Assessing the Sensitivity of Small-Scale Fishery Groups to Climate Change in Lake Kariba, Zimbabwe
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Research Design
2.2.1. Development of Questionnaire to Measure First Order Stressors
2.2.2. Primary Data Collection and Analysis
3. Results
3.1. Community Characteristics and Livelihood Assets
3.2. Threats Affecting Fishers and Conflicts with Other Lake Users
4. Discussion
4.1. Community Characteristics and Livelihood Assets
4.2. Threats Affecting Fishers and Conflicts with Other Lake Users
4.3. Linking Sensitivity with Exposure and Adaptive Capacity
4.4. Policy Suggestions to Reduce Sensitivity
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Indicators | Variables | References |
---|---|---|
Community characteristics and assets | ||
Sex | No. of men that were interviewed No. of women that were interviewed | [41,43] |
Education | Education level of the interviewee | [44] |
Household income from fishing | Average daily catch (kg/day) × fish price ($1.50/kg) | [22,41,45,46] |
Livelihood Activities | Dependence on fisheries, fish gear making, aquaculture | [24,41,45,47,48,49] |
Assets | Fishing gear, boats, fishing permit, crop field, livestock (cattle, goats, chicken) | [9,22,40,41,50] |
Fishing gear access | Places where fishers go to access fishing gear | [42,51] |
Fish processing (post-harvest losses) | Immediate sale of fish Salting and drying Refrigeration | [1,52] |
Household diet (Nutrition) | No. of days in a week that people eat fish, meat, and vegetables | [41,47,49,53] |
Threats and conflicts (stressors) | ||
Events that disrupt fishing | low water levels, winds, storms and wildlife attacks. | [1,40,42,44,47,49,54,55] |
Conflicts | Conflicts with other lake users (commercial fishery, aquaculture, tourism, and crocodile farming) | [42,56] |
Socio-ecological | Increase in fishing pressure | [40,44] |
Financial | Loans/credit access | [23,42,57] |
Group | Village | Total Number of Households | Sampled Households | Sampling Ratio % |
---|---|---|---|---|
Fishing camps | Gache-gache | 41 | 26 | 63.4 |
Fothergill | 32 | 27 | 84.4 | |
Nyaodza | 39 | 31 | 79.5 | |
River range | 5 | 3 | 60 | |
King’s camp | 27 | 23 | 85.2 | |
Sub-total | 144 | 110 | 76.4 | |
Fishing villages | Nematombo | 56 | 24 | 42.9 |
Nyamunga | 54 | 26 | 48.1 | |
Dandawa | 55 | 29 | 52.7 | |
Mudzimu | 51 | 25 | 49.0 | |
Musambakaruma | 59 | 31 | 52.5 | |
Sub-total | 275 | 135 | 49.1 | |
Total | 419 | 245 | 58.5 |
Indicators | Variables | Fishing Camps | Fishing Villages | Total | X2/U′ |
---|---|---|---|---|---|
(n = 110) | (n = 135) | (n = 245) | |||
Sex | Total men | 103 (94%) | 111 (82%) | 214 (87%) | * |
Total women | 7 (6%) | 24 (18%) | 31 (13%) | ||
Education | Primary education | 39 (36%) | 66 (49%) | 105 (43%) | * |
Secondary education | 64 (58%) | 69 (51%) | 133 (54%) | ||
High School | 5 (5%) | 0 | 5 (2%) | ||
Vocational training | 0 | 0 | 0 | ||
College diploma | 1 (1%) | 0 | 1 | ||
University degree | 1 (1%) | 0 | 1 | ||
Household income from fishing | Income | USD16 ± 11.5 | USD11 ± 10.6 | *** | |
Livelihood activities (Dry season) | Only depend on fishing | 91 (83%) | 109 (81%) | 200 (82%) | |
Aquaculture | 0 | 14 (10%) | 14 (6%) | *** | |
Fishing gear making | 6 (6%) | 4 (3%) | 10 (4%) | ||
Fishing gear trading | 1 (1%) | 0 | 1 | * | |
Crops | 3 (3%) | 2 (2%) | 5 (2%) | ||
Livelihood activities | Only depend on fishing | 57 (52%) | 100 (74%) | 157 (64%) | *** |
(Wet season) | Aquaculture | 0 | 14 (10%) | 14 (6%) | *** |
Fishing gear making | 5 (5%) | 4 (3%) | 9 (4%) | ||
Fishing gear trading | 1 (1%) | 0 | 1 | * | |
Crops | 39 (36%) | 12 (9%) | 51 (21%) | *** | |
Livelihood Assets | Boats | 34 (31%) | 48 (36%) | 83 (34%) | |
Fishing gear (nets & rods) | 66 (60%) | 109 (81%) | 175 (71%) | *** | |
Fishing permit | 14 (13%) | 48 (36%) | 62 (25%) | *** | |
Crop field | 52 (47%) | 34 (25%) | 86 (35%) | *** | |
Cattle | 23 (21%) | 7 (5%) | 30 (12%) | *** | |
Goats | 24 (22%) | 28 (21%) | 51 (21%) | ||
Chickens (Poultry) | 14 (13%) | 23 (17%) | 36 (15%) | ||
Fishing gear access | Accessed locally | 28 (26%) | 75 (56%) | 103 (42%) | *** |
Capital city | 61 (56%) | 51 (38%) | 112 (46%) | ** | |
Zambia | 15 (14%) | 5 (4%) | 20 (8%) | * | |
Other | 8 (7%) | 11 (8%) | 19 (8%) | ||
Fish processing | Salting & drying | 10 (9%) | 36 (23%) | 46 (19%) | *** |
Refrigeration | 3 (3%) | 0 | 3 (1%) | ||
Immediate sale | 107 (97%) | 130 (90%) | 237 (97%) | ||
Household diet | Fish | 6.08 | 5.34 | 5.67 | *** |
Meat | 0.36 | 0.19 | 0.26 | * | |
Vegetables | 3.04 | 3.45 | 3.27 | * |
Indicators | Variables | Fishing Camps (n = 110) | Fishing Villages (n = 135) | Total (n = 245) | X2 |
---|---|---|---|---|---|
Events that disrupt fishing | Low water levels | 35 (32%) | 45 (33%) | 80 (33%) | |
Winds | 106 (96%) | 134 (99%) | 140 (98%) | ||
Storms | 23 (21%) | 18 (13%) | 41 (17%) | *** | |
Wildlife attacks | 68 (62%) | 111 (82%) | 179 (73%) | ||
Conflicts with other lake users | Tourism | 23 (21%) | 6 (4%) | 29 (12%) | *** |
Aquaculture | 4 (4%) | 3 (2%) | 7 (3%) | ||
Commercial fishery | 35 (32%) | 48 (36%) | 83 (34%) | ||
Crocodile farming | 3 (3%) | 5 (4%) | 8 (3%) | ||
Other | 18 (16%) | 30 (22%) | 48 (20%) | ||
Increase in fishing pressure | Yes | 69 (63%) | 113 (84%) | 182(74%) | *** |
Lack of access to loans | No | 107 (97%) | 133 (98%) | 240 (98%) |
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Ndhlovu, N.; Saito, O.; Djalante, R.; Yagi, N. Assessing the Sensitivity of Small-Scale Fishery Groups to Climate Change in Lake Kariba, Zimbabwe. Sustainability 2017, 9, 2209. https://doi.org/10.3390/su9122209
Ndhlovu N, Saito O, Djalante R, Yagi N. Assessing the Sensitivity of Small-Scale Fishery Groups to Climate Change in Lake Kariba, Zimbabwe. Sustainability. 2017; 9(12):2209. https://doi.org/10.3390/su9122209
Chicago/Turabian StyleNdhlovu, Nobuhle, Osamu Saito, Riyanti Djalante, and Nobuyuki Yagi. 2017. "Assessing the Sensitivity of Small-Scale Fishery Groups to Climate Change in Lake Kariba, Zimbabwe" Sustainability 9, no. 12: 2209. https://doi.org/10.3390/su9122209