Which areas will climate change render uninhabitable? Climate models alone cannot say
Scientists often rely on global climate models and high-level data to anticipate which regions of the world will face flooding, droughts, and other hardships in the future. We use those models to communicate the urgency of climate change and to provide a general sense of which regions are likely to be high-risk "hotspots," and therefore potentially uninhabitable in the future. Yet, as we learned during the 2019 Managed Retreat Conference at the Earth Institute at Columbia University, that approach isn't always welcomed by communities at risk. Top-down modeling approaches can contribute to a climate determinism that minimizes the potential for human ingenuity to find creative, locally appropriate solutions. Privileging likely future climate impacts can also come across as tone deaf in communities that have suffered redlining and racist land grabs.
In a new commentary in Science, we argue that the typical "top-down" approaches of climate modelers should be combined with "bottom-up" approaches that engage communities, collect local data, and evaluate solutions. This combined strategy is essential for helping communities to build resilience and adapt to climate change, and will be part of the discussion at the upcoming Managed Retreat conference from June 22 to 25, which we helped to organize.
The "top-down" approach has its merits. It's relatively easy to use multiple model runs to produce global or regional maps that convey important information about the distribution and severity of threats. These models also allow for comparisons between different areas, and can reveal large-scale trends and interconnected features of global systems. However, their broader scope overlooks factors that drive hazards at the local scale, and leaves out characteristics of local populations—such as health, socioeconomic status, historical context and culture—that can shape exposure and vulnerability.
For example, it is possible to combine projections of sea level rise with elevation models to estimate that coastal flooding is likely to affect between 310 and 630 million people around the world by 2100. Yet threats to infrastructure and the risk of rising seas contaminating wells with salt water depend on other factors, such as local geography. In addition, different communities vary in their ease of evacuation, access to flood control measures, and exposure to coastal storms. Factors such as levels of inequity, strength of governance and social networks, and quality of infrastructure will also be critical in determining whether specific areas remain survivable. Thus, top-down methods cannot define a single coastal flooding threshold that applies to every community.
By definition, bottom-up assessments provide data that is more rich in detail. These methods can engage various stakeholders to produce qualitative data and explore high-impact scenarios and local solutions that would be missed by top-down approaches. These approaches can account for how people respond behaviorally to changing environmental conditions—the loss of assets and livelihood opportunities, shifts in insurance premiums, threats to life, and changing structure of social networks. In fact, such societal tipping points could be greater predictors of when communities retreat than top-down geophysical modeling results. Engaging the community also empowers them to take action, rather than projecting a feeling of inevitability and hopelessness that can make individuals resistant to working together or with local authorities to reduce risks and build resilience.
However, to date, most locales have not been subject to such an integrated habitability assessment. In addition, the specificity of bottom-up methods makes it difficult to compare across geographies and groups, and to apply the lessons and solutions from one area to another.
The solution is to meet in the middle—by creating a holistic, people-centric approach that incorporates models, data aggregation, and ethnographic work. We should use top-down habitability assessments to identify groups and regions that should be prioritized for bottom-up work. As a matter of climate justice, many semi-arid regions, much of the tropics, and some low-lying deltas and islands should be high priorities for this combined approach, since many of the most vulnerable populations are those who have the fewest resources to cope with climate change, and who have contributed the least to greenhouse gas emissions.
We must develop policies that identify the most feasible local adaptation options across diverse geographies and groups, rather than options that are deterministic and one-size-fits-all. Such a mid-level strategy also avoids hyper-local solutions that cannot be applied in other communities, whose development can be costly and time-consuming.
Some organizations, such as the Consortium for Climate Risk in the Urban Northeast, part of NOAA's Regional Integrated Sciences and Assessments Program, are already working to bridge the divide between top-down research and community-led initiatives. The organization works by framing research around the needs articulated by communities through deliberative, long-term engagement and co-generation of knowledge. The Intergovernmental Panel on Climate Change (IPCC), national efforts, and institutions such as the recently developed Columbia Climate School can also provide the innovative and transdisciplinary approaches that are needed to further develop this promising middle space between top-down and bottom-up approaches.
It is only by joining these approaches that we can avoid climate determinism and hopelessness, and instead implement proactive policies on adaptation and migration that will reduce damages from climate change and save lives.
More information: Radley M. Horton et al, Assessing human habitability and migration, Science (2021). DOI: 10.1126/science.abi8603
Journal information: Science
Provided by Earth Institute at Columbia University
This story is republished courtesy of Earth Institute, Columbia University http://blogs.ei.columbia.edu.