Editing IPCC:AR6/WGII/Chapter-12 (section)

==== 12.5.8.2 Perceptions ====

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Perception and understanding of climate change can be seen as an adaptive feature. In CSA, the awareness of climate change as a threat is increasing, a situation related to growth in climate justice activism and to the occurrence of extreme weather events of all kinds ( ''high confidence'' ) ( [[#Forero--2014|Forero et al., 2014]] ; [[#Magrin--2014|Magrin et al., 2014]] ; [[#Capstick--2015|Capstick et al., 2015]] ). Perception of climate change is positively associated across countries with the HDI and ND-Gain Readiness Index and negatively associated with the Vulnerability Index and, within countries, with education level, while perception is negatively associated with the degree of political affinity for the market economy ( [[#Azócar--2021|Azócar et al., 2021]] ). However, some communities do not associate their problems with the scientific concept of climate change, so discussions on whether it is human induced and its causes or relationship with other problems can become irrelevant ( [[#Sapiains%20Arrué--2017|Sapiains Arrué and Ugarte Caviedes, 2017]] ). Even communities affected by the same changes do not necessarily perceive them in the same way ( [[#Bonatti--2016|Bonatti et al., 2016]] ). The interpretations of change, as well as its causes and effects, can vary widely ( [[#Paerregaard--2018|Paerregaard, 2018]] ; [[#Scoville-Simonds--2018|Scoville-Simonds, 2018]] ). Rather than adapting to climate change, some people adapt climate change to their social worlds ( [[#Rasmussen--2016a|Rasmussen, 2016a]] ).

Perceptions tend to be different in rural and urban areas ( [[#Sherman--2015|Sherman et al., 2015]] ). In rural areas, it largely relates to temperature rise and changes in rainfall patterns, changes in agriculture (pests, calendars), biodiversity loss, solar radiation or changes in the oceans, and their impacts are sometimes related or even more attributed to socioeconomic and environmental drivers, as well as to negative financial outcomes ( ''high confidence'' ) ( [[#Infante--2013|Infante and Infante, 2013]] ; [[#Postigo--2014|Postigo, 2014]] ; [[#Jacobi--2015|Jacobi et al., 2015]] ; [[#Barrucand--2017|Barrucand et al., 2017]] ; [[#Harvey--2018|Harvey et al., 2018]] ; [[#Martins--2018|Martins and Gasalla, 2018]] ; [[#Meldrum--2018|Meldrum et al., 2018]] ; [[#Córdoba%20Vargas--2019|Córdoba Vargas et al., 2019]] ; [[#Leroy--2019|Leroy, 2019]] ; [[#Viguera--2019|Viguera et al., 2019]] ; [[#Gutierrez--2020|Gutierrez et al., 2020]] ; [[#Iniguez-Gallardo--2020|Iniguez-Gallardo et al., 2020]] ; [[#Lambert--2020|Lambert and Eise, 2020]] ). In such places as Amazonia, perception increases with age ( [[#Funatsu--2019|Funatsu et al., 2019]] ). In Mediterranean Chile, younger, more educated producers and those who own their land tend to have clearer perceptions than older, less educated or tenant farmers, but they do not have a clear perception or how it may affect their yields and farming operation ( [[#Roco--2015|Roco et al., 2015]] ). In some dry and humid Ecuadorian montane forests, peasantss perceptions are in line with the scientific data, but they have a lot of difficulties to predict the changes and believe that they may not be prepared and can only be reactive ( [[#Herrador-Valencia--2016|Herrador-Valencia and Paredes, 2016]] ). In an Andean community, perceptions of climate change are homogeneous and do not vary according to gender, age or ethnicity ( [[#Cáceres-Arteaga--2020|Cáceres-Arteaga et al., 2020]] ). Among representatives of five municipalities of Lima, it was found that climate change is not well understood and residents have trouble distinguishing it from other environmental issues ( [[#Siña--2016|Siña et al., 2016]] ). In an Amazonian region, farmers provided a more accurate description than regional institutions of how it affects the local livelihood system ( [[#Altea--2020|Altea, 2020]] ). In Cuenca Auqui peasants attribute recently experienced challenges in agricultural production mainly to perceived changes in precipitation patterns, but statistical analyses of daily precipitation records at nearby stations do not corroborate those perceived changes ( [[#Gurgiser--2016|Gurgiser et al., 2016]] ).

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