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Vulnerability and Resilience of Sidama Enset and Maize Farms
in Southwestern Ethiopia
Author(s): Robert J. Quinlan, Marsha B. Quinlan, Samuel Dira, Mark Caudell,
Amalo Sooge, Awoke Amzaye Assoma
Source: Journal of Ethnobiology, 35(2):314-336.
Published By: Society of Ethnobiology
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VULNERABILITY AND RESILIENCE OF SIDAMA ENSET
AND MAIZE FARMS IN SOUTHWESTERN ETHIOPIA
Robert J. Quinlan
*, Marsha B. Quinlan
, Samuel Dira
, Mark Caudell
, and Awoke Amzaye Assoma
Enset (Ensete ventricosum) is the traditional staple food of Sidama people who live in Rift Valley
lowlands to highlands in southwest Ethiopia. Enset is drought resistant, but it matures slowly, requires
substantial manure inputs from cattle, and intensive processing. Maize, introduced to Sidamaland in the mid-
twentieth century, is common in midlands and lowlands. Maize matures rapidly and provides more kcal/kg
than enset, but it is prone to failure in dry years and requires chemical fertilizer, which is subject to global
market price fluctuations. We compare cultural ecology, productivity, failure, and resilience of enset and maize
in 410 farms across four Sidama ecological zones. The risks and benefits of enset and maize are complexly
associated with variable local environments. Enset offers drought-resistant produce that, with sufficient manure
inputs, is adequate for subsistence in the wet highlands, but its performance is more variable elsewhere.
Fertilized, maize yields larger harvests than enset, but vulnerability to rainfall and global processes create
special challenges. Maize and enset appear to be in different adaptive cycle phases: maize grows quickly and
maize farms rebounded from crop loss within four years. Only half of enset farms recovered within six years
after crop failure, complicating farming decisions in an environment with tremendous localized variation. In
general, the Sidama zone shows a pattern of regional diversity with local specialization for maize only, enset
only, or mixed maize and enset cultivation. In some areas maize has become a preferred crop and food for
Keywords: enset, Sidama people, crop failures, Ethiopia, crop diversity
Enset (Ensete ventricosum [Welw.] Cheesman) is the source of waasa, the staple
food of Sidama people of southwestern Ethiopia. Indigenous to East Africa, and
widely distributed in sub-Saharan Africa, enset is hardly known as a food plant
outside of Ethiopia where it is an important, drought-resistant crop that feeds
millions of people, mostly those living in Southern Nations, Nationalities and
Peoples Regional State (SNNPRS)(Brandt et al. 1997). A relative of the banana,
enset bears no edible fruit; rather, people mash the pseudostem and root into
a pulp, which they ferment for at least two months, and then eat it as a flat bread
or as a mash mixed with milk or butter (similar to ugali or thick grits). Though
drought resistant (Brandt et al. 1997; Mohammed et al. 2013; Shigeta 1990), enset
has a very long maturation period with a minimum of four years to produce
sufficient edible starch and up to ten years to produce the inedible fruit. Earlier
ethnographers noted the cultural centrality of enset: William Shack (1966)
Washington State University, Department of Anthropology, Pullman, Washington, USA
Hawassa University, Department of Behavioral Science, Anthropology Program, Hawassa, SNNPRS,
*Corresponding author (firstname.lastname@example.org) Washington State University, P.O. Box 44910, Pullman
WA, USA 99164
Journal of Ethnobiology 35(2): 314–336 2015
dubbed the Gurage, north of Sidama Zone, ‘‘people of the enset culture.’’ Enset
has been at the base of Sidama livelihood for as long as anyone can remember.
Maize (Zea mays subsp. mays L.), in contrast, is a newcomer to Ethiopia. It
was first documented in 1623, and maize agriculture only recently ‘‘expanded
and matured’’ in southwest Ethiopia, from 1950 to 1975 (McCann 2001:265).
Despite enset’s traditional position, several features contribute to maize’s spread:
maize only needs one plowing before planting (other cereals require up to four
plowings), available varieties require relatively little weeding, and it provides
a high yield in a short time. However, farmers relying on maize ‘‘gambled that
the rains would come on time’’ (McCann 2001:265).
Our interest is the comparative vulnerability and resilience of enset and
maize farming in Sidama Zone of SNNPRS, Ethiopia. Ethiopian food security
requires that we understand the productivity and vulnerabilities of traditional
and introduced crops on the ground as produced by smallholders. Agricultural
experiments are an excellent source of information, but results, often for
‘‘normal’’ conditions, cannot assess ecological variation common to southwest
Ethiopia. USAID (2005) reports 40 different climatic ‘‘livelihood zones’’ in
SNNPRS, with six different zones in Sidamaland. Comparing productivity and
vulnerability of traditional (enset) versus introduced (maize) crops across
ecological zones provides useful information for guiding cultural transmission
and acceptability of new agricultural technologies and crop varieties. We
conceptualize farming practices as key components of alternative social-
ecological configurations (sensu Walker et al. 2002) embedded in Sidama culture.
Social-ecological thinking imagines system evolution involving multiple
‘‘basins of attraction’’ (Folke et al. 2010; Walker et al. 2004). ‘‘Stability landscapes’’
include multiple possible ‘‘regimes’’ or ‘‘configurations’’ with properties in-
cluding stability, transformability, resilience, latitude, etc. A social-ecological
regime or configuration is a collection of variables that respond systematically to
perturbations. In response to perturbations, social-ecological systems (SES) exhibit
adaptive cycles with periods of expansion, reorganization, and transformation that
respond to internal (local) and external (global) shocks (Folke 2006). The expansive
‘‘r’’ phase of the cycle may be followed by a conservative, stable ‘‘K’’ phase (Folke
2006; Walker et al. 2004). We compare the productivity, vulnerability to crop loss,
and time to recovery of maize and enset in four social-ecological contexts: the
Sidama ‘‘homeland’’ in the wet highlands; semi-arid midlands, the site of recent
drought relief efforts; the dry lowlands; and a peri-urban, lakeshore community
near the regional capital. We examine the relationship between enset and cattle as
fundamental to the enset ‘‘configuration.’’ Finally we examine the ‘‘engineering
resilience’’ (Pimm 1991) of maize and enset in relation to the stark differences in
their growth, production, processing, and reproduction.
Enset agriculture and Sidama cultural models indicate that enset is a crucial
drought-resistant crop with significant cultural value. Here we show that Sidama
enset and maize farming exhibit complex relationships with ecological condi-
tions, land constraints, livestock ownership, fertilizer and manure input, and
rainfall associated with elevation. In general, enset farms appear to be in the
conservative ‘‘K’’ phase of the adaptive cycle, while maize farms are in the
expansive ‘‘r’’ phase. In some cases, enset performs poorly compared to maize in
2015 JOURNAL OF ETHNOBIOLOGY 315
terms of risk of crop loss. Common notions of enset as a drought-resistant crop
warrant recasting in a more nuanced empirical framework.
Sidama are a Cushitic-speaking people inhabiting areas between the Rift
Valley lakes of Hawassa and Abaya (Hamer 1987) (Figure 1). Most Sidama reside
in the SNNPRS, the most rural of nine states in the Federal Democratic Republic
of Ethiopia (Figure 1). SNNPRS contains 18 zones and special districts with
boundaries demarcated along ethnic lines; hence, most Sidama live in Sidama
Zone (Aalen 2011; CSAE 2013). Census figures estimate three million Sidama, the
fifth largest ethnic group in Ethiopia (CSAE 2013) among more than 80 distinct
ethnicities (Levine 2000). Additional cultural information on Sidamaland can be
found in Hamer (1987), Quinlan et al. (2014) and Quinlan et al. (n.d.).
The rural Sidama are mostly subsistence agropastoralists (Asfaw and A
2007; CSAE 2013; Hamer 1987). Staple crops are enset and maize, and less
commonly wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). Enset,
which is the main and preferred food, provides more calories per unit of area than
do most cereals (e.g., maize) and is drought resistant; these are important
characteristics given increases in population density and the frequency of
droughts (Asfaw and A
˚gren 2007). Cash crops include coffee (Coffea arabica L.)
and ch’at (khat,Catha edulis Forssk. ex Endl.), a perennial bush chewed as
a stimulant. Crops vary across elevation, rainfall, and soil differences. Cattle play
an important role in Sidama subsistence and risk-coping strategies (Caudell et al.
2015; Hamer 1987). Sidama raise zebu cattle, Bos indicus Linnaeus, primarily for
Figure 1. SNNPRS and study area.
316 QUINLAN et al. Vol. 35, No. 2
dairy and fertilizer. Beef consumption is rare and is limited to ceremonies
(e.g., marriage, funeral) or the natural death of the animal.
Sidama people recognize a symbiotic relationship between cattle and enset.
Enset provides fodder for cattle, especially in times of drought when other
grasses and grains are not available, and, in turn, cattle provide fertilizer for the
enset. Sidama also keep smallstock and chickens (Gallus gallus domesticus
Linnaeus) for consumption and sale (Asfaw and A
˚gren 2007). In general, Sidama
favor using the profits from the sale of crops and wage-labor to purchase
livestock and for livestock care (Yilma 2001).
Enset (E. ventricosum)
Maize is firmly established in much of Africa, and smallholder cultivation is
well documented (McCann 2001). Enset is less familiar. Ethiopian farmers fall in
two broad categories: ‘‘plow cultures’’ of cereal grains—primarily teff, but also
maize, wheat, barley, sorghum, and millet—and ‘‘hoe cultures’’ growing enset
and root crops—taro, sweet potatoes, and yams (Murdock 1959; Steward 1967;
Westphal and Westphal-Stevels 1975). Among hoe cultures, enset is the most
important food by far (Murdock 1959). The ‘‘enset complex’’ (Shack 1963:72)
feeds a dense rural population across southwest Ethiopia (e.g., Bezuneh 1971;
Bezuneh and Feleke 1966; Brandt et al. 1997; Rahmato 1995; Shack 1963) of ten to
15 million people (Brandt et al. 1997; Shank and Ertiro 1996). In all but the highest
altitudes, where enset thrives best (Pijls et al. 1995), people grow it along with
other roots or cereals (Brandt et al. 1997).
Sidama generally grow enset at elevations between 1200-3100 meters. Enset
tolerates cool temperatures but not freezing, which causes frost damage. Above
3000 meters growth is stunted. Areas below 1500 meters are often too dry for
enset (Brandt et al. 1997). Historically, the Sidama area had seasonal bimodal
rainfall—an eight- to nine-month rainy season from March to November with
a midland annual rainfall between 1300 and 2000 mm (Yilma 2001).
The pasture grass in the highlands is primarily Andropogon abyssinicus R.Br. ex
Fresen., which highlanders say is good for cattle (Smeds 1955). The dense rural
population in the Sidama Zone limits grazing land. Hence, enset is important
livestock fodder (Asfaw and A
˚gren 2007; Brandt et al. 1997). Livestock eat parts of
the enset plants that humans do not eat (leaves and outer stems), which contain
the most protein (Yilma 2001). Enset and cattle dominate Sidama subsistence
models, with an important place in Sidama cultural values (Hamer 1987).
Sidama call an enset garden weesete gate or gate.Gate range from .25 to 1.5
hectares (Tesfaye 2008). Gardens contain plants of various ages and sizes as enset
takes years to mature. The Sidama language has about ten terms referring to
enset age-stages (Quinlan et al. 2014; Tesfaye 2008). Large plants are transplanted
closest to the house. Sidama people propagate enset by vegetative cloning,
speeding up the naturally very long maturation process. Enset is never
propagated by seed as far as we know.
A Sidama dwelling, or mine, is a combination house and barn at the edge of
the enset garden. It is divided into a salon with a hearth, bedroom(s), and stalls
for cattle and goats, all separated by bamboo walls or interior fences (see
Figure 2). Sidama build mine on a slight slope with the animal stalls on the
2015 JOURNAL OF ETHNOBIOLOGY 317
downhill side of the house. Floors have small trenches excavated into them,
channeling urine outside into the gate (Figure 2). Women and children gather
manure from the mine, yard, and pasture to spread on their gardens.
Sidama harvest enset before or while the plant is flowering. The time from
planting to flowering depends on the breed, soil nutrients, and rain. Flowering
time ranges from four to ten years. Processing, fermentation, and storage can take
as much as three additional years (Quinlan et al. 2014).
Collaborative Ethnographic Science
Principles of collaborative ethnography (Lassiter 2005) guided our efforts.
Lassiter’s (2005) collaborative approach developed for public anthropology
provides ethical and methodological principles useful for ethnobiology. Our aim
was to level power differentials between Sidama people and researchers by
facilitating the development of colleagues from southwestern Ethiopia. Sidama
and Koore anthropologists (Dira, Sooge, and Assoma) are senior personnel,
Hawassa University faculty, and coauthors of this report. Assoma and Dira are
also PhD candidates in anthropology at Washington State University. Data from
this study have been freely disseminated to researchers at Hawassa University
through an integrated data analysis workshop.
There are empirical benefits to this collaboration. The team has advanced
skills including field methods, statistical analysis, and native language pro-
ficiency. Accuracy of representations is enhanced through a dialectical process
among researchers fluent in modes of anthropology and social science.
Collaboration makes claims of ‘‘time in the field’’—a hallmark of quality
ethnography—meaningless: half of the senior personnel are native to Sidama and
nearby ‘‘enset culture.’’
Figure 2. Model Sidama house with livestock and enset garden or weesete gate.
318 QUINLAN et al. Vol. 35, No. 2
Washington State University Human Subjects Research Compliance Office,
Sidama Zone Administration, and District (Woreda) Authorities in Arbegona,
Boricha, Lokka Abaya and Hawassa Zuria approved this research. Participants
were given a thorough description of the project activities and data use. Verbal
informed consent was obtained and all participants were paid 50 Ethiopian birr
Qualitative data were collected using open-ended ethnographic interviews
with key informants and focus groups in four districts of the Sidama Zone. We
conducted interviews with individuals and/or groups concerning personal and
environmental histories, agricultural practices, inheritance, ethnic and interper-
sonal conflict, social support, family health, gender relations, intra-community
cooperation, etc. All interviews were conducted in Sidama by native speakers.
Interviews were translated into English for the benefit of non-Sidama speaking
project personnel (Quinlan et al. n.d.).
Quantitative data were collected by oral self-report questionnaires
concerning household demography, health, and production. The instrument
included over 200 items yielding a range of data for comparison with other East
African social and economic studies. The interviewers were five Sidama
research assistants, four of whom had university degrees, and three of whom
had prior survey research experience. The research assistants received the
instrument in English and Amharic, then the research assistants and authors
developed appropriate Sidama translations together. The authors field-tested
the Sidama language instrument. Then, the assistants received one week of
training in instrument administration. During the first week of data collection,
assistants worked in teams of two supervised by senior personnel to ensure
uniformity in instrument administration. These surveys took 30 to 90 minutes to
We created a judgment sample of four Sidama districts (woreda) representing
a range of ecological and economic variation in the Sidama Zone (detailed
below). Each Sidama assistant was randomly assigned a different kebele
(neighborhood), within which they obtained a convenience sample. The
assistants recruited participants as they encountered adults while walking main
neighborhood footpaths. We set a target sample size of 100 for each district.
When we reached that target we moved on to the next woreda. This sampling
method was chosen to facilitate rapid pilot data collection. Random sampling
would have dramatically increased research time and expense. We were unable
to reach the target sample in Lokka Abaya. Heightened ethnic tension between
Sidama and neighboring Wolayta people posed an unacceptable risk for the
research team, and we terminated data collection after interviewing 72 Lokka
Abaya farmers. Given five data collectors and randomly assigned neighbor-
hoods, we do not believe our sampling method introduced systematic bias. We
do not claim that our analyses represent precise population estimates; however,
these data are suitable for examining effects on production, risk, and resilience in
the Sidama Zone. These analyses offer a foundation and guide for future
2015 JOURNAL OF ETHNOBIOLOGY 319
Dependent variables include (1) self-reported yields (kg) produced from
enset and maize farms; (2) estimated energy (kcal produced per person per
day), calculated from the total reported production in kg divided by 365 days
and the number of household residents, then multiplied by 2110.37 for enset
and 3749.91 for maize following estimates in Tsegaye and Struik (2001:90);
(3) major recent crop failure (15lost 50% or more of a crop in last seven years,
05did not lose 50% or more of a crop in last seven years); and (4) self-reported
time to recovery from crop failure in years for which participants were asked to
indicate whether the household was worse off, better off, or the same as before
the crop failed.
Independent variables include the following: (1) woreda (district) indicators
(Arbegona, Boricha, Lokka Abaya or Hawassa Zuria); (2) self-reported hectares
planted; (3) fertilizer expense for the last year; (4) number of cattle owned (other
livestock were recorded but cattle are of primary importance); and (5) primary
and secondary crop indicators (maize only, enset only, enset primary and maize
secondary, and maize primary and enset secondary).
Our analysis strategy includes descriptive statistics to characterize farming in
different districts of Sidama Zone, followed by multivariate analyses using
General Linear and Linearized Models (GLM). For Ordinary Least Squares (OLS)
regression the dependent variables were log transformed to normalize residuals,
as required by assumptions of OLS regression. Residuals for raw dependent
variables were not normal; however, log transformation approximated a normal
distribution. Diagnostics were conducted for multicolinearity, outliers, hetero-
scedasticity, non-linearity, etc. All analyses conformed to model assumptions. In
one analysis, dependent variables had extreme outliers so values were
Winsorized by recoding the highest value (i.e., the outlier) to the next highest
value (discussed below). Interaction effects entered the analysis for variables
suggested by Sidama cultural models of enset and maize agriculture. Alpha was
set at 0.05. Non-significant interaction effects were removed from the models.
There were insufficient sample sizes for some categorical variables; hence, some
categories were combined. Recommended n/k (sample size/independent
variables) was greater than 10. For analyses of production, households
that produced no crops, a small fraction of the sample, were excluded from
the analysis. For several models we predicted production estimates for log-
transformed variables using the following back-transformation: Y~eb0zPbnxnzs2
Here b0is the constant, Pbnxnis the summed products of variable values and
regression coefficients, and s2
2is half of the model Mean Squared Error.
Sidama Study Sites
We selected four districts for study: Arbegona in the Sidama highlands,
Boricha straddling the midlands and lowlands, Lokka Abaya in the lowlands,
and Hawassa Zuria in the peri-urban zone of Hawassa City, the capital of
SNNPRS. These site descriptions are based on available records and interviews
regarding local history and livelihood conducted by Sooge, Dira, Assoma and
Quinlan between 2011 and 2014.
320 QUINLAN et al. Vol. 35, No. 2
Arbegona woreda (home to the Harbee and Harbagona clans) is located 74
kilometers from Hawassa in the highland east of the Sidama Zone on the Oromia
state border. In the 2007 national census, Arbegona’s population was 144,300
with about 95% living in rural areas, and a population density of 405.1 people per
(CSAE 2013). The majority of the population practices mixed subsistence
agriculture. Coffee and chat, major cash crops in Sidama, are rare in Arbegona.
Arbegona receives substantial rainfall (up to 2500 mm in long rainy seasons from
June to September). At approximately 2600 m above sea level, Arbegona is wet
and cool. The highland climate has buffered Arbegona from the drought
experienced elsewhere in the Sidama Zone in recent history. However, Arbegona
was at the center of an armed conflict through much of the 1980s as the Sidama
Liberation Movement rebelled against the Derg Regime (Quinlan et al. n.d.).
Many consider Arbegona and other highland areas to be archetypical landscapes
of the Sidama Zone.
Boricha (homeland of the Yanase Clan) is a densely populated woreda in the
center of the Sidama Zone, 39 kilometers south of Hawassa. The 2007 population
of Boricha was 250,260 with a density of 382 people per km
Elevation ranges between 560 and 1700 m above sea level with bimodal rainfall,
from 56 mm (March–May) to 180 mm (June-October). Annual temperature varies
from 20–33 uC (Boricha Woreda Rural Development Coordination Office 2005).
Sugarcane (Saccharum), chat, and coffee are major cash crops in the area. Boricha
has a recent history of periodic drought leading to famine in years 1998–99, 2001,
2003 and 2008. Multiple key informants report that before the mid-1970s, rains
were reliable and sufficient from year to year in the area. However, the long and
most important rains (March to May) have been delayed or absent periodically
(Quinlan et al. n.d.). Local people used to get water from natural springs and
traditional ponds until the 1999 drought, which caused water from all sources to
dry up. In some villages there are standpipes and wells; however, most people in
rural areas buy drinking water from a distance supplied by donkey carts. Boricha
was the site of relief efforts, including food and agricultural aid, in recent years.
Lokka Abaya is a lowland woreda at the western border of the Sidama Zone
located at about 50 kilometers southwest of Hawassa. The Lokka Abaya district
population was 99,233 in 2007 (CSAE 2013). The topography is flat with a gentle
downhill gradient from east to west towards the Bilate River. The altitude ranges
from 560-1700 m above sea level. This is a low rainfall area with an erratic pattern
during the two rainy seasons: The belg (February to April), and the kiremt rains
(July to early October). The temperature ranges from 26–33 uC (USAID 2005). The
soil type is mainly gray sandy loam and it is susceptible to erosion. The district’s
recent drought history is similar to Boricha’s. In addition, Sidama people of
Lokka Abaya experience periodic conflict with neighboring Wolayta people
(Aalen 2011). People in Lokka Abaya also pay for water delivery.
Hawassa Zuria woreda is along the shores of Lake Hawassa; it is within less
than an hour bus commute to Hawassa City. The administrative center, Dore
Bafeno, is 18 kilometers from Hawassa. The population was 124,472 in 2007
(CSAE 2013). The average elevation is 1700 m above sea level with a mean annual
rainfall ranging from 900 to 1400 mm. March to September is the rainy season.
Mean annual temperature varies from 23 to 27 uC (EOSA 2007). Soil is sandy and
2015 JOURNAL OF ETHNOBIOLOGY 321
prone to water and wind erosion. There is no river in the district. Drinking water
is in short supply and many residents pay for water delivery.
Sidama Farm Production
Across four woreda, 71% of Sidama households indicated that enset was their
primary crop. Twenty-seven percent indicated that maize was primary, with the
remainder growing coffee, chat, carrot or cabbage. Seven households (1.7% of the
sample) with crops other than enset or maize primary were excluded. Secondary
crops were diverse: 33% indicated that maize was their secondary crop, less than
8% indicated that enset was their secondary crop, and 44% did not indicate
a second crop.
The proportion of enset and maize grades from predominantly enset
cultivation in Arbegona to predominantly maize in Hawassa Zuria (Table 1).
Arbegona and Hawassa Zuria appear to specialize in one crop. Enset as the
primary crop with maize secondary is common in all four districts. Maize
primary with enset secondary is uncommon. Boricha and Lokka Abaya have the
most diversity in farms; however, enset is the primary crop in a plurality of
Sidama stress that land shortage and associated food insecurity is a serious
concern, even in the highlands. Traditional land tenure requires that a man
divide his land equally among his sons. In the 1970s the communist Derg regime
instituted land reforms whereby an individual could only possess ten ha. Larger
holdings were redistributed. Technically, all land belongs to the state, and the
accumulation of land has been minimal. Since redistribution, the pattern of
inheritance resulted in small landholdings. As one Boricha man reported: ‘‘Now
plots are too small. We don’t have enough for ourselves. We even fight with the
birds to protect our crops.’’ Another informant in Arbegona said that Sidama
need four to five hectares for crops and grazing to make a comfortable living, yet
mean landholding in Arbegona is 2.6 hectares (the most) compared with 1.7
hectares in Hawassa Zuria (the least) (see Figure 3). Land shortage is a cause for
interpersonal and interethnic conflict. When asked if there are conflicts over land,
Table 1. Proportion of enset and maize as primary crops in Sidama Zone.
Arbegona Boricha L. Abaya H. Zuria
Total N 114 105 72 122
N maize only 2 13 6 73
Proportion maize only 0.02 0.12 0.08 0.60
N enset only 77 44 21 15
Proportion enset only 0.68 0.42 0.29 0.12
Proportion maize-enset 0 0.05 0.13 0.09
34 42 36 22
Proportion enset-maize 0.30 0.40 0.50 0.18
Total % 100% 99% 100% 99%
Maize-enset 5maize primary crop with enset secondary
Enset-maize 5enset primary crop and maize secondary
322 QUINLAN et al. Vol. 35, No. 2
a woman in Boricha responded, ‘‘Many! Even brothers from the same mother
argue over land…if it is just a small argument, then the father will settle the
argument. If there is harm…if there is bleeding or violence, then the law will
settle the matter.’’ Armed conflict over land between neighboring Oromo to the
east and Wolayta to the west is not uncommon (Aalen 2011). Hence, choice of
crops, land management, and productivity are key concerns for Sidama people.
Hectares planted varied from .98 in peri-urban Hawassa Zuria to 1.64
hectares in highland Arbegona (Table 2). Boricha woreda showed the most
variation in planted area with a coefficient of variation (CV) more than three
times that of Hawassa Zuria, the second most variable district. The self-reported
data did not permit precise estimates of hectares planted for each crop, but the
predominance of enset and maize in the Sidama Zone is economically salient.
More precise land use and production estimates would be useful.
The productivity of Sidama farms depends on location and crop (Table 3). The
most productive farms in Hawassa Zuria yield over 1100 kg/ha combining maize
with secondary enset. These mixed farms, however, show huge variation in
production and they are scarce: less than 9% of farms sampled. The least
productive farms are also in Hawassa Zuria where enset only produces 117 kg/ha.
Figure 3. Average crop and grazing landholdings in Sidama Zone. Hectares include land for crops
Table 2. Area of crops planted by woreda, in hectares.
District Mean SD
Arbegona 1.64 1.00 0.61
Boricha 1.36 3.59 2.64
Lokka Abaya 1.07 0.61 0.57
Hawassa Zuria 0.98 0.75 0.77
Coefficient of variation
2015 JOURNAL OF ETHNOBIOLOGY 323
Fertilizer and manure are important for crop production. Enset relies on
manure from cattle to enhance productivity. Hence, cattle ownership and enset
production are intimately intertwined. Milk and butter are key ingredients for
raisame, a thick waasa porridge and staple food. Cattle ownership varies (Table 4).
Farmers in Arbegona own the most cattle (mean 53.4), farmers in Boricha own
the least (mean51.6). When crops fail, farmers sell livestock to purchase food;
hence, periodic drought in Boricha may explain the low number of cattle per
According to key informants, maize productivity can be increased by 100%
by using chemical fertilizer—50 kg of chemical fertilizer (one bag) can double the
output of a half hectare of maize. Sidama informants indicated that the chemical
fertilizer price was a constraint on maize productivity. Fertilizer was approxi-
mately 60 birr for 50 kg in 2000, but increased to 800 birr by 2012. Price hikes put
chemical fertilizer out of reach. Variation in maize productivity and fertilizer
exacerbated famine in Boricha in 2003. Sidama described a bumper 2001 maize
crop that caused a severe price decline, resulting in maize being less attractive in
Table 3. Productivity of enset and maize across the Sidama Zone.
Arbegona Boricha Lokka Abaya Hwa Zuria
kg/ha 168 279 499 884
26 376 482 726
N 2 13 6 73
Proportion 0.02 0.12 0.08 0.60
kg/ha 460 220 183 117
SD 884 143 170 66
Proportion 0.68 0.42 0.29 0.12
kg/ha 2275 533 1195
SD 2440 625 1364
Proportion 0.00 0.05 0.13 0.09
kg/ha 476 487 466 872
SD 474 435 731 709
Proportion 0.30 0.40 0.50 0.18
Table 4. Cattle owned and fertilizer expense among Sidama farms.
Cattle Fertilizer expense
District Mean SD
Mean SD CV
Arbegona 3.4 3.7 1.1 79.5 197.6 2.5
Boricha 1.6 1.5 1.0 141.0 262.1 1.9
Lokka Abaya 1.8 1.4 0.8 409.7 363.9 0.9
Hawassa Zuria 2.2 3.2 1.5 382.4 334.0 0.9
Coefficient of variation
324 QUINLAN et al. Vol. 35, No. 2
following years. Price increases in nitrogenous fertilizers associated with oil price
increases (Wright 2011) following the Multi-National Force Iraq War, coupled
with declines in maize prices, set the scene for food insecurity to follow. By 2012
the average expense for chemical fertilizer in our sample’s most maize-
dependent district (Hawassa Zuria) was 382 birr (Table 4), not enough to
fertilize a quarter hectare of maize.
We used OLS regression analysis to model productivity of Sidama crop
configurations (Table 5). We are especially concerned with effects of cattle (as
a proxy for manure input) and chemical fertilizer expense on production. Enset
yielded the least per year compared with maize farms (Model 1; Table 5). This is
a counterintuitive result given previous agricultural studies showing high enset
output per meter-squared (Pijls et al. 1995; Tsegaye and Struik 2001). A farmer
can grow many enset plants on a small plot, but slow maturation means only
a portion of enset grown is harvested in a year. In comparison, an entire maize
crop is harvested per season. One hectare of maize produced about 120 kg more
per year than did one hectare of enset averaged across districts (Model 1;
Table 5). Chemical fertilizer and manure inputs fully mediate this production
difference (Model 2; Table 5). Differences in production were not statistically
significant after controlling for soil nutrient inputs. Manure from a single cow
increases production by about 40 kg per hectare, while 100 birr of fertilizer
increases production by about 17 kg per hectare. This corroborates our
qualitative analysis: 800 birr of fertilizer, the cost of 50 kg, increased production
by 76% for .5 ha of maize.
There are significant productivity differences geographically (Model 3;
Table 5). Boricha and Lokka Abaya produced significantly less than Arbegona or
Table 5. OLS regression of productivity of Sidama farms in log kg of harvested crops.
Model 1 Adj
Model 2 Adj
=.14 Model 3 Adj
=.20 Model 4 Adj
Log kg crops produced
Hectares of crops 0.056 0.129 0.022 0.526 0.019 0.562 0.161 0.013
Enset only -0.408 0.018 -0.215 0.214 -0.010 0.958 -0.161 0.443
Maize-enset 0.156 0.589 -0.208 0.450 0.067 0.807 0.126 0.645
Enset-maize 0.046 0.791 0.019 0.907 0.308 0.094 0.309 0.097
Fertilizer expense in
Birr 0.001 0.000 0.001 0.000 0.001 0.001
Winsorized cattle 0.208 0.000 0.153 0.000 0.115 0.006
Boricha -0.623 0.000 -0.499 0.005
Lokka Abaya -0.752 0.000 -0.615 0.002
Hwa Zuria -0.025 0.901 0.044 0.825
Boricha X hectares
planted -0.372 0.001
Hwa Zuria X hectares
planted -0.341 0.053
Enset only X fertilizer -0.001 0.044
Constant 5.715 0.000 5.069 0.000 5.262 0.000 5.086 0.000
Note: Farmers who lost their entire crop or who did not plant enset or maize in the most recent year are excluded.
5R-squared adjusted for the number of variables
B5unstandardized regression coefficient adjusted for covariates; p5significance for B
2015 JOURNAL OF ETHNOBIOLOGY 325
Hawassa Zuria; this is noteworthy because Arbegona farmers specialize in enset
while Hawassa Zuria farmers specialize in maize. Farms in Boricha were less
productive per hectare and enset production did not improve with chemical
fertilizer inputs (Model 4; Table 5). Results for Boricha may reflect erosion and
soil depletion—targeted intervention areas for NGOs in Boricha. ‘‘Hectares
planted’’ was only a significant predictor in Model 4, suggesting two conclusions:
(1) production per hectare is variable across the districts, and (2) there is little
variation in farm size. Many Sidama farms have been subdivided to minimal size
over generations of partitioning for inheritance among sons.
Cattle are associated with improved enset production. In Arbegona, there
was no significant difference between farms growing only enset and those that
also grew maize as a secondary crop; hence, they were not distinguished in the
model. There were too few maize farms in Arbegona to indicate in analyses. In
Arbegona the number of cattle was the only significant predictor of enset
production—cattle increased productivity (Table 6). This result corroborates the
Sidama ethno-agricultural model of enset management where production
depends on manure inputs. The interaction between cattle and hectares planted
was not a significant predictor of enset production in Arbegona; likewise, small
stock and total TLU (biomass adjusted measure of mixed livestock) were not
significant predictors of production.
Sidama indicated that people need about five cattle to fertilize a good enset
crop. Given densely populated territory and perceived land shortage, we
expected the average number of cattle in Arbegona of 3.4 is optimal for the enset
complex. We treated number of cattle owned as a reference-coded variable
indicating a threshold herd size for enhanced enset production. Owning one or
two cows was not a significant improvement over none, though a trend toward
improved production is apparent (Table 7). Three cows, however, offered
a significant improvement in enset production. Each cow beyond three provided
little additional benefit, suggesting the mean of 3.4 in Arbegona may be optimal
given land constraints.
Table 6. OLS regression for log kg produced in four districts.
Woreda Arbegona N=98 Boricha N=89 L. Abaya N=72 H. Zuria N=115
log kg crops
BpB p Bp B p
Hectares of crops 0.217 0.199 -0.005 0.892 0.168 0.399 0.123 0.231
Enset only 0.626 0.122 -0.021 0.954 -0.711 0.005
Enset-maize 0.956 0.022 0.324 0.245 0.370 0.057
Maize-enset 1.899 0.021 0.412 0.106
Fertilizer expense in
birr 0.000 0.672 0.002 0.002 0.001 0.099 0.001 0.000
Winsorized cattle 0.279 0.012 -0.053 0.574 0.182 0.042 0.022 0.638
Constant 4.716 0.000 4.303 0.000 4.471 0.000 5.358 0.000
5.20 Adj R
5.14 Adj R
Note: Farmers who lost their entire crop or who did not plant enset or maize in the most recent year are excluded.
B5unstandardized regression coefficient adjusted for covariates; p5significance for B
5R-squared adjusted for the number of variables
326 QUINLAN et al. Vol. 35, No. 2
Mixed crops of enset and maize outperformed farms with only enset or
maize in Boricha (Table 6). Maize as the primary crop with enset as a secondary
crop appears to be the most productive farm configuration. Residents of Boricha
claim they need enset and maize to survive there. Fertilizer expense was
associated with increased productivity in Boricha, but cattle owned was not. The
lack of effect of cattle on production in Boricha may reflect the smaller grazing
area and enset pruning to feed cattle. Excessive pruning reduces enset’s
productivity (Tsegaye and Struik 2001). Given pasture shortage in Boricha (.37
ha vs. 1 ha in Arbegona), enset trimmings are an important fodder that may lead
to excessive pruning.
In Lokka Abaya, cattle owned was the only predictor of production and there
were no differences between crop configurations, nor was there any threshold
effect for cattle owned as in Arbegona.
Hawassa Zuria was the least enset dependent woreda. Enset by itself
performed poorly in Hawassa Zuria, and fertilizer inputs were significantly
associated with farm productivity.
Arbegona and Lokka Abaya showed little predictable variability with low r-
square values (.12 and .14 respectively compared to .20 and .37 for Boricha and H.
Zuria). If ‘‘unpredictable variability in the outcome of an adaptively significant
behavior’’ (Winterhalder and Leslie 2002:61) is an important component of risk,
then Arbegona and Lokka Abaya may be the most vulnerable agricultural
environments in the Sidama Zone. This approach to risk, proposed for analyses
of fertility, may be poorly operationalized for subsistence agriculture because it
does not account for differences in probability of failure across environments.
Productivity measured in kilograms disregards nutrient values. Tsegaye and
Struik’s (2001) agricultural experiments on enset production indicated 883 kj/
100 g of energy from enset, compared to the 1569 kj/100 g published values for
maize (2110 kcal/kg of enset vs. 3750 kcal/kg of maize). We used this conversion
rate to estimate kilocalories/person/day. We multiplied kg produced by kcal
values for enset and maize, divided that by 365 days, and then divided that value
by the number of people living in the household to estimate per capita energy
production. The natural log of kcal/day/person normalized model residuals.
Table 7. OLS regression with cattle as reference-coded variable.
log kg crops produced
Hectares of crops 0.240 0.165
Fertilizer expense in birr 0.000 0.616
Cattle (05reference) 1 1.320 0.107
2 1.574 0.054
3 2.002 0.013
4 2.151 0.017
Constant 3.721 0.000
Note: Farmers who lost their entire crop or who did not plant enset or maize are excluded.
B5unstandardized regression coefficient adjusted for covariates, p5significance for B
5R-squared adjusted for the number of variables
2015 JOURNAL OF ETHNOBIOLOGY 327
Analyses are not weighted for age and sex of household members, but rather
estimate energy per person.
The average Sidama farm produces about 785 kcal/day/person from enset
and maize (Table 8). Maize primary and enset secondary farms in Hawassa Zuria
have the greatest energy production, but there is huge variation (CV51.94). This
CV is due largely to one farm that produced more than 17,000 kcal/day/person.
(We Winsorized this value to the next highest value of 8219 kcal/day/person to
reduce its influence on the models.) Maize-only farms in Hawassa Zuria and
enset primary and maize secondary farms Arbegona and Hawassa Zuria yield
roughly equivalent energy per capita. Farms growing only enset produced
significantly less kcal/person than maize farms. Mixed farms were not
significantly different from maize-only farms (Model 1; Table 9). Nutrient
inputs significantly increased kcal production (Model 2; Table 9). Controlling
for geography, Lokka Abaya and Boricha produced significantly less kcal/
person/day than did Arbegona; there was no difference between Arbegona and
Hawassa Zuria (Model 3; Table 9). This suggests that the predominant crops for
Arbegona and Hawassa Zuria are a good fit for the local environments.
Interaction effects indicated differences in kcal/ha in Boricha, where farms
appear to be significantly less productive per hectare than in other woredas
(Model 4; Table 9). The effect of cattle was mediated by interaction effects. In the
final model (Table 9), enset-only farms produced significantly less energy than
maize-only farms, and mixed maize-primary/enset-secondary farms produced
significantly more energy per capita.
After back transformation, Model 4 (Table 9) gives predicted energy
production. The maximum predicted value is approximately 1623 kcal/
person/day for farms of one hectare with maize as the primary crop in Hawassa
Zuria with roughly 380 birr worth of fertilizer and manure from 2.2 cows. The
least productive farms in Boricha, growing 1.3 hectares of enset-only, produced
about 334 kcal/person/day with 1.6 cows and 140 birr worth of fertilizer (the
means for Boricha). This estimate may reflect the near-famine conditions
recurring in Boricha. Energy intake values do not include food from other
sources such as food aid, gifts, purchased foods, etc. Indeed, 45% of our Boricha
sample reported receiving food aid in the last year. Average enset-only and
mixed enset-maize farms in Arbegona with 3.4 cows and 79 birr of fertilizer
produced about 690 and 1250 kcal/day/person, respectively. Our energy
Table 8. Average kcal/day/person in four districts.
Total Maize Enset Maize-enset Enset-maize
Arbegona Mean 784 251 654 1127
876 191 762 1054
Boricha Mean 441 114 294 889 612
SD 667 133 364 956 863
Lokka Abaya Mean 616 1304 292 726 663
SD 848 1520 387 1095 787
Hawassa Zuria Mean (wins.) 1151 (1077) 1151 240 2529 (1719) 1082
SD 1827 (1274) 1269 158 4914 (2316) 671
Note: values in parentheses are Winsorized (see text).
SD 5standard deviation
328 QUINLAN et al. Vol. 35, No. 2
estimates compare to 880 kcal/day/person from enset (1100 kcal total) from
a study of the Gurage people 200 km north of Sidama (Pijls et al. 1995).
Crop Failure and Resilience
Analysis of productivity suggests crops respond to different highland,
lowland, and peri-urban environments with different nutrient inputs. We
examined the probability of recent crop loss for farm configurations in different
environments. We asked whether the household lost 50% or more of crops in one
season in the last five years. If they reported a loss, they were asked when the loss
occurred. Thirty-nine percent of our Sidama sample reported a recent crop loss.
Lokka Abaya and Hawassa Zuria were the riskiest environments, with 57%
reporting a loss in Lokka Abaya and 51% in Hawassa Zuria, followed closely by
Boricha at 48% (Table 10). Arbegona had a low risk of crop failure at only 3%. In
all woredas except Hawassa Zuria, enset only is the least risky farm configuration
with five-year loss at 24%. In Hawassa Zuria farming only enset is high risk with
80% of enset farmers reporting crop loss (Table 10).
Farming in Hawassa Zuria is risky, but potential for high productivity is
substantial. Farming in Arbegona offers high yields and low risk. We return to
risks and returns in the discussion section.
Finally, we examined ‘‘engineering resilience’’ of farm configurations.
Engineering resilience is time from crop loss to full recovery or the time it takes
a variable ‘‘displaced from equilibrium’’ to return to it (Pimm 1991). Given the
cross-sectional nature of our data, we cannot measure return to pre-shock
conditions precisely. We used a self-reported measure of household well-being as
a proxy. Participants reporting crop loss were asked to indicate whether the
household was worse off, better off, or the same now as before the crop loss.
Farmers reporting the same or better subjective household conditions were coded
Table 9. Multiple linear regression showing log kcal/day/person for enset and maize.
N=393 Model 1 Model 2 Model 3 Model 4
Hectares of crops 0.053 0.196 0.021 0.601 0.015 0.705 0.196 0.010
Enset only -1.030 0.000 -0.776 0.000 -0.487 0.033 -0.570 0.013
Maize-enset -0.203 0.517 -0.512 0.096 -0.171 0.576 -0.121 0.689
Enset-maize -0.302 0.113 -0.274 0.137 0.096 0.650 0.026 0.902
in birr 0.001 0.000 0.001 0.000 0.001 0.000
Winsorized cattle 0.076 0.001 0.045 0.056 0.020 0.423
Boricha -0.722 0.000 -0.660 0.001
Lokka Abaya -0.815 0.000 -0.723 0.001
Hwa Zuria -0.001 0.997 0.090 0.683
Boricha X hectares
planted -0.301 0.005
Constant 6.450 0.000 5.967 0.000 6.079 0.000 5.906 0.000
0.08 0.15 0.21 0.22
Note: Production of calories was winsorized for one farm with very high production with nearly twice the next
highest level of calorie production. Farmers who lost their entire crop or who did not plant enset or maize in the
most recent year are excluded.
B5unstandardized regression coefficient adjusted for covariates; p5significance for B
5R-squared adjusted for the number of variables
2015 JOURNAL OF ETHNOBIOLOGY 329
‘‘recovered.’’ We used hazard analyses and Kaplan-Meier failure functions to
model resilience of farm configurations. A Hazard Ratio (HR) is interpreted
similarly to an odds ratio in logistic regression: HR .1 indicates a greater
‘‘instantaneous likelihood’’ of an event. Here the event is recovery from crop loss,
and the HR models the likelihood of recovery per year. We used maize farms in
Boricha as the reference category. Farms in Hawassa Zuria were more resilient and
296% (HR53.96) more likely to have recovered from crop loss (Model 1; Table 11)
compared with maize only in Boricha. The Kaplan-Meier plot shows that about
85% of farms in Hawassa Zuria recovered in four years compared to 26% in
Boricha. Only 50% of Boricha farms recovered after six years (Figure 4). Boricha
and Lokka Abaya were not significantly different. Geographic differences,
however, were mediated by farm configuration: enset farms were significantly
less likely to recover than were maize farms independent of district (HR 50.16 and
0.14 for enset and enset-maize farms, respectively). The Kaplan-Meier Plot shows
nearly 100% of maize farms recovered in four years, whereas only about 50% of
enset farms recovered in six years (Figure 5). About 60% of maize farmers reported
recovering in three years or less. No doubt, these differences reflect the long life
cycle and processing time for enset compared with maize. There appear to be
potentially complex trade-offs in productivity, risk, and resilience for Sidama
farmers. Under the right circumstances, enset is as productive as maize and less
prone to crop loss, but enset has a much longer recovery time.
Qualitative interviews in Boricha (conducted by SJD and AS) show how enset
and maize have become complementary staples in some areas. Yet farmers
Table 11. Hazard ratios for return to pre-shock household condition.
Model 1 Model 2
L. Abaya 1.573 0.596 0.989 0.991
H. Zuria 3.960 0.009 1.422 0.598
Enset only 0.156 0.021
Maize 0.135 0.006
Note: Maize farm in Boricha is the reference category. Farms in Arbegona were excluded from this analysis as there
were too few reporting recent crop loss to include them as a separate category.
Table 10. Proportion of farms reporting a loss of 50% or more of crops in the recent past.
Maize Enset Maize-enset Enset-maize Total
Farms in Arbegona 2 77 0 34 113
Proportion lost half or more crops 0.00 0.01 0.06 0.03
Farms in Boricha 13 44 5 42 104
Proportion lost half or more crops 0.54 0.36 0.60 0.57 0.48
Farms in Lokka Abaya 6 21 9 36 72
Proportion lost half or more crops 0.50 0.38 1.00 0.47 0.51
Farms in Hawassa Zuria 73 15 11 22 121
Proportion lost half or more crops 0.49 0.80 0.36 0.81 0.57
330 QUINLAN et al. Vol. 35, No. 2
growing both enset and maize typically claim enset is their primary crop, even
when they produce more maize. More than 20% of Sidama farmers reporting
enset as their most important crop harvest more maize than enset. Controlling for
recent crop loss reduces probability of a mismatch between perception and
production at about 10% (analysis not shown).
According to older Sidama, enset is the life of Sidama people: by-products
from enset are important for rope for tethering animals and for house
construction. Many people still use dried enset leaves and fiber for mattresses.
Enset leaves serve as wrap and plates for food. Dry remains of harvested plants
Figure 4. Kaplan-Meier plot of resilience by Sidama District. The horizontal axis indicates years, and
the vertical axis indicates the proportion of the sample recovered. Boricha is the solid line and
reference category for hazards analysis in Table 12. Dotted line indicates Lokka Abaya, and the
dashed line indicates Hawassa Zuria.
Figure 5. Kaplan-Meier plot of resilience by farm configuration in Sidama Zone. The horizontal axis
indicates years, and the vertical axis indicates the proportion of the sample recovered. Maize farms are
indicated by the dashed line, which is the reference category for Model 2, Table 12. Dashed and dotted
lines indicate enset and mixed enset-maize farms, respectively.
2015 JOURNAL OF ETHNOBIOLOGY 331
are used for cooking fuel during the dry season. Sidama claim that enset
maintains soil nutrients much better than other crops. Enset is a sign of
household beauty, and a symbol of respect for the family.
Every Boricha informant in 2014, 34 adults (20 male) and 30 adolescents (15
male), reported that enset is crucial for survival during droughts. Sidama can
store enset much longer than any other crops they grow, and people agree that
wasa quality increases with age. Wasa can keep for three years, and the growing
plant stores energy that Sidama can either use when needed or leave to mature.
Sidama consider women who save wasa for a long time to be wise, and their
families will survive difficult times better than one who saves other crops.
Despite the recognized enset advantages, most Boricha farmers report that
enset takes only a third of their farmland; maize and cash crops occupy the
remainder. People give different reasons for diversification. Some say other crops
provide more cash for expenses for school, medicine, clothing, taxes, and
emergencies. Maize can be planted and harvested within a year. Other Sidama
mentioned a need for diet diversity: adults in Boricha said that wasa alone does
not provide enough energy, and maize provides fuel for hard work.
All Boricha adolescents report that they prefer to eat maize over wasa. Adults
report that adolescent sons consider farming enset a backward practice; they
prefer cash crops. Some adults report that adolescents do not know how to grow
enset. Lately, some Boricha parents eschew Sidama traditional land inheritance
rules by giving a small plot to their unmarried sons for chat production.
These factors contribute to the decline of enset farming in Boricha. However,
some people indicated a recent trend towards expanding enset cultivation in the
wake of recurring drought and crop failures. Sidama people typically do not sell
enset products, but that may be changing.
Efforts at marketing enset products is afoot in the region (Assoma n.d.).
Neighboring Koore farmers bring surplus enset by-products (bull’a) to local
markets for sale to middlemen who distribute it. This trade created new value-
chain networks for enset. Urban Ethiopians are gaining appreciation of enset as
a variant of national cuisine (Geda 2009).
Discussion and Conclusion
Ethiopians sometimes claim that enset farmers do not experience famine,
even during the worst Ethiopian famines (Brandt et al. 1997). Lay people and
researchers attribute this reduced vulnerability to the heartiness of the enset
plant, which can withstand dry periods of several months (Brandt et al. 1997;
Karlsson et al. 2013; Mohammed et al. 2013; Rahmato 1995; Shack 1971; Shigeta
1990). Perhaps the highlands, where enset grows best, are not as drought-prone
as other areas. While drought is rarely a concern to highland enset farmers, it is
a primary concern for mid- and lowlanders.
The benefits of enset appear highly dependent on local conditions. Highland
Arbegona appears to behave as expected of the model enset environment: crop
loss is infrequent, production is high, and the statistical relationship between
cattle and enset production conforms to the Sidama cultural model of enset-
cattle-human interdependence. In Hawassa Zuria, however, enset farms produce
332 QUINLAN et al. Vol. 35, No. 2
little, have a high risk of crop loss (80%, Table 10), and a long recovery time
compared with maize farms. Yet 30% of farms in Hawassa Zuria grow enset as
the primary crop. Enset farms may persist in Hawassa Zuria, because of the high
cultural value placed on enset farming and waasa as a traditional food. Hawassa
Zuria farmers, furthermore, may persist in dedicating substantial portions of
their farming to enset because they believe it to be drought resistant, following
local cultural models. As the archaeological record indicates with maize adoption
in eastern North America (Gremillion 1996; Hart 1999), and as Winterhalder and
Goland (1997) predict for agricultural change, a significant lag appears between
cultural models, farming practices, and climate change, leaving some Sidama
farmers at risk. Sidama say the annual rainfall has changed substantially in 40
years, especially at lower elevations. Prior to the mid-1970s rain was reliable and
sufficient. In terms of social-ecological systems theory, we may be witnessing
shift in a ‘‘basin of attraction’’ or ‘‘regime’’ (Walker et al. 2004) from enset
farming to maize farming as a central feature of Sidama livelihood in Hawassa
Diversity may promote resilience in social-ecological systems (Elmqvist et al.
2003). Biodiversity is a key for sustainable food security (FAO 2008; Kuhnlein
2014). We show that crop diversity may improve resilience at a regional
geographic scale—across the entire Sidama Zone. However, within districts, the
evidence is equivocal for the importance of diversity in staples. The best-
producing farms in our analysis were in Arbegona (specializing in enset) and
Hawassa Zuria (specializing in maize). In one district out of four, Boricha, mixed
enset and maize farms out-performed single crops in production, but not in risk of
crop loss. There may be substantial benefits to ‘‘bet hedging’’ by growing multiple
crops; however, diversity may not contribute more to resilience than a good fit between
the local environment and a single crop.
Ethnobiology focuses on traditional subsistence practices as the foundation
of adaptive adjustment (Braje and Rick 2013; Lepofsky and Feeney 2013; Nolan
and Pieroni 2014), but ecological change may render millennia-old management
systems unstable, providing a role for ethnobiology as new traditions emerge
(Lepofsky 2009). In sum, the diverse Sidama landscape does not lend itself to
‘‘ideal cultural models’’ of agriculture. Rather, smallholders strategically assess
the mix of crops, soil, water, and space. With climate change in full swing in
Ethiopia, guided culture change for adaptation is likely to be an important
component of food security.
Washington State University Initiative for Global Innovation Studies provided
funding thanks to Dr. Paul Whitney. We are deeply thankful to the Sidama for their
kindness and patience. Special thanks to Misters Muleka, Sisay, Israel, Temesgen and
Solomon for their professional help and friendship. Thanks to Mr. Mulye Girma, Sidama
Zone, and woreda officials for their invaluable assistance. Thanks to Drs. Thomas Rotolo
and Jon Yoder for help in design and project development. Many thanks to Drs. Walelign
Tedesse Robele, and President Yosef of Hawassa University for encouraging and
facilitating our collaborative efforts. Any shortcomings in this study are the authors’ alone.
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