Environmental Indicators and Impact Assessment Commons^™

Assessing Indoor Heat Vulnerability And Cooling Strategies In Three Mobile Home Communities In Boulder, Colorado, Usa, Mehdi P. Heris, Skye Niles, Alana Wilson, Megan Mccurdy, Amy Lacourse, Nick Lankau

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Extreme heat is an increasing public health and environmental threat shaped by both physical and social factors. This study assesses the vulnerability of mobile homes and their residents at three mobile home parks in Boulder, Colorado. We examined indoor temperature, housing conditions, and social and personal risk factors of the households. We monitored indoor and outdoor temperatures using 27 indoor and 5 outdoor temperature data loggers, comparing mobile homes with air conditioning, swamp coolers, and passive cooling designs. This work provides a detailed analysis of indoor temperature patterns and demonstrates how evaluating trends yields insights into the performance and effectiveness …

Bioclimatic Reorganization Of Carbon–Water–Energy Coupling Revealed By Eddy Covariance And Interpretable Machine Learning, Koong Yi, Margaret S. Torn, Gabriel B. Senay, Lixin Wang, Kosana Suvočarev, Joshua B. Fisher, Arman Ahmadi, Housen Chu, Gil Bohrer, Georgianne W. Moore, Stephen P. Good, Steven A. Kannenberg, Justine E. C. Missik, Kanishka Mallick, Kul Khand, Youngryel Ryu, Kuno Kasak, A. Christopher Oishi, David E. Reed, Xiangzhong Luo, Carl J. Bernacchi, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ecosystem exchanges of carbon, water, and energy are central to Earth system functioning, yet their sensitivities to environmental variability remain poorly constrained across biomes and climates. Here, we analyzed ≥ 5 years of eddy covariance data from 87 AmeriFlux sites (964 site-years) spanning six vegetation types and a broad range of climatic conditions to examine the controls and multi-year trends of gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency (WUE), and the Bowen ratio. We trained boosted regression tree ensembles with environmental (air temperature, vapor pressure deficit, soil water content, atmospheric CO2, radiation, wind speed) and temporal (month, year) variables …

A Review Of Satellite-Derived Terrestrial Evapotranspiration: Theories, Methods And Products, Yunjun Yao, Jiquan Chen, Joshua B. Fisher, Changliang Shao, Yuanbo Liu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurately estimating terrestrial evapotranspiration (ET), the second-largest hydrologic flux in the terrestrial water cycle, is vital for understanding global water and carbon exchanges. It is difficult to measure and estimate terrestrial ET at regional and global scales. Satellites have provided us an effective tool to estimate regional and global terrestrial ET in recent decades. In this article, we provide a comprehensive review of the basic theoretical foundations, methods and products of satellite-derived terrestrial ET. The basic theoretical foundations for estimating terrestrial ET are the Monin–Obukhov similarity theory (MOST) and other budding theories (e.g., Maximum entropy production theory, and generalized Hamilton …

Thermal Inequities In Public Parks And Open Spaces In Los Angeles Determined By Remote Sensing, Ashley Agatep, Joshua B. Fisher, Kainani Tacazon, Ambar Rivera, Rossmery Zayas, Reginald Archer, Juan Carlos Ruiz Malagon, Jason A. Douglas

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Urban heat island (UHI) effects are amplified by disparities in community-level cooling infrastructure—such as urban public parks and open spaces (PPOS)—with the most severe impacts occurring in communities that lack sufficient city-wide cooling resources. We found that the underserved community of South Los Angeles, as compared to their neighboring West Los Angeles counterparts, suffers a double burden of inequitable (1) access to and (2) absence of cooling materials and surfaces within these spaces, resulting in significantly hotter temperatures. Identifying these inequities requires high-resolution temporal and spatial mapping of surface temperatures, which has been previously limited. In this community-based participatory research …

Satellites, Urban Heat, And Environmental Justice: Community As The Bridge Between Analysis And Action, Joshua B. Fisher, Ambar Rivera, Ava Cison, Ashley Agatep, Kainani Tacazon, Sophia Spiegleman, Alison Mckenery, Rio E. Fisher, Reginald Archer, Jason A. Douglas

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Heat waves are increasing in frequency, intensity, magnitude, and duration, causing a disproportionate impact on marginalized communities exposed to urban heat islands. Newly emerging spaceborne thermal sensing instruments, such as ECOSTRESS and Hydrosat, now have the capabilities to measure urban surface temperatures accurately at the block level (< 100 m) and with enough frequency to capture transient heat waves (daily to subweekly). Such data are critical for monitoring and informing policy and mitigation efforts, such as resurfacing, green space, cooling stations, and medical mobilization. These serve to advance environmental justice and reduce health risks—and deaths—among the most vulnerable: minority, low-income, elderly, those with physical- and mental-health preconditions, unhoused, children, and outdoor workers. While scientists have increasingly used satellite data to quantify urban heat islands and risks to communities, there remains a significant gap in action resulting from such analyses—a figurative and literal “valley of death.” Reviewing over 500 scientific publications, we identify a critical lack of engagement with the communities being analyzed (10.9%; n = 58); yet, community engagement is key to bridging such analysis with subsequent action. Here, we demonstrate how participatory community engagement directly with data and analysis leads to increased policy changes and mitigation efforts. Our framework has immediate implications for how scientists may augment their work and thought processes to achieve …

High Spatiotemporal Resolution Monitoring Of Crop Water Stress Across The Contiguous United States Using Harmonized Landsat And Sentinel-2 Data, Na Chen, Yanlei Feng, Na Wang, Jevan Yu, Mohammad Reza Alizadeh, Yifeng Cui, Ning Ye, Wenzhe Jiao, Joshua B. Fisher, César Terrer

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurate and timely monitoring of crop water stress is essential for efficient agricultural water management, ultimately maintaining and improving crop productivity. While Landsat has been used for this purpose, its temporal resolution hampers timely detection of crop water stress. The recently released Harmonized Landsat and Sentinel-2 Version 2.0 dataset, which enables a higher-frequency time series of satellite observations (2–3 days, 30 m), offers a promising solution to this challenge. However, its potential for crop stress monitoring remained unexplored. In this study, we utilized 923 HLS satellite tiles to assess crop water stress across the contiguous United States (CONUS). Crop water …

Climate Change Has Increased Global Evaporative Demand Except In South Asia, Saeed Karimzadeh, Arman Ahmadi, Dennis Baldocchi, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change alters how strongly the atmosphere draws water from the land, yet a consistent global assessment of this evaporative demand has been lacking. Here, we analyze 45 years of climate data and global models to quantify trends in the key drivers—air temperature, humidity, radiation, wind speed, and cloud cover—that determine the atmosphere’s drying power. We find that evaporative demand has increased worldwide, indicating a stronger atmospheric thirst, except in South Asia, where it has declined. There, widespread irrigation has increased soil and air moisture, enhanced cloud formation, and reduced sunlight reaching the surface, counteracting the global signal. These contrasting …

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

Dramatic Biases In Terrestrial Nitrogen Fixation In Earth System Models Revealed By Natural Isotope Signatures, Maoyuan Fang, Shushi Peng, Philippe Ciais, Daniel S. Goll, Benjamin Z. Houlton, Ying-Ping Wang, Yilong Wang, Pan Liu, Joshua B. Fisher, Pierre Regnier

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Biological nitrogen fixation (BNF) is the primary input of new reactive nitrogen to natural terrestrial ecosystems. However, this flux is poorly constrained due to its unclear drivers and associated control mechanisms. Here, we extend the existing theory of nitrogen (N) isotope mass balance to estimate BNF rates and then use a Bayesian approach to constrain the BNF rates in natural terrestrial ecosystems by using measurements of natural N-isotope ratios (δ¹⁵N) in plants (δ_P) and soil (δ_S). Together with pairwise δ_P and δ_S measurements from 18 forest sites covering diverse climates and thousands …

A Feature Engineering Technique For Enhancing The Generalization Of Machine Learning Models In Estimating Crop Evapotranspiration, Gaku Yokoyama, Sohta Harigai, Shigehiro Kubota, Koichi Nomura, Gregory R. Goldsmith, Daisuke Yasutake, Tomoyoshi Hirota, Masaharu Kitano

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurate and precise estimation of evapotranspiration (ET) is crucial for understanding the terrestrial carbon, water, and energy cycles. While process-based models of ET, such as the Penman–Monteith model offer robust generalization capabilities, they are limited by the need for detailed parameters (e.g., stomatal conductance,) that are challenging to measure continuously. On the other hand, machine learning models can estimate ET by capturing relationships between ET and environmental variables without experimentally measuring model parameters. However, machine learning models face the challenge of limited generalizability. This issue is particularly significant given the uncertainty introduced by changing climatic …

Warming Induces Unexpectedly High Soil Respiration In A Wet Tropical Forest, Tana E. Wood, Colin Tucker, Aura M. Alonso-Rodríguez, M. Isabel Loza, Iana F. Grullón-Penkova, Molly A. Cavaleri, Christine S. O'Connell, Sasha C. Reed

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Tropical forests are a dominant regulator of the global carbon cycle, exchanging more carbon dioxide with the atmosphere than any other terrestrial biome. Climate models predict unprecedented climatic warming in tropical regions in the coming decades; however, in situ field warming studies are severely lacking in tropical forests. Here we present results from an in situ warming experiment in Puerto Rico, where soil respiration responses to ⁺4 ^oC warming were assessed half-hourly for a year. Soil respiration rates were 42-204% higher in warmed relative to ambient plots, representing some of the highest soil respiration rates reported for any …

Performance Mapping And Weighting For The Evapotranspiration Models Of The Openet Ensemble, M. Reitz, J. M. Volk, T. Ott, M. Anderson, G. B. Senay, F. Melton, A. Kilic, R. Allen, Joshua B. Fisher, A. Ruhoff, A. J. Purdy, J. Huntington

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Evapotranspiration (ET) accounts for the majority of water available from precipitation in the terrestrial water cycle, and improvements to the accuracy, resolution, and coverage of ET data can enhance hydrologic models and assessments. The OpenET collaboration of six remotely sensed ET modeling teams has demonstrated that an ensemble approach to ET estimation generally provides improved accuracy relative to individual ensemble members. The performance of individual models has been shown to vary by land cover type and climate zone, but a thorough study of the variables that influence model performance differences has not yet been conducted. In this paper, we model …

Mitigation Behaviors Of Homeowners And Renters In The Wildland Urban Interface, Aishwarya Borate, Omar Pérez Figueroa, Douglas Houston, Christopher Ihinegbu, Ariane Jong-Levinger, Jochen E. Schubert, Brett F. Sanders

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Residential development within the wildland-urban interface (WUI) has greatly expanded in the United States since the 1990s, amplifying wildfire risk by placing people and structures in greater proximity to flammable vegetation. Household wildfire mitigation actions can vary substantially by cost, knowledge required, and perceived effectiveness, but few studies have examined them separately and how their adoption varies by housing tenure in the context of wildfires. To address this gap, we surveyed residents living in WUI areas within Southern California near recent burn scars in the Santa Ana and San Bernardino Mountain ranges. Drawing on the Protection Motivation Theory and the …

Remote Sensing-Based Assessment Of Evapotranspiration Patterns In A Unesco World Heritage Site Under Increasing Water Competition, Maria C. Moyano, Monica Garcia, Luis Juana, Laura Recuero, Lucia Tornos, Joshua B. Fisher, Néstor Fernández, Alicia Palacias-Orueta

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In water-scarce regions, natural ecosystems and agriculture increasingly compete for limited water resources, intensifying stress during periods of drought. To assess these competing demands, we applied a modified PT-JPL model that incorporates the thermal inertial approach as a substitute for relative humidity (RH) in estimating soil evaporation—a method that significantly outperforms the original PT-JPL formulation in Mediterranean semi-arid irrigated areas. This remote sensing framework enabled us to quantify spatial and temporal variations in water use across both natural and agricultural systems within the UNESCO World Heritage site of Doñana. Our analysis revealed an increasing evapotranspiration (ET) trend in intensified agricultural …

A Novel Approach To Increase Accuracy In Remotely Sensed Evapotranspiration Through Basin Water Balance And Flux Tower Constraints, Kul Khand, Gabriel B. Senay, Mackenzie Friedrichs, Koong Yi, Joshua B. Fisher, Lixin Wang, Kosana Suvočarev, Arman Ahmadi, Housen Chu, Stephen Good, Kanishka Mallick, Justine Missik, Jacob A. Nelson, David E. Reed, Tianxin Wang, Xiangming Xiao

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address …

Assessment Of Spatial Autocorrelation And Scalability In Fine-Scale Wildfire Random Forest Prediction Models, Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfire prediction models that can be applied across diverse regions at fine scales (<  100 m) are critical for wildfire management. Remote sensing offers a path forward by providing heterogeneous and dynamic measurements of fuel load, type, and flammability. Machine learning methods such as random forests provide an empirical framework that are high-accuracy, computationally efficient, interpretable and able to model complex ecological relationships. Here we use high resolution (70 m, every 3–5 days) remote sensing observations of evapotranspiration and evaporative stress index, which represent plant water stress, from Ecosystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS), as well as topography and weather data, to predict burn severity and occurrence for 8 large wildfires that burned 3715 km² from 2021 and 2022 in New Mexico, USA. These fires ranged from low to high burn intensity, and covered a diverse range of ecoregions (deserts, grasslands, forests), plant species, and topographies. We used a single model to predict the burn severity of all wildfires one week before occurrence. The prediction accuracy was greatest when using all predictors (ECOSTRESS, weather, topography) (R² = 0.77). We assessed the role of spatial autocorrelation in driving model performance by: (1) increasing the sample spacing of our dataset, (2) …

Evaluation Of Ecostress Collection 2 Evapotranspiration Products: Strengths And Uncertainties For Evapotranspiration Modeling, Zoe Amie Pierrat, Adam J. Purdy, Gregory Halverson, Joshua B. Fisher, Kanishka Mallick, Madeleine Pascolini-Campbell, Youngryel Rye, Martha C. Anderson, Claire Villanueva-Weeks, Margaret C. Johnson, Brenna Hatch, Evan Davis, Yun Yang, Kerry Cawse-Nicholson

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) collects thermal observations from the International Space Station to support evapotranspiration (ET) research at fine spatial resolutions (70 m × 70 m). Initial ET from ECOSTRESS Collection 1 was used in scientific research and applications, though subsequent analyses identified areas for improvement. This study outlines updates to ECOSTRESS Collection 2 ET and presents an accuracy assessment of ET and auxiliary variables validated against in situ data from AmeriFlux. Key updates in Collection 2 include use of four independent model estimates of instantaneous latent energy (LE) and improved auxiliary forcing data. …

Remotely Sensed High-Resolution Soil Moisture And Evapotranspiration: Bridging The Gap Between Science And Society, Jingyi Huang, Vinit Sehgal, Laura V. Alvarez, Luca Brocca, Shuohao Cai, Rui Cheng, Xinghua Cheng, Jinyang Du, Bassil El Masri, K. Arthur Endsley, Yilin Fang, Jie Hu, Mahesh Jampani, Md Golam Kibria, Gerbrand Koren, Lingcheng Li, Laibao Liu, Jiafu Mao, Hernan A. Moreno, Angela Rigden, Mingjie Shi, Xiaoying Shi, Yaoping Wang, Xi Zhang, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

This paper reviews the current state of high-resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high-resolution remote sensing using visible, near-infrared, thermal-infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio-geo-physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily). …

From The Ground Up: Community-Based Participatory Research Reclaiming The Science Of Lead, Juan Manuel Rubio, Bavisha Kaylan, Anthony Diaz, Patricia Flores, Maya Cheav, David C. Bañuelas, Ashley Green, Annika Hjelmstad, Ariane Jong-Levinger, Tim Schütz, Maya Carrasquillo, Alana M. W. Lebron, Jun Wu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

For decades, the dominant approach to lead poisoning has been to focus on homes affected by lead paint and to treat children who are already suffering from lead poisoning. This individualizing approach developed in the context of the defunding and deregulation of government agencies in the 1980s. In recent years, however, community–academic partnerships have reframed lead as an environmental issue produced by the development of the lead industry in the twentieth century and connected to overlapping histories of exploitation, discrimination, and inaction. These community-based projects have contributed to shifting research agendas (by emphasizing historical analysis and the study of the …

Transfer Learning In Junction With A Light Use Efficiency Model For Estimating Grassland Gross Primary Production, Ruiyang Yu, Yunjun Yao, Qingxin Tang, Xueyi Zhang, Changliang Shao, Joshua B. Fisher, Jiquan Chen, Xiaotong Zhang, Yufu Li, Jia Xu, Lu Liu, Zijing Xie, Jing Ning, Jiahui Fan, Luna Zhang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

It is significant to simulate grassland gross primary production (GPP) to understand the terrestrial carbon budget over Inner Mongolia (IMG), China. Nevertheless, there is not sufficient in situ GPP data over this region. In this study, we proposed a novel model-based transfer learning (MTL) approach with generative adversarial networks-long short-term memory (GAN-LSTM) and light use efficiency (LUE) models to derive grassland GPP over IMG, China. We first used 25 grassland eddy covariance sites over the conterminous United States to establish the GAN-LSTM model and then fine-tuned it with six sites over IMG to estimate water constraints that were embedded into …

Reviews And Syntheses: Variable Inundation Across Earth’S Terrestrial Ecosystems, James Stegen, Amy J. Burgin, Michelle H. Busch, Joshua B. Fisher, Joshua Ladau, Jenna Abrahamson, Lauren Kinsman-Costello, Li Li, Xingyuan Chen, Thibault Datry, Nate Mcdowell, Corianne Tatariw, Anna Braswell, Jillian M. Deines, Julia A. Guimond, Peter Regler, Kenton Rod, Edward K. P. Bam, Etienne Fluet-Chouinard, Inke Forbrich, Kristin L. Jaeger, Teri O'Meara, Tim Scheibe, Erin Seybold, Jon N. Sweetman, Jianqiu Zheng, Daniel C. Allen, Elizabeth Herndon, Beth A. Middleton, Scott Painter, Kevin Roche, Julianne Scamardo, Ross Vander Vorste, Kristin Boye, Ellen Wohl, Margaret Zimmer, Kelly Hondula, Maggi Laan, Anna Marshall, Kaizad F. Patel

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal …

Extraordinary 21st Century Drought In The Po River Basin (Italy), Abel Andrés Ramírez Molina, Glenn Tootle, Giuseppe Formetta, Thomas Piechota, Jiaqi Gong

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Recent research identified 2022 as being the year of lowest seasonal April–May–June–July (AMJJ) observed streamflow for the Po River Basin (PRB) in the past two centuries. Expanding upon this research, we applied filters (2-year to 30-year filters) to the AMJJ observed streamflow and identified the late 20th and 21st century as displaying extreme drought. In this study, we introduce PALEO-RECON, an automated reconstruction tool developed to leverage tree ring-based proxies and streamline regression processes. Using PALEO-RECON, we reconstructed the AMJJ streamflow, applying traditional regression techniques and using a nested approach in which 30-, 40-, and 50-year windows within the ~200-year …

Invasion Stress Mitigates Climate Stress In A Brackish Marsh Amphipod, Lorna E. Haworth, Sarah Nancollas, Susie N. Landa, Anne E. Todgham, Richelle L. Tanner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

1. Organisms in coastal brackish ecosystems face not only highly variable environmental conditions, but the intensity and stochasticity of these environmental conditions are anticipated to increase due to climate change. While environmental changes are often presented unilaterally as stressors, there are some anthropogenic environmental transformations, such as the introduction of habitat forming plant species, that may mitigate physiological stress imposed by warming. In Suisun Marsh in the California Delta, native plant canopies allow light and heat to penetrate to the understory yet the canopies of the introduced Phragmites australis reed block out sunlight and heat for organisms living below.
2. We set …

Identifying Opportunities For Nature-Based Solutions With Geospatialized Life Cycle Assessments And Fine-Scale Socioecological Data, Gabriela Shirkey, Annick Anctil, Ranjeet John, Venkatesh Kolluru, Leah Mungai, Herve Kashongwe, Lauren T. Cooper, Ilke Celik, Joshua B. Fisher, Jiquan Chen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) …

Coupling Between Evapotranspiration, Water Use Efficiency, And Evaporative Stress Index Strengthens After Wildfires In New Mexico, Usa, Ryan C. Joshi, Annalise Jensen, Madeleine Pascolini-Campbell, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Aim

Methods

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Examining Wildfire Dynamics Using Ecostress Data With Machine Learning Approaches: The Case Of South-Eastern Australia's Black Summer, Yuanhui Zhu, Shakthi B. Murugesan, Ivone K. Masara, Soe W. Myint, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfires are increasing in risk and prevalence. The most destructive wildfires in decades in Australia occurred in 2019–2020. However, there is still a challenge in developing effective models to understand the likelihood of wildfire spread (susceptibility) and pre-fire vegetation conditions. The recent launch of NASA's ECOSTRESS presents an opportunity to monitor fire dynamics with a high resolution of 70 m by measuring ecosystem stress and drought conditions preceding wildfires. We incorporated ECOSTRESS data, vegetation indices, rainfall, and topographic data as independent variables and fire events as dependent variables into machine learning algorithms applied to the historic Australian wildfires of 2019–2020. …

Carbon Restoration Potential On Global Land Under Water Resource Constraints, Shouzhang Peng, César Terrer, Benjamin Smith, Philippe Ciais, Qinggong Han, Jialan Nan, Joshua B. Fisher, Liang Chen, Lei Deng, Kailiang Yu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ecosystem restoration is a critical nature-based solution to mitigate climate change. However, the carbon sequestration potential of restoration, defined as the maximum achievable carbon storage, has likely been overestimated because previous studies have not adequately accounted for the competition between ecosystem water demands for maximizing carbon sequestration and human water needs. Here we used a comprehensive process-based model combined with extensive land-use data and evaporation recycling accounting for land–atmosphere feedback to estimate the water requirements associated with ecosystem restoration. We found that achieving the carbon sequestration potential of restoration would significantly reduce global water availability per capita by 26%, posing …

Methane Fluxes In Tidal Marshes Of The Conterminous United States, Ariane Arias-Ortiz, Jaxine Wolfe, Scott D. Bridgham, Sara Knox, Gavin Mcnicol, Brian A. Needelman, Julie Shahan, Ellen J. Stuart-Haëntjens, Lisamarie Windham-Myers, Patty Y. Oikawa, Dennis D. Baldocchi, Joshua S. Caplan, Margaret Capooci, Kenneth M. Czapla, R. Kyle Derby, Heida L. Diefenderfer, Inke Forbrich, Gina Groseclose, Jason K. Keller, Cheryl Kelley, Amir E. Keshta, Helena S. Kleiner, Ken W. Krauss, Robert R. Lane, Sarah Mack, Serena Moseman-Valtierra, Thomas J. Mozdzer, Peter Mueller, Scott C. Neubauer, Genevieve Noyce, Katrina V. R. Schäfer, Rebecca Sanders-Demott, Charles A. Schutte, Rodrigo Vargas, Nathaniel B. Weston, Benjamin Wilson, J. Patrick Megonigal, James R. Homquist

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Methane (CH4) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre-industrial times. Wetlands account for a large share of global CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH4 emissions. This effort included creating an open-source database of chamber-based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH4 …

Spatial Optimism And Cross-Over Effects In The Perceptions Of Interconnected Wildfire, Flood, And Mudslide Hazards, Douglas Houston, Omar Pérez Figueroa, Ariane Jong-Levinger, Brett F. Sanders

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Communities near the wildland urban interface (WUI) are exposed to a mix of three interconnected hazards (wildfire, flood, and mudslide), and understanding multi-hazard perceptions is critically important for emergency preparation and hazard mitigation—particularly given the WUI’s rapid expansion and intensifying environmental hazards. Based on a survey of residents living near recent burn scars in Southern California, we document cross-over effects in hazard perceptions, where resident experience with one hazard was associated with greater hazard rankings for other hazards. Additionally, for all three hazards analyzed we document perceptions of increasing hazard levels with increasing spatial scales (home, near-home, neighborhood, and community), …

Estimating Post-Fire Flood Infrastructure Clogging And Overtopping Hazards, Ariane Jong-Levinger, Douglas Houston, Brett F. Sanders

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Cycles of wildfire and rainfall produce sediment-laden floods that pose a hazard to development and may clog or overtop protective infrastructure, including debris basins and flood channels. The compound, post-fire flood hazards associated with infrastructure overtopping and clogging are challenging to estimate due to the need to account for interactions between sequences of wildfire and storm events and their impact on flood control infrastructure over time. Here we present data sources and calibration methods to estimate infrastructure clogging and channel overtopping hazards on a catchment-by-catchment basis using the Post-Fire Flood Hazard Model (PF2HazMo), a stochastic modeling approach that utilizes continuous …