Multilevel predictors of climate change beliefs in Africa

Abstract

Although Africa is the most vulnerable region to climate change, little research has focused on how climate change is perceived by Africans. Using random forest methodology, we analyze survey and climate data from second-order political boundaries to explore what predicts climate change beliefs in Africa. We include five different dimensions of climate change beliefs: climate change awareness, belief in anthropogenic climate change, risk perception, the need to stop climate change, and self-efficacy. Based on these criteria we identify five key results: (1) climate change in Africa is largely perceived through its negative impacts on agriculture; (2) actual changes in local climate conditions are related to climate change beliefs; (3) authoritarian and intolerant ideologies are associated to less climate change awareness, and a diminished risk perception and belief that it must be stopped; (4) women are less likely to be aware of climate change, and (5) not speaking French, English or Portuguese is linked to a hindered understanding of climate beliefs. Our combined results can help policy makers better understand the need to jointly consider the multilevel complexities of individual beliefs and hydroclimatic data for the development of more accurate adaptation and mitigation strategies to combat the impacts of climate change in Africa.

Fig 1. Key predictors for climate change awareness, anthropogenic climate change, and climate change-related risk perception.

Top 15 predictors of climate change awareness (A) (69.4% prediction accuracy), human causation of climate change (C) (63.4% prediction accuracy), and risk perception (E) (73.9% prediction accuracy). (B) Partial dependence plot (PDP) of gender (female), access to online news (news tech), being favourable to one-party rule (authoritarian), and perceived agricultural conditions (agric. cond.) about climate change awareness. (D) PDP of mean temperature anomalies (temp. anom.), precipitation anomalies (precip. anom.), trust in institutions (trust institutions), and access to online news (news tech) over belief in human causation of climate change. (F) PDP of belief in human causation of CC (CC human cause), perceived severity of drought (drought percep.), perceived agricultural conditions (agric. cond.) and being favourable to one-man rule (authoritarian) over climate change risk perception.

Fig 2. Key predictors of need to stop climate change and self-efficacy.

Top 15 predictors of need to stop climate change (A) (79.5% prediction accuracy) and self-efficacy (C) (74.1% prediction accuracy). (B) Partial dependence plot (PDP) of mean temperature anomalies (temp. anom.), belief in human causation (CC human cause), perceived worsening of agricultural conditions (agric. cond.), and perceived risk from climate change (CC risk percep.) over need to stop climate change. (D) Partial dependence plot of mean temperature anomalies (temp. anom.), belief in human causation (CC human cause), perceived risk from climate change (CC risk percep.) and being favourable to one-man rule (authoritarian) over self-efficacy.