Proportion of population in Pacific Island Countries and Territories (PICTs) living in Low Elevation Coastal Zones (LECZ) of 0-10 and 0-20 meters above sea level. LECZ were delineated using the bathub method overlaid on the Advanced Land Observing Satellite (ALOS) Global Digital Surface Model (AW3D30). Populations within the LECZs were estimated using the Pacific Community (SPC) Statistics for Development Division’s 100m2 population grids.

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Increased frequency and intensity of storms, saltwater intrusion, sea level rise, and warming temperatures are affecting forests along the mid-Atlantic, Southeastern, and Gulf coasts of the US. However, we still lack a clear understanding of how the structure of coastal forests is being altered by climate change drivers. Here, we used data from the Forest Inventory and Analyses program of the United States Forest Service to examine structure and biomass change in forests along the mid-Atlantic, Southeastern, and Gulf coasts of the US. We selected plots that have been resampled at low (5 m) and mid (30-50 m) elevations in coastal areas of states from Texas to New Jersey, allowing us to determine change in live trees, standing dead wood, and downed dead wood biomass (and carbon) stocks across a decade. We estimated forest attributes at the county level for each elevational class. Forest area increased by 1.9% in low elevation counties and by 0.3% in mid elevation counties. Live tree biomass density increased by 13% in low elevation counties, and by 16% in mid elevation counties. Standing dead biomass decreased in low elevation counties by 9.2% and by 2.8% in mid elevation counties. On average, downed dead wood increased by 22% in low elevation counties and decreased by 50% in mid elevation counties. Changes in the stock of C in standing and downed dead wood (0.45 to 9.1 Tg C) are similar to soil marsh C loss (9.54 Tg C). Annualized growth and harvest were both higher (16% and 58% respectively) in mid elevation counties than low elevation counties, while annualized mortality was 25% higher in low elevation counties. Annualized growth in low elevation counties was negatively correlated to sea level rise rates, and positively correlated to number of storms, illustrating tradeoffs associated with different climate change drivers. Overall, our results illustrate the vulnerability of US southeastern coastal low and mid elevation forests to climate change and sea level rise with indications that the complexity and rate of change in associated ecosystem functions (e.g., growth, mortality, and carbon storage) within the greater social environment (e.g., agricultural abandonment) may increase. Methods We used data from the National Forest Inventory and Analysis (FIA) program which, administered by the USDA Forest Service, provides a comprehensive statistical inventory and associated database of forests across the United States. The program applies standardized techniques to measure forest characteristics across a national plot sampling network of approximately one plot per 2,428 ha, with plot locations determined using a hexagonal sampling framework designed to be as spatially balanced as possible. The plot location within each 2,428 ha hexagon was visited by field crews if remotely sensed data indicated it was in forest land use (having ≥ 10% tree canopy cover, or evidence of such cover) that was at least 0.4 ha in area and 37 m wide. We focused on data for the mid-Atlantic and Southeast coast of the US, from Texas to New Jersey. We selected information from forested plots located in low (~5m) and mid elevation (30-50 m) areas with slopes less than 15%, and had either hydric conditions, or were near a water feature, which are indicative of forested wetlands. We used the FIA methodologies to estimate forest resources attributes from plot level to the county level. We looked at changes in live trees (biomass and C), standing dead wood (SD, biomass and C), and downed dead wood (biomass and C, DD). The systematic FIA sample design further allowed for statistical population-level estimates of various forest attributes, such as the area of a low-elevation forest in a county, using an “expansion factor” assigned to each plot condition. Using a design-based approach to population inference, expansion factors can be summed across plots in a population to provide an estimate of the total area within that population. Similarly, the FIA sample design allows individual trees inventoried on plots to be scaled via an expansion factor to estimate the total C of trees within an area. In this case, we calculated the area and biomass (from standing live, standing dead, and downed dead) of low-elevation and mid-elevation forests in low-elevation and mid-elevation counties, respectively, and within each state. Field crews collected a wide variety of data using standardized protocols from each FIA plot, which covered 0.067 hectares within four 7.31-m radius subplots arranged at the vertices and center of a triangle. This included the diameter, height, and species for every live and dead tree with a diameter at breast height (DBH) ≥ 12.7 cm. All trees with DBH ≥ 2.54 cm but < 12.7 cm were measured in a single 2.07-m-radius microplot within each of the plot’s four subplots. Using the component ratio method, the FIA program estimates the aboveground dry biomass of each tree with DBH ≥ 2.54 cm in pounds. Biomass and C densities were calculated by scaling plot-level data to per hectare estimates for the counties. We estimated change in the stocks of different pools by subtracting time 2 from time 1. We also looked at changes in different size classes and decay classes (for dead wood). We used data from the two latest survey evaluation periods, spanning a decade of change (Table 1). We estimated forest biomass standing stocks and change among key structural components using data from 1700 plots in low elevation counties and 3200 plots in mid elevation counties. We estimated population level values for 126 low elevation counties and 179 mid elevation counties (Fig 1). We excluded counties for which there were less than three plots in any survey year. To examine potential climate change drivers of forest dynamics we used publicly available datasets. We obtained sea level rise rates for 43 of the National Oceanic and Atmospheric Administration (NOAA) tide gauges from the Permanent Service for Mean Sea Level (PSMSL, Supplementary Table 1). We used the website to estimate rates of sea level rise from 2010-2020 to match the FIA dataset, given reports of accelerating rates of sea level rise in the Southeastern US. We calculated mean annual temperature and mean annual precipitation from the GridMet dataset (4 km2 spatial resolution), accessed through the Climate Engine portal (https://app.climateengine.org/climateEngine) for the period 2010-2020, to roughly match the FIA measurements. We also estimated change in temperature and precipitation by estimating the sen slope of each factor over the same time period using the Climate Engine portal. We used the NOAA National Hurricane Center Atlantic Hurricane Catalog (HURDAT2), accessed through Google Earth Engine, to count the number of tropical cyclones that passed through a 100 km radius buffer of the NOAA tide gauges for the same period. On average, low elevation counties were located 22.4 ± 2.6 km, while mid elevation counties were 108 ± 5.9 km from the NOAA tide gauges.

The towed-diver method is used to conduct benthic surveys, assessing large-scale disturbances (e.g., bleaching) and quantifying benthic components such as habitat complexity/type and the general distribution and abundance patterns of live coral, Crustose Coralline Algae (CCA), macroalgae, and macroinvertebrates. Surveys are conducted in the Hawaiian and Mariana Archipelagos, American Samoa, and the Pacific Remote Island Areas as part of the NOAA National Coral Reef Monitoring Program (NCRMP). A suitable method for assessing relatively large areas of reef habitat, the method involves towing a pair of SCUBA divers—one benthic and one fish—behind a small boat for approximately 50 minutes following the ~15-m depth contour and covering about 2–3 km of habitat. Each diver is equipped with a towboard and attempts to maintain a constant elevation above the surface of the reef (~1 m) for the duration of the survey. A complete towed-diver survey is divided into 10, 5-minute segments, with visual observations recorded by 5-minute segment.

The visual estimate data provided in this dataset were collected during towed-diver surveys which includes percentage cover of total live hard corals, stressed hard corals, soft corals, sand, coralline algae, and macroalgae, and the number of individual macroinvertebrates (crown of thorns starfish (COTS), sea urchins, and giant clams). Benthic habitat complexity and type data are also collected as part of the survey with the following habitat type categories: continuous reef, spur and groove, patch reefs, rock boulders, pavement, rubble flat, sand flats, pinnacle, and wall.

The data were collected around the Pacific Remote Island Areas as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led mission in 2017.

The towed-diver method is used to conduct benthic surveys, assessing large-scale disturbances (e.g., bleaching) and quantifying benthic components such as habitat complexity/type and the general distribution and abundance patterns of live coral, CCA, macroalgae, and macroinvertebrates. Surveys are conducted in the Hawaiian and Mariana Archipelagos, American Samoa, and the Pacific Remote Island Areas as part of the NOAA National Coral Reef Monitoring Program (NCRMP). A suitable method for assessing relatively large areas of reef habitat, the method involves towing a pair of SCUBA divers—one benthic and one fish—behind a small boat for approximately 50 min following the ~15-m depth contour and covering about 2–3 km of habitat. Each diver is equipped with a towboard and attempts to maintain a constant elevation above the surface of the reef (~1 m) for the duration of the survey. A complete towed-diver survey is divided into 10, 5-min segments, with visual observations recorded by 5-min segment.

The visual estimate data provided in this dataset were collected during towed-diver surveys which includes percentage cover of total live hard corals, stressed hard corals, soft corals, sand, coralline algae, and macroalgae, and the number of individual macroinvertebrates (crown of thorns starfish (COTS), sea urchins, and giant clams). Benthic habitat complexity and type data are also collected as part of the survey with the following habitat type categories: continuous reef, spur and groove, patch reefs, rock boulders, pavement, rubble flat, sand flats, pinnacle, and wall.

The data were collected around American Samoa as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led mission in 2015. These data can be accessed online via the NOAA National Centers for Environmental Information (NCEI) Ocean Archive.

The towed-diver method is used to conduct benthic surveys, assessing large-scale disturbances (e.g., bleaching) and quantifying benthic components such as habitat complexity/type and the general distribution and abundance patterns of live coral, CCA, macroalgae, and macroinvertebrates. Surveys are conducted in the Hawaiian and Mariana Archipelagos, American Samoa, and the Pacific Remote Island Areas as part of the NOAA National Coral Reef Monitoring Program (NCRMP). A suitable method for assessing relatively large areas of reef habitat, the method involves towing a pair of SCUBA divers—one benthic and one fish—behind a small boat for approximately 50 min following the ~15-m depth contour and covering about 2–3 km of habitat. Each diver is equipped with a towboard and attempts to maintain a constant elevation above the surface of the reef (~1 m) for the duration of the survey. A complete towed-diver survey is divided into 10, 5-min segments, with visual observations recorded by 5-min segment.

The visual estimate data provided in this dataset were collected during towed-diver surveys which includes percentage cover of total live hard corals, stressed hard corals, soft corals, sand, coralline algae, and macroalgae, and the number of individual macroinvertebrates (crown of thorns starfish (COTS), sea urchins, and giant clams). Benthic habitat complexity and type data are also collected as part of the survey with the following habitat type categories: continuous reef, spur and groove, patch reefs, rock boulders, pavement, rubble flat, sand flats, pinnacle, and wall.

The data were collected at coral reefs across all U.S.-affiliated regions as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led missions since 2000.