About

Jennifer King is a Professor in the Department of Geography at UC Santa Barbara, where she also serves as Vice Chair of Undergraduate Programs. She joined the faculty in 2008 and has a background rooted in Texas, having lived and conducted research in various locations including Texas, California, Alaska, Colorado, and Minnesota. Her research focuses on biogeochemistry, specifically the study of element cycling through the Earth system. She is interested in understanding the natural and anthropogenic processes that influence patterns of element cycling in terrestrial ecosystems, with particular attention to interactions between vegetation, soil, and the atmosphere. Her work examines how human activities affect the cycling of carbon and nutrients, exploring questions such as the factors influencing litter decomposition under different environmental conditions and how land management practices impact soil carbon and nutrient status. To address these questions, she employs a range of laboratory and field techniques. Her current research centers on mechanisms of photodegradation of plant litter and changes in carbon cycling during wetland restoration.

Research topics

• Computer Science
• Environmental science
• Ecology
• Environmental chemistry
• Oceanography
• World Wide Web
• Biology
• Geology
• Chemistry
• Operating system
• Soil science
• Database
• Geomorphology

Selected publications

• Photodegradation Increases Solubility of Grass Litter Carbon

  Journal of Geophysical Research Biogeosciences · 2026-04-01

  articleSenior author

  Abstract Solar radiation is an important factor influencing dryland decomposition. Research suggests that, in the presence of water, previously irradiated plant litter experiences greater microbial decay than litter which was not exposed to radiation. The mechanism of this photopriming of microbial decomposition is unclear. We tested the hypothesis that solar radiation would (a) increase dissolved organic carbon (DOC) from litter subsequently extracted with water, and (b) produce DOC that stimulates more microbial activity than unexposed litter. Samples of dried senesced grass litter from three species, Bromus diandrus , Avena fatua , and Hordeum murinum , were exposed to radiation in indoor and outdoor experiments. Treated litter was soaked in water and the extract was analyzed to determine the DOC concentration and bioavailability. Radiation exposure produced more DOC in both experiments (40% greater outdoors and 21% greater indoors with visible radiation compared to blocked; 20% greater outdoors and 51% greater indoors with UV and visible compared to visible alone), suggesting that solar radiation enhances grass litter solubility. During a microbial incubation of extracted DOC, mean CO 2 production increased by 24%, and increased significantly for indoor samples. However, radiation reduced CO 2 production by ∼23% when DOC concentration is taken into account, indicating that photodegradation produces recalcitrant compounds. Photodegradation still stimulated the microbial activity overall by increasing the total available DOC. These results suggest that litter carbon is made more soluble by radiation and is mobilized by water, allowing for increased microbial decomposition. This mechanistic insight could improve carbon cycle models that include photopriming.

  PublisherDOI

• 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

  article
  PublisherDOI

• Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

  Maryland Shared Open Access Repository (USMAI Consortium) · 2025-03-21

  articleOpen access

  We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

  PublisherDOI

• Unlocking ecological insights from sub‐seasonal visible‐to‐shortwave infrared imaging spectroscopy: The <scp>SHIFT</scp> campaign

  Ecosphere · 2025-03-01 · 11 citations

  articleOpen access

  Abstract We stand at the threshold of a transformative era in Earth observation, marked by space‐borne visible‐to‐shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter‐ and intra‐annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub‐seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High‐Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer‐Next Generation (AVIRIS‐NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub‐seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open‐source processing methods and cloud‐based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high‐frequency time series data from space‐borne VSWIR imaging spectrometers.

  PublisherDOI

• Using imaging spectroscopy and elevation in machine learning to estimate soil salinity in intermittently tidal wetlands

  Ecosphere · 2025-08-01

  articleOpen accessSenior author

  Abstract Coastal soil salinization patterns are changing due to drought, sea level rise (SLR), and changing freshwater inflow. These changes are expected to impact coastal wetland plant health and ecosystem function, such as changes to biomass and productivity. These impacts have led to greater interest in how we monitor soil salinization across spatial and temporal scales. Remote sensing is a promising tool for estimating soil salinity at the spatial scales required for decision making by land managers. However, the development of a remote sensing estimation approach for wetland soil salinity must account for two factors: (1) the high spatial and temporal heterogeneity of coastal wetlands and (2) the fact that soil salinity is the result of multiple historical land use, hydrological, and geomorphic processes. In spring 2022, a combined airborne‐field campaign, known as SHIFT, collected a weekly time series of airborne visible to shortwave infrared (VSWIR) image spectroscopy data. This dataset provides a unique opportunity to assess the application of fine spatial (5 m) and temporal (weekly) resolution VSWIR data to estimate root zone soil salinity; when combined with environmental variables such as elevation, these data can account for some of these factors. In this study, we utilized VSWIR and elevation datasets in a random forest regression to predict and map soil salinity in an intermittently tidal estuary, Devereux Slough, located in Santa Barbara County, California. The final model combined spectral indices with elevation to better capture soil salinity dynamics despite lower correlation ( r = 0.85) than solely using elevation ( r = 0.92). This research demonstrates the utility of remote sensing datasets, namely, elevation and the modified Anthocyanin Reflectance Index (mARI), for predicting root zone soil salinity in intermittently tidal coastal wetlands. These findings are an important step in advancing coastal remote sensing by creating a gridded salinity dataset that can be used for salinity monitoring and other coastal applications, such as modeling change in vegetation communities or ecosystems facing the impacts of climatic variability and change.

  PublisherOA PDFDOI

• Shifts in Salt Marsh Vegetation Landcover after Debris Flow Deposition

  Remote Sensing · 2022 · 10 citations

  Senior authorCorresponding
  • Environmental science
  • Geology
  • Ecology

  On 9 January 2018, Carpinteria Salt Marsh Reserve received a large quantity of sediment following debris flows in Montecito, California. Because disturbances potentially impact the ecosystem services and functions that wetlands provide, an understanding of how the ecosystem responded to the debris flows is important for the management of salt marsh systems. However, a lack of field data before and after this disturbance makes this task impossible to complete by field methods alone. To address this gap, we used Sentinel-2 satellite imagery to calculate landcover fractions and spectral indices to produce maps of landcover before, during, and after the debris flow using a random forest classifier. Change detection showed that vegetation extent in November 2020 approached pre-debris flow conditions. While total vegetated area experienced little net change (0.15% decrease), there was a measurable change in the areal extent of vegetation type, with high marsh vegetation transitioning to mid marsh vegetation in regions that initially showed an increase in bare soil cover. These results are uniquely quantifiable using remote sensing techniques and show that disturbance due to debris flows may affect ecosystem function via plant community change. These impacts will need to be taken into consideration when managing wetlands prone to depositional events.

  PublisherOA PDFDOI

• Photodegradation influences litter decomposition rate in a humid tropical ecosystem, Brazil

  The Science of The Total Environment · 2020 · 43 citations

  Senior authorCorresponding
  • Environmental science
  • Environmental chemistry
  • Chemistry
  PublisherDOI

• It's a Long Way... from Private Ground-based Gamma-ray Data to Public Release: Open-data, Open-source Tools, First Real TeV Data Release from H.E.S.S.

  Astronomical Data Analysis Software and Systems XXVII · 2020

  • Computer Science
  • Computer Science
  • Database
  Publisher

• Classifying California plant species temporally using airborne hyperspectral imagery

  Remote Sensing of Environment · 2019-07-17 · 53 citations

  article
  PublisherDOI

• Plant species' spectral emissivity and temperature using the hyperspectral thermal emission spectrometer (HyTES) sensor

  Remote Sensing of Environment · 2019-03-01 · 39 citations

  article
  PublisherDOI

Recent grants

• Photodegradation of Plant Litter in Grassland Ecosystems: A Mechanism for Uncoupling C and N Biogeochemistry

  NSF · $225k · 2008–2012

• Photodegradation of Plant Litter in Grassland Ecosystems: A Mechanism for Uncoupling C and N Biogeochemistry

  NSF · $458k · 2006–2009

• DISSERTATION RESEARCH: Photodegradation as an Abiotic Mechanism in the Decomposition of Surface Litter

  NSF · $10k · 2006–2009

• DISSERTATION RESEARCH:Quantifying Changes in Lignin Chemistry During Photodegradation Versus Biotic Decomposition Using 2D NMR Spectroscopy

  NSF · $20k · 2014–2015

Frequent coauthors

• Thomas Quertermous

  29 shared

• Raymond Tabibiazar

  29 shared

• Euan A. Ashley

  Stanford University

  29 shared

• Leslie A. Brandt

  US Forest Service

  27 shared

• Anya Tsalenko

  Agilent Technologies (United States)

  27 shared

• A. R. Mosier

  22 shared

• E. Carol Adair

  University of Vermont

  20 shared

• Philip S. Tsao

  VA Palo Alto Health Care System

  20 shared

Labs

• Jennifer King's LabPI

  Not provided