About

Professor Kelly Caylor is a faculty member and Associate Vice Chancellor for Research at the Department of Geography, UC Santa Barbara. His research focuses on the interactions between water, vegetation, and society across the world's drylands. This work situates him within the Terrestrial Sciences domain, where he investigates the complex relationships and dynamics that govern dryland ecosystems and their human components. Professor Caylor's expertise contributes to understanding how these critical environments function and respond to various environmental and societal factors.

Research topics

• Environmental science
• Ecology
• Geography
• Computer Science
• Agricultural economics
• Telecommunications
• Geology
• Atmospheric sciences
• Environmental planning
• Botany
• Business
• Environmental engineering
• Socioeconomics
• Mathematics
• Biology
• Economics
• Physics
• Economic growth
• Soil science
• Meteorology
• Chemistry

Selected publications

• Bridging the Gap: Transforming Reliable Climate Data into Climate Policy

  Eos · 2026-01-16

  articleOpen accessSenior author

  A new special collection welcomes research that bridges the gap between rigorous Essential Climate Variable (ECV) monitoring, AI analytics, and climate policy.

  PublisherDOI

• Capturing Fine-Scale Variability in Dryland Evapotranspiration Through Multi-Scale Thermal Image Analysis

  2025-03-15

  preprintOpen access1st author

  Accurate estimation of evapotranspiration (ET) in drylands is critically dependent on capturing fine-scale spatial variability, yet current thermal remote sensing approaches face significant scaling limitations. While satellite-based thermal imagery provides broad coverage for ET estimation, its coarse resolution fails to capture the heterogeneous vegetation patterns characteristic of dryland ecosystems, leading to systematic biases in ET estimates. The non-linear relationship between land surface temperature (LST) and ET means that coarse-resolution LST measurements cannot simply be averaged to estimate ecosystem-scale ET. Instead, the underlying spatial variance in LST must be properly accounted for when scaling between observations at different resolutions. Here, we demonstrate an approach using very high resolution (VHR) UAV-derived thermal imagery (0.3-m resolution) combined with multi-scale satellite observations (up to 90-m resolution) to develop scaling relationships between LST variance and spatial resolution. We show how these relationships vary with vegetation composition and seasonal dynamics in a dryland ecosystem over one year. By modeling how LST variance changes across scales, we can better estimate ET from coarser thermal imagery while preserving the influence of fine-scale heterogeneity. Our results indicate that vegetation pattern and phenological stage significantly influence scaling behavior, allowing us to identify optimal measurement resolutions for different ecosystem conditions. This approach reduces uncertainty in ET estimates from satellite thermal imagery by incorporating the effects of sub-pixel spatial variability revealed by VHR observations. The scaling relationships we develop provide a framework for improving regional ET estimates in drylands while accounting for their characteristic fine-scale vegetation patterns.

  PublisherDOI

• Wind stress effects on drone-based thermal infrared surface velocimetry measurements of tidal flow in an estuary

  2025-08-26

  articleOpen access

  We evaluate the effect of surface wind stress on remote velocimetry measurements of tidal flow by comparing these measurements to the bulk flow velocity measured by a co-located acoustic velocity profiler in a tidal channel. The remote velocity measurements are made with a thermal imager mounted on a drone hovering directly over the acoustic measurement location. Drones are a useful platform to support a variety of cameras and sensors for capturing images that can be used to infer surface velocities. Drone-mounted thermal infrared microbolometer cameras are a lower-cost infrared imaging solution that can detect subtle temperature patterns which naturally occur at the surface of many flows. These thermal patterns are used as signals for pattern-tracking to produce velocity measurements across the observed water surface. Drone flights were conducted at Carpinteria Salt Marsh Reserve (California, USA). Wind speed and direction relative to the flow direction caused the drone-based surface velocimetry measurements to deviate from in-channel surface-extrapolated acoustic velocity measurements. Drone-based velocity measurements were slower than in-channel velocity measurements when the parallel wind stress direction was opposite the tidal flow, while drone-based velocity measurements were faster than in-channel velocity measurements when the parallel wind stress and tidal flow were in the same direction. The effect of wind stress on remote surface velocimetry measurements is relatively unstudied, and herein we quantify this effect by comparing image-derived estimates to in-channel velocity measurements. This experiment also demonstrates the feasibility of drone-based thermal surface velocimetry measurements in an estuary.

  PublisherOA PDFDOI

• Thank You to Our 2024 Reviewers

  Earth s Future · 2025-03-29

  articleOpen access1st authorCorresponding

  Abstract On behalf of the journal, AGU, and the scientific community, we, the editors of Earth's Future, are delighted to publish the names of the 1,061 peer reviewers who provided 1,642 reviews for our journal in 2024 (italicized names have contributed three or more reviews). Your diligent efforts to provide timely comments on our submissions have significantly improved the manuscripts and elevated the scientific rigor of future research. As a unique transdisciplinary journal, Earth's Future delves into the state of the planet and its inhabitants, sustainable and resilient societies, the science of the Anthropocene, and predictions of our shared future through research articles, reviews, and commentaries. In the face of observed and anticipated global environmental and climatic changes, the need for high‐quality scientific theories, assessments, and projections about the future of our planet has never been more pressing. To safeguard research integrity in this crucial area, we rely on our reviewers' expertise and selfless cooperation. We extend our heartfelt thanks to each of the individuals listed below for their contributions to our journal and the broader scientific discourse. Your dedication is immensely appreciated.

  PublisherOA PDFDOI

• Five Lessons for Closing the Last Mile: How to Make Climate Decision Support Actionable

  Earth s Future · 2025-07-31 · 2 citations

  articleOpen access

  Abstract Climate shocks are increasing, threatening global agricultural production and food security. But a more extreme climate allows for improved predictions and enables advisory services that allow farmers, ranchers and consumers to respond effectively. To date, there is limited uptake of forecasts. How can we make sure these predictions are valued by and valuable for users of agro‐climatic forecasts? Over the past two years, we held over 40 interviews with food system stakeholders to identify their needs and shortcomings of existing decision support. In this Commentary, we combine these findings and nascent modeling efforts with existing literature to characterize five lessons for improving the uptake and utilization of predictive tools for last mile users in the agrifood system. Given the explosion of machine learning prediction efforts across many applications, we believe our lessons are broadly applicable to forecasting models intended for decision support. Improved accuracy alone does not necessarily lead to improved decision support, and the trust required to motivate action.

  PublisherOA PDFDOI

• Wind Stress Effects on Drone‐Based Thermal Infrared Surface Velocimetry Measurements of Tidal Flow in an Estuary

  Water Resources Research · 2025-09-01

  articleOpen access

  Abstract We evaluate the effect of surface wind stress on remote velocimetry measurements of tidal flow by comparing these measurements to the bulk flow velocity measured by a co‐located acoustic velocity profiler in a tidal channel. The remote velocity measurements are made with a thermal imager mounted on a drone hovering directly over the acoustic measurement location. Drones are a useful platform to support a variety of cameras and sensors for capturing images that can be used to infer surface velocities. Drone‐mounted thermal infrared microbolometer cameras are a lower‐cost infrared imaging solution that can detect subtle temperature patterns which naturally occur at the surface of many flows. These thermal patterns are used as signals for pattern‐tracking to produce velocity measurements across the observed water surface. Drone flights were conducted at Carpinteria Salt Marsh Reserve (California, USA). Wind speed and direction relative to the flow direction caused the drone‐based surface velocimetry measurements to deviate from in‐channel surface‐extrapolated acoustic velocity measurements. Drone‐based velocity measurements were slower than in‐channel velocity measurements when the parallel wind stress direction was opposite the tidal flow, while drone‐based velocity measurements were faster than in‐channel velocity measurements when the parallel wind stress and tidal flow were in the same direction. The effect of wind stress on remote surface velocimetry measurements is relatively unstudied, and herein we quantify this effect by comparing image‐derived estimates to in‐channel velocity measurements. This experiment also demonstrates the feasibility of drone‐based thermal surface velocimetry measurements in an estuary.

  PublisherDOI

• Low-cost autonomous chambers enable high spatial and temporal resolution monitoring of soil CO₂ exchange across landscapes

  2025-08-15

  articleOpen access

  1. Soil CO₂ flux is a critical component of ecosystem carbon cycling, but due to high cost and mechanistic constraints, existing measurement systems are often limited by trade-offs between resolution (temporal and spatial), and spatial coverage. These constraints hinder efforts to monitor soil fluxes across diverse, heterogeneous landscapes and environmental gradients. 2. We developed Fluxbot 2.0, a low-cost, autonomous chamber system capable of continuous, distributed soil CO₂ flux measurements without external power or infrastructure. To assess its capability to capture landscape-scale variability, we deployed two Fluxbot 2.0 arrays, one at each of two hemlock forest sites in Harvard Forest, Massachusetts, USA, and compared its estimates of flux to those from existing, well-established automated chamber arrays that rely on multiplexed chambers and high-accuracy CO2 analyzer units. 3. Fluxbots successfully captured site means, spatial variability, temporal patterns, and environmental responses, including temperature-driven flux dynamics. These measurements reflected differences in forest conditions between two sites and showed that distributed arrays of low-cost sensors can effectively capture both fine-scale variability and broader patterns across a landscape. 4. By enabling low-cost, autonomous monitoring of soil carbon flux in strategically distributed arrays, Fluxbot 2.0 addresses key gaps in existing soil CO₂ flux datasets. The system facilitates measurements across environmental gradients and heterogeneous landscapes, supporting research on soil carbon dynamics and biotic interactions that influence carbon cycling.

  PublisherOA PDFDOI

• Nonlinear Soil Moisture Loss Function Reveals Vegetation Responses to Water Availability

  Geophysical Research Letters · 2025-06-03 · 5 citations

  articleOpen accessSenior author

  Abstract Soil moisture drydown patterns encode signatures of vegetation water‐use. Previous characterizations of the drydown patterns assume a static linear relationship between water‐limited transpiration and available moisture. However, ecohydrological studies show that vegetation exhibits a spectrum of responses to water availability, suggesting that soil moisture loss functions may be nonlinear. To represent these dynamics, we introduce a nonlinearity parameter to the loss function. Our analysis shows that the nonlinear loss model improves the characterization of the satellite‐observed soil moisture drydowns. Globally, functional responses of drydowns are dominated by convex nonlinearity, showing less ecosystem water loss in dry soils than the linear loss function predicts. We find distinct degrees of nonlinearity among different vegetation types; areas with non‐woody vegetation more frequently exhibit a concave nonlinearity, the signature of aggressive water‐use strategies. We propose the nonlinear loss function as a continuous and dynamic framework to represent vegetation water‐use under changing water availability.

  PublisherOA PDFDOI

• The Executive Order “Restoring Gold Standard Science” is Dangerous for America

  AGU Advances · 2025-08-01 · 3 citations

  articleOpen access

  Abstract The recent U.S. executive order “Restoring Gold Standard Science” poses a significant threat to the U.S. national economy and security. The order replaces the scientific experts who lead U.S. governmental scientific organizations with non‐scientific political appointees who would have the power to decide what science could and could not be published. In doing so, the executive order threatens to reverse more than 80 years of scientific advancements that have given the U.S. its world‐leading military, technology, and economy. The justifications provided in the executive order for this change in policy are false or misleading in their assessment and representation of the current state of U.S. scientific scholarship. Hypocritical in its aims, the executive order claims to promote integrity in science while at the same time calling to remove the “Framework for Federal Scientific Integrity Policy and Practice” that currently ensure veracity and credibility in science. The executive order is also unconstitutional, threatening to take away the First Amendment rights of scientists by punishing them if they publish truthful and accurate science that is contrary to the administration's political agenda. Such censorship of scientists has been attempted by failed governments of the past such as Nazi Germany, the Soviet Union, and early communist China, always with disastrous consequences for their citizens. “Restoring Gold Standard Science” needs to be rescinded to avoid catastrophic consequences for the U.S. economy and national security.

  PublisherOA PDFDOI

• Using hyperspectral and thermal imagery to monitor stress of Southern California plant species during the 2013–2015 drought

  ISPRS Journal of Photogrammetry and Remote Sensing · 2025-01-16 · 10 citations

  articleSenior author
  PublisherDOI

Recent grants

• Collaborative Proposal: Distribution and Dynamics of Belowground Carbon in Savannas

  NSF · $208k · 2007–2010

• CAREER: An ecohydrological framework for understanding land degradation in dryland ecosystems

  NSF · $1.5M · 2009–2014

• ESE: Collaborative Research: Spatial Resilience of Agriculturalists to Coupled Ecological and Hydrological Variability in Rural Zambia

  NSF · $350k · 2010–2015

• Collaborative research: Quantifying the ecosystem-wide impacts of a strong interactor in African watersheds

  NSF · $123k · 2012–2016

• WSC-Category 2 Collaborative: Impacts of Agricultural Decision Making and Adaptive Management on Food Security

  NSF · $629k · 2017–2020

Frequent coauthors

• Lyndon Estes

  74 shared

• Tom Evans

  56 shared

• John C. Stella

  40 shared

• Stephen P. Good

  Oregon State University

  35 shared

• Eric F. Wood

  32 shared

• Lixin Wang

  Inner Mongolia University

  30 shared

• Justin Sheffield

  30 shared

• Michael Bliss Singer

  University of California, Santa Barbara

  29 shared

Labs

• Kelly Caylor's LabPI

  Hydrology, rainfall-runoff process, soil moisture dynamics, floods & droughts, land-use & climate change.

Education

• PhD, Department of Environmental Sciences

  University of Virginia

  2003

• BA, Department of Environmental Sciences

  University of Virginia

  1996

Awards & honors

• Early Career Award from the NSF
• Inaugural recipient of the Early Career Award in Hydrologica…