A5059956331- Rangeland and Wildlife Management
- Fire effects on ecosystems
- Ecology and Vegetation Dynamics Studies
- Plant Water Relations and Carbon Dynamics
- Turfgrass Adaptation and Management
- Species Distribution and Climate Change
- Remote Sensing in Agriculture
- Atmospheric and Environmental Gas Dynamics
- Climate variability and models
- Bioenergy crop production and management
- Soil Carbon and Nitrogen Dynamics
- Remote Sensing and Land Use
- Landslides and related hazards
- Peatlands and Wetlands Ecology
- Urban Heat Island Mitigation
- Forest Management and Policy
- Archaeology and Natural History
- Mosquito-borne diseases and control
- Botany, Ecology, and Taxonomy Studies
- Ruminant Nutrition and Digestive Physiology
- Soil Geostatistics and Mapping
- Land Use and Ecosystem Services
- Geophysical Methods and Applications
- Viral Infections and Vectors
- Climate change and permafrost
United States Geological Survey
2014-2024
Earth Resources Observation and Science Center
2013-2023
United States Department of the Interior
2021
Stinger Ghaffarian Technologies (United States)
2011-2018
South Dakota State University
2008-2012
Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting underfitting effects in model. The goal this study is to develop an optimal sampling usage strategy any dataset identify appropriate number rules regression model that will improve its accuracy robustness. Landsat 8 Moderate-Resolution Imaging Spectroradiometer-scaled Normalized Difference Vegetation Index (NDVI) were...
Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic grass cover dynamics over large areas requires use remote sensing support early detection rapid response initiatives. However, few studies leveraged technologies computing frameworks capable providing rangeland managers with...
Background The incidence of West Nile virus (WNv) has remained high in the northern Great Plains compared to rest United States. However, reasons for sustained risk WNv transmission this region have not been determined. To assess environmental drivers Plains, we analyzed county-level spatial pattern human cases during 2003 epidemic across a seven-state region. Methodology/Principal Findings County-level data on were examined using cluster analysis, and used fit statistical models with...
Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard Terra Operational Land Imager Landsat 8 into four regression-tree models applied those to a mapping application. This application produced downscaled maps utilize 30-m resolution in conjunction with daily acquisitions...
Abstract Exotic annual grasses (EAG) are one of the most damaging agents change in western North America. Despite known socio‐environmental effects EAG there remains a need to enhance monitoring capabilities for better informing conservation and management practices. Here, we integrate field observations, remote sensing climate data with machine‐learning techniques estimate assess patterns historical (1985–2019; R 2 = 0.86 ± 0.05; MAE 6.7 1.4%), present (2020), future (2025–2040) abundance...
The invasion of exotic annual grass (EAG), e.g., cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), into rangeland ecosystems the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, adds to land management costs. However, identifying individual species EAG abundance from remote sensing, particularly at early stages or growth, can be problematic because overlapping controls similar phenological characteristics...
Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing other data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, start of season time based input data to estimate cheatgrass beginning spring growth (BOSG) in northern Basin. The was then applied map location timing for entire area. strong (R2 = 0.85) predicted...
Vegetation has been effectively monitored using remote sensing time-series vegetation index (VI) data for several decades. Drought monitoring a common application with algorithms tuned to capturing anomalous temporal and spatial patterns. stress models, such as the Response Index (VegDRI), often use VIs like Normalized Difference (NDVI). The EROS expedited Moderate Resolution Imaging Spectroradiometer (eMODIS)-based, 7-day NDVI composites are integral VegDRI. As MODIS satellite platforms...
Abstract This study dynamically monitors ecosystem performance ( EP ) to identify grasslands potentially suitable for cellulosic feedstock crops (e.g., switchgrass) within the Greater Platte River Basin GPRB ). We computed grassland site potential and anomalies using 9‐year (2000–2008) time series of 250 m expedited moderate resolution imaging spectroradiometer Normalized Difference Vegetation Index data, geophysical biophysical weather climate models. hypothesize that areas with fairly...
Expansion of exotic annual grass (EAG), such as cheatgrass (Bromus tectorum L.) and medusahead (Taeniatherum caput-medusae [L.] Nevski), could cause irreversible changes to arid semiarid rangeland ecosystems in the western United States. The distribution abundance EAG species are highly affected by weather variables temperature precipitation. study's goal is understand how different precipitation scenarios affect estimates dynamics, we develop a machine learning modeling approach predict...
Abstract This research builds upon the extensive body of work to model exotic annual grass (EAG) characteristics and invasion. EAGs increase wildland fire risk intensifies behavior in western U.S. rangelands. Therefore, understanding EAG growth increases its dynamics can inform rangeland management decisions. To better understand phenology spatial distribution, monthly weather (precipitation, minimum maximum temperature) variables were analyzed for 24 level III ecoregions. characterizes...
Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training over large geographic spaces, allowing a better understanding broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux from towers that are located strategically across conterminous United States (CONUS). We calculate...
Abstract High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within‐season predictions annual (i.e., yearly production) can provide specific boundaries for these decisions with more information and possibly higher confidence. In this study, we use a recently developed model, ForageAhead, that uses environmental seasonal climate...