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Differences between observed and predicted energy costs at rest and during exercise in three subsistence-level populations.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 99:537-545 (1996)
Differences Between Observed and Predicted Energy
Costs at Rest and During Exercise in Three
Subsistence-Level Populations
PETER T. KATZMARZYK, WILLIAM R. LEONARD,
MERRILL A. STEPHEN, PETER R. BERTI, AND ALLEN G.P. ROSS
Department of Physical Education and Exercise Science, Michigan State
University, East Lansing, Michigan 48824-1049 (PZK.);
Department of
Human Biology and Nutritional Sciences, University of Guelph, Guelph,
Ontario Canada N l G 2Wl (W.R.L., M.A.S., P.R.B., A.G.PR.)
KEY WORDS
Energy expenditure, Metabolic adaptation,
Factorial method, Temperature stress, Siberia, Ecuador
ABSTRACT
Estimates of daily energy expenditure are important for
many areas of research in human ecology and adaptability. The most common
technique for estimating human energy expenditure under field conditions,
the factorial method, generally relies on activity-specific energy costs derived
from published sources, based largely on North American and European
subjects. There is concern that such data may not be appropriate for nonWestern populations because of differences in metabolic costs. The present
study addresses this concern by comparing measured vs. predicted energy
costs at rest and during sub-maximal exercise in 83 subjects (52 males, 31
females) from three subsistence-level populations (Siberian herders and highland and coastal Ecuadorian farmers). Energy costs at rest (i.e., lying, sitting
and standing) and while performing a standard stepping exercise did not
significantly differ among the three groups. However, resting energy costs
were significantly elevated over predicted levels (+16% in men, +ll%
in
women), whereas exercising costs were comparable to predicted values (-6%
in men, +3% in women). Elevations in resting energy needs appear to reflect
responses to thermal stress. These results indicate that temperature adjustments of resting energy costs are critical for accurately predicting daily energy
needs among traditionally living populations. o 1996 Wiley-Liss, Inc.
Accurate estimates of energy expenditure
are critical to research in human ecology and
adaptability (Ulijaszek, 1992). Quantifications of daily energy requirements and energy balance help to provide insights into
physiological and behavioral responses to
fluctuations in food availability that are so
common among traditional, subsistencelevel populations (de Garine and Harrison,
1988; Ferro-Luzzi, 1990; Huss-Ashmore,
1988;Leonard, 1992).Additionally energetic
data are useful in understanding the adaptive significance of human subsistence strategies in different ecosystems (Dufour, 1983;
Little et al., 1988;Montgomery and Johnson,
1976; Smith, 1981; Thomas, 1973).
0 1996 WILEY-LISS, INC.
There are several methods currently
available for assessing total daily energy expenditure (TDEE) in free-living human populations. The most widely used technique
remains the factorial method of recall and
observation. This approach involves having
either the subject or an observer record the
amount oftime that the subject spends in various activities throughout the day. The energetic costs for these activities are then ob-
Received May 2, 1995;accepted July 14, 1995
Address reprint requests to William R. Leonard, Department
of Human Biology and Nutritional Sciences, 116JT Powell Building, University of Guelph, Guelph, Ontario Canada N1G 2W1
538
P.T.KATZMARZYK ET AL.
tained by indirect calorimetry, or, more often,
from published sources (e.g., Passmore and
Durnin, 1955; Durnin and Passmore, 1967;
James and Schofield, 1990).The most recent
WHO recommendations on energy and protein requirements (FAO/WHO/UNU, 1985)
advocate the use of the factorial method for
estimating adult energy demands in populations throughout the world; however, there
remain concerns regarding the accuracy of
this approach, in part because it is unclear
whether activity-specific energy costs derived on one population can be effectively applied to a different population (Durnin, 1990).
Several recent studies have indicated that
the factorial method may underestimate
daily energy needs. Both Roberts and colleagues (1991) and Haggarty et al. (1994)
found that the factorial method underestimated energy expenditures relative to values obtained using the doubly labelled water
technique. Leonard et al. (1995a) demonstrated a similar pattern among farmers of
highland and coastal Ecuador; for this sample, factorial estimates based on the WHO
methodology were 16%lower than those obtained from daily heart-rate (HR) monitoring. Yet, while these and other studies have
questioned the accuracy of the factorial
method, none have specificallyidentified the
factors that contribute to the inaccuracy.
The purpose of this study is to examine
the potential sources of error associated with
the factorial method, by comparing measured vs. predicted energy costs at rest and
during sub-maximal exercise for adults from
three subsistence-level groups (Siberian
herders and highland and coastal Ecuadorian farmers). We expect that if the errors in
the factorial method are due to differences in
energetic demands among populations, that
the measured energy costs for the resting
andlor active conditions will be significantly
different from those derived from the reference values, based largely on subjects from
Europe and North America.
METHODS
Subjects
Anthropometric and energy expenditure
data were collected from herding and fishing
populations of central Siberia and from agricultural populations of highland and coastal
Ecuador. In Siberia, data were collected in the
context of a larger, ongoing research project
examining the ecology, health and genetic
structure of indigenous Siberian groups (see
Leonard et al., 1992).The Siberian sample includes 44 individuals (30 males, 14 females)
of the Evenki and Keto populations randomly
selected from three villages of the Stony Tunguska region (Surinda,Poligus and Sulamai).
Subjects rangedin age from 14to 4lyears (see
Katzmarzyket al., 1994,for additional details
of the sample). Physiological and anthropometric data were collected in the village
health posts (for individuals living in the central communities) or in the bush (forthose living in the herding parties).
The Ecuadorian data were collected as
part of a research program examining the
biosocial determinants of undernutrition
and growth stunting among rural farmers
(see Leonard et al., 1995b). The highland
Ecuadorian sample was derived from two
communities of the Salcedo county (Cotopaxi
Province), and includes 29 subjects (17
males, 12 females) between 16 and 63 years
of age. Data from coastal Ecuador were collected from a single village in the Jipijapa
county (Manabi Province) on a sample of 10
subjects (5 males, 5 females) who ranged in
age from 23 to 71 years (see Leonard et al.,
1995a, for additional details on the Ecuadorian samples). In each region, measurements
were taken in a field laboratory that was set
up in one the community’s households.
Anthropometrics
Anthropometrics for each subject were obtained following the methods outlined in
Lohman et al. (1988). Stature was measured
to the nearest millimeter using a portable
field anthropometer (Creative Health Products, Plymouth, MI), and body mass was assessed t o the nearest 0.5 kg using a standing
spring scale (Seca Corp., Columbia, MD).
Mid-arm circumference was measured to the
nearest millimeter using insertion tape measures (Ross Labs, Columbus, OH). Skinfold
measurements (mm) at the triceps and subscapular sites were measured to the nearest
0.5 mm with Lange calipers (Cambridge Scientific, Cambridge, MD). Upper-arm muscle
area (UMA, cm2)was derived from the triceps skinfold and mid-arm circumference
measurements.
VARIATION IN HUMAN ENERGY DEMANDS
Energy expenditure
For each subject, energy expenditure (EE;
kJ/min) and heart rate (HR) were measured
for three resting positions (lying, sitting and
standing) and two t o four exercise levels. The
exercise data were collected while the subject performed a standard step test (the Canadian Aerobic Fitness Test [CAFT]; Jett6
et al., 1976;Fitness Canada, 1986). For both
the resting and exercising conditions, HR
was measured continuously via a portable
HR monitor (Polar Vantage XL HR monitor;
Polar Electro, Stamford, CT). Energy expenditure was measured using the Douglas bag
method of indirect calorimetry (Douglas,
1911). Expired air samples were collected
for 3 minutes under resting conditions, and
during the final minute of each 3 minute
exercise bout. These samples were analyzed
for oxygen ( 0 2 ) content using a portable 0,
monitor (Model 74222; Biotek Instruments
Inc., Winoosk, VT) which had been calibrated with external air, and a tank containing 15% 0,. The volume of expired air
was then determined with a dry gas volume
meter (Model 802; American Meter Go., Fullerton, CA), and corrected to standard temperature and pressure, dry (STPD). Energy
expenditure for each of the resting and exercising conditions was then calculated as:
EE
=
20.6 . (VE/100)(20.93- FeOd
where VE = volume of expired air (Umin)
and FeOz = fraction of 0, in expired air (%).
Basal metabolic rate (BMR;kJ/min) was estimated from body mass using the age and
sex-specific predictive equations of the FAO/
WHOAJNU (1985).
Energy costs of the step test were used to
calculate the net mechanical efficiency
(NME) of stepping for each subject. The mechanical efficiency reflects the amount of
work performed as a percentage of the metabolic costs associated with the task. For the
CAFT step test, NME was calculated as:
NME(%) = 100
where Wt
Work load (joules/min)
Energy cost (jouleshin)
Wt . Ht ' 9.8 ' N
(EE - BMR)
=
100.
=
body mass (kg), Ht
=
height of
539
stairs (m), N = number of ascentdmin,
EE = energy expenditure of exercise level
(joules/min) and BMR = basal metabolic
rate (jouledmin).
Analytical methods
Predicted energy costs of the three resting
conditions (lying, sitting and standing) were
estimated from data compiled by James and
Schofield (1990).These costs were calculated
as 1.2 x BMR for lying and sitting, and
1.4 X BMR for standing (James and Schofield, 1990).For the exercise levels, predicted
energy costs were derived from values presented by Fitness Canada (1986). Paired
t-tests were used to assess differences between measured and predicted energy costs
in the resting and exercising conditions. Differences among the three samples were evaluated using one-way analyses of variance
(ANOVA) with SPSSpc (SPSS, 1990).
RESULTS
Mean age and anthropometric characteristics of the three samples are presented
in Table 1. Siberian men and women are
significantly younger than their Ecuadorian
counterparts. Body size and composition,
however, are similar among the three populations, with men and women from all of
the groups being short relative to US norms
(55th centile; Frisancho, 1990).The only dimension that differs among the groups is
UMA, with the Siberian women being significantly less muscular than their coastal Ecuadorian counterparts.
Table 2 presents basal and resting energy
costs for men and women of the three samples. One-way ANOVAs indicate that there
are no significant differences in EE among
the three regional groups for any of the resting conditions. However, average expenditure levels for the three resting conditions
are 16% higher than predicted from the
James and Schofield (1990) standards for
males (6.80 vs. 5.88 kJ/min; t = 5.58;
P < 0.001) and 11%higher for females (5.24
vs. 4.74 kJ/min; t = 3.17; P = 0.004). As
shown in Figure 1, expenditure levels for
males are 15%greater in Siberians, and are
elevated by 16% and 26% in highland and
coastal Ecuadoreans, respectively. For
women, the differences are more modest, but
are still statistically significant. Siberian
540
P.T.KATZMARZYK ET AL.
TABLE 1. Anthropometric characteristics of male and female samples from the three subsistence-leuel populations
n
Age
(yr)
Body mass
(kg)
Stature
(cm)
Triceps
(mm)
Subscapular
(mm)
UMA
(cm2)
Males
Siberia
Highland Ecuador
Coastal Ecuador
30
17
5
26 ? 6a,b
37 t 13"
49 C l g b
61.4 t 7.7
60.6 t 6.6
55.6 5 7.4
161.3 t 5.3
160.0 t 6.6
157.6 i 5.5
6.7 5 3.1
6.8 t 2.3
10.1 ? 6.6
9.0 t 3.4
10.2 t 4.1
13.8 t 8.8
51.2 2 8.6
47.6 t 6.2
53.3 f 15.9
Females
Siberia
Highland Ecuador
Coastal Ecuador
14
12
5
23 2 6c,d
39 2 13'
34 2 16d
50.6 4.7
55.6 t 11.0
47.8? 3.4
149.8 t 4.1
146.9 t 5.8
145.8 t 2.1
15.4 _f 4.5
16.2 t 4.7
18.0? 6.1
14.6 t 4.4
19.0 t 7.7
20.6 t 3.6
32.0 -t 6.0'
39.3 t 8.6
39.5 t 5.6'
Values expressed as mean 2 SD.
"Shared letters denote significant
_f
(P< 0.05) differences between groups using Tukey's HSD test
TABLE 2. Resting physiologic characteristics of male and female subiects from the three subsistence-level populations
BMR'
(kJ/min)
Lying EE
(kJ/mini
Sitting EE
(kJ/mini
Standing EE
(kJ/mini
Males
Siberia
Highland Ecuador
Coastal Ecuador
F-ratio
4.67 t .31
4.61 t .43
4.44 t .26
0.89
6.17 t 1.39
6.66 f 1.33
6.92 t 0.83
0.08
6.67 ? 1.86
6.74 2 1.54
7.42 t 0.65
0.39
7.09 i 1.85
6.84 t 1.00
7.00 t 1.46
0.16
Females
Siberia
Highland Ecuador
Coastal Ecuador
F-ratio
3.75 t .20
3.84 t .41
3.57 t .13
1.49
4.91 2 1.32
5.11 t 1.03
5.40 t 1.06
0.33
4.97 t 1.40
5.60 t 0.78
6.22 t 0.55
2.70
5.35 ? 1.45
4.94 t 0.85
5.64 f 0.66
0.80
Values expressed as mean i SD.
' Basal metabolic rate predicted from FAO/WHO/LTNU (1985)equations
Percent Difference
40
T
30
20
DSiberia
OHighland Ecuador
10
Coastal Ecuador
0
-1 0
-20
Rest Exercise
Males
Rest Exercise
Females
Fig. 1. Percent differences (%SE)between observed and expected energy costs a t rest and during
exercise for males and females of three subsistence-level groups (Siberians and highland and coastal
Ecuadoreans). Resting energy costs are significantly greater than predicted values for both men and
women. Exercise costs are comparable to predicted levels for both sexes.
54 1
VARIATION IN HUMAN ENERGY DEMANDS
TABLE 3. Exercising energy costs (kJ/min) for the first four levels ofthe Canadian Aerobic Fitness R s t (CAFT)
Population
n
Males
Siberia
Highland Ecuador
Coastal Ecuador
F-ratio
1
3
5
Females
Siberia
Highland Ecuador
Coastal Ecuador
F rati o
13
11
5
~
Level 1
kJImin
n
Level 2
kJImin
7
26.8
22.9 t 3.5
21.6 t 4.9
0.57
17
5
20.0 t 3.7
21.0 2 5.9
17.8 t 4.4
0.87
13
12
5
n
28.9 t 2.6
27.5 t 5.0
27.6 t 6.1
0.25
30
17
3
22.5 t 3.9
23.2 t 4.6
20.7 t 4.7
0.61
8
8
3
Level 3
kJImin
31.9 t 5.6
30.8 t 7.9
31.1 -t 7.6
0.15
26.3 t 5.5
31.8 ? 11.2
25.3 t 1.7
0.81
n
28
15
-
Level 4
kJImin
36.5 t 6.1
35.7 % 6.1
-
0.20
1
1
-
31.9
29.1
-
Stepping rates for levels 1 through 4 are 11, 14, 17 and 19 ascentdmin.
women expend 6%more energy a t rest than
predicted, as compared to +8% in highland
Ecuadoreans and +31% in coastal Ecuadoreans.
Table 3 presents energy costs for the first
four levels of the CAFT. Variation in sample
sizes across the four levels reflects the fact
that not all subjects started and finished at
the same points. EE does not significantly
vary across the three samples for any exercise level. Moreover, expenditure levels are
also comparable to those predicted based on
data collected among Canadian samples.
This point is demonstrated in Figure 2,
which shows the mean measured energy
costs at each stepping level for the three
samples, along with the predicted costs,
based on the reference data (Fitness Canada,
1986). Among men, measured energy costs
for the exercise levels average 6%below predicted values (see Fig. l), whereas for
women, the measured values differ by +3%.
The NME of stepping is presented in Figure 3. Again, no significant differences are
evident between the samples. For the male
samples, NME averages 15.4%in the coastal
Ecuadoreans, 15.9% in the Siberians, and
16.8% in the Ecuadorian highlanders. For
women, average NMEs are 15.9% in the
highland sample, 16.3%in the coastal group,
and 16.0% in the Siberians. As shown in
Table 4, the stepping efficiencies for all three
groups are similar to those reported for most
other populations, with the exception of Tamang men and women from Nepal, who have
substantially higher efficiencies (22-27%).
The greater efficiency of the Nepali subjects
is thought to reflect adaptation to nutritional
stress (Strickland and Ulijazsek, 1990) and/
or anemia (Panter-Brick et al., 1992).
DISCUSSION
The factorial method is currently the technique prescribed by the World Health Organization for assessing TDEE in free-living
human populations (FAO/WHO/UNU, 1985;
James and Schofield,1990). However, recent
work has indicated that this method may
consistently underestimate TDEE (Roberts
et al., 1991; Haggarty et al., 1994; Leonard
et al., 1995a). The findings of this study suggest that the inaccuracy in the factorial estimates arises from underestimation of energy
costs a t rest. Our results demonstrate that
measured energy costs for resting conditions
(i.e., lying, sitting and standing) significantly differ from those predicted from current standards, whereas EE during low to
moderate exercise does not. Resting EE values averaged 16%higher than predicted in
males and 11%greater in females; exercising
levels, on the other hand, deviated by only
-6% in men and +3% in women. The energetic efficiency of the three groups for the
step test was also comparable to that observed among Canadian and British populations, ranging from 15 to 17%.
These results are surprising in that they
suggest that differences in work efficiency
(e.g., mechanical efficiency) are not a large
source of error in estimating energy needs
with the factorial approach. Rather, they imply that the sedentary component of daily
expenditure is more important in contributing to the biases observed. Since a large pro-
542
P.T.KATZMARZYK ET AL.
Energy Cost (kJ/min)
15
10
1
2
3
4
1
2
3
4
Level (CAFT)
*Canada
(Reference) -Siberia
0 Highland Ecuador +Coastal Ecuador
Fig. 2. Sub-maximal energy expenditure for males and females of three subsistence-level groups
(Siberians and highland and coastal Ecuadoreans) for four levels of a standard stepping exercise test.
Reference values for Canadian subjects were derived from Fitness Canada (1986). Energy costs do not
significantly differ among the three groups, and all are comparable to the Canadian reference values.
Net Mechanical Efficiency (%)
22
20
Men
0
18
16
14
12
1
2
3
4
1
2
3
4
Level (CAFT)
I
-Siberia
0 Highland Ecuador
-D Coastal
Ecuador
1
Fig. 3. The net mechanical efficiency of stepping for the meals and females of the three subsistencelevel groups (Siberians and highland and coastal Ecuadoreans).
543
VARIATION IN HUMAN ENERGY DEMANDS
TABLE 4. Comparison of net mechanical efficiency (NME) estimates for stepping in selected populations
Population
Body mass
(kg)
Stature
(cm)
NME
(%)
References
Shephard et al. (1968)
Strickland and Ulijaszek (1990)
Strickland and Ulijaszek (1990)
Young Canadian men
British soldiers
Gurkha soldiers
-
-
67.4
67.6
173.7
167.1
16.3
15.3
21.1
Nepal
Tamang men (anemic)
Tamang men (non-anemic)
Tamang women (anemic)
Tamang women (non-anemic)
Rural women
51.3
52.0
47.1
48.4
43.6
160.0
158.0
150.0
151.0
148.1
26.6
22.0
23.4
22.6
16.9
Panter-Brick et al. (1992)'
Panter-Brick et al. (1992)
Panter-Brick et al. (1992)
Panter-Brick et al. (1992)
Malville (1991)'
-
14.8
15.3
Shephard (1974)
Shephard (1974)
Eskimo men
Eskimo women
Highland Ecuador
Men
Women
60.6
55.6
160.0
146.9
16.8
15.9
This study
This study
Coastal Ecuador
Men
Women
55.6
47.8
157.6
145.8
15.4
16.3
This study
This study
Siberia
Men
Women
61.4
50.6
161.3
149.8
15.9
16.0
This study
This studv
'Anemic group defined as having a hemoglobin concentration below 120.3 g L (men) and 109.4 g L (women)
2Rural sample includes Brahman, Chetri, Newar and Tamang women.
portion of typical day is spent in sedentary
activities (James and Schofield, 1990), only
a small deviation from predicted energy requirements at rest (i.e., 0.5-1.0 kJ/min) is
necessary to produce a large bias in daily
energy requirements.
The elevations in resting metabolic costs
presented here are similar to those reported
for other subsistence-level populations (see
Katzmarzyk et al., 1994; Table 4),and likely
reflect the influence of thermal stress. Unlike populations of the developed world,
these traditionally living groups are exposed
to temperatures that are outside of their
thermoneutral range throughout the course
of a normal day. For this reason, physiological measurements for the present samples
were taken in typical dwellings so as to most
closely approximate the actual energy demands in each environment. As shown in
Table 5, the data indicate a significant interaction between resting energy costs and temperature at the time of measurement for
both males and females. Deviations from
predicted energy costs are smallest for temperatures ranging from 20-25°C (+7% in
males, +3% in females), and are significantly greater for temperatures below 20°C
TABLE 5. Variation in resting energy expenditure
with temperature
Temperature
range'
<2O0C
20-25°C
>25T
F-ratio
n
27
15
10
Males
%Difference2
16.0 i 18.5
7.3 1- 21.5a
30.1 ? 13.2a
4.20*
n
19
6
6
Females
%Difference
4.9 i- ll.gh
3.2 t 18.8'
37.1 i 11.2b,e
14.61**
Variation among temperature groups is significant at: *P < 0.05;
**P < 0.0001.
Shared letters denote significant ( P < 0.05) differences between
groups using Tukey's HSD test.
'The samples in each temperature category are composed as follows.
Males, <20T = 10 Siberians, 17 Highland Ecuadoreans; 20-25°C =
15 Siberians; >25"C = 5 Siberians, 5 Coastal Ecuadoreans. Females,
<20"C = 7 Siberians, 12 Highland Ecuadoreans; 20-25°C = 5 Siberians, 1 Coastal Ecuadorean, >25"C = 2 Siberians, 4 Coastal Ecuadoreans.
2Percent difference from predicted EE, based on James and Schofield
(1990).
(+16% in males, +5% in females) and above
25°C (+30%in males, +37% in females).
It is possible, as well, that the higher resting energy costs among these three populations reflect longer term adaptations in basal
energy requirements. Roberts' (1978) classic
work, Climate and Human Variability, found
a strong negative relationship between BMR
and mean annual temperature, suggesting
a genetic andor developmental component
544
P.T. KATZMARZYK ET AL.
to BMR variation among humans. Additionally, metabolic studies on indigenous high
latitude populations of Europe and the New
World (e.g., Itoh, 1980; Rode and Shephard,
1995), and on high altitude populations of
the Andes (e.g., Picon-Reategui, 1961; Mazess et al., 1969) have demonstrated significant elevations in BMR. Consequently, there
is reason to expect th at BMRs in the Siberian
and highland Ecuadorian samples of this
study may be higher than those predicted
by the WHO’S equations (FAO/WHO/LTNU,
1985, a s derived from Schofield, 1985). Unfortunately, this hypothesis cannot be directly tested here, since none of the metabolic data were collected under basal
conditions. Our ongoing research in Siberia,
however, is examining BMR levels among
the Evenki herders to address this question.
In light of the research cited above, it is
surprising that the most recent WHO report
on energy and protein requirements found
insufficient evidence for recommending a
temperature adjustment in determining
daily energy needs (FAO/WHO/UNU, 1985).
Earlier FAOMrHO recommendations (FAO,
1957)acknowledged the influence of climate
on EE, and other recent models for predicting energy expenditure have also advocated use of a temperature adjustment for
basal and resting metabolic needs (see Buskirk and Mendez, 1980; Leslie et al., 1984;
Little et al., 1988). Results presented here
strongly indicate that a temperature adjustment is necessary for accurately predicting
energy expenditure with the factorial approach, especially among traditionally living
populations, who are exposed to greater
amounts of thermal stress. Without such correction, the current WHO protocol will tend
to substantially underestimate energy demands and potentially minimize evidence of
nutritional stress.
ACKNOWLEDGMENTS
We are indebted to the subjects who participated in this study. We also thank Katherine McCaston, James Stansbury, Ramon Rodriguez, and Nadia Blagitko for assistance
with data collection. The Siberian portion of
this research was conducted in collaboration
with Drs. M.H. Crawford (Universityof Kan-
sas) and R.I. Sukernik (Russian Academy of
Sciences); the Ecuadorian component was a
collaboration with Drs. K.M. DeWalt (University of Pittsburgh), J.E. Uquillas (World
Bank), and el Fundacion para el Desarrollo
Agropecuario (Quito, Ecuador). This research was supported by grants from the
Natural Sciences and Engineering Council
of Canada (OGP-0116785;WRL), the US National Science Foundation BSR-99101571
[MHC, WRL], 9106378 [KMD, WRL]), the
US Man and the Biosphere Program, and
the International Development Research
Centre of Canada (MAS, AGPR).
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