PREFACE


	This monograph, is a compendium of the individual works of 
seventeen students enrolled in a newly cross-listed course NR 545 (EIH 
575). The focus of this course, like prior years, is captured in its 
title Population-Environment Dynamics: Toward building a Theory.  The 
course began with an examination of alternative theoretical constructs 
useful in studying the interaction between human populations and the 
environment. Also, at the beginning of the course, each participant was 
asked to select a topic of inquiry and a geographical setting for their 
study. This selection then became their major focus for the entire semester.
Students participating formally in the course this fall had a delightful 
mixture of backgrounds and interests. Schools and colleges represented 
included the School of Natural Resources and Environment, School of 
Public Health, School of Business Administration, College of  
Engineering, College of Architecture and Urban Planning, and College of 
Literature Sciences and Arts. One undergraduate, fourteen masters and 
four Ph D students participated formally.  Others sat in from time to 
time, including participants from previous years seminars. Disciplines 
represented included biology, economics, sociology, architecture, 
anthropology, mathematics, law, engineering, urban planning, public 
health, forestry and natural resources. Participants included colleagues 
from the Continents of North America, Europe, Asia, and Africa.  In 
addition, several U. S. students had spent considerable time living and 
working in countries such as Russia, Benin, Costa Rica, India, Thailand 
and Nepal.
A very important element in the seminar was the use of data sources which 
recently have become available in machine-readable form. These data 
sources permitted the students to quickly gain exposure in handling 
longitudinal datasets, especially those which were not amenable to 
modeling with linear functions.  As a consequence, part of the course 
required mastery of non-linear curve fitting techniques.  The most useful 
and user friendly dataset provided participants was The World Resources 
Institute Data System (1994-95).  Another tool used in the course was 
state-of-the-art PC-based Geographic Information Systems. The GIS package 
selected as most helpful, was ATLAS GIS version 3.0.  The digital maps, 
used as separators of monograph chapters, help to unify monograph content 
as they depict, taken together, a spatial view of population-environment 
dynamics. New to this term was the availability of the Digital Chart of 
the World.  Dr. Sandra Lach Arlinghaus, adjunct professor in The School 
of Natural Resources and Environment, provided instruction in curve 
fitting, GIS and ongoing individualized support to all participants. 
A new feature of this terms course was the use of  outside reviewers. 
These reviewers, all faculty in major teaching institutions, provided an 
additional level of academic feedback to participants. Papers included in 
this monograph had completed this review process by the time of 
publication. Remaining papers will be published at a later date.
The success of the course resulted largely from the enthusiasm of the 
participants. As in previous years, extra sessions were held near the end 
of the semester, which often extended beyond scheduled meeting times. 
Feedback from fellow participants was provided in these sessions. In 
addition, each student was asked to develop a brief synopsis of how their 
study related to the other participants in the class. These thoughtful 
remarks are presented as the main body of the concluding chapter.  This 
monograph was published during the winter term in the academic year 1995-96.



								             
William D. Drake
								          
University of Michigan
								           
Ann Arbor, Michigan
`								              
February 1996
 INTRODUCTION
This volume is a collection of separate but related studies focusing on 
the relationship between human populations and the environment. The 
effort consists of this introduction followed by seventeen chapters each 
written by a seminar participant which investigates a different aspect 
and geographic setting of the population-environment dynamic. A 
concluding chapter provides comments written by each participant relating 
their work to those of the others. 
In this introduction we present a synopsis of the common framework, which 
we call a family of transitions. In addition to the common framework, 
this introductory chapter presents the abstracts for each ensuing chapter.
Readers of the monograph reporting last year's work should note that the 
material in the following section on a family of transitions is repeated 
here for background and therefore can be skipped.

1.    A FAMILY OF TRANSITIONS 
One way of viewing the complex dynamic relationships between population 
and the environment is to visualize them as a family of transitions. That 
is, not only is there a demographic and epidemiologic transition but also 
a deforestation, toxicity, agricultural, energy and urbanization 
transition as well as many others. In this chapter it is argued that for 
each transition there is a critical period when society is especially 
vulnerable. During that period, rates of change are high, societal 
adaptive capacity is limited, in part, due to this rapid change, and 
there is a greater likelihood that key relationships in the dynamic 
become severely imbalanced. The trajectory society takes through a 
transition varies, depending upon many factors operating at local and 
national levels. Transitions not only are occurring in many different 
sectors but also at different scales, both temporal and spatial. At 
times, a society experiences several transitions simultaneously, which 
can raise social vulnerability because of how they amplify each other.

1.1 TYPES OF TRANSITIONS
The Demographic Transition
Let us begin with a review of the ideas behind the widely accepted 
demographic transition. At the onset of this transition, births and 
deaths are both high and are in relative equilibrium with each other. 
Historically, births exceed deaths by small amounts so total population 
rises only very gradually. Occasionally, famine or an epidemic causes a 
downturn in total population but in general, changes in rates are low.  
During the transition, however, death rates drop dramatically, usually 
due to a change in the health condition of the population. This change in 
health is caused by many, often interrelating factors. After some time 
lag, the birth rate begins to drop and generally declines until it is in 
approximate balance with the death rate again.

The Epidemiological Transition
The term epidemiologic transition was coined to describe the changing 
source of mortality and morbidity from infectious diseases occurring 
primarily in the younger age groups to degenerative diseases in older age 
groups.  As with the demographic transition, there is considerable 
volatility during the transition.  At the onset, infectious diseases 
begin their decline usually due to extensions of health care and 
sanitation by the national or local government. Single vector programs 
such as malaria control and immunization programs are often the first 
implemented because they are capable of ready extension and do not 
require as heavy a commitment to education and other sustained 
infrastructure - especially in rural areas. These single vector programs 
are then followed by broader-based health care which demand heavier 
investment in infrastructure. But an entirely successful move through 
this transition does not always happen. At times, other sectors in 
transition overpower the health care delivery system. 

The Agricultural Transition
For several hundred years, worldwide agricultural production has been 
rising in relative harmony with population. Overall, increases in 
production have kept up with and even outpaced growth in population. The 
two factors that have been responsible for these increases are 1) 
extensions of land under cultivation and 2) improvements in 
productivity.  At times changes have been dramatic. Formulating an 
agricultural transition reflects the condition that, in general, sources 
of increase in production shift from extending land to intensifying 
production on land already under cultivation. 

The Forestry Transition
At the onset of the forestry transition generally a large percentage of a 
region is under forest cover. Rapid deforestation occurs during the 
transition and finally forest cover stabilizes at a lower level 
determined by many factors such as the local region's needs, the state of 
the local and national economy, climate and soil characteristics. In most 
settings this transition will end in a steady state equilibrium balancing 
growth and harvest. Again, how society handles the vulnerable transition 
period often determines in a profound way the quality of life for the region.

The Toxicity Transition
The toxicity transition can be considered a composite of many 
transitions:  global atmospheric, local air pollution, surface water, 
ground water and solid waste to name a few. Again, there are at least two 
sets of factors operating in tandem. The transition begins with low 
levels of industrial or agricultural production and correspondingly low 
levels of toxins. As production and population increase, toxic byproducts 
increase to levels which eventually become unacceptable to the general 
public. This in turn, causes a public demand for pollution abatement. 
After an environmentally costly time lag, remediation steps are taken 
which helps to bring pollution under control.

The Urbanization Transition
The urbanization transition is driven by the dual forces of rural to 
urban migration and central city population growth. The early stages of 
the transition are characterized by rapid growth of urban population; 
however, in later stages, growth declines and may reverse. Rural to urban 
migration is a product of many forces - both  "pull"  and "push". In 
terms of the population-environment dynamic, the urbanization transition 
often acts as an amplifier as it interacts with other transitions.

The Fossil Fuel Transition
The fossil fuel transition is a special case of the energy transition. 
Historically, many energy transitions have already occurred in different 
regions and time periods. Significant transformations began in the 
sixteenth century brought about by sail and later, by steam power. Today, 
we are now in the most universal and perhaps critical energy transition: 
fossil fuels. Studying this transition is especially instructive because 
the record on different societies' passage through the vulnerable period 
is varied and appears to be heavily influenced by public policy. 


1.2  GENERAL CHARACTERISTICS OF TRANSITIONS
Similarity of Trajectory Across Sectors
We have attempted to show in the seven example sectors discussed earlier 
that the notion of transitions apply across all sectors of investigation. 
Each class of transition, whether it be demographic, toxicity, forestry, 
agriculture, urbanization, energy or epidemiological have similar 
patterns. It is this perception that has caused us to posit the existence 
of a family of transitions possessing some common attributes useful in 
analysis. The first common attribute of all transitions is their 
trajectory. They all begin in reasonable stability, then move to the 
volatile transition period where change is rapid, and finally return 
again to relative balance. Analytically, these are clearly nonlinear 
systems but ones which have properties that lend themselves to 
well-understood mathematical functions. 

Applicability of Transitions Across Scales
The second attribute has to do with scale. One of the most interesting 
and at the same time vexing aspects of studying population-environment 
dynamics is that many phenomena manifest themselves at all levels of 
geographic and temporal scale. For example, data depict one demographic 
transition for an entire continent, a different one for a country within 
that continent and still other different transitions at the regional 
level. Local conditions may delay or advance the onset and or completion 
of the transition in relation to the larger body. Thus, moving through 
the demographic transition can take more or less time as the scale changes.
This same variation seems to exist in all other population-environment 
transitions that have been investigated. True, national or regional-level 
determinants often set the stage for the local dynamic, but in the end it 
is these local conditions which determine the timing, magnitude and 
specific trajectory of the overall transition. 
One can think of our world, seeming to be chaotic, but instead consisting 
of a multitude of well defined transitions in many sectors, each with its 
own local characteristic. Different transitions begin at different times 
and places, but ebb and flow in an overlapping way, sometimes reinforcing 
one another and at other times dampening their dynamic. As adjustment 
occurs, occasionally useful niches are created which are then exploited 
by stressed elements of the ecosystem. Unfortunately, at other times, 
different sectors interact with each other in a harmful way to broaden 
and extend the susceptible period.

Societal Vulnerability
During transitions there seems to be a special vulnerability borne by 
society. Ample evidence indicates that key relationships are most likely 
to become out of balance during the transition. A primary cause of this 
vulnerability is the rapidity of change during the high velocity portion 
of the transition. Adaptive capacity is impeded because there is little 
time for systems to adjust and often there are limited feedback 
mechanisms operating which otherwise could help this process. Another 
contribution to social vulnerability during a transition is the 
amplifying effects created by transitions occurring simultaneously in 
several sectors.  Rapid rates of change in several sectors could more 
easily overpower the available infrastructure which leads us to the next 
source of vulnerability during transitions: capital availability.
Capital or investment capacity can either amplify or reduce societal 
vulnerability during a transition. If there are financial resources 
available to deal with the effects of rapid change, remediation is easier 
to implement. Africa which is trying to deal with a difficult demographic 
transition has almost no capital available for its use and will therefore 
undergo great hardship. The Soviet Union and Eastern Europe are 
struggling to find financial resources to deal with their flawed toxicity 
transition. Another dimension of transitions which affects societal 
vulnerability is the degree of interconnectedness. How closely is the 
local village connected to the regional and national economy? How much 
does what happens in one location determine what happens in another? 
There is no question that interconnectedness is increasing worldwide. We 
also know that under some circumstances linkage creates dependencies 
which in turn, increase vulnerability. However, it can work in the 
opposite direction as well. These very same links to a larger domain can 
also act as a safety net. If there are connections, resources can be 
brought to the stressed area more easily to mitigate the local adversity. 
The final and perhaps most important dimension of transitions affecting 
vulnerability is feedback.

Analytic Properties of Transitions
We have seen that many characteristics of transitions are common across 
all sectors and geographic scales. The question then, is whether there 
are analytic techniques which might be useful in describing this family 
of transitions. If so, these techniques may be helpful in portraying 
transitions in a way that facilitates comparison and thereby increases 
our understanding. In this quest we are especially interested in 
techniques and functions which reduce complexity and at the same time 
provide a reasonably accurate portrayal of reality 
Functions which are candidates for consideration include exponential, 
exponential to the limit L, logistic, Gompertz, and the power function. 
Bounded functions which fit data more precisely but cannot be used for 
predictive purposes may also be helpful in uncovering patterns.

1.3  POLICY IMPLICATIONS OF TRANSITION THEORY
But what does it gain us to fit an exponential or logistic or for that 
matter any function to transition data? The answer lies in our ability to 
gain insights by relating different transitions to each other. First, 
consider the transitions within a given sector and at a given scale. We 
know there are transitions in a sector which some societies have already 
experienced while others have yet to endure. If the nature of these 
experiences can be captured in general form, it is more likely that 
knowledge can be transferred to other settings where a transition is 
first starting. Of course, each civilization or local culture has its own 
unique characteristics but any one emerging transition may be comparable 
to one or more of those which have occurred before because conditions are 
similar.
Second, there may be useful comparisons across different scales. We 
already surmise that a national-level transition, perhaps now in process, 
is actually comprised of a myriad of local transitions also in process or 
which have recently occurred. But there may be other locales in the 
region for which the transition has yet to happened. If similar patterns 
emerge because of similar local conditions, a useful prediction could be 
made about the nature of the passage through the transitions yet to appear.
Third, there may be insights gained simply by the process of fitting a 
function to historical data. Different mathematical functions often have 
very specific underlying characteristics which can provide useful ideas. 
The next potential use of transition theory is to facilitate analysis 
across sectors. There is, of course, no good reason to expect the 
trajectory of, say, a forestry or agricultural transition to mimic an 
epidemiologic transition. However, for any society at a given time, there 
may be similarities in the rates of change across sectors. Developed 
economies have slower rates of change in their agriculture sector than 
developing economies when conditions are favorable. Rural based cultures 
may be expected to have urbanization transitions which are steeper than 
non-rural cultures. In short, it is worth testing to see if patterns can 
be empirically determined which would be helpful in predicting the shape 
of future transitions, given a stated level of intervention.
We have already mentioned the special societal vulnerability associated 
with several sectors being in rapid transition simultaneously.  From a 
modeling perspective this simultaneity a very difficult condition to 
describe and analyze, which may be why less progress has been made in 
this area to date. However, being able to portray these multiple 
transitions with specific functions could be helpful. There is no 
question that each transition interacts with the other. And to the 
analyst this means that a reliable model must be structured as a set of 
simultaneous relationships. Describing transitions as functions 
facilitates this manipulation.
Another potential benefit of transition theory lies in the identification 
of lead indicators. If success is achieved in fitting transition data to 
an appropriate function, then for a given condition and point in time, 
the future trajectory can be predicted more accurately. Identifying lead 
indicators is facilitated because with an orderly function, only one, or 
at most, two parameters need to be determined to define the trajectory. 
This advantage is even more evident when several functions are considered 
simultaneously.
Finally and perhaps most importantly, transition theory may permit more 
informed public and private intervention. At one level we find ourselves 
believing that the trajectory of a transition is somehow fixed by an 
immutable law of nature. But at another level we know that this is not 
the case. Public and private policy can make a difference as we have seen 
from some of the cases discussed in this book. Rates of change can be 
influenced by policy redirection and consequent resource allocation. To 
the extent that we can link historical rate differentials with historical 
policy implementation, a better determination can be made about which 
intervention mix works best in dealing with problems facing society today.