@conference {JRN55403, title = {Building a wind erosion and dust emission model for rangelands using National Wind Erosion Research Network data }, booktitle = {2021 LTAR Annual Meeting}, year = {2021}, month = {7/22/2021}, abstract = {Existing wind erosion and dust emission models are poorly developed for assessing the impacts of land management and environmental change on rangelands. Models that leverage standardized vegetation and soil monitoring data and produce estimates that capture intra- and inter-annual spatial variability in sediment transport rates are needed to develop indicators and benchmarks for wind erosion in support of land health and air quality assessments. It is also important to describe, quantify, and communicate estimates of model uncertainty to users. The Aeolian EROsion (AERO) model was developed in response to these concerns and has been parametrized for rangelands. We used a Generalized Likelihood Uncertainty Estimation (GLUE) framework to calibrate AERO using vegetation, sediment transport, and meteorological data collected from 2015 to 2019 at five grassland and shrubland National Wind Erosion Research Network (NWERN) sites. Results show good agreement for individual sampling periods across the sites and a one-to-one relationship between median predictions and sediment flux observations. In addition, on a site-by-site basis, combined distributions of aeolian sediment flux estimates closely approximate the probability distribution of observed flux at the site over intermediate time scales (seasons to years). These results suggest AERO effectively represents temporal variability in aeolian transport rates and provides robust estimates suitable for assessing rangeland health and better predicting changes in air quality and the impacts of land management activities. Here, we present the AERO wind erosion and dust emission model, the parameterization for rangelands, and example applications of AERO to large monitoring data sets.}, author = {Brandon Edwards and Nicholas Webb and Brad Cooper and Ericha Courtright and Danielle Duni and Beth Newingham and Frederick B. Pierson and Drew Scott and John Tatarko and Negussie H. Tedela and David P. Toledo and Paul S. Verburg and Jason C. Williams and Scott Van Pelt and Justin Van Zee} } @article {JRN55341, title = {Parameterizing an aeolian erosion (AERO) model for rangelands}, journal = {Aeolian Research}, volume = {54}, year = {2021}, month = {12/13/2021}, chapter = {100769}, abstract = {Aeolian processes are fundamental to arid and semi-arid ecosystems, but modeling approaches are poorly developed for assessing impacts of management and environmental change on sediment transport rates over meaningful spatial and temporal scales. For model estimates to provide value, estimates of sediment flux that encapsulate intra- and inter-annual and spatial variability are needed. Further, it is important to quantify and communicate transparent estimates of model uncertainty to users. Here, we present a wind erosion and dust emission model parameterized for rangelands using a Generalized Likelihood Uncertainty Estimation framework. Modeled horizontal sediment flux was calibrated using data from five diverse grassland and shrubland sites from the USDA National Wind Erosion Research Network. Observations of wind speed, vegetation height, length of gaps between vegetation, and percent bare ground were used as model inputs. Horizontal sediment flux estimates from 10,000 independently selected parameter sets were compared to flux observations from 44 \~{} month-long collection periods to calculate a likelihood measure for each model. Results show good agreement for individual sampling periods across sites with few observations falling outside prediction bounds and a one-to-one relationship between median predictions and observations. Additionally, combined distributions of sediment flux estimates from all sample periods for a given site closely approximated the probability of observing a given flux at that site. These results suggest AERO effectively represents temporal variability in aeolian transport rates at rangeland sites and provides robust assessments suitable for assessing land health and better predicting changes in air quality and the impacts of land management activities.}, keywords = {aeolian, assessment, dust emission, indicators, land management, monitoring, wind erosion}, doi = {10.1016/j.aeolia.2021.100769}, url = {files/bibliography/21-052.pdf}, author = {Brandon Edwards and Nicholas Webb and Magda Galloza and Justin Van Zee and Ericha Courtright and Brad Cooper and Loretta Metz and Jeffrey E. Herrick and Gregory S. Okin and Danielle Duni and John Tatarko and Negussie Tedela and Daniel N. Moriasi and Beth Newingham and Frederick B. Pierson and David P. Toledo and Scott Van Pelt} } @article {JRN55137, title = {Climate change impacts on wind and water erosion on US rangelands}, journal = {Journal of Soil and Water Conservation}, volume = {74}, year = {2019}, month = {07/2019}, pages = {405-418}, chapter = {405}, abstract = {

Soil erosion by water and wind in US rangelands has serious implications for rangeland health, food security, and poses significant hazards to human health and communities. Accordingly, understanding how future climate change may impact soil erosion is critical for developing appropriate management strategies that mitigate negative impacts to the extent practical and potentially build resilience. Here, we review potential impacts of climate change on controls of erosion in US rangelands and discuss potential erosion responses. Projected climate changes are expected to have regionally variable effects on important controls of erosion, especially vegetation cover; community composition; frequency, magnitude, and geographical range of fire disturbance; and high intensity, erosive weather events, all of which have the potential to increase rangeland vulnerability to erosion. We identify knowledge gaps relevant to these controls and discuss management considerations to address climate change impacts to soil erosion concerns for US rangelands. We recommend using existing monitoring data to create assessments of vulnerability, that soil erosion should be explicitly included in management benchmarks and decision support tools, and that no-regrets management options be implemented in anticipation of future impacts, which can improve resilience and the efficacy of climate change adaptation.

}, keywords = {climate change, rangeland, soil erosion, water erosion, wind erosion}, doi = {doi.org/10.2489/jswc.74.4.405}, url = {files/bibliography/19-017.pdf}, author = {Brandon Edwards and Nicholas Webb and David A. Brown and Emile H. Elias and Dannele E. Peck and Frederick B. Pierson and Jason C. Williams and Jeffrey E. Herrick} } @article {JRN55003, title = {Stand density and carbon storage in cypress-tupelo wetland forests of the Mississippi River delta}, journal = {Forest Ecology and Management}, volume = {441}, year = {2019}, month = {03/2019}, pages = {106-114}, chapter = {106}, abstract = {

Forested wetlands play a vital role in the coastal zone, but their vulnerability to coastal change{\textemdash}and the impact to high-value ecosystem services{\textemdash}is not as well established as that of more seaward systems such as saltmarsh and mangroves. To address this need, we develop field-based stand density classes, then classify baldcypress-water tupelo (Taxodium distichum (L.) Rich var. distichum; Nyssa aquatica L.) stand density on the Mississippi River delta using a multitemporal ordination of reflectance from Landsat Thematic Mapper imagery. Approximately 29, 50, and 21\% of forest was classified as full canopy, intermediate, and open canopy, respectively. We estimate stand-level live-stem carbon stocks and annual accumulation rates of 96, 67, and 39 t-C ha-1 and 1.9, 1.4 and 0.8 t-C ha-1 yr-1 for full-canopy, intermediate, and open-canopy forest, respectively. Regional live-stem carbon stocks are \~{} 69 t-C ha-1, and total carbon and annual increment for all forest analyzed are \~{}17 Mt-C and \~{}0.34 Mt-C yr-1. Much of the cypress-tupelo forest on the delta stores carbon at rates significantly below the potential of fully stocked stands, yet overall rates of accumulation are comparable to other forest types and coastal systems. Delta-wide, there is a well-defined coastward gradient of stand density, which has important implications for the future of deltaic forests and their ecosystem services. The similarities between forest density gradients and well-documented marsh loss patterns in the region suggest that the same processes driving coastal marsh loss{\textemdash}relative sea level rise exacerbated by human activity{\textemdash}are likely responsible for a second, more gradual interface of land loss at the marsh-forest boundary. Results highlight the potential response of coastal forests to continued environmental change{\textemdash}and associated impacts to the carbon cycle{\textemdash}and provide a baseline for detecting future change to forests on the Mississippi River delta.

}, keywords = {baldcypress, carbon cycle, coastal change, forested wetlands, mississippi river delta, water tupelo}, doi = {doi.org/10.1016/j.foreco.2019.03.046}, url = {files/bibliography/19-005.pdf}, author = {Brandon Edwards and Allen, Scott T. and Braud, Dewitt H. and Keim, Richard F.} } @conference {JRN54944, title = {AERO, a wind erosion modeling framework with applications to monitoring data}, booktitle = {73rd Soil and Water Conservation Society International Annual Conference }, year = {2018}, month = {07/2018}, address = {Albuquerque, New Mexico}, abstract = {

The Aeolian Erosion Model (AERO) is a flexible aeolian transport and dust emission modeling framework developed to inform fundamental research and provide decision support for land managers. The model simulates size-resolved horizontal and vertical mass flux on the plot scale from user inputs of meteorological, soil and vegetation data via user-selectable drag portioning, transport and emission schemes. AERO is adaptable to many research and management applications over a range of site conditions and can leverage emerging large-scale ecological datasets to provide new opportunities to evaluate aeolian sediment transport responses to land surface conditions, potential interactions with disturbances and ecological change, and impacts of anthropogenic land use and land cover change.

}, author = {Brandon Edwards and Nicholas Webb and Sarah McCord} } @conference {JRN54943, title = {AERO: An Aeolian erosion modeling environment}, booktitle = {International Conference on Aeolian Research}, year = {2018}, month = {06/2018}, address = {Bordeaux, France}, abstract = {

The Aeolian Erosion Model (AERO) is a versatile aeolian transport and dust emission modeling environment developed to provide a robust interface for fundamental research while also acting as a decision-support tool for land managers. The model simulates size-resolved horizontal and vertical mass flux on the plot scale from user inputs of meteorological, soil and vegetation data. AERO is highly customizable; the model can be run for a single set of conditions, a time series of conditions, conditions over space, or a time series of conditions over space. Drag partitioning, vertical dust emission schemes, and horizontal transport equations are user-selectable. Key variables (e.g., vegetation cover, canopy gap distribution, soil type) can be input as scalars, defined by descriptive statistics, supplied as probability distributions, or, when run spatially, as remote sensing-derived inputs and atmospheric data from the Weather Research and Forecasting (WRF) weather prediction model. As such, the model is adaptable to many research and management applications over a range of site conditions. Here, we detail the model framework and processing options and provide an example of model application to U.S. Bureau of Land Management (BLM) Assessment, Inventory and Monitoring (AIM) plots in New Mexico, USA to assess potential implications of management actions for dust emission rates. The test case demonstrates how the AERO model can leverage emerging large-scale ecological datasets like AIM to provide new opportunities to evaluate aeolian sediment transport responses to land surface conditions, potential interactions with disturbances and ecological change, and impacts of anthropogenic land use and land cover change.

}, author = {Brandon Edwards and Sarah McCord and Nicholas Webb and Nelson Stauffer} } @conference {JRN54942, title = {Vegetation effects on spatiotemporal variability in Aeolian mass flux over a range of ecological conditions}, booktitle = {International Conference on Aeolian Research}, year = {2018}, month = {06/2018}, address = {Bordeaux, France}, abstract = {

Issues of scale have long been a chief concern in efforts by the aeolian research community to monitor and model aeolian mass flux over spatially large areas. Observations over small sampling scales (\< 1 m2 ) dominate physical descriptions of aeolian transport processes and predictive mass flux equations. Consequently, those descriptions are unlikely to represent the controls of transport over space (\>\> 1 m2 ). Loss of process fidelity is compounded as area increases because additional sources of variance are introduced and unknown synergies occur between controlling factors (Figure 1). Uncertainty is further amplified by increasing landscape heterogeneity, but because monitoring efforts are often limited in scope, few data are available to adequately describe spatial variability of transport to produce unbiased areal estimates, particularly in vegetated landscapes. In this paper, we use transport and vegetation data from US National Wind Erosion Research Network (http://winderosionnetwork.org) sites to investigate spatiotemporal variability of transport and its controls for a range of vegetation conditions. For a given site, vegetation characteristics (e.g., canopy height, vegetative cover fraction, and gap size distribution) are recorded seasonally using standardized methods. Transport is measured using a stratified scheme of 27 MWAC collectors randomly located in groups of 3 within 9 cells in a 100 m2 plot. We use regression co-kriging to map monthly transport and investigate how vegetation as a controlling factor drives variability in transport. Results are expected to inform future modeling efforts and improve analyses of wind erosion and dust emission responses to land use and land cover change.

}, author = {Brandon Edwards and Nicholas Webb and Justin Van Zee and A. Chappell} }