Climate Gentrification: Methods, Gaps, and Framework for Future Research

Best, Kelsea; Jouzi, Zeynab

doi:10.3389/fclim.2022.828067

MINI REVIEW article

Front. Clim., 01 March 2022

Sec. Climate, Ecology and People

Volume 4 - 2022 | https://doi.org/10.3389/fclim.2022.828067

Climate Gentrification: Methods, Gaps, and Framework for Future Research

$\nKelsea Best &#x;$ Kelsea Best¹^*^†

Zeynab Jouzi²^†

¹Department of Earth and Environmental Science, Vanderbilt University, Nashville, TN, United States
²Department of Parks, Recreations and Tourisms Management, Center for Geospatial Analytics, North Carolina State University, Raleigh, NC, United States

The topic of climate gentrification has been receiving increasing attention in both peer-reviewed literature and in popular discourse. Climate gentrification refers to the ways that climate impacts and adaptations may contribute to changes in community characteristics and potential displacement of vulnerable residents through changes in property values. Here, we conduct a review of the current literature on climate gentrification in order to understand methods and key themes, identify research gaps, and guide future research. Our search yielded a total of 12 relevant articles, beginning in 2018. After reviewing these articles, we identified several key methodological gaps including the lack of participatory methods, limited availability of longitudinal data, difficulty defining and measuring displacement, and challenges surrounding causality. We suggest that future work on climate gentrification should draw from Coupled Human and Natural Systems (CHANS) theory to further understand the complex feedbacks that exist in climate gentrification dynamics. To guide future research, we propose a framework as a CHAN that highlights the multi-spatial, multi-temporal, and multi-faceted dimensions of climate gentrification.

Introduction

It is well-established that the impacts of climate change are poised to disproportionately impact groups of people that have less adaptive capacity and have contributed the least to the problem, and this is also true within cities (Schlosberg and Collins, 2014; Anguelovski et al., 2019; Rice et al., 2020). Similarly, climate change adaptation action at the local level, much like climate impacts, has the potential to reinforce uneven risk exposure and socio-economic vulnerability across groups within a community (Caulfield, 1994; Smith, 2005; Dooling, 2009; Quastel, 2009; Pearsall and Anguelovski, 2016).

Researchers and the media have started to popularize a theory of “climate gentrification” as a mechanism by which climate change may contribute to inequality in housing. Though there are varying definitions, climate gentrification is the idea that climate impacts and adaptations may contribute to differences in property value (Flavelle, 2016; Bolstad, 2018; Keenan et al., 2018). In this way, climate change may interact with gentrification by creating and reinforcing pathways of displacement due to economic, physical, and social upgrading (Slater, 2006; Lees et al., 2013). It has been suggested that climate gentrification is already occurring in several cities in the U.S. (Flavelle, 2016; Milman, 2018; Zanzilotti, 2018; Benson, 2019).

As with any new area of research, there is much work to be done to understand the complexities of climate gentrification. With the peer-reviewed literature and popular discourse on climate gentrification growing, it is important to consider the current state, gaps, and future directions of research in this area. The goal of this article is to begin to assess the emerging field of climate gentrification and guide future research. Here, we present a review of the existing peer-reviewed literature, which allows us to synthesize the state of the literature and present a framework of climate gentrification that can unify current work and inform future research.

Methods: Literature Search

To conduct this review, we searched Web of Science using the keywords “climate” + “gentrification”. Results were limited to only English-language articles. This initial search yielded 69 total articles. These articles' abstracts were manually screened based on the following criteria:

1. Only articles with a study area in the United States

2. No review articles

3. Peer-reviewed

Finally, full-text articles were further screened manually based on relevance to our climate gentrification topic. While an article did not have to explicitly mention “climate gentrification” to be included, it did have to refer to gentrification in the context of a climate related impact or adaptation. After our review and screening, we identified a total of 12 relevant articles for full evaluation (Table 1). During the evaluation of these articles, we extracted information related to climate gentrification definitions and mechanisms, data and methods, and identified gaps or future work.

TABLE 1

Table 1. Summary of research articles in the review including primary definition of gentrification, methods, data, and key themes.

Results

Definitions and Mechanisms of Climate Gentrification

Beginning with Keenan et al.'s pioneering work in 2018, we identified 12 relevant articles at the time this review was conducted (Table 1). Keenan et al.'s work establishes the groundwork for the study of climate gentrification. It provides a model for “the pathways by which climate change could operate to impact geographies and property markets whose inferior or superior qualities for supporting the built environment are subject to a descriptive theory known as ‘Climate Gentrification”' (Keenan et al., 2018). They propose three possible pathways for climate gentrification: superior investment, resilience investment, and cost-burden (Keenan et al., 2018). With our review, we identify typologies of climate gentrification and how they connect to Keenan's three pathways, demonstrating how these definitions are connected within the literature (Figure 1). This allows us to highlight how the field has been evolving.

FIGURE 1

Figure 1. We map the pathways of climate gentrification identified in this review to the original three pathways (resilience investment, cost-burden, and superior investment) identified by Keenan et al. (2018).

All of the papers that explicitly refer to climate gentrification include citations to Keenan et al. (2018), highlighting its importance in the field (McAlpine and Porter, 2018; Aune et al., 2020; de Koning and Filatova, 2020; Shokry et al., 2020). McAlpine and Porter's work draws from Keenan's definition of climate gentrification to study real-estate financial losses and projected losses due to flooding (2018). Their work provides additional evidence for Keenan's described superior investment pathway of climate gentrification phenomenon of climate exposure translating into changes to property values (McAlpine and Porter, 2018). Similarly, de Koning and Filatova reference Keenan et al. (2018) but further emphasize traditional gentrification outcomes including displacement of low-income residents due to superior investment (de Koning and Filatova, 2020). Aune et al. also place additional conceptual emphasis on socioeconomic factors of climate gentrification including shifts in community racial composition, education, and income level, though their overall definition of climate gentrification draws directly from Keenan et al. (2018) and Aune et al. (2020). Shokry et al. (2020) propose “green resilience gentrification” as an additional pathway to climate gentrification in which the selection of sites for green resilience infrastructure projects work to reinforce social and environmental vulnerability.

The remaining articles, which do not explicitly refer to “climate gentrification”, still meet the criteria of our review in that they all explore gentrification in the context of climate-related impacts or adaptation measures. We include these seven works because they can help us understand climate gentrification more broadly than the current, narrow literature. The majority of these papers fall broadly into the category of the “resilience investment” pathway of climate gentrification, in which resilience investments into a community can lead to increases in property values and gentrification outcomes (Turan, 2018; Finewood et al., 2019; DiValli and Perkins, 2020; Shokry et al., 2020). This is especially true when community members are not actively included in the process (Turan, 2018; Finewood et al., 2019).

These works are aligned with Shokry's pathway of climate gentrification through green resilience infrastructure (Shokry et al., 2020), which we consider as a subset of Keenan et al.'s resilience investment pathway (2018). Turan (2018) applies critical urban theory to the case of rezoning and revitalization in Gowanus, NY and describes how rezoning, motivated by addressing flood risk, leads to socio-political exclusion and gentrification due to lack of community participation. Similarly, Finewood et al. (2019) argue that investments into green infrastructure for stormwater management can lead to culture loss and gentrification. Shokry et al. (2020) makes a similar argument against “green resilience gentrification” in which green resilience infrastructure may contribute to new landscapes of environmental injustice. Distinctive from gentrification and displacement driven by resilience investments, DiValli and Perkins (2020) argue that resilience planning may achieve resilience through the displacement of residents, where displacement is not a side-effect of resilience planning but a direct aspect of it.

Another important distinction that emerges in the literature is post-disaster gentrification. DuPuis and Greenberg (2019) explore how resilience investment after Hurricane Sandy risks leaving out the most vulnerable residents in New York City. In a similar vein, Aune et al. (2020) choose the context of post-Katrina New Orleans to begin to assess temporal dimensions of climate gentrification. In these works, it seems possible that natural disasters may serve to speed up the gentrification process by creating new opportunities for investment and urgency for resilience infrastructure. Therefore, post-disaster gentrification may operate through a combination of Keenan et al.'s (2018) superior investment and resilience investment pathways.

This review also identifies an additional pathway of climate gentrification in the ways that energy efficiency, retrofitting, and low-carbon urban development can contribute to gentrification outcomes by increasing property values (Knuth, 2019; Rice et al., 2020). These pathways, which Rice et al. (2020) calls “carbon gentrification” are an important contribution to the understanding of climate gentrification as carbon mitigation efforts increase and, we propose, may be considered a unique subset of climate gentrification via resilience investment.

Finally, one article included does not directly link gentrification outcomes to climate impacts or resilience efforts, but rather suggests that gentrification could be an underlying process that contributes to unequal distributions of climate impacts (Wilson and Chakraborty, 2019). This work is a reminder that processes of climate change and gentrification interact in complex ways to contribute to climate justice or injustice. The emerging field of climate gentrification should consider not just where climate change or climate resilience drive gentrification, but all the different ways that gentrification and climate change may be interlinked and contribute to social and climate injustice.

Methods and Data

Works in this review employ a range of methods and data (Table 1). Six of the papers use quantitative methods including regressions (Keenan et al., 2018; McAlpine and Porter, 2018), the development of indices (Wilson and Chakraborty, 2019; Aune et al., 2020), spatial analysis (McAlpine and Porter, 2018; Wilson and Chakraborty, 2019; Shokry et al., 2020), and agent-based modeling (de Koning and Filatova, 2020). The remaining six articles utilized qualitative methods including document analysis (DuPuis and Greenberg, 2019), interviews (Finewood et al., 2019), community observations (Turan, 2018), historical analysis (Knuth, 2019), or these methods in combination (DiValli and Perkins, 2020; Rice et al., 2020).

We are also interested in the data and indicators that these works utilize. To assess this, we looked at each article and identified what, if any, environmental, social, and housing indicators were used (Table 1). From this, we see that environmental or climate considerations most frequently include flooding in some form, whether that is elevation as a proxy for flood risk (Keenan et al., 2018) or future projections of flood risk due to sea level rise (McAlpine and Porter, 2018). Several of the articles also include consideration of extreme heat with direct land surface temperature data (Wilson and Chakraborty, 2019) or data regarding community perceptions of heat (DiValli and Perkins, 2020). Other articles use data about resilience infrastructure or green investments as environmental indicators (DuPuis and Greenberg, 2019; Rice et al., 2020).

A wide range of social indicators were used across the articles reviewed. Five of the articles do not include any consideration of social or economic variables (Table 1). When socioeconomic indicators are included, race and income are the most frequently used. Some works also include age, education (Wilson and Chakraborty, 2019), English language proficiency, and unemployment (Shokry et al., 2020). As with the social indicators, the use of housing indicators varies widely in this work, and four of the articles do not consider housing or property indicators explicitly (Table 1). The most common housing indicator used is property values (Keenan et al., 2018), while one article also considers community housing characteristics including housing density, new constructions, and rates of resident relocation (Aune et al., 2020). Beyond specific environmental, social, and housing indicators, other indicators include rezoning data (Turan, 2018), community engagement (DuPuis and Greenberg, 2019), access to air conditioning (Wilson and Chakraborty, 2019), and sense of place (DiValli and Perkins, 2020).

Key Themes

From the identification of key themes in each paper (Table 1), the concept of the neoliberal growth model, in which economic development and private interests are valued above all else, is used to describe much of the broad processes that lead to gentrification in general. As DiValli and Perkins (2020) state, the neoliberal growth model of development often results in the displacement of poor residents (often of color) and their replacement with middle-class white residents. As an extension of the neoliberal growth model, other articles emphasize the emergence of a “green growth machine” (DuPuis and Greenberg, 2019; Knuth, 2019) in which urban greening efforts are employed to increase property values, while poor residents carry the greatest social and environmental burdens but receive less of the benefit (DuPuis and Greenberg, 2019). In this way, this analysis of key themes highlights how overarching economic incentives and systems interact with resilience planning to contribute to exclusion, of which climate gentrification is one possible outcome.

As climate gentrification stems, in part, from exclusion of vulnerable groups, community engagement and the democratization of urban climate resilience planning are important additional themes that are identified. Beyond climate change exposure and risks, the literature highlights that climate mitigation and adaptation actions can be a strong contributor to gentrification, especially where local community participation is not included. Without the “local green voice” (Turan, 2018), or the inclusion of locals in resilience planning, infrastructure and investment can further result in the socio-political exclusion and eventual displacement of community members.

Finally, the themes of the right to the city and justice are prevalent in these works. Questions of who has a right to a city (especially the right to a resilient city) underlie questions of climate gentrification (DuPuis and Greenberg, 2019). Climate gentrification raises questions related to “Who has the right to a safe environment?” and “Who has the right to climate protections?” Such questions have profound implications for climate justice as both the impacts of climate change and the benefits of climate resilience measures are unequally distributed. These questions should underlie future research and policies surrounding climate gentrification and just climate adaptation. Taken together, these key themes and guiding questions highlight the spatial dimensions of climate gentrification from macroeconomic systems to the local community participation.

Discussion and Conceptual Framework

From Figure 1, we immediately see that Keenan et al.'s cost-burden pathway of climate gentrification is understudied (Keenan et al., 2018). This pathway describes the idea that lower income households may be forced to relocate from high climate exposure areas due to the inability to afford the costs of remaining in place (such as insurance premiums, repair costs, etc.). None of the papers in this review could be classified under the cost-burden pathway, while the majority of the papers identified can be classified under the resilience investment pathway (Figure 1). Future studies that aim to consider cost-burden pathways of climate gentrification may need to incorporate new sources of data and indicators such as socioeconomic characteristics over time, insurance data, and climate damages.

By analyzing methods and key themes, we found that lack of participatory methods, longitudinal studies, and consideration of displacement to be a few key gaps in the climate gentrification literature. As has been discussed, where local residents have no voice in local governance, they cannot effectively advocate for their benefits, and consequently their needs can be overlooked. As an extension, research on climate gentrification should utilize participatory methods to ensure that the local voice is included. One possible example of getting engaged with the residents might be participatory mapping of residents' cultural values in a way that emphasizes knowledge co-production (Norström et al., 2020). Cultural values are important components and indicators of gentrification but might not be apparent to an outsider. For example, the places that people have the strongest sense of place or are meaningful for the community can be identified by them and researchers can bring them to the maps and make the invisible cultural assets of the community visible. By making the invisible, visible, local advocates may be empowered and policy makers and planners can include these data into their plans.

Considering temporal scale, most studies either happened during a specific time (e.g., after a hurricane) or they took place in a short span of time. We suggest that longitudinal studies can be helpful to have a better understanding of the sequence of processes and can provide in-depth understanding of the issue. For example, longitudinal studies will help us to identify the possible pre-stages of gentrification and enable policy intervention. In addition, some important social concepts related to gentrification, such as poverty, are dynamic. Furthermore, climate gentrification is likely related to historic events such as red lining and racial segregation in the past that led to the current uneven distribution of higher exposure to climate risks and lower access to green infrastructure. Hence, we suggest that climate gentrification studies need to take a temporal perspective.

Displacement is one of the most important components of gentrification, but a nuanced consideration of displacement and its different forms is lacking in the climate gentrification literature. Direct displacement (due to the high prices residents can't afford to stay in neighborhood), indirect displacement/exclusionary displacement (the high prices are barrier to low income to get into the neighborhood), and finally cultural displacement (with transformation of neighborhood and services provided, the remaining older residents feel detached from the neighborhood), are examples of displacement due to gentrification (The Uproot project¹) More in-depth studies with differentiation of various types of displacement are suggested for future research. To address these gaps and future challenges related to climate gentrification research, a combination of top-down methods and data (quantitative), such as remote sensing data for earth observation as well as the bottom-up methods (qualitative) such as interview and photo elicitation should be utilized.

Ultimately, this review highlights the complexity of climate gentrification as a multi-causal, multi-spatial process that involves dimensions of both natural and human systems. As climate gentrification considers both natural (climate change) and human (housing, displacement, justice, etc.) systems, we propose that it can be studied, and some of the identified gaps in the current literature may be addressed most effectively, by utilizing Coupled Human and Natural Systems (CHANS) theory (Ferraro et al., 2019). After reviewing the existing literature, we have developed a framework to help explain the complex temporal and spatial dynamics of climate gentrification as a CHAN (Figure 2). According to the framework, climate gentrification happens across global and regional scales spatially and from the past to future temporally. Consistent with our analysis of data sources and methods, we divided the main components of climate gentrification into two main categories of socio-economic and environmental variables. In this framework, all components are interconnected and any change in one group of variables can be a driver of change for the other group. For example, political exclusion and lower social capital, can lead the minorities to live in congested neighborhoods with very limited green infrastructure. This will increase the community's vulnerability through increasing the exposure to climate change hazards (e.g., flooding) and will exacerbate their situation.

FIGURE 2

Figure 2. A conceptual framework of climate gentrification as a coupled human and natural system. The framework highlights the multi-spatial, multi-temporal, and multi-factored elements of climate gentrification dynamics.

Our hope is that this framework will help to inform climate gentrification research as it expands. Future research must embrace and acknowledge the complexity of climate gentrification as a CHAN in order to advance research as well as provide insights for policymakers and communities. The emerging topic of climate gentrification highlights the need to consider multiple human and natural dimensions in future climate adaptation policy. To address possible future climate gentrification, such multi-facetted policies are needed to avoid disproportionate impacts on low-income and vulnerable populations (Anguelovski et al., 2019; Thomas and Warner, 2019; Shokry et al., 2020).

Author Contributions

All authors contributed equally to the conceptualization, development, and writing of this work.

Funding

This material is based in part by work supported by the U.S. National Science Foundation under grant CNH 1716909 and by Vanderbilt University's Grand Challenge Initiative on Climate and Society.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

1. ^Available online at: https://sites.utexas.edu/gentrificationproject/understanding-gentrification-and-displacement/.

References

Anguelovski, I., Connolly, J. J. T., Pearsall, H., Shokry, G., Checker, M., Maantay, J., et al. (2019). Why green “climate gentrification” threatens poor and vulnerable populations. Proc. Natl. Acad. Sci. U. S. A. 116, 26139–26143. doi: 10.1073/pnas.1920490117