影响加强喀麦隆中部地区小农农场气候适应能力决策的因素

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
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引用次数: 0

摘要

本研究考察了喀麦隆中部地区小农家庭农场对气候变化的适应能力。采用混合方法收集数据,并使用描述性、多变量和推理统计进行分析。家庭农场的平均气候适应力指数为 0.46(中等),恩图伊、姆班加西纳、巴特琴加和奥巴拉地区的指数分别为 0.42、0.44、0.47 和 0.51。家庭农场主的转化能力较高(59.07%),适应能力较低(32.10%),吸收能力极低(8.82%)。逻辑回归显示,农场适应气候波动和变化的能力与年收入、获得农业投入的机会、获得农业机械的机会以及农民组织成员资格之间存在明显的因果关系(p < 0.05)。这些都是可以显著提高喀麦隆家庭农场气候适应能力的主要因素。因此,这些地区及其他地区的决策者在制定加强当地农业系统气候适应能力的政策时,应将这些因素作为指标加以考虑。在此过程中,他们还应考虑社区监测和本土知识,这有助于缩小当地不利影响与必要的气候变化适应之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Factors affecting decision-making to strengthen climate resilience of smallholder farms in the Centre region of Cameroon

Factors affecting decision-making to strengthen climate resilience of smallholder farms in the Centre region of Cameroon

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.

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