Geology topics

Thomas E. McGinnis

Publications and source records attributed to Thomas E. McGinnis.

4 recordsLinked to original sources

USGS2020

Aboveground and belowground vegetation biomass and nutrients

Wetland biomass production, decomposition, and storage of organic matter govern estuarine energy transfer, in addition to determining the physical sustainability of marshes exposed to sea-level rise and subsidence. Peak standing biomass represents an indicator of wetland production or productivity but does not account for turnover (production and decomposition) of different pools of biomass with time. Understanding the nutrient status of plant biomass can be particularly helpful in diagnosing what constituents may be limiting wetland production. The biomass and nutrient measures described in the following field/laboratory data collection procedures are designed to provide the raw data to support predictive ecosystem models, as well as answer basic wetland process questions that will help inform restoration decisions. The following procedures outline the field and laboratory methods to collect vegetation biomass and other plant or soil characteristics as needed for the SWAMP. The sampling design incorporates expanded collection from predefined target plant species that typically occur within selected CRMS stations. CPRA will provide instructions regarding any data collection adjustments that may deviate from the general steps provided herein.

Louisiana↗

USGS2020

Imagery

As part of CRMS, Digital Orthophoto Quarter Quadrangles (DOQQs) for the coastal region of Louisiana are created for years when coastwide land-water classifications are required. A DOQQ is a raster image in which displacement in the image caused by sensor orientation and terrain relief has been corrected. These images combine the image characteristics of a photo with the geometric qualities of a map. The DOQQs generated for this project consist of four components or spectral bands of information: blue, green, red and very-near infrared (VNIR). These images are referred to as Color Infrared (CIR) digital imagery. CRMS site-level assessments of land-water coverage will be based off of color-infrared photography acquired for coastal Louisiana and clipped to each 1-km2 CRMS-Wetlands site. Unless otherwise noted as a specific preliminary condition, all vegetation such as scrub-shrub, emergent vegetation, and forested areas will fall under the land classification, while open water, non-vegetated, regularly flooded mud flats, and aquatic vegetation beds will be characterized as water. CRMS imagery contracts are managed and issued by the United States Geological Survey (USGS) Wetland and Aquatic Research Center.

Louisiana↗

USGS2016

Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits ( e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km 2 ) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

Louisiana↗

USGS2013

Submergence Vulnerability Index development and application to Coastwide Reference Monitoring System Sites and Coastal Wetlands Planning, Protection and Restoration Act projects

Since its implementation in 2003, the Coastwide Reference Monitoring System (CRMS) in Louisiana has facilitated the creation of a comprehensive dataset that includes, but is not limited to, vegetation, hydrologic, and soil metrics on a coastwide scale. The primary impetus for this data collection is to assess land management activities, including restoration efforts, across the coast. The aim of the CRMS analytical team is to provide a method to synthesize this data to enable multiscaled evaluations of activities in Louisiana’s coastal wetlands. Several indices have been developed to facilitate data synthesis and interpretation, including a Floristic Quality Index, a Hydrologic Index, and a Landscape Index. This document details the development of the Submergence Vulnerability Index, which incorporates sediment-elevation data as well as hydrologic data to determine the vulnerability of a wetland based on its ability to keep pace with sea-level rise. The objective of this document is to provide Federal and State sponsors, project managers, planners, landowners, data users, and the rest of the coastal restoration community with the following: (1) data collection and model development methods for the sediment-elevation response variables, and (2) a description of how these response variables will be used to evaluate CWPPRA project and program effectiveness.

Louisiana↗