Confident and wise decision-making is possible even under conditions of
conflicting values, shifting conditions, and high uncertainty.
At KDV, we help clients improve the efficiency and effectiveness of decisions that depend on multifaceted and complex data. Drawing from our diverse background in natural sciences, social sciences, and emerging data sciences, we bring proven experience, unique insights and passion to our projects. We help organizations identify decision objectives and evaluate alternatives given the uncertainty and complexity of the decisions' context (e.g., fiscal realities, social values, legal requirements, etc). To accomplish these tasks, we offer services to gather and analyze data from databases, expert elicitations, personal narratives, and community workshops. Final products include data driven apps, interactive visualizations, and web-based decision support tools.  For more information, including DUNS, CAGE, and NAICS codes, see our Capability Statement.  

Core Competencies

Environmental Modelling
  • Machine-learning, statistical, and expert-knowledge approaches to modeling
  • Wetland delineation and classification models
  • Species habitat modeling for rare and common species
  • Water resource quality and use models

Adaptive Management
  • Workshop facilitation to define vision, scope, and objectives
  • Transparent decision prioritization and optimization
  • Strategic solutions at the programmatic and project levels
  • Metrics to monitor for thresholds, tipping points, and weak signals
  • Threat assessment and modeling (e.g., climate change, invasive species, and urbanization)

Information Services
  • Expert knowledge elicitation, analysis, and application
  • Elicitation and analysis of stakeholder and organizational values, beliefs, and motivations
  • Literature review and meta-analysis
  • Natural and social science data collection, management, analysis, and reporting

Decision Modeling
  • Use of Bayesian and frequentist statistics to model ecological systems and simulate decision outcomes
  • Creation of web-based graphic user interfaces for decision models
  • Tactical strategies to maximize likelihood of adaptive learning
  • Uncertainty and risk assessment with scenario analysis

C. Ashton Drew, PhD
Owner, Lead Scientist and Data Analyst

Ashton has over 30 years research and consulting experience at the intersection of science, social values, and organizational development.  As a researcher at North Carolina State University, she managed and collaborated on diverse multi-investigator, multi-year projects serving the USGS, USFWS Raleigh Ecological Services Field Office, USFWS Caribbean Ecological Services Field Office, NC Wildlife Resources Commission, Biofuels Center for NC, The Nature Conservancy, and Keystone Institute Field-to-Market program.  As a consultant, she has served the NC Department of Transportation, the Yukon Land Use Planning Council, Environment Yukon, and the US Fish and Wildlife Service, among others.  She has co-edited two textbooks and authored multiple papers on topics of landscape ecology, conservation planning, expert knowledge elicitation, and inquiry-guided teaching. For more information, see Ashton's resume or curriculum vitae.

Will Saulnier, MSc
Senior Data Analyst and Software Engineer

Will is an experienced and innovative leader in data science with a proven track record of driving strategic initiatives, building high-performing teams, and leveraging data-driven insights to achieve organizational goals. He specializes in machine learning, geospatial analysis, web application development, and remote sensing. Since 2022, Will has utilized his highly specialized skillset to assist in developing a cutting-edge machine learning framework for a wetland prediction model for the North Carolina Department of Transportation. For more information, see Will's resume.

Eliot Dixon
Data Analyst and Software Engineer

Eliot has experience in data analysis, systems administration, and application development.  While completing an undergraduate degree at UNC Asheville, he participated in several software development projects, gaining experience across multiple platforms and languages.  His focus on these projects has been applied conservation and environmental science.  At KDV, he has led development of Shiny applications to visualize team dynamics within organizations (for client Team Elements) and to document ecological insights from ecological data (for client Michael Baker).  A gifted communicator, he also contributes to our R instructional materials and serves as teaching assistant. He is often one of the lead developers when projects require knowledge of MongoDB, PostgreSQL, R, or Shiny.  For more information, see Eliot's resume.

Nicholas Post
Data Analyst and Software Engineer

Nicholas brings a unique blend of experience in web development and biological anthropology.  This combination of expertise in data communication and analytics fits our projects well.  At KDV, he has contributed to projects on 3D morphometric analyses for forensic research and redevelopment of an application that constructs and analyzes paleoecological food web structures.  Nick's knowledge of statistics also enables him to support our large data projects that use linear and non-linear regression techniques, important techniques for our bat habitat projects. For more information, see Nick's resume.