2986381.70 2984470.27 2987478.67 2986680.22 2989264.35 2994864.29 2990122.55 2980987.76 2998998.69 2979342.64 2981372.39 2996330.05 2981568.60 2986292.32 2981866.48 2990460.67 2999023.53 2987023.70 2991249.71 2989613.87 2981201.14 2980763.55 2979947.08 2995683.87 2980790.52 2987472.73 2984778.24 2999213.97 2993390.65 611226.22 606784.88 609222.15 604650.25 611666.30 610365.33 609964.90 610701.06 593950.94 598880.91 598634.65 609277.47 593336.62 612029.08 612057.63 610544.52 610022.19 612192.11 608062.53 600083.88 610446.87 598946.99 610246.74 591116.81 609298.08 608752.13 608286.85 608306.03 596712.61 611199.81 595909.39 597415.67 612338.28 598743.21 608835.44 599008.84 609499.67 596788.03 608013.19 602205.45 611919.20 605805.93 599525.28 609075.59 612284.36 605243.20 604711.40 609216.30 596802.45 610302.32 608952.90 595575.58 608776.50 609105.81 610195.69 604476.67 595056.47 605098.83 604149.56 604991.85 609175.40 609289.85 610006.50 597335.60 597396.06 609853.75 605312.23 606176.54 602046.43 769.23 820.29 925.88 869.40 1045.30 1930.34 1151.21 1266.26 1368.61 732.54 995.11 890.19 950.55 992.14 967.79 1237.94 1672.03 1435.86 1225.16 1035.77 1718.60 1552.74 1162.27 1094.99 1782.33 1756.72 343.44 230.09 496.50 410.24 327.20 522.91 P_Perim P X (UTM) P_Perim P 2003.37 1654.86 1941.95 1578.10 2214.72 1397.78 1824.26 401.73 318.43 611.86 274.63 357.27 530.67 344.28 494.31 503.93 603.31 614.47 476.80 404.31 475.41 365.92 384.94 889.51 872.00 2275.71 2362.62 2251.94 2986.80 3148.16 4218.22 9517.84 4904.44 6003.49 9653.73 662.62 12761.52 2.75 2.96 2.98 3.04 3.07 3.42 3.47 3.65 3.72 3.83 3.96 4.07 4.13 4.29 4.50 4.77 5.07 5.30 5.42 5.43 5.46 5.55 Area 6.20 6.28 6.81 7.28 7.84 7.85 8.65 8.66 8.95 9.19 9.26 9.35 10.31 12.64 15.62 0.26 0.31 0.31 0.32 0.32 0.36 0.40 0.41 0.44 0.47 0.52 0.55 0.60 39.17 41.03 49.20 75.08 0.62 0.63 0.69 0.71 0.74 0.74 0.77 0.79 0.82 0.90 0.92 0.95 62.68 77.58 257.27 19 198 144 1302 774 732 851 769 534 GIS- 2129 1615 1148 2167 1899 1798 2020 1621 1964 1833 1415 1938 1890 502 601 702 738 507 896 814 542 Label 2200 2213 2226 1593 1528 1455 1458 1533 1628 1347 1522 409 353 593 596 2107 2197 2144 1165 2125 1221 1161 1630 1937 1569 1552 1602 1893 1147 1207 1132 1188 1596 1641 1830 1793 1226 1273 1012 157 2 1 1 1 2 3 3 1 2 1 1 5 5 5 2 5 3 1 1 1 1 1 , -r re! ,=,.."-ne .M+ "I'""4"77V-1, 'rn:;,#?.i.1,- 4 5 3

f. TB TB TB VB TB TB VB TB TB TB VB VB TB VB TB TB TB TB TB TB TB TB TB TB TB VD RD TG TD TD VG TG TD VD RD TO RD TO TO RD TD TO TO TD RD TD VZ TD TO TO TO PZ Type Intensity VD TO TO TO RD TD TO TO TD RD TO TD TO TO VD TD TD 91 Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw Iw 1w Iw Iw Iw Iw Iw Iw Iw Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn 1wn Iwn Ivvn Iwn Iwn Lucid Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn Iwn lwn Iwn Iwn Iwn Iwn 5.88 3.20 6.27 7.33 5.88 5.67 87.77 76.88 87.77 3.20 5.88 4.21 76.88 76.88 88.20 Area91 153.72 117.20 153.72 102.66 87.77 6033.70 2266.96 6033.70 6033.70 6033.70 6033.70 2266.96 6033.70 6033.70 6033.70 2266.96 2266.96 6033.70 2266.96 6033.70 2266.96 2266.96 2266.96 470.63 212.12 212.12 470.63 212.12 6033.70 2266.96 2266.96 2266.96 6033.70 6033.70 6033.70 2336.36 2336.36 2336.36 2336.36 2336.36 212.12 212.12 241.99 2336.36 2336.36 2336.36 2336.36 2336.36 2336.36 2336.36 2336.36 2336.36 27475.18 27475.18 91 B I B2 B1 BI B1 B1 B2 BI 131 BI B2 B2 B1 B2 BI B2 B2 B1 B2 B2 B2 B2 B1 B1 B1 D7 D2 GI D6 GI GI D2 GI D5 GI 02 D6 02 GI D8 01 GI GI 02 GI 02 D9 D13 D25 D23 D25 D7 02 GI D3 D2 01 GI GI D7 D25 D17 D24 D13 D27 D24 D23 D26 D19 Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu 73 Iu Iu Iu Iu Iu Iu 1u Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu lu Iu lu Iu Iu Iu Iu 1u Iu Iu lu Iu Iu Iu Iu lu In Iu Iu Iu Iu Iu Iu Iu Iu Iu Iu In Lucid 5.54 2.29 4.86 13.61 18.10 1.28 1.42 1.81 39.60 30.08 73.40 84.33 23.33 84.33 4.35 2.16 247.36 207.92 208.16 233.17 208.16 106.03 73.40 68.93 32.62 23.29 41.20 19.86 44.79 11.41 6.17 3.07 3.35 Area73 247.36 247.36 208.16 247.36 207.92 207.92 208.16 247.36 506.29 207.92 140.04 123.82 123.82 32.62 64.76 62.20 45.17 13.61 51.44 219.84 233.17 506.29 792.86 792.86 207.92 792.86 233.17 212.74 68.93 233.17 207.92 207.92 555.04 247.36 140.06 1252.89 73 VI V8 V7 V6 V9 R 1 T34 T15 T33 T33 T35 T34 U12 T34 T33 V13 T34 V4 VI RI Ti Ti VI V1 JI P1 T48 T15 T38 T15 T49 T24 T49 T33 T38 T34 T21 T15 U15 T45 T37 T27 T19 Ul T5 T6 R4 V8 T4 R30 R30 T15 T25 T47 R30 U15 T14 T31 T16 T15 T18 R10 T15 T17 T30 T34 T21 T20 U22 2982257.01 2999077.33 2994555.04 2979858.60 2992239.19 2979794.57 2998806.55 2984214.30 2980526.93 2983483.82 2999155.00 2996788.58 2992821.72 2999742.43 2982767.10 2996026.33 2998410.88 2984746.54 2999530.94 2995204.49 2996910.58 2995569.14 2993985.86 2986603.14 2986197.73 2998770.56 2990782.28 3001955.72 3001179.64 2996832.36 3000079.89 2998220.03 2981690.93 2985274.62 2991225.81 3005046.26 2987336.51 3000644.24 2981305.31 2985366.36 3000791.01 2981897.90 3003973.46 2999351.77 2985397.66 3000134.09 2987240.05 3004549.91 3004184.88 3000003.09 2980004.79 2999949.26 2981680.37 3000398.40 2981822.07 3000930.58 2998738.27 2982099.73 3000085.34 2986825.29 2995503.34 2991278.78 3005012.50 2981653.30 3001829.10 3000872.85 2998692.93 2983666.23 2997345.04 608231.32 594892.27 599867.81 595705.38 609546.04 603365.74 610224.95 606608.75 609545.70 607052.39 594625.25 594586.52 602765.95 594110.76 607669.79 596468.72 595462.01 594235.89 599181.17 598227.73 606788.06 594398.53 601124.32 606110.24 605537.24 595373.18 609249.93 591241.79 591270.00 593914.24 600728.24 591554.56 594516.88 591629.92 610113.69 608314.85 609132.56 610783.98 613265.03 610538.76 591914.46 613156.08 593903.67 596132.90 610985.16 601215.32 604739.85 601292.21 591329.79 591666.02 609417.51 592449.26 612459.11 591365.06 612725.95 596458.26 595196.70 591170.92 595201.48 613689.21 607728.02 609785.34 593266.90 608464.51 590983.53 590700.85 595305.73 611203.51 603512.85 421.35 492.15 727.55 952.51 951.58 738.39 846.76 941.99 907.48 1284.72 1996.10 1353.49 1285.44 1079.29 1278.64 1586.46 1943.86 255.58 235.94 301.67 317.98 368.55 342.13 919.45 287.37 304.23 401.07 365.87 445.60 413.69 516.66 718.54 743.58 479.39 554.94 531.90 842.48 P_Perim P_X (UTM) P_Y(UTM) P_Perim P_X 2324.37 2431.74 2078.05 1777.86 2778.73 2275.99 3319.26 3920.65 634.57 495.28 709.31 507.04 563.96 618.72 915.56 654.76 851.90 583.81 981.58 909.91 695.50 885.00 957.82 652.33 846.64 828.75 746.64 938.48 874.33 836.15 1009.70 1180.68 1.01 1.08 1.39 1.53 1.55 1.57 1.62 1.89 1.89 1.96 2.10 2.22 Area 2.26 2.27 3.03 3.42 4.44 5.20 5.21 5.69 6.27 8.11 9.37 0.33 0.33 0.41 11.72 12.23 0.44 0.46 0.46 0.47 0.47 0.54 0.58 0.59 0.62 0.77 0.81 0.83 0.84 0.87 0.90 0.92 0.95 1.00 1.24 1.24 1.28 1.42 1.54 1.81 1.81 1.86 1.91 2.04 2.05 2.12 2.16 2.29 2.52 2.53 2.54 2.63 2.75 3.35 3.50 3.55 3.63 331 839 424 183 35 38 42 56 60 57 1473 296 294 212 450 401 775 253 657 909 397 43 81 31 45 16 11 GIS- 1702 1079 1863 1290 1687 1318 1043 1370 206 914 301 1301 1244 1206 1640 1855 1608 201 466 957 953 508 366 159 Label 1485 2049 2274 1951 2270 1159 1658 351 367 2075 2243 2263 2281 1386 1770 1494 1089 2112 158

GIS- AreaP Perim P X (UTM) P Y(UTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 2090 3.74 832.86 610992.93 2983798.19 U4 3.74 Iu D26 241.99 Iwn TD 5 1654 3.97 1062.64 609431.35 2988664.86RI 506.29 lu DI 13.03 Iwn RD 1 14 4.21 1379.99 590898.68 2998231.03T45 23.29 Iu GI 2336.36 Iwn TG 2 1733 4.26 1247.14 609703.99 2985117.12T37 41.20 Iu D25 76.88 Iwn TD 2 2091 4.40 1460.18 611087.40 2984256.24 T8 559.45 lu D26 241.99 Iwn TD 133 4.52 1470.48 593106.40 2995927.31 V5 215.80 lu D24 27475.18 lvm VZ 2074 4.65 1195.37 610944.91 2987144.84R30 792.86 lu D5 117.20 Iwn RD 828 4.70 1629.92 599716.39 3002523.37T13 128.72 lu D13 470.63 Iwn TD 92 5.01 1149.39 592681.63 2998378.82 V4 219.84 Iu DIO 158.50 Iwn VD 936 5.27 1037.32 600980.70 3003302.64T14 212.74 Iu DIS 5.30 Iwn TD 24 5.53 1466.63 590889.86 3000516.45T18 11.41 Iu GI 2336.36 Iwn TG 3 1842 5.55 1429.41 610240.99 2982052.57 U25 10.48 lu D26 241.99 Iwn TD 4 1671 5.58 924.29 609452.36 2980188.66U12 18.10 lu D27 7.33 Iwn TD 3 2122 5.80 3000.62 611861.65 2985030.01 T8 559.45 Iu D21 78.62 Iwn TD 1 2014 6.12 1393.00 610777.04 2984255.01 U5 7.10 Iu D26 241.99 Iwn TD 4 2233 6.72 1588.09 612363.77 2982510.38 T4 140.06 lu G2 212.12 Iwn TG 1 1609 8.43 1646.61 609298.50 2985193.49T37 41.20 lu D25 76.88 Iwn TD 3 1070 8.53 5551.64 603867.45 2990957.92V2 136.73 lu D24 27475.18 Iwn VZ 1 894 8.69 1541.03 600441.21 3001577.59R22 14.02 Iu D13 470.63 Iwn RD 4 926 9.39 1676.83 601281.46 3004427.88R19 10.98 lu D13 470.63 Iwn RD 4 1358 9.48 1669.05 607736.11 2986351.86U6 16.82 lu D4 14.47 Iwn TD 4 15 9.58 2003.61 591060.71 3000842.52T19 19.86 lu 01 2336.36 Iwn TG 3 1496 10.12 2045.13 608512.10 2991423.15T10 38.54 lu D2 87.77 Iwn TD 3

5 10.58 1741.47 590707.41 2997908.82 V5 215.80 lu GI 2336.36 Iwn VG 1 735 10.70 1525.03 598767.69 3000626.26R15 27.49 Iu D14 34.15 Iwn RD 3 77 11.80 3658.49 592941.35 3000329.95T15 207.92 lu D6 153.72 Iwn TD 1 161 12.94 3365.59 593901.76 2996641.09 V6 30.08 lu GI 2336.36 Iwn VG 3 156 13.61 3312.73 593814.90 2996535.32 V6 30.08 lu D24 27475.18 Iwn VZ 3 2287 14.08 1938.83 613920.70 2982711.60 T5 555.04 lu 02 212.12 Iwn TO 1 37 16.44 4313.59 591851.53 3000774.46T15 207.92 lu GI 2336.36 Iwn TO 1 2232 17.03 3307.11 612523.01 2981540.69 T4 140.06 lu 02 212.12 Iwn TO 2 29 20.83 2660.81 591359.12 3002564.88T22 31.62 lu GI 2336.36 Iwn TG 4 1530 22.04 2835.39 608850.25 2990961.70RI 506.29 lu D2 87.77 Iwn RD 1 1686 23.71 2503.35 609689.87 2990840.56RI 506.29 lu D2 87.77 Iwn RD 1 170 26.85 4322.05 594206.08 3004073.53T25 44.79 Iu GI 2336.36 Iwn TO 4 85 27.44 3105.64 592737.68 3005224.63T29 89.87 lu GI 2336.36 Iwn TO 3 10 31.27 3161.20 590551.56 3002993.19T21 68.93 Iu GI 2336.36 Iwn TO 3 776 32.35 2839.49 599316.66 3002148.59R17 58.37 lu D13 470.63 Iwn RD 4 74 34.13 2937.95 592855.12 3005557.38T28 87.59 Iu GI 2336.36 Iwn TO 3 7 38.91 7986.78 592148.58 2996237.86 V5 215.80 lu D24 27475.18 Iwn VZ 2 2247 50.08 3754.09 612871.40 2981421.43Ul 1252.89 lu 02 212.12 Iwn TO 2252 50.41 5871.13 613287.60 2981960.07Ul 1252.89 lu 02 212.12 Iwn TO 2123 61.96 4093.71 611843.92 2985386.09R30792.86 lu D21 78.62 Iwn RD 2250 66.18 4445.72 612991.25 2982641.48 T5 555.04 Iu 02 212.12 Iwn TO 2 1898 96.1610016.84 611118.46 2986237.00R30792.86 Iu D5 117.20 Iwn RD 2 834 100.075876.04 600260.84 3000552.35R16 116.64 Iu D13 470.63 Iwn RD 4 878 137.579217.69 600684.24 3002626.58T14212.74 lu D13 470.63 Iwn TD 4 91 200.26 6154.08 592997.01 2997380.06 V4 219.84 Iu G 1 2336.36 Iwn VG 5 1100 0.25 208.96 603613.83 2998768.82T46 58.21 Iu E21 0.25 lwv TE 763 0.26 283.91 598771.85 3000867.71 R15 27.49 Iu E 1 1 122.96 lwv RE 520 0.29 248.48 596509.08 2999652.52 R9 3.17 Iu F17 85.55 Iwv FtF 877 0.30 251.06 600175.37 3002416.26T14 212.74 lu E 1 2 21.10 lwv TE 908 0.34 302.86 600638.19 2999960.13R16 116.64 lu F25 308.05 lwv RF 268 0.35 335.37 594349.88 2996856.93T24 23.33 Iu F12 2.38 lwv TF 2196 0.36 294.16 611818.99 2985204.99R30 792.86 lu E2 0.36 lwv RE 536 0.37 316.52 596762.98 3001118.58R10 64.76 lu F21 40.58 Iwv RF 1740 0.38 373.96 609672.24 2986746.97RI 506.29 Iu F9 196.96 Iwv RF 340 0.44 280.20 594884.75 2996149.06T48 106.03 lu F26 1.80 Iwv TF 115 0.46 569.59 592888.07 3000421.99T15 207.92 lu E5 21.59 lwv TE 354 0.47 343.40 595065.64 2998975.16 V9 4.86 Iu F16 18.71 Iwv VF 787 0.50 379.47 599149.12 2994937.77T49 84.33 lu F27 14.36 lwv TF 330 0.51 410.11 594933.31 2999013.09T15 207.92 Iu F16 18.71 Iwv TF 1536 0.52 463.59 608687.37 2986916.13 RI 506.29 Iu F9 196.96 lwv RF 1960 0.56 611.74 610460.44 2978424.79 VI 233.17 Iu E27 170.97 lwv VE 2246 0.59 351.71 612433.02 2982951.79 T4 140.06 lu F54 2.52 lwv TF 1259 0.61 665.46 605988.72 2995096.64 R6 96.34 lu F31 37.37 Iwv FtF 622 0.62 344.91 597567.94 3000923.93R10 64.76 Iu Ell 122.96 Iwv RE 1631 0.63 366.09 609128.02 2981008.88T34247.36 lu F69 0.63 lwv TF 1123 0.64 407.80 603980.75 2997041.55 R5 24.94 lu F30 145.76 lwv RF 159 1 1 1 3 1 1 1 1 5 1 1 1 1 1 3 4 2 5 1 1 4 3 5 4 5 5 1 1 3 1 5 1 2 2 1 3 1 -,f - !-V1 ,r 4 TF RH RF VF VF VF TF TF TF RF TF TF RE VF TF TF TF TF TE TF TF RE TE VE TE TF TF TF TF TF VF VF TE RH RE TF RF TF RE TF TE TF TE RF VF TF TF RF TF TF TF TE RF TE TE TF TE VF TF RF RF RE TE RE RF TF TE TF Type Intensity TH 91 Iwv lwv lwv lwv lwv Iwv lwv Iwv lwv Iwv Iwv lwv lwv Iwv lwv Lwv Iwv Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv Iwv Ivvv Iwv lwv lwv lwv lwv lwv Iwv Iwv lwv lwv Iwv Iwv lwv lwv 1w'.' Iwv Iwv Iwv Iwv Iwv Iwv lwv Iwv lwv Iwv lwv Iwv Iwv lwv lwv Iwv Iwv Iwv lwv lwv Iwv Iwv lwv lwv Iwv Iwv lwv Lucid 0.64 5.71 1.09 0.97 1.15 1.14 1.31 12.37 11.31 10.84 5.39 2.49 6.72 2.15 24.21 85.55 85.55 61.23 30.40 18.71 52.71 25.55 12.37 18.71 6.35 2.52 2.28 3.06 2.44 2.66 3.01 61.23 27.85 88.71 62.03 12.37 18.71 18.71 325.04 308.05 279.10 122.96 122.96 60.62 42.00 24.21 21.59 21.59 12.37 279.10 145.76 145.76 170.97 122.96 196.96 145.76 170.97 60.62 21.10 85.55 Area91 325.04 308.05 308.05 170.97 196.96 196.96 122.96 308.05 325.04 91 F6 Fl HI E9 F4 F6 F9 F56 F28 F25 F20 F77 F17 F19 F68 F17 F62 E15 F64 F76 F16 F13 F55 Hi E7 F2 F7 F6 E5 E3 E5 F9 F9 Eli F77 E15 E25 Eli F60 F30 F24 F30 F16 E7 F6 E27 E 1 1 F37 F30 E22 F32 E27 F63 F54 F25 F28 F58 F25 E27 F36 F16 F16 HI F67 E12 E18 F25 Eli F17 lu Iu Iu Iu lu 73 lu lu lu Iu Iu lu Iu Iu lu Iu Iu lu Iu Iu lu Iu lu Iu Iu lu lu lu Iu lu Iu lu Iu lu lu lu Iu lu Iu lu Iu lu lu Iu lu lu Iu lu Iu Iu Iu lu lu Iu lu Iu lu lu Iu Iu lu Iu Iu lu lu lu Iu lu lu lu Lucid 1.66 1.65 1.09 2.57 0.93 7.10 1.19 1.63 1.47 1.98 1.50 1.58 4.86 2.57 58.37 96.34 27.49 2.05 5.54 3.17 140.06 193.41 42.86 33.08 30.08 30.62 58.21 51.44 37.50 43.23 23.33 4.35 215.80 233.17 207.92 208.16 247.36 233.17 207.92 207.92 140.06 116.64 247.36 32.62 96.34 27.49 27.49 13.31 Area73 208.16 247.36 506.29 233.17 208.16 555.04 193.41 247.36 559.45 128.72 165.18 1252.89 207.92 207.92 207.92 247.36 506.29 792.86 208.16 1252.89 1252.89 73 R6 T4 V5 VI VI U5 T4 V6 R17 Vii T15 T33 U8 V9 Ul T7 Ul RI VI T5 R6 T8 RI R33 U16 T34 R15 T15 Ull T15 U19 T36 R16 U14 U20 T34 T46 T33 V10 U22 R18 R11 T42 Ul V7 R9 R29 520 T24 T34 U17 T33 521 Ull T34 U15 T15 T15 T15 T34 R30 T13 R15 R15 T33 T44 T26 T47 P_Y(UTM) 2982358.01 3002644.61 2994914.86 2999241.24 2996159.38 2979771.73 2999739.70 U17 2998129.23 2989580.84 2980787.12 2999454.85 2983722.33 3000459.06 2982424.52 2984465.40 2998950.51 2992497.04 2999857.52 3001379.46 2982795.56 2978880.33 3000236.25 2998994.77 2996632.23 3001207.01 2988774.49 2984615.94 2998163.01 2989312.71 2999065.25 2998004.81 2998893.78 2978401.26 3003788.56 3001848.60 2987470.73 2986071.57 2997014.31 2999041.54 2997253.33 2978344.33 2982980.24 2999850.51 2991160.84 2987466.66 2989089.09 2983060.65 2999215.96 2994351.47 2985732.74 3000055.88 2980980.07 2995433.38 3000157.87 2984916.78 2999181.96 2999910.11 2999030.74 2981157.23 2987032.56 2999867.66 3002221.23 2985559.16 3000474.86 3000334.56 2988894.72 3002531.99 3004718.55 2999186.96 612015.67 598417.55 606285.11 597410.57 593074.85 609557.17 596639.61 595365.01 596472.26 598977.61 604964.85 609783.13 606878.00 607821.76 610630.78 594670.81 608000.49 593773.59 597981.36 612030.30 610905.21 599543.96 603157.84 593601.90 598002.98 609698.46 606290.21 602205.40 605044.59 596874.74 595336.59 596503.41 597753.29 602851.84 611404.19 608454.56 609215.02 604043.20 602681.65 594507.08 610672.65 607391.53 596648.24 608194.97 605154.44 605083.28 612443.14 599979.18 607290.47 605732.41 601190.22 612007.21 606859.87 593224.93 611958.52 594440.50 593529.67 594688.78 609121.48 596572.85 599741.50 598850.15 598818.94 610131.50 610013.46 605227.08 597562.01 595778.30 596215.48 320.81 778.66 577.03 340.25 822.66 519.75 525.34 452.92 394.83 564.28 585.65 1058.96 383.53 778.03 433.09 451.66 774.97 663.72 438.45 727.77 571.56 441.73 592.11 606.50 512.93 526.65 705.20 666.03 506.67 849.41 795.27 634.97 461.48 627.70 588.89 520.50 627.01 547.01 761.87 858.20 554.94 1067.49 694.39 631.05 672.90 611.68 631.65 642.13 895.61 719.89 816.04 690.24 945.77 594.70 926.30 699.44 803.26 784.66 789.03 869.67 894.04 911.49 957.30 844.58 P_Perim P_X (UTM) P_Perim P_X 1096.57 1013.91 1126.68 1257.95 1327.91 0.64 1.04 1.08 1.09 1.12 1.14 1.14 1.17 0.65 0.73 0.74 0.76 0.77 0.77 0.80 0.84 0.86 0.89 0.96 0.96 0.98 0.98 0.99 1.14 1.19 1.22 1.27 1.30 1.30 1.31 1.43 1.43 1.44 1.47 1.48 1.50 1.58 1.60 1.64 1.65 1.70 1.80 1.84 Area 1.78 1.82 1.92 1.94 2.04 2.10 2.11 2.12 2.42 2.43 2.44 2.44 2.51 2.57 2.62 2.62 2.63 2.73 2.88 2.90 3.01 3.06 3.16 3.21 3.28 3.38 708 594 136 526 389 506 778 308 181 663 820 168 1275 1703 681 540 377 524 640 530 140 167 GIS- 2221 1184 1794 1307 1408 1422 1081 1749 1282 1025 295 864 954 276 309 518 843 Label 2013 2207 2066 1189 1057 2166 1519 1613 1126 1045 1999 1344 1462 1198 1194 1335 1245 1313 1583 1848 749 741 609 445 465 2245 2201 2199 1857 1219 160

GIS- Area P_Perim P_X (UTM)P_Y(UTM) 73 Area73Lucid 91 Area91 LucidTypeIntensity Label 73 91 1965 3.41 1210.72 610584.70 2987386.73R30 792.86 lu F9 196.96 lwv RF 1 676 3.49 2656.01 598698.09 2995151.16T49 84.33 lu F27 14.36 Iwv TF 1 1876 3.52 1144.56 610286.27 2987158.53R26 4.66 lu F9 196.96 lwv RF 4 1711 3.53 756.83 609566.49 2988814.65 RI 506.29 lu F4 5.39 lwv RF 1 1407 3.58 1690.80 607972.93 2982455.49T34 247.36 lu F64 10.84 Iwv TF 1 385 3.69 821.52 595345.57 3004648.36T27 140.04 lu HI 325.04 Iwv TH 1 1389 3.71 1108.08 607777.23 2986898.36 T6 6.17 lu F9 196.96 Iwv TF 4 1470 3.79 1009.77 608260.15 2989573.77 R1 506.29 Iu F3 4.97 Iwv RF 1498 3.79 1268.72 608464.67 2987216.85 RI 506.29 lu F37 88.71 lwv RF 1483 3.85 1207.49 608362.44 2981959.09T34 247.36 lu F65 7.44 lwv TF 119 4.00 1173.64 592966.26 2995700.50 V5 215.80 Iu F73 4.78 lwv VF 1973 4.25 1110.68 610547.95 2986934.36R30 792.86 Iu E4 25.53 lwv RE 1739 4.33 1202.32 609717.50 2985231.83T37 41.20 Iu F9 196.96 Iwv TF 2 1620 4.41 1144.12 609302.55 2984789.20137 41.20 lu F75 23.26 lwv TF 2 1364 4.41 1246.07 607686.98 2986496.01 136 16.82 lu F9 196.96 lwv TF 3 1841 4.42 1435.17 610160.18 2981969.63U25 10.48 lu F77 279.10 lwv TF 3 1645 4.52 1101.10 609205.78 2980753.94T34 247.36 lu F70 4.53 Iwv TF 1293 4.52 1425.47 606634.52 2984113.41 T34 247.36 Iu F61 4.52 Iwv TF 2028 4.86 1019.84 610757.90 2987226.71 R30 792.86 lu E4 25.53 Iwv RE 2042 4.96 1198.29 610802.11 2986685.97R30 792.86 lu E4 25.53 lwv RE 1049 5.02 1100.82 602879.77 2998917.94U14 33.08 Iu E22 6.72 Iwv TE 2 607 5.05 1287.77 597450.67 3001853.28 1318 7.69 Iu Eli 122.96 Iwv TE 4 826 5.12 1540.44 599747.13 3000024.568.16 116.64 lu F25 308.05 lwv RF 1 1774 5.13 2355.16 610096.75 2978948.75 VI 233.17 lu F77 279.10 Iwv VF 1 893 5.32 1450.50 600523.69 3001209.858.22 14.02 Iu E16 60.92 Iwv RE 3 404 5.44 1019.27 595532.35 2998846.59 V8 13.61 lu F16 18.71 lwv VF 3 1650 5.70 1039.32 609455.79 2980441.75U12 18.10 lu F71 5.70 lwv TF 3 1864 5.89 1284.40 610231.15 2987889.17RI 506.29 Iu El 5.89 Iwv RE 1 1164 5.89 2466.62 605107.93 2995869.81 R31 96.84 lu F31 37.37 lwv RF 1 1445 6.02 1751.37 608266.29 2992047.43TIO 38.54 lu Fl 52.71 lwv TF 2 898 6.38 1798.97 600656.91 2999655.98U15 32.62 Iu F25 308.05 Iwv TF 2 1467 6.40 1980.07 608359.01 2991026.84 T9 38.92 Iu F2 42.00 Iwv TF 2 1535 6.64 1419.30 608786.75 2981470.80134 247.36 lu F66 6.78 Iwv TF 1 1862 7.56 1632.48 610158.60 2986420.778.30 792.86 lu F9 196.96 Iwv RF 1 629 8.12 1861.86 597818.64 3002232.42R13 58.72 Iu Eli 122.96 Iwv RE 2 748 8.51 1683.65 598841.26 3001983.60R17 58.37 Iu HI 325.04 lwv RH 2 1565 9.37 2047.79 609199.43 2988359.95 RI 506.29 lu F37 88.71 Iwv RF 1 897 9.57 1988.85 600711.52 3000411.12R16 116.64 Iu E16 60.92 lwv RE 1 1105 9.84 2027.73 603856.52 2997334.63 95 24.94 lu F30 145.76 lwv RF 3 1095 10.01 1623.61 603680.19 2997385.29U22 51.44 Iu F30 145.76 lwv TF 2 105 10.18 2286.45 593103.22 2996607.99V4 219.84 Iu E9 27.85 lwv VE 1 1258 10.75 2182.87 605801.92 2985259.63134 247.36 Iu F59 11.46 lwv TF 1 695 11.39 1920.51 598346.23 3001422.68U21 34.00 Iu E 1 1 122.96 lwv TE 3 1129 11.53 1911.04 604246.61 2996986.36T42 37.50 lu F31 37.37 Iwv TF 3 915 12.36 2228.48 600844.98 3000005.70U15 32.62 Iu E16 60.92 Iwv TE 3 694 14.80 2166.45 598458.28 3001767.75 1321 34.00 1u HI 325.04 lwv TH 3 1515 16.62 2684.53 608648.09 2989547.99 RI 506.29 Iu F5 27.51 Iwv RF 1 618 16.81 3506.07 597936.58 3002665.73R13 58.72 Iu HI 325.04 Iwv RH 3 1523 18.04 2020.67 608599.76 2990640.60RI 506.29 lu F2 42.00 Iwv RF 1 511 18.26 2715.68 596601.87 3002813.97914 28.69 lu HI 325.04 lwv RH 4 1360 18.30 2618.20 607908.71 2994286.70Ul 1 193.41 lu E20 18.83 Iwv TE 931 19.14 3748.48 600713.29 3003184.23T14 212.74 lu F22 19.85 Iwv TF 2138 20.93 2742.54 611594.84 2979168.19Ul 1252.89 lu E27 170.97 Iwv TE 1513 21.62 4034.52 608950.82 2991311.04RI 506.29 Iu Fl 52.71 lwv RF 1073 36.37 4968.76 604017.68 2998627.34U23 46.21 lu F30 145.76 lwv IF 4 1778 36.92 2747.16 610143.24 2979393.38T35 39.60 lu F77 279.10 Iwv TF 5 2068 41.00 3588.97 611104.97 2979049.80T36 42.86 Iu E27 170.97 lwv TE 5 499 63.30 5383.41 597047.54 3003937.58T26 165.18 lu HI 325.04 lwv TH 3 781 0.38 345.93 599034.87 3003202.15 15 6295.09 II S6 28.33 II IS 1 1992 0.39 326.11 610553.44 2991259.09 Ii 8605.42 II S2 1.81 II IS 1 1277 0.43 553.63 606265.06 2996691.76 Il 8605.42 II Sll 4.25 II IS 1 2248 0.79 349.30 612370.18 2992598.64S17 0.79 II 12 6200.17 II SI 5 1365 0.81 514.14 607525.13 2994578.93 14 37.46 II S20 15.99 II IS 1 637 1.06 885.31 597702.40 3004350.77S21 178.90 II II 10031.38 II SI 1 2184 1.36 455.46 611581.58 2992925.84S16 1.36 11 12 6200.17 II SI 5 1634 1.80 532.17 609126.37 2992635.53S15 1.80 II 12 6200.17 II SI 5 1724 2.32 727.23 609498.50 2993334.16Sll 2.32 II 12 6200.17 II SI 5 788 3.18 877.87 599281.70 3005770.95 15 6295.09 II S27 3.18 II IS 1 1725 3.43 748.61 609440.28 2994861.68S12 3.43 IL 12 6200.17 II SI 5 161

GIS- AreaP Perim P X (UTM) P Y(UTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 1304 3.48 1174.12 606416.81 2996983.66 S8 3.48 II 11 10031.38 II SI 5 2230 3.84 822.31 612137.07 2994954.49S18 3.84 II 12 6200.17 II SI 5 1901 4.37 1156.73 610191.07 2995015.80 S I 3 5.23 II 12 6200.17 II SI 4 1329 4.53 827.06 607095.18 2999689.58 Ii 8605.42 II S14 4.53 II IS 1 1685 6.44 996.11 609274.59 2992331.79S14 6.44 II 12 6200.17 II SI 5 988 6.73 1304.76 601773.39 3004154.55 IS 6295.09 II 05 8.13 II 10 1 460 6.74 1389.77 596161.86 3005195.63 IS 6295.09 II S7 65.85 II IS 1 1580 7.14 1498.46 609102.30 2993156.46 II 8605.42 II S4 14.07 II IS 1 1563 7.75 1663.22 609159.12 2993603.07SIO 14.67 II 12 6200.17 II SI 4 1497 8.04 1265.40 608529.89 2994521.18S23 9.15 II 12 6200.17 II SI 4 1925 8.37 1244.87 610371.76 2994918.20 Ii 8605.42 II S19 9.24 II IS 768 10.43 2058.83 598886.83 3005060.35S20 10.43 II II 10031.38 II SI 498 13.19 2176.43 596756.23 3005727.37 IS 6295.09 II S26 114.55 II IS 1029 14.15 1959.58 602428.46 3005510.63 IS 6295.09 II S17 14.15 II IS 967 15.15 2157.29 601501.30 3002070.61 15 6295.09 II S8 15.15 II IS 1002 17.36 2309.55 602012.13 3005230.69 IS 6295.09 II S9 22.33 II IS 1850 17.86 2741.51 609884.29 2998170.22 II 8605.42 II S21 17.86 II IS 1367 20.01 2739.11 607952.39 2995179.73 S28 26.35 II 12 6200.17 II SI 4 1013 23.39 3245.49 602371.42 2999712.22 S22 214.82 II II 10031.38 II SI 2. 1217 27.35 4069.67 605768.88 2996645.46 S7 34.14 II Ii 10031.38 II SI 4 1829 27.53 2686.48 610336.07 2990763.40 Ii 8605.42 II Si 57.24 II IS 925 27.55 2796.67 601231.01 3001401.21 IS 6295.09 II S 10 27.86 II IS 1042 31.88 3288.25 602936.67 3001963.19 IS 6295.09 II S15 36.20 II IS 1974 32.58 2864.62 610470.36 2988651.85 S4 32.58 II 12 6200.17 II SI 5 1438 35.67 2927.53 608352.37 2993101.01 S19 42.22 II 12 6200.17 II SI 4 1611 40.37 6844.86 610372.25 2991399.09 S5 64.42 II 12 6200.17 II SI 4 2165 50.59 5411.10 611835.52 2987498.91 S3 57.17 II 12 6200.17 II SI 4 1262 62.12 3524.53 606440.21 2996362.84 S6 63.38 II Ii 10031.38 II SI 5 649 67.22 5276.23 598590.69 3003998.77S21 178.90 II I 1 10031.38 II SI 3 975 74.40 7828.38 602252.08 3001279.81S22 214.82 II I1 10031.38 II SI 3 1994 0.25 215.99 610482.67 2997661.67 11 8605.42 II L32 0.25 III IL 1575 0.27 220.27 608927.07 2993732.69 Ii 8605.42 II L19 0.27 III IL 2050 0.28 219.93 610732.40 2990426.76 Ii 8605.42 II L6 0.28 III IL 1330 0.29 227.79 607100.32 3005145.08 15 6295.09 II L64 0.29 III IL 2011 0.31 239.42 610583.12 2992731.98 11 8605.42 II L5 0.31 III IL 1434 0.32 237.82 607968.03 2997619.83 II 8605.42 II L34 0.32 III IL 2108 0.34 255.04 611040.82 2989340.05 11 8605.42 II LI 0 0.34 III IL 1064 0.36 227.01 602956.17 3003220.98 15 6295.09 II L53 0.36 III IL 1203 0.36 244.11 605009.14 3005563.36 15 6295.09 II L67 0.36 III IL 1732 0.37 249.26 609620.01 3002909.46 15 6295.09 II L76 0.37 III IL 2257 0.37 238.36 612734.30 2995799.88 Ii 8605.42 II L42 0.37 III IL 2160 0.38 256.86 611278.16 2997763.85 Ii 8605.42 II 131 0.38 III IL 1758 0.38 235.15 609666.40 2990385.53 Ii 8605.42 II L8 0.38 III IL 1612 0.40 246.43 609062.38 2995725.88 II 8605.42 II L26 0.40 III IL 1322 0.42 331.03 606973.11 3005354.84 15 6295.09 II L65 0.65 III IL 1111 0.42 277.19 603774.91 2999513.06 IS 6295.09 II L57 0.42 III IL 1804 0.44 272.76 609828.60 2992733.94 Ii 8605.42 II L4 0.44 III IL 1106 0.44 271.19 603774.01 3000014.37 IS 6295.09 II L56 0.44 III IL 852 0.44 258.08 599713.65 3004665.73 15 6295.09 II L16 0.44 III IL 2026 0.45 263.26 610585.64 2994457.75 Ii 8605.42 II L22 0.45 III IL 1343 0.45 261.10 607259.63 2995632.24 Ii 8605.42 II L39 0.45 III IL 862 0.46 272.47 599934.17 3003630.56 15 6295.09 II L17 0.46 III IL 1801 0.48 271.39 609822.98 2993769.38 Ii 8605.42 II 13 0.48 III IL 621 0.48 277.39 597552.23 3005544.34 IS 6295.09 II L18 0.48 III IL 2210 0.49 305.37 612026.65 2987682.74 Ii 8605.42 II LII 0.60 III IL 2062 0.50 270.79 610732.26 2993412.88 II 8605.42 II L20 0.50 III IL 2266 0.51 278.11 612891.28 2994727.26 II 8605.42 II L40 0.51 III IL 1428 0.52 296.86 607918.22 2997773.73 Ii 8605.42 II L35 0.52 III IL 917 0.52 283.87 600775.78 3005709.70 15 6295.09 II L14 0.52 III IL 2177 0.52 298.25 611482.37 2993484.09 11 8605.42 II L21 0.52 III IL 2269 0.54 295.96 612897.30 2993588.11 II. 8605.42 II 138 0.54 III IL 1255 0.54 285.45 605809.27 2997643.85 Ii 8605.42 II L51 0.54 III IL 1000 0.57 327.31 601746.74 3002965.85 IS 6295.09 II L52 0.57 III IL 2022 0.58 295.81 610632.31 2994782.98 Ii 8605.42 II L23 0.58 III IL 1874 0.58 309.02 610070.12 2996647.31 Ii 8605.42 II 130 0.58 III IL 2240 0.58 293.75 612314.92 3001721.28 II 8605.42 II L75 0.58 III IL 1286 0.60 304.42 606320.09 3000680.30 S9 0.60 II L59 1.34 III SL 1589 0.61 299.30 609032.63 2997731.00 11 8605.42 II 133 0.61 III IL 2082 0.61 321.80 610862.67 2990451.52 11 8605.42 II L7 0.61 III IL 162 1 1 1 ...... , 3 5 5 1 1 5 5 1 1 3 5 IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IL IK IT IT IT ST SR ST SR ST SR SR IT IR IT ST ST IT IT IT IT IT IT IT OT OT ST ST ST ST ST ST ID ID ID Type Intensity SD SD OD OD 91 III III III III III III III III III III III III III III III III III III III III III III Iu Iu lu lu III III III III III III III III III III Iu 1u Iu Iu Iu lu Iu lu lu lu Iu lu Iu Iu lu Iu lu Iu Iu lu lu Iu Iu lu lu Iu Iwn Iwn Iwn Iwn Iwn Iwn Iwn Lucid 0.66 0.61 0.61 0.62 0.62 0.68 0.69 0.70 0.70 0.70 0.70 0.71 0.72 1.34 0.80 0.83 0.85 0.92 1.04 1.04 1.15 1.21 1.34 1.40 1.47 1.59 1.75 2.07 4.52 5.54 1.90 11.34 4.14 4.14 7.88 6.23 6.23 6.33 3.85 18.52 30.83 62.17 62.17 62.17 23.89 20.34 18.23 Area91 120.56 198.32 100.49 20.82 87.77 120.51 120.56 120.56 100.49 120.51 102.66 102.66 158.50 102.66 241.99 3055.16 3055.16 3055.16 3055.16 3055.16 3055.16 3055.16 91 L9 L15 L29 L77 L43 L60 K3 U9 L44 L46 L66 136 L74 L25 L45 L54 L59 L58 L50 L55 L68 L72 L61 L47 L73 148 L49 L41 U3 U4 U2 137 L63 L79 L62 L80 T20 T11 T36 R13 T36 R13 T17 R13 R15 T48 R15 U2 D2 U15 T26 T27 T20 T20 U13 U13 U13 T48 U13 U13 U12 U13 D17 Dll D26 D17 DI 0 D17 U13 H II II II H II II II II II II II II 73 II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II II 11 II II II II II II II II II II Lucid 8.92 8.92 8.92 8.92 57.17 34.14 23.75 63.38 34.14 13.40 14.24 17.62 178.90 26.35 20.68 62.40 17.62 Area73 214.82 178.90 178.90 6295.09 8605.42 6295.09 8605.42 8605.42 6295.09 8605.42 6295.09 8605.42 8605.42 8605.42 8605.42 8605.42 6295.09 6295.09 6295.09 6295.09 6295.09 8605.42 6295.09 6295.09 8605.42 8605.42 8605.42 8605.42 8605.42 8605.42 6295.09 6295.09 6295.09 8605.42 8605.42 8605.42 214.82 6295.09 6295.09 6295.09 6295.09 6295.09 6295.09 6295.09 6295.09 8605.42 8605.42 8605.42 8605.42 6295.09 8605.42 6295.09 IS II 15 11 II IS II 15 73 II Ii II II IS 15 IS II IS IS Ii IS IS Il Ii Ii II 11 II 15 IS 15 Ii II Ii 15 S3 S7 S6 S7 IS 15 15 15 15 IS IS II 01 01 Si II S2 II Ii IS Ii IS S24 S21 S22 01 01 S21 S28 S26 S27 S21 S25 S27 S22 3005637.58 2993706.83 3005438.94 2996820.02 2996835.55 3001183.53 2999896.09 3005639.84 2997566.46 3003232.32 2995609.78 2998947.15 3002573.46 3000624.05 2999554.68 2998114.50 3000616.42 3004150.15 2989678.59 3005449.52 3002542.51 2998779.34 3004338.61 3001147.36 2998640.43 2994721.05 2993253.88 3003866.31 3005621.07 3003597.99 2999811.47 2989503.12 3001021.73 3004645.94 2999057.15 2987741.12 2996406.50 2987830.21 2996275.64 3004233.29 2998760.50 2996756.93 3004596.85 3000525.08 3001809.08 3000675.23 2999362.17 3004359.28 2994891.96 3003149.07 3004721.53 3003439.91 2983451.89 2983949.47 2986861.34 3000763.66 2983566.76 2982803.20 2987033.93 2985854.88 3004397.17 2982509.80 3000544.86 2999016.97 2983651.36 3000621.03 2998580.83 2990531.29 3000892.91 599738.42 613295.47 607447.61 612463.79 612605.71 605737.13 611130.13 605679.30 606608.55 611674.49 609095.70 612176.16 603140.59 606318.07 604232.65 609397.21 603260.35 602789.87 609887.91 611660.62 605191.34 609967.19 612305.72 612777.81 607984.98 612737.13 612064.33 608157.67 601815.40 606286.90 610008.91 593909.43 611745.33 609338.39 601983.64 611363.27 605781.77 611159.70 605906.94 598372.42 593884.83 60531136 597203.92 601557.88 609529.81 601312.32 603021.65 598588.80 607413.87 599374.75 601441.02 600149.74 614299.59 613092.99 612902.56 608091.38 611518.33 598056.71 593923.80 614238.21 612850.73 614707.79 614864.95 601381.94 611282.96 601537.05 593830.19 609797.78 601196.03 323.01 307.08 325.59 349.92 330.97 320.75 338.28 317.69 400.02 323.77 328.94 340.89 342.31 766.45 374.90 413.82 380.09 402.65 384.68 424.71 407.31 443.01 447.05 483.96 539.90 509.70 563.78 568.45 961.06 952.20 343.61 988.83 463.45 343.45 353.92 436.32 632.54 662.08 727.35 776.51 887.21 1240.44 1770.51 363.15 574.67 P_Periin P_X (UTM) P_Y(UTM) P_Periin P_X 1032.01 1360.33 1821.42 1087.58 1116.04 1070.49 1548.37 448.94 415.74 674.27 814.56 2186.13 3470.12 2786.81 2034.17 2282.22 5348.71 2162.85 1838.86 2449.22 2209.40 6246.90 4308.04 2124.71 0.61 0.61 0.61 0.62 0.62 0.68 0.69 0.70 0.70 0.70 0.70 0.71 0.72 0.75 0.80 0.83 0.85 0.92 1.04 1.04 1.15 1.21 1.34 1.40 1.47 1.59 1.75 5.54 1.27 1.90 Area 2.07 4.52 7.51 0.33 0.46 0.55 0.55 0.61 0.84 2.11 2.36 2.81 2.88 2.90 3.24 3.70 3.85 5.54 6.11 1.77 1.91 18.52 0.27 0.63 0.95 2.02 6.93 11.49 11.58 13.40 14.24 14.38 14.40 16.67 20.68 20.72 26.13 56.07 62.40 848 1362 203 192 GIS- 2276 2254 2255 1251 2128 1246 1305 2186 1619 2231 1077 1287 1136 1699 1083 1055 1828 1211 1822 1454 1456 1001 1278 1805 1649 724 559 978 964 726 780 939 838 189 Label 2187 2235 2265 2259 2229 2204 1005 2164 1249 2130 1263 1216 1586 1051 1337 1325 638 972 202 976 938 2290 2258 2242 2151 2294 2241 2293 1766 2295 2143 s 163

GIS- Area P_Perim P X (UTM) P Y(UTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 921 9.54 2784.76 600851.93 3002286.69 15 6295.09 II D13 470.63 Iwn ID 1566 15.69 2142.02 609273.06 2990527.56 II 8605.42 II D2 87.77 Iwn ID 977 16.75 2707.05 601729.36 3000362.80S22 214.82 II D17 102.66 Iwn SD 949 0.52 360.18 601058.32 3003734.15 IS 6295.09 II F22 19.85 Iwv IF 1431 0.53 515.32 608073.05 2994556.32 14 37.46 II E20 18.83 lwv IE 1312 0.63 582.07 606917.06 2995422.92 II 8605.42 II F36 3.06 Iwv IF 2052 0.85 426.02 610770.39 2987488.98S24 23.75 II F9 196.96 Iwv SF 1653 0.87 413.85 609362.28 2990660.34 II 8605.42 II Fl 52.71 Iwv IF 1150 1.39 515.08 604567.88 2997022.54 12 76.26 II F31 37.37 Iwv IF 190 3.72 1114.07 593923.48 2998936.31 01 8.92 II F32 62.03 Iwv OF 924 4.62 1163.18 600966.05 3001490.76 15 6295.09 II E16 60.92 lwv IE 1564 11.64 1376.98 609071.49 2990420.51 II 8605.42 II F2 42.00 Iwv IF 1011 16.81 2517.51 602172.02 3000013.13S22 214.82 II F23 16.81 Iwv SF 929 24.22 2144.87 601139.60 3002113.10 15 6295.09 II El7 24.22 Iwv IE 704 34.96 5398.63 598234.87 3004129.85 S21 178.90 II H2 34.96 Iwv SH 2 1392 0.26 232.88 607616.48 3003571.33L27 0.26 III II 10031.38 II LI 5 1414 0.27 228.49 607800.46 3003834.78L22 0.27 III Ii 10031.38 II LI 5 1254 0.29 242.86 605827.49 3005399.43L40 0.29 III 11 10031.38 II LI 5 1292 0.30 283.22 606367.28 3004020.46137 0.30 III 11 10031.38 II LI 5 1090 0.34 247.98 603404.67 3005501.14L47 0.34 III II 10031.38 II LI 5 1080 0.34 238.18 603177.39 3000579.91L61 0.34 III 11 10031.38 II LI 5 1114 0.35 252.43 603765.37 3003056.46133 0.35 III II 10031.38 II LI 5 1133 0.35 234.90 604072.83 2999539.06L50 0.35 III II 10031.38 II LI 5 2272 0.38 231.35 613159.72 2996258.91L64 0.38 III 12 6200.17 II LI 5 1104 0.38 262.34 603653.62 3000505.14L60 0.38 III II 10031.38 II LI 5 1272 0.39 254.09 605976.86 3004438.56L38 0.39 III II 10031.38 II LI 5 1102 0.40 267.65 603648.09 2999978.34L51 0.40 III 11 10031.38 II LI 5 1570 0.40 262.42 608880.13 2996186.22 13 0.40 III 12 6200.17 II LI 5 1303 0.42 303.78 606586.73 3004466.69L28 0.42 III II 10031.38 II LI 5 1465 0.42 281.74 608129.85 3004053.71 L20 0.42 III Ii 10031.38 II LI 5 2267 0.42 277.21 612844.85 2999757.76 L13 0.42 III 12 6200.17 II LI 5 1321 0.42 330.76 606952.22 3005470.66L29 0.66 III II 10031.38 II LI 4 842 0.46 295.53 599683.33 3005691.18L57 0.51 III II 10031.38 II LI 5 1548 0.50 280.87 608616.94 3004431.43L19 0.50 III II 10031.38 II LI 5 1795 0.50 284.10 609789.74 2998680.62L12 0.50 III Ii 10031.38 II LI 5 1253 0.52 282.93 605754.76 3004931.171.39 0.52 III Ii 10031.38 II LI 5 1421 0.52 297.51 607846.37 3003518.46L23 0.52 III Ii 10031.38 II LI 5 1099 0.52 301.24 603626.41 2999490.41L49 0.52 III 11 10031.38 II LI 5 1040 0.54 307.72 602480.12 3002528.26L54 0.54 III Il 10031.38 II LI 5 1155 0.57 310.42 604558.35 3005406.72L43 0.57 III Il 10031.38 II LI 5 2219 0.57 291.39 611983.66 2992471.62 L7 0.57 III 12 6200.17 II LI 5 1039 0.61 362.12 602521.08 3003569.91L55 0.61 III Ii 10031.38 II LI 5 1197 0.61 339.81 605048.52 2998742.81 L2 0.61 III 11 10031.38 II LI 5 1119 0.63 306.02 603838.85 3005572.72 LAS 0.63 III II 10031.38 II LI 5 1264 0.64 338.85 605795.34 3003950.50L36 0.64 III II 10031.38 II LI 5 1157 0.65 331.49 604595.35 3000365.11L53 0.65 III II 10031.38 II LI 5 2195 0.65 356.74 611806.62 3003536.67L17 0.65 III I I 10031.38 II LI 5 1845 0.67 311.05 609975.14 2999556.58L14 0.67 III II 10031.38 II LI 5 2268 0.70 336.03 612944.14 3003470.02L18 0.70 III Il 10031.38 II LI 5 1281 0.71 344.75 606170.36 3005440.44L41 0.71 III II 10031.38 II LI 5 2045 0.74 325.61 610656.72 2992521.28 L6 0.74 III 12 6200.17 II LI 5 1205 0.75 367.40 605041.17 3005453.12L42 0.75 III II 10031.38 II LI 5 1154 0.78 337.81 604628.05 2999331.20L52 0.78 III II 10031.38 II LI 5 2260 0.80 407.62 612750.74 2993093.46L67 0.80 III 12 6200.17 II 1.1 5 1846 0.80 345.56 609971.92 2992488.66 L5 0.80 III 12 6200.17 II LI 5 1517 0.82 382.57 608313.80 2996104.31 IA 0.82 III 11 10031.38 II LI 5 2193 0.83 362.48 611785.72 2997702.48 L9 0.83 III 12 6200.17 II LI 5 1349 0.90 383.12 607334.15 3003592.45L26 0.90 III II 10031.38 II LI 5 1406 0.96 448.58 607686.37 3005403.95L30 0.96 III I 1 10031.38 11 LI 5 1139 0.99 388.16 604233.23 3005446.86L44 0.99 III 11 10031.38 II LI 5 1928 1.05 405.51 610237.56 2997704.64L10 1.05 III 12 6200.17 II LI 5 1892 1.07 470.02 610104.39 2989979.49L66 1.07 III 12 6200.17 II LI 5 1061 1.25 426.31 602954.80 2999713.26L48 1.25 III I 1 10031.38 II LI 5 2024 1.28 562.91 610598.93 3003495.87L16 1.28 III 11 10031.38 II LI 5 1116 1.42 558.38 603822.75 3002047.33132 1.42 III Ii 10031.38 II LI 5 1115 1.44 477.49 603789.99 3003481.52L34 1.44 III II 10031.38 II LI 5 1103 1.45 476.35 603590.30 3005424.40L46 1.45 III Il 10031.38 II LI 5 1151 1.65 634.02 604677.32 2999075.92L58 1.65 III I 1 10031.38 II LI 5 991 1.71 551.13 601687.77 3005649.03136 1.71 III II 10031.38 II LI 5 164

GIS- AreaP_Perim P_X (UT M) P Y(UTM) 73 Area73Lucid 91 Area91 LucidType Intensity Label 73 91 2162 1.76 870.97 611521.19 2999821.18 K3 16.38 III 11 10031.38 II KI 2 1398 1.76 514.61 607674.41 3005801.21 1.31 1.76 III II 10031.38 II LI 5 1554 1.97 543.23 608623.05 3002605.52L24 1.97 III II 10031.38 II LI 5 1125 2.05 693.36 603804.04 3004481.481.35 2.05 III II 10031.38 II LI 5 2087 2.66 664.84 610850.61 2998685.07L11 2.66 III 12 6200.17 II LI 5 2285 3.00 672.46 613562.38 2996197.69L65 3.00 III 12 6200.17 II LI 5 1059 4.32 910.09 602969.69 3001766.83L62 4.32 III S I 5 36.20 II LS 5 1722 4.33 987.52 609577.23 2993835.30 L 1 4.33 III 12 6200.17 II LI 5 2289 7.23 1315.59 613502.88 2994710.30 1.8 7.23 III 12 6200.17 II LI 5 1336 8.40 1638.77 607041.24 3002619.27L25 8.40 III II 10031.38 II LI 5 1409 9.02 1719.13 607898.64 2993092.73 K2 13.57 III S23 35.20 II KS 4 1223 9.84 1459.09 605143.23 3004700.61L59 9.84 III Ii 10031.38 II LI 5 2282 10.69 1586.30 613320.19 2996448.99L63 10.69 III 12 6200.17 II LI 5 1802 13.51 2047.52 609767.29 3000145.001.15 17.33 III Ii 10031.38 II LI 4 2161 14.63 1481.74 611558.85 2999625.63 K3 16.38 III 12 6200.17 II KI 4 1239 1.06 1057.39 605705.03 2995276.47 K1 10.33 III F31 37.37 lwv KF 2 1411 1.71 608.59 607874.79 2992731.62K2 13.57 III Fl 52.71 lwv KF 2 165

APPENDIX 2

ESTIMATED COSTS FOR THE PROCEDURAL MODEL

FIXED COSTS Materials/Supplies Units Cost per Unit Total Historical vertical photography 1973 5 $ 5.00 $ 25 Historical vertical photography 1991 4 $ 5.00 $ 20 Maps 20 $ 3.00 $ 60 Census Information 3 $ 50.00 $ 150 Plastic Sheets 20 $ 0.40 $ 8 Pens to Plastic Sheet 4 $ 2.00 $ 8 Total Materials $ 271

Equipment Units Cost per Unit Total Films 20 $ 9.00 $ 180 Video Tape 5 $ 15.00 $ 75 Computer & Plotter Supplies $ 200 Total Equipment $ 455

VARIABLE COSTS Personnel Hour Cost per Hour Total Photo interpretation $ 2,400 Wetland Inventory 80 $ 15.00 Land Use Pattern Inventory 80 $ 15.00 Digitizing 120 $ 7.00 $ 840 Georeferencing 40 $ 10.00 $ 400 GIS Integration 120 $ 10.00 $ 1,200 GIS Processing 160 $ 15.00 $ 2,400 Maps Integration 240 $ 10.00 $ 2,400 Field verification 100 $ 7.00 $ 700 Total Personal $ 10,340

Travel Expenses Days Cost per day Per diem, 2 people 12 $ 120.00 $ 1,440 Gas & transportation /120 liters per day 120 $ 17.00 $ 2,040 Field assistant 10 $ 10.00 $ 100 Total Travel $ 3,580

Total Fixed Costs $ 726.00 Total Variable Costs $ 13,920.00 *Variable Cost per Square Kilometer $ 36.62

Cost per Km2 = Fixed Costs + (Variable Costs * Km2) For case of Tobari (400 Km2) = $ 726.00 + ($ 36.62 * 400)

Total estimated cost for the Procedural Model= $15,374.00

*Note: This estimate is before any administrative costs.