Protecting Wetlands Yields Staggering Economic Benefit, Study Finds
By Kimberly M.S. Cartier
Mangrove forests, marshes and seagrass beds protect inland areas from storm surges and strong winds. Over long periods, coastal wetlands like these build up sediment that mitigates sea level rise and local land subsidence.
A new analysis of property damage from Atlantic and Gulf of Mexico coastal storms has shown that counties with larger wetlands suffered lower property damage costs than did counties with smaller wetlands.
"Starting in 1996, the U.S. government started to produce damage estimates for each tropical cyclone in a consistent manner," explained coauthor Richard Carson, an economist at the University of California, San Diego (UCSD) in La Jolla. Before that, the data were collected only for hurricanes, which hindered past attempts to put a price on the marginal value, or price per unit, of wetlands, he said.
With the complete data set, the researchers examined all 88 tropical cyclones and hurricanes that affected the U.S. starting in 1996. That time period includes Hurricanes Katrina and Sandy.
A Protective and Economic Boon
In addition to property damage data for tropical cyclones of all strengths, "our data set has considerably more spatial resolution," Carson said, "which is a result of large amounts of information on storm tracks, property location, and wetland location all being digitized for use in a geographical information system basis."
First author Fanglin Sun, formerly at UCSD and now an economist at Amazon.com, added that "areas subject to flood risk in a county are more accurately estimated, based on local elevation data and detailed information on individual storm trajectories" and wind speeds throughout affected areas.
The finer level of detail for the storm data let the researchers finally begin connecting wetland coverage and storm damage on a county-by-county basis, Carson said. "A storm track moving a couple of kilometers one direction or the other allows the amount of wetland protection to vary within the same county."
In terms of property damage, Sun and Carson found that a square kilometer of wetlands saved an average of $1.8 million per year. Over the next 30 years, an average unit of wetlands could save $36 million in storm damage.
Some wetlands were valued at less than $800 per year per square kilometer and some at nearly $100 million. That marginal value depended on many factors, including a county's property values, existing wetland coverage, coastline shape, elevation, building codes, and chance of actually experiencing damaging winds. And each of those variables fluctuated over the 20 years the team studied.
Overall, the highest-valued wetlands were in urban counties with large populations and the lowest-valued were in rural areas with small populations. However, wetlands provided a greater relative savings against weaker cyclones and in counties with less stringent building codes — areas that might not expect or plan for a tropical storm.
The team found no significant difference in the marginal value of saltwater versus freshwater wetlands or mangroves versus marshes. "Forested wetlands tend to be better at reducing wind speed and marshes tend to be better at absorbing water," Carson said, "so the specific nature of the storm when it hits an area is likely to matter. [But] our results suggest that, on average, there is no difference."
The team published these results in Proceedings of the National Academy of Sciences of the United States of America on March 3.
Wetlands at Risk
Most areas that have experienced storm-related property damage in the past 20 years have also lost wetland coverage, the researchers found. They calculated that Floridians would have been spared $480 million in property damage from Hurricane Irma alone had the state's wetland coverage not shrunk by 2.8% in the decade prior.
Moreover, recent changes to the Clean Water Act have made the remaining coastal wetlands more vulnerable.
"The federal government, with respect to the U.S. Clean Water Act, took the position that the previous wetland studies were not reliable enough for use in assessing the benefits and cost of protecting wetlands," Carson said.
"The value coastal wetlands provide for storm protection is substantial and should be taken into account as policy makers debate the Clean Water Act," Sun said. "It's also worth noting," she added, "that storm protection for property is just one of many ecological services that wetlands provide. We hope our study will spur future research quantifying these other services as well."
With tropical storms and hurricanes expected to happen more often because of climate change, the team wrote, wetlands will be more economically valuable than ever.
Reposted with permission from The Revelator.
- Saving the World's Largest Tropical Wetland - EcoWatch ›
- Protecting the World's Wetlands: 5 Essential Reads - EcoWatch ›
- How Protecting Wetlands Can Help the Climate - EcoWatch ›
- How to Save Saltwater Wetlands From Rising Seas ›
A rare yellow penguin has been photographed for what is believed to be the first time.
- World-Renowned Photographer Documents Most Remote ... ›
- This Penguin Colony Has Fallen by 77% on Antarctic Islands ... ›
EcoWatch Daily Newsletter
By Stuart Braun
We spend 90% of our time in the buildings where we live and work, shop and conduct business, in the structures that keep us warm in winter and cool in summer.
But immense energy is required to source and manufacture building materials, to power construction sites, to maintain and renew the built environment. In 2019, building operations and construction activities together accounted for 38% of global energy-related CO2 emissions, the highest level ever recorded.
- Could IKEA's New Tiny House Help Fight the Climate Crisis ... ›
- Los Angeles City-Owned Buildings to Go 100% Carbon Free ... ›
- New Jersey Will Be First State to Require Building Permits to ... ›
By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.