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  • This study revealed that local agro-pastoralists were quite aware of their own actions that could influence the changing abundance of the natural forage resources. Moreover, the local informants suggested means through which their rich LEK in the traditional management and regulation of plant resources including forage plants could be applied. This is necessary for them to tackle negative effects of the ecological drivers to changing forage plants communities especially crops. One of the topmost suggestions made by local agro-pastoralists was that cutting down of trees for charcoal production and fuel wood should be stopped, while afforestation of useful trees should be encouraged by fellow farmers to increase the frequency of rainfall incidences and increase soil fertility.

  • This table contains relevant socio-demographic variables of local agro-pastoralists(and including varying climatic aridity)and number of valuation criteria cited from 2012 to 2013. The number of valuation criteria for the rainy season, dry season, cattle, goats and sheep are captured in this table.

  • Recording local ecological knowledge (LEK) is a useful approach to understanding interactions of the complex social-ecological systems. In spite of the recent growing interest in LEK studies on the effects of climate and land use changes, livestock mobility decisions and other aspects of agro-pastoral systems, LEK on forage plants has still been vastly under-documented in the West African savannas. Using a study area ranging from northern Ghana to central Burkina Faso, we thus aimed at exploring how aridity and socio-demographic factors drive the distributional patterns of forage-related LEK among its holders. With stratified random sampling, we elicited LEK among 450 informants in 15 villages (seven in Ghana and eight in Burkina Faso) via free list tasks coupled with ethnobotanical walks and direct field observations. We performed generalized linear mixed-effects models (aridity- and ethnicity-based models) and robust model selection procedures. Our findings revealed that LEK for woody and herbaceous forage plants was strongly influenced by the ethnicity-based model, while aridity-based model performed better for LEK on overall forage resources and crop-related forage plants. We also found that climatic aridity had negative effect on the forage-related LEK across gender and age groups, while agro- and floristic diversity had positive effect on the body of LEK. About 135 species belonging to 95 genera and 52 families were cited. Our findings shed more light on how ethnicity and environmental harshness can markedly shape the body of LEK in the face of global climate change. Better understanding of such a place-based knowledge system is relevant for sustainable forage plants utilization and livestock production.

  • This table contains survey data whether the forage resources cited by local agro-pastoralists were many, few or rare in numbers.

  • The free list data was generated from ethnobotanical interviews which were carried out in northern Ghana and southern-central Burkina Faso. This dataset only contains 450 interviews from 15 villages (seven in Ghana and eight in Burkina Faso) to obtain a balanced dataset for further statistical analysis.

  • The main topic of the survey is the assessment of the impact of 2012 flood on income and expenditure and poverty status of farmers. Twelve farmers in 19 villages in two municipalities (Malanville and Karimama) have been interviewed.

  • This table contains survey data whether the forage resources cited by local agro-pastoralists were increasing or decreasing rapidly or gradually or were being stable or they had no idea at all.

  • The data set contains the applications to the WASCAL Farmer Innovation Contest. The contest took place in the years 2012-2015, respectively, in the Upper East Region in Ghana. Eligible to partake in the contest were local small-scale farmers form the region. Their agricultural innovations could be either of technical, institutional or organisational kind. A broad range of innovation themes were covered, such as animal husbandry, crop management or storage innovations. The table provides information about the applicants, e.g. basic demographics, and their innovations, e.g. theme of innovation, problem addressed, or obstacles and costs in applying the innovations. The data was collected in questionnaires that served as the application to the contest. Local extension officers assisted in the application process. In the final step, a jury of experts evaluated the innovations and determined the contest winners. Winners of the contest were awarded with material or monetary prices. Additionally, the data set provides basic descriptive statistics for all contest runs, e.g. share of pest or disease related innovations of total innovations.

  • This survey aims to collect data on farmers in the Niger basin of Benin. The data collected are relative to: (i) demographic information; (ii) crop production; (iii) livestock production; (iv) off-farm activities, and wages; (v) Access to extension, markets, credit, food consumption and social capital; (vi) climate change perception and shocks; (vii) adaptation strategies; (viii) household assets, and basic services. Three-stage sampling was used. First, municipalities were randomly selected within each agro-ecological zone (AEZ) based on their number of agricultural households. Second, villages were randomly selected within selected municipalities. Finally, random farm households were selected within selected villages. Therefore, the municipalities were randomly selected within each AEZ (AEZ I: one municipality, AEZ II: two municipalities, AEZ III: three municipalities, and AEZ IV: one municipality). The choice of the number of municipalities per AEZ is linked to the number of municipalities covered by AEZs I and IV (they covered two municipalities, and it has been decided to select one of the two). The number of municipalities for the AEZs II and III was determined proportionally to their size, referring to the size of AEZ I as a reference. Only four out of the five AEZs covered by the basin are considered, namely AEZ I (totally), AEZ II (totally), AEZ III (partially), and AEZ IV (partially). AEZ V was disregarded because only one of its municipalities is located within the Niger basin and it is a small part of the municipality that is included in the basin. Moreover, Pèrèrè was disregarded, because this municipality is partially covered by the basin (just a small part). Similarly, two municipalities that are partially included in the basin within AEZ III were avoided (Kouandé was maintained because its major part is within the basin). The municipalities were selected within each AEZ by the means of probability-proportional-to-size (PPS). Finally the municipalities that were chosen are: Malanville in AEZ I, Banikoara and Kandi in AEZ II, Bembèrèkè, Kouandé, and Nikki in AEZ III, and Natitingou in AEZ IV. The sample size was 545 agricultural households allocated across selected municipalities by the means of N-proportional allocation . Moreover, some adjustments have been made due to logistical constraints. Based on the allocation of the sample size across municipalities, it has been decided to allocate twenty households per villages, meaning four villages should be surveyed in each municipality, except Natitingou (three villages) and Kandi (due to the fact that one village of Kandi was already randomly selected for the pilot survey). At the end of the process, 28 villages had been surveyed. Due to logistical constraints, twenty agricultural households were not surveyed in every village.

  • This dataset describe household survey conducted in the Vea watershed of Ghana between the periods May 2013 to February 2014. It describes several household characteristics such as age, gender, income sources, agricultural production levels, Occurrence of droughts and floods as well as the impact of these hazards. The data also include several derived parameters such as household income, household size in adult equivalent scale, Tropical livestock units and poverty prevalence.