Xiaodong Zhang | Search USGS

USGS2026

Calcareous nannofossil assemblage changes in the Surprise Hill core and their implications for floral response to the Paleocene-Eocene Thermal Maximum across the Salisbury Embayment of Virginia, USA

We present Paleocene-Eocene calcareous nannofossil biostratigraphy and paleoecology for the Surprise Hill core, U.S. Atlantic Coastal Plain, Virginia. Calcareous nannofossil datums ranging from Zone NP3 to NP14 were identified. The Danian-aged Brightseat Formation rests unconformably atop the Lower Cretaceous Potomac Group at 211.4 m and disconformably underlies the Aquia Formation at 208.8 m. The absence of Zone NP7 suggests a hiatus is present in the Aquia Formation (Zones NP5 – NP9a). The contact between the Marlboro Clay and the overlying Nanjemoy Formation (Zones NP10 – NP14) at 189.5 m is truncated. The Paleocene-Eocene transition is marked by a shift from glauconitic sands of the Aquia Formation to pelitic muds of the Marlboro Clay at 202.7 m. A 3–3.5‰ negative δ 13 C excursion of benthic foraminifer and a thin dissolution interval (201.6–202.5 m) are recorded in the basal Marlboro Clay. Nannofossil response to the Paleocene-Eocene Thermal Maximum (PETM) include (1) a bloom in taxa with affinities for changing salinity conditions just prior to the PETM basin wide ( Hornibrookina australis arca ), (2) a decline in taxa with ecological affinities for cool, eutrophic waters ( Chiasmolithus bidens ) during PETM, (3) fluctuations in mesotrophic to eutrophic, opportunistic taxa (e.g., Neochiastozygus junctus ) during PETM, (4) successive turnovers in species of Toweius spp. during core-PETM and its recovery. Our findings suggest that overall nannofossil assemblages in the southernmost portion of the Salisbury Embayment responded similarly to assemblages from South Dover Bridge, but had differing response to local changes in nearshore paleoecology.

Maryland, Virginia↗

USGS2026

Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder

Retrieving the phytoplankton absorption coefficient (a phy ; m−1), one of the most spectrally rich inherent optical properties, remains challenging in optically complex coastal waters worldwide. Leveraging NASA's new hyperspectral mission, PACE, we introduce Hyper-MoE-VAE, a deep-learning architecture that integrates a Mixture-of-Experts with a Variational Autoencoder to retrieve high-dimensional a phy and subsequent estimation of phytoplankton community composition (PCC) from PACE-OCI hyperspectral remote sensing reflectance (R rs ). Pre-trained on global hyperspectral bio-optical datasets and fine-tuned using regional field R rs –a phy pairings from inland– estuarine–coastal waters, Hyper-MoE-VAE demonstrated strong transferability and effective adaptation across regions. Validation with in-situ Rrs showed accurate aphy retrievals in Lake Erie (NRMSE = 0.12, ε = 17.10), Lake Pontchartrain (NRMSE = 0.11, ε = 37.12), and the Barataria–Terrebonne Estuary (NRMSE = 0.14, ε = 38.89). Using same-day PACE-OCI Level 2 Rrs, the model achieved comparable performance in Lake Erie (NRMSE = 0.19, ε = 55.19), Lake Pontchartrain (NRMSE = 0.14, ε = 51.39), and the Barataria–Terrebonne Estuary (NRMSE = 0.17, ε = 47.92). Hyper-MoE-VAE derived PACE-OCI hyperspectral aphy was further decomposed against mass-specific absorption spectra to estimate group-specific contributions to total chlorophyll a. The resulting PCC showed strong agreement with HPLC–CHEMTAX in Lake Erie ( R 2 = 0.692) and Gulf estuarine–coastal systems ( R 2 = 0.732). Monte Carlo noise experiments further revealed group-dependent sensitivities, with diatoms and dinoflagellates showing moderate susceptibility to noise, while cyanobacteria and cryptophytes exhibited narrow uncertainty distributions. These results demonstrate Hyper-MoE-VAE's capability for regional, operational water-quality monitoring with PACE-OCI and its adaptability to current and future hyperspectral missions.

Great Lakes, Lake Pontchartrain↗