Frequency of pollutants listed by section 303(d) of the Clean Water Act for catchments in networks 5, 8, and 9.

<p>The counts of sediment/siltation and temperature are likely due to incompatible forestry.</p

Dendrogram showing hierarchical division of estuary networks and agglomeration schedule.

<p>The hierarchical clustering identified nine substantive networks at a Euclidean distance of 2.5. Major divisions are by development (Network 2; d = 16), impaired inflows (Networks 1, 5, 8; d = 10), and approved shellfish growing areas (Networks 4; d = 7.5).</p

Geographic summary statistics for each estuary network.

<p>Standard distance is a measure of the spatial dispersion of the network, lower values are compact, higher values are spread out. The proportion area is the total area of the network divided by the total area of all estuaries in the study. Proportion sample is the number of estuaries in the network divided by the total number in the study.</p

Map of estuary networks in the study region.

<p>Networks were created using hierarchical cluster analysis of 11 variables that represent stresses to estuaries in the region.</p

Conceptual diagram showing estuary stresses mapped from land and sea sources combined using cluster analysis to create regional networks.

<p>These networks can ideally inform local conservation actions.</p

Mean values for threat variables for each network (development, shoreline development and armoring, port facilities, toxics release, agriculture, dams, shellfish aquaculture, clearcutting, 303(d) streams, precipitation reduction).

<p>High values for any threat indicates relatively more stress on the estuary.</p

Cost-benefit analysis.

<p>Comparison of the costs and benefits of the adaptation measures. Benefit to cost ratios are represented in the vertical axis (height of the bars), with the horizontal axis noting the aggregated benefit (i.e. total averted damage), and the width of the bars the individual benefit from each measure. The blue bars identify nature-based adaptation measures, while the brown color represent the remaining adaptation measures. The values correspond to net present values with a 2% discount rate, for low future economic exposure growth and an implementation period of 20 years. Sources of images: flickr from U.S. Geological Survey, National Oceanic and Atmospheric Administration, U.S. Fish and Wildlife Service, and U.S. Geological Survey LandSat imagery.</p

Future damages-frequency curve compared to present.

<p>Values represent the expected losses for each return period (a return period R, has a probability of occurring of 1-in-R-years) across the US Gulf Coast. Current Risk is shown in grey. The contributions of the future economic exposure (red) and the change in climate (blue; which includes subsidence, sea level rise and changes in storms) are marked atop current climate risk. The dashed lines show the costs of Katrina and Andrew (updated to 2015 US$’s) for reference purposes. The contribution of economic development and climate change is assessed by calculating the risk in the future with (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192132#sec002" target="_blank">Methods</a>): the future exposure and present climate (red), and present exposure and future climate (blue).</p

Effectiveness of measures.

<p>Effectiveness of measures.</p

Comparing the cost effectiveness of nature-based and coastal adaptation: A case study from the Gulf Coast of the United States

<div><p>Coastal risks are increasing from both development and climate change. Interest is growing in the protective role that coastal nature-based measures (or green infrastructure), such as reefs and wetlands, can play in adapting to these risks. However, a lack of quantitative information on their relative costs and benefits is one principal factor limiting their use more broadly. Here, we apply a quantitative risk assessment framework to assess coastal flood risk (from climate change and economic exposure growth) across the United States Gulf of Mexico coast to compare the cost effectiveness of different adaptation measures. These include nature-based (e.g. oyster reef restoration), structural or grey (e.g., seawalls) and policy measures (e.g. home elevation). We first find that coastal development will be a critical driver of risk, particularly for major disasters, but climate change will cause more recurrent losses through changes in storms and relative sea level rise. By 2030, flooding will cost $134–176.6 billion (for different economic growth scenarios), but as the effects of climate change, land subsidence and concentration of assets in the coastal zone increase, annualized risk will more than double by 2050 with respect to 2030. However, from the portfolio we studied, the set of cost-effective adaptation measures (with benefit to cost ratios above 1) could prevent up to$57–101 billion in losses, which represents 42.8–57.2% of the total risk. Nature-based adaptation options could avert more than $50 billion of these costs, and do so cost effectively with average benefit to cost ratios above 3.5. Wetland and oyster reef restoration are found to be particularly cost-effective. This study demonstrates that the cost effectiveness of nature-based, grey and policy measures can be compared quantitatively with one another, and that the cost effectiveness of adaptation becomes more attractive as climate change and coastal development intensifies in the future. It also shows that investments in nature-based adaptation could meet multiple objectives for environmental restoration, adaptation and flood risk reduction.</p></div