Small-scale fishing: Income, vulnerability and livelihood strategies at Lake Itezhi-Tezhi, Zambia

Figures & data

Figure 1. Map showing Lake Itezhi-Tezhi fishery, Kafue National Park, and GMAs (Source: Authors).

Figure 2. Sustainable Livelihood Framework (Source: DFID (1999)).

Table 1. Five livelihood assets or capacities.

Assets/Capital	Description
Human	Skills, knowledge, good health and ability to work that together enable fishers to pursue different livelihood strategies and achieve their livelihood objectives.
Social	Social resources which fishers can draw on including informal relationships of trust, reciprocity and exchange with families, friends and neighbours as well as more formalised groupings (e.g. community and faith groups).
Physical	Tools and equipment (fishing nets, canoes, and others.) that fishers need to be productive along with the necessary infrastructure needed to function, for example, affordable transport and energy, decent housing and access to information.
Financial	Earned income, pensions, savings, credit facilities, state benefits, child maintenance, and others.
Natural	Fish, soil, the weather, livestock, and crops which many poor fishers in developing countries rely on to produce their food and to gain an income.

Sources: Adapted from DFID (1999) and May et al. (2009).

Table 2. Composition of the strata for Lake Itezhi-Tezhi fishery.

Strata	Number of sampled fishers in each stratum	Number of sampled fishing locations in each stratum	Number of focus group discussions in each stratum
Stratum 1	266	17	5
Stratum 2	101	10	3^a
Stratum 3	84	13	4
Total	451	40	12

Note: ^a - One of the focus group discussions (FGDs) in Stratum 2 was not conducted due to logistical challenges. However, this FGD was replaced with another one comprising women fish traders at Lake Itezhi-Tezhi habour in order to capture their perspectives as well.

Source: Authors.

Table 3. Characteristics of human assets in the fishing community (n = 451).

Human Capital		% of fishers
Education level	None to completion of primary education	86
	Secondary to tertiary education	14
Marital status	Married	71
	Single	21
	Widowed, divorced	8
Age group	18–40 years	65
	Above 40 years	35
Residence status	Immigrant fisher	81
	Resident fisher	19

Figure 3. Number of household members involved in fishing-related activities (n = 577).

Figure 4. Number of household members involved in the fish selling business (n = 231).

Figure 5. Percentages of fishers’ accessibility to social amenities within Lake Itezhi-Tezhi fishing community in relation to research strata.

Table 4. Factors that influenced fishing income levels among fishers (n = 451; R²= 0.06; p < 0.001).

Variables	Parameter Estimates
	Estimate Coefficient	Std. Error	P Value
Fishing income = Less than $100	18.646	0.507	0.000
Fishing income = $100.1–$200	19.804	0.507	0.000
Education
Some primary education	18.613	0.493	0.000
Completed primary education	19.268	0.507	0.000
Some secondary education	18.981	0.547	0.000
Completed secondary education	19.312	0.000	0.000
None	0^a	.
Research Stratum
One	0.791	0.237	0.001
Two	0.933	0.282	0.001
Three	0^a	.

Note: ^aSet at zero because it is redundant and is a reference variable

Table 5. Percentages of fishers based on major income sources and income ranges.

Income Ranges	Major Income Sources (n = 451)
	Fishing Income/Month	Crop Production Income/Year	Livestock Production Income/Year	Other Income^a/Year
0	0	39.2	60.8	39.5
$0.1–$100	30.6	10.2	4.9	5.5
$100.1–$200	26.6	3.2	0.2	0.7
More than $200	42.8	3.5	0.4	2.3
Not sure	0	43.9	33.7	31.0
Total %	100	100	100	100

^aincludes trading in non-fish items, charcoal, employment, and others (stone crushing, motor repairing, bricklaying).

Table 6. Ordinal logistic regression prediction of whether or not fishers’ ownership of physical assets was dependent on different levels of fishing income. Reference fishing income = more than $200; n = 451; * Significant (Sig.) at p < 0.05 or ** p ≥ 0.001, ns: Not significant at p ≥ 0.05.

Fishers’ Physical Assets	Fishing Income	Estimate Coefficient	Pseudo R^2
Mud and poles/thatched houses	Less than $100	0.934**	0.042
	$100.1–$200	0.444ns
Unburnt bricks/thatched houses	Less than $100	0.212ns	–
	$100.1–$200	0.234ns
Unburnt bricks/iron sheet roofed houses	Less than $10	–0.725**	0.026
	$100.1–$200	–0.337ns
Burnt bricks/iron sheet roofed houses	Less than $100	–0.878*	0.022
	$100.1–$200	–0.148ns
Cement blocks/iron sheet roofed houses	Less than $100	–1.087ns	–
	$100.1–$200	–0.167ns
Fishing nets	Less than $100	–0.694**	0.028
	$100.1–$200	–0.716**
Fishing canoes	Less than $100	–1.032**	0.06
	$100.1–$200	–0.673**
Bicycles	Less than $100	–0.8**	0.045
	$100.1–$200	–0.782**
Radios	Less than $100	–0.782**	0.044
	$100.1–$200	–0.754**
Cell phones	Less than $100	–1.343**	0.105
	$100.1–$200	–1.017**
Solar panels	Less than $100	–0.745**	0.039
	$100.1–$200	–0.724**
House tables	Less than $100	–0.837**	0.058
	$100.1–$200	–0.93**
House beds	Less than $100	–0.89**	0.047
	$100.1–$200	–0.562*

Figure 6. Preferred selling locations in relation to percentages of fishers’ fishing income levels in each research stratum.

Table 7. Ordinal logistic regression predictions of whether or not fishers’ expenditures were dependent on different levels of fishing income. Reference for fishing income = more than $200; n = 451; * Significant at p < 0.05 or ** p < 0.001, ns: Not significant at p ≥ 0.05.

Expenditures	Fishing Income	Estimate Coefficient	Pseudo R^2
Expenditure on food stuffs	Less than $100	−0.714**	0.032
	$100.1–$200	−0.587**
Expenditure on medication	Less than $100	0.137 ns	–
	$100.1–$200	0.117 ns
Expenditure on school fees	Less than $100	−0.671**	0.03
	$100.1–$200	−0.522*
Expenditure on transport and energy sources	Less than $100	−0.709**	0.032
	$100.1–$200	−0/592*
Expenditure on alcohol and beverages	Less than $100	−0.346 ns	–
	$100.1–$200	−0.136 ns

DFID (Department for International Development), 1999. Sustainable livelihoods guidance sheets. http://www.livelihoodscentre.org/documents/20720/ (Accessed on 21 March 2017).

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May, C, Brown, G, Cooper, N, & Brill, L, 2009. The sustainable livelihoods handbook: an asset-based approach to poverty. UK: Church Action on Poverty/Oxfam GB.

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