Disastrous consequences: shortcomings of resiliency strategies for coping with accelerating environmental change

Insight

INTRODUCTION

The cost, frequency, intensity, and scale of disasters such as flooding and wildfires is increasing, driven by climate and other global environmental changes (Coronese et al. 2019). Governments globally recognize this threat and have created plans to cope with expected change, with large areas of the Earth at risk from sea level rise (IPCC 2022) and other negative effects of climate change. Responses to disasters have typically been described in terms of recovery to normal, influenced by a belief that social-ecological systems (SES) can return to how they looked and functioned before a disaster. Resiliency is the rate of return to a previous equilibrium or baseline (or the ability of an object to spring back into shape) and is critically important for physical and engineered systems (Allen et al. 2019). Such an approach works for many disasters, because few disasters push a system beyond tipping points and thus systems can recover to some extent from most disasters (Birkland and Waterman 2009). Although resiliency approaches are typically preferred in practice (Rockstrom et al. 2023), those approaches are truly only appropriate for stationary physical or engineered systems, such as a manufacturing process. When engineered systems such as infrastructure are nested within biophysical systems such as a city, they are subsumed by the rules of nature such that coupled systems of humans and nature are subject to processes and structures interacting at multiple scales, exhibiting non-stationarity and tipping points (Jozaei et al. 2022). Thus, if policy for SES is based solely upon resiliency it can perversely lead to undesirable consequences when thresholds are exceeded

Social-ecological resilience

The term ecological resilience (Holling 1973) has through time evolved to encompass coupled systems of humans and nature and become more comprehensively social-ecological resilience (Folke 2016, Allen et al. 2019, Reyers et al. 2022). The concept is based on a well-developed body of theory (Folke 2016) that has general applicability and accounts for bounce back (Allen et al. 2019), alternative regimes (Holling 1973), and transformation (Chaffin et al. 2016), as well as non-linear dynamics at multiple scales (Gunderson and Holling 2002). Social-ecological resilience includes resiliency because most disturbances are relatively small, and recovery is possible. However, SES can be pushed beyond a tipping point and reorganize into fundamentally different systems. Though crossing a critical threshold is much more uncommon than bounceback dynamics, they are also much more consequential. At its most basic level, social-ecological resilience is the amount of disturbance an SES can withstand before crossing a threshold (tipping point) and reorganizing as a different system (e.g., a healthy coral reef shifting to a macroalgae dominated state).

Given the inevitability of accelerating global change (Kemp et al. 2022), a narrow resiliency response strategy to disasters may have negative consequences for humanity. Social-ecological systems do not have a single response to perturbation; their responses depend upon, for example, proximity to a tipping point, adaptive capacity, and the scale of the disturbance (Gunderson 2000). Even if resiliency actions for SES look successful in the short-term, living systems (SES) never really recover to some certain pre-disaster condition or state: they emerge, regenerate, and adapt (Reyers et al. 2018). Even built systems such as cities can exist in alternative states, some of which are better suited for humans (Herrmann et al. 2016, Elmqvist et al. 2019).

Here, we further describe the ramifications of focusing on resiliency by examining different responses to disasters. The most robust responses to disasters address both resiliency and social-ecological resilience, and some organizations, institutions, and governments do have robust preparedness strategies, but the focus on resiliency in community and disaster resilience is prevalent enough to require this cautionary perspective.

Pitfalls of resiliency approaches to climate change

Decades of work has established the importance of considering ecological, economic, and social systems and their responses to perturbations as intricately connected, and impossible to separate (Gunderson et al. 2022). Attempting to separate complex systems into individual subcomponents leads to partial responses that displace perturbations to different parts of the system and creates the potential for unwelcome surprises. Below, we contrast core resiliency approaches and responses to climate-induced disasters with alternatives that focus on social-ecological resilience.

Focus on efficiency

Efficiency is a key design and operational component in human systems that maximizes production and reduces costs (Kara et al. 2021). Large-scale agricultural production systems, energy systems, and water control systems are examples where a focus on production, efficiency, and economic considerations emphasize resiliency while ignoring ecosystems and social-ecological interactions (Sundstrom et al. 2022). The failure of the Texas power grid in February 2021 epitomizes the shortcomings of an approach singularly focused on efficiency (Busby et al. 2021). In February 2021 a cold snap led to electrical demand exceeding capacity, in part due to the lack of redundancy in the Texas power grid, lack of diversity of power sources available at the time, and over compartmentalization and lack of connectivity to other power grids. The focus on efficiency led to simple controls that contributed to system collapse. Although the severity of the winter storm that occurred in Texas was unforeseen and likely aggravated by climate change, the collapse of the power grid in 2021 was due to multiple factors in the system, each of which decreased overall social-ecological resilience. One was a reliance on economic controls to limit the use of electricity; increasing the price of electricity during shortage (and as lines were broken or producers, such as wind turbines, went offline), which did not lead to a decrease in demand. Another contributing factor was “just in time” delivery and limited energy storage. This focus on efficiency led to a spectacular failure of the Texas power grid. A social-ecological resilience approach to energy provision would include the creation of redundant energy production systems, better connectivity to other power grids, and include more power options, to provide delivery under a range of climatic variability.

An additional efficiency example comes from water management. Flood control is the primary design goal for many riparian and wetland ecosystems across the world (Venkataramanan et al. 2020). The primary technologies of levees, canals, and water control through dams have afforded flood protection that has enabled humans to utilize riparian ecosystems for agriculture and urban development. Water management designs and construction are based on resiliency approaches, affording flood protection and the ability to withstand very low frequency events such as a 1 in 500-year flood. In Pakistan in 2022, record setting heatwaves contributed to warmer air holding more moisture, significant glacial melting in areas feeding into watersheds, and massive flooding that resulted in two-thirds of the country being flooded, 33 million people displaced, the destruction of 1.2 million homes, and 1200 deaths (Mallapaty 2022). A typical resiliency response to such floods is to strengthen and increase the height of existing levees and other water control devices and use more and stronger pumps (Collenteur et al. 2015). Although such approaches can buy time, they are short-term fixes based on stationarity assumptions (i.e., the belief that the context and underlying conditions of the system does not change, for example, flooding will not worsen with accelerating global change) and may ultimately lead to worse disasters when these higher levees are eventually breached (e.g., Hurricane Katrina) as more extreme weather events driven by climate change become more frequent, larger, and more intense. The magnitude of the flooding event in Pakistan highlights challenges to abate such climate-induced extremes. At such broad scales slow variables, such as established governance and cultural norms largely dictate social-ecological system dynamics. However, planning scenarios including transdisciplinary collaborations among, for example, meteorologists, hydrologists, ecologists, social scientists, lawyers, landscape planners, engineers, politicians, and other public and private stakeholders may help to envision a range of potential worst-case to best-case futures and slowly transform current SES into forms that may be more sustainable in the long term (Kapucu 2008).

Efficiency has become the driving model for businesses and in many cases government, because it provides low costs and high productivity when operating conditions are stable and ideal. However, we live in a world that is rapidly changing on many levels and a singular focus on efficiency can, and demonstrably has, a high cost when a disturbance occurs. Social-ecological resilience may provide lower productivity because of the need to account for multiple factors, however, these approaches are much more likely to guarantee production over a wide range of circumstances (Walker et al. 2023) and potentially avoid catastrophes such as the American dustbowl in the 1930s, which arose from attempts to maximize agricultural yield across large spatial extents in the U.S. Great Plains (Egan 2006). Phenomena similar to the American dustbowl will likely intensify with climate change because of increasing rates of desertification (Ma et al. 2021). Rather than managing for optimization, transformations of entire agricultural sectors will be necessary to ensure demands are met given shifting social-ecological baselines and accelerating climate change.

Managing for social-ecological resilience rather than efficiency reduces the chance for a total collapse of SES in the face of climate change, but also requires some explicit trade-offs (Garmestani et al. 2023). Efficient approaches focus on providing the greatest output during ideal conditions, whereas social-ecological resilience focuses on providing an output during all conditions, given that ideal conditions are rarely achieved. A shift to social-ecological resilience requires an acceptance of slightly reduced output during ideal conditions in return for better outputs during less ideal conditions, but with less likelihood of collapse. For instance, one of the U.S. government’s responses to flooding was to develop management approaches that would allow for flooding of land that was afforded flood control prior to 1993 (similar initiatives are implemented worldwide). This strategy was implemented by acquiring land to restore natural riparian integrity that absorbs floods, rather than constraining rivers within levees. Such solutions are generally considered inefficient and expensive by engineers but working with nature rather than against nature enhances social-ecological resilience of the Earth at multiple scales (Jozaei et al. 2022).

Focus on recovery

A second disaster-in-waiting for resiliency approaches is the singular consideration of return time as a meaningful metric, as this approach assumes that recovery in SES is possible, is linear, and has a single equilibrium endpoint. However, recovery following a disaster occurs over time, with different activities occurring at different times post-disaster (Changnon et al. 2000). Immediate recovery involves emergency treatment and sustenance of human life, through supplies of water and food (Kates et al. 2006), resilience-by-design (stockpiling of medication), and resilience-by-intervention (mobilization of healthcare personnel) models in healthcare systems, followed by slower processes of rebuilding damaged infrastructure without the guarantee that these slower processes keep pace with a broader systemic (economic, social, ecological) change that an SES has undergone (Kapucu 2008). Similar patterns occur following natural disasters in ecosystems where recovery is a complex set and series of stages, not a singular pathway (Chuang et al. 2019) and it is seldom possible to return to the exact pre-disturbance state given non-stationarity. A management focus on resiliency often ignores that many social-ecological baselines have become obsolete because of persistent and intensifying human activities (Duarte et al. 2009). In the case of climate change, if the current global climatic regime becomes obsolete, such as Earth potentially flipping into a “hothouse regime,” a return to a glacial-interglacial Holocene climate regime is not feasible (Steffen et al. 2018). Because of inherent complexity and uncertainty in SES, the recovery of such systems cannot be captured by the singular metric of return time inherent in resiliency.

For example, following Hurricane Katrina, the infrastructure of the 9th Ward of New Orleans was severely damaged. The ground elevations in this impoverished area were lower than in other areas of the city (Chuang et al. 2019). As a result, when the levees were overtopped during the storm, the resulting flooding was much more severe as was the damage to residential housing. The long-term recovery of the area followed a resiliency trajectory, where levees were rebuilt to correct the structural inadequacies that led to failure, yet the hazard of flooding by future overtopping or levee collapse remains and will intensify with accelerating climate change. Moreover, the damaged structures were rebuilt in such a way (on the ground rather than raised) that did not reduce their vulnerability to future flood events (Craig 2010). This is an example where the attempt to recover to the original configuration failed, and missed an opportunity to transform neighborhoods to a more desirable condition by addressing infrastructure issues in conjunction with economic, cultural, and ethnic inequities (Comfort et al. 2010).

Focus on linear responses

History is littered with examples of civilizations that have failed because of an unexpected regime shift (Diamond 2011). Often these shifts are caused by human changes to critical slow variables such as climate and have often been driven by the collapse of agriculture. Agriculture is a type of system needing intense management; hence, it has become more dependent upon external subsidies and increasingly less resilient (Angeler et al. 2020a) because of an intense focus on efficiency including just-in-time supply chains, increasing field sizes, and increasing homogeneity (Sundstrom et al. 2023). The failure of agriculture due to salinization in many locations globally during many different time periods is an example (Diamond 2011). Salinization occurs when, in order to optimize crop production, agricultural lands are irrigated in arid regions leading to an increase in soluble salts in the root zones of cultivated plants (Schuler et al. 2019). This is due to several factors, including the use of saline groundwater for irrigation, groundwater table changes, high evapotranspiration, sea level rise, and the increase in extreme weather events impacting the mobility of soluble salts. Such salinization leading to loss of arability has occurred on all continents and is a core contributor to the collapse of Mesopotamia (Artzy and Hillel 1988).

Reducing carbon emissions is another example of a complex global issue that has typically been approached from a linear perspective. To address carbon emissions, many economists argue that carbon taxation is the single most powerful way to combat climate change (Garcia and Sterner 2021). However, most research on carbon taxation does not consider the possibility that SES can exist in different configurations separated by tipping points. Recently, some economic studies have begun to address these shortcomings by explicitly modeling uncertainty, learning, and irreversibility in climate impacts (e.g., Kelly and Tan 2015, Garcia and Torvanger 2019). Notably, numerical simulations and integrated assessment models show that when tipping points are added to climate change models, the optimal carbon tax schedule increases considerably (Lemoine and Traeger 2014) and may double today’s optimal carbon taxes (Lemoine and Traeger 2016). Despite important progress in improving climate-economic models, these models often fail to account for all relevant tipping points and the interactions between them (Dietz et al 2021). The ramifications for climate policy are quite evident when focused upon resiliency of a single variable such as the economy under stationary climate assumptions, as opposed to the social-ecological resilience of the climate system in which SES, the economy, governance, and the environment are embedded.

With increasing frequency, SES are disturbed beyond tipping points (Santos-Martin et al. 2019). As previously discussed, when a tipping point is crossed, the SES cannot simply be restored or moved back to its original configuration. Hysteresis is a term used to convey that restoration is not a simple process once an SES has been pushed past a tipping point and into a new regime, i.e., an SES’s path into a regime is not the same as the path out of a new regime, as restoring a system back to its original state may be prevented or made more difficult by hysteresis. Such is the case with tree invasions into some grasslands (Collins et al. 2021) and likely is the case with the Atlantic meridional overturning circulation (Ditlevsen and Ditlevsen 2023). In other words, simply removing the perturbation, or replacing a lost system element, is often not enough to restore an SES to a previous regime. With hysteresis, much more effort is required to restore the original regime than it took to collapse it, and restoration may not even be possible (Angeler et al. 2020a). This serves as a cautionary note because it is far easier to prevent an SES regime shift than it is to explicitly and purposefully change the regime back to its original configuration.

Focus on a single scale

Other types of natural disturbances, such as the spread of trees into grassland biomes globally (Uden et al. 2019, Bardgett et al. 2021), fires at the urban/wildland interface (Radeloff et al. 2018), or the spread of COVID-19 (Castro et al. 2021), are spatially contagious processes that can transgress the scales at which they originated. The typical management response to such phenomena is to focus on stopping the contagion: controlling the spread of tree seeds, extinguishing fires, or quarantining infected individuals. Following these outbreaks, a return to normal that focuses on local recovery generally often fails to address the role of variables and dynamics at other scales (Garmestani et al. 2020). For example, at the urban-wildland fire interface in areas experiencing transitions from grasslands to cedar woodlands, management should focus on small scale spatial and temporal patterns of fuel accretion post-fire and propagule dynamics for red cedar, and at large scales should focus on reducing transport and reducing the overall abundance of red cedar in the landscape.

Accounting for scale can also provide insight into the management of SES. Scale is a critical component of social-ecological resilience, and failure at one scale can scale up or down to cause cascading collapses. Returning to our Texas power grid example, not accounting for spatial scale contributed to the extent and duration of power failure. The state of Texas chose to not abide by federal regulations, which govern interstate transfers of electricity, thereby removing access to other sources of power available from adjacent states (Baker and Coleman 2021). Localized outages propagated across the limited Texas power grid, causing a sequence of failures across much of the system. As a result, during and after the collapse, the system became operational only after internal sources of production were restored because resources available at different scales, such as the Southwest Power Grid, were not utilized, and could not be because of a lack of connection across most of Texas.

Implicit focus on stationarity

Stationarity means that historical baselines in SES can be used as an anchor from which to guide restoration, mitigation, and even adaptation of SES (Craig 2010). Because of accelerating climate change, the relationship among these key components is changing as well as the distributions of these variables. Such non-stationarity means that there is no static baseline condition from which SES change can be assessed, and the SES we manage are increasingly non-stationary (Angeler et al. 2020b). Given this, recovery targets are increasingly difficult or impossible to achieve. When an SES is constantly changing, it is not possible to reasonably choose a recovery point; restoration ecologists have grappled with this challenge for decades (Angeler and Allen 2016). Improved policy for SES increasingly affected by climate change driven disasters would seek to protect/create processes, structures, and functions desirable for humans, even if individual components also change (Green et al. 2015). Like other systems, a major component of designing and operating water resource systems involves assessing the distribution and central tendencies of key (hydrologic) variables. Spatial and temporal patterns of rainfall, flow and water levels are used not just in the design but operation of water control systems such as the Everglades (Gunderson and Holling 2002). The Comprehensive Everglades Restoration Plan was initially funded in 2000 and has cost many billions of dollars, yet is threatened by non-stationarity in the form of increased rainfall and salt water intrusion (ICCG 2009, Bernhardt 2022).

Response to disturbance is an important component of social-ecological resilience (Gunderson et al. 2022). Recovery is not possible where an SES is strongly non-stationary as the original configuration of the SES and its components have changed. A social-ecological resilience approach allows variability in the SES being managed and explicitly seeks to avoid crossing tipping points (adaptation) or intentionally directing an SES to a new, more desirable configuration (transformation; Chaffin et al. 2016). Capacities to prepare for, learn from, and navigate uncertainty and surprise, for keeping options open and creating space for innovation, and for systemic transformation in the face of crises and unsustainable development pathways and traps are central in this context. Transformative approaches will become more necessary as humanity, at least in the foreseeable near-term, experiences increased non-stationarity that limits the success of adaptation and mitigation. Transformation is an aspect of social-ecological resilience and describes the purposeful erosion of a system in an undesirable state to foster the emergence of a more desirable system (Garmestani et al. 2025).

CONCLUSION

Our message is precautionary: approaches that cope with environmental change by hardening systems, reducing variability, and focusing on obsolete recovery points will ultimately fail, and where failure includes the emergence of an alternative, undesirable regime, that failure is likely consequential for humanity. Resiliency is the dominant paradigm for engineered systems such as buildings, bridges, or production lines, where stability and consistency are the primary design goal. However, the resiliency paradigm has significant limitations for managing SES, as the types of climate change approaches and responses employed to govern SES are dependent upon the framing of resilience (Clement et al. 2024). Responses to accelerating climate change, especially over longer time frames (e.g., 50–100 years), require a reframing of strategies for coupled systems of humans and nature (Gunderson et al. 2022), including pathways for transformation rather than recovery moving forward in the Anthropocene (Manyena et al. 2011, Chaffin et al. 2016, Lade et al. 2020).

Although resiliency is attractive because it is a linear approach, successful implementation of resiliency approaches requires that the system in question be effectively stationary, possess a single equilibrium, and have an easily identified and desirable prior state to which one can return. These requirements are rarely met for living systems and are increasingly less likely considering rapidly accelerating climate change. A social-ecological resilience framing for SES means focusing on maintaining functionality over a wide range of conditions rather than optimizing a few components and recovering when possible. It also means being prepared for transformation: fostering regime changes in undesirable situations, identifying tipping points and managing them, accounting for drivers of change from scales other than the focal scale, and embracing, rather than resisting, non-stationarity (Gunderson et al. 2022). It often involves a shift in the focus of practice from capitals to capacities, from objects to relations, from outcomes to processes, from closed to open systems, from generic interventions to context sensitivity, and from linear to complex causality (Reyers et al. 2022).

Moving beyond a resiliency paradigm to a social-ecological resilience paradigm that considers, for example, reiterative alternative scenarios for SES to account for non-stationarity, should increase the diversity and robustness of responses to climate change (Herrmann et al. 2021). Such paradigms should form diverse methodologies, such as dynamic modeling and local knowledge input, that address the inherent complexity of SES. Current assessments and standardized indicators can be useful for initial measurement and comparison (Chuang et al. 2018), but forward-looking approaches must confront the inherent uncertainty in SES with adaptive management (Allen et al. 2011), adaptive governance (Folke et al. 2005), and transformative governance (Chaffin et al. 2016), focusing on adaptive and transformative capacities (Garmestani et al. 2019), learning, and flexibility (Gunderson et al. 2022).

Current disaster responses vary by location, both within and across national borders. In many cases SES responses and planning have been embraced, or at least partially implemented (Guo et al. 2021). But a narrow focus on resiliency, which persists to some degree everywhere around the world, risks repeating past failures originating in responses to perturbation that simply seek to limit variability at multiple scales (Holling and Meffe 1996) and increases the odds of a global tipping point to a “hothouse regime” (Steffen et al. 2018). Responses to disasters in SES based upon social-ecological resilience provides humanity a much better chance for a bright future moving forward in the Anthropocene.

Policy recommendations

Resiliency approaches suggest business as normal is acceptable moving forward, and that recovery is always possible given sufficient time and resources. We have argued that such an approach needs reform because the planetary conditions that have allowed for humans to thrive are rapidly degrading. Thus, approaches and responses based upon how the Earth behaved in the past are fraught with increasing risks for humanity given the rapid rate of societal and environmental change and the concomitant increasing probability of changes that limit systems’ abilities to recover.

In contrast, social-ecological resilience approaches are primarily proactive and focus on preparation before disasters and enhancing adaptive and transformative capacities of SES (Angeler et al. 2019, Garmestani et al. 2019). This is the “mitigation phase” in emergency management (Laakso and Palomäki 2013), which typically ends with a “recovery” phase. Below, we summarize and contrast resiliency approaches with social-ecological resilience approaches.

1. Efficiency: Some efficiency needs to be sacrificed for social-ecological resilience. Efficiency seeks to maximize production under rarely achieved ideal conditions; social-ecological resilience sacrifices some productivity under ideal conditions to guarantee productivity under a wide range of conditions.
2. Recovery: Baselines are rapidly changing, and recovery to a historic average is rarely possible or desirable. Instead, recover in a way that enhances social-ecological resilience (adaptive and transformative capacity of the SES) and reduces the need for recovery actions in the future.
3. Focus on linear responses: A belief that recovery is always possible given sufficient time is incorrect, can decrease social-ecological resilience over time, and wastes resources propping up the idea that a return to past conditions is possible. This belief creates the conditions for non-recoverable change; instead focus on capacities that allow for adaptation and transformation (see Chaffin et al. 2016, Angeler et al. 2019, Garmestani et al. 2019).
4. Focus on a single scale: Focusing on resisting rising sea levels (i.e., with higher levees), for example, ignores larger scale changes to the climate system that will eventually overcome resistance strategies.
5. Implicit focus on stationarity: Flexibility in responses and allowing variability in the face of change builds adaptive and transformative capacities.

A combination of approaches that incorporate all facets of resilience (Allen et al. 2019) is necessary. Sometimes resistance works, at least over short terms. Sometimes recovery is successful. But always, the systems we manage behave as complex social-ecological systems and this should be reflected in management and governance.

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