Geology topics

S. A. Hall

Publications and source records attributed to S. A. Hall.

2 recordsLinked to original sources

USGS2020

Vulnerability of resource-users in Louisiana’s oyster fishery to environmental hazards

Knowledge of vulnerability provides the foundation for developing actions that minimize impacts on people while maximizing the sustainability of ecosystem goods and services. As a result, it is becoming increasingly important to determine how resource-dependent people are vulnerable to environmental hazards. This is particularly true in coastal Louisiana where the current era of rapid land loss has the potential to undermine oyster fisheries. Yet, little is known about how such environmental change might differentially impact resource-users and stakeholders. We examined social components of vulnerability to environmental hazards using indicators of susceptibility and adaptive capacity within the oyster fishery of Terrebonne Parish, Louisiana. Specifically, we used structured interviews to compare three resource-user roles: oyster fishers, oyster fishers/lease owners, and oyster lease owners only. Results indicated that oyster fishers/lease owners were highly dependent and thus susceptible to changes in the fishery due to high levels of occupational identity. The same people, however, were the most adaptable to change, which was reflected in their willingness to learn about new practices and evolve over time; higher susceptibility in this group was offset by an increased ability to adapt, cope, and respond to changes in the environment. In contrast to these findings, oyster fishers that did not own any portion of a lease or business in which they operated were bad at coping with change and frequently held negative or fatalistic views on financial planning. These attributes made them the most vulnerable to environmental hazards. Overall, the most vulnerable participants in the Terrebonne Parish oyster fishery were those with low to moderate levels of personal and financial buffers and trust, coupled with high occupational identity and a low motivation to change. Local policy actions that target these attributes are likely to be the best entry points to reducing vulnerability of stakeholders to hazards.

Louisianna↗

USGS2005

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r 2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

Colorado↗