Geology topics

Steven Sesnie

Publications and source records attributed to Steven Sesnie.

4 recordsLinked to original sources

USGS2024

Lidar estimation of storage capacity for managed water resources used by Desert Bighorn Sheep (Ovis canadensis mexicana) at Cabeza Prieta National Wildlife Refuge, Arizona

In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey Southwest Biological Science Center employed ground-based light detection and ranging (lidar) during February 2022 to help meet two resource management objectives at the Cabeza Prieta National Wildlife Refuge (CPNWR), Arizona. The two objectives are (1) characterize the water storage capacity for one developed and two modified tanks, which are bedrock catchments also referred to as tinajas, that are important water sources for desert bighorn sheep ( Ovis canadensis mexicana ) in designated wilderness at the CPNWR; and (2) develop a stage-storage model to estimate water volumes from monitoring observations of water surface levels in each tank. We measured storage capacity for the three tanks identified by refuge managers, Buckhorn, Senita, and Eagle, using ground-based lidar collected during February 2022. These data produced high-resolution (centimeter scale) topographic models that improved estimates of maximum water storage capacity over previous geometry-based estimates, permitting estimations of storage capacity at multiple water surface levels (stage heights). We found that the maximum water storage capacity for the Buckhorn, Senita, and Eagle tanks was 9,108.730, 8,623.308, and 6,039.603 US gallons (gal), respectively. For each tank we report a stage-storage model based on a polynomial function that best explained variability in water storage capacity as a function of water stage height. The results presented herein will permit the CPNWR managers to (1) easily estimate water available for wildlife at any point of time, (2) interpret tank recharge following rainstorms, and (3) decide whether and when to transport water via vehicles to mechanically refill the tanks in designated wilderness.

Arizona↗

USGS2021

Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland

The spread of flammable invasive grasses, woody plant encroachment, and enhanced aridity have interacted in many grasslands globally to increase wildfire activity and risk to valued assets. Annual variation in the abundance and distribution of fine-fuel present challenges to land managers implementing prescribed burns and mitigating wildfire, although methods to produce high-resolution fuel estimates are still under development. To further understand how prescribed fire and wildfire influence fine-fuels in a semi-arid grassland invaded by non-native perennial grasses, we combined high-resolution Sentinel-2A imagery with in situ vegetation data and machine learning to estimate yearly fine-fuel loads from 2015 to 2020. The resulting model of fine-fuel corresponded to field-based validation measurements taken in the first (R 2 "> 2 = 0.52, RMSE = 218 kg/ha) and last year (R 2 "> 2 = 0.63, RMSE = 196 kg/ha) of this 6-year study. Serial prediction of the fine-fuel model allowed for an assessment of the effect of prescribed fire (average reduction of −80 kg/ha 1-year post fire) and wildfire (−260 kg/ha 1-year post fire) on fuel conditions. Post-fire fine-fuel loads were significantly lower than in unburned control areas sampled just outside fire perimeters from 2015 to 2020 across all fires ( t = 1.67, p < 0.0001); however, fine-fuel recovery occurred within 3–5 years, depending upon burn and climate conditions. When coupled with detailed fuels data from field measurements, Sentinel-2A imagery provided a means for evaluating grassland fine-fuels at yearly time steps and shows high potential for extended monitoring of dryland fuels. Our approach provides land managers with a systematic analysis of the effects of fire management treatments on fine-fuel conditions and provides an accurate, updateable, and expandable solution for mapping fine-fuels over yearly time steps across drylands throughout the world

Arizona↗

USGS2020

Identifying sustainable winter habitat for whooping cranes

The only self-sustaining population of endangered whooping cranes ( Grus americana ) requires a network of conservation lands for wintering along the Texas Gulf Coast (USA), so that this increasing population can reach downlisting under the Endangered Species Act (1,000 birds). We identify locations providing the highest quality and most sustainable wintering habitat for these whooping cranes through 2100 by predicting future habitats under three projections of sea level rise (0.6, 1.0 and 2.0 m by 2100), while incorporating two scenarios of future urban development. Our method combines predictions of future habitat quality with current whooping crane density estimates to calculate the potential carrying capacity of whooping cranes for each 10 m pixel within this 17,725 km 2 area. We found whooping cranes used locations with salt marsh at twice the rate of places lacking marsh. Areas > 15 km from development or < 2 km from estuarine water had increased crane use. Predicted area of salt marsh habitat oscillated across time given different rates of sea level rise. One urbanization scenario predicted 3% and the other 1% of the area converting to development by 2100. We estimated the study area can support 4414 (95% CI: 4096-4789) whooping cranes currently, 4795 (95% CI: 4402-5269) with 0.6 m sea level rise, 3559 (95% CI: 3352-3791) with 1 m sea level rise, and 2480 (95% CI: 2375-2592) with 2 m sea level rise by 2100, under the more aggressive urban development scenario. By anticipating climate-induced habitat loss with species population expansion we provide the requisite spatial information for conservation planners to build a sustainable conservation estate for downlisting whooping cranes. By coupling wildlife biology with conservation planning and on-the-ground implementation, our work exemplifies a proactive approach to recover endangered species.

Texas↗

USGS2016

Managing water and riparian habitats on the Bill Williams River with scientific benefit for other desert river systems

This report details modeling to: 1) codify flow-ecology relationships for riparian species of the Bill Williams River as operational guidance for water managers, 2) test the guidance under different climate scenarios, and 3) revise the operational guidance as needed to address the effects of climate change. Model applications detailed herein include the River Analysis System (HEC-RAS) and the Ecosystem Functions Model (HEC-EFM), which was used to generate more than three million estimates of local seedling recruitment areas. Areas were aggregated and compared to determine which scenarios generated the most seedling area per unit volume of water. Scenarios that maximized seedling area were grouped into a family of curves that serve as guidance for water managers. This work has direct connections to water management decision-making and builds upon and adds to the rich history of science-based management for the Bill Williams River, Arizona, USA.

Arizona↗