About

Christopher Jerde is a faculty member at the UC Santa Barbara Bren School of Environmental Science & Management, where he serves as a lecturer. His research areas include applied statistics, data science, biodiversity, environmental DNA, and invasive species. He teaches courses such as ESM 206 Statistics and Data Analysis for Environmental Science and Management and ESM 211 Applied Population Ecology. Growing up in northeastern South Dakota, Jerde developed an early interest in ecology through fishing and camping among prairie pothole lakes. He completed his B.Sc. in 1998 and M.Sc. in 2002 at Montana State University, where his studies focused on ecology and bison population dynamics. He further pursued his Ph.D. at the University of Alberta's Centre for Mathematical Biology, which he completed in 2008. His postdoctoral work and subsequent position as a research assistant professor at the University of Notre Dame involved developing environmental DNA surveillance programs for invasive species, notably Bighead and Silver Asian Carp. Currently, as an Associate Researcher at UCSB’s Marine Science Institute, Jerde emphasizes using novel quantitative, data science, and sampling approaches to address pressing environmental problems and ecological theory.

Research topics

• Ecology
• Biology
• Fishery
• Environmental science
• Geography

Selected publications

• Evaluating short-term porewater dynamics and tracing carbon storage across a seagrass-fringing reef interface in Moorea, French Polynesia

  2026-03-26

  articleOpen access

  Seagrass meadows are particularly understudied in the tropical Indo-Pacific. Although this region is a hotspot of seagrass diversity, there is limited published monitoring data for seagrasses and to date, there is no data on the carbon storage potential of sediment underlying seagrass meadows in Moorea. In Moorea, French Polynesia, Halophila decipiens is found in lagoons and nearshore environments, adjacent to fringing reefs around the island. Here, we take a multidisciplinary approach to investigate organic and inorganic carbon storage in the seagrass meadows of Moorea via high spatial resolution sampling across an individual seagrass meadow and island-wide surveys. We use elemental analyses of carbon, nitrogen, and sulfur of seagrass sediment and grain size analysis to better understand organic carbon storage and sources of carbon across the seagrass meadow and into an adjacent fringing reef. We also conduct short-term porewater sampling for total alkalinity and concentrations of dissolved inorganic carbon within the seagrass meadow and adjacent fringing reef to investigate inorganic carbon storage. Our results show universally high carbonate (wt %) present across the fringing reef and seagrass samples, however; we find elevated but variable organic carbon content (wt% C) in the seagrass sediments. Smaller grain sizes were a reliable predictor of organic carbon of surface sediments in Moorea. We found elevated alkalinity levels at depth in porewater from within the seagrass meadow compared to the fringing reef. Our study provides the first estimates of seagrass’ blue carbon potential in Moorea, a critical step towards the effective management and understanding of these tropical blue carbon ecosystems.

  PublisherOA PDFDOI

• A Metadata Checklist and Data Formatting Guidelines to Make eDNA FAIR (Findable, Accessible, Interoperable, and Reusable)

  ResearchOnline - JCU (James Cook University) · 2025-01-01

  article

  The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding-based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data-driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA-specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready-to-use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user-driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long-term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources.

• A Metadata Checklist and Data Formatting Guidelines to Make <scp>eDNA FAIR</scp> (Findable, Accessible, Interoperable, and Reusable)

  Environmental DNA · 2025-05-01 · 27 citations

  articleOpen access

  ABSTRACT The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding‐based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data‐driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA‐specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready‐to‐use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user‐driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long‐term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources.

  PublisherDOI

• Optimising species detection probability and sampling effort in lake fish eDNA surveys

  Metabarcoding and Metagenomics · 2024-07-24 · 16 citations

  articleOpen access

  Environmental DNA (eDNA) metabarcoding is transforming biodiversity monitoring in aquatic environments. Such an approach has been developed and deployed for monitoring lake fish communities in Great Britain, where the method has repeatedly shown a comparable or better performance than conventional approaches. Previous analyses indicated that 20 water samples per lake are sufficient to reliably estimate fish species richness, but it is unclear how reduced eDNA sampling effort affects richness, or other biodiversity estimates and metrics. As the number of samples strongly influences the cost of monitoring programmes, it is essential that sampling effort is optimised for a specific monitoring objective. The aim of this project was to explore the effect of reduced eDNA sampling effort on biodiversity metrics (namely species richness and community composition) using algorithmic and statistical resampling techniques of a data set from 101 lakes, covering a wide spectrum of lake types and ecological quality. The results showed that reliable estimation of lake fish species richness could, in fact, usually be achieved with a much lower number of samples. For example, in almost 90% of lakes, 95% of complete fish richness could be detected with only 10 water samples, regardless of lake area. Similarly, other measures of alpha and beta-diversity were not greatly affected by a reduction in sample size from 20 to 10 samples. We also found that there is no significant difference in detected species richness between shoreline and offshore sampling transects, allowing for simplified field logistics. This could potentially allow the effective sampling of a larger number of lakes within a given monitoring budget. However, rare species were more often missed with fewer samples, with potential implications for monitoring of invasive or endangered species. These results should inform the design of eDNA sampling strategies, so that these can be optimised to achieve specific monitoring goals.

  PublisherOA PDFDOI

• Repeated Pass Removal Survey for Estimating Land-Based Trash Abundance v1

  2024-10-11

  preprintOpen accessSenior author

  Land-based litter negatively impacts human and ecosystem health, tourism and recreation, and the economy.1 Most terrestrial, aquatic, and marine litter consists of plastic items, and a majority of aquatic and marine litter comes from terrestrial sources.2, 3, 4 Yet, plastic litter in terrestrial systems remains understudied relative to litter in aquatic and marine environments.3, 5 Surveying is a common method for determining litter abundance in terrestrial systems. Single-pass litter surveys, in which a surveyor passes through a transect once by foot, bicycle, or car, serve as the established method for assessing the qualitative or quantitative abundance of land-based litter. Established single-pass survey methods include but are not limited to the Bay Area Stormwater Management Association On-Land Visual Trash Assessment, various Surfrider and Channel Keeper “Beach Clean Up” methods, the Southern California Coastal Water Research Program Southern California Bight Regional Monitoring Program Trash Surveys, the Keep America Beautiful National Visible Litter Survey, the National Oceanic and Atmospheric Administration Marine Debris Monitoring and Assessment Project, the Ocean Conservancy International Coastal Cleanup, 5 Gyres Plastic Beach and Plastic Ocean methods, the University of Washington Coastal Observation and Seabird Survey Team Marine Debris Survey, the State of California Surface Water Ambient Monitoring Program Rapid Trash Assessment, the Alliance for the Great Lakes Adopt-A-Beach Litter Monitoring method, and some United States Environmental Protection Agency Trash Free Waters Projects.6 Single-pass litter survey methods are useful given the time and cost constraints often associated with boots-on-the-ground surveying. However, there is a tradeoff: single-pass surveys underestimate litter abundance relative to multiple-pass surveys, and single-pass surveys lack measures of the variance in litter abundance. This is primarily because single-pass surveys involve variable levels of surveying effort, and do not always result in quantitative measures. Underestimation of litter abundance and knowledge gaps regarding the variation in litter abundance will result in inaccurate results when it comes to monitoring and predicting litter source, transport, and fate. Additionally, due to unmeasured variation in litter abundance, data acquired through single-pass trash assessment methods or clean-up events are difficult to compare without measures of effort. To address these issues, the Repeated Pass Removal Survey for Estimating Land-Based Trash Abundance aims to better estimate the number of visible and removable plastic litter items in the environment, with a quantification of the uncertainty around that estimate suitable for comparison between sites.

  PublisherOA PDFDOI

• Snail slime in real time: Challenges in predicting the relationship between environmental DNA and apple snail biomass

  Management of Biological Invasions · 2024-01-01 · 3 citations

  articleOpen access

  As environmental DNA (eDNA) becomes a fixture in the invasive species management toolbox, expectations of its utility extend beyond presence/absence to analyses that provide more detailed information about target populations.Studies with fish and other vertebrates have reported moderately reliable, positive relationships between eDNA concentrations and biomass.However, few studies have considered this relationship in invertebrates.To address this gap, we investigated whether increasing biomass of apple snails (Pomacea maculata) resulted in a similar predictive relationship with eDNA concentration, and we did so under cold conditions that make apple snails less conspicuous and more difficult to detect with traditional methods.Placing snails in either distilled or stream water, we used a species-specific quantitative PCR assay to measure eDNA concentrations after 24 hr over an apple snail biomass gradient (0, 2, 4, or 6 snails; 143 to 624 g total biomass).Detection success of eDNA derived from apple snails kept in a small volume (i.e., 13 L) of cold water (13 C) averaged 66% overall.Successful detection in distilled water (75%) exceeded the overall average.Lower detection efficiency occurred in stream water (58%).Despite the cold conditions, we observed snail activity in 90% of our replicates, but net eDNA accumulation failed to reflect patterns commonly observed with vertebrates.Censored regression modeling efforts, which account for a disproportionate number of zeros (i.e., non-detections), identified a significant predictive relationship between snail biomass and eDNA concentration, but only starting at a high amount of biomass (~ 422 g).Future management strategies to monitor apple snails will likely include eDNA, but its utility in ascertaining biomass remains unclear.Considering the ecology of eDNA of invasive invertebrates will help bolster managers' ability to understand the utility and limitations of this valuable tool.

  PublisherDOI

• Best Practice for Publishing Environmental DNA (eDNA) Data According to FAIR Principles

  Biodiversity Information Science and Standards · 2024-10-14 · 4 citations

  articleOpen access

  Reversing global biodiversity loss will require transformational human actions and robust measurements of their effectiveness. Diversity assessment using environmental DNA (eDNA) has emerged as a cutting-edge technique with the potential to address the challenges of measuring biodiversity. Vast amounts of eDNA sequences and eDNA-based species detections are generated in scientific studies. These datasets are typically stored in a variety of different repositories in multiple formats, hindering their reuse (Berry et al. 2020). Ensuring the publication of eDNA data following the FAIR (Findable, Accessible, Interoperable, Reusable) principles (Wilkinson et al. 2016) would revolutionise environmental assessment, including monitoring of biodiversity, individual species, and interactions across extensive spatial and temporal scales, and generate critical knowledge for evidence-based management. Archiving FAIR eDNA data requires standardising data formats and vocabularies, cyberinfrastructures, guidelines, data sharing policy, and collaboration among scientists and institutions. Some of these requirements are addressed by existing data standards and infrastructures, including Darwin Core (DwC) (Wieczorek et al. 2012), Minimum Information about any (x) Sequence (MIxS) (Yilmaz et al. 2011), the Global Biodiversity Information Facility (GBIF) network, and International Nucleotide Sequence Database Collaboration (INSDC) partners (Arita et al. 2020). However, multiple challenges remain and FAIR data practices have yet to be established among the eDNA community. This is partly because critical attributes unique to eDNA data are not adequately accommodated by existing standards. For example, monitoring contamination and excluding non-target taxa, and the parameters used for quality filtering and species detection vary greatly between studies, depending on the study scopes and the associated financial and ecological costs of incorrectly inferring presence or absence. Making such information FAIR is needed for future studies reusing data and requiring high confidence levels in species detection and taxonomic assignment. Furthermore, the procedures of targeted-taxon detection approach (e.g., interpretations of quantitative polymerase chain reaction (qPCR) results in detecting the presence of DNA from individual taxa) have not yet been fully captured by existing standards. Increasing efforts have been made to establish minimum reporting requirements to validate eDNA study methods and data (Klymus et al. 2020, Thalinger et al. 2021). These requirements need further development to be translated into data standards and formats to enhance machine readability and reusability, and to support and guide the eDNA community, so that they are effectively utilised. In this talk, we share our best practice guide for formatting and publishing eDNA data, developed by an international multidisciplinary working-group comprising eDNA researchers, journal editors, and biodiversity and omics data scientists. We identified required data types, formats and metadata checklists through reviewing and integrating existing data standards, devising subject-specific vocabularies, and introducing additional terms to accommodate the distinctive properties of eDNA data. Implementing the FAIR eDNA data best practice guide, offers a pivotal step towards standardising and enhancing the publication and re-use of eDNA data.

  PublisherDOI

• Optimising species detection probability and sampling effort in lake fish eDNA surveys

  2023-05-02 · 1 citations

  preprintOpen access

  Environmental DNA (eDNA) metabarcoding is transforming biodiversity monitoring in aquatic environments where the method has repeatedly shown comparable or better performance than conventional approaches to fish monitoring. This method has been developed and deployed, primarily using shoreline sampling during the winter months, across 101 lakes in Great Britain alone, covering a wide spectrum of lake types and ecological quality. Previous analyses on a subset of these lakes indicated that 20 water samples per lake are sufficient to reliably estimate fish species richness, but it is unclear how reduced eDNA sampling effort affects richness, or other biodiversity estimates and metrics. As the number of samples strongly influences the cost of monitoring programmes, it is essential that sampling effort is optimised for a specific monitoring objective. The aim of this project was to explore the effect of reduced eDNA sampling effort on biodiversity metrics (namely species richness and community composition) using algorithmic and statistical resampling techniques. The results showed that reliable estimation of lake fish species richness could in fact usually be achieved with a much lower number of samples. For example, in almost 90% of lakes, 95% of complete fish richness could be detected with only 10 water samples, regardless of lake area. Similarly other measures of alpha and beta-diversity were not greatly affected by a reduction in sample size from 20 to 10 samples. We also found that there is no significant difference in detected species richness between shoreline and offshore sampling transects, allowing for simplified field logistics. This could potentially allow the effective sampling of a larger number of lakes within a given monitoring budget. However, rare species were more often missed with fewer samples, with potential implications for monitoring of invasive or endangered species. These results should inform the design of eDNA sampling strategies, so that these can be optimised to achieve specific monitoring goals.

  PublisherOA PDFDOI

• Critical considerations for communicating environmental <scp>DNA</scp> science

  Environmental DNA · 2023-09-01 · 21 citations

  articleOpen access

  The economic and methodological efficiencies of environmental DNA (eDNA) based survey approaches provide an unprecedented opportunity to assess and monitor aquatic environments. However, instances of inadequate communication from the scientific community about confidence levels, knowledge gaps, reliability, and appropriate parameters of eDNA-based methods have hindered their uptake in environmental monitoring programs and, in some cases, has created misperceptions or doubts in the management community. To help remedy this situation, scientists convened a session at the Second National Marine eDNA Workshop to discuss strategies for improving communications with managers. These include articulating the readiness of different eDNA applications, highlighting the strengths and limitations of eDNA tools for various applications or use cases, communicating uncertainties associated with specified uses transparently, and avoiding the exaggeration of exploratory and preliminary findings. Several key messages regarding implementation, limitations, and relationship to existing methods were prioritized. To be inclusive of the diverse managers, practitioners, and researchers, we and the other workshop participants propose the development of communication workflow plans, using RACI (Responsible, Accountable, Consulted, Informed) charts to clarify the roles of all pertinent individuals and parties and to minimize the chance for miscommunications. We also propose developing decision support tools such as Structured Decision-Making (SDM) to help balance the benefits of eDNA sampling with the inherent uncertainty, and developing an eDNA readiness scale to articulate the technological readiness of eDNA approaches for specific applications. These strategies will increase clarity and consistency regarding our understanding of the utility of eDNA-based methods, improve transparency, foster a common vision for confidently applying eDNA approaches, and enhance their benefit to the monitoring and assessment community.

  PublisherOA PDFDOI

• Time to invest in the worst: a call for full genome sequencing of the 100 worst invasive species

  Frontiers in Environmental Science · 2023-10-30 · 3 citations

  articleOpen access

  OPINION article Front. Environ. Sci., 30 October 2023Sec. Conservation and Restoration Ecology Volume 11 - 2023 | https://doi.org/10.3389/fenvs.2023.1258880

  PublisherOA PDFDOI

Frequent coauthors

• David M. Lodge

  Atkins (United States)

  45 shared

• Andrew R. Mahon

  Central Michigan University

  38 shared

• Brett P. Olds

  Hawaii Pacific University

  20 shared

• W. Lindsay Chadderton

  The Nature Conservancy

  20 shared

• Matthew A. Barnes

  Texas Tech University

  19 shared

• Marion E. Wittmann

  University of California, Santa Barbara

  18 shared

• Mark A. Renshaw

  Cherokee Nation

  13 shared

• Kristy Deiner

  ETH Zurich

  13 shared

Labs

• UC Santa Barbara - Bren School of Environmental Science & ManagementPI

Education

• Environmental Biology and Ecology, Biological Sciences

  University of Alberta

  2008

• Ecology, Ecology

  Montana State University Bozeman

  2002

• B.Sc Biological Science, Biological Sciences

  Montana State University Bozeman

  1998