Pierre Marie Chimi , William Armand Mala , Jean Louis Fobane , Karimou Ngamsou Abdel , Baruch Batamack Nkoué , Lethicia Flavine Feunang Nganmeni , Eusebe Ydelphonse Nyonce Pokam , Sophie Patience Endalle Minfele , John Hermann Matick , Franc Marley Tchandjie , François Manga Essouma , Joseph Martin Bell
{"title":"Factors affecting decision-making to strengthen climate resilience of smallholder farms in the Centre region of Cameroon","authors":"Pierre Marie Chimi , William Armand Mala , Jean Louis Fobane , Karimou Ngamsou Abdel , Baruch Batamack Nkoué , Lethicia Flavine Feunang Nganmeni , Eusebe Ydelphonse Nyonce Pokam , Sophie Patience Endalle Minfele , John Hermann Matick , Franc Marley Tchandjie , François Manga Essouma , Joseph Martin Bell","doi":"10.1016/j.csag.2024.100004","DOIUrl":null,"url":null,"abstract":"<div><p>This study examined the resilience to climate change of smallholder family farms in the Centre Region of Cameroon. Data were collected using a mixed-methods strategy and analyzed using descriptive, multivariate, and inferential statistics. Family farms exhibited a mean climate resilience index of 0.46 (medium), with the Ntui, Mbangassina, Batchenga, and Obala regions scoring 0.42, 0.44, 0.47, and 0.51, respectively. Family farmers had a high transformation capacity (59.07 %), a low adaptation capacity (32.10 %), and a very low absorption capacity (8.82 %). Logistic regression revealed significant causal relationships (<em>p</em> < 0.05) between the capacity of the farms to adapt to climate fluctuations and change and annual income, access to agricultural inputs, access to agricultural machinery, and membership in a farmers organization. These are the primary factors that could significantly increase climate resilience in Cameroonian family farms. Consequently, policymakers in these regions and beyond should consider these as indicators when developing policies to strengthen the climate resilience of local agricultural systems. In doing so, they should also consider community monitoring and indigenous knowledge, which can help bridge the gap between local adverse impacts and the necessary adaptations to climate change.</p></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"1 1","pages":"Article 100004"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2950409024000042/pdfft?md5=30e1d6a9348ce693c369713b8bf718f9&pid=1-s2.0-S2950409024000042-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climate Smart Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950409024000042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study examined the resilience to climate change of smallholder family farms in the Centre Region of Cameroon. Data were collected using a mixed-methods strategy and analyzed using descriptive, multivariate, and inferential statistics. Family farms exhibited a mean climate resilience index of 0.46 (medium), with the Ntui, Mbangassina, Batchenga, and Obala regions scoring 0.42, 0.44, 0.47, and 0.51, respectively. Family farmers had a high transformation capacity (59.07 %), a low adaptation capacity (32.10 %), and a very low absorption capacity (8.82 %). Logistic regression revealed significant causal relationships (p < 0.05) between the capacity of the farms to adapt to climate fluctuations and change and annual income, access to agricultural inputs, access to agricultural machinery, and membership in a farmers organization. These are the primary factors that could significantly increase climate resilience in Cameroonian family farms. Consequently, policymakers in these regions and beyond should consider these as indicators when developing policies to strengthen the climate resilience of local agricultural systems. In doing so, they should also consider community monitoring and indigenous knowledge, which can help bridge the gap between local adverse impacts and the necessary adaptations to climate change.