Title Page
 Table of Contents
 List of Tables
 List of Tables
 List of Figures
 Results - Section A: Emergy Synthesis...
 Results - Section B: Subsystems...
 Results - Section C: Rainforest-Land...
 Results - Section C: Rainforest-Land...
 Results - Section C: Rainforest-Land...
 Results - Section D: Emergy Basis...
 Results - Section E: Energy, Time...
 Results - Section F: Perspectives...
 Summary and Discussion
 Literature Cited

Emergy Synthesis Perspectives, Sustainable Development and Public Policy Options for Papua New Guinea
Full Citation
Permanent Link: http://ufdc.ufl.edu/AA00004018/00001
 Material Information
Title: Emergy Synthesis Perspectives, Sustainable Development and Public Policy Options for Papua New Guinea
Physical Description: Report
Language: English
Creator: Doherty, Stephen J.
Brown, Mark T.
Murphy, Richard C.
Odum, Howard T.
Publisher: Center for Wetlands
Publication Date: 1993
Subjects / Keywords: policy
simulation modeling
Spatial Coverage: Papua New Guinea
Coordinates: -6 x 147
General Note: 169 Pages
 Record Information
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: AA00004018:00001


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Table of Contents
    Title Page
        Page i
        Page ii
        Page iii
    Table of Contents
        Page iv
        Page v
    List of Tables
        Page vi
    List of Tables
        Page vii
    List of Figures
        Page viii
        Page ix
        Page x
        Page 1-1
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        Page 2-18
    Results - Section A: Emergy Synthesis of Papua New Guinea's Resource Base
        Page 3A-1
        Page 3A-2
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        Page 3A-21
    Results - Section B: Subsystems Analyses of Major Rural Production Systems
        Page 3B-1
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        Page 3B-10
        Page 3B-11
        Page 3B-12
    Results - Section C: Rainforest-Land Rotation Model
        Page 3C-1
        Page 3C-2a
    Results - Section C: Rainforest-Land Rotation Model
        Page 3C-2b
    Results - Section C: Rainforest-Land Rotation Model
        Page 3C-3
        Page 3C-4
        Page 3C-5
        Page 3C-6
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        Page 3C-8
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        Page 3C-13
        Page 3C-14
        Page 3C-15
    Results - Section D: Emergy Basis for Determining the Carry Capacity of Tourism
        Page 3D-1
        Page 3D-2
        Page 3D-3
        Page 3D-4
        Page 3D-5
        Page 3D-6
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        Page 3D-27
    Results - Section E: Energy, Time and Economic Expectations in a Highlands Valley
        Page 3E-1
        Page 3E-2
        Page 3E-3
        Page 3E-4
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    Results - Section F: Perspectives on Emegy Support of Indigenous Culture
        Page 3F-1
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    Summary and Discussion
        Page 4-1
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        Page 4-19
    Literature Cited
Full Text

Final Report to


Steven J. Doherty and Mark T. Brown

R.C. Murphy, H.T. Odum and G.A. Smidi

CFWWR' Publ.iLtion # 93-i"n

Research studies conducted under contract
to The Cousteau Society

Center for Wetlands & Water Resources
University of Florida
Phelps Lab, P.O. Box 116350
Gainesville, Florida 32611-6350


The Center for

An Education and Research
Unit of the University of Florida


Among the most important problems humanity faces today are the management of natural resources and
the integration of human and natural processes. There is a need to understand both human and natural
domains, each in the context of the other, and it is important to develop sound management strategies
which acknowledge and promote the vital interconnections between the two.

Traditionally, a reductionist approach to the study of humanity and nature has dominated. By comparison,
much less attention has been given to studying the biosphere at the ecosystem level of organization. It is at
the ecosystem level, however, where many of nature's most important processes occur, where human
benefits are derived and where our impacts fall most severely.

Most regions of the planet have already felt the heavy hand of development. Often such activities
undermine the natural resource base due to a focus on short-term benefits. Too often this approach sets in
motion long-term processes that drastically affect culture and minimize alternatives for sustainability.
There are, though, a few jewels, such as Papua New Guinea, where cultural and natural resources have
not yet been eliminated. These regions are coming under greater external pressure to "develop" along the
same destructive paths seen elsewhere. Consequently, there is an urgent need to protect and manage
wisely the cultural and natural heritage of Papua New Guinea. For these reasons the Cousteaus committed
the "Rediscovery of the World" expeditions to explore, study and document on film the richness of Papua
New Guinea.

Part of this project has been an investigation of Papua New Guinea's wealth in the broadest sense and an
analysis of major economic activities (forestry, fisheries and tourism). Supported by members of The
Cousteau Society, a research team from the University of Florida, USA, working under the direction of
Drs. H. T. Odum and Mark Brown, undertook a substantial research effort to understand the connections
among the human and economic sectors and the natural system. Using energy as a common denominator,
the study compares and analyzes alternative uses of Papua New Guinea's resources in a search for
sustainable strategies.

The research effort has shown that Papua New Guinea is one of the richest countries in the world: its
natural wealth provides people with a quality of life, independence and stability, which provide relative
immunity from the unpredictable fluctuations of external economics and politics.

We hope the insights provided by this report will encourage leaders to implement long-term strategies to
accomplish one of the objectives stated in Papua New Guinea's constitution, ". . . for Papua New Guinea's
natural resources and environment to be conserved and used for collective benefit of us all, and be
replenished for the benefit of future generations."

Richard C. Murphy
Vice President for Science and Education
Cousteau Society


As part of our effort to evaluate resource management questions in Papua New Guinea, we traveled to
Papua New Guinea in the spring of 1989. Responding to The Cousteau Society 's strong interest in
education, we offered a short course in techniques of resource evaluation and systems modeling at the
University of Papua New Guinea. We would like to express our gratitude to Dr. Patty Osborne of the
Biology Department, University of Papua New Guinea, for his hospitality and the excellent job he did in
organizing our workshop. With out his help we could not have had such an outstanding short course.
Participants in that workshop were a most interesting and enthusiastic blend of students and government
officials and we would like to thank them and wish them well in their endeavors to manage the resources
of their developing nation.

The participants in the short course were: David Coates, FAO, Papua New Guinea; Christopher Hershey,
Melanesian Environment Foundation, Inc., Papua New Guinea; William Asigau, Department of
Environment and Conservation, Papua New Guinea; Charles D. Tenakanai, Fisheries Research-DMFR,
Papua New Guinea; Ana Marikawa, Finance and Planning, Papua New Guinea; Malcolm Leveti, Dept. of
Geography, UPNG; Gavera Arua Rei, Melanesian Environment Foundation, Inc. Papua New Guinea;
Phille P. Daur, Biology Department, UPNG; Monica T. Rau, Forest Research Institute, Papua New
Guinea; Lester Seri, Department of Environment and Conservation, Papua New Guinea; Mary Walta,
Biology Department, UPNG; Tatsio Matsuoka, Department of Biology, UPNG; Anne Bothwell,
Department of Biology, UPNG; Ilaiah Bigilal, Natural History Museum,Papua New Guinea; Harold Ure,
USAJD/Radio Science Project, Papua New Guinea; Mathias Ure, Division of Research and Planning,
Papua New Guinea; Sir Ebia Olewale, Karawane Pty Ltd., Papua New Guinea; Alois Wafy, Department
of Fisheries/Marine Resources, Papua New Guinea; Barbara Brett, Department of Education, Papua New
Guinea; Carrie Turk, Department of Finance and Planning, Papua New Guinea; Pins Piskaut, Department
of Biology, UPNG; Robert Vonole, Department of Education, Papua New Guinea.

We would also like to thank Max Benjamin, owner of the Walindi Plantation on the Island of New Britain,
who provided a wonderful setting and data that allowed us to evaluate tourism. His dive resort was one of
the most ecologically sensitive, low energy, and culturally friendly resorts we have experienced . .. not to
mention the most incredible diving we have experienced an. where in the world.

John Furby, company secretary for Burns Philp Limited, Port Moresby, provided travel assistance. Dr.
David Scienceman of New South Wales, Australia, visiting scientist with the University of Florida's
Center for Wetlands & Water Resources, helped with logistical support, initiated contacts and supplied
preliminary data and literature sources. His interest and support are greatly appreciated.

An acknowledgement section would not be complete without recognizing the pivotal role The Cousteau
Society, Captain Jacques-Yves Cousteau, and Jean-Michel Cousteau have played in supporting our
research over the past eight years. Since beginning their series of expeditions titled "Rediscovery of the
World" they have provided funds and logistical support for our research as we accompanied the Cousteau
teams on numerous expeditions. As a result, we have gained much in our understanding of the relation-
ships between humanity and nature and have been able to share our insights with governments and citizens
around the world. We cannot thank the Cousteaus enough for the opportunity they have provided to both
research the complex questions facing humanity and to educate leaders, and future leaders of our water
planet in how we might begin to solve these important questions.


PREFA CE . . . . .. . . . . . . . . . . . . . . .... . . . . . ... . ... . . . .. . . . . ... . . . . . i

ACKNOWLEDGEMENTS ......... ............... ..... ........ ..... ii

LIST OF TABLES ...... ....................... .......... ...... . vi

LIST OF FIGURES.. . ..... ..................... .............. . viii

1. INTRODUCTION . . . . . . . ........................................... 1-2
Ecological Economics ....... . . . . .................. . ...... 1-2
Overview of Papua New Guinea . ................................... 1-3
Natural History and Ecological Support Base........ ........ ...... ......... . 1-3
Economy ..... . ....................... .............. . 1-5
Systems View of Papua New Guinea . . .... ........ .. .. ............ .. . 1-7
Study Plan ...... ......... ........ ........... . . . . . . 1-10

2. METHODS ............ .. ......... * ....... ...... . 2-2
Step 1: Detailed Energy Systems Diagrams .... ... ........................ 2-2
Step 2: Aggregated Systems Diagrams ... .. ............................. 2-4
Step 3: Solar Emergy E valuation Tables . . . . ... .... ................ . 2-5
Step 4: Solar Emergy Indices ... ........ .......................... . 2-6
Step 5: Microcomputer Simulation Models . . . . . . ....... ........ .. . 2-16
Step 6: Public Policy Questions .... ......... . ................... . 2-17

Section A: Emergy Synthesis of Papua New Guinea's Resource Base . ............... A-1
N national Overview ......... .. . ... .................. ........ A-i
Regional Analysis of the Highlands and Lowlands .. ................. . . A-12
Emergy Evaluation of Indigenous Resource Reserves . . ...... . .. . .... A-17

Section B: Subsystems Analyses of Major Rural Production Systems. . ............ .. B-i
Forestry in New Britain .......... ........................... . B-1
Sago Palm Cultivation in the Gulf Province . . .......................... . B-8
Sweet Potato Farming in a Typical Highland Village ...... . . . . . . . . . . . . . B-10

Section C: Rainforest-Land Rotation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-1
Introduction. ........................... . . . . . . . . . . . . . . . C-1
Model Description ..... . . . . . . . . . . . . C-1
M odel Simulation . ............ ............................ . C-9
Discussion . . .. ............................ ................ . C-14

Section D: Emergy Basis for Determining the Carrying Capacity of Tourism. . . . . . . . . . . . D-1
Introduction .................... ...... ....... ......... ... D-1
Results . ...... ................. ...... ...... ............ D-8
Discussion . . ...................... ........... ......... . D-21

Section E. Energy, Time and Economic Expectations in a Highland Village . . . . . . . . . . . . E-1
Introduction . .... . ... ..... . .. .. ... ...... .. .. .. ... . .... ... E-I
Results . ................ ............. ........... ....... E-4
Discussion . ..... ..... ...... ....... ........... .......... E-10

Section F: Perspectives on Emergy Support of Indigenous Culture . ................ . F-
Introduction ............... ........ ..... .......... ....... F-I
Results and Discussion ....................................... F-2

The Basis for Wealth in Ecologic-Economic Systems . ....................... 4-1

Resource Policy Perspectives for Papua New Guinea . ........................ 4-3
Solar Emergy Basis for Nation.................................... 4-3
Comparisons with Other Countries ................................ 4-5
International Trade and Balance of Payments . . ................ . . . . . . . .4-10
Regulauon and Investment Considerations in Forestry Sector ................... 4-15

Tourism Development, Environmental Impact, and the Local Economy ............... 4-17
A Definition for Ecotourism .................................... 4-18


APPENDIX: Brochure of collaborative workshop titled: Into the Future: Ecology, Economic and Public
Policy in Papua New Guinea. May 5-10, 1990. Co-Sponsored by The Cousteau Society, The
Department of Environment and Conservation and The University of Papua New Guinea.


Table Page No.

3A-1. Solar energy basis for Papua New Guinea's indigenous resource base, 3A-2
imports and exports in 1987.

3A-2. Summary of major solar energy and monetary flows for Papua New 3A-7
Guinea in 1987.

3A-3. Overview indices of annual solar emergy-use, origin, and economic and 3A-11
demographic relations for Papua New Guinea in 1987.

3A-4. Indigenous renewable solar emergy support for highlands and lowlands 3A-14
regions in Papua New Guinea.

3A-5. Storage of solar emerg. in resource reserves within Papua New Guinea. 3A-19

3B-1. Resource flows supporting rainforest logging in New Britain, Papua New 3B-4

3C-1. Calibration of variables and coefficients for Rainforest-Land Rotation 3C-4
Model (corresponding to systems diagram in Figure C-I).

3C-2. BASIC computer program used in simulation of Rainforest-Land Rotation 3C-6
Model (Figure C-i).

3D-1. Comparative national emergy indices for Papua New Guinea, Mexico and the 3D-12
United States

3D-2. Emergy evaluation of tourist resort on island of New Britain, Papua New 3D-13

3D-3. Emergy evaluation of four star tourist hotel in Puerto Vallarta, Mexico (from 3D-15
Brown et al 1992).

3D-4. Comparative emergy indices for tourist resorts in Papua New Guinea and 3D-18

3E-1. Time budgets for nine-hour work d&i s for highland villagers in Papua New 3E-6
Guinea in 1933 and 1953.

Table Page No.

3E-2. Summary of time budgets for a 168 hour-week for Papua New Guinea in 3E-7
1933, 1953 and 1975 and for the USA in 1975.

3E-3. A typical daily diet for an adult Papua New Guinea highland villager in 3E-9

3F-1. Estimate of solar emergy basis of indigenous culture in Papua New Guinea 3F-4
based on resident renewable inputs from ecological support base.

3F-2. Macro-economic value of shared and genetic information on Papua New 3F-6
Guinea culture.

4-1. Summary of solar emergy flows and indices for Papua New Guinea in 1987. 4-4

4-2. Solar emergy self-sufficiency and trade balance for Papua New Guinea and 4-7
other countries of the world for overview.

4-3. Environmental and economic components of annual solar emergy-use for 4-8
Papua New Guinea and other countries of the world for overview.

4-4. Population dcnsit. and solar emergy-use per unit area for Papua New Guinea 4-11
and other countries of the world for overview.

4-5. Solar emergy-use, population and per capital use for Papua New Guinea and 4-12
other countries of the world for overview.

4-6. Solar emergy-use, gross national products and solar emergy/dollar indices for 4-13
Papua New Guinea and other countries of the world for overview.

4-7. Summary of the solar emergy evaluation of tourism in New Britain, Papua 4-17
New Guinea.


Figure Page No.

1-1, Map of Papua New Guinea showing its location in the SouLh\west Pacific 1-4
Ocean, its major rivers, central mountain range, major cities, mining
operations and ports.

1-2. Systems diagram of the combined ecologic-economic system of Papua 1-8
New Guinea.

2-1. Symbols and definitions of the energy language diagramming used to 2-3
represent systems.

2-2. Simplified diagrams illustrating calculation of(a) net emer gy yield ratio; 2-7
(b) net emerg, exchange ratio; and (c) solar transformity.

2-3. Systems diagram illustrating a calculation of investment r:itio. environ- 2-10
mental loading ratio and net yield ratio for a regional economy.

2-4. Systems diagram illustrating calculation of investment ratio, environmental 2-12
loading ratio and net yield ratio for a sector of an economic

2-5. Overview diagram of a nation, its environmental resource base, economic 2-15
component, imports and exports: (a) main flows of money and solar emergy;
(b) procedure for summing solar emergy flows.

3A-1. National summary diagrams of annual solar emergy flows of Papua New 3A-9

3A-2. Map of Papua New Guinea showing its inland relief; lowlands coastal plains 3A-13
and highlands above 3t)l1m.

3A-3. Systems diagram relating solar emergy flows associated with highlands and 3A-18
lowlands regions of Papua New Guinea (data from Table A-4).

3B-1. Map of Papua New Guinea showing its forests of known and possible 3B-3
development potential.

3B-2. Systems diagram of biomass production and cutting in lowland rainforest 3B-6
of New Britain, Papua New Guinea (data from Table B-1).

Figure Page No.

3B-3, Aggregated systems diagram of sago palm cultivation in the Gulf Province 3B-9
of Papua New Guinea.

3B-4. Aggregated s\ stems diagram of sweet potato production in a typical highlands 3B-11

3C-1. Energy systems diagram of a computer simulation model of rainforest-land 3C-2

3C-2. Output of model simulation of rainforest growth and net primary production 3C-10
over 150 years.

3C-3. Simulation of biomass yield, iainlorest growth, and land rotations based on 3C-12
57/30 harvest schedule over 300 years.

3C-4. Simulation of total yield response over 300 years due to changes in minimum 3C-13
and maximum land rotations.

3D-1. Systems diagram of (a) a regional economy having no trade with external 3D-6
markets and (b) an economy that has developed trade.

3D-2. Systems diagram illustrating the interactions of tourism with the regional 3D-9

3D-3. Detailed s. stems diagram of a tourist facility showing the main production 3D-11
function that provides goods and services from the tourists who are attracted
by the resort's image.

3D-4. Overview diagrams illustrating USA trade advantage when tourists spend 3D-20
money in (a) Papua New Guinea and (b) Mexico.

3D-5. Schematic diagrams of a coastline showing alternate ways of grouping tourist 3D-24
resorts within their ecological support regions so as not to exceed economic
carrying capacity.

3E-1. Systems diagram of a pre-World War II village family unit in the highlands 3E-2
of Papua New Guinea, circa 1930 prior to industrialization.

3E-2. Systems diagram of a modem family unit in the highlands of Papua New 3E-3
Guinea, circa 1980.

3F-1. S� stems diagram showing the resource basis of cultural and genetic 3F-3
information, and their role in the organization of the combined system
of humanity and nature.


Page No.

4-1. Summary diagrams of ecological contributions, imports and export exchanges 4-9
with the world economy for Papua New Guinea and the United States (values
are normalized relative to environmental source inputs).

Emergy Synthesis Perspectives, Sustainable Development,
and Public Policy Options for Papua New Guinea

S.J. Doherti and M.T. Brown, editors


Papua New Guinea is at a pivotal point in its history. Rich in both culture and resources, the country is
poised between its isolated past and a complicated future. Papua New Guinea is increasingly being drawn
into the greater world economy at the expense of these rich ecologic and cultural systems. As its population
grows and its economy is further incorporated into the world economy. one based on imports and exports,
Papua New Guinea is confronted with man\ of the policy questions regarding the exploitation of natural
resources that all developing nations face.

This study was undertaken to address specific questions regarding resource utilization and proposed
developments in order to identify public policy perspectives for Papua New Guinea and make
recommendations for a sustainable future. Systems analyses of the national economy, its resource base of
environmental flows, imports and its exports were conducted. Several subsystems within Papua New Guinea
were also analyzed for investment requirements and net contribution to the combined national ecologic-
economic system.

Forest operations, rural production systems and tourism were each analyzed using data obtained from
industry experts and the current literature. Resource allocation between highland and lowland regions was
investigated based on demographic, socioeconomic and environmental conditions unique to each region A
microcomputer simulation model of rainforest gro- th and harvesting was developed to investigate the
relationships between land clearings and forest recovery. Energy and time in a highlands village was studied
and the concept of ecological support was applied to indigenous cultures. The question of whether or not raw
products should be directly shipped out of the country instead of using these resources internally was
addressed. A proper balance of development and environment was investigated based on the extent of free
indigenous sources which drive the economy. Alternative public policies were suggested which mni\ aid
Papua New Guinea in its eLforl to develop and still maintain its rich cultural and ecological systems.


Regional and national economies are increasingly becoming more global. Issues of resource development,
trade and information exchange are likewise growing in proportion to expanding populations and related
activities. Resources needed to support human potential today are placing great demands on our biosphere.
The days of frontier economics are behind us. Uncontrolled exploitation of limited resources has proven
disastrous in many regions of the globe. As economies and ecological support systems become more
interdependent, new disciplines are needed to "bridge the gap" of understanding between societies and nature.
It is now clear that neither ecology nor economics alone can address the problems of our global commons.
New measures of calth, of value, of contributions and production are needed that acknowledge the "natural
capital" and "ecosystem services" provided from healthy environments.

A new interface is now being recognized called "ecological-economics." It is an ambitious and necessary
attempt to understand the affairs of humanity and nature as a single, interdependent system. New tools are
being investigated to measure wealth, services and production fairly and equitably. In this report we use
systems analysis, a holistic approach to studJ ing the combined ecological-economic system of Papua New
Guinea. We use an alternative measure of value, based on real contributions to system performance, termed
FMI-ERG Y, spelled with an "M." It is a concept which quantifies "energy memory" in products and processes.
It is an accounting unit of total contributions, direct and indirect, used in the generation of a product or
service. It is a concept derived from understanding whole systems, their interactions and interdependencies,
and the resources driving and maintaining them.

While most analyses of energy investment have traditionally been used to investigate efficiency in industrial
processes, a broader approach is undertaken here to investigate Papua New Guinea's resource utilization and
exchange. Emergy analysis allows comparison and incorporation of environmental costs and benefits with
variables of traditional economic costs and benefits to provide a more comprehensive perspective for public
policy directives affecting the common good.


The country of Papua New Guinea (Figure 1-1) lies on the eastern half of the island of New Guinea just
above Australia in the southwestern Pacific Ocean. Its only island neighbor is Irian Jaya, which occupies the
island's western half. Together, they form the western end of Melanesia. It is one of the largest countries in
the South Pacific with a total area of 460,000 km2 including some 600 offshore islands.

Natural History and Ecological Support Base

Situated between the stable land mass of Australia and the deep ocean basin of the Pacific, the island of New
Guinea is considered one of the most mobile zones of the earth's crust (Loffler 1982). It is characterized by
high seismic activity, widespread volcanism, with young faulted and folded mountain chains being the most
conspicuous features of New Guinea. A great central spine of mountain ranges, extends for the length of the
island, with few gaps below 2000 m for much of its length. Between 2 and 10 degrees south latitude, New
Guinea lays claim to being the largest tropical island, the highest island, one of only three tropical areas with
glaciers (Gressitt 1982), as well as a land of a great v ariety of vegetation types, and most kinds of
environments except deserts (Johns 1982). Biolo!.icjll, . New Guinea is one of the most diverse habitats on
earth, with characteristic groups of biota such as the famous birds of paradise, the tree kangaroos, and the
specialized moss-forest weevils.

The indigenous populations of Papua New Guinea have historically been isolated from the world ccononim
and have only recently been in contact with external markets and political forces (Matthicssen 1962, Howlett
1967, Rappaport 1968, Bulmer 1988). The coLniln 's independence only came in 1975 after a century of
complicated political history and colonial rule. Owing to difficult terrain, plentiful resources as well as
cultural mechanisms, the peoples of PNG remain a fragmented and diverse society with over 700 pidgin
languages known to be spoken. The present day inhabitants of PNG exhibit a di\ ersity that "undoubtedly
reflects a lengths and complex history of settlement from outside the area, internal migration and
intermarriage" among the many villages (Chowning 1982).

15 0 1



Solomon Sea

Gulf of Papua

Port Moresb

Coral Sea


Figure 1-1. Map of Papua New Guinea showing its major rivers, central mountain range, major cities, mining operations and roads (from
Baldwin et al 1978).




The country's population is about 3.5 million, but is growing at a rapid 2-3% per .%car (Qureshi et al 1988)
due largely to immigration along its coastal port cities. Villages in the highlands, which has historically been
the more populated region, however, have maintained an average population of about 200 over the past 30
years even though the country's population has doubled (Bell 1986). Most of the immigrant population is
settling along coastal areas near ports where a monied economy has developed based mainly on exports of
unprocessed minerals, timber, tuna, and cash crops.


Traditionally, almost the entire indigenous population of Papua New Guinea was supported by a subsistence
economy based on agric culture A few groups were hunters and gatherers and those along the coast relied
largely on fishing (Howlett 1967). Every village had pigs, though they were more a part of cultural and
religious spheres rather than the economic sector (Rappaport 1968). The majority of inhabitants, however,
were cultivators, practicing various forms of swidden agriculture. Trade has always been an important form
of exchange which cannot be accounted for in traditional economic terms.

Even today, 80-85% of the population rely on some form of subsistence farming (Bell 1 986, Qureshi et al
1988) and 97% of all land is still held within customary land tenure systems (Qureshi et al 19881, Contact
with a monied economy has meant a shift from subsistence farming of indigenous crops to crops grown for
sale outside the village for the purchase of materials and energy which are increasingly being incorporated
into their culture. The economy is still in the earlk stages of de elopment, dominated by agriculture and
mining activities (PNG Information Booklet 1986). Since independence in 1975, the national economic
policy has aimed at financial stability while "promoting sustained, broad based growth and raising the rural
living standards" (Qureshi et al 1988). This is accomplished primarily by encouraging subsistence villagers
to increasingly participate in the production of cash crops either for export or for domest i, markets.

The mining sector now accounts for close to 15"% of the gross domestic product (GDP) and 60% of the
money received for exports (Qureshi et al 1988). Present mining of copper, gold, silver and the prospects for
oil exploration indicate that this sector will continue to contribute significantly to the annual GDP (Coopers et
al 1988). All minerals are extracted and exported directly; there is presently no internal processing of any

kind. Companies are foreign owned and Qureshi et al (1988) state that PNG receives only the money paid to
its people for the work they contribute and through leasing of the land.

Agriculture, while supporting either directly or indirectly 85% of the population, accounts for only 35% of the
GDP and about 43% of exports (Qureshi et al 1988) in monetary terms. Cash cropping systems constitute
55% of the total agricultural production, with the remaining 45% representing subsistence cultivation. Four
tree crops--coffee, cocoa, oil palm and copra--provide about 90% of agricultural exports (PNG National
Statistics Office 1986). Small holder farming tracts produce two-thirds of the output of these crops, with
commercial plantations accounting for the rest. Present ly timber extraction and fisheries together account for
only 7% of the dollar income earned from exports, although both sectors are considered to have considerable
potential for growth (Qureshi et al 1988). Exports, making up about 42% of the GDP, roughly balance
imports in monetary terms.

GDP in 1987 was 2.535 billion US$ with a debt service ratio (external loans/GDP) averaging 30% annually
(Qureshi et al 1988). More than half of this foreign financing requirement is related to private industry,
predominantly the mining sector. In addition foreign aid and an annual grant from the Australian
Government amount for about 37" u of budget revenue (PNG Information Booklet 1986). The growth of
GDP during the seventies averaged 1.2% annually (Galenson et al 1982). With an annual population growth
rate of 2.4%, the gro\ th in GDP averaged less than half the rate of population increase. Growth of GDP has
improved over the last few years, averaging 2.3% (Qureshi et al 1988), due mainly to increased mineral
extractions and sales.

Because of the continued importance of subsistence agriculture, only about 12.5% of the labor force is
considered formally employed (PNG National Stats. Office 198 7a) The remainder of the labor force is part
of the self-sustaining subsistence economy outside of the cash economy.


Papua New Guinea is an area of incredible variety of gcomorphology, biota, peoples, languages, history,
traditions and cultures. Diversity is its primary characteristic, whatever the subject of interest These
relationships of indigenous storage, environmental and economic inputs and outflows of Papua New Guinea
are shown in the conceptual energy diagram in Figure 1-2. The system's boundaries include the continental
shelf to a depth of 152 m below sea level (estimate made from map by Espenshade et al 1986) to insure the
environmental contributions of marine resources to the overall economy.

At the left of the diagram, outside renewable sources of sunlight, rain and tides are illustrated as input flows
driving the natural production systems. These major ecoregions are diagrammed as coastal/mangrove,
grasslands, lowland rainforests and montane/alpine rainforests for overview. Mixed lowland rain forests are
the predominant life zone, covering as much as 40% of the country (Davidson 1983). Geologic uplift is an
important input to Papua New Guinea, creating the vast mountain ranges as a land form with real
geopotential work stored. The top soils in the highlands valleys are fertile, often up to 1.5 m in depth
(Grossman 1984), and the climate is tropical and monsoonal with a high average annual rainfall of 1.2 meters
on the coasts to 3.8 m in the central highlands (PNG Information Booklet 1986). The heavy rainfall and
steep slopes give rise to extensive rivers, considerable erosion, depositing large quantities of alluvial material
into the highland valleys and flat coastal plains. These large river systems are shown being driven by the
interaction of mountains and rainfall.

Large mineral deposits of copper, gold and silver exist and are being mined and potential hydrocarbon
reserves are only beginning to be realized (Hapgood 1989). It is expected that these storage, although
concentrated and exhaustible, will continue to be the major source of revenue from PNG's rich natural

Subsistence farming is shown as a subsystem dependent on indigenous sources and energy production in
natural systems, with only minimal ties to the main economy. Religion and rituals are still very important in
rural villages shown in the diagram as information storage which feedback to the labor and land involved in
gardens. Subsistence agriculture and smallholder cash cropping involve the

raw material

Figure 1-2. Systems diagram of the combined ecologic-economic system of Papua New Guinea for overview. Shown are indigenous source
flows and imports (drawn outside the system frame)- major ecological sy stems, resource resent es. industries, economic sectors, rural and
urban communities, and culture (drawn as internal components); and exports and trade. P=Price.

most intensive and widespread use of Papua New Guinea's land resources. Bell (1986), however, notes that
many parts of PNG, perhaps 80% of the total area, remain unused due to steep topographic relief and
inhospitable climate. Most of Papua New Guinea's population is rural with 2/3 of the people involved in
subsistence gardening or cash cropping in highlands valleys and coastal plains. Shifting cultivation with a
rotation period of 10-15 years, has traditionally been the main basis of food production for villagers, growing
sweet potato, taro, cassava, and sago. These gardens may be used for up to 5 years or more before a new site
is selected (Bell 1986).

Increasingly, small landholders are converting land to produce cash crops such as coconuts, coffee, and cocoa.
Cash crop farms and tree plantations are diagrammed as fuel subsidized production systems drawing from the
environment. With human derived inputs of fossil fuels, fertilizers, goods and services the environmental
resources are incorporated into the overall economy of PNG. Industries are shown as subsystems drawing
from the storage of environmental and geologic production. Mining, fishing, and forest extraction are shown
as subsectors within the overall system. As indicated by their outflow lines, most of their product is not
incorporated or refined within the country and exported directly, contributing only to the economic (right
hand) side of the system. Hydroelectric power is harnessed from the rivers and used internally, since it cannot
be exported as a product like other fuels.

Money is shown on the right hand side of the diagram as dotted lines flowing in opposite direction of energy
flow, acting as a counter current to real products. Notice that money is paying only for the services of human
work and therefore not represented on the left hand, production side of the system diagram. Money is not
represented as pa) ing for the vast work of the environment. Further, as illustrated in the country diagram,
major aspects of PNG's economy are operating without money pathways, and therefore not accompanied by
dashed lines. Foreign aid is shown as an economic input with a multiplier action in the return flow of interest


In the study that follows, the nation of Papua New Guinea is considered as a system with its large inventory
of indigenous energy storage and flows as well as its interactions with the global economy. The report is
organized in four sections: Introduction, Methods, Results and Discussion. Results and Discussion are
presented as follows:

First, emergy analysis is used to develop perspectives on the country's resource-use and competitive position
with other nations of the world. Relationships of solar emergy flows to the economy are developed to make
policy recommendations based on resource requirements, use and exchange. All major components are
identified, including environmental sources, flows of money, human roles, imported goods and fuels, and
international exchanges. Highland and lowland regions are evaluated individually as well as analyses of all
major. known resource reserves. Indices are then presented which enable comparisons of emergy measures
with those of traditional economics.

Anal\ ses of several sectors of Papua New Guinea's economy are then presented: evaluations of forest
operations and tourism on the island of New Britain, sago palm cultivation in the Gulf Province, sweet potato
production in a highland A village A microcomputer model of forest-land rotation is presented to investigate
the exploitation rates, land clearings and ecosystem response in tropical rainforests. Activities studies are
then used to evaluate changes in economic expectations and time spent in varying tasks in a typical highland
villagee from 1930 to the present. Finally, a preliminary analysis of indigenous culture is presented.

New concepts such as ecological support area, net yield on investment. environmental loading and
buying power are presented which may aid the reader in better understanding solar emergy measures of
combined ecologic-economic systems. Conclusions are then drawn for each of these subsystems and an
interpretation and discussion of the implications and meaning of the results are given. Finally, these results
are used to evaluate management alternatives and make policy recommendations which account for the work
of nature and humans in the capital production of Papua New Guinea.

Given next is a short list of definitions given for key words and concepts used throughout this report.

Energy: Sometimes referred to as the ability to do work, with work defined simply as the ability to do or
perform something. Energy is a property of all things which can be turned into heat, and is measured in
heat units (BTUs, calories, or joules).

Emergy: An expression of all the cnerg, used in the work processes that generate a product or service in
units of one type of energy. Solar emergy of a product or service is the solar energy embodied, through
successive transformations, required to create and maintain the product or service. Emergy can be
thought of as energy memory -- that energy used up and transformed in a long chain of interactions.
culminating in a product or process that is being evaluated. Emergy, unlike energy, is not directly
measurable, but must be quani flied using sy ltmcis anal sis

Emjoule: The unit of measure of emergy is the" emergy joule," abbreviated emjoule. In this report, it is
expressed in the units of solar energy. previously used to generate a product or service, therefore
expressed as a solar emjoule (sej).

Empower: Power is defined as the ability to influence. Empower is the flow of emergy per unit time, a
measure of potential influence.

Macro-economic value: This is a measure of the money that circulates in an economy as the result of
some process. To obtain the macro-economic dollar value of an emcrgy flow or storage, the emcrgs was
multiplied by the ratio of total cmerg. use by Papua New Guinea to its Gross National Product (solar
em joules / kina or sej / US $).

Maximum empower principle: Systems that tend to prevail are those that take the most effective
ad\ antage of available emergy. S\ stems, economic or ecological, accomplish this by: reinforcing
productive processes, drawing more resources, and overcoming more limitations through effective sN stem
organization. A theory investigated in this study is that palterrns which maximize emergy contribute the
most wealth.

Nonrenewable energy: Energy and material storage that are used at rates that far exceed the rates at
which they are produced. Examples are fossil fuels and mineral ores. In each, geologic and
environmental processes of heating, compression and concentration occur at a rate much slower
than society's consumption. Soil can also be nonrenewable if it is depleted faster than its environmental
support system can naturally replenish it. Nonrenewable resources generally have large emergy values
since they represent large amounts of biological and geologic work.

Renewable energy: Energy flows of the biosphere that are generallN constant and reoccurring, and which
ultimately drive the bio-chemical processes of the earth and contribute to geologic processes. Examples
are sunlight, rainfall and wind. Each of these resources is ultimately limited by its flow rate -- systems
cannot draw from these sources any faster than they are delivered.

Resident energy: These are renewable resources that are characteristic of a region

Transformity The ratio obtained by dividing the total emergy used in a process by the energy . yielded by
the process. Solar transformity is measured as the solar emjoules per joule (sej/J) for a given product
or service. Solar transformities are used to convert energies of different types to solar emergy in order to
compare different energies of resources, products and services.


This study was undertaken using a "top-down" systems approach. The first step is to construct systems
diagrams that are a means of organizing large arrays of components, pathways of exchange and resource
flows that combine to form the combined ecologic-economic systems under study. The second step was to
evaluate all resources identified through discussion, literature review and diagramming which contribute to
the combined ecologic-economic system under study. The third step involves calculating several indices that
relate resource flows and monetary exchange in order to identify support base, economic vitality and carrying
capacity. Finally, public policy options are recommended for proposed development and resource-use

In order to determine the relation between resource-use and the gross national product and to better
understand and subsystem analyses and resource models in perspective of the national trends, the natural
resource base and economy of Papua New Guinea was first synthesized. Subsystems anahlses of the
highlands and lowlands, forest operations, tourism and culture were then undertaken. Computer simulation
models were constructed for forest rotations and offshore tuna and coastal shrimp fisheries operations.

Each system or subsystem was studied with a similar methodology (steps 1-6) as follows:

(1) First a detailed energy systems diagram of each system studied was drawn as a way to gain an initial
network overview, combine information of participants, and organize data-gathering efforts. This
was done for the entire count ry of Papua New Guinea and each of the subsectors that were
in% estimated.

(2) Next, aggregated diagrams were generated from the detailed ones by grouping components into
those believed important to system trends, those of particular interest to current public policy
questions, and those to be evaluated as line items in resource evaluation tables.

(3) Solar emergy evaluation tables were set up to facilitate calculations of main sources and
contributions to each system studied. Resource inputs and yields are reported in each table as
general accounting units (tons, joules, kina, US$, etc.) and also evaluated in solar emergy units
(solar emjoules) and macro-economic terms to facilitate comparisons and public policy inferences.

(4) Indices of solar emergy-use and source origin were calculated to compare systems, predict trends, to
suggest alternatives, identify system efficiencies, and which will be successful.

(5) For some systems a microcomputer simulation program was written to study the temporal and/or
spatial properties of an aggregated model. The program was used as a controlled experiment to

study the effects of varying one factor at a time. Data from literature, resource specialists in Papua
New Guinea, and the solar emergy analyses were used as calibration. Insights on sensitivities and
trends were then suggested from computer graphs.

(6) Models, evaluations and simulations were used to consider which alternatives generate more real
contributions to the unified economy of humanity and nature in Papua New Guinea.

Each of these steps are described in detail below.

Step 1: Detailed Energy Systems Diagram

For understanding, for evaluating, and for simulating, our procedures start with diagramming the system of
interest, or a subsystem of particular interest. This initial diagramming is done in detail with anything put on
paper that can be identified as a relative influence to the system of interest, even though it is thought to be
minor. The first complex diagram is like an inventory. Since the diagram usually. includes environmental and
economic components, it might be considered an organized impact statement. The following are the steps in
the initial diagramming of a system to be evaluated:

1. The boundary of the system is defined.

2. A list of important sources (external causes, external factors, forcing functions) is made.

3. A list of principal component parts believed important, considering the scale of the defined system, is

4. A list of processes (flows, relationships, interactions, production and consumption processes, etc.) is
made. Included in these are flows and transactions of money believed to be important.

5. With these lists agreed on as the important aspects of the system and the question under consideration,
the diagram is drawn using the following conventions of energy language diagramming (from Odum
1971, 1992):

Symbols: The symbols each have rigorous energetic and mathematical meanings (Figure 2-1). An
example of a system diagram is given in Figure 3 as an overview of the combined environmental-
economic system of Papua New Guinea.

System Frame: A rectangular box is drawn to represent the boundaries that are selected.


Pr -

Energy circuit. A pathway whose flow is proportional to the
quantity in the storage or source upstream.
Source. Outside source of energy delivering forces according to a
program controlled from outside; a forcing function.

Tank. A compartment of energy storage within the system storing a
quantity as the balance of inflows and outflows; a state variable.

Heat sink. Dispersion of potential energy into heat that accompanies
all real transformation processes and storage; loss of potential
energy from further use by the system.

Interaction. Interactive intersection of two pathways coupled to
produce an outflow in proportion to a function of both; control
action of one flow on another; limiting factor action; work gate.

Consumer. Unit that transforms energy quality, stores it, and feeds it
back autocatalytically to improve inflow.

Switching action. A symbol that indicates one or more switching

Producer. Unit that collects and transforms low-quality energy
under control interactions of high-quality flows.

Self-limiting energy receiver. A unit that has a self-limiting output
when input drives are high because there is a limiting constant
quality of material reacting on a circular pathway within.

Box. Miscellaneous symbol to use for whatever unit or function is

Constant-gain amplifier. A unit that delivers an output in
proportion to the input I but changed by a constant factor as long as
the energy source S is sufficient.

Transaction. A unit that indicates a sale of goods or services (solid
line) in exchange for payment of money (dashed line). Price is
shown as an external source.

Figure 2-1. Symbols and definitions of the energy language diagramming used to represent systems
(from Odum 1971, 1983).

Arrangement of Sources: Any input that crosses a boundary is a source, including pure energy
flows, materials, information, the genes of living organisms, human scr ices, as well as inputs that are
destructive. All of these inputs are given a circular symbol. Sources are arranged around the outside
border from left to right in order of their ability to influence the system (i.e., their solar transformities)
starting with sunlight on the left and information and human services on the right.

Pathway Line: Any flow is represented by a line including pure energy, materials and information.
Money is shown with dashed lines flowing in opposite direction of energy flows. Lines without barbs
to indicate direction of flow, may flow in either direction dependent on the difference between two

Out lows: An> out low which still has available potential energy, material more concentrated than the
environment, or usable information is shown as a pathway from either of the three upper system
borders, but not out of the bottom.

Degraded Energy: Energy that has lost its ability to do work according to the second law of
thermodynamics is represented as pathways converging to a heat sink at the bottom center of the
diagram. Included is heat energy as byproducts of processes and the dispersed energy from
depreciation of storage.

Adding Pathways: Paihwa) s add their flows when they join or when they go into the same the storage
tank. Every flow in or out of a tank must be the same type of flow and measured in the same units.

Interactions: Two or more flows that are different, but are both required for a process are drawn to an
interaction symbol. The flows to an interaction are connected from left to right in order of their solar
transformity; the lower transformity flow connecting to the notched left margin of the symbol (refer to
Figure 2-1 for details).

Counterclockwise Feedbacks: High-qualiht outputs from consumers such as information, controls, and
scarce materials are fed back from right to left in the diagram. Feedbacks from right to left represent a
loss of concentration because of divergence, the service usually being spread out to a larger area.

Material Balances: Since all inflowing materials either accumulate in systems storage or flow out,
each inflowing material such as water or money needs to have outflows drawn.

Step 2: Aggregated Systems Diagrams

Aggregated diagrams were simplified from the detailed diagrams, not by leaving things out, but by combining
them in aggregated categories. Simplified diagrams have: the source inputs (cross boundary flows) to be
evaluated; environmental inflows (sun, wind, rain, rivers, and geological processes, etc.); the purchased
resources (fuels, minerals, clectriciti, foods, fiber, wood); human labor and indirect services; money and

exchanges; and information flows. Export flows were also drawn. Initial evaluations were useful in deciding
what was important enough to retain as a separate unit in the diagram.

Components inside the system boundary included: the main land use areas, large storage of fuel, water, and
soil; the main economic interfaces with environmental resources, and final consumers. Interior circulation of
money was not drawn, but all the major flows of money in and out of the systems were included.

Step 3: Solar Emergy Evaluation Tables

All systems studied, including the national overview a nal sis and subsystems evaluations of forest
production, development and use are summarized using solar emergy evaluation tables with calculations of
inputs and summaries of solar emergy indices given as footnotes. Each table is presented similarly, with 6
columns, each with the following headings:

1 2 3 4 5 6

Solar Solar Macro-economic
Footnote Item Basic data transformity emergy value
(J, tons, $ cost) (sejIJ) (.j/.quanity,'.iimec (US$, 1988)

Column One is the line item number, which is also the number of the footnote in the table where the
source of the raw data is cited and calculations shown.

Column Two is the name of the item being evaluated, which is also shown on the aggregated diagram.

Column Three is the resource inputs to production, given in units reported by industry accounting or
obtained from environmental and statistical abstracts. These are reported as average annual flows (joules,
grams or US $) per unit volume or area, derived from various sources and identified as footnotes (column

Column Four is the solar transformity or solar emergy per unit for each input, measured in solar emjoules
per joule, s.,i/J (or . Ljigram: or s //dollar. see definitions below). These are obtained from pre% ious,
independent studies (updated from Odum et al 1983; McClanahan and Brown 1991, Odum and Arding
1991, and Odum 1991).

Column Fi e is the solar emergy of the resource input, measured in solar emjoules per year per production
output. It is the product of columns 3 and 4.

Column Six is the macro-economic value, reported in macro-economic dollars, for 1988. This was
obtained by dividing the solar emergy (column 5) by the relation of annual solar emergy-use to Papua New
Guinea's GNP in 1988. See definitions below for solar emergy per dollar index and macro-economic

Inputs and outputs for any evaluated sector is identified on each solar energy evaluation table and in the text
and footnotes using a similar notation. Aggregations of environmental inputs are identified as (I); each set of
purchased inputs associated with a particular process step is summed as (F); and product yields are
identified as Yi. Any solar transformities calculated as a result of a subsystems analysis are indexed in the
tables by lower case letters (a, b, c...) given as footnotes. This was done in order to separate solar
transformities derived from other, referenced independent studies and those that were calculated as a result of
this study.

Step 4: Solar Emergy Indices

From the emergy evaluation tables, comparative indices of solar emergy origins, allocations, exchange, and
relations to macro-economic valuation were calculated to draw inferences, gain perspectives, and aid in
decisions regarding public policy and welfare.

Net Yield Ratio

The net solar energy yield ratio is the solar emergy of an output divided by the solar emergy of those inputs
to the process that are purchased and fed back from the economy (Figure 2-2a). This ratio indicates whether
the process can compete in supplying a primary energy source for an economy. Typical competitive fuel
sources have been about 4 or 6 to 1, though these favorable ratios are declining as fossil reserves decline
increasing extraction and processing costs. Processes yielding less than those available may not be currently
economic as primary sources.

PUrckmaed Inflow (F)

Outflow of
Upgraded Energy (Y)

Net Emergy Yield Ratio = (Y-F)/F

Nation A: Emergy Exchange Ratio Imports-

A4-+C (au in nwW
Transformity of 0 = A-i- ofsome type)
0 energy )

Simplified diagrams illustrating (a) the calculation of the net emergy yield ratio (NYR) for
an economic activity where purchased goods, fuels and services are used to upgrade a
lower grade resource; (b) the calculation of the net emergy exchange ratio (ER) for trade
between two nations; and (c) the calculation of a solar transformity for the energy flow
"D" that is a product of the process that requires the input of 3 different sources of solar

Non- Renewabl. Source

Figure 2-2.

Exchange Ratio

The solar emerge exchange ratio is the ratio of solar emergy received to solar emergy delivered in a trade or
sales transaction. If the market transaction is trade, for example a trade of grain for oil, the ratio can be
expressed as the relation of solar emergy supporting each commodity (Figure 2-2b). If the exchange is a sale
of a commodity in order to generate revenue to purchase necessary goods or scrn ices. the exchange ratio can
be calculated as the solar energy of the product sold divided by the solar emergy that could be purchased with
the earned revenue. This is estimated using the solar cmenrgy/dollar index for the buyer nation or region.

A central theorem investigated here is that the area recei% ing the more solar emergy due to the market
transaction has its economy stimulated more. Previous studies have indicated that raw products such
as minerals, rural products from agriculture, fisheries, and forestry general. tend to have high exchange
ratios when sold at market price (Brown et al 1991, Brown and McClanahan 1991, Odum and Arding 1991).
This is a result of money. being paid for human services and not for the extensive work of nature that went
into these products. The solar emergy exchange ratio is used in this study as a measure of the relative trade
advantage of one trade partner over another.

Solar Transformity

As previously defined, this is the relationship between "what it took" to make a product or service and
its actual energy content. All independent contributing resources to a productive process, evaluated in
solar emergy, are summed logelhcr as the numerator and divided by the observed or actual energy\ content in
the denominator (Figure 2-2c). The units, thercfoi e, are solar emjoules /joule (sej/J). Solar transformiiies
used to convert natural resources, imports and exports in this study are drawn from independent studies
[Odum and Odum 1983 (updated in Odum 1991), Odum et al 1986, Odum et al 1987, Odum and Arding
1991). From emergy evaluations conducted in this stud\. some solar transformities are calculated for
products and services of Papua New Guinea and are listed separately (see emergy evaluation table heading
descriptions above).

If systems are operating at maximum power, a solar transformity for a product or service is a measure
of "potential value" to the receiving system. A related theorem investigated here, is that systems will self-

organize over time to develop components and pathways that stimulate productive processes which generate
at least as much as they require.

Investment Ratio

The solar emergy investment ratio (IR) is the ratio of solar emerge derived from the economy [F] to
the solar emergy delivered free from environmental sources (both renewable [I] and nonrenewable [N])
(Figure 2-3):

IR=F/(I+N) (1)

This ratio indicates if the process is economical as a utilizer of the economY's investments in comparison with
alternatives. The larger the IR, the greater the amount of purchased emergy is required per unit of resident
emergy. To be economical, the process should have a similar ratio to its competitors. If it receives less from
the economy, the ratio is less and its prices are less so that it will tend to compete in the market place. Its
prices are less when it is receiving a higher percentage of its useful work free from environmental inputs than
its competitors.

However, operation at a low investment ratio uses less of the attracted investment than is possible. The
tendency may be to increase the purchased inputs so as to process more output and generate more cash flow.
The tendency is towards optimum resource use. This suggests that operations above or below the current
regional investment ratio will tend to change towards the investment ratio common for that region.

Environmental Loading Ratio

Environmental loading ratio (ELR) is a measure of potential impact or "loading" a particular development
activity can have on its environment. It is the relationship of purchased emergy [F] plus resident
nonrenewable emcrgv [N] to resident renewable emergy [I] (Figure 2-3) as follows:

ELR= (N + F) /I (2)

Purchased Inputs (F)

Renewable Inputs

, / /1 . ------ C -- Yield (Y)


Investment Ratio of Regional Economy:

IRvon = F/(I + N)

Environmental Loading Ratio of Regional Economy:

ELR?, = ( F + N ) / I

Net Yield Ratio of Regional Economy:

YR oon = Y / F

Figure 2-3. Systems diagram illustrating a regional economy that imports purchased inputs (F) and
uses resident renewable inputs (I) and nonrenewable storage (N). Several ratios used for
comparison between systems are below the diagram and are explained in the text. The
letters on pathways refer to flows of solar emergy per unit time. Thus, ratios of flows are
dynamic and changing over time.


Nearly all productive processes of humanity involve the interaction of nonrenewable resources with
renewable sources from the environment. Low ELRs indicate relatively small "loading" on the ecosystem
support base, while high ELRs reflect greater potential impact. When compared with other ELRs of the
region, an ELR as a measure of environmental stress due to a proposed action can be used to address carn, ing

Evaluating Regional and Local IRs and ELRs

Figure 2-4 is a simplified diagram of a regional economy and a sector of the economy The sector uses
renewable resources (I,) and purchased goods and services from both the local economy (Fm) and external
markets (Fi). The sector is actually part of the regional economy, but is shown separately to highlight the
comparison between it and the region in which it is embedded. The investment ratio in the regional economy
(IR.) is derived using the ratio of purchased resources (F) to resident emergy (renewable sources supporting
the main economy [IJ plus nonrenewables [Nj) as follows:

IR = F / ( l,, +N,,) (3)

The investment ratio of the sector (IR) is calculated in a similar manner, accounting for all sources of
renewable and purchased resources as follows:

IR = (F, + F) / ( I, + N,) (4)

The environmental loading for the region and sector within the regional economy are calculated somewhat
dilTfferently from each other. The regional ELR is calculated as the ratio of nonrenewable (F+N,) to renewable
emergy (I,) as before. The ELR for the economic sector, howec er. has to take into account the portion of Fm
that comes from I,,,, since that area of environment is not adding to the "load" on the environment of the sector
but, in effect is part of the environmental support for the sector. Thus the ELR for the sector is calculated by
subtracting the portion of F,, that is from I,,. This done by first calculating the total solar energy of the main
economy (Total solar emergy {U] = Fm,+F,+N,+N,+I,+I,), then di\ iding by l, to determine the percent of the
total that is derived from renew able sources supporting the main economy (I,,).

-Purchased Inputs (F)

Investment Ratio for Economic Sector:

IR tor = ( F+FM)/( Is + Ns)

Environmental Loading Ratio for Economic Sector:
ELR or = [ FI + ( FM - kF ) + Ns / ( Is + kF )

Net Yield Ratio for Economic Sector:
NYRseor = Y / ( F + F)

Figure 2-4. Systems diagram of a regional economy showing the flows of energy from external
sources and from within the economy. The sector of the economy being investigated is
shown separated from the main economy in the lower left. The sector receives resources
from imports (F,), from the main economy (FM), from nonrenewable storage (Ns), and
from the environment (Is). The ratios given in the diagram are explained in the text.

The ELR for the sector is then determined as follows:

ELR,= [F + ( F- kF ) +N] /(I, +kF.) (5)
k = percent of total solar cnicrgy budget for main economy [U] that is derived from
environmental sources [I]

Determining Carrying Capacity for Economic Investments

Once the ELR for a region is known and the total annual nonrenewable energy use by a development
is determined, the area of land necessary to balance the development can be calculated using the average
annual flux of renewable solar emergy per unit area of landscape. This is can be used as a measure of power
density of renewable solar emergy, and is derived from the analysis of the regional or national economy. The
area of support necessary for a proposed development is here defined as its Carrm ing Capacity. To determine
the carr ing capacity of a proposed development, the ELR for the region is calculated (as above), and then the
following equivalent proportion is determined:

ELR -gon= ELRpropod development (6)
ELR,:,, = known
ELRdaveIopt = [ Fi + ( Fm - kF. ) + N, ] / (1 + kF )

and the equation is solved as follows:

(I, +kFm) = [ Fj+(F. -kFm, ) +NJ/ ELR ro (7)

Once the quantity (I, + kF ) is known, the area of landscape required to balance the proposed development
can be calculated as follows:

Support area (i.e. Carr-. ing Capacit) = (I, + kF, ) / I, (8)
egion = known power density for renewable resources of the region (sej / m2)


Relation of Solar Emergy Support Base and Economic Product
The relation of annual solar emergy-use to the gross national product of a country was considered an
estimate of the solar emerge supporting each unit of currency circulating in the economy for a particular year
(Figure 2-5). As the diagram shows, it includes renewable environmental sources such as sunlight, wind and
rain, non-renewable resources used such as fossil and mineral reserves and soil, imported fuels, goods and
services. In general, rural countries tend to have higher solar emergy/dollar indices because more of their
economy involves direct environmental resource inputs that are not paid for (Odum et at 1983, Odum and
Arding 1991, Brown et al 1991).

In this study, the solar energy to dollar index calculated for Papua New Guinea in 1988 is used to estimate
the amount of direct and indirect resources supporting each unit of currency. This is used to address all
inputs and all costs to production sectors, including an estimate of solar emergy supporting life-styles of
workers discussed below.

Macro-economic Value

The term macro-economic value refers to the total amount of dollar flow generated in the entire economy
supported by a given amount of solar emergy input. It is calculated by dividing the solar energy of a product
or process by the solar emergy/dollar index for the economy to which it contributes. This is a way of putting
an monetary value on services and storage not traditionalI\ accounted for in economics such as transpired
rainfall, photos. nthetic production, forest bicnmas<, volunteer labor, parenting and information. This is not a
market value, but instead a value for public policN inferences and directives.

Estimate of the Solar Emergyv Support Base of Human Services

The money paid for machinery, fuels and other goods necessary in a production sector pays for the human
services involved in the refinement, manufacture and delivery of the commodity. By summing the total solar
emergy input to Papua New Guinea in 1988, including environmental sources, fuels and foreign purchases,
the amount of solar cmergv supporting the gross national product was estimated, measured as solar emjoules
per unit currency (sej!kina or sej/US$) for that year. This relation was

E22 solar emjoules/yr


Indigenous Exports
R.No. NN2 N2B', E3


Figure 2-5. Overview systems diagram of a nation, its environmental resource base, economic component,
imports and exports (from Odum et al 1983): (a) main flows of money and solar energy; (b)
procedure for summing solar emergy inflows and outflows.



used to assign a solar emergy value to human services in proportion to the money paid for the service,
assuming that each kina paid for a product or service represents a proportional amount of solar emergy
supporting the direct and indirect human labor requirements. By multiplying the monetary cost of a
commodity or labor hour by this index of annual solar emcrg- flow to monetary flow, an estimate of
solar emergy supporting labor inputs and indirect human services was assigned.

Since money is only paid to people for their contributions and not for environmental work, this estimate was
derived so that human services could be cqui\ alentl) evaluated along with other inputs to the forest sector.
An average solar energy base for wages earned is an estimate of the lifestyle support requirements of both
direct forest laborers in Sweden as well as the associated human services that produce and deliver imported
commodities. This method of assigning resources supporting labor in proportion to the money paid is used in
other ecological economic accounting methods such as input-output matrix algebra (Costanza 1980, Hannon
et al 1985) and is not without its limitations (Odum 1992). Other methods are possible. For example, the
solar energy supporting labor can be estimated using an a% eragc solar transformity of human metabolism for
a given socio-economic class. While the method used here is an approximation, some measure of total
contributions to human work is necessary if the real requirements to sN stem production is to be assessed.

Step 5: Microcomputer Simulation Models

For simulation, the models in the systems diaigriims were aggregated further, combining features that
were unchanging, small, or belonging to a more general component or process. The source inputs, boundary
flows of money, and the main features of production and consumption were retained. State variables were
identified with descriptive names and mathematical expressions were written for interactions and processes
between state variables. These equations follow criteria predetermined by the orientation of components and
the relationships identified in the diagrams.

Numerical values for flows were written on the pathwl N\ s and on the storage tanks for the state variables in
the systems diagram Steady states were estimated for expected carn ing capacities within the system being
modeled and coefficients were determined for each interactive pathway (i.e. mathematical expression
identifying the relationship of two or more state variables over time). These equations, written into BASIC
computer language, could then be simulated over time and with changes in inputs or state variables using the


constructed mircocomputer program. By first identil\ ing the baseline calibration at steadN state, one variable
at a time can be changed in the program to study the effects made by manipulating the system. Graphs were
obtained from the computer simulations and included with the text in order to illustrate principles made
clearer by the simulation models.

Step 6: Public Policy Questions

Public policy alternatives that involve decisions regarding development and use of resources are guided
by two criteria in this study: (1) the proposed or existing activity should increase the total flow of solar
emergy into the economy, and (2) the alternative should be sustainable in the long term. The tools for
determining policy options have been outlined above. General themiodynamic principles of all systems are
then used to evaluate these tools and develop criteria for alternative public policies.

Development alternatives that result in higher energy inputs to an economy increase its vitality and
competitive position. A principle that is useful in understanding why this is so is the Maximum Emergy
Principle (which follows from the work of Lotka [1922a], who named it the "maximum power principle"). In
essence, the Maximum Emergy Principle states that the sN stem (or development alternative, in this case) that
will prevail in competition with others is the one that develops the most useful work with inflowing emergy
sources. Useful work is related to using inflowing emergy in reinforcement actions that insure and, if
possible, increase the inflow ing cmerg.. The principle is somewhat circular. That is, processes that are
successful maximize useful work, and useful work is that work which increases inflow, ing emergy.

It is important that the term "useful" is used here. Energy dissipation without useful contribution to
incrlesing inflowing emergy is not reinforcing, and thus cannot compete with sN stems that use inflowing
emergy in self-reinforcing ways. Thus, drilling oil wells and then burning off the oil may use oil faster (in the
short run) than refining and using it to run machines, but it will not compete in the long run with a system that
uses oil to develop and run machines that increase drilling capacity and, ultimately, the supply of oil.

Development alternatives that do not maximize emergy may not compete in the long run and are "selected
against." In the trial and error processes of open markets and individual human choices, the patterns that
generate more emergy will tend to be copied and will prevail. Recommendations for future plans and


policies that are likely to be successful are those that go in the natural direction toward maximum emergy

The second guiding criterion is that development alternatives be sustainable in the long run To be sure,
sustainability is an elusive concept. Ultimatel), sustainable developments are activities that use no
nonrenewable energy, for once supplies have dwindled, developments that depend on them must also dwindle.
However, the criteria for maximum emergy would suggest that energy be used effectively in the competitive
struggle for existence. Thus, when energy is available, its use in actions that reinforce overall performance is
a prerequisite for sustainability. To do othen, ise would suggest that the development would not be
competitive, and in the short run would not be sustainable. This alternative (no use of nonrenewable energy)
provides the lower bound for sustainability. The upper bound is determined by the Maximum Emergy
Principle as well. Sustainable developments are those that operate at maximum power, neither too slow
(elTicient) nor too fast (inefficient). The question of defining sustainability becomes one of defining
maximum power. In this analysis, we use the Investment Ratio and the Environmental Loading Ratio as the
criteria for sustainability. By matching the ratios of a development with those of the economy in which it is
imbedded, a proposed development is neither more nor less sustainable than the economy as a whole.

The systems analysis procedure is designed to evaluate the flows of energy and materials of systems in
common units that enables one to compare environmental and economic aspects of systems. Usually
questions of development policy and uses of resources involve environmental impacts that must be weighedd
against economic gains. Most often impacts and benefits are quantified in different units resulting in a
paral\ sis of the decision-making process because ihcrc is not a common means of evaluating the trade-offs
between environment and development. Emergy provides a common basis, the energy of one th pe that is
required by all productive processes.

While "Ecological Economics" and methods of se slems analyses of emerg) support are comparatively
new and still evolving, and often difficult to understand, we believe they offer an important step in developing
a quantitative basis for public policy decision making.



Section A: Emergy Synthesis of Papua New Guinea's Resource Base

by S.J. Doherty


Papua New Guinea is a resource rich country. Abundant rainfall, year round sun and deep soils provide a
renewable supply of energy, for forests and agriculture. Coastal resources are supported through waves and
tidal action along extensive shorelines and the continuous inflow of rivers into estuarine systems. Reserves of
minerals, metals and fossil fuels are currently being mined with increased prospects for the future based on
explorations and new discoveries. An emerg- analysis of indigenous sources, imports and exports identified
major resource contributions to PNG's ecological and economic base (Table A-1). The table, as described in
methods, identifies each source flow in energy units (J0. r) or mass (g.'yr), in solar emergy units (scj/. r), as
well as its macro-economic value. The resource flows are broken into three categories: 1) renewable inputs,
2) indigenous production, and 3) extraction of nonreplenishable storage.

Annual precipitation contributed the greatest emergy to terrestrial systems. A chemical potential energy in
rainfall was calculated as the Gibbs free energy in transpired rain. It is a measure of energy derived (4940
J/kg) from a chemical gradient between soil water taken up by plants and pure water that is transpired at the
leaf surface as part of photosynthesis and evaporative cooling. Geopotential energy in rainfall was calculated
as a gravitational potential due to impact of the rainfall on the earth's contoured surface. Thus rain
contributes to environmental work in two % a s -- potential energies due to chemical composition and
elevational position. The solar emerg) was measured as 600E+20 sej/yr and 730E+20 sej/yr, respectively% for
each potential energy in annual rains (items 3 and 4, Table A-1).
Large numbers of islands, extensive coasilincs and a wide continental shelf off the southern mainland result
in large solar emergy contributions from waves received at shore and the tides. Together these


Table A-1. Solar emergy support for Papua New Guinea's indigenous resource base, imports and
exports. All flows are based on annual contributions, using 1987 data. Calculations for
basic data are given as footnotes to this table (referenced in column 1).

Annual flows Solar Solar Macro-economic
Note Item raw units/yr transformityO emergy value"
(J, g) ksej/J) (10' sej/yr) (million US$, 1987)


Solar insolation
Wind, kinetic
Rain, chemical
Rain, geopotential
Waves received
Tidal energy
Earth cycle

2.59E+21 J
1.34E+18 J
3.30E+18 J
8.57E+18 J
6.15E+17 J
1.23E+18 J
1.85E+18 J





8 Hydroelectricity
(total electric generation)
9 Agriculture production
0 Livestock
I Fuelwood harvested
2 Fisheries
3 Forest extraction
4 Topsoil formation

1.08E+15 J
5.37E+15 J
3.97E+16 J
1.58E+15 J
3.60E+16 J
1.38E+14 J
2.00E+16 J
1.43E+17 J


2 OOE+06





1.75E+11 g
1.45E+07 g
3.68E+07 g





a) Mineral and metal ore resources are evaluated using solar emtergy per mass (ejigj>.
b) Solar emergy value divided by annual solar cmerg:, ue!GNP for PNG, 1987 (48 x 102 sejl$).

Table A-1, continued.

Annual flows Solar Solar Macro-economic
Note Item raw units/yr transformitya) emergy value
(J, g, $, p-y) (s.i/J) (10. sej/ r) (million US$, 1987)


18 Oil 2.80E+16 J 66000 18.49 38.54
19 Phosphorus 1.49E+11 J 4.14E+07 0.06 0.13
20 Nitrogen 5.69E+11 J 1.69E+06 0.01 0.02
21 Potash 4.09E+10 J 2.62E+06 0.001
22 Miscellaneous goods 5.13E+08 $ 3.60E+12 18.48 38.53
23 Net human migration) 9280 p-y 3.47E+16 3.22 6.72
24 Tourism 5.85E+06 $ 2.60E+12 0.15 0.32
25 Foreign aid 9.46E+08 $ 3.60E+12 34.06 71.00
26 Services in imports 9.63E+08 $ 3.60E+12 34.67 72.28


27 Cash crops 5.52E+15 J 2.00E+05 11.04 23.02
28 Fisheries products 4.8oE+13 J 2.00E+06 0.97 2.03
29 Forcstr) products 9.46E+15 J 2.53E+05 23.94 49.86
30 Copper 1.75E+11 g 4.50E+10 78.80 164.26
31 Gold 1.45E+07 g 5.00E+10 0.01 0.02
32 Silver 3.68E+07 g 5.00E+10 0.02 0.04
33 Services in exports 1.03E+09 $ 4.80E+13 495.47 1032.90

a) Mineral and metal ore resources are evaluated using solar emergy per mass (sej/g); human services, tourism and foreign
aid are estimated using sej/$ for Papua New Cuini-a for 1987.
b) Solar emergy value divided by annual solar emerg)y-LserGNP for PNG, 1987 (P, = 48 x 10"2 sej/$, Table A-2).
c) Net immigration of people to PNG is evaluated using an estimate for solar emergy supporting an immigidnt for an
average livespan ejipeo[ile-year.

Footnotes to Table A-1.

Derivation of annual energy flows of environmental contributions and principle production systems in Papua New Guinea,
circa 1987. 1 joule = 10' ergs = 1 I.g*n!esc2.

Renvr'able resources:

1. Direct solar insolation received over inland areas and continental shelf:
Shelf area based on measurement within the 153 m below sea level contour [est. from Eperiah:ae (1986)1 .
= [land area + shelf areal*(avg. insolation)*(1-albedo) = (4 h2E I1 m2 + 1.43E+1lm')(85 kcalkm/v'yriEt -l cm2/m2)
*(1-0.3 41 .L0/kcajli =2.59E+21 J/yr


Table A-i footnotes, continued.

2. Wind, kinetic energy (within 90 m of surface) =(3.717E+11 kWh/yrfl 3.6E+6 J/kWh) = 1.34E+18 J/yr (Gabel et al

3. Chemical potential, .-.nL-rg. in rainfall is estimated as the sum of highlands, lowlands and coastal systems contributions
(see subsystems analysis): highlands, 1.31E+18 J/yr + lowlands, 0 s7E+lS J/yr + continental shelf, 0.17E18 J/yr =
2.35E+18 J/yr

4. Gravitational potential energy in rainfall is estimated as the sum of highlands and lowlands contributing energies (see
subsystems analysis): highland.. 6.58E+18 J/yr + lowlands, 0.10E+18 J/yr = 6 45E+18 J/yr

5. Wave energy received at shoreline; (1.708E+11 kWh/yr; Gabel et al I187) (3.6E+6 J/KwH) = 6.15E+17 J/yr

6. Tidal energy = (continental shelf area) (0.5) (no. tides/yr)2 (density of seawater) (gravitational force) = (1.43E+11 m2;
Espenshade et al 1986) (mean tidal rangc. 1.56 m; US Dept. Commerce 1987) (1030 kg!'ni; Odum et al 1983) (706
tides/yr) (9.8 m/s) = 1 2 E+1I ' J/yr

7. Earth cycle = (4 62E +11 m2) (estimate heat il> o,'e, 4E+6 J/m2/yr; Odum et al 1983) = E 85E+ I J/yr

8. a) Hydroelectricity; 1,31L)[+6 k\\'hlt; Gabel et al lS47) (3.6E+6 J/kWh) = I 08E+15 J/yr
b) Total electricity generation, 1.49E�9 kWh, 1984 (UN 1986); (1.49E+9 kWh/yr) (3.6E+6 J',kWh)
= 5.37E+15 J/yr

9. Agrkultural production, 2.71E+6 tonne crop yield, 1982; United Nations 1984a); (2.706E+6 t) (E+6 g/t) (3.5 kcal/g)
(4186 Jl/1. = 3.97E+lb J/yr

10. Livestock production, 4.28E+5 t, 1982 (UN 1984a); (4.28E+5 t) (E+6 g/t) (4 kcal/g) (4186 J/kcal) 122% protein) =
1.58E-- l5 J/yr

11. Fuelwood production, 1.79IE+6 t, 1983 (UN lyx:5i; (1.7tbE+6 t) (1E+6 g/t) (2E+4 J/t) = 3 0.,E+lt J/yr
Solar Uarnsforrmity (40,000 sej/J) from sub.-.ten is analysis of rainforest biomass (Table B-l)

12. Fisheries (tuna, crayfish and prawn), 3.75E+4 t, 1982 (UN 1984a); (3.75E+4 t) (E+6 g/t) (4 kcal/g) (4186 J/kcal) (22%
protien)= 1.3SLE 14 J/yr

13. Forestry, 1.25E+6 mi avg. annual harvest (PNG Information Booklet 1986); (1.25E+6 mi) (8E+5 g/m') (2E+4 J/g) =
2 (iE+16 Ji/:r. Solar transformity (253,000 sej/J) from ul):,,.Ieni, analysis of forest products (Table B-1).

14. Net topsoil formation;

a) Soil formation assumed occurring on half of forest area = (1/i2c,3 3'4E--11 m2 rainforest; McIntosh 1974) (1260 g
soil build up/m2/yr) = 2.14E+14 g/yr;

b) Soil loss on agricultural areas estimated as ,.3 ? NE' mi agricultural land; UN 1984b) (850 g soil loss/m'/yr; est.
Odum et al 1987) = 3.2E1 l 2 g/yr;

(soil fIorrnaiionu-isoil eroded) = (2.14E+14 g/m2/yr) - ('3 2E+12 g/rri/:,T) = 2.11E+14 g/yr

Energy in organic matter of soil estimated as (2.11E+14 g/yr) ('.3 OM content) (5.4 kcal/g) (4186 J/kcal)
= 1.43E+17 J/yr

15. Copper, :.75Et5 t/yr mined (UN 1984a); (1.75E+5 t/yr) (1.0E+6g/t) = 1.75E+11 g/yr

16. Gold, 1.45E+4 kg/yr mined irIN 1y4j)., (14500 kg.1 i 0IClIg/k.g; = 1.45E+7 g/yr


Table A-1 footnotes, continued.

17. SiIver, 3bx.0O kg/yr (UN 1984); (36800 kg)l(100 X/kg) = 3.68E+7 g/yr

18. Oil, foreign imports = 2.80E+16 J/yr (Johnston 1984)

19. Phophorus imports, 1300 t/yr (UN 1984); % P by atomic wgl, P04 = .33; est. [PO0] as 10% of bulk fertilizer; (1300 t)
(.33) (.1) (E+6g/t) i3-18J/g) = 1.AE+l I J/yr

20. Nitrogen imports, 3200 t/yr (UN 1984); % N by atomic wgt, NH, = .82; est. [NH3] as 10% of bulk fertilizer; (3200 t)
(.82) (.1) (E+6g/t) 12.17E+3 J/g) = 5.6'E+ll J/yr

21. Potash imports.. 1100 t/yr .,UN 1984); est. K as 53% of bulk fert; (1100 t) (.53) tE+6g/i) (702 JIg) = 4.09E+10 J/yr

22. Goods (Yearbook of International Trade Statistics 1981): .food/l ,e animals, 9.227E+7 US$ + beverages/tobacco,
7 334E+6 US$ + crude materials excluding fuels, 2.02SE+o LIS$ + machines/transport equipment, 1.378E+8 US$ +
basic manufactures, 6.066E+7 US$, misc. manufactured goods, 3.471E+7 US$ + other goods not classified, 1.785E+S
US$ = 5.13E+8 US$

23. Net human immigration, 371 irminigatio.rLns (PNG Natd. Stats. Ollike 1987b); (371 persons/yr) (25 yrs old, avg.) = 9280

24. Tourism, visitor arrivals (19r..i = 8363 people (PNG Nail. Stats. Office 1987b); (8363) %Sl00l/day average expenditures)
(7 day stay) = 5.85E+6 US$

25. Foreign, Aid, K 880 million iCoopers and Lybrand 9IJS.; (8.8E+8) (US$ 1.075,K.) = 9.46E+8 US$

26. Human services in import products; (K 8.73E+8 import expenditures; Qureshi et al 1988)/(K 0.9302/USS) = 9.63E+8
US$. Solar emergy determined from emerg,'GNP index calculated from this study (Table A-2).

27. Cash crop exports (PNG National Stats. Off. 1986); (cocoa beans, 3.09E+4 + coffee, 5.31E+4 + copra, 1.13E+5 + copra
oil, 4.11E+4 + palm oil, 1.29E+5 + rubber, 4940 + tea, 5320)tonnes = 3.77E+5 t; (3.77E+5 t) (E+6 g/t) (3.5 kcal/g) =
(4186 J/kcal) = 5.52E+15 J/yr

28. Fisheries 1985 exports, 1.32E+4 t (P'NG Info. Booklet I9.S7.); (1.32E+4 t) (E+6 g/t) (4 kcal/g) (4186 J/kcal) (22%
protein) = 4.86E+13 J/yr

29. Forest products 1986 experts (PNG Info. Booklet 1987); logs, 4.5E+5 m3 + lumber, 4.0E+4 m3) = 4.9E+5 m3; (4.95
E+5 m') (8E+5 g/m3) (2E+$ J/g) = 7.84E+15 J/yr.

woodchips, 8.10E+4 t i1PNG Natl. Stats. Office 1987a); (8.1E-+4 t) (E+t. g/t) t2E+4 J/g) = 1.62E+15

total energy in forest exports = 9.46E+15 J/yr.

Solar transformity .253.0U.i .,)'Jj from analysis of forest products (Table B-1).

All mineral, metal ores are exported without refinement:
30. Copper exports, 1.75E+11 g/yr

31. Gold icporrt, 1.45E+7 g/yr

32. Silver exports, 3 ?EE+7 g/yr

33. Human services in export products, 1987 = 1.03E+09 USS (Qureshi et al 1988)


independent sources supply almost 400E+20 sej/yr to PNG, about 20% of total free c.unibuiiins from
indigenous environmental resources. Productive estuaries and extensive coral reefs are supported by
these energies along with extensive inland runoff resulting in large volumes of freshwater to deltas supplied
from numerous rivers. An estimate of earth cycling due to subsurface heat flow was calculated as about
10% of indigenous renewable contributions. This estimate is considered low, as evidenced by tih- high
degree of orographic and volcanic activity in this geologically young land mass (Dow 1977, Loffler 1982).

Many environmental inputs (ie. rain, wind, waves and earth heat flow) are byproducts of the same coupled
solar, atmospheric and geologic processes. Global solar insolation drives physical processes and bi,'lugicil
processes, which in turn are coupled. Wind patterns and surface waves, :on\.ection currents, c% :iporation
over oceans and land surfaces, and weather systems, among other processes are all driven either directly
or indirectly from the sun's energy. The solar transformities used to determine the solar emergy of each
of these inputs were calculated using the annual global flux of solar insolation and deep earth heat released.
The solar transformities are therefore coupled, and in order not to "double count" resource inputs that are
not independent, only the largest contributor of solar energy is counted, representing all co' upled
environmental sources. A total rented ble solar ermergy flow for Papua New Guinea (R) was estimated as
the sum of rain, tides and earth cycle -- a contribution of 1050E+20 seji's r. over 80% of annual solar
emergy-use in the country. Table A-2 summarizes all resource flows for Papua New Guinea in 1987.

Productive sectors of the economy include agriculture, livestock, forest, and fisheries (itemv 8-13, Table
A-1). Hydroelectricity generation is a fledgling industry with potential for growth as evidenced by current
production and the emergy supplied from runoff collected in rivers moving across elevated g radients (i.e.
gravitational potential energy of rain runoff). These indigenous production systems are supported by the
independent sources described above. Almost 2 million tons of fuelwood is harvested each year for
domestic cooking and heating, representing a rural resource formed from past environmental work. This
resource supplies 14E+20 sej/yr on average to the country's indigenous resource base. E..ni a:tti, on of
forest materials was calculated using a solar transfurmity of 2.53E+5 sej/J derived from a subsystems
analysis of forest development in Section B of this report. Forest products contributed 50E+20 sej in 1987
and over half was exported as logs and woodchips (items 13 and 29). An estimate of topsoil loss and
formation showed a net build up contributing about 8% of the


Table A-2. Summary of major solar emcrg flows and market economic monetary flows for Papua
New Guinea, 1987. Complete analyses are given in Table A-1.

Solar energy Market value
Variable Item (10" sej/yr) (109 US$, 1987) sej/$

R Renewable sources') 1050.1
N Nonrenewable sources within Papua New Guinea 190.3

No Dispersed rural sources2) 104.5
N, Concentrated use3) 2.6
N2 Export of unprocessed raw materials4) 78.8
F Imported fuels and fertilizers 18.6 0.246
G Imported goods 18.5 0.717
I Dollars paid for imports5) 0.963
P21 Solar emergy value of service in imports6) 17.1
E Dollars received for exports) 1.033
PIE Solar emergy value of service in exports'7 290.5
B Exports transformed, upgraded within country"' 36.0
x Gross National Product, 19S7 (0.93 kina/US$) 2.535
P2 World solar emergy/$ index9) 3.6 x 1012
P, Papua New Guinea's solar energyy$ index 48.0 x 1012

Footnotes to Table A-2.

1) solar emergy contributions from rainlall, tidal energy and earth cycle. Other renewable sources are accounted in this
summation -- since they are coupled, gIb.ilb flows, their solar transfomities share global solar energy flux.
2) fuelwood production and net top soil formation (items 11 and 14, table 1)
3) hydroelectricity gener.tliiir (item 8, table 1)
4) all mined minerals (Cu, Ag, Au) are currently exported directly without value-added processing.
5) data for import expenditures and export revenues from Qureshi et al (1988).
6) imported services (P21) are corrected by subtraLiing the cost of goods (item 22, table 1) whose solar transformity includes
human services from import expenditures: (.1 't.31 - 0.513 lEt9 US$ = 0.450 E+9 US$; solar emergy value is estimated
by multiplying the $ received for imported services by 3.6E+12sej/$ averagee sej/S index for world economy):
(0.450E+09 $) (3.8E+12seji$) = 17.12 E+20 sej/yr
7) exported services (PE) are corrected by subtracting revenues for agricultural, forestry, and fisher) products (items 27-29,
table 1) whose solar transformities include human labor involved in their production and retrieval: (1.033 - 0.342 - 0.077
- 0.008)E+9 US$ = 0.6056 E+9 US$; solar emergy value is estimated using sej/$ index for Papua New Guinea (48.0E+12
sej/$): ,0 (t156E+9 $) (48.0E+12 sej/$) = 290.69 E+20 sej/yr
8) agriculture, fisheries and forestry product. (items 27-29, table 1)
9) from Odum and Odum (1983), updated in Odum 1991.


solar emergy base of Papua New Guinea. Large reserves of solar emergy are mined each year in the form of
copper, gold and silver (items 15-17), totaling about 80E+20 sej/yr. All excavated material is currentlI
exported, thus not contributing directly to production sectors in the country's economy, except for what the
revenues from overseas sales can purchase in terms of needed goods, fuels and services not yet available
within its boarders.

Goods (G), fuels (F) and services (P2) purchased outside the country contributed 54E+20 sej in 1987, about
5% of annual solar cmcrgy-use (Table A-2). Imported fuels represented the largest single import commodity
in 1987 (item 18, Table A-1); over 30% of imports, though less than 2% of the total solar emergy used. The
solar emergy buying power in foreign aid (950 million US $ in 1987) represented an inflow of 35E+20 sej,
representing 60% of imports, yet only 3% of the country's annual emergy base. Over seven times as much
solar emerg) was exported than received through imports in 1987. Direct export of unrefined metal ores (N2:
Cu, Ag, Au) accounted over 20% of exports. Cash crops such as coffee, cocoa, sorghum, and rubber,
accounted for roughly 3% of exports. A majority of forest products are still used within the country as
indicated by the larger amount of wood harvested for domestic use than for export pulp and logs.

Copper ores and forest products represented the two greatest exports of solar emergy. The solar emergy
supporting Papua New Guineans employ ed in services related to the extraction, production and delivery of
export commodities was estimated at 290E+20 sej in 19s8 (PE). As described in methods, this value is a
measure of resources and purchased goods that are consumed directly and indirectly in order to support the
people who produce services or commodities for sale to outside markets. This value suggests that the
majority (75%) of solar emergN exported from Papua New Guinea was the support base of the people, largely
the environment. In other words, low cost raw materials and upgraded goods are subsidized by an abundant
and still healthy ecosystem fe support base.

Figure A-1(a) summarizes resource flows for Papua New Guinea in 1987. Environmental sources are
identified at the left; mineral, soils and forest wood are shown as internal storage, market goods, services
and money are shown toward the right Numbers and variables on the pathim as s correspond to evaluations in
Table A-I and summarized in Table A-2. A three-arm diagram [Figure A-l(b)] further aggregates
contributing flo\\ s as three pathways: 1) free indigenous, environmental sources



Indigenous 1237

Figure A-1.

1 1 58

Total Exports 406

National summary diagrams of annual solar emergy flows of Papua New Guinea. (a)
Aggregated diagram of major resource flows and monetary exchange. Values on pathway
correspond to Table A-2. (b) Three-arm diagram further summarizing contributions as
indigenous sources, imports and exports.


[R + (No + N1)]; 2) purchased imports (F + G + P21); and 3) exports to other countries (B + PIE and N2).
These diagrams assist the reader in s) nthesi.'ing the energy evaluations by combining similar flows from the
tables and aggregating the systems diagram of the country presented in the introduction.

A number of indices relating resources, people and the economy of Papua New Guinea have been prepared in
order to draw perspectives on the relative importance of contributing emergy sources (Table A-3). The first
seven entries are simple aggregations of supporting emergy flows evaluated in Tables A-1 and A-2. The
other listings are ratios and indices derived from these summations. Over 85% of PNG's total support base is
delivered from renewable environmental sources -- much higher than most other countries of the world.
Including nonrenewable sources, about 95% of PNG's emergy basis is derived from within the country (item
14). In other words, the environment contributes more than 6 times the solar emergy than is received through
economic transactions. Currently, electricity and fossil fuel consumption account for less than 5% of the
country's annual emergy-use

On the other hand, Papua New Guinea exports more than 7 times as much solar emergy as it can purchase
with revenues from overseas sales (item 11, Table A-3). This translates into a net emergy deficit due to trade
of about 350E+20 sej/yr -- about 25% of the country's annual emerg -use Relating annual emergy-use to the
country's GNP, 52 trillion solar emergy joules are used annually for each kina circulating in the economy
(exchange rate 0.93 kina/US $, 1988 ; 48E+12 sej / international $ US). This index is an order of magnitude
higher than more developed countries. For instance, in 1987 the USA emergy/money index was about 2E+12
sej/$ US (Odum 1988). This suggests that much more solar energy supports each unit of currency in PNG.
When products are sold at market value to overseas buyers, PNG delivers 20 times more solar emergy to the
foreign market than thce could purchase with the revenues from the sale. This solar emcrgy represents
environmental resources supporting the people of PNG, including both monied and unmonied lifestyles. By
not recognizing the services and products provided from PNG's ecological support base, resources sold to
foreign buN crs are subsidized resulting in low prices that do not accurately rellect the ability of a resource to
stimulate real work in the receiver's economy.

An estimate of a carrying capacity based on renewable resource use for the people of Papua New Guinea was
estimated using current emergy-use and the percentage of that annual consumption that


Table A-3. Overview indices of annual solar emergy-use, origin, and economic and demographic
relations for Papua New Guinea, 19S7.

Name of Index Derivation Quantity

1 Renewable solar energy flow
(rain, tides, earth heat floA)
2 Solar emergy flow from indigenous
nonrenewable reserves
3 Flow of imported solar emergy
4 Total solar emergy inflows
5 Total solar emergy used, U
6 Economic component
7 Total exported solar emergy
8 % Locally renewable (free)
9 Economic/cnvironment ratio
10 Ratio of imports to exports
11 Export to imports
12 Net solar emergy deficit due to trade
(imports minus exports)
13 % of solar emergy-use purchased
14 % of solar emergy-use derived
from home sources
15 Solar emergy-use per unit area
(0.462 million km2)
16 Solar emergy-use per person
(3.5 million people)
17 Renewable canr ing cjpacit)
at present living standard
18 Developed carrying capacity
at same living standard

1050.1 x 1020 sej/yr

(U-R) / R
(F+G+P21) / (N2+B+PiE)
(N2+B+PiE) / (F+G+P21)

(F+G+P21) - (N2+B+PE)
(F+G+P21) / U

190.3 x 1020
54.1 x 1020
1294.6 x 1020
1215.8 x 1020
165.6 x 10'0
405.3 x 1020

- 351.2 x 1020

(N,+R) / U



95.5 %

U / area

U / population

(R/Ll)* po(pulat ion0)


0.26 x 1012 sej/m2

34.7 x 101s sej/person

3.02 x 106 people

24.2 x 106 people

Index of solar emerge -usc to GNP
% Electric (1.5 TWh)
% Fossil fuels
Fuel-use per person

P, = U / GNP,187
(electricity use) / U
(fuel use) / U
fuel-use / population


48.0 x 1012
0.53 x 10i"


was renewable (R/U). Just over 3 million people can presumably be supported on a sustainable basis using
only resident renewable resources (about 87% of current population). With increasing ties to world
economies, developing to global standards, Papua New Guinea could presumably support almost 7 times the
current population. This assumes greater trade with outside markets, greater use of indigenous resources, and
an increase in the country 's regional investment ratio (IR) to a world average of 8 to 1 (purchased imports to
environmental source contributions). Such an increase would be accompanied by further integration into a
monied economy and a lowering of per capital energy consumption resulting in a lower standard of living. A
few other indices relating population and area to solar emergy-use are presented in Table A-3. These indices
and the others discussed here will be revisited in the Recommendations and Conclusion Section of this report
comparing Papua New Guinea's emergy and economic indices to other countries of the world.

It is evident here that Papua New Guinea is still a rural country with most of its real wealth derived from free
indigenous sources. There is a 20:1 ratio of environmental emerg) to purchased imports, re% dealing a low
dependence on foreign exchange. At the same time, a large amount of solar emergy is exported %without any
refinement in the country. Raw materials provide societ- with a net contribution of solar emergy due to past
unmonied environmental work, supporting value-added industries and peoples. Currently, as evidenced by
low solar energy contributions from imports relative to exported resources, Papua New Guinea is operating
at a net trade deficit. This is possible due primarily to a large ecological support system -- one that will
increasingly be threatened with further developments that don't consider these free contributions.


An emergy evaluation of the highland and lowland regions of Papua New Guinea was undertaken to better
understand the role of ecological and ph. siographic conditions considered unique to each region and their
effects on resource production and allocation. The country's relief is shown in Figure A-2 and Table A-4
summarizes physiographic and climatological differences between the regions.

The highlands represent those lands greater than 300 meters in elevation, comprising 56% of PNG's land
base. Based on data from Davidson (1983), the mean elevation of the highlands above the upper limit of the
lowlands (300 meters) is 1000 meters. This elevation was used to calculate the


Map of Papua New Guinea, showing its inland relief; lowlands coastal plains, highlands above 300m, and the central
cordillera above 2400m.

Figure A-2.

Table A-4. Indigenous, renewable solar cmrrgy support for highlands and lowlands regions in Papua
New Guinea. Calculations are given as footnotes to this table.

Highlands" Lowlands2 Country total

% Total area 56 44 100 %

Avg. elevation 1000 150 794 m

Annual rainfall 3.73 1.20 2.62 m/yr

volume 699 68 767 x 109 m4/yr
percent of incident rainfall 72 28 53 %

Evapotranspiration 28 72 47 %

Chemical potential emergy in rainfall" 238 189 427 x 1020 sej/yr

Geopotential emergy in rainfall 719 11 730 x 102) sej/yr

Chemical stream emergy ---- ---- 1708 x 1020 sej/yr

Phi),ical stream emergy4 ---- ---- 314 x 10' sej/yr

Footnotes to Table A-4.

1. Highlands region
a. chemical potential: "highlands area) (rainfall) (% ET) (density of rain water) (Gibbs free erierg.) = (56%)(4.62E+11
m') (3.73 m rain) (0.28) (1000 kg/m') (4940 JI/kg) = 1.31E+18 J/yr;
solar trherg:, = (1.31E+t8 J/yr)(18200 s.'j,'J) = 2.3X[+22 sej/yr

b. geopotential energy: (highlands area) (avg. elevation) (rainfall) (% runoff) (density of rain water) 'gravitational force)
= (5r(')I.4.62E+ll m2) (1000 m) (3.73 m rain) (0.72) (1000 kg/m') (9.8 m/s2) = 6.85E+18 J/yr;
solar emergy = (6.85E+18 J/yr) (10500 sej/J) = 7.19E+22 sej/yr

2. Lowlands region
a. chemical energy. rain over land: (lowlands area) tirinfill) (% ET) (density of rain water) (Gibbs free energy) =
(44%)(4.62E+11 m2) (1.20 m rain) (0.72) (1000 kg/m3) (4940 J/kg) = 0.87E+18 J/yr;
solar emergy = (0.87E+-18 J/yr) (18200 sej/J) = 1.58E+22 sej/yr

chemical energy, rain over coastal system: (continental shelf) .rainfall) (density of rain water) (Gibbs free energy
for seawater/rainwater differential) = (1.43E+11 m2) (1.20 m rain) (1000 kg/m1) (1000 J/kg) = 0.17E+18 J/yr;
solar energy = (0.17E+18 J/yr, over sea) (18200 sej/J) = 3.09E+21 sej/yr

total chemical emergy in rainfall = (1.58 + 0.31)Ei22 sej/yr = 1.89E+22 sej/yr


Table A-4 footnotes, continued.

2. b. physical energy, rain over land: (lowlands area) (avg. elevation) (rainfall) (% runoff) (density of rain water)
(gravitational force) = (44%)(4.62E+11 m2) (150 m) (1.20 m rain) (.28) (1000 kg/m') (9.8 m/s2) = 0.10E+18 J/yr;
solar energy = Q.U.lUEtl8 J/yr) (105O0 sej/J) = . 05E+21 sej/yr

3. Chemical stream energy estimated as contributions from 2 sources: 1) volume flow from highlands runoff into
lowlands and 2) runoff from lowlands into coastal systems:

1) highlands runoff into lowlands = (% runoff from highlands) ('highlands rain) (highlands area) = 6.99E+11 m3/yr;
(6.99E+11 m3/yr) (I10-Xikg/mr) (4940 J/kg) = 3.45E+18 J/yr;

2) lowlands runoff into coastal systems = (lowlands runoff) (lowlands rain) (lowlands area) = 6.83E+10 m'/yr;
(6.83E+10 m3/yr) ,0, 0kg,"m') (1000 J.,kgj = U.UtLb E+1 J/yr;

Solar energy = (3.45E+18 J/yr + 0.68E+18 J/yr) (48500 sej/J) = 1.71E+23 sej/Ar

4. PlJ,,sical stream energy estimated as the sum of 1) -.ur'face water runoff from highlands into lowlands and 2) direct
precipitation on lowlands not evapotranspirated:

Solar emergy = (highlands + lowlands runoffT (avg. elev. drop of lowlands drainage area) (gravitational force)
(density of water) = [6.99E+11 m3 + 0.68 m3j (150 m elevational change) (9.8 m/s2) (1000 kg/m') = 1.13E+18 J/yr;
(1.13E+18 J/yr) (27900 sej/J) = 3.14E+22 sejiyr


geopotential energy due to rain runoff for the highlands. A% erage annual rainfall for this region is 3.73 m
(van der Leeden 1985). Evapotranspiration rates (ET) were estimated to be around 30% of incident rain;
runoff was considered to be that which is not evaporated or transpired (100 - %ET = 72%).

The lowlands represent the remaining 44% of the land area with an average elevation of 150 m (the mean
height between sea level and 300 m), including the coastal waters out to the edge of the continental shelf.
Lowlands have lower cloud coverage, greater solar insolation, lower rainfall, more winds and less steep
slopes yielding greater evapotranspiration rates and lower runoff rates. An average of 1.20 m of precipitation
falls annually on the lowlands and surrounding coastal waters (PNG Info. Booklet 1986). Evapotranspiration
and runoff rates were considered inverse of those in the highlands.

From these regional analyses, it is clear that a vast majority of the emergy delivered from annual rains is due
to climatic conditions, ecological cover and physiographic relief unique to the highlands. Nearly all of the
gravitational potential in rainwater across the country's topography is due to highland conditions. About 98%
of the 730E+20 sej/yr is contributed from actions of highlands rains (Table A-4). In contrast, much of rain's
chemical potential energy is derived from lowland i egetati'. e cover, higher temperatures and winds which
drive photosynthesis and transpiration (almost 60% of the 427E+20 sej/yr in transpired rain is delivered from
lowland and coastal areas).

The chemical and physical energies in rivers were also estimated based on volume of runoff from the
two regions' 1) the volume of surface water runoff leaving the highlands which is concentrated in river
channels and flows into the lowlands, and 2) the volume of runoff into coastal systems due to the direct
rainfall on the lowlands which is not evapotranspired. The chemical potential emergy in river flow was
estimated 1708E+20 sej/yr; the physical stream emergy was estimated at 314E+20 scij/r. This regional
analysis brings into perspective the large energy contributions due to prevailing conditions of the
environment in these two regions of the mainland. Further, it is apparent that although the highlands receive
greater rainfall, most is runoff and collected in stream channels entering the lowlands, so that much of its
potential is directed downstream toward the receiving systems below.

In an attempt to investigate issues of resource allocation, demographic and socioeconomic conditions were
attributed to each region. Two-thirds of the country's population was considered rural highlands (Bell 1986)
or roughly 2.3 million people, with 1.2 million inhabitants in the lowlands and along the coast. It was


assumed that a quarter of the imported goods and services reached the highlands; the lowlands being the more
urban area with its large port cities. Solar emergy flows for both regions are summarized in Figure A-3. The
total solar emergy base for the highlands was estimated at just over 1000E+20 sej/yr. Lowlands solar emergy
base totalled 2500E+20 sej/yr, over twice that of the highlands. Using this scenario, per capital emergy-use in
the lowlands was over 4 times as great as per capita-use in the highlands. This regional analysis identifies the
importance of highlands rain, forest cover and stream network to the country's renewable resource base.


Papua New Guinea has large resource rescr\ cs, including forest biomass. organic matter in soil, metal ores
and fossil hydro-carbon reserves. Estimates of solar emergy were made for all known major reserves (Table
A-5). Solar emergy of rainforest reserves were calculated using a solar transformity for standing forest
biomass derived in the subsystems analysis of forest operations in New Britain (see Table B-1). Coastal
plain swamps were evaluated using a solar transformity derived from subsystems analh sis of sago palm (see
footnotes to Figure B-2). Other solar transformities are drawn from independent studies and cited as
footnotes. All storages are expressed in billion macro-economic dollars, by dividing the solar emergy stored
in a resource reserve by 2E+12 sej/$ US, the emerg. dollarr index for the United States in 1987 (Odum 1988).
This was done in order to relate real value based on past environmental production of existing reserves. As
defined in the methods section, macro-economic value refers to the total amount of dollar flow that could be
generated by use of a resource. By expressing solar emergy in macro-economic dollars, potential
contributions to Papua New Guinea's total, combined economy are made relative to international markets.

Based on energy content and wood density values for rainforest biomass derived from Brown and Lugo
(1984) and standing crop estimates of PNG's different forest types (Davidson 1983), estimates of stored solar
emergy were made. Lowland rainforests, the largest area of forest cover type (about 20 million ha), had the
largest biomass storage of solar emergy (item 1, Table A-5), about 6.5E+24 sej.


Total Inputs into Highlands:

--- 1022 x 10 sej/yr

Fo' " ion Total Inputs Into Lowlands:

S40 20
208 2513 x 10 sej/yr


Figure A-3. Systems diagram relating solar emergy flows associated with highlands and lowlands
regions of Papua New Guinea. Calculations for pathway values are given as footnotes to
Table A-4.


Table A-5. Storage of solar energy in resoruce reserves within Papua New Guinea.
Calculations for basic data given as footnotes to this table.

Storage Solar Macro-economic
Note Indigenous quantity emergy') valueb)
reserves (J, g) (sej) (billion US $, 1988)

1 Lowland rainforest 1.62E+20 J 6.46E+24 3228
2 Lower montane forest 1.04E+20 J 4.17E+24 2085
3 Alpine/montane forest 9.48E+18 J 3.80E+23 190
4 Coastal plains swamps 5.88E+17 J 7.44E+22 39
5 Mangroves 7.10E+18 J 1.04E+18 52
6 Regrowth and gardens 2.95E+18 J 5.60E+22 28
7 Soil organic matter 6.65E+18 J 4.15E+23 208
8 Copper ore 6.24E+12 g 2.81E+23 140
9 Gold 9.72E+09 g 4.86E+20 < 1
10 Oil 2.95E+18 J 1.56E+23 78
11 Natural gas 1.10E+19 J 5.29E+23 265

total macro-economic value of resource reserves: 6.3 trillion US $, 1988.

a) Solar emergy derived using solar transformilies given below.
b) Solar emergy divided by solar emnrgy,' index for U.S. in 1988 (2 x 10" sej/$) to give perspective of
value on international markets.


Footnotes toTable A-5.

1 Lowland tropical rainforest; area of forest cover = 19.9E+6 ha (McIntosh 1974), biomass = 405.4 ton/ha (Broun and
Lugo 1'~S-); energy content = 4.78 kcal/g (E.P. Odum 1971); solar transformity = 40,000 sej/J (for derivation see Table
B-1): (19 4'E-rb ha) (405.4. t/ha) (1E+6 g/ton) (4.78 kcal/g) (4186 J/kcal) = 1.62E+20 J; (1.62E+20 J) (40000 sej/J) =
6.46E+24 sej

2 Lower montane forest; 9.1E+6 ha (MNclrntoh 1974), 572.6 t/ha (Brown and Lugo 1984): (9.1 E+6 ha) (572.6 t/ha) (1E+6
g/t) (4.78 kcal/g) (4186 J/kcal) = 1 .U4E+2J J; (1.04E+20 J) (40000 sej/J) = 4.17E+24 sej

3 Montane and alpine forest; 1.2E+6 ha (McIntosh 1974), 394.9 t/ha (Brown and Lugo 1984): (1.2E+6 ha) (394.9 t/ha)
(1E+6 g/t) (4.78 kcal/g) (4186 J/kcjlh = 9.48E+18 J; (9.48E+18 J) (4u0() sej/J) = 3 80E-23 sej

4 Sago palm and woodland swamps; 3.5E+6 ha (McIntosh 19741. 4.012 kcal/ha (Ulijaszek and Poraituk 1983); solar
:ransfo.rmii> = 131600 -_j/JJ (for derivation see footnotes to Figure B-2): (3.5E+6 ha) (135 trunks/ha) (74.3 kg/trunks)
(400 kcal/U.I kg) (4186 J/kca ) = 5.88E+17 J; (5.88E+17 J) (131600 sL'J'JI = 7.74E+22 sej

5 MNagruves. 4.5E+6 ha (McIntosh 19744); 1E+4 g/m2 (Snedaker 1986), energy content 3.77 kcal/g: (4.5E+6 ha) (10000
m2/ha) (1E+4 g/m2) (3.77 kcal/g) (4186 J/kcal) = 7. IUE+1 J; (7.10E+18 J) (14700 SLj/J i = 1 04E+23 sej

6 Regrowth and gardens; 2.4E+b ha (MklnroA h 1974)., 4.2 kcal/g (Odum et al 19.'13): (2.4E+6 ha) (10000 m%/ha) (7000
g/m2) (4.2 k'c alg) (4186 J/kcal) = 2.95E+18 J; (2.95E+18 J) (19000 sej/J) = 5.60E+22 sej

7 Organic matter in soil; est. 7000 g/m2, 10% ,rganrik matter content: (4.2E+7 ha) (10000 m2/ha) (7000 g/m') (0.1) (5.4
kcal/g) (4186 J/kcal) = 6.65E+18 J; (6.652E+18 J) (62500 ojj/I = 4 15E+23 sej

8 Copper ore; estimates 950 million tons i.Parigun.i Mine, 0.4% Cu coriterL') + 350 million tons (Ok Tedi Mine, 0.7%)
(PNG Info. Bk. ] $4-l = 6.25E+6 tons: (6.25E+6 t) (I 0E+n g/t) = 6.25Et12 g; (,.25E+12 g) (4.5E+10 sej/g) =
2.81E+23 sej

9 Gold; estimate 34E+6 tons, (Ok Tedi Mine, 286g/t purity) (PNG Info. Bk. 1984): (3.4E+7 t) (286 g/t) = 9.72E+9 g;
:.9 72E+9 g) (5.0E+10 sej/J) = 4 86E+20 sej

10 Oil reserves = 345 mbbI oil + 137 mbbl condensate (Qureshi et al 198S): (482E+6 bbl) (5.8E+6 Btu/bbl) (1055 J/Btu) =
2.95E+1,S J; 2.95E+18 J) (53000 scy'i = 1.56E+23 sej

11 Natural gas; estimate 10 millionn cu ft (Qureshi et al 1,Q88y (10E+12 cu ft) (2 832E 02 m'!cu ft) (3.89E+7 J/m3) =
1.102E+19 J; (1.IO2Et19 J) (48000 sej/J) = 5.29E+23 sej


Referring back to Table A-1, only about 0.04E+24 sej of forest products including fuelwood was harvested in
1988. This lowland rainforest emergy expressed as macro-economic contributions, was estimated to be
worth 3.2 trillion dollars, roughly half of all solar energy stored in major reserves in PNG. Lower montane
forests are the next largest emergy storage with over 9 million ha and over 2E+12 sej stored in standing
biomass (Table A-5, item 2). Coastal plain swamps and mangroves together represent about 90E+9 US$ in

Other biotic reserves of include regrow\th and gardens and organic matter stored in forest soils, together worth
almost 250 billion macro-economic dollars (items 6 and 7). The two largest mining companies in Papua New
Guinea, Panguna and Ok Tedi, have an estimated 140 billion macro-dollars in copper reserves (item 8).
Known gold reserves represent insignificant contributions of solar emergy. Known, potential and possible
hydrocarbon reserves, while relatively small (oil and natural gas store 340 billion US$), may be significantly
larger if future explorations meet current discoveries (Dow 1977 and Hapgood 1989).

Together, all major reserves store over 6 trillion US$ in macro-economic value within Papua New Guinea.
The macro-economic value of these resource reserves is almost 2500 times greater than the current national
product of 2.54 billion US$. Further, 90% of all reserves are forest biomass, based on renewable energy
sources of sunlight and rainfall. These resource reserves will play important and expanding roles in the
country's future economy. In chapter 3-F of this report, we make a preliminary estimate of the solar emergy
of stored genetic and cultural information in PNG nationals, representing the convergence of past
environmental work into high quality information storage. The large solar emergy stored in these resource
and information reserves illustrates the abundant %eahlih not only in annual production but in sa% ings as well.
By recognizing real value of all contributing sources, not simply those with market value, a new perspective is
gained which identifies Papua New Guinea as a resource wealthy counir) with great amounts of solar emergy
delivered mostly free from home sources and stored in indigenous reserves. These values will be compared
with those of other countries as concluding remarks to this report in order to draw perspectives relative to
other rural and developed nations.


Section B: Subsystems Analyses of Major Rural Production Systems

by S.J. Doherty

In this section, three indigenous production ss stems are evaluated for net N field and return on investments
using measures of solar emergy. These systems are: 1) a lowland rainforest logging operation on the island
of New Britain; 2) sago palm cultivation in the Gulf Province; and 3) sweet potato production in a typical
highlands village. Each one will be introduced briefly, accompanied by a systems diagram with calculations
footnoted. Sources from both the environment and any purchased resources derived outside the system were
evaluated. Ratios of net yield and investment as described in the methods section of this report are calculated
for each production sector. Solar transformities calculated for each product was then used in the national
overview analysis (Section A) in order to estimate as accurately as possible the contributions due to major
production sectors. Finally an estimate of environmental support area is given for each sector which
demonstrates the role of Papua New Guinea's rich renewable resource base in supporting its people and their


Overview of Forest Resources

For many thousands of years the forests of Papua New Guinea have been the primary renewable resource for
its people, providing building materials, fuels, food, medicine and gardening plots. The commercial
exploitation of forests began after World War II. Eighty-five percent of the country's land area is tree-
covered, and one-third is considered accessible commercial forest K ing et al 1982). Other valuations are
lower; Galenson et al (1982) estimated that one million hectares (2 percent of the land area) were under
allocation for exploitation and another 6 million hectares are of known and possible potential. The
discrepancy in figures is largely due to the debate over accessibility of forest products and variable
assessments of timber grade. Davidson (1984) reports that although PNG has the highest forest/land area
ratio of all the Indo-Pacific nations, it has a low percentage of operable forest area due to difficulty of the


The forests of Papua New Guinea are broken into major ecotypes Table A-5, along with emergy valuations of
standing reserves based on solar transformities determined from these subsystem analyses. The major
forestry operations have been in lowland rainforests which cover the greatest land area. Much of the country
is difficult to access owing to extensive swamps and steep slopes. What is accessible is of a mixed variety
hardwood type with generally low economic returns on investment (McIntosh 1974, Tickell per. comm.
1990). Some 200 timber species have economic potential (Komtagarea 1979), but presently only a few
account for the bulk of merchantable timber. The island of New Britain is the major forest industry area of
PNG (Perry 1985), but the largest individual clear felling project has been the Gogol/JANT project in the
valleys south of Madang Province.

The Office of Forests (1977) developed an inventory of known, possible and potential forest development
areas based on difficulty of access, suitability of terrain to clear felling operations and risk assessment.
Important ecological variables such as biomass produatiL ity, stability, evapotranspiration rates and water
quality have not been included in the inventory. These known and possible areas of forestry potential along
with the major timber operations existing in 1977 are gi% en in Figure B-I. Most of the marketable timber
comes from a few select species such as Pomctiai spp., Eucalvptis spp., Agathis spp., and Araucaria spp. in
the higher elevations. Because of the high diversity of low-grade timber, the steep slopes, high rainfall
(average 2500-3500 mm annually), the remoteness of much of the resource, and the division of land tenure,
the rainforests of much of Papua New Guinea's landscape are afforded, at least temporarily, some protection--
if by nothing more than aggravation.

Emergy Analysis of Forestry in New Britain

Data for forestry operating expenses (fuel, machinery, road materials, labor) and estimates of forest biomass
(total organic matter, stemwood biomass, annual production) were derived from the literature and synthesized
with known values supplied by industry (Tickell per. comm. 1990). The evaluation was made for a 20,000 ha
operation in lowland rainforests of New Britain. Table B-I lists all resource flows in raw input units per ton
wood product and as solar emergy (sej/ton). All calculations are given as footnotes to the table. An overview
diagram is gi ven in Figure B-2 summarizing all solar emergy flows for forest production.


.Phii l pines
Mlas- Papuad
)i Ne w Guinea
Areas f orest types low , mid in e n wh t y
cllan Coreal <:= t' 'dmh ind . ns 0t
< Ocean Pacifeic
\ sAustralia Ocean
e, New s

14 1440 147 5' 0 153� 156-

Figure B-1. Map of Papua New Guinea showing its forests of known and possible development potential (redrawn from Baldwin et al 1978).
Areas of forest types (lowland, montane, alpine, coastal plains and mangroves) are reported in Table A-5 with the emergy
calculations of forest biomass reserves. Note the high development potential on the island of New Britain.

Table B-1. Resource flows supporting rainforest logging in New Britain, Papua New Guinea. All
values are given per ton of harvestable wood.

Resource Solar Solar
Note Item inputs transformity emergy
(J, g, $/ton) (sej/J) (sej/ton)

1 environmental energy 4.40E+10 J 1.82E+04 8,00E+14
2 fuels 2.70E+08 J 5.30E+04 1.43E+13
3 oil 6.77E+07 J 6.80E+04 4.61E+12
4 machinery 11.20 $ 2.00E+12 2.24E+13
5 other equipment 1.28 $ 2.00E+12 2.55E+12
6 road construction 3.20E+06 g 1.50E+06 4.80E+12
7 labor 4.57$ 4.80E+13 2.19E+14
8 miscellaneous costs 12.10 $ 2.00E+12 2.42E+13

Standing crop biomass 2.00E+10 J (a) 8.00E+14
Harvested yield 4.32E+09 J (b) 1.09E+15

(a) Solar transformity of standing biomass: 40000 sej/J
(b) Solar transformity of harvested wood: 253000 sej/J

Net yield ratio of harvested wood: 4.19
Investment ratio of harvested wood: 0.33

Footnotes to Table B-1.

Energy content of rainforest wood: 4.78 kcal/g (4186 J/kcal) = 2 00E+t- J/g
%% oud density: 8.00E+5 g/m'

Estimate of standing crop of lowland rainforest biomass , 1 ickill per. comm. 1990):
min 120 m'/ha, max 250 im/hd, 185 m'/ha avg.
extractable, usable volume = 40 rnm/h. = 22 % of avg volume
(40m'/ha) (0.8E+6 g/m3) = 145 tons/ha i,21:i-4 J/g) = 2.9oE+12 J/ha

total standing crop on 20,000 ha: (185 m'/ha) (0.8 t/m3) (2Uii)0 ha) = 2.'E+u6 tons
total energy: (2.96E+6 t) (2E+4 J/g) = 5.92E+16 J

Annual yield
premium qualtiy: (1500 m3/mo) .0 8E+5 t/m') (12 mo/yr) = 14400 tons/yr (2E+4 J/g) = 2.88E+14 J/yr
construction quality: i35.iJ m'/ino) (U SEtb g/m') (12 mo/yr) = 33600 tons/yr (2E+4 J/g) = 6.72E+14 J/yr
total volume harvested: 48000 tons/yr
total uen-Tgy in harvest: 9.60E+14 J/yr


Table B-1 footnotes, continued.

Percent of total harvested armuLhIll (annual harvest, 48000 tons/yr) / (total standing crop, 2 9vE+ 6 tons) = 2 %
Average area cleared annually: 324 ha/yr
Lifetime of project: 62 yrs

1. Transpired rain, chemical potential: land area = 10000 m'/ha; annual rainfall = 80 in; runoff = 28%; evapotranspiration =
72; (72%) (80 in) (.0254 m/in) (lJ00 m2) (1000 kg/mn) (4940 J/kg) = 7.23E+10 J/ha/yr; (7.23E+10 J/ha/yr) (18200
sej/l) = 1.32E+15 sej/ha/yr

Total rdanf.JI supporting total standing crop: estimated time to grow forest (200t/ha, max voume) = 90 yrs (based on
simulation of forest land rotation model, section C); (90 yrs) (1.32E+15 sej/ha/yr) = 1.19E+17 sej;

sej per ton standing crop: (1.19E+17 sej) (148 t/ha, average) (20,000 ha, total project area) = 8.00E+14 sej/ton

sej per ton harvested: (8.00E+14 sej/ton) (22% estractable) = 3.70E+15 sej/ton

2. Fuel used: 30000 liters/mo; (30000 liters/mo) (energy content 3 60E+07 J/l) (12 mo/yr) = 1.30E+13 J/mo (53000 sej/J)
= 6.87E+17 sej/yr;

sej per ton: (6.87E+17 sej/yr) / (48000 tons/yr harvested) = 1.43E+13 sej/ton

3. Oil, lubricants, etc. (3500 kina/month) / (0.93 k/$) 1 (0.50 $Ihlnr) = (7527 1/mo) energyy content, 3.60E+07 J/l) (12 mo/yr)
= 3 25E+ 12 J/mo (6S0u.I sej/J) = 2.21E+17 sej/:,r,

sej per ton: (2.21E+17 sej/yr) / (48000 tons/yr harvested) = 4.61E+12 sej/ton

4. Machinery: (capital outlay, 2.00E+06 kina) (estimated lifetime, 4 yrs) / (0.93 k/$) = 5.38E+5 $/yr (U.S. sej/$ index,
'2 oE+12 sej/S)= 1 I 08E-t s Sj/,r.

sej per ton: (1 tISE+ 1 sej/yr) / (48000 tons/yr harvested) = 2.24E+13 sej/ton

5. Other equipment: (5 70E-iJ5 kina) (est. lifeurnei, 10 yrs) / (0.93 k/S) = b.13Eo4-1 $/yr (2.i)lE+12 sej/US $)= 1 23E+17

sej per ton: (1.23E+17 sej.'yr) / (i48(.10 tuns/.,,r harvested) = 2.55E+12 sej!IIon

6. Road construction: (length, 4 km) (width, 6 m) = 22000 m2 surface area:
gravel: (800 m/lmo) (est. rock density 2.W00Eato g/m3) (12 mo/yr) = 1.54E+11 g/yr (est. solar transformity using
concrete, 1.50E+06 se.ggI = 2.30E+17 sej/yr:

sej per ton: (2.30E+17 sej/yr) / (48000 tons/yr harvested) = 4.80E+12 sej/ton

7. Labor:
nationals, 8000 kina/mo / .0.93 k/$) (12 mo/yr) = 1.03E+05 $/yr;
expatriates, 9000 kina/mo / (0.93 k/$) (12 mo/yr) = 1.16E+05 $/yr
total labor costs = 2.19E+05 $/yr (4.80E+13 sej/$, P,, table A-2) = 1.05E+19 iej/r,

sej per ton: (1 U5E+ I~ sej/yr) / (48000 tons/yr hav'cstd) = 2.19E+14 sej/ton

8. Miscellaneous costs = 45t0 0O kina/mo / (0.93 k/$) (12 mo/yr) = 5.S I E-45 $/yr (2 00E+12 sej/ US $) = 1.16E+18 sej/yr;

sej per ton: (1.16E+18 sej/yr) / (48000 tons/yr hIrc<-stc*a = 2.42E+13


Figure B-2. Systems diagram of biomass production and cutting in lowland rainforests in New Britain.
All pathway values are 1012 sej/Ion Values correspond to those in Table B-1 with
accompanying footnotes and citations.


Transpired rainfall was used to estimate environmental emergy supporting forest growth and maintenance.
Rainfall in New Britain averages 80 inches (2000 mm) annually. Using the forest land rotation model
(Section 3-C of this report), it was estimated that about 90 years would be required to reach a mature steady
state forest, averaging 148 tons of stemwood biomass per hectare. Using a wood density estimate for tropical
woods of 0.8 tons/m3, this represents 185 m'/ha. As described in the previous paragraphs, although there is a
high volume of Ibrest biomass (range 120 m3 to 250 m3 per hectare, mean 185 mn/ha), the exportable volume
of lumber and construction quality stemwood was estimated to be 40 m3/ha (32 tons), or about 22% of total

Using this information, a solar transformity for total biomass standing in forest was calculated as 40,000
sej/J [Table B-I, item (a)]. This is the same order of magnitude as other tropical wood (Odum et al 1986,
Keitt 1991) though this Iransformiti does not include societal goods and services required to extract and
process it. Once the wood has been harvested, the solar transformity increases to 253,000 sej/J (item b).
Solar transformities for temperate wood products are generally much lower. For instance, harvested spruce
and pine in Sweden had solar transformities of about 10,000 sej/J (Doherty et al 1991). The higher values for
tropical woods are due in part to two factors: 1) high environmental emergy per unit product and 2) a greater
diversity of structure in complex rainforests. This greater complexity yields much of material that is not
targeted for exploitation and structure that is wasted in the process of extracting marketable timber. This is
certainly the case in Papua New Guinea where, because of the difficult terrain and diverse mix of forest
species, much of the standing forest biomass is wasted when forests are clearcut.

A net yield ratio of just over 4 to 1 suggests that forest products deliver a net benefit to Papua New Guinea's
combined economy, though the net yields are not as high as previous studies of other tropical regions have
reported. An investment ratio of 0.3 similarly demonstrates that nature is contributing 3 times as much solar
emergy as that invested from the main economy for forest development projects. Using 40.000 sej/J for
standing forest biomass, the rainforests of Papua New Guinea were estimated to store as much as 14E+24 sej
with a macro-economic value of 5.5 trillion dollars (refer to Table A-5, items 1, 2 and 3 summing lowland
rainforests, montane and alpine forests). Of course, this value is an estimate for all restt biomass, not just
export quality stemwood. The question of whether these forest products should be used by PNG nationals or
sold overseas for needed revenues will be discussed in the concluding sections of this report



Sago palm woodlands along the coastal plains of Southern Papua New Guinea cover an estimated 3.5 million
hectares (Davidson 1983). Traditionally sago palm has been either harvested through progressive clearings
from natural woodlands or cultivated under limited management by local villagers for building materials and
other resources. Although some plantations exist, sago palm is still considered a local resource and is not
targeted for export (Pernetta and Hill 1984). Coastal plains woodlands are vast wetlands receiving large
amounts of environmental resources in the form of surface water runoff from the highlands. Direct rainfall is
tN pically lower than in the highlands and solar insolation is greater than a erage due to lower cloud coverage.

A subs� steins anal) sis for sago palm cultivation was conducted using data drawn from a comprehensive
study in Papua New Guinea's Gulf Province by Ulijaszek and Poraituk (1983). Values for productivity
ranged from 7 mature trunks/ha per annum for subsistence gathering of uncultivated woodlands to 330
trunks/ha/yr from plantations under intensive management. A mean production of 135 trunks/ha taken
annually under village management was considered a sustainable harvest. This value was used in the
following analysis. Palm trunk weight (74 kg.'trunk) and energy content (4000 kal 'kg1 and estimates of
village labor (133 hrs/106 kcal dry sago palm) were drawn from Ulijasiek and Poraituk (1983). Rainfall was
estimated as the average for the country (2.62 m).

The solar emergy supporting labor was calculated two ways: 1) using a transformi\ for human metabolism
calculated in Section F (Table F-1, item 2) and 2) using a measure of solar emergy per capital calculated from
the national analysis (Section A, Table A-3, item 16). The average of these two calculations was used to
estimate solar emergy supporting labor. The ecological support area for labor was estimated following
methods for calculating carn ing capacity for economic investments described in the Methods Section of this
report. Simply, the percent of the country's total emergy budget that was locally renewable ([R/U = 86%];
Table A-3, item 8) was used as to determine how much village labor was supported by the local environment.

Solar emergy values are shown in Figure B-3 with corresponding calculations given as footnotes to the
summary diagram A solar transformity for harvested sago palm was determined at 131,600 sej/J.


188 x 10 J/ha-yr

x 10 iseJ/ha yr

Solar transformity = 131,600 sej/J
Net yield ratio = 8
Investment ratio = 0.15

Figure B-3. Aggregated systems diagram of sago palm cultivation in the Gulf Province of Papua New
Guinea. All pathway values are 10"1 sej/ha/yr for sustainable production.

footnotes to Figure B-3
Sago palm yield = (135 trunks/ha/yr) (74.3 kg/trunk) (400 kcal/O.1 kg) (4186 J/kcal) = 1.68E+11 J/ha/yr

Chemical rain = (2.62 m/yr) (10000 m2/ha) (1000 kg/m3) (4940 J/kg i = 1.29E+11 J/ha/yr; (1.29E+11 J/ha/yr) (18200 sej/J) =
2.36E+15 sej/ha/yr

Labor estimated using average of two calculations:
(133 hrs labor/I E +6 kcal dry sago palm) (4.0122E+7 kcal SP/ha/yr production) (2927 kcal/day food intake) / (24 hrs/day)
(4186 J/kcal) = 2.724 E+9 J/ha/yr; (2.724E+9 J/hyr.)(6.7E+6 sej/J; Table F-1, item 2) = 18.25E+15 sej/ha/yr
(133 hrs labor/lE+6 kcal dry sago palm) (4.0122E+7 kcal SP/ha/yr production) = 5336 hrs/yr; (5336 hrs/yr) / (8736
hrs/yr) = 61% of annual activity; U/person = 34.7E+15 sej/per (Table A-3, item 16); (0.61) (34.7E+15 sej/per) =
21.2E+15 sej/ha/yr
average = [(18.25 + 21.2)/2] E+15 sej/ha/yr = 19.7E+15 sej/ha/yr

Environmental support for labor, [10als.n] = R/U = 86% (Table A-3, item 8); 0.86,) (19.7E+15 sej/ha/yr) = 16.9E+15 sej/haTyr
Outside village support for labor, [F(tabor)] = 1 -R/U = 14%; (0.14) (19.7E+15 sej/ha/yr) = 2.8E+15 sej/ha/yr

I = total ecosystem emergy = rain + I(labor) = (2.36 +16.9) E+15 sej/ha!yT = 19.3E+15 sej/ha/yr
F = total support outside village = F(labor) = 2 8E+ 15 sej/ha/yr
Y = total solar energy input = I + F = 22.1E+15 sej/ha/yr

Net yield ratio = Y/F = 8:1
Investment ratio = F/I = 0.15
Solar transformity = (22.1E+15 sej/ha/yr) / (1.68E+11 J/ha/yr) = 131600 sej /J

Renewable cnmergy density for country [R/ha] = [R - (waves, tides)] / (area of PNG) = (712E+20 sej/yr) / (46.2E+6 ha) =
1.54E+15 sej/ha
Ecological support area = I(labor) / (R/ha) = (16.9 E+15 sej/ha/yr) / (1.54E+15 seji/a/yr) = 11


This value is of similar magnitude of other agricultural crops in tropical regions (2E+5 sej/J). A net energy
yield ratio of 8:1 and an investment ratio of 0.15 suggest the importance of environmental sources in sago
palm cultivation. Most other agro-forest operations yield much lower returns on investment [compare for
c\ample harvested lowland rainforest wood at 4:1 (Table B-l)]. An ecological support area of 11 ha for each
hectare of sago palm further demonstrates the role of the environment in rural production of indigenous crops.


Although not native to Papua New Guinea, the sweet potato or yam (lpomea batatas) has quantitatively been
the most important food crop in subsistence agriculture (Kimber 1972). As of 1985, sweet potato production
was worth an estimated K200 million per year (0.22 trillion US $) (Bourke 1985). No other single crop,
including exports crops, contributes as much to the national economy. Over 100,000 ha of sweet potato are
planted throughout the country. As well as being a major subsistence crop, sweet potato is now an important
cash crop with over 450,000 tons produced per annum. The role of the sweet potato in village life has been
widely reported through ethnographic and agronomic studies (Rappaport 1968; Malynicz 1971; Kimber
1972; Bourke 1977; Grossman 1984 among many others). The principle products are cooked tubers for
human consumption and raw tubers, vines and leaves used as pig feed.

In this overview analysis, 22.4 tons/ha of sweet potato produced annually was used as an average production
(from Grossman 1984 and Bourke 1985). Purchased inputs included fertilizers as well as goods and services
support ing \ village labor. About 30% of a villager's time was estimated spent tending sweet potato gardens
(2770 hrs/yr). This value was determined as the average of two activities studies in Papua New Guinea
villages (Lea 1970 and Grossman 1984). Solar emergy basis for labor and its ecological support area were
determined using the methods given in the 'subs% stems anal sis of sago palm.

Solar emergy flows are summarized in Figure B-4 with accompanying calculations given as footnotes. A
solar transformity of 52,100 sej/J was calculated for sweet potato. A net emery yield ratio of 12:1


J/ha - yr

Solar transformity = 52,100 sej/J
Net yield ratio = 12
Investment ratio = 0.14

Figure B-4. Aggregated systems diagram of sweet potato production in a typical highland village. All
pathway values are 10'5 sej/ha/yr for average production.

Footnotes to Figure B-4.
Sweet potato yield = (22.4 tons/ha/yr) (1E+6 g/t) (2.77 kcal/g) (4186 J/kcal) = 2.59E+11 Ih-a/yr

Chcniicl rain = (2.62 m/yr) i.1l)(i0j m2/ha) (1000 kg/m3) (4940 J/kg) = 1 29E-- 11 J/ha/yr; (1 29E+11 J/!h./rl (18200 sej/J) =
2 3 E+15 sej/ha/yr

Nitrogen fertilizer = (100 kghla/;, r. (1000 g/kg) (0.82) (0.1) (2170 J/g) = 1.7SE+7 J/ha/yr; (1.78E+7 J/ha&yr) (1.69E+6 sej/J) =
301E+13 sej/haUr,
Potash = (100 kg/ha/yr) (1000 g/kg) (0.53) (702 J/g) = 3.72E+7 Jihayr. (3 72E+7 J/ha/yr) (2.62E+6 sej/J) = 9.75E+13
Phosphorus = (50 kg/ha/)T) (1000 g/kg) (0.33) (0.1) (348 J/g) = 5.74E+5 J/h.l.yr: (5.74E+5 J/lha/yr) (4.14 EB+7 sej/J) =
2.38E+13 scj/,hayr;
total fertilizer input = 0.15E+15 sej/haiyr

Village labor = 2768 hrs/ha/yr (Lea 1970 and Grossman 19S4): (2768 hrshlia/>r)/(8736 hrs/yr) = 32% of annual activity;
(U/persun) = 34.7E+15 sej/person (Table A-3, item 16); (0.32) (34.7E+15 sej/pr) = ll.OE+15 sej/ha/yr
Environmental support for labor, [1.itil.cJ = R/U = 86% (Table A-3, item 8); (0.86) (1l.OE+15 sej/yr) = 9.45E+15
Outside village support for labor, [F(labor)] = 1 -R/U = 1 - 0.86 = 0,14; (0.14) (ll.0E+15 sej/yr) = 1.54E+15 se./ha/yr

I = total ecosystem emergy = chemical rain + I(labor) = (2.36 + 9.45) E+15 sej/ha/yr = 11.81E+15 sej/hrd/r
F = total support outside k illige = fertilizers + F(labor) = (0.15 + 1.54) E+15 sej/ha/yr = 1.69E+15 sejta/'.r
Y = total solar emergy input = I + F = (11.81 + 1.69) E+15 sej/ha/yv = 13.5E+15 sej/ha!yr

Net yield ratio = Y/F = 12:1
Investment ratio = F/I = 0.14
Solar transformity = (13.5E+15 sej/ha/yr) / (2.59E+11 J/ha/yr) = 52100 sej/J

Ecological support area = I(labor) / (R/ha) = (9.45E+15 sej/ha/yr) / (1 54E+15 sej/ha/yr) = 6.1


suggests a greater return on labor and investment than either rainforest wood or sago palm production. More
than seven times as much solar emergy is contributed from environmental sources than from outside goods
and services delivered outside the village as illustrated by an investment ratio of 0.14. An ecological support
area of 6 ha means that six hectares of surrounding environment is required or "used" by villagers indirectly
in support of one hectare of sweet potato gardens

In each of these studies, as well as the analysis of tourism (Section D), it is clear that resources from
surrounding areas are needed to support not only production or proposed development, but the people
themselves. In fact, it is this "ecological support area" that determines the large net yields for rural
production systems. It is therefore unreasonable to assume that much of the country could be opened
for development since a large portion of it is required for support of rural production systems, the people and
their lifestyles. Further, cash crops and tourist activities generally draw emergy away from local production
systems because, as shown in Section A, the revenues cannot purchase an equivalent amount of solar emergy
as was sold to overseas buyers These issues will be further explored in the Recommendations and
Conclusions Section of this report.


Section C: Rainforest-Land Rotation Model

by S.J. Doherty


Large scale clear-fell logging operations in the tropical lowland rainforests of Papua New Guinea began in
1973 with the Gogol/JANT timber project This operation has since cleared all of its 68,140 hectares at an
annual cutting rate of 3-4000 hectare per annum (Seddon 1984). Eighty-seven percent of the cleared areas
have naturally reverted to secondary rcgrowih and grasslands, while only 4800 hectares (13%) have been
actively reforested (Qureshi et al 1988). A study of the site indicates that primary and secondary trees
account for only 15 and 1 percent, respectively, of the abandoned clear-fell area (Saulei 1984). Further, most
of the regrowth was achieved by coppicing from old tree stumps and germination of the stored seed bank in
the soil. There is little indication of seed dispersal from adjacent forests (Saulei 1984).

At the time of this research, forestry stalT indicated that the government had put a halt on all forestry projects
until a thorough assessment of the costs (including land, forest products, and money lost overseas) incurred
from the Gogol Valley project is complete. Due to problems of slope, heavy rains, and increased runoff with
land clearings. forestry) projects are met with limited success in most parts of Papua New Guinea. A better
understanding of the role of forest seed reserves left in place to aid secondary succession through
recolonization of forest species and the multiplicative effects from clearcuts of increasing size are sought to
alleviate some of the problems of the past. As an initial inquiry into the problems with forestry in lowland
rainforest areas of difficult terrain, a computer simulation model was developed to explore the relationships
between forest production, harvest rates and the rotation of lands between forested and unforested states.


A theoretical model of timber extraction and the resulting patterns of landscape disturbance is presented
which addresses some of the problems caused by large scale clear-culling and raw resource extraction in
lowland rainforests. The model, shown in Figure C-1, rotates land area between three


Figure C-1. Energy systems diagram of the rainforest-land rotation model Variables (k1) are pathway coefficients; their mathematical
expressions are given in Table C-1 and explained in the text.


25 50 75 100 125 150

Output of modcl simulation of rainforest growth and net primary production over 150 years. A mature steady state forest
(NPP= 0) takes 143 years.


7.5 .

5.0 Z





Figure C-2.

conditions: 1) native forest [F] (though mostly second growth). 2) cleared land [C] immediately following
harvest; and 3) degraded land [D] which results from both the scale of clearcuts as well as erosion of exposed
top soil from the run off of heavy rains. The percentage of land that is forested [F] is directly proportional to
amount of forest biomass [B] present. Forest biomass changes as a function of its own mass, respiration, and
the environmental inputs which drive production as well as the rate of land returning to forest.

The systems diagram is a visual expression of the mathematics which determine the flows and storage within
the model. A set of calibrated values for initial storage and flows were determined for steady state forest
production (Table C-1). Data were synthesized from Saulei (1984), Brown and Lugo (1984), Odum (1971)
and Vitousek et al (1971). A mature tropical lowland rainforest was estimated to have a standing crop of 380
tons/ha (item 2, Table C-1) and an a% cra�e annual gross production of 42 tons/ha/yr [20,000 kcal/m2/yr]
(item 6). These values were calibrated to determine transfer coefficients (k) for each pathway and rates of
change for state variables when the model is simulated (items 5-12). A computer program written in BASIC
is listed in Table C-2. In this program are the mathematical expressions that represent pathways and rate
equations that represent changes in state variables.

The environmental energy driving forest production was considered the amount of incident rain that is
transpired. This is a flow-limited source; only a given amount of rain is available during any given time
period (3.73 m/year). Thus forest production is limited if all incident rain is transpired [initial capture was
estimated as 60% of incoming rainfall for a mature forest; see Table C-1 (1)]. The more biomass that is
present the greater the percentage of incoming rain that is transpired, and less is runoff. Notice that some
pathways are connected to state variables by a small rectangular box. This symbol, called a sensor, indicates
that the state variable changes in proportion to the flow or storage where the symbol is located, but does not
directly draw from that flow or storage. In the example of degraded land [D], cleared land [C] becomes
degraded as a function of the amount of runoff [R] -- the greater the amount of rain that is unused and
ninoffs, the greater the rate at which rcLently cleared land becomes degraded


Table C-1. Calibration of variables and coefficients for Rainforest-Land Rotation Model
(RF ver_2.BAS) corresponding to systems diagram in Figure C-1.

1 Total incident energy inflows (JO):
a. Energy used by system (kO*R*B):
b. Available energy, unused (R):


E+9 J/ha/yr
E+9 J/ha/yr

State variables:

2 B = Forest biomass (380 tons/ha):

3 Land quality types:
a. F = Forested land =
b. C = Recently cleared land =
c. D = Degraded land =

4 Mangement switch: H = Harvest

Flow equations (E+12 J/ha/year):

5 Available incident energy
6 Average annual production
7 Annual harvest
8 Forested land that is cleared
9 Cleared land that is degraded
10 Cleared land returning to forest
11 Degraded land returning to forest
12 Forest metabolism

7.603 E+12 J/ha

1 ha
1 ha
1 ha

1 = begin cutting
0 = stop cutting

R = JO/(1 + kU*B*F) =
kl*R*B*F =
k2*B*H =
k3*F*(k2*B*H) =
K4*C*R =
k5*C*B2 =
kb*D*B =
k7*B =


FooiLteCs to Table C-1

1 Chemical potential energy in transpired rainfall:
annual rainfall = 3.73 nm/yr; evapotranpiration = 60 %; runoff (100 - %ET) = 40 %

Total energy coming in (JO): (3.73 m) (10,000 m2) (1000 kg/m3) (4940 J/kg) = 1.8426E+11

b. Incident energy used by forest system = evapotranspired rain (k04 R*B) = (% ET) (JO) = 1.1056E+11 J/ha/yr
c. Available energ., unsed = runoff [remainder (R)] = JO / (1 + kO*B) = (% rnuff (JO) = 73704E+10 J/ha/yr

2 Energy in forest biomass [(B) after 143 years of growth; (36 yrs to reach 50% of steady state storage]:

Organic matter in stemwood biomass = 380 tons/ha (Brown and Lugo 1984);

Caloric content per unit mass = 4.78 kcal/g (E.P. Odum 1971)
(380 tons OM/ha) (1E+6 g/ton) (4.78 kcal/g) (4186 J/kcal) = 7.603E+12 J/ha


kO =
kl =
k3 =
k6 =
k7 =


Footnotes to Table C-1, continued.

3 Rotational lands: At steady state calibration, each land cover type occupied 1 ha (1/3 total area).

4 Harvest (H) is a management switch that is turned on (1) or off (0) to initiate or stop forest cutting based on extent of
forested land available.

5 Available incident energy = unused chemical energy from rainfall (i.e., runoff); see lb.

6 Annual production (GPP = kl*R'B) = 20,000 kcal/m2/yr, Viluusck 1971):

(2.OE+4 kcal/m2/vr) (10,000 ms/ha) (4186 J/kcal) = 8 372E+11 Jiha/yr = 41.84 tons OM/ha/yr

7 Annual harvest (k2*B*H) considered 50% of annual production at steady state:

(0 837E+12 J/ha/yr) (501 ) = 0.4185E+12 J/ha/yr cut (21 icns/ha/yr)
then, (0.- 18 5E+12 J/ha/yr) / (7.603E+12 J/ha mature forest biomass) = 5.51 .

8 Forested land cleared [k3 'F* k2*Bl H.] = constant percent of harvested biomass: 5.51% (F)= 0.055 ha/yr

9 Cleared land that is degraded t4 * C * R) = 50q;

10 Cleared land returned to forested land (k5*C*B') = 50%; (0.0551 ha) (50%) = 0.0275 ha/yr

11 Degraded lands returning to forested lands (k6*D*B) = 50%

12 Annual forest metabolism (Respiration + Death = k7*B):

NPP = GPP - Respiiation; at steady state NPP = 0, therefore GPP = Respiration:
kl*R*B*F = k7*B

Forest turnover time: (forest biomass) / (annual production) =

(7.603E-12 J/ha) / (0.837E+12 J/ha/yr) = 9.08 years = 11.0 % annual replacement


Table C-2. BASIC computer program used in simulation of Rainforest-Land Rotation Model.

REM filename: RF ver 2.BAS
REM PNG Rainforest - Land Rotation Simulation Model
CLS 'Clears monitor for new simulation
REM Opens output file to store data for graphic analysis:
REM Sets coordinates of graph for monitor display:
SCREEN 1, 1: COLOR 0, 1
REM Colors are defined at end of LINE and PSET statements as:
REM 1 = blue; 2 = purple; 3 = white
LINE (0, 0)-(300, 180), 3, B
LINE (0, 100)-(300, 100), 3, B
LINE (0, 45)-(300, 45), 3, B
REM Initial values:
I= 1
REM Management switches:
CUT = 2.9
GROW = 1
H= 1
REM Scaling factors:
FO =25
CO = 25
DO = 25
BO = .25
YO = 60
TO= 1
REM Inputs (chemical potential energy driving gross production):
JO = .18426
REM Initial Storages:
B = .76
F=I; C=l;: D=1
REM Transfer coefficients:
kO = .197291
kl = 1.494009
k2 = .055057
k3 = .131527
k4 = .373502
k5 = .000476
k6 =.003621
k7 =.110114
REM Sets X,Y coordinates for monitor display:
PSET (T / TO, 45 - Y * YO), 1 ' Yield (Y) is displayed in top graph
PSET (T / TO, 100 - B / BO), 2 ' Biomass is graphed second from top
PSET (T / TO, 170 - C * CO), 3 ' Cleared land is displayed in lower graph
PSET (T / TO, 160 - D * DO), I ' Degraded land is displayed in lower graph


Table C-2, continued.

110 REM Management alternatives:
111 IF F > CUT THEN H = 1 ' Begin harvesting
112 IF F < GROW THEN H = 0 ' Stop harvesting, allow forest recovery
120 REM Mathematical model:
121 R= JO / (1 +kO*B*F)
122 Y = k2 * B * H
123 Ytot = Ytot + Y
130 REM Difference equations:
131 DB = (kl * R * B * F) - (k2 * B * H) - (k7 * B)
132 DF = (k5 * C * B A 2) + (k6 * D *B) - (k3 * F * k2 * B * H)
133 DC = (k3 * F* k2 * B * H) - (k4* C* R) - (k5* C * B A 2)
134 DD=(k4*C*R)-(k6*D*B)
140 REM Rate equations:
141 B = B + DB
142 F = F + DF
143 C = C + DC
144 D = D + DD
145 T = T + I
150 REM Prints data to output file identified in line 20 of program:
151 PRINT #1, T, Y, B, C, D
200 REM Subroutine 1: Loop counter to simulate model for 300 years:
210 'LOCATE 15, 1
211 'PRINT "NPP="; 'PRINT USING ####.###"; ((kI * R * B * F) - (k7 * B))
220 IF T / TO < 300 GOTO 100
221 GOTO 400
300 REM Subroutine 2: Loop counter to determine which management alternative
301 REM results in maximum total yield (Ytot) over 300 year rotation:
302 REM Note: must disable lines 200-221for subroutine 2 to work.
310 REM Sets X,Y coordinates for monitor display
311 REM (Total biomass harvested as a function of forest rotation):
312 PSET (GROW*GROWO, 180 -Ytot / YtoIO), 1
320 REM Simulate total yield under different harvest and fallow requirements:
322 IF GROW < 3 THEN GROW = GROW + 0.05
323 IF GROW >= 3 THEN GOTO 400
330 REM Reset initiation values:
331 T = 1
332 Ytot = 0
340 GOTO 60
400 END


The amount of forested land available for reseeding acts as a control over the rate of biomass production.
Here, biomass [B] is increased proportionally to the change in forested land [F] as indicated by the pathway
expression kRBF. This is a measure of gross primary production (GPP). For initial calibration, the model
was set at steady state for a mature rainforest. At steady state, there is no net primary production (NPP), and
forest respiration (R, defined as forest metabolism and death) was calculated to equal gross primary
production [(kB) = (klRBF)].

As an approximation of the effects of spatial scale of land clearings on seed dispersal from forest biomass, a
sensor was put on the biomass variable which controls the rate at which cleared and degraded lands return to
forest. If there is too little land left as seed refugia, the successional ability of forest clearings is slowed by
lack of seed reserves. Cleared land, however, can be cycled back to forest as a square function of the biomass
because of its limited scale (k5CB2). As more of the forest is cut, more land becomes cleared and
consequently more land becomes degraded. The rate at which cleared land becomes degraded [D] is a
function of the amount of cleared land [C] and amount of runoff [R] due to low forest cover--thus the
pathway expression k4CR. The gravity model suggests that communication (in this case genetic dispersal by
seeds) is a phenomenon of the squared distance between two objects (Forman and Godron 1987). Once land
has become degraded it is more difficult for secondary succession to regenerate forest. Therefore degraded
land only cycles back to forest as a simple multiplier interaction with biomass as a control (k6CB). Finally,
cutting of forest biomass is activated with a switch [H], representing goods and services, that is either on (1)
or off (0). Thus a certain percentage of forest biomass is harvested as a function of the transfer coefficient k2.

In the initial calibration, forests were cut at a rate equal to 50% of average annual production or about 5% of
mature forest biomass at steady state [Table C-1 (7)]. This value was chosen as it closely approximates the
harvest schedule of Gogol/JANT. Each of three land conditions were given equal area (1 ha each, totalling 3
ha) for model calibration. Since the model tracks biomass on a per hectare basis, the results of the model can
be interpreted per hectare. Thus, each land type can be considered to represent a percentage of the total (i.e.,
1 = 33% of land total). Management switches, therefore, rotate forest land between values of 0 and 3 (0%
and 100%). Next, a few outcomes of model simulation are given to illustrate trends and forecast predictions,
followed by some simple management recommendations based on insights gained from the model.



First, only the forest production and metabolism components of the model were run in order to determine
forest maturation and turnover times. Based on 3.73 meters of incident rainfall driving an average gross
primary production (GPP) of 42 tons/ha,' r, about 140 years is required for the system to develop a mature
forest of 380 tons OM/ha (Figure C-2). Maximum net primary production (NPP) was measured at 34 years
(9.4 tons OM/ha/yr). At a mature steady state gross production is balanced with forest respiration and net
production equals zero. These calibrations suggest that this forest system has an annual replacement rate of
about 10% (Table C-I).

State variables and production processes are calibrated in energy units (J/ha for biomass storage and J/ha/yr
for production and harvest yields). Therefore in order to express model outputs on a volume basis, the values
must be converted using an energy content of 4.78 keal/g (20000 J/g) and the estimate for biomass volume
(380 tons OM/ha). These conversions are gi\ en in Table C-1 and discussed in the text.

The next step was to simulate the model using all state variables, i.e. incorporating the rotation of land
storage with forest production and harN esting schedules. Forest harvesting is started and stopped with a
switch (H) in the program, based on management alternatives which are input by the user. Two variables
determine the harvesting schedule: CUT and GROW (lines 110-112). The forest is allowed to grow until its
land area reaches a value set by the variable cuT, at which time harvesting begins until the forested area is
below a value set by variable GROW (lines 50-53). Input values range between 0 and 3 (0% and 100% of land
area as explained in the methods).

A management period of 300 years was chosen in order to simulate long-term trends based on forest growth,
harvest schedules and land rotations. Thus, annual changes in forest production, harvest volumes and land
cover are re-calculated each time the program loop is executed for 300 iterations subroutinee 1). This
simulation period allows a natural forest to complete two full successional cycles of growth (143 years to
mat ural ion') and the biomass to turn over more than 20 times, as well as adequate time to observe trends from
harvest schedules and land rotations.


In the example in Figure C-3, the rainforest was allowed to grow until it reached 57% (curr = 1.7) of the total
land area. Harvesting then began until the amount of forested land was reduced to 30% (GROW = 0.9), at
which time cutting is stopped and the cleared and degraded lands begin to recover to forest. This
management schedule resulted in a rotation of about 60 years. Forest biomass (middle graph) recovers
quickly as secondary growth is most rapid in early stages of succession. Before net production begins to
decline as the forest matures toward steady state, the forested land is again harvested when it has recovered
57% of the land in rotation. Lands rotate between forested, cleared and degraded states (lower graph--
forested land is not shown as it changes in direct proportion to forest biomass). Harvest yields (upper graph)
are greatest at initial cutting when biomass is highest, and declines in volume as the return per unit harvesting
effort increases. In this example, yields range between 5 and 7 tons/ha/year, on average with a total yield of
870 tons/ha over 300 years.

In a series of computer runs, the minimum amount of forest land required before harvesting was discontinued
was held constant (i.e., GROW = 0.9; 30%) while the extent of recovered forest land required before
harvesting could begin again (i.e., CUT) was changed by increments of 0.05 (approximately 2% change in
total land cover). The harvest schedule described above (and shown in Figure C-3), rotating forested land
between 30 and 57%, was determined to yield the greatest volume output over the 300 year simulation period,
without degrading forest lands to an unrecoverable extent.

Figure C-4 shows the results of this simulation, changing both the harvest times and recovery times (given as
subroutine 2 in program). Here the total yield over 300 years is calculated based on extent of forest land
necessary before harvesting can begin as well as the minimum extent at which time harvesting is stopped.
Forest yields are reduced as a function of the extent of forest land required by management for a particular
rotation schedule. It appears that maintaining forest land extent between about 60% (before cutting begins)
and 30% (when cutting stops) yields the greatest volume of biomass while still allowing the land enough time
and resources to recover to forest.



Simulation of biomass yield (upper graph), rainforest growth (middle), and land rotations (lower) based on 57/30 harvest
schedule over 300 year management scenario (start curling when forest land reaches 57% of total land area; Stop cutting when
forest land reaches 30%).

Figure C-3.


800 / A % Forest land before
,,/ / harvest begins [CUT]
S\ /\ s7
,o. 6 00 \ ,\

� %- \ 72

& 400


0 10 20 30 40 50 60 70 80 90 100
% Minimum forest land [ R ow]

Figure C-4. Simulation of total harvest yields over 300 years (Y-axis) due to changes in minimum and maximum allowable land rotations.
X-axis is the minimum amount of forest land allowed before cutting is stopped [GROWl. Graphed are results based on forest
land requirements of 30%, 57%, and 72% necessary before cutting is again started [ctr].


The rainforest-land rotation model presented here simulates forest production and recovery based on
harvest schedules and rotation of land between forested and two states of post-clearcut lands. It makes
an attempt at accounting for conditions of increased runoff from forest cover removal compounded by
high rainfall and mountainous terrain. Forest operations in Papua New Guinea have faced these adverse
conditions with limited success in the past (Saulei 1984 and Seddon 1984). It is shown that previously
forested lands can quickly degrade and that degraded land is slow to recover. Further, the ability of cleared
lands to reforest is not a simple linear function of available forest seed reserves; harvest schedules, recovery
times, proximate forest reserves, and spatial extent of clearcuts, among others, all contribute to successful
and sustainable forest management practices. The model illustrates some of these principles. If for example,
har\ testing began before the forest had recovered, cleared lands became degraded and land could no longer
recover. Also if the forest is not cut before the forest begins to mature and net production declines, total yield
also declines.

A question not addressed with this model is "what is the optimum harvesting schedule not only for
maximizing yield but minimizing investment" -- i.e., optimizing effort. Forest plantations are generally
managed on rotations that cut the forest when it is at its maximum net production (the inflection point in
Figure C-2; 34 years). In fact the rotation schedules determined by this model to maximize yields include this
interval. Further, forest trees could be harvested in small quantities but at very rapid intervals so that the
effect is an almost continual thinning program. This combination, hocw evr, would not reduce investment
inputs but rather increase them, diminishing the net return on investment.

An evaluation of solar energy supporting forest production as well as the solar emergy in required economic
investments may provide the information needed to determine net yield and investment ratios for forest
schedules. The subsystems analysis of forest operations in New Britain (Section B) found that 3 times as
much solar energy is contributed from environmental sources than from the main economy in rainforest
harvests, providing a net yield on investments of about 4 to 1 (Table B-1). In New Britain, annual harvests
were estimated to be about 2% of standing crop--a rate slower than reported by Gogol/JANT and slower than
the 5% cutting rate used in this model.


These questions of net return and investment should be addressed as a next step of model development, using
solar emergy as a baseline unit of measure. As in the past, rainforests, their services and products, will
continue to play important roles in the quality of life of nationals and the sustainable development of their
resource base. This was demonstrated in calculation of macro-economic values for forest reserves (Table A-
5) and in the 4:1 net yield ratio determined for forest operations in New Britain. The few general
recommendations that are given here are based on energetic, temporal and spatial considerations. This model
of forest-land rotation is presented as an exercise to investigate some of the problems forest operations are
faced within diverse rainforest si semns on diflicult terrain and to begin considering han testing schedules that
are appropriate for a given set of site conditions. Management goals ultimately should pertain to more than
just resource output yields and begin to ensure the full range of ecologic values and functions remain intact.


Section D: Emergy Basis for Determining the Carrying Capacity of Tourism

by Mark T. Brown and Richard C. Murphy


With the recently increased emphasis placed on tourism and on attracting economic investment for tourism
development by many governments around the world, some hard questions are beginning to emerge. Is
tourist development the cn% ironmentally benign industry it is touted to be? Is tourist development beneficial
to local cultures and economies? Is tourist development a form of sustainable development that should be
encouraged in developing economies of the world?

This portion of the study investigates the relationship of outside investment, in general, and tourism
development, in particular, to cultural and environmental integrity, and to local economies, regional welfare,
and international balance of payments. Using data from tourism development in New Britain, Papua New
Guinea and a related study in Nayarit, Mexico, and techniques of energy analysis, several questions related
to economic development are addressed: (1) What is the carrying capacity for outside economic investment
within local, undeveloped regions that is environmentally and culturally benign and economically beneficial?
(2) What are the benefits and costs of differing intensities of development? (3) W\\hat intensity of economic
development is most beneficial to the economy and welfare of populations?

Ecotourism and Intensity of Economic Investment

Recently. ecotourism (Laarman and Durst 1987, Boo 1989) has been coined to mean a variety of things, but
primarily to mean tourism that has an ecological imperative. Ecotourism should not only seek to expose
tourists to the environment of a region, but should also be balanced with the local environment and not cause
cultural degradation or serious economic shifts. There is much in the literature documenting the
consequences of large development projects on the culture, environment, and economy of relatively
"underdeveloped" regions (e.g., Archer and Sadler 1976; Archer 1985; Burn 1975; Caribbean Tourism
Research Center 1976, 1977 a, b; Cohen 1978; Edelman 1975 a, b; Jenkins 1982; Oliver-Smith et al. 1989;
Rodenburg 1980). Some of the documented impacts are as follows:


Cross-cultural contacts result in changes in traditional dress, habits, values, ethics, and social

Local economies become more externalized as wages are paid to populations who never used
money before and who have to import goods and resources to purchase.

Additional strain is placed on the environment to provide food, building materials, and other
services like waste recycling, which result in loss of environmental value and capacity for
support of the population.

Local control of resources like land and water is lost as the result of their sale to foreign

In all, the larger the development and its intensity, the greater the potential for negative impacts on culture,
environment, and economy (Jenkins 1982, Rodenburg 1980). Thus, ecotourism that seeks to expose the
traveler to a natural environment without regard to the effect a visitor's presence has on that environment may
not be sustainable in the long run. To be truly an ecotourist development, it should neither exceed the
carrying capacity of the local environment and culture, nor cause secondary or tertiary environmental

Tourism as an Extractive Industry

Economic investments in undeveloped regions of the world are, for the most part, investments in extractive
enterprises. The investments are used to assemble the technology and pay the human labor necessary to
extract resources and sell them for more than the costs of extraction. In a way, tourist development is an
extractive enterprise. The resources are more varied: sun, wind, waves, and scenic vistas, as well as an
unspoiled environment and a dissimilar culture. Unlike other extractive industry, the tourist industry does not
cut, dig, or catch its resource and thereby exhaust the reserve. Yet with over-exploitation, the tourist resource
is "used up" (Maihicson and Wall 1982). Too many tourists translates into loss of environmental quality and
shifting of the local culture away from traditional elements that were of interest, toward the values, customs,
and fads of the outside culture.

The question regarding outside investment and its sustainability is: how much is too much? At certain levels
of investment and for certain resources, the extracted resource may last indefinitely because it is renewed at a
rate that is equivalent to or less than the rate at which it is extracted. Under these circumstances the
development is often described as sustainable. As in other types of extractive investments, tourism


dc clopment has an appropriate intensity of investment at which it will not exceed the ability of the local
environment and culture to absorb it (Edelman 1975a,b; Gunn and Jafari 1980). Determining the appropriate
intensity of development that does not cause negative cultural, economic, or ecologic impacts is what is meant
by determining the economic carrn ing capacity of an external investment.

The Benefits and Costs of Economic Investments

For many years, economic investments in undeveloped and developing regions have been considered
beneficial to the local economy. The increased number of jobs and higher wages were cited as proof of the
positive benefits of investment. For the most part, it has long been believed that the bigger the project, the
greater the benefit to the local economy, since bigger always translated into more jobs and greater payrolls.
In fact, the opposite in many cases was true. Large projects often displaced local populations, disordered the
environment, and disrupted the local economic system. Smaller projects, scaled to the local economy and
social organization, were better integrated into the cconoms and caused less social and environmental
disruption (Jenkins 1982, Lichty and Steinnes 1982, Rodenburg 1980).

It appears that an economic investment from outside can either act to amplify existing social and ecologic
order and stimulate the local economy, or it can act as a disrupt ive force, much like a disaster. In fact,
"economic earthquake" might be a fitting way of describing what happens to local, small-scale economies and
social organization when large-scale investments occur. The greater the differences in intensity between
existing systems and imposed developments, the more disaster-like they become.

The Disappearing Benefits of Economic Investments

Experience has shown that some economic investments have not yielded the benefits to local economies that
were anticipated (Oliver-Smith et al. 1989). This results from several different but complementary factors:
First, investments from outside must be repaid. Considering current interest rates and the emergy trade
advantage enjoyed by most developed nations over undeveloped nations, investing nations receive far more
from their investments than just repayment of principle and interest (Odum 1984, Odum et al. 1986, Odum
and Arding 1991). The undeveloped nation finds that more national wealth flows out of their economy than
flows in as the result of an unfavorable emergy exchange ratio. Second, if the investment is from sources
outside the region, little of the currency generated by it remains %w within the local economy (Oliver-Smith et al.


1989). Other than a local payroll and some user taxes, if a development project uses funds from elsewhere
and is foreign owned, most of the currency generated is "drawn" back outside the region as profit and debt
service. Third, the currency that is added to the local economy causes local inflation (Oliver-Smith et al.
1989). When more money "chases" the same amount of resources, prices rise.

Unaccountable Costs of Economic Investments

Impact analyses aimed at determining costs and benefits often fail to properly account for costs, especially
social and environmental costs (Archer 1985, Bum 1975, Cohen 1983, Pigram 1980, Wang et al. 1980).
When economic benefit/cost accounting is used, the benefits are easily quantified using a monetary system of
value, but social and environmental costs, since they are outside the monied economy, are often not included
because they are not easily or reliably quantified in monetary units. The resulting picture of economic
benefits is one-sided, showing increased numbers of people employed and money flowing through the
economy, but not including increased costs of social disorder, or loss of environmental systems or services.

Impacts of Economic Investments

Emergy analysis may offer a more complete perspective of the impacts of economic investments on the
ecological and cultural resources of regions. A systems perspective of a region suggests that its ecological,
economic, and cultural systems are closely inter-twined. As a region's economic system changes, for
example, there are resulting changes in its ecological and cultural systems, as the increased economic activity
affects a wider and wider spatial area and may cause changes in values and ethics. The extent of change in
each of these systems is more or less dependent on the extent of change in the other. Figure D- illustrates
the interconnections between environmental, cultural, and economic systems of regions. A balanced and well-
adapted subsistence economy might have the organization depicted in Figure D-la. Ecological resources are
extracted by the economic system, converted to goods, and consumed by cultural components which, in turn,
provide the necessary organizational structure and "manpower" for the economic system. By-products of the
economic system are recycled back to the environment, and information and "good stewardship" are fed back
from culture. The driving forces are renewable emergies shown coming from the left side of the diagram and
the nonrenewable emergy storage from % within The overall system that develops (i.e., the levels of
ecological productivity, economic activity, and cultural organizations is, to a large degree. dependent on the
magnitude of renewable emergy flow and the nonrenewable storage that are available.


Economic investment from outside can be depicted like that in the bottom diagram (Figure D-lb).
Investment dollars are used to purchase fuels, goods, and services from outside the local economy. A second
outside energy source now influences the system. As a result of the connections between components of the
regional system, any increase in one compartment affects the other two compartments (whether they increase
or decrease depends on the nature of the interconnections and is not necessarily important at this point). The
bigger the influence of outside investment (that is, the bigger the magnitude of the flows coming from the top
right compared to the flows coming from the left), the greater the impact. The emergy analysis technique
utilized in this study quantitatively evaluates the relative size of both of these driving energy flows in a
regional economy, and suggests that the appropriate intensity of a new economic investment is one that does
not alter their relative proportion significantly (Odum 1980).

The secondary impact of economic investments is also illustrated in Figure D-lb. Economic investments
from outside are made as a means of financing enterprises that either directly extract natural resources (e.g.,
wood, minerals, fuels, or fish) and sell them to outside markets, or to develop enterprises for the conversion
of resources within the local economy (hydroelectric projects or tourist developments). In either case, the
"attracted" investments carry with them a significant debt that must be repaid and which is financed through
the export and sale of resources. The net benefit of investments from outside to the local economy, then,
becomes a matter of determining the balance between what is purchased with the investment, and the
resources that are exported over the long term. Additional insight related to the net benefit from investment
is gained using emergy analysis.

One of the basic principles of the emergy systems perspective is that true wealth comes from resources, not
from money (Odum and Arding 1991). Money can be used to purchase resources, but the moneN in itself is
not representative of wealth. E\ aluating international trade and net benefit from investments using only the
inflows and outflows of currency often shows a monetary balance of payments, but does not take into account
the inflows and outflows of wealth. Often, the investing economy receives double benefit--the resources
extracted directly. and the resources that must be extracted and sold by the developing economy in order to
pay interest on outside loans. Most developing economies seek money from outside sources instead of
seeking resources (the true basis of wealth), and thus often sell their wealth cheaply to purchase economic
goods that have less effect t in stimulating their economy and that do not lead to a sustainable future.


Figure D-1. Systems diagram of a regional economy having no trade with external markets (top) and
an economy that has developed trade (bottom). Money is shown as dashed lines, and
energy and information flows as solid lines. While invested money may circulate within
the economic system, eventually, like income from exports, it is used to purchase goods
and services from external economies.


A Theoretical Approach to Determining Carry ing Capacity of Local Environments

One theory for determining carr, ing capacity is that the scale or intensity of development' in relation to
existing conditions may be critical in predicting its effect and ultimately its sustainability (Odum 1980, Odum
and Arding 1991). If a development's intensity is much greater than that which is characteristic of the
surrounding landscape, the development has greater capacity to disrupt existing social, economic, and
ecologic patterns (Brown 1980, Odum 1980). If it is similar in intensity it is more easily integrated into
existing patterns. For example, because of the differences between a hea% ilv urbanized area and an
undeveloped wilderness area, the appropriate intensity of development in each environment is much different.

Large-scale developments and those N ith greater intensity than the surroundings can be integrated into the
local economy and environment if there is sufficient regional area to balance their effects. Much like the
ecological concept of carrying capacity, where differing environments require different aerial extent of
photosynthetic production for support of a given biomass of animals, environmental carrying capacity for
economic investments depends on the area of "support" over which a development can be integrated. As the
intensity of development increases (and therefore its consumption of resources, requirement for laborers, and
environmental impacts increase), the area of natural, undeveloped environment required for its support must
increase. All other things being equal, the more intense a development, the greater the area of environment
necessary to balance it. Thus, the spacing between developments should increase as their intensity increases.

The methodology described in this report uses emergy analysis to measure intensity of two tourist resorts and
the local environment, and then uses a ratio of purchased emergy to resident renewable emergy as a means of
determining carrying capacity. The theoretical construct and primary assumption is that this ratio is, in itself,
a measure of the intensity of the local economnN, based on how the environmental and cultural systems are
adapted to the level of economic activity present. This is complicated when the local economy is in a state of
flux, to which neither the ecological nor cultural systems have adapted or reached a balanced steady-state
Our rationale for using the current regional intensity of economic activity (the Environmental Loading Ratio)
is that, if a new development is significantly greater in intensity than the surroundings, even if a balance has

' Inlcnst) ma\ be measured using any quantity (energy, materials, money, or information) per unit time per unit
area. If one uses energy per unit time, or power, expressed over a unit area, ihe intensity is power density (Brown


not been reached, it may further exacerbate the existing problems of cultural and ecological integration of


Systems Diagrams

Figure D-2 is a systems diagram of a region that includes, among other activities, tourism. Tourism is shown
drawing on resources of the local economy and importing resources from outside. The region is shown as
being driven by two main sources of outside emergy: (1) free, renewable emergies, and (2) purchased
emergies (sometimes referred to as nonrenewable since they are based on resources that are nonrenewable).
Inflowing renewable energies combine and interact to drive the productive processes in ecological systems.
Purchased inputs from outside develop systems of extraction and consumption internally, which interact with
indigenous environmental resources to provide resources, emergies and products for use and export. Money
derived from exported resources and from visiting tourists is used to purchase goods and fuels from other

As with any tourist facility or tourist region, there is an image maintained by the combined interaction of the
environment, urban structure, culture. and the development itself. Image is the information that "draws"
people from outside to visit the development The greater the image, the greater the draw. Image is
negatively affected by increased wastes in the environment (pollution), overcrowding, and loss of resources,
including culture, that form the image of a region or development.

Resources are extracted or harvested from marine and terrestrial systems and sold to the local economy or to
the tourist facility. Money paid by tourists for imported goods, fuels, services, and locally derived resources
enters the local economy before exiting the region in quantities equal to the inflows. Increased spending by
tourists drives inflation up if inflows of local and imported resources and fuels are not increased.

A simplified systems diagram of the main driving energies and internal processes of a tourist resort facility is
given in Figure D-3. As in the regional diagram (Figure D-2), image plays a central role in "attracting"
tourists. The regional image is augmented by the attributes of the resort facility including beach, grounds and
landscaping, and assets (or hotel structure and furnishings) The main production function of the hotel


Figure D-2. Energy systems diagram of a region showing the relationship of tourism with the
local economy. Often tourism is a competitive system. competing with the local economy for
goods and resources. Dashed lines are money and solid lines are energy flows.

provides goods and services for tourists by combining potable water, food and liquor, fuels, electricity, goods
and materials, and labor. The assets and tourists are also part of the production function. Money income
from tourists is used to pay for all of the above goods and services, shown as the dashed lines accompanying
each purchased flow of energy. The diagram in Figure D-3 is the diagram from which the emergy analysis of
tourism in Papua New Guinea and Mexico (Brown et al. 1992) were performed.

Emergy Analysis of National Economies

Summary statistics and indices of Papua New Guinea, Mexico and the USA are given in Table D-1. Total
emergy-use (U) varies from a low of 1213 E+20 sej/yr (PNG) to a high of 87,570 E+20 sej/yr (USA). Gross
national product (GNP) varies by 3 orders of magnitude. with PNG having a GNP of only 0.005% of the
USA. Probably the most telling relationships are the various ratios (E-I). The relation between emerg) and
money (sej / $), a measure of relative buying power, shows that the USA has the lowest ratio. Thus when US
dollars are used to purchase goods and services from PNG or Mexico, the benefit to the US economy is 18.5
to 1 and about 1.5 to 1, respectively. The USA has the highest emergy density --3.6 times that of PNG and
about 2.7 times that of Mexico Emergy per capital in the USA and PNG are similar, but result from different
supporting resources. The main emergies driving the PNG economy are inflows of renewable resources
(about 85%) of the economy while nonrenewable resources are the dominant sources of emergy of the US
economy (about 75%).

Total cmcrgx -usec per capital in the USA and PNG is nearly equal. The world emergy exchange ratio, which is
a relative measure of world buying power (or trading advantage), shows that the USA has the highest trade
advantage; it receives, on the average, 1.5 units of emergy for each unit of emergy exported. Mexico's ratio
suggests it receives roughly equal emergy imported for each unit exported, PNG has, on the average, a net
loss receiving only 0.08 units of emergy for each unit exported (an average trade deficit of 13 to 1). The
highest environmental loading is in the USA; it is 30 times that characteristic of the PNG economy.

Emergy Analysis of Tourism

Tables D-2 and D-3 give the results of the emergy analysis of a small, high quality tourist resort on the island
of New Britain, PNG, and a "four-star" tourist hotel in Puerto Vallarta, Mexico. The facilities are as different


Figure D-3. A detailed systems diagram of a tourist facility showing the main production function that provides goods and services from the
tourists who are anracted by the resort's image. Dashed lines are money and solid lines are resource flows.

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