Aboveground carbon loss associated with the spread of ghost forests as sea levels rise

Abstract

Coastal forests sequester and store more carbon than their terrestrial counterparts but are at greater risk of conversion due to sea level rise. Saltwater intrusion from sea level rise converts freshwater-dependent coastal forests to more salt-tolerant marshes, leaving ‘ghost forests’ of standing dead trees behind. Although recent research has investigated the drivers and rates of coastal forest decline, the associated changes in carbon storage across large extents have not been quantified. We mapped ghost forest spread across coastal North Carolina, USA, using repeat Light Detection and Ranging (LiDAR) surveys, multi-temporal satellite imagery, and field measurements of aboveground biomass to quantify changes in aboveground carbon. Between 2001 and 2014, 15% (167 km2) of unmanaged public land in the region changed from coastal forest to transition-ghost forest characterized by salt-tolerant shrubs and herbaceous plants. Salinity and proximity to the estuarine shoreline were significant drivers of these changes. This conversion resulted in a net aboveground carbon decline of 0.13 ± 0.01 TgC. Because saltwater intrusion precedes inundation and influences vegetation condition in advance of mature tree mortality, we suggest that aboveground carbon declines can be used to detect the leading edge of sea level rise. Aboveground carbon declines along the shoreline were offset by inland aboveground carbon gains associated with natural succession and forestry activities like planting (2.46 ± 0.25 TgC net aboveground carbon across study area). Our study highlights the combined effects of saltwater intrusion and land use on aboveground carbon dynamics of temperate coastal forests in North America. By quantifying the effects of multiple interacting disturbances, our measurement and mapping methods should be applicable to other coastal landscapes experiencing saltwater intrusion. As sea level rise increases the landward extent of inundation and saltwater exposure, investigations at these large scales are requisite for effective resource allocation for climate adaptation. In this changing environment, human intervention, whether through land preservation, restoration, or reforestation, may be necessary to prevent aboveground carbon loss.

Sea Level‐Driven Marsh Migration Results in Rapid Net Loss of Carbon

“…However, previous work suggests that living trees dominated the aboveground C stock while dead woody vegetation comprised <9% of aboveground C (K. Krauss et al., 2018). Additionally, far greater C stocks in live tree biomass than in marsh soils (Figures 2a, Smart et al., 2020) suggests that most carbon stored in live trees does not persist in marsh soils and is instead lost through decomposition, as indicated by rapid decomposition rates (Kozlowski, 1997) and elevated tree methane fluxes near the marsh‐forest boundary (Martinez & Ardon, 2021; Norwood et al., 2020). This indicates that forest carbon preservation is relatively small, but the exact quantification of preserved forest carbon is still unknown.…”

Long-Term Community Dynamics Reveal Different Trajectories for Two Mid-Atlantic Maritime Forests

“…In order to enhance or support resilience of ecosystems, it is important to know which factors contribute to their maintenance. Geographic location of coastal and maritime forests coupled with elevation may be critical factors that determine how ecosystems will respond to RSLR and may be a significant form of maintenance for maritime forests [33,[67][68][69][70][71]. Savage Neck Dunes forest is protected from the full force of storms through position on the bayside and large intact dunes.…”

Quantifying Drivers of Coastal Forest Carbon Decline Highlights Opportunities for Targeted Human Interventions

“…We mapped aboveground biomass change between 2001 and 2014 using a combination of field measurements, repeat light detection and ranging (LiDAR) surveys (see Table S1 for specifications) [54,55], and Landsat imagery (see Table S2 for specifications) [49,56]. We quantified vegetation structure and composition with metrics derived from LiDAR and Landsat data for 2001 and 2014 (see Tables S3 and S4 for complete lists of satellite-derived and LiDAR-derived variables).…”

“…We quantified vegetation structure and composition with metrics derived from LiDAR and Landsat data for 2001 and 2014 (see Tables S3 and S4 for complete lists of satellite-derived and LiDAR-derived variables). To relate the remote sensing metrics to aboveground biomass, we inventoried the size and density of woody vegetation in 98 plots of 12 m radius [57] across a vegetation gradient from forest to marsh [49]. We calculated total (e.g., woody and herbaceous species) aboveground biomass in megagrams per hectare (Mg ha −1 ), from these field measurements using established allometric equations [58][59][60] relating diameter at breast height (dbh) or percent cover to total aboveground biomass.…”

“…Carbon has been successfully estimated using derived spectral metrics from multispectral satellite imagery [32][33][34], structural metrics from light detection and ranging (LiDAR) data [35][36][37][38], or a combination of the two [39][40][41] in correlative models linking these metrics with field data and has become a common source for carbon estimation at regional scales. Access to multitemporal remote sensing data provides additional opportunities to measure change in carbon stocks over time; however regional analyses assessing carbon dynamics have focused on upland forests (e.g., [42][43][44][45]), herbaceous marsh (e.g., [46]), and mangrove forests (e.g., [47,48]) and not temperate coastal forests (however, see [49]). These studies also do not quantify the combined effects of the natural and anthropogenic factors driving carbon variability and change at regional scales, nor do they account for the spatial heterogeneity in the strength of the relationships between drivers and aboveground carbon stocks by implementing appropriate spatial modeling approaches.…”