{"title":"尼日利亚雨养农民对气候变化的适应策略","authors":"A. Towolawi","doi":"10.5455/jbau.120899","DOIUrl":null,"url":null,"abstract":"Climate change puts food system at risk if there are no effective adaptation strategies. The study investigated influence of farmers' demographics (education, age and gender) on twelve considerable factors for adaptation strategies across four (Edo, Ondo, Benue and Niger) States in Nigeria by subjecting 1600 copies of pretest questionnaire to stepwise multiple regression analysis. The factors are Years of Practice (YoP), Farm Size, (FS), Places of Selling Produce (PSP), Use of Family as Labour (UFL), Use of Hired Labour (UHL), Transportation Situation (TS), Diversification into Non-farming Activities (DINA), Substitutions of Scarce Resources (SSR), Government Agriculture Extension Services (GAES), Awareness of Climate Information (ACI), Access to Farm Input (AFI), and Access to Credit Services (ACS). The model entered UFL, PSP and ACI in Benue State, YoP, UHL, SSR, and TS in Edo State, UFL, PSP, DINA, ACS, AFI, UHL and SSR in Niger State, and UFL and ACS in Ondo State. The Durbi-Watson values of all the models were ranged from 1.568 in Benue State to 1.905 in Niger State, indicating positive autocorrelation. The ANOVA indicated that F-test was highly significant for each State’s model and explained a significant variation in the influence of farmers’ demographics. Tolerance > 0.1 and Variable Inflation Factor < 10 showing there was multicollinearity and the variables were highly correlated. In conclusion, the adaptation strategies to tackle climate change effects are collectively determined by the farmers’ demographics.","PeriodicalId":15283,"journal":{"name":"Journal of Bangladesh Agricultural University","volume":"47 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptation Strategies of Rain-fed Farmers to Climate Change in Nigeria\",\"authors\":\"A. Towolawi\",\"doi\":\"10.5455/jbau.120899\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Climate change puts food system at risk if there are no effective adaptation strategies. The study investigated influence of farmers' demographics (education, age and gender) on twelve considerable factors for adaptation strategies across four (Edo, Ondo, Benue and Niger) States in Nigeria by subjecting 1600 copies of pretest questionnaire to stepwise multiple regression analysis. The factors are Years of Practice (YoP), Farm Size, (FS), Places of Selling Produce (PSP), Use of Family as Labour (UFL), Use of Hired Labour (UHL), Transportation Situation (TS), Diversification into Non-farming Activities (DINA), Substitutions of Scarce Resources (SSR), Government Agriculture Extension Services (GAES), Awareness of Climate Information (ACI), Access to Farm Input (AFI), and Access to Credit Services (ACS). The model entered UFL, PSP and ACI in Benue State, YoP, UHL, SSR, and TS in Edo State, UFL, PSP, DINA, ACS, AFI, UHL and SSR in Niger State, and UFL and ACS in Ondo State. The Durbi-Watson values of all the models were ranged from 1.568 in Benue State to 1.905 in Niger State, indicating positive autocorrelation. The ANOVA indicated that F-test was highly significant for each State’s model and explained a significant variation in the influence of farmers’ demographics. Tolerance > 0.1 and Variable Inflation Factor < 10 showing there was multicollinearity and the variables were highly correlated. In conclusion, the adaptation strategies to tackle climate change effects are collectively determined by the farmers’ demographics.\",\"PeriodicalId\":15283,\"journal\":{\"name\":\"Journal of Bangladesh Agricultural University\",\"volume\":\"47 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Bangladesh Agricultural University\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5455/jbau.120899\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bangladesh Agricultural University","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5455/jbau.120899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptation Strategies of Rain-fed Farmers to Climate Change in Nigeria
Climate change puts food system at risk if there are no effective adaptation strategies. The study investigated influence of farmers' demographics (education, age and gender) on twelve considerable factors for adaptation strategies across four (Edo, Ondo, Benue and Niger) States in Nigeria by subjecting 1600 copies of pretest questionnaire to stepwise multiple regression analysis. The factors are Years of Practice (YoP), Farm Size, (FS), Places of Selling Produce (PSP), Use of Family as Labour (UFL), Use of Hired Labour (UHL), Transportation Situation (TS), Diversification into Non-farming Activities (DINA), Substitutions of Scarce Resources (SSR), Government Agriculture Extension Services (GAES), Awareness of Climate Information (ACI), Access to Farm Input (AFI), and Access to Credit Services (ACS). The model entered UFL, PSP and ACI in Benue State, YoP, UHL, SSR, and TS in Edo State, UFL, PSP, DINA, ACS, AFI, UHL and SSR in Niger State, and UFL and ACS in Ondo State. The Durbi-Watson values of all the models were ranged from 1.568 in Benue State to 1.905 in Niger State, indicating positive autocorrelation. The ANOVA indicated that F-test was highly significant for each State’s model and explained a significant variation in the influence of farmers’ demographics. Tolerance > 0.1 and Variable Inflation Factor < 10 showing there was multicollinearity and the variables were highly correlated. In conclusion, the adaptation strategies to tackle climate change effects are collectively determined by the farmers’ demographics.