A Multi-Decadal Investigation of Tidal Creek Wetland Changes, Water Level Rise, and Ghost Forests

Coastal wetlands play a vital role in protecting coastlines, which makes the loss of forested and emergent wetlands devastating for vulnerable coastal communities. Tidal creeks are relatively small hydrologic areas that feed into larger estuaries, are on the front lines of the interface between saltwater and freshwater ecosystems, and are potentially the first areas to experience changes in sea level. The goal of this study was to investigate wetland changes through time at two tidal creeks (Smith Creek and Town Creek) of the Cape Fear River estuary in southeastern North Carolina, USA, to determine if there is a spatial relationship between habitat change, physical geography characteristics, and the rate of wetland migration upstream. Historic aerial photography and recent satellite imagery were used to map land cover and compute change through time and were compared with derived physical geography metrics (sinuosity, creek width, floodplain width, floodplain elevation, and creek slope). The primary results were: (1) there was a net gain in emergent wetlands even accounting for the area of wetlands that became water, (2) wetlands have migrated upstream at an increasing rate through time, (3) land cover change was significantly different between the two creeks (P = 0.01) where 14% (67.5 ha) of Smith Creek and 18% (272.3 ha) of Town Creek transitioned from forest to emergent wetland, and (4) the transition from emergent wetland to water was significantly related to average change in creek width, floodplain elevation, and average water level. In conclusion, this research correlated habitat change with rising water level and identified similarities and differences between neighboring tidal creeks. Future research could apply the methodologies developed here to other coastal locations to further explore the relationships between tides, sea level, land cover change, and physical geography characteristics.

Wetland Dynamics Inferred from Spectral Analyses of Hydro-Meteorological Signals and Landsat Derived Vegetation Indices

The dynamic response of coastal wetlands (CWs) to hydro-meteorological signals is a key indicator for understanding climate driven variations in wetland ecosystems. This study explored the response of CW dynamics to hydro-meteorological signals using time series of Landsat-derived normalized difference vegetation index (NDVI) values at six locations and hydro-meteorological time-series from 1984 to 2015 in Apalachicola Bay, Florida. Spectral analysis revealed more persistence in NDVI values for forested wetlands in the annual frequency domain, compared to scrub and emergent wetlands. This behavior reversed in the decadal frequency domain, where scrub and emergent wetlands had a more persistent NDVI than forested wetlands. The wetland dynamics were found to be driven mostly by the Apalachicola Bay water level and precipitation. Cross-spectral analysis indicated a maximum time-lag of 2.7 months between temperature and NDVI, whereas NDVI lagged water level by a maximum of 2.2 months. The quantification of persistent behavior and subsequent understanding that CW dynamics are mostly driven by water level and precipitation suggests that the severity of droughts, floods, and storm surges will be a driving factor in the future sustainability of CW ecosystems.

Evaluation of Approaches for Mapping Tidal Wetlands of the Chesapeake and Delaware Bays

The spatial extent and vegetation characteristics of tidal wetlands and their change are among the biggest unknowns and largest sources of uncertainty in modeling ecosystem processes and services at the land-ocean interface. Using a combination of moderate-high spatial resolution (≤30 meters) optical and synthetic aperture radar (SAR) satellite imagery, we evaluated several approaches for mapping and characterization of wetlands of the Chesapeake and Delaware Bays. Sentinel-1A, Phased Array type L-band Synthetic Aperture Radar (PALSAR), PALSAR-2, Sentinel-2A, and Landsat 8 imagery were used to map wetlands, with an emphasis on mapping tidal marshes, inundation extents, and functional vegetation classes (persistent vs. non-persistent). We performed initial characterizations at three target wetlands study sites with distinct geomorphologies, hydrologic characteristics, and vegetation communities. We used findings from these target wetlands study sites to inform the selection of timeseries satellite imagery for a regional scale random forest-based classification of wetlands in the Chesapeake and Delaware Bays. Acquisition of satellite imagery, raster manipulations, and timeseries analyses were performed using Google Earth Engine. Random forest classifications were performed using the R programming language. In our regional scale classification, estuarine emergent wetlands were mapped with a producer’s accuracy greater than 88% and a user’s accuracy greater than 83%. Within target wetland sites, functional classes of vegetation were mapped with over 90% user’s and producer’s accuracy for all classes, and greater than 95% accuracy overall. The use of multitemporal SAR and multitemporal optical imagery discussed here provides a straightforward yet powerful approach for accurately mapping tidal freshwater wetlands through identification of non-persistent vegetation, as well as for mapping estuarine emergent wetlands, with direct applications to the improved management of coastal wetlands.

Checklist of bees (Hymenoptera: Apoidea) from managed emergent wetlands in the lower Mississippi Alluvial Valley of Arkansas

Here we present the results from a two-year bee survey conducted on 18 managed emergent wetlands in the lower Mississippi Alluvial Valley of Arkansas, USA. Sample methods included pan traps, sweep netting and blue-vane traps. We document 83 bee species and morphospecies in 5 families and 31 genera, of which 37 species represent first published state records for Arkansas. The majority of species were opportunistic wetland species; only a small number were wetland-dependent species or species largely restricted to alluvial plains.We present new distributional records for bee species not previously recorded in managed emergent wetlands and report specimens of thirty-seven species for which no published Arkansas records exist, expanding the known ranges ofCeratinacockerelli,Diadasiaenavata, Lasioglossumcreberrimum, SvastracressoniiandDieunomiatriangulifera. We also distinguish opportunistic wetland bee species from wetland-dependent and alluvial plain-restricted species.