9 Inclusive Resilience
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The physical impacts of climate change pose complex risks to Canadians. Climate impacts—wildfires, floods, droughts, heat waves, permafrost melt, sea-level rise—will be felt unevenly across individuals, communities, provinces, and regions. Some Canadians are more vulnerable to a changing climate than others. Clean growth requires increasing the resilience of those that are vulnerable.
Headline Indicator #9: Poverty Rates in Canada
Vulnerability to climate change has three key dimensions (see Figure 9.1). Some regions and communities in Canada face higher exposure to climate risks than others, based on location-specific climate risks (e.g., flood, wildfire, heat waves) and other key variables, such as where people work and live and how they move around. Other individuals and households are more sensitive to climate impacts when they occur. This group includes children, disabled persons, pregnant women, the elderly, those with pre-existing health conditions, or those with low incomes. Lastly, vulnerability is shaped by how much adaptive capacity people and communities have before, during, and after climate-related events occur (USGCRP, 2016). Vulnerability is shaped by the confluence of all three dimensions (IPCC, 2007; Lavell et al., 2012; Manangan et al., 2016).
Vulnerability does not imply weakness; rather, it is shaped by the scale of change individuals and communities face—in combination with other challenges and historical circumstances.
Importantly, all people and communities in Canada can experience vulnerability. It does not imply weakness; rather, vulnerability is shaped by the scale of change individuals and communities face—in combination with other challenges and historical circumstances (Haalboom & Natcher, 2012). Measuring vulnerability is about better understanding the risks that different individuals, groups, communities, and regions face and how to leverage existing strengths and community values to improve resilience.
We use poverty rates to measure the resilience (and vulnerability) of Canadians (see Figure 9.2). Although an imperfect proxy, poverty is a driving factor behind all three dimensions of vulnerability. Those that can afford to prepare, move, rebuild, or recover are not as vulnerable as those that are poor (Hallegatte et al., 2020). Poverty is also highly correlated with other key factors that shape vulnerability, such as inadequate access to housing, clean drinking water, education, health care, and other factors such as discrimination and colonization (Heisz et al., 2016; ESDC, 2016; Thomas et al., 2015).
At the same time, poverty is indirectly connected to exposure to climate risks. Some low-income communities, for example, are more exposed to climate hazards, such as communities located in flood plains or in urban areas where the “heat island effect” is most intense (Health Canada, 2020). Nearly 22 per cent of residential properties on Indigenous reserve lands in Canada, for example, are at risk of a 100-year flood (Thistlethwaite et al., 2020). Moreover, key social programs can become disrupted during climate emergencies, leaving vulnerable populations isolated and more exposed. Low-income populations are also more vulnerable to higher food prices from disrupted supply chains.
Despite progress over time, the data indicate that some Canadians remain highly sensitive and poorly equipped to deal with climate impacts, given high poverty rates. People under the age of 18 who live in households parented by single females, for example, are nearly three times more likely to experience poverty than the average Canadian. Poverty rates are also higher for males and females not in an economic family (27 per cent and 22 per cent, respectively). Several climate risk assessments in Canada highlight the climate vulnerability of these specific groups (Council of Canadian Academies, 2019; Government of British Columbia, 2019).
Similar to national trends, poverty rates have declined across provinces and cities, though to varying extents. Here, too, poverty data give a clue as to how climate vulnerability might vary across Canada. Figure 9.3 shows poverty rates for all 10 provinces and eight of Canada’s largest cities. At the provincial level, the biggest reductions in poverty rates were in British Columbia, New Brunswick, and Prince Edward Island. At the municipal level, the biggest reductions were in Vancouver, Toronto, and Montreal.
Notably, these data do not include poverty rates for the territories or Indigenous and Northern communities. Data from other sources suggest poverty rates are generally much higher in these communities relative to the Canadian average, especially for children (ESDC, 2016). According to census data from 2006 and 2016, 47 per cent of status First Nations children live in poverty (53 per cent for those living on reserve and 41 per cent for those living off reserve). And unlike national poverty rates, which declined over time, child poverty rates in Indigenous communities have remained largely unchanged. Child poverty rates are highest in Manitoba and Saskatchewan (Beedie et al., 2019). Across Canada, these high poverty rates in Indigenous communities are linked to historic and ongoing colonization and systemic discrimination (Cameron, 2012).
Poverty rates provide key insights on Canadians’ resilience to climate change but have clear limitations:
Poverty rates are an incomplete measure of sensitivity and adaptiveness. Individuals with significant financial resources may still be highly sensitive to climate impacts because of their age or pre-existing health conditions. At the same time, poverty rates within a community might be improving, but other underlying inequities—such as access to clean drinking water, transportation, or discrimination—may make the community highly sensitive to climate impacts and inhibit its adaptability. Remote Indigenous communities, for example, lack basic infrastructure relative to Southern Canada (Johnston & Sharpe, 2019), which makes them less resilient and less accessible to outside help when disasters strike.
Poverty rates provide limited information on the relative exposure to climate impacts. Exposure to climate risks is a critical part of vulnerability (Cardona et al. 2012). Overall, Canadians’ exposure to extreme climate risks—floods, droughts, sea-level rise, permafrost thaw, wildfires, etc.—is expected to increase over time as global temperatures increase (ECCC, 2019). These risks will also vary across provinces, regions, and even neighbourhoods.
Poverty rates do not capture direct local exposure and how exposure is changing over time. While decreasing poverty rates may help Canadians become less sensitive and more adaptable to climate impacts, increasing exposure may easily offset these gains.
True vulnerability lies at the intersection of exposure, sensitivity, and adaptability. The most comprehensive way to measure vulnerability is at the intersection of exposure, sensitivity, and adaptability. Layering and mapping each dimension of vulnerability—at a high level of disaggregation—can help researchers and policy makers truly understand the complexities and interactions of climate risks facing Canadians (Minano et al. 2019).
For example, Chakraborty et al. (2020) uses 2016 census data to construct a socio-economic status index that includes 49 different indicators of sensitivity and adaptiveness (e.g., racial and ethnic composition, household and family structure, access to financial resources, and demographic characteristics). The index is then layered on top of each communities’ exposure to flood risk to identify the most vulnerable communities in Canada. This type of data and analysis is key to designing policies that help build resilience amongst these affected populations. Poverty rates are a component of this larger picture but are incomplete on their own.
Although Canada generally has good data to identify at-risk populations, governments can improve existing datasets and connect them directly to climate change (see Table 9.1). The biggest data gaps involve Indigenous and Northern communities. National datasets often do not include these communities due, in part, to challenges with data collection and small sample sizes. Yet these communities are some of the most vulnerable to climate change. Canada also lacks data on specific factors of sensitivity that have historically not been connected to climate change, such as mental health, immigrant communities, racial discrimination, and the long-term employment impacts from natural disasters.
More consistent and standardized data across communities can help, as data collection standards vary across provinces and municipalities. The City of Montreal has developed some leading approaches to tracking vulnerability and heat wave risk. Due to better reporting standards, Montreal can appear to suffer higher damages and health risks from heat waves relative to other provinces. During the heat wave of 2018, for example, Montreal experienced 66 heat-related deaths, whereas Ottawa reported zero, despite experiencing similar temperatures (Oved, 2019).
Finally, Canada could benefit from more research on the interaction and overlap between the different dimensions of vulnerability. Statistics Canada has made progress, for example, by combining its Canadian Index of Multiple Deprivation with historical flood data from several cities in Canada. These data were used to identify the most exposed and sensitive communities to spring flooding in Fredericton-St. John, Montreal, Southern Manitoba, and Ottawa-Gatineau (Figure 9.4).
More of this type of data and research could dramatically improve our understanding of the most vulnerable populations to climate change (Chakraborty et al., 2020). It can help governments design policies that improve Canadians’ adaptability and resilience while avoiding policies that exacerbate pre-existing vulnerabilities (e.g., providing inequitable flood relief to low-income households and renters). This type of data can also be used to conduct forward-looking analyses to better understand how vulnerabilities might change over time.