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Tyson Swetnam
University of Arizona Tucson AZ USA

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Research article
Published: 09 July 2021 in Journal of Geophysical Research: Earth Surface
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Post-wildfire changes to hydrologic and geomorphic systems can lead to widespread sediment redistribution. Understanding how sediment moves through a watershed is crucial for assessing hazards, developing debris flow inundation models, engineering sediment retention solutions, and quantifying the role that disturbances play in landscape evolution. In this study, we used terrestrial and airborne lidar to measure sediment redistribution in the 2016 Fish Fire, in the San Gabriel Mountains in southern California, USA. The lidar areas are in two adjacent watersheds, at spatial scales of 900 m2 to 4 km2, respectively. Terrestrial lidar data were acquired prior to rainfall, and two subsequent surveys show erosional change after rainstorms. Two airborne lidar flights occurred (1) 7 months before, and (2) 14 months after the fire ignition, capturing the erosional effects after rainfall. We found hillslope erosion dominated the overall sediment budget in the first rainy season after wildfire. Only 7% of the total erosion came from the active channel bed and channel banks, and the remaining 93% of eroded sediment was derived from hillslopes. Within the channelized portion of the watershed erosion/deposition could be generally described with topographic metrics used in a stream power equation. Observed sediment volumes were compared with four empirical models and one process-based model. We found that the best predictions of sediment volume were obtained from an empirical model developed in the same physiographic region. Moreover, this study showed that post-wildfire erosion rates in the San Gabriel Mountains attain the same magnitude as millennial time scale bedrock erosion rates.

ACS Style

F. K. Rengers; Luke A. McGuire; Jason W. Kean; Dennis M. Staley; Mariana Dobre; Peter R. Robichaud; Tyson Swetnam. Movement of Sediment Through a Burned Landscape: Sediment Volume Observations and Model Comparisons in the San Gabriel Mountains, California, USA. Journal of Geophysical Research: Earth Surface 2021, 126, 1 .

AMA Style

F. K. Rengers, Luke A. McGuire, Jason W. Kean, Dennis M. Staley, Mariana Dobre, Peter R. Robichaud, Tyson Swetnam. Movement of Sediment Through a Burned Landscape: Sediment Volume Observations and Model Comparisons in the San Gabriel Mountains, California, USA. Journal of Geophysical Research: Earth Surface. 2021; 126 (7):1.

Chicago/Turabian Style

F. K. Rengers; Luke A. McGuire; Jason W. Kean; Dennis M. Staley; Mariana Dobre; Peter R. Robichaud; Tyson Swetnam. 2021. "Movement of Sediment Through a Burned Landscape: Sediment Volume Observations and Model Comparisons in the San Gabriel Mountains, California, USA." Journal of Geophysical Research: Earth Surface 126, no. 7: 1.

Editorial
Published: 13 May 2021 in PLOS Computational Biology
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Faryad Sahneh; Meghan A. Balk; Marina Kisley; Chi-Kwan Chan; Mercury Fox; Brian Nord; Eric Lyons; Tyson Swetnam; Daniela Huppenkothen; Will Sutherland; Ramona L. Walls; Daven P. Quinn; Tonantzin Tarin; David LeBauer; David Ribes; Dunbar P. Birnie; Carol Lushbough; Eric Carr; Grey Nearing; Jeremy Fischer; Kevin Tyle; Luis Carrasco; Meagan Lang; Peter W. Rose; Richard R. Rushforth; Samapriya Roy; Thomas Matheson; Tina Lee; C. Titus Brown; Tracy K. Teal; Monica Papeș; Stephen Kobourov; Nirav Merchant. Ten simple rules to cultivate transdisciplinary collaboration in data science. PLOS Computational Biology 2021, 17, e1008879 .

AMA Style

Faryad Sahneh, Meghan A. Balk, Marina Kisley, Chi-Kwan Chan, Mercury Fox, Brian Nord, Eric Lyons, Tyson Swetnam, Daniela Huppenkothen, Will Sutherland, Ramona L. Walls, Daven P. Quinn, Tonantzin Tarin, David LeBauer, David Ribes, Dunbar P. Birnie, Carol Lushbough, Eric Carr, Grey Nearing, Jeremy Fischer, Kevin Tyle, Luis Carrasco, Meagan Lang, Peter W. Rose, Richard R. Rushforth, Samapriya Roy, Thomas Matheson, Tina Lee, C. Titus Brown, Tracy K. Teal, Monica Papeș, Stephen Kobourov, Nirav Merchant. Ten simple rules to cultivate transdisciplinary collaboration in data science. PLOS Computational Biology. 2021; 17 (5):e1008879.

Chicago/Turabian Style

Faryad Sahneh; Meghan A. Balk; Marina Kisley; Chi-Kwan Chan; Mercury Fox; Brian Nord; Eric Lyons; Tyson Swetnam; Daniela Huppenkothen; Will Sutherland; Ramona L. Walls; Daven P. Quinn; Tonantzin Tarin; David LeBauer; David Ribes; Dunbar P. Birnie; Carol Lushbough; Eric Carr; Grey Nearing; Jeremy Fischer; Kevin Tyle; Luis Carrasco; Meagan Lang; Peter W. Rose; Richard R. Rushforth; Samapriya Roy; Thomas Matheson; Tina Lee; C. Titus Brown; Tracy K. Teal; Monica Papeș; Stephen Kobourov; Nirav Merchant. 2021. "Ten simple rules to cultivate transdisciplinary collaboration in data science." PLOS Computational Biology 17, no. 5: e1008879.

Journal article
Published: 08 April 2021 in Remote Sensing
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In this work we explore three methods for quantifying ecosystem vegetation responses spatially and temporally using Google’s Earth Engine, implementing an Ecosystem Moisture Stress Index (EMSI) to monitor vegetation health in agricultural, pastoral, and natural landscapes across the entire era of spaceborne remote sensing. EMSI is the multitemporal standard (z) score of the Normalized Difference Vegetation Index (NDVI) given as I, for a pixel (x,y) at the observational period t. The EMSI is calculated as: zxyt = (Ixyt − µ xyT)/σ xyT, where the index value of the observational date (Ixyt) is subtracted from the mean (µ xyT) of the same date or range of days in a reference time series of length T (in years), divided by the standard deviation (σ xyT), during the same day or range of dates in the reference time series. EMSI exhibits high significance (z > |2.0 ± 1.98σ|) across all geographic locations and time periods examined. Our results provide an expanded basis for detection and monitoring: (i) ecosystem phenology and health; (ii) wildfire potential or burn severity; (iii) herbivory; (iv) changes in ecosystem resilience; and (v) change and intensity of land use practices. We provide the code and analysis tools as a research object, part of the findable, accessible, interoperable, reusable (FAIR) data principles.

ACS Style

Tyson Swetnam; Stephen Yool; Samapriya Roy; Donald Falk. On the Use of Standardized Multi-Temporal Indices for Monitoring Disturbance and Ecosystem Moisture Stress across Multiple Earth Observation Systems in the Google Earth Engine. Remote Sensing 2021, 13, 1448 .

AMA Style

Tyson Swetnam, Stephen Yool, Samapriya Roy, Donald Falk. On the Use of Standardized Multi-Temporal Indices for Monitoring Disturbance and Ecosystem Moisture Stress across Multiple Earth Observation Systems in the Google Earth Engine. Remote Sensing. 2021; 13 (8):1448.

Chicago/Turabian Style

Tyson Swetnam; Stephen Yool; Samapriya Roy; Donald Falk. 2021. "On the Use of Standardized Multi-Temporal Indices for Monitoring Disturbance and Ecosystem Moisture Stress across Multiple Earth Observation Systems in the Google Earth Engine." Remote Sensing 13, no. 8: 1448.

Preprint content
Published: 08 February 2021
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In adaptive management of rangelands, monitoring is the vital link that connects management actions with on-the-ground changes. Traditional field monitoring methods can provide detailed information for assessing the health of rangelands, but cost often limits monitoring locations to a few key areas or random plots. Remotely sensed imagery, and drone-based imagery in particular, can observe larger areas than field methods while retaining high enough spatial resolution to estimate many rangeland indicators of interest. However, the geographic extent of drone imagery products is often limited to a few hectares (for resolution ≤ 1 cm) due to image collection and processing constraints. Overcoming these limitations would allow for more extensive observations and more frequent monitoring. We developed a workflow to increase the extent and speed of acquiring, processing, and analyzing drone imagery for repeated monitoring of two common indicators of interest to rangeland managers: vegetation cover and vegetation heights. By incorporating a suite of existing technologies in drones (real-time kinematic GPS), data processing (automation with Python scripts, high performance computing), and cloud-based analysis (Google Earth Engine), we greatly increased the efficiency of collecting, analyzing, and interpreting high volumes of drone imagery for rangeland monitoring. End-to-end, our workflow took 30 days, while a workflow without these innovations was estimated to require 141 days to complete. The technology around drones and image analysis is rapidly advancing which is making high volume workflows easier to implement. Larger quantities of monitoring data will significantly improve our understanding of the impact management actions have on land processes and ecosystem traits.

ACS Style

Jeffrey K. Gillan; Guillermo E. Ponce-Campos; Tyson L. Swetnam; Alessandra Gorlier; Philip Heilman; Mitchel P. McClaran. Innovations to expand drone data collection and analysis for rangeland monitoring. 2021, 1 .

AMA Style

Jeffrey K. Gillan, Guillermo E. Ponce-Campos, Tyson L. Swetnam, Alessandra Gorlier, Philip Heilman, Mitchel P. McClaran. Innovations to expand drone data collection and analysis for rangeland monitoring. . 2021; ():1.

Chicago/Turabian Style

Jeffrey K. Gillan; Guillermo E. Ponce-Campos; Tyson L. Swetnam; Alessandra Gorlier; Philip Heilman; Mitchel P. McClaran. 2021. "Innovations to expand drone data collection and analysis for rangeland monitoring." , no. : 1.

Biodiversity research
Published: 21 January 2021 in Diversity and Distributions
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Aim To develop an updated distribution model and habitat suitability analysis for the Mexican wolf, to inform the recovery efforts in Mexico and the United States. Location Mexico and the southwestern United States. Methods We used an ensemble species distribution modelling (SDM) approach and a spatial analysis combining anthropogenic and ecological variables, including, for the first time, rangewide relative density estimates of wild ungulates, to determine the extent of suitable habitat for wolves within a region that includes the known historical range of the Mexican wolf and adjacent areas. Results The results showed that the modelled distribution of the Mexican wolf extended from central Arizona and New Mexico, and western Texas in the United States, southwards along the Sierra Madre Occidental and the Sierra Madre Oriental, to the high sierras of Oaxaca, in Mexico. The habitat suitability models indicated that large tracts (>81,000 km2) of high‐quality habitat still exist for the Mexican wolf in the southwestern United States, and the Sierra Madre Occidental and the Sierra Madre Oriental in Mexico, which could ensure recovery within its historical range. Main conclusions The recovery of the Mexican wolf is a complex, multidimensional socio‐ecological challenge, which requires binational cooperation guided by reliable information and robust scientific procedures. The next step is to carry out specific socio‐ecological studies and actions for selected candidate sites to assess their viability for hastening its recovery.

ACS Style

Enrique Martínez‐Meyer; Alejandro González‐Bernal; Julián A. Velasco; Tyson L. Swetnam; Zaira Y. González‐Saucedo; Jorge Servín; Carlos A. López‐González; John K. Oakleaf; Stewart Liley; James R. Heffelfinger. Rangewide habitat suitability analysis for the Mexican wolf ( Canis lupus baileyi ) to identify recovery areas in its historical distribution. Diversity and Distributions 2021, 27, 642 -654.

AMA Style

Enrique Martínez‐Meyer, Alejandro González‐Bernal, Julián A. Velasco, Tyson L. Swetnam, Zaira Y. González‐Saucedo, Jorge Servín, Carlos A. López‐González, John K. Oakleaf, Stewart Liley, James R. Heffelfinger. Rangewide habitat suitability analysis for the Mexican wolf ( Canis lupus baileyi ) to identify recovery areas in its historical distribution. Diversity and Distributions. 2021; 27 (4):642-654.

Chicago/Turabian Style

Enrique Martínez‐Meyer; Alejandro González‐Bernal; Julián A. Velasco; Tyson L. Swetnam; Zaira Y. González‐Saucedo; Jorge Servín; Carlos A. López‐González; John K. Oakleaf; Stewart Liley; James R. Heffelfinger. 2021. "Rangewide habitat suitability analysis for the Mexican wolf ( Canis lupus baileyi ) to identify recovery areas in its historical distribution." Diversity and Distributions 27, no. 4: 642-654.

Editorial
Published: 22 October 2020 in PLOS Computational Biology
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ACS Style

Alise Ponsero; Ryan Bartelme; Gustavo De Oliveira Almeida; Alex Bigelow; Reetu Tuteja; Holly Ellingson; Tyson Swetnam; Nirav Merchant; Maliaca Oxnam; Eric Lyons. Ten simple rules for organizing a data science workshop. PLOS Computational Biology 2020, 16, e1008226 .

AMA Style

Alise Ponsero, Ryan Bartelme, Gustavo De Oliveira Almeida, Alex Bigelow, Reetu Tuteja, Holly Ellingson, Tyson Swetnam, Nirav Merchant, Maliaca Oxnam, Eric Lyons. Ten simple rules for organizing a data science workshop. PLOS Computational Biology. 2020; 16 (10):e1008226.

Chicago/Turabian Style

Alise Ponsero; Ryan Bartelme; Gustavo De Oliveira Almeida; Alex Bigelow; Reetu Tuteja; Holly Ellingson; Tyson Swetnam; Nirav Merchant; Maliaca Oxnam; Eric Lyons. 2020. "Ten simple rules for organizing a data science workshop." PLOS Computational Biology 16, no. 10: e1008226.

Journal article
Published: 03 April 2019 in Rangeland Ecology & Management
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Monitoring of forage utilization typically occurs at sample locations, or key areas, selected for their presumed potential to represent utilization across pastures. However, utilization can vary greatly across landscapes and may not be well represented by traditional ground-based sampling without great effort. Remote sensing from satellite and manned airborne platforms offers spatial coverage at landscape scale, but their poor spatial resolution (satellite) and cost (manned airborne) may limit their use in monitoring forage utilization. High-resolution photogrammetric point clouds obtained from small unmanned aerial systems (sUAS) represent an appealing alternative. We developed a method to estimate utilization by observing the height reduction of herbaceous plants represented by 3-dimensional point clouds. We tested our method in a semiarid savanna in southern Arizona by comparing utilization estimates with ground-based methods after a month-long grazing duration. In six plots, we found strong correlation between imagery and ground-based estimates (r2 = 0.78) and similar average estimate of utilization of across all plots (ground-based = 18%, imagery = 20%). With a few workflow and technological improvements, we think it is feasible to estimate point cloud utilization over the entire pasture (150 ha) and potentially even larger areas. These improvements include optimizing the number of images collected and used, equipping drones with more accurate global navigation satellite systems (e.g., Global Positioning System), and processing images with cloud-based parallel processing. We show proof of concept to provide confident estimates of forage utilization patterns over large pastures and landscapes, at levels of spatial precision that are consistent with ground-based methods. The adoption of drone-based monitoring of utilization of forage on rangelands could follow the paradigm shift already demonstrated by Global Positioning Systems and Geographic information systems technologies, where the initial high computing costs were reduced, use became the norm, and the availability of more precise spatial patterns was applied to prescribe and evaluate management practices.

ACS Style

Jeffrey K. Gillan; Mitchel P. McClaran; Tyson Swetnam; Philip Heilman. Estimating Forage Utilization with Drone-Based Photogrammetric Point Clouds. Rangeland Ecology & Management 2019, 72, 575 -585.

AMA Style

Jeffrey K. Gillan, Mitchel P. McClaran, Tyson Swetnam, Philip Heilman. Estimating Forage Utilization with Drone-Based Photogrammetric Point Clouds. Rangeland Ecology & Management. 2019; 72 (4):575-585.

Chicago/Turabian Style

Jeffrey K. Gillan; Mitchel P. McClaran; Tyson Swetnam; Philip Heilman. 2019. "Estimating Forage Utilization with Drone-Based Photogrammetric Point Clouds." Rangeland Ecology & Management 72, no. 4: 575-585.

Journal article
Published: 22 February 2019 in Water
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This paper describes coupling field experiments with surface and groundwater modeling to investigate rangelands of SE Arizona, USA using erosion-control structures to augment shallow and deep aquifer recharge. We collected field data to describe the physical and hydrological properties before and after gabions (caged riprap) were installed in an ephemeral channel. The modular finite-difference flow model is applied to simulate the amount of increase needed to raise groundwater levels. We used the average increase in infiltration measured in the field and projected on site, assuming all infiltration becomes recharge, to estimate how many gabions would be needed to increase recharge in the larger watershed. A watershed model was then applied and calibrated with discharge and 3D terrain measurements, to simulate flow volumes. Findings were coupled to extrapolate simulations and quantify long-term impacts of riparian restoration. Projected scenarios demonstrate how erosion-control structures could impact all components of the annual water budget. Results support the potential of watershed-wide gabion installation to increase total aquifer recharge, with models portraying increased subsurface connectivity and accentuated lateral flow contributions.

ACS Style

Laura M. Norman; James B. Callegary; Laurel Lacher; Natalie R. Wilson; Chloé Fandel; Brandon T. Forbes; Tyson Swetnam. Modeling Riparian Restoration Impacts on the Hydrologic Cycle at the Babacomari Ranch, SE Arizona, USA. Water 2019, 11, 381 .

AMA Style

Laura M. Norman, James B. Callegary, Laurel Lacher, Natalie R. Wilson, Chloé Fandel, Brandon T. Forbes, Tyson Swetnam. Modeling Riparian Restoration Impacts on the Hydrologic Cycle at the Babacomari Ranch, SE Arizona, USA. Water. 2019; 11 (2):381.

Chicago/Turabian Style

Laura M. Norman; James B. Callegary; Laurel Lacher; Natalie R. Wilson; Chloé Fandel; Brandon T. Forbes; Tyson Swetnam. 2019. "Modeling Riparian Restoration Impacts on the Hydrologic Cycle at the Babacomari Ranch, SE Arizona, USA." Water 11, no. 2: 381.

Special issue paper
Published: 02 September 2018 in Concurrency and Computation: Practice and Experience
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Jetstream is a first of its kind system for the NSF — a distributed production cloud resource. We review the purpose for creating Jetstream, discuss Jetstream's key characteristics, describe our experiences from the first year of maintaining an OpenStack‐based cloud environment, and share some of the early scientific impacts achieved by Jetstream users. Jetstream offers a unique capability within the XSEDE‐supported US national cyberinfrastructure, delivering interactive virtual machines (VMs) via the Atmosphere interface. As a multi‐region deployment that operates as an integrated system, Jetstream is proving effective in supporting modes and disciplines of research traditionally underrepresented on larger XSEDE‐supported clusters and supercomputers. Already, Jetstream has been used to perform research and education in biology, biochemistry, atmospheric science, earth science, and computer science.

ACS Style

David Y. Hancock; Craig A. Stewart; Matthew Vaughn; Jeremy Fischer; John Michael Lowe; George Turner; Tyson L. Swetnam; Tyler K. Chafin; Enis Afgan; Marlon E. Pierce; Winona Snapp-Childs. Jetstream—Early operations performance, adoption, and impacts. Concurrency and Computation: Practice and Experience 2018, 1 .

AMA Style

David Y. Hancock, Craig A. Stewart, Matthew Vaughn, Jeremy Fischer, John Michael Lowe, George Turner, Tyson L. Swetnam, Tyler K. Chafin, Enis Afgan, Marlon E. Pierce, Winona Snapp-Childs. Jetstream—Early operations performance, adoption, and impacts. Concurrency and Computation: Practice and Experience. 2018; ():1.

Chicago/Turabian Style

David Y. Hancock; Craig A. Stewart; Matthew Vaughn; Jeremy Fischer; John Michael Lowe; George Turner; Tyson L. Swetnam; Tyler K. Chafin; Enis Afgan; Marlon E. Pierce; Winona Snapp-Childs. 2018. "Jetstream—Early operations performance, adoption, and impacts." Concurrency and Computation: Practice and Experience , no. : 1.

Article
Published: 21 April 2018 in Biogeochemistry
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Climate-driven changes in carbon (C) cycling of forested ecosystems have the potential to alter long-term C sequestration and the global C balance. Prior studies have shown that C uptake and partitioning in response to hydrologic variation are system specific, suggesting that a comprehensive assessment is required for distinct ecosystems. Many sub-humid montane forest ecosystems in the US are projected to experience increased water limitation over the next decades and existing water-limited forests can be used as a model for how changes in the hydrologic cycle will impact such ecosystems more broadly. Toward that goal we monitored precipitation, net ecosystem exchange and lateral soil and stream C fluxes in three semi-arid to sub-humid montane forest catchments for several years (WY 2009–2013) to investigate how the amount and timing of water delivery affect C stores and fluxes. The key control on aqueous and gaseous C fluxes was the distribution of water between winter and summer precipitation, affecting ecosystem C uptake versus heterotrophic respiration. We furthermore assessed C stores in soil and above- and below-ground biomass to assess how spatial patterns in water availability influence C stores. Topographically-driven patterns in catchment wetness correlated with modeled soil C stores, reflecting both long-term trends in local C uptake as well as lateral redistribution of C leached from upslope organic soil horizons to convergent landscape positions. The results suggest that changes in the seasonality of precipitation from winter snow to summer rain will influence both the amount and the spatial distribution of soil C stores.

ACS Style

Julia Perdrial; Paul D. Brooks; Tyson Swetnam; Kathleen A. Lohse; Craig Rasmussen; Marcy Litvak; Adrian A. Harpold; Xavier Zapata-Rios; Patrick Broxton; Bhaskar Mitra; Thomas Meixner; Kate Condon; David Huckle; Clare Stielstra; Angélica Vázquez-Ortega; Rebecca Lybrand; Molly Holleran; Caitlin Orem; Jon Pelletier; Jon Chorover. A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage. Biogeochemistry 2018, 138, 225 -243.

AMA Style

Julia Perdrial, Paul D. Brooks, Tyson Swetnam, Kathleen A. Lohse, Craig Rasmussen, Marcy Litvak, Adrian A. Harpold, Xavier Zapata-Rios, Patrick Broxton, Bhaskar Mitra, Thomas Meixner, Kate Condon, David Huckle, Clare Stielstra, Angélica Vázquez-Ortega, Rebecca Lybrand, Molly Holleran, Caitlin Orem, Jon Pelletier, Jon Chorover. A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage. Biogeochemistry. 2018; 138 (3):225-243.

Chicago/Turabian Style

Julia Perdrial; Paul D. Brooks; Tyson Swetnam; Kathleen A. Lohse; Craig Rasmussen; Marcy Litvak; Adrian A. Harpold; Xavier Zapata-Rios; Patrick Broxton; Bhaskar Mitra; Thomas Meixner; Kate Condon; David Huckle; Clare Stielstra; Angélica Vázquez-Ortega; Rebecca Lybrand; Molly Holleran; Caitlin Orem; Jon Pelletier; Jon Chorover. 2018. "A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage." Biogeochemistry 138, no. 3: 225-243.

Original research article
Published: 10 January 2018 in Frontiers in Plant Science
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Remotely sensing recent growth, herbivory, or disturbance of herbaceous and woody vegetation in dryland ecosystems requires high spatial resolution and multi-temporal depth. Three dimensional (3D) remote sensing technologies like lidar, and techniques like structure from motion (SfM) photogrammetry, each have strengths and weaknesses at detecting vegetation volume and extent, given the instrument's ground sample distance and ease of acquisition. Yet, a combination of platforms and techniques might provide solutions that overcome the weakness of a single platform. To explore the potential for combining platforms, we compared detection bias amongst two 3D remote sensing techniques (lidar and SfM) using three different platforms [ground-based, small unmanned aerial systems (sUAS), and manned aircraft]. We found aerial lidar to be more accurate for characterizing the bare earth (ground) in dense herbaceous vegetation than either terrestrial lidar or aerial SfM photogrammetry. Conversely, the manned aerial lidar did not detect grass and fine woody vegetation while the terrestrial lidar and high resolution near-distance (ground and sUAS) SfM photogrammetry detected these and were accurate. UAS SfM photogrammetry at lower spatial resolution under-estimated maximum heights in grass and shrubs. UAS and handheld SfM photogrammetry in near-distance high resolution collections had similar accuracy to terrestrial lidar for vegetation, but difficulty at measuring bare earth elevation beneath dense herbaceous cover. Combining point cloud data and derivatives (i.e., meshes and rasters) from two or more platforms allowed for more accurate measurement of herbaceous and woody vegetation (height and canopy cover) than any single technique alone. Availability and costs of manned aircraft lidar collection preclude high frequency repeatability but this is less limiting for terrestrial lidar, sUAS and handheld SfM. The post-processing of SfM photogrammetry data became the limiting factor at larger spatial scale and temporal repetition. Despite the utility of sUAS and handheld SfM for monitoring vegetation phenology and structure, their spatial extents are small relative to manned aircraft.

ACS Style

Tyson L. Swetnam; Jeffrey K. Gillan; Temuulen T. Sankey; Mitchel P. McClaran; Mary H. Nichols; Philip Heilman; Jason McVay. Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States. Frontiers in Plant Science 2018, 8, 1 .

AMA Style

Tyson L. Swetnam, Jeffrey K. Gillan, Temuulen T. Sankey, Mitchel P. McClaran, Mary H. Nichols, Philip Heilman, Jason McVay. Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States. Frontiers in Plant Science. 2018; 8 ():1.

Chicago/Turabian Style

Tyson L. Swetnam; Jeffrey K. Gillan; Temuulen T. Sankey; Mitchel P. McClaran; Mary H. Nichols; Philip Heilman; Jason McVay. 2018. "Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States." Frontiers in Plant Science 8, no. : 1.

Research article
Published: 07 December 2017 in Earth Surface Processes and Landforms
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Soil‐mantled pole‐facing hillslopes on Earth tend to be steeper, wetter, and have more vegetation cover compared with adjacent equator‐facing hillslopes. These and other slope aspect controls are often the consequence of feedbacks among hydrologic, ecologic, pedogenic, and geomorphic processes triggered by spatial variations in mean annual insolation. In this paper we review the state of knowledge on slope aspect controls of Critical Zone (CZ) processes using the latitudinal and elevational dependence of topographic asymmetry as a motivating observation. At relatively low latitudes and elevations, pole‐facing hillslopes tend to be steeper. At higher latitudes and elevations this pattern reverses. We reproduce this pattern using an empirical model based on parsimonious functions of latitude, an aridity index, mean‐annual temperature, and slope gradient. Using this empirical model and the literature as guides, we present a conceptual model for the slope‐aspect‐driven CZ feedbacks that generate asymmetry in water‐limited and temperature‐limited end‐member cases. In this conceptual model the dominant factor driving slope aspect differences at relatively low latitudes and elevations is the difference in mean‐annual soil moisture. The dominant factor at higher latitudes and elevations is temperature limitation on vegetation growth. In water‐limited cases, we propose that higher mean‐annual soil moisture on pole‐facing hillslopes drives higher soil production rates, higher water storage potential, more vegetation cover, faster dust deposition, and lower erosional efficiency in a positive feedback. At higher latitudes and elevations, pole‐facing hillslopes tend to have less vegetation cover, greater erosional efficiency, and gentler slopes, thus reversing the pattern of asymmetry found at lower latitudes and elevations. Our conceptual model emphasizes the linkages among short‐ and long‐timescale processes and across CZ sub‐disciplines; it also points to opportunities to further understand how CZ processes interact. We also demonstrate the importance of paleoclimatic conditions and non‐climatic factors in influencing slope aspect variations. Copyright © 2017 John Wiley & Sons, Ltd.

ACS Style

Jon D. Pelletier; Greg A. Barron‐Gafford; Hugo Gutiérrez‐Jurado; Eve‐Lyn S. Hinckley; Erkan Istanbulluoglu; Luke A. McGuire; Guo-Yue Niu; Michael J. Poulos; Craig Rasmussen; Paul Richardson; Tyson L. Swetnam; Gregory Tucker. Which way do you lean? Using slope aspect variations to understand Critical Zone processes and feedbacks. Earth Surface Processes and Landforms 2017, 43, 1133 -1154.

AMA Style

Jon D. Pelletier, Greg A. Barron‐Gafford, Hugo Gutiérrez‐Jurado, Eve‐Lyn S. Hinckley, Erkan Istanbulluoglu, Luke A. McGuire, Guo-Yue Niu, Michael J. Poulos, Craig Rasmussen, Paul Richardson, Tyson L. Swetnam, Gregory Tucker. Which way do you lean? Using slope aspect variations to understand Critical Zone processes and feedbacks. Earth Surface Processes and Landforms. 2017; 43 (5):1133-1154.

Chicago/Turabian Style

Jon D. Pelletier; Greg A. Barron‐Gafford; Hugo Gutiérrez‐Jurado; Eve‐Lyn S. Hinckley; Erkan Istanbulluoglu; Luke A. McGuire; Guo-Yue Niu; Michael J. Poulos; Craig Rasmussen; Paul Richardson; Tyson L. Swetnam; Gregory Tucker. 2017. "Which way do you lean? Using slope aspect variations to understand Critical Zone processes and feedbacks." Earth Surface Processes and Landforms 43, no. 5: 1133-1154.

Article
Published: 24 July 2017 in Ecosphere
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Better understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources, tree-ring and forest inventory data. A Bayesian hierarchical model was used to gain inference on the effects of many factors on tree growth—individual tree size, climate, biophysical conditions, stand-level competitive environment, tree-level canopy status, and forest management treatments—using both diameter at breast height (dbh) and tree-ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. This model was applied to a data set of ~130 increment cores and ~500 repeat measurements of dbh at a single site in the Jemez Mountains of north-central New Mexico, USA. The tree-ring data serve as the only source of information on how annual growth responds to climate variation, whereas both data types inform non-climatic effects on growth. Inferences from the model included positive effects on growth of seasonal precipitation, wetness index, and height ratio, and negative effects of dbh, seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model were confirmed by a dendroclimatic analysis. Combining the two data sources substantially reduced uncertainty about non-climate fixed effects on radial increments. This demonstrates that forest inventory data measured on many trees, combined with tree-ring data developed for a small number of trees, can be used to quantify and parse multiple influences on absolute tree growth. We highlight the kinds of research questions that can be addressed by combining the high-resolution information on climate effects contained in tree rings with the rich tree- and stand-level information found in forest inventories, including projection of tree growth under future climate scenarios, carbon accounting, and investigation of management actions aimed at increasing forest resilience.

ACS Style

Margaret E. K. Evans; Donald A. Falk; Alexis Arizpe; Tyson L. Swetnam; Flurin Babst; Kent Holsinger. Fusing tree-ring and forest inventory data to infer influences on tree growth. Ecosphere 2017, 8, e01889 .

AMA Style

Margaret E. K. Evans, Donald A. Falk, Alexis Arizpe, Tyson L. Swetnam, Flurin Babst, Kent Holsinger. Fusing tree-ring and forest inventory data to infer influences on tree growth. Ecosphere. 2017; 8 (7):e01889.

Chicago/Turabian Style

Margaret E. K. Evans; Donald A. Falk; Alexis Arizpe; Tyson L. Swetnam; Flurin Babst; Kent Holsinger. 2017. "Fusing tree-ring and forest inventory data to infer influences on tree growth." Ecosphere 8, no. 7: e01889.

Article
Published: 21 April 2017 in Ecosphere
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Mountains are vital to ecosystems and human society given their influence on global carbon and water cycles. Yet the extent to which topography regulates montane forest carbon uptake and storage remains poorly understood. To address this knowledge gap, we compared forest aboveground carbon loading to topographic metrics describing energy balance and water availability across three headwater catchments of the Boulder Creek Watershed, Colorado, USA. The catchments range from 1800 to 3500 m above mean sea level with 46–102 cm/yr mean annual precipitation and −1.2° to 12.3°C mean annual temperature. In all three catchments, we found mean forest carbon loading consistently increased from ridges (27 ± 19 Mg C ha) to valley bottoms (60 ± 28 Mg C ha). Low topographic positions held up to 185 ± 76 Mg C ha, more than twice the peak value of upper positions. Toe slopes fostered disproportionately high net carbon uptake relative to other topographic positions. Carbon storage was on average 20–40 Mg C ha greater on north to northeast aspects than on south to southwest aspects, a pattern most pronounced in the highest elevation, coldest and wettest catchment. Both the peak and mean aboveground carbon storage of the three catchments, crossing an 11°C range in temperature and doubling of local precipitation, defied the expectation of an optimal elevation-gradient climatic zone for net primary production. These results have important implications for models of forest sensitivity to climate change, as well as to predicted estimates of continental carbon reservoirs.

ACS Style

Tyson L. Swetnam; Paul D. Brooks; Holly R. Barnard; Adrian Harpold; Erika L. Gallo. Topographically driven differences in energy and water constrain climatic control on forest carbon sequestration. Ecosphere 2017, 8, 1 .

AMA Style

Tyson L. Swetnam, Paul D. Brooks, Holly R. Barnard, Adrian Harpold, Erika L. Gallo. Topographically driven differences in energy and water constrain climatic control on forest carbon sequestration. Ecosphere. 2017; 8 (4):1.

Chicago/Turabian Style

Tyson L. Swetnam; Paul D. Brooks; Holly R. Barnard; Adrian Harpold; Erika L. Gallo. 2017. "Topographically driven differences in energy and water constrain climatic control on forest carbon sequestration." Ecosphere 8, no. 4: 1.

Article
Published: 07 April 2017 in Earth Surface Processes and Landforms
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Hillslope asymmetry, i.e. variation in hillslope form as a function of slope aspect and/or mean solar insolation, has been documented in many climates and geologic contexts. Such patterns have the potential to help us better understand the hydrologic, ecologic, and geomorphologic processes and feedbacks operating on hillslopes. Here we document asymmetry in the fraction of hillslope relief accommodated by cliffs in weathering-limited hillslopes of drainage basins incised into the East Kaibab Monocline (northern Arizona) and Raplee Ridge Monocline (southern Utah) of the southern Colorado Plateau. We document that south- and west-facing hillslopes have a larger proportion of hillslope relief accommodated by cliffs compared with north- and east-facing hillslopes. Cliff abundance correlates positively with mean solar insolation and, by inference, negatively with soil/rock moisture. Solar insolation control of hillslope asymmetry is an incomplete explanation, however, because it cannot account for the fact that the greatest asymmetry occurs between southwest- and northeast-facing hillslopes rather than between south- and north-facing hillslopes in the study sites. Modeling results suggest that southwest-facing hillslopes are more cliff-dominated than southeast-facing hillslopes of the same mean solar insolation in part because potential evapotranspiration rates, which control the soil/rock moisture that drives weathering, are controlled by the product of solar insolation and a nonlinear function of surface temperature, together with the fact that southwest-facing hillslopes receive peak solar insolation during warmer times of day compared with southeast-facing hillslopes. The dependence of water availability on both solar insolation and surface temperature highlights the importance of the diurnal cycle in controlling water availability, and it provides a general explanation for the fact that vegetation cover tends to exhibit the greatest difference between northeast- and southwest-facing hillslopes in the Northern Hemisphere and between southeast- and northwest-facing hillslopes in the Southern Hemisphere. Copyright © 2017 John Wiley & Sons, Ltd.

ACS Style

Jon D. Pelletier; Tyson L. Swetnam. Asymmetry of weathering‐limited hillslopes: the importance of diurnal covariation in solar insolation and temperature. Earth Surface Processes and Landforms 2017, 42, 1408 -1418.

AMA Style

Jon D. Pelletier, Tyson L. Swetnam. Asymmetry of weathering‐limited hillslopes: the importance of diurnal covariation in solar insolation and temperature. Earth Surface Processes and Landforms. 2017; 42 (9):1408-1418.

Chicago/Turabian Style

Jon D. Pelletier; Tyson L. Swetnam. 2017. "Asymmetry of weathering‐limited hillslopes: the importance of diurnal covariation in solar insolation and temperature." Earth Surface Processes and Landforms 42, no. 9: 1408-1418.

Article
Published: 04 April 2017 in Remote Sensing in Ecology and Conservation
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Unmanned aerial vehicles (UAVs) provide a new research tool to obtain high spatial and temporal resolution imagery at a reduced cost. Rapid advances in miniature sensor technology are leading to greater potentials for ecological research. We demonstrate one of the first applications of UAV lidar and hyperspectral imagery and a fusion method for individual plant species identification and 3D characterization at submeter scales in south-eastern Arizona, USA. The UAV lidar scanner characterized the individual vegetation canopy structure and bare ground elevation, whereas the hyperspectral sensor provided species-specific spectral signatures for the dominant and target species at our study area in leaf-on condition. We hypothesized that the fusion of the two different data sources would perform better than either data type alone in the arid and semi-arid ecosystems with sparse vegetation. The fusion approach provides 84–89% overall accuracy (kappa values of 0.80–0.86) in target species classification at the canopy scale, leveraging a wide range of target spectral responses in the hyperspectral data and a high point density (50 points/m2) in the lidar data. In comparison, the hyperspectral image classification alone produced 72–76% overall accuracies (kappa values of 0.70 and 0.71). The UAV lidar-derived digital elevation model (DEM) is also strongly correlated with manned airborne lidar-derived DEM (R2 = 0.98 and 0.96), but was obtained at a lower cost. The lidar and hyperspectral data as well as the fusion method demonstrated here can be widely applied across a gradient of vegetation and topography to monitor and detect ecological changes at a local scale.

ACS Style

Temuulen T. Sankey; Jason McVay; Tyson L. Swetnam; Mitchel P. McClaran; Philip Heilman; Mary Nichols. UAV hyperspectral and lidar data and their fusion for arid and semi‐arid land vegetation monitoring. Remote Sensing in Ecology and Conservation 2017, 4, 20 -33.

AMA Style

Temuulen T. Sankey, Jason McVay, Tyson L. Swetnam, Mitchel P. McClaran, Philip Heilman, Mary Nichols. UAV hyperspectral and lidar data and their fusion for arid and semi‐arid land vegetation monitoring. Remote Sensing in Ecology and Conservation. 2017; 4 (1):20-33.

Chicago/Turabian Style

Temuulen T. Sankey; Jason McVay; Tyson L. Swetnam; Mitchel P. McClaran; Philip Heilman; Mary Nichols. 2017. "UAV hyperspectral and lidar data and their fusion for arid and semi‐arid land vegetation monitoring." Remote Sensing in Ecology and Conservation 4, no. 1: 20-33.

Conference paper
Published: 17 July 2016 in Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale
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In this paper we present the experience of scaling in parallel a geographic information system modeling framework to hundreds of processors. The project began in an active learning cyberinfrastructure course which was followed by an XSEDE ECSS effort in collaboration across multiple-institutions.

ACS Style

Tyson Swetnam; J. D. Pelletier; C. Rasmussen; N. R. Callahan; N. Merchant; E. Lyons; M. Rynge; Yan Liu; Viswanath Nandigam; Christopher Crosby. Scaling GIS analysis tasks from the desktop to the cloud utilizing contemporary distributed computing and data management approaches. Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale 2016, 21 -21:6.

AMA Style

Tyson Swetnam, J. D. Pelletier, C. Rasmussen, N. R. Callahan, N. Merchant, E. Lyons, M. Rynge, Yan Liu, Viswanath Nandigam, Christopher Crosby. Scaling GIS analysis tasks from the desktop to the cloud utilizing contemporary distributed computing and data management approaches. Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale. 2016; ():21-21:6.

Chicago/Turabian Style

Tyson Swetnam; J. D. Pelletier; C. Rasmussen; N. R. Callahan; N. Merchant; E. Lyons; M. Rynge; Yan Liu; Viswanath Nandigam; Christopher Crosby. 2016. "Scaling GIS analysis tasks from the desktop to the cloud utilizing contemporary distributed computing and data management approaches." Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale , no. : 21-21:6.

Research article
Published: 08 July 2016 in PLOS ONE
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A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across three semi-arid conifer forests in relation to: (1) tree condition and physical form, (2) the level of inter-tree competition (e.g. open vs closed stand structure), (3) increasing tree age, and (4) differences in site productivity. Scaling exponent values derived from non-linear least-squares regression for trees in excellent condition (n = 381) were above the MST prediction at the 95% confidence level, while the exponent for trees in good condition were no different than MST (n = 926). Trees that were in fair or poor condition, characterized as diseased, leaning, or sparsely crowned had exponent values below MST predictions (n = 2,058), as did recently dead standing trees (n = 375). Exponent value of the mean-tree model that disregarded tree condition (n = 3,740) was consistent with other studies that reject MST scaling. Ostensibly, as stand density and competition increase trees exhibited greater morphological plasticity whereby the majority had characteristically fair or poor growth forms. Fitting by least-squares regression biases the mean-tree model scaling exponent toward values that are below MST idealized predictions. For 368 trees from Arizona with known establishment dates, increasing age had no significant impact on expected scaling. We further suggest height to diameter ratios below MST relate to vertical truncation caused by limitation in plant water availability. Even with environmentally imposed height limitation, proportionality between height and diameter scaling exponents were consistent with the predictions of MST.

ACS Style

Tyson L. Swetnam; Christopher D. O’Connor; Ann M. Lynch. Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA. PLOS ONE 2016, 11, e0157582 .

AMA Style

Tyson L. Swetnam, Christopher D. O’Connor, Ann M. Lynch. Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA. PLOS ONE. 2016; 11 (7):e0157582.

Chicago/Turabian Style

Tyson L. Swetnam; Christopher D. O’Connor; Ann M. Lynch. 2016. "Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA." PLOS ONE 11, no. 7: e0157582.

Dataset
Published: 02 June 2016 in Forest Service Research Data Archive
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This archive contains research data collected and/or funded by Forest Service Research and Development (FS R&D), U.S. Department of Agriculture. It is a resource for accessing both short and long-term FS R&D research data, which includes Experimental Forest and Range data. It is a way to both preserve and share the quality science of our researchers.

ACS Style

Tyson L. Swetnam; Christopher D. O'connor; Ann M. Lynch. Supporting data for "Morphologic plasticity and increasing competition explain deviation from the Metabolic Scaling Theory in semi-arid conifer forests, southwestern USA". Forest Service Research Data Archive 2016, 1 .

AMA Style

Tyson L. Swetnam, Christopher D. O'connor, Ann M. Lynch. Supporting data for "Morphologic plasticity and increasing competition explain deviation from the Metabolic Scaling Theory in semi-arid conifer forests, southwestern USA". Forest Service Research Data Archive. 2016; ():1.

Chicago/Turabian Style

Tyson L. Swetnam; Christopher D. O'connor; Ann M. Lynch. 2016. "Supporting data for "Morphologic plasticity and increasing competition explain deviation from the Metabolic Scaling Theory in semi-arid conifer forests, southwestern USA"." Forest Service Research Data Archive , no. : 1.

Journal article
Published: 01 June 2015 in Ecosphere
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ACS Style

T. L. Swetnam; A. M. Lynch; D. A. Falk; S. R. Yool; D. P. Guertin. Discriminating disturbance from natural variation with LiDAR in semi-arid forests in the southwestern USA. Ecosphere 2015, 6, art97 .

AMA Style

T. L. Swetnam, A. M. Lynch, D. A. Falk, S. R. Yool, D. P. Guertin. Discriminating disturbance from natural variation with LiDAR in semi-arid forests in the southwestern USA. Ecosphere. 2015; 6 (6):art97.

Chicago/Turabian Style

T. L. Swetnam; A. M. Lynch; D. A. Falk; S. R. Yool; D. P. Guertin. 2015. "Discriminating disturbance from natural variation with LiDAR in semi-arid forests in the southwestern USA." Ecosphere 6, no. 6: art97.