1. Introduction
Coastal wetlands provide crucial ecosystem services, with these landscapes acting as nekton nurseries, providing wave attenuation, absorbing carbon, and improving water quality by sequestering and removing excess nutrients [
1,
2]. Coastal wetlands must vertically gain elevation (sediment accretion) at rates greater than or equal to sea-level rise (SLR) to resist converting to mudflats or open water. Yet, it is unclear if coastal marshes will be able to keep up with the current pace of SLR, especially in the mid-Atlantic, where SLR rates are three to four times higher than global averages [
3].
Accelerated SLR threatens coastal landscapes as the vegetation community has varying tolerances to increased inundation and salinity [
4]. The vegetation of the estuarine landscape is unique as individual plant species are adapted to live in areas with specific salinity and moisture regimes controlled by the influx of tides and groundwater [
5]. Therefore, increased inundation and saltwater intrusion from SLR can shift the thresholds of vegetation species, leading to the reconstruction of plant zonation of the coastal landscape [
6,
7,
8,
9] (
Figure 1). Marsh vertical accretion rates less than SLR can cause these ecosystems to convert to open water (i.e., marsh drowning); however, marsh vegetation can migrate upslope into the upland forest to resist conversion [
10,
11,
12]. This conversion from upland forest to tidal marsh is termed “marsh migration” and may offset marsh loss caused by erosion at the seaward edge [
8,
9,
13].
As the upland forest becomes increasingly exposed to inundation and salinity with gradual SLR, changes to the edaphic characteristics inhibit regeneration and ultimately lead to mature tree death [
9,
11,
14]. The subsequent and successive forest dieback and the lack of regeneration of new trees increase light exposure, allowing salt-tolerant halophytic plants to colonize the formerly forested area. As upland forests are converted into a marsh, what remains are standing tree snags and stumps surrounded by marsh vegetation often termed ‘
ghost forests’ [
4,
12,
15].
Rapid conversion from forest to marsh and the development of ghost forests can also occur following an intense storm. Accelerated SLR and coastal storms are inherently linked, as storms’ flooding frequency dramatically increases with higher sea levels [
11,
12,
16]. Additionally, global warming is likely to intensify and increase the frequency of coastal cyclones in the North Atlantic ocean, compounding the effects of SLR-induced flooding on coastal landscapes [
17]. Strong winds and storm surges produced by coastal storms can cause rapid forest dieback. Strong winds damage the physical forest structure, leading to canopy defoliation and tree uprooting, whereas prolonged flooding from intensified storm surges starves the soil of oxygen and promotes the activity of sulfide-producing bacteria, creating a toxic environment for upland plants [
11,
18,
19,
20]. Additionally, increased soil salinity can lead to canopy browning, defoliation, alter freshwater uptake by roots, and inhibit forest regeneration [
19,
21,
22,
23]. Forest dieback and lack of forest regeneration from episodic events can facilitate rapid marsh migration as short-term forest recovery may not be possible, leading to the transition from forest to marsh over much shorter time scales. Moreover, forest dieback triggered by a strong storm may pave the way for further upslope marsh expansion as the forest seedlings may be more sensitive to the effects of gradual SLR, thereby shifting the regeneration niche further inland [
9].
In contrast to the landscape effects of increased tidal flooding, upland environments can also be converted into marshes from saltwater intrusion into the groundwater. Although linked with gradual SLR, the result of saltwater intrusion on upland habitats may precede the effects of increased tidal inundation [
24].
Marsh migration may be the most salient process for estimating future wetland resiliency to accelerated SLR and frequency in coastal storms. Recent evidence has suggested that global wetlands’ resiliency primarily depends on the availability of accommodation space or adequate lateral space for wetlands to colonize and persist with SLR [
25,
26]. However, the timing and process by which the marsh vegetation replaces upland vegetation are poorly understood, as many factors influence the ability for upslope migration and future resiliency to SLR (e.g., sediment supply, accretion rates, topography, management, land use, and hydrology) [
11,
12,
26].
Evidence supports that upland forest dieback driven by accelerated SLR may vary over spatial scales as specific site conditions could influence various magnitudes of forest dieback; however, there is limited literature using remote sensing to understand large scale coastal forest decline and its mirror image–inland marsh migration [
3,
10,
26,
27]. Previous work has focused on measuring upslope marsh expansion and subsequent forest dieback over time using historical aerial photographs and other optical sensors [
4,
27,
28,
29]. While this approach helps trace the landward migration of marshes into forests that have been defoliated, more subtle changes to the forest structure, such as loss in canopy height, could be early signs of initial marsh expansion before extensive forest dieback occurs.
Forest structure changes can be observed using Lidar remote sensing [
30,
31]. The height of the vegetation can act as an indicator for species composition, successional stage, climate, and land cover classification [
30]. Furthermore, the combination of high-resolution Lidar data and high-resolution aerial imagery may be a powerful tool to classify and monitor changes associated with marsh migration [
32]. This combination results in better classification accuracy than with imagery alone [
32]. For example, Smart et al. [
3] used multitemporal Lidar and spectral indices derived from Landsat to map ghost forests along the Albemarle-Pamlico Peninsula in North Carolina; however, the multi-temporal Lidar was resampled to match the resolution associated with Landsat (30-m). This coarser resolution may miss areas experiencing initial dieback along the upland-marsh boundary, especially in areas where the widths of forests adjacent to tidal wetlands are thin. Thus, there is considerable interest in exploring the potential of high-resolution Lidar and imagery toward detecting changes in forest structure as an indicator for future marsh migration.
In this paper, we quantify recent coastal forest loss between 2007 to 2015 in the coastal areas in Delaware using multi-temporal high-resolution imagery from the National Agriculture Imagery Program (NAIP) and publicly available airborne Lidar. The remainder of this paper is as follows: we first discuss the data and methodology used for the change detection, then report the area of recent forest loss and investigate larger landscape patterns and potential predictors for forest loss within the local 12-Hydrologic Unit Code (HUC-12) watersheds. We further explore the utility of airborne Lidar to observe changes to canopy height that may be associated with forest structure changes ensued by marsh migration. Finally, we discuss relevant environmental drivers that may have induced the rapid conversion of forest to marsh over this sub-decadal timespan.
4. Discussion
Between 2007 and 2015, we quantified widespread forest loss along two coastal counties in Delaware. Forest losses were concentrated in the Delaware Bay estuary’s southern, more coastal watersheds and negatively correlated with watershed drainage density. Over this short time, the forest loss is consistent with rapid marsh migration, likely driven by a series of episodic events exacerbated by climate change and gradual sea-level rise. In the following discussion, we provide further insight into the results and limitations of this study.
4.1. Classification and Change Map
Coastal ecosystems are challenging to monitor using remote sensing as they are highly dynamic and heterogeneous landscapes. However, the increased availability of data with high spatial and temporal resolution coupled with machine learning classification algorithms could assist in monitoring coastal ecosystem change. This study is one of the few that quantify recent upland forest loss due to marsh migration in Delaware Bay using high-resolution Lidar and imagery. Our classification and subsequent post-classification analysis mapped recent forest loss likely due to marsh migration. Although the user accuracy of forest loss derived from the change map was relatively inaccurate (~49%), the estimated area was “error-adjusted” to reflect the classification error within a confidence interval. While this method is considered a best practice for quantifying post-classification accuracy, many studies leave out the erroneous area attributed to classification error. Overlooking these errors could lead to dramatic differences in numerical models that utilize land change estimates (e.g., carbon flux, carbon storage, biomass loss) [
44].
The classification errors accompanying forest change (i.e., forest loss, forest growth) may be attributable to the species composition in the ecotone between the upland forest and the marsh platform. This ecotone is primarily compromised of P. australis. These invasive reeds are tall, typically between 2 to 5 m, have a high NDVI value, and are known to colonize rapidly, which we speculate may be easily misclassified as forest in 2009 or 2015 forest/non-forest maps, leading to the errors in the mapping of forest loss and forest growth. The sources of misclassification would be better interpreted with ground truth landcover reference data. However, ground-truth samples were not available for the periods of our study.
4.2. Landscape Change Analysis
We found that watersheds with higher drainage densities are less likely to experience forest dieback than subregions with lower drainage densities. We were surprised by the negative drainage density coefficient, but this finding is consistent with the results by White et al. (2021), which also found a significant negative coefficient for drainage density when evaluating the predictive power for freshwater forested wetland loss in HUC-4 subregions in the North American coastal plain. While other work has shown that increased connectivity to saline water bodies can drive the salinization and subsequent deforestation of freshwater habitats [
27,
51,
52], we suspect that improper drainage from historic tidal impoundments in our study area may be contributing to upland dieback compared to other regions that may have better drainage networks.
The current tidal impoundments in Delaware serve as a habitat for waterfowl and recreational areas. Yet, these impoundments may have been breached during intense storms, contributing to the rapid conversion from forest to marsh. Inundation from storm surges in impounded areas may not be able to recede as fast as areas that have tidal access, leading to more significant forest dieback [
53]. More research is needed to address how historic and current management of these impoundments will affect future marsh migration routes [
53].
Ground elevation is a principal determinant of the forest–marsh boundary and its movement with SLR [
52,
53]. Although we did not find average watershed elevation to be a significant predictor of increased forest loss, we found that ground elevation decreased in areas that experienced forest dieback from 2007 to 2014, suggesting that pulses of inundation from episodic events may be causing root breakdown and ground subsidence, reflected in overall lower ground elevations. This finding agrees with much of the marsh migration literature, which suggests that trees in lower elevations are likely to be converted to marsh first, whereas trees in higher elevations may be able to persist as higher elevations limit the reaches of inundation [
7,
11,
52,
54,
55].
Increased inundation inland, whether from gradual SLR or episodic events, changes the ecosystem function of forested habitats, which may manifest in vertical forest structure changes. Forest height and the variability in height may provide early evidence of forest seral stage or disturbance to the vegetation [
30,
56]. Our results show that average canopy height decreased in areas of forest loss over our study period, whereas in regions classified as stable forest and growth, canopy height increased, highlighting the potential of Lidar to provide important information on structural changes attributed to forest retreat before mortality.
Additionally, we can explore particular forest characteristics that may be more susceptible or resilient to marsh migration using data from Lidar. For example, we found that, on average, taller trees (>16 m) do not experience as much dieback as trees that are shorter (<12 m). We speculate that taller forests with more established root systems may allow for enhanced resiliency as deeper roots may access the fresh groundwater from deeper depths [
57]. In contrast, shorter forest stands with shallower root systems may be more susceptible to salt stress due to increased exposure to tidal inundation or saltwater intrusion in the groundwater. Our findings are supported by Krauss et al. 2009 [
58], who found reductions in freshwater forest height and basal area of areas impacted by saltwater intrusion. Further research is required to determine forest resiliency in response to episodic events of inundation and increased saltwater intrusion.
We also characterized canopy dynamics using a height transition matrix, and while we found that taller height classes tended to remain stable, we identified that all height classes had at least a 7% chance of converting to the shortest height class (< 2 m), indicating a possible disturbance that affected all height classes. This perturbation may have resulted from prolonged edaphic stress on the forest, which could have resulted in widespread canopy thinning consistent with the effects of marsh migration.
Our transition matrix displays a mortality rate (inferred by height losses) of ~1% per year, which is consistent with estimations of mortality from the United States Forest Service (USFS) of approximately 1–2% [
59]. However, the USFS rate includes mortality by harvesting and it is unclear how this mortality rate may extend to coastal forest dieback associated with the effects of accelerated SLR [
60].
While Lidar can be a powerful tool to map canopy height over broad scales, validating Lidar-derived height changes can be challenging. Both Lidar acquisitions had a vertical accuracy within 18.5 cm, as defined by the National Digital Elevation Program (NDEP) [
61], but we did not have any field height measurements to validate Lidar-derived height changes during our study period. Additionally, the Lidar used for our analysis had low point densities, which could have led to height errors due to points not reaching the ground. Therefore, future efforts should use higher point density Lidar to monitor structural changes through time.
We suspect that regime shifts in the understory could have occurred during our study period (invisible migration, [
62]); however, we did not quantify changes to vegetation under the canopy. Additionally, changes to the forest composition, namely, invasions of
P. australis, could be early signals of marsh migration as
P. australis is often the first to colonize and can colonize in the understory [
8]. As such, future studies using higher resolution Lidar may assist in detecting changes to the understory that are typically limited by canopy cover.
4.3. Drivers for Forest Loss–Episodic Events
The timing and spatial distribution of forest dieback within the estuary suggest that forest mortality reflects the effects of rapid marsh migration following a series of episodic events. Sea level increased by approximately 2.5 cm over our study period (9 years), which is lower than the present rate of SLR (3.76 ± 0.43 mm/year, [
63]), leading us to investigate additional drivers that may have caused rapid rates of marsh migration [
63].
Over our study period, there were four major coastal storms, here defined as tropical cyclones that were within 30 km of the Delaware coast, categorized based on the Saffir-Simpson Hurricane Wind Scale (i.e., Tropical storm Hanna, 2011; Hurricane Irene, 2011; Hurricane Sandy, 2012; Tropical storm Andrea, 2013). Each of these storms could have caused prolonged flooding, windthrow, and saltwater intrusion to the groundwater, all of which may have contributed to the forest mortality (
Table 6) [
64]. These hydrologically connected areas are low-lying with shallow groundwater depths, making them, particularly at risk for saltwater intrusion [
52,
65].
Another consideration to be investigated is the effect of drought on coastal tree mortality. Drought conditions can intensify the impacts of the gradual sea-level rise as the availability of fresh groundwater in areas with active marsh transgression is essential for forest stands to cope with salinity pulses [
7,
24,
54,
65]. However, if fresh groundwater is limited (e.g., drought-induced), salt-stressed forested regions will begin to convert to marsh [
58]. Additionally, severe droughts can cause increased saltwater intrusion into the groundwater because the lack of precipitation allows the salt pulse from the tides to persist, whereas, with regular rainfall events, those salt pulses associated with the tides tend to get diluted [
24]. During prolonged drought events, especially during the growing season when temperatures are hot and evapotranspiration by the vegetation is highest, groundwater can become hypersaline and result in pulses of tree mortality [
54].
A considerable drought occurred in the mid-Atlantic in the summer of 2011. The Palmer Drought Severity Index (PDSI) for the study area indicated extreme drought conditions with values between −4.0 to −4.70 during the growing season [
66]. We suggest that this severe drought, followed by Hurricane Irene in 2011, with almost a direct hit on the Delaware coast, could have been the main driver for the forest loss and subsequent shift in habitat ranges during our study period. This finding is consistent with previous work during the same time interval in the Chesapeake Bay and Albemarle-Pamlico Estuaries [
7,
65].
5. Conclusions and Future Directions
This study used publicly available Lidar and NAIP imagery fusion to detect forest losses related to recent marsh migration in two counties along the Delaware Bay Estuary. Although our analysis showed changes in canopy height, our Lidar point density was low, and future efforts to monitor structural changes through time should use the highest point density that is practical and affordable. With state and federal funding for routine airborne Lidar data acquisitions becoming more common, Lidar can be a powerful tool for natural resource managers to map potential marsh conservation corridors as the effects of accelerated sea-level rise persist. In addition, Lidar has the ability to map the upland vegetation’s three-dimensional vertical structure, which may enable early detection of initial landscape-level changes associated with sea-level rise and coastal storms ahead of widespread forest dieback.
As policy moves toward expanding coastal wetland restoration to carbon markets and state climate action plans, we first need to determine if, where, and how tidal marshes are expanding into the upland forest to cope with accelerated SLR. Efforts to map marsh migration and upland forest retreat need to consider the effects of SLR while also accounting for extreme events (i.e., hurricanes, drought) as they are inherently linked to global climate change and, as we have shown in this study, may result in rapid marsh migration and extensive forest dieback on sub-decadal timescales.