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Abstract Ecosystems vary broadly in their responses to disturbance, ranging from highly impacted to resilient or resistant. We conducted a large‐scale analysis of hurricane disturbance effects on coastal marshes by examining 20 years of data from 10 sites covering 100,000 ha at the Georgia Coastal Ecosystems Long‐Term Ecological Research site distributed across gradients of salinity and proximity to the ocean. We analyzed the impacts of Hurricanes Matthew (in 2016) and Irma (in 2017) on marsh biota (plants, crabs, and snails) and physical attributes (erosion, wrack deposition, and sedimentation). We compared these variables prior to the storms (2000–2015) to years with storms (2016, 2017) to those after the storms (2018–2020). Hurricanes generated storm surges that increased water depth and salinity of oligotrophic areas for up to 48 h. Biological variables in the marsh showed few effects of the hurricanes. The only physical variable affected was creek bank slumping; however, slumping had already increased a year before the hurricanes, suggesting that slumping could have a different cause. Thus, our study uncovered only minor, ephemeral impacts on Georgia coastal marshes, highlighting their resistance to hurricane disturbance of the lower magnitude that typically confronts this region of coastline. 

Abstract. Slump blocks are widely distributed features along marsh shorelines that can disturb marsh edge habitats and affect marsh geomorphology and sediment dynamics. However, little is known about their spatial distribution patterns or their longevity and movement. We employed an unoccupied aerial vehicle (UAV) to track slump blocks in 11 monthly images (March 2020–March 2021) of Dean Creek, a tidal creek surrounded by salt marsh located on Sapelo Island (GA, USA). Slump blocks were observed along both convex and concave banks of the creek in all images, with sizes between 0.03 and 72.51 m2. Although the majority of blocks were categorized as persistent, there were also new blocks in each image. Most blocks were lost through submergence, and both decreased in area and moved towards the center of the channel over time. However, some blocks reconnected to the marsh platform, which has not been previously observed. These blocks were initially larger and located closer to the marsh edge than those that submerged, and they increased in area over time. Only 13 out of a cohort of 61 newly created blocks observed in May 2020 remained after 5 months, suggesting that most blocks persist for only a short time. When taken together, the total area of new slump blocks was 886 m2, and that of reconnected blocks was 652 m2. This resulted in a net expansion of the channel by 234 m2 over the study period, accounting for about 66 % of the overall increase in the channel area of Dean Creek, and this suggests that slump block processes play an important role in tidal creek channel widening. This study illustrates the power of repeated UAV surveys to monitor short-term geomorphological processes, such as slump block formation and loss, to provide new insights into marsh eco-geomorphological processes. 

Abstract Predators regulate communities through top‐down control in many ecosystems. Because most studies of top‐down control last less than a year and focus on only a subset of the community, they may miss predator effects that manifest at longer timescales or across whole food webs. In southeastern US salt marshes, short‐term and small‐scale experiments indicate that nektonic predators (e.g., blue crab, fish, terrapins) facilitate the foundational grass,Spartina alterniflora, by consuming herbivorous snails and crabs. To test both how nekton affect marsh processes when the entire animal community is present, and how prior results scale over time, we conducted a 3‐year nekton exclusion experiment in a Georgia salt marsh using replicated 19.6 m²plots. Our nekton exclusions increased densities of plant‐grazing snails and juvenile deposit‐feeding fiddler crab and, in Year 2, reduced predation on tethered juvenile snails, indicating that nektonic predators control these key macroinvertebrates. However, in Year 3, densities of mesopredatory benthic mud crabs increased threefold in nekton exclusions, erasing the tethered snails' predation refuge. Nekton exclusion had no effect onSpartinabiomass, likely because the observed mesopredator release suppressed grazing snail densities and elevated densities of fiddler crabs, whose burrowing alleviates soil stresses. Structural equation modeling supported the hypotheses that nektonic predators and mesopredators control invertebrate communities, with nektonic predators having stronger total effects onSpartinathan mud crabs by controlling densities of species that both suppress (grazers) and facilitate (fiddler crabs) plant growth. These findings highlight that salt marshes can be resilient to multiyear reductions in nektonic predators if mesopredators are present and that multiple pathways of trophic control manifest in different ways over time to mediate community dynamics. These results highlight that larger scale and longer‐term experiments can illuminate community dynamics not previously understood, even in well‐studied ecosystems such as salt marshes. 

Salt marshes play a crucial role in coastal biogeochemical cycles and provide unique ecosystem services. Salt marsh biomass, which can strongly influence such services, varies over time in response to hydrologic conditions and other environmental drivers. We used gap-filled monthly observations ofSpartina alternifloraaboveground biomass derived from Landsat 5 and Landsat 8 satellite imagery from 1984-2018 to analyze temporal patterns in biomass in comparison to air temperature, precipitation, river discharge, nutrient input, sea level, and drought index for a southeastern US salt marsh. Wavelet analysis and ensemble empirical mode decomposition identified month to multi-year periodicities in both plant biomass and environmental drivers. Wavelet coherence detected cross-correlations between annual biomass cycles and precipitation, temperature, river discharge, nutrient concentrations (NO_xand PO₄^3–) and sea level. At longer periods we detected coherence between biomass and all variables except precipitation. Through empirical dynamic modeling we showed that temperature, river discharge, drought, sea level, and river nutrient concentrations were causally connected to salt marsh biomass and exceeded the confounding effect of seasonality. This study demonstrated the insights into biomass dynamics and causal connections that can be gained through the analysis of long-term data. 

Abstract Quantifying ecosystem resilience to disturbance is important for understanding the effects of disturbances on ecosystems, especially in an era of rapid global change. However, there are few studies that have used standardized experimental disturbances to compare resilience patterns across abiotic gradients in real‐world ecosystems. Theoretical studies have suggested that increased return times are associated with increasing variance during recovery from disturbance. However, this notion has rarely been explicitly tested in field, in part due to the challenges involved in obtaining long‐term experimental data. In this study, we examined resilience to disturbance of 12 coastal marsh sites (five low‐salinity and seven polyhaline [=salt] marshes) along a salinity gradient in Georgia, USA. We found that recovery times after experimental disturbance ranged from 7 to >127 months, and differed among response variables (vegetation height, cover and composition). Recovery rates decreased along the stress gradient of increasing salinity, presumably due to stress reducing plant vigor, but only when low‐salinity and polyhaline sites were analyzed separately, indicating a strong role for traits of dominant plant species. The coefficient of variation of vegetation cover and height in control plots did not vary with salinity. In disturbed plots, however, the coefficient of variation (CV) was consistently elevated during the recovery period and increased with salinity. Moreover, higher CV values during recovery were correlated with slower recovery rates. Our results deepen our understanding of resilience to disturbance in natural ecosystems, and point to novel ways that variance can be used either to infer recent disturbance, or, if measured in areas with a known disturbance history, to predict recovery patterns.