Geology topics

Cheryl A. Brown

Publications and source records attributed to Cheryl A. Brown.

4 recordsLinked to original sources

USGS2025

Blue carbon stocks along the Pacific Coast of North America are mainly driven by local rather than regional factors

Coastal wetlands, including seagrass meadows, emergent marshes, mangroves, and temperate tidal swamps, can efficiently sequester and store large quantities of sediment organic carbon (SOC). However, SOC stocks may vary by ecosystem type and along environmental or climate gradients at different scales. Quantifying such variability is needed to improve blue carbon accounting, conservation effectiveness, and restoration planning. We analyzed SOC stocks in 1,284 sediment cores along >6,500 km of the Pacific coast of North America that included large environmental gradients and multiple ecosystem types. Tidal wetlands with woody vegetation (mangroves and swamps) had the highest mean stocks to 1 m depth (357 and 355 Mg ha −1 , respectively), 45% higher than marshes (245 Mg ha −1 ), and more than 500% higher than seagrass (68 Mg ha −1 ). Unvegetated tideflats, though not often considered a blue carbon ecosystem, had noteworthy stocks (148 Mg ha −1 ). Stocks increased with tidal elevation and with fine (<63 μm) sediment content in several ecosystems. Stocks also varied by dominant plant species within individual ecosystem types. At larger scales, marsh stocks were lowest in the Sonoran Desert region of Mexico, and swamp stocks differed among climate zones; otherwise stocks showed little correlation with ecoregion or latitude. More variability in SOC occurred among ecosystem types, and at smaller spatial scales (such as individual estuaries), than across regional climate gradients. These patterns can inform coastal conservation and restoration priorities across scales where preserving stored carbon and enhancing sequestration helps avert greenhouse gas emissions and maintains other vital ecosystem services.

Pacific Coast of North America↗

USGS2012

Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries

As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.

Oregon;Washington↗

USGS2011

Moderate-resolution sea surface temperature data for the nearshore North Pacific

Coastal sea surface temperature (SST) is an important environmental characteristic in determining the suitability of habitat for nearshore marine and estuarine organisms. This publication describes and provides access to an easy-to-use coastal SST dataset for ecologists, biogeographers, oceanographers, and other scientists conducting research on nearshore marine habitats or processes. The data cover the Temperate Northern Pacific Ocean as defined by the 'Marine Ecosystems of the World' (MEOW) biogeographic schema developed by The Nature Conservancy. The spatial resolution of the SST data is 4-km grid cells within 20 km of the shore. The data span a 29-year period - from September 1981 to December 2009. These SST data were derived from Advanced Very High Resolution Radiometer (AVHRR) instrument measurements compiled into monthly means as part of the Pathfinder versions 5.0 and 5.1 (PFSST V50 and V51) Project. The processing methods used to transform the data from their native Hierarchical Data Format Scientific Data Set (HDF SDS) to georeferenced, spatial datasets capable of being read into geographic information systems (GIS) software are explained. In addition, links are provided to examples of scripts involved in the data processing steps. The scripts were written in the Python programming language, which is supported by ESRI's ArcGIS version 9 or later. The processed data files are also provided in text (.csv) and Access 2003 Database (.mdb) formats. All data except the raster files include attributes identifying realm, province, and ecoregion as defined by the MEOW classification schema.

Open-File Report↗

USGS2010

Impacts of climate change on Oregon's coasts and estuaries

Earth’s changing climate is expected to have significant physical impacts along the coast and estuarine shorelands of Oregon, ranging from increased erosion and inundation of low lying areas, to wetland loss and increased estuarine salinity. The environmental changes associated with climate change include rising sea levels, increased occurrences of severe storms, rising air and water temperatures, and ocean acidification. The combination of these processes and their climate controls are important to beach and property erosion, flood probabilities, and estuarine water quality, with the expectation of significant changes projected for the 21st century. In the following sections we attempt to summarize the most recent literature documenting historical changes as well as what may be expected to occur in response to climate change. Where little information is available we draw preliminary conclusions about the potential for specific impacts. When possible we highlight what research is needed to bridge knowledge gaps to improve our ability to identify climate change impacts more precisely, ultimately allowing for future projections.

Oregon↗