Results for “VEGETATION Newsletter”

USGS1995

Monitoring seasonal dynamics of North America grasslands using VEGETATION

No abstract available.

VEGETATION Newsletter↗

USGS2023

Riparian vegetation response amid variable climate conditions across the Upper Gila River watershed: informing Tribal restoration priorities

Restoring degraded river systems is an enormous challenge, especially given the uncertainty in a time of climate change. Here, Roy Petrakis explains how restoration approaches informed by remote sensing and a climate adaptation framework increase the potential for overall success. He discusses research being done on the Gila River as a case study of how it might work.

Arizona, New Mexico↗

USGS2020

Quantifying microplastics in Indiana’s Lake Michigan watershed and submerged aquatic vegetation

Environmental breakdown of plastics produces synthetic microfibers, a class of microplastics that are most prevalent in surface waters. A main source of these pollutants is wastewater treatment plants which discharge into surface waters, including those that flow into Lake Michigan. Microplastics can settle into aquatic sediment or exist for lengths of time in the swash zone of the lakes; they can be ingested by organisms or concentrated in algae or other lake plankton, among other possibilities. As part of a larger Great Lakes study of the growth and senescence of submerged aquatic vegetation (SAV), the loads of synthetic microfibers in the SAV have been determined from Lake Michigan samples collected during the summer months of 2018, 2019 and 2020, and from various samples collected in the watershed and along the shoreline in Northwest Indiana. In order to effectively address microplastics pollution, a complete understanding of the distribution and fate of these pollutants is needed; this project is working toward that goal.

Indiana↗

USGS2002

Monitoring dust storms and mapping landscape vulnerability to wind erosion using satellite and ground-based digital images

Wind-induced dust emission in the southwestern United States is important regionally because of its impact on human health and safety and its influence on ecosystem dynamics. Factors that control dust emission include wind velocity, sediment availability, and surface conditions (e.g., vegetation type and degree of cover, surface crusts and armoring, and soil moisture - Gillette and Passi, 1988; Gillette and Hanson 1989; Marticorena and others, 1997). Emission of dust from the land surface is a process of degradation that depletes fine-grained minerals needed for optimum vegetation growth, creates potentially hazardous air quality for humans on a local and regional scale, and can affect climate on a regional and global scale. Future climatic change may lead to increased aridification of southwestern deserts, reducing protective vegetation and enhancing dust emissions, thereby increasing the impacts of dust in this region. It is currently not well understood how climate change in the Southwest will affect dust emission and, in turn, how dust emission will affect climate and human health. As part of a study of landscape vulnerability to wind erosion and the potential impacts of dust, we are investigating remotely sensed satellite, airborne, and ground-based image data to determine their ability to detect and monitor active dust storms, as well as to map areas vulnerable to wind erosion. A main objective has been to investigate the use of high temporal resolution digital images collected by satellite and a long-term, ground-based digital camera station, along with wind data collected at our field sites, to detect, monitor, and analyze the location, size, frequency, duration, and transport patterns of dust storms in the Mojave Desert of the southwestern United States. Generally, many current methods and instruments are not developed to the level required to routinely detect and monitor dust storms or to develop models that accurately predict total dust flux and emission rates. Improving these capabilities is critical to generating baseline datasets for assessments of landscape vulnerability to future climate change. On going modeling efforts are attempting to identify meteorological parameters and soil surface roughness parameters needed to predict the vulnerability of various geomorphic substrates to wind erosion. Datasets to calibrate model results are difficult to collect and typically not available. Results of our studies, incorporating digital image maps and new methods using remotely sensed images to identify and monitor dust sources, will be useful for the calibration of dust-emission models of the Mojave Desert and other arid environments. At the same time, we are exploring new methods to map the amount, sizes, and spatial distribution of particles at the surface to enable detailed wind-erosion vulnerability mapping at a regional scale.

California↗