P25412_ODOT_Degradation_Analysis.pdf

P25412

TECHNICAL PROPOSAL:

OHIO DEPARTMENT OF TRANSPORTATION

PAVEMENT MARKING DEGRADATION DATA ANALYSIS

Solicitation No. 536-26

30 September 2025

Prepared for:

Ohio Department of Transportation

1980 West Broad Street, Columbus, OH 43223

Prepared by:

Environmental Solutions & Innovations, Inc.

ODOT Pavement Marking Degradation Analysis i

TABLE OF CONTENTS

Page

1.0 Introduction / Project Understanding

2.0 Technical Approach

3.0 Organizational Experience and Capabilities

3.1 Analytical Experience

3.2 Topical Experience

3.3 Data Visualization and Communication with Stakeholders

4.0 Staff Experience and Capabilities

5.0 Timeline

6.0 Contacts at ESI

Copyright ©2025 by Environmental Solutions & Innovations, Inc.

1.0 Introduction / Project Understanding

Environmental Solutions & Innovations, Inc. (ESI) understands the Ohio Department of Transportation (ODOT) seeks analytical assistance in quantifying the rate of pavement marker degradation across the State. Retroreflective pavement markers degrade over time as reflective materials wear off markers or markers become covered in road debris or damaged by maintenance equipment. The result is decreased effectiveness of markers over time, thereby increasing risk to vehicle operators and occupants, and to pedestrians near roadways.

ODOT has an existing dataset of retroreflectivity measurements repeated 5 times at each of 118 sites using standard 30-meter geometry. These data will be used to complete the Service Life Based on Historical Data analysis as detailed in the Methods for Maintaining Pavement Marking Retroreflectivity (FHWA-SA-22-028; 2022). To accomplish that goal, ODOT requests a series of at least four analyses using appropriate statistical and machine learning techniques.

This document is organized to address the criteria identified in the RFP. Section 2.0 provides credentials and background information on the proposed ESI project team members and their relevant experience. Section 4.0 identifies eight potential families of models that could (depending on quantity and quality of data) be used to complete the required analyses (final determination of the applicable analytical methods will be made after a meeting with ODOT); Section 5.0 provides information on ESI’s specific, relevant project experience.

2.0 Technical Approach

ESI proposes a series of at least four complementary analytical approaches to quantify the rate of pavement marker degradation across time and conditions with the goal of estimating service lives of markers. Exact analytical approaches are highly dependent on data availability and quality, completeness, and distributions of the data. ESI first evaluates the existing dataset to determine what analytical approaches are feasible and most likely to achieve goals of the study. The project team then meets with relevant personnel from ODOT to discuss options and chart a path forward on analyses.

Potential statistical methods relevant to quantifying degradation of retroreflectivity include non-linear and/or mixed effects regression, curve fitting, and Monte Carlo simulations, among others. Potential machine learning models relevant to quantifying degradation include gradient boosting models, random forests, variance partitioning, and principal components analyses. Hybrid options like supervised learning of curve fitting might also prove valuable, depending on variability captured within ODOT data.

ESI has experience applying each of these analytical approaches.

ESI completes analyses using at least two statistical approaches and two machine learning approaches. All analytical approaches, whether statistical or machine learning, fall along a continuum from descriptive to predictive. Highly descriptive analyses “fit the model to the data” with the goal of fully capturing variation in the available dataset.

Predictive analyses “fit the data to the model” with the goal of capturing larger patterns in degradation of retroreflectivity. Each has distinct advantages and disadvantages.

Descriptive analyses are valuable for quantifying degradation of retroreflectivity under the range of conditions captured by the dataset but are less useful in predicting degradation under other conditions found across the State. Conversely, predictive analyses are less useful for quantifying the available dataset but are more useful for inferring degradation under conditions potentially common across the State but not explicitly included in the dataset.

ESI has the experience and expertise to not only conduct the four analyses ODOT requires, but to also balance descriptive and predictive modeling in the four approaches used to maximize the understanding of marker degradation over time in Ohio. By combining complementary approaches instead of using four independent approaches, ESI creates a prescriptive and practical maintenance schedule that ensures pavement markers exceed regulatory standards for retroreflectivity without excessive waste in cost and effort by ODOT. ESI completes all analyses in the open-source programming language R, allowing for easy reanalysis or modification as future data are collected. To facilitate future analyses, ESI provides all R-scripts used to generate final analyses.

Included with scripts are notes and other descriptive material intended to explain the process.

3.0 Organizational Experience and Capabilities

ESI was founded as an environmental firm, but its expertise and scope have expanded considerably in recent years to include substantial forays into data sciences and engineering, among others.

3.1 Analytical Experience

ESI has vast expertise in statistical and machine learning methods relevant to degradation of retroreflectivity of pavement markers (Table 1) and its documented history of analytical excellence far outpaces that typical of consulting firms. Collectively, ESI’s scientists have taught Ph.D.-level statistics courses at universities, provided statistical consultation to scientists and graduate students, conducted statistical analyses for local, state, and federal agencies, and created custom analytical metrics to address complex questions. ESI’s scientists have expertise in both frequentist and Bayesian statistical paradigms, with relevant experience in reliability (survival) analysis, data resampling techniques (e.g., Monte Carlo, Markov chain, bootstrapping), probabilistic and simulation modeling, curve fitting, and regression analysis.

ESI’s scientists also have a long history of using machine learning models in both research and regulatory arenas. That experience has been documented in numerous peer-reviewed papers in top international scientific journals and countless regulatory documents. Relevant experience includes random forests, gradient boosting machines, cluster analysis, and supervised and unsupervised learning.

3.2 Topical Experience

ESI has worked extensively in the built environment, including transportation infrastructure and light reflectivity (Table 1). ESI has experience analyzing behavior of light, including reflected light, in the environment. Unlike most consulting firms, this experience goes beyond use of commercial software and has resulted in creation of custom modeling scripts to address unique questions of light reach into the environment. This work included consideration of light reach (and reflection) into the environment from vehicle headlights and road lighting.

ESI frequently works with Departments of Transportation, including ODOT. Most recently, ESI led a project that provided ODOT with information about the relative value to bats of more than 20,000 bridges throughout the State. ESI’s analysis included formal statistical analyses and associated reporting (https://rosap.ntl.bts.gov/view/dot/59870.)

but also provided ODOT with a “step-down” analysis that helped summarize results for non-statisticians in a user-friendly format.

3.3 Data Visualization and Communication with Stakeholders

ESI prides itself on timely and accurate written communication products that range from public education to highly technical scientific documents and aesthetically pleasing and informative data visualization products to communicate important findings in easily digestible formats. Examples of proposed project Key Staff prior experience are contained in Table 1.

https://rosap.ntl.bts.gov/view/dot/59870

Table 1. Example Projects Demonstrating Experience Relevant to Degradation Analysis

Project Description

Cleaning and Analysis of Time Data

Relevant Statistical

Models

Relevant Machine Learning Visualization and Communications

Light reflectivity in the environment

Project created custom computer scripts to model throw of artificial light at night, including reflectivity, into the environment. Results are currently being analyzed for a peer-reviewed publication.

Physical modeling of light throw

Canal System Thermal Hydraulic Machine Model

Project developed and calibrated a thermal hydraulic model of a closed canal system to determine the effects of canal closure alternative scenarios on thermal distributions and algae growth.

Change in winter length over 120+ years in the NE United States

Project involved conceptualizing and writing custom scripts to download, clean, collate, and analyze large weather datasets containing daily temperature and precipitation data from over 500 weather stations, going back to

1900. The result was submitted as a peer-reviewed publication in an international scientific journal.

Regression and curve fitting

Evaluation of meteorology and climate to explain changes in population abundance

Project used machine learning models and frequentist statistics to determine how populations changed with weather and climate factors. The result was published as a peer-reviewed publication in an international scientific journal.

fitting, variance partitioning

Random forests

Ecological niche modeling and species distribution modeling

Numerous projects used hybrid statistical and machine-learning algorithms to evaluate importance of biotic and abiotic factors in predicting species distributions.

Results of this work have been communicated in agency reports, multi-decade conservation plans, and peer-reviewed publications.

Gradient boosting machines, principal components analysis

Hydraulic Rainfall Modeling

Project developed rainfall runoff models based on surveyed site data and statistical evaluation of local rainfall historical data to determine low-probability rainfall depths.

Forestry Habitat Conservation Plans

Developed models to predict long-term changes in habitat quality for bats based on forestry practices including complete and partial harvest, thinning, and prescribed fire.

Habitat suitability modeling

Predicting future infrastructure projects

Project involved creation of models to predict areas where electric infrastructure would be built across multiple states during the next 30 years. Scores were displayed as “heat maps” which played a crucial role in helping utility and agency staff understand the analysis.

Remote Sensing Shoreline Response Modeling

Project evaluated surveyed shoreline data, observed offshore wave characteristics and remote sensing imagery to model shoreline response to varying wave climates and tidal forcing.

Survival (aka reliability) of populations over time

Projects estimated survival (directly analogous to degradation statistically and conceptually) of organisms exposed to various conditions. Results have been published in several peer-reviewed publications.

Survival

(reliability) analysis

Growth analysis over time

Project used curve fitting to describe growth under various conditions. The result was published as a peer-reviewed publication in an international scientific journal.

Growth curves

Supervised learning algorithms

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4.0 Staff Experience and Capabilities

Unusual among consulting firms, ESI has a dedicated research group staffed by PhD-level professionals with exceptional skills in data analytics, statistics, management of complex data, simulation modeling, and computer programming. These individuals are all well-versed in all aspects of data management, analysis, and visualization necessary to complete the tasks required by ODOT. Several of ESI’s most senior staff will be involved with the project, collectively bringing more than 50 years of data analysis expertise to bear. Brief summaries for Key staff are identified below; resumes providing detailed relevant experience are available in Appendix 1.:

Dr. Shaun Kline is a licensed Professional Engineer with nearly 20 years of professional experience and serves as Project Manager for this effort. Dr. Kline has extensive experience with Hydrologic and Hydraulic (H&H) modeling associated with flooding, coastal storm surge, wave effects, probable maximum flooding for riverine environments, dam break inundation, local intense precipitation runoff, regional site-specific meteorology, sea level rise. Dr. Kline’s data modeling experience also includes geomorphology and sediment transport models to predict wave energy dissipation, shoreline response and statistical geo-analysis. Dr. Kline’s has worked in a variety of statistical modeling environments including MATLAB, R, FLO-2D Pro, Delft3D, HEC- RAS, HEC-HMS, and FLOW3D. Dr. Kline’s role in the project is to serve as the liaison between the Department of Transportation and ESI, budgeting, resource allocation, and provide overall guidance and quality assurance. Time allocation: 35% project management; 25% data analysis; 40% report preparation.

Dr. Justin Boyles serves as Project Principal on the project, bringing years of cutting-edge research experience to the team. Before moving to ESI, Dr. Boyles spent 16 years in academia and has published over 90 peer-reviewed papers in leading scientific journals. Dr. Boyles possesses extensive expertise in modeling, complex analyses, handling “messy” data, and simulation modeling including frequentist and Bayesian statistics, multivariate statistics, structural equation modeling, agent-based modeling, dynamic and simulation modeling, among others. He has worked in statistical and mathematical environments including R, Python, MATLAB, Mathematica, SAS, and many project-specific programs. He has taught graduate-level statistics courses and published papers on statistical techniques, including creation of new analytical methods.

Time allocation: 10% project management; 50% data analysis; 10% data visualization;

30% report preparation.

Dr. Benjamin Merritt serves as Senior Data Analyst on the project, balancing the understanding and needs of personnel using results of the analysis with the limits and advantages of different analytic techniques. Dr. Merritt has worked extensively with

P25412 10 departments of transportation (DOTs) staff to craft complicated planning documents that require meeting needs of DOT objectives with engineers and state and federal agencies. He conducts and/or oversees many of the statistical analyses completed at ESI, ranging from large, landscape-scale conservation planning data analyses and species distribution modeling projects requiring the use of machine learning, to smaller evaluations of data collection techniques and ecology-based studies. Dr. Merritt also takes pride in developing dashboards and visualizations valuable to convey complex ideas and findings. Time allocation: 50% data analysis; 20% data visualization; 30% report preparation.

Dr. Dale Sparks serves as Project Advisor on the project, bringing over 30 years of experience working on transportation-related projects across North America. This experience ranges from building and maintaining transportation infrastructure to decades spent analyzing interactions between transportation infrastructure and the surrounding landscape. This lived experience makes Dr. Sparks especially effective at communicating science to practitioners. For this project he helps ensure models contain input from technical staff who have day-to-day experience with how reflectivity degrades over time and also ensures model output is distilled into actionable information for these same staff. Time allocation: 15% project management; 10% data analysis; 75% report preparation.

5.0 Timeline

ESI proposes a kick-off meeting with relevant ODOT staff shortly after the project is awarded to discuss specifics of data collection, data formats, and any modifications to the stated goals of the project. ESI begins cleaning and collating data in appropriate formats for analysis and conducting analyses based on this meeting, with as-needed check-ins, per ODOT’s preference. A draft report is submitted by 2 March 2026 and based on revisions and recommendations from ODOT, a final report is submitted by 3 April 2026.

P25412 11

6.0 Contacts at ESI

ESI appreciates the opportunity to propose on this project. Please do not hesitate to contact us if you have any questions. All communications should be directed to:

Dr. Shaun Kline, P.E., Project Manager Phone: 352-514-3340 Email: skline@envsi.com

Or, Dr. Justin Boyles, Principal Scientist Phone: 618-201-2770 Email: jboyles@envsi.com mailto:skline@envsi.com mailto:jboyles@envsi.com

APPENDIX 1

STAFF RESUMES

Shaun Kline, Ph.D., P.E.

Project Manager

Dr. Shaun Kline, P.E. 1

Real Science, Real Solutions

EDUCATION

Ph.D., Geological Sciences, University of Florida, 2013

M.S., Coastal & Oceanographic Engineering, University of Florida, 2009

B.S., Civil Engineering, University of Florida, 2006

PROFESSIONAL

CERTIFICATIONS

Professional Engineer (P.E.)

• Colorado (PE.0055749)

• Florida (82676)

• Maine (PE15736)

• Nebraska (E-18146)

• Nevada (27248)

• North Carolina (044918)

• Ohio (PE.84364)

• Oklahoma (31920)

• Oregon (95782PE)

• Pennsylvania (PE085658)

• Texas (134074)

• Virginia (402061678)

• West Virginia (23986)

NCEES Model Law Engineer (Record ID 17-130-48)

PEC/SafeLand Certification

(PEC100690267)

QUALIFICATIONS AND EXPERIENCE

Dr. Kline is a civil/environmental engineer and earth scientist with over 19 years of experience in applied water resources and civil engineering. His project experience spans multiple disciplines across multiple industries.

Dr. Kline has unique, specialized, quantitative modeling experience in several areas:

• 316a and 316b: Thermal hydraulic evaluations; computational fluid dynamics (CFD); field instrument deployment strategy;

instrumentation data post-processing; engineering cost estimates;

engineering construction schedules; environmental reports; and regulatory presentations.

• Hydrologic & Hydraulic (H&H) Assessments: External flooding;

internal flooding; coastal storm surge; wave effects (wave runup and wave overtopping); seiche; tsunami; riverine flooding (probable maximum flood); dam break inundation; local intense precipitation runoff; regional site-specific meteorology; sea level rise; sedimentation (erosion/deposition); hydrostatic / hydrodynamic loading; projectile/debris strikes; shore/channel protection; third-party independent reviews; report development;

and subject matter expertise in regulatory inspections/reviews.

• Geomorphology and Sediment Transport: Numerical modeling;

wave energy dissipation; shoreline response; field and remote sensing instrumentation deployment/collection; data post-processing; statistical geo-analysis; sea cliff retreat; sea level rise effects; riverine sediment transport.

• Water Quality: nutrient loading quantification; algae biomass predictors; waste load allocation studies (WLAS).

Dr. Kline is well versed in federal and state regulatory review processes, inspections, and audits, serving as subject matter expert and client representative.

EXAMPLE PROJECTS

Williams, Southeast Supply Enhancement Virginia and North Carolina Senior Engineer

Development oversight of a RUSLE/RUSLE2 sedimentation model for proposed pipeline expansion. Project includes dynamic incorporation of proposed erosion and sediment controls to minimize anticipated sedimentation effects in streams and coordinating with sediment transport experts to determine potential impacts on stream habitat.

MVP, Mountain Valley Pipeline West Virginia and Virginia Senior Engineer

Sedimentation modeling using Revised Updated Soil Loss Equation 2 (RUSLE2) methodology for a proposed 303-mile pipeline. Developed a simplified sediment transport model to predict anticipated excess deposition patterns respective of streambed embeddedness changes and

Dr. Shaun Kline, P.E. 2 habitat impacts. Incorporated existing (“as-built”) erosion and sediment control features and other maintenance strategies.

NextEra Energy Resources, Turkey Point Florida Lead Responsible Engineer

Evaluated effects of sea level rise on the PTN closed cooling canal (CCS) system, including increased risk of perimeter berm overtopping during high tides and hurricanes; groundwater gradient changes; and increased extreme rainfall. Authored report that provided maps of highest vulnerable areas as well as recommendations for future countermeasures.

Dominion Energy Virginia, Chesterfield Power Station Virginia Lead Responsible Engineer

Directed 316a demonstration update at SPS for submittal to Virginia Department of Environmental Quality (VDEQ). Work scope included field monitoring program, bathymetry collection, and development/calibration of hydrothermal model.

Exelon, Calvert Cliffs Nuclear Power Plant Maryland Lead Responsible Engineer

Performed 316b hydraulic evaluation (with CFD software) at CCNPP to determine flow patterns adjacent and under baffle wall near intake structure. Different configurations of the baffle wall at both high and low tide flow regimes were considered. Created a particle tracking methodology to better assess flow contributions throughout water column.

Confidential Client, Confidential Project New Hampshire Lead Responsible Engineer

Thermal hydraulic evaluation (with CFD software) to determine general shape and extent the discharge plume under low flow river conditions and varying meteorological conditions. Evaluated historical plant and river data to characterize plume impacts under a range of flow regimes and operational configurations.

Entergy, Palisades Power Plant Michigan Project Engineer

Authored (r)(2) and (r)(8) reports for source water physical data and operational status, respectively, in support of the facility’s 316b evaluation.

Ascend Performance Materials, Decatur Plant Alabama Project Manager

Managed cogeneration feasibility assessment which included conceptual design of recommended cogeneration solution with preliminary capital budget and implementation construction schedule.

NextEra Energy Resources, Seabrook Station Nuclear Power Plant New Hampshire Lead Responsible Engineer

Evaluated current design basis (CDB) and beyond design basis (BDB) for storm surge overtopping and local intense precipitation (four total assessments).

Electric Power Research Institute California Subject Matter Expert

Quarterly subject matter expert reviews of current literature, databases and regulatory guidance related to external flooding at U.S. power plant facilities. Specific focus areas included storm surge, tsunami, extreme rainfall, riverine flooding, dam breaks and ice jams.

Justin G. Boyles, Ph.D.

Project Principal

4525 Este Avenue Cincinnati, OH 45232

513-451-1777

Dr. Justin G. Boyles 1

EXPERIENCE

Principal Scientist, ESI 2025- Present

Associate Professor, School of Biological Sciences, Southern Illinois University, 2012-2025

Post-Doctoral Research Fellow, University of Tennessee, 2011-2012

Post-Doctoral Research Fellow, University of Pretoria, South Africa, 2009-2011

EDUCATION

Ph.D., Biology, Indiana State University, 2009

M.S., Biology, Missouri State University, 2004

B.S., Ecology, Evolution and Systematics, Missouri State University, 2002

Dr. Boyles joins ESI after a 13-year career in academia as a professor at Southern Illinois University. His research focuses on anthropogenic changes in the landscape including light pollution, noise pollution, and the built environment. His analytical experience includes simulation modeling, complex analyses, and “messy” data, among others. At ESI, he applies cutting-edge research and technical skills common at universities to address real world issues at both small and large scales.

ANALYTICAL EXPERIENCE AND TRAINING

Class: Philosophy of science, statistics, and publishing Southern Illinois University Professor

Designed and presented a Ph.D.-level course on epistemology (ways of knowing) and the “philosophy” of statistics. Course was taught four times over eight years. Topics included study of different methods of obtaining knowledge, applying appropriate statistics to address questions of interest, and using statistics and writing to tell a compelling scientific “story”.

Class: Calling shenanigans in science, publishing, and the media Southern Illinois University Professor

Designed and presented an undergraduate course on understanding and spotting deceptive practices in scientific writing and the popular media.

Topics included distinguishing between good and deceptive writing, preparing informative and accurate infographics, and evaluating deception in speech and writing.

Statistical Teaching and Advising South Africa, Tennessee, and Illinois Professor

Taught introductory statistics for first-year graduate students and provided statistical advice and assistance to more than two dozen graduate students across three universities in South Africa and the United States.

Light Reach into the Environment Global Principal Investigator

Modelled the throw of artificial light at night into the environment, focusing on relevant light sources (e.g., road lights, house lights, vehicle headlamps), accounting for the intensity and number of lights, lighting angles, and lighting design. Included analysis of reflected light into the environment from shielded and directional lights.

Dr. Justin G. Boyles 2

Relevant Coursework Multiple

More than 30 credit hours of statistical coursework across multiple universities including: Advanced Probability, Regression Analysis I and II, Non-parametric Statistics, Messy Data Analysis, Multivariate Statistics, Structural Equation Modeling, and Simulation Modeling, among others.

Cave Environments and Microclimate Indiana Data Analyst

Conducted analysis of physical properties of caves for Indiana Department of Natural Resources using previously collected data. Project required conceptualization and writing of custom analytical scripts to clean data, conduct analyses, and create visual outputs for reports and publications.

Selected Publications (Statistics based)

Boyles, J. G. 2019. A brief introduction to methods for describing body temperature in endotherms.

Physiological and Biochemical Zoology. 92: 365-372.

Koen, E. L, C. Minnaar, C. L. Roever, and J. G. Boyles. 2018. Emerging threat of the 21st century lightscape to global biodiversity. Global Change Biology. 24: 2315-2324.

Neiles, B., C. S. Carey, A. Araujo, D. Burkhart, L. J. Kirschman, B. LaBumbard, S. LaGrange, J. J. Maine, A. M. Rombenso, M. N. Wood, and J. G. Boyles. 2015. Writing your way into high impact factor journals. ESA Bulletin. 96: 312-316.

Boyles, J. G. and R. W. Warne. 2013. A novel framework for predicting use of facultative heterothermy by endotherms. Journal of Theoretical Biology. 336: 242-245.

Boyles, J. G., C. L. Sole, P. M. Cryan, and G. F. McCracken. 2013. On estimating the economic value of insectivorous bats: A prospectus for researchers. Chapter 24 In: Bat Evolution, Ecology and Conservation. Adams, R. A. and S. C. Pedersen, eds. Springer Science Press, New York.

Boyles, J. G., B. Smit, and A. E. McKechnie. 2011. A new comparative metric for estimating heterothermy in endotherms. Physiological and Biochemical Zoology. 84: 115-123.

Boyles, J. G., D. A. Aubrey, B. S. Cooper, J. G. Cox, D. R. Coyle, J. D. Hoffman, R. J. Fisher, and J. J. Storm. 2008. Statistical confusion among graduate students: sickness or symptom? Journal of Wildlife Management. 72: 1869-1871.

Benjamin J. Merritt, Ph.D.

Senior Data Analyst

4525 Este Avenue

Dr. Benjamin J. Merritt 1

Ph.D., Biological Sciences, University of Cincinnati, 2021

B.S., Environmental Science, University of Cincinnati, 2013

PROFESSIONAL

AFFILIATIONS

Member, Botanical Society of America

Member, Ecological Society of America

Dr. Merritt is an ecologist with expertise in statistical tools to assess how species interact with their environments. His technical expertise ranges from characterizing genetic variation within individuals to assessing the role of species-specific environmental niches in taxonomic classification of species complexes. His work with a wide breadth of techniques is founded in both field- and computationally based scientific studies gained while working in an academic setting and with local interest groups, including conservation and land management organizations.

Dr. Merritt’s geospatial and statistical prowess has led to management of multiple large-scale habitat conservation plans, fostering collaborative relationships between agencies and private stakeholders to arrive at solutions amenable to all parties: balancing the needs of various energy transmission utilities with species conservation.

PROJECTS

American Electric Power, Multi-state, Multi-species Habitat Conservation Plan (HCP) 11 States (AR, IN, KY, LA, MI, OH, OK, TN, TX, VA, WV) Project Manager

The nation’s largest multi-species HCP addressing the conservation needs of over 300 threatened and endangered species associated with over 40,000 miles of right-of-way and 188 million acres of land. Providing data management, data analysis, and editorial and technical review.

Northeast Utility Working Group, Multi-state Bat Habitat Conservation Plan (HCP) 7 States (CT, MA, ME, NH, NY, RI, VT) Project Manager

A low effects HCP addressing operations and maintenance activities for electrical, telecommunications, and gas infrastructure across over 1.5 million acres of Rights-of-Way owned by eight utilities across seven states in the northeastern U.S. Oversaw development of the HCP, conducted the take analysis, and led coordination between utilities and federal agencies.

Great Lakes Restoration Initiative (GLRI), Rusty Patched Bumble Bee Predictive Modeling 8 States (IN, IL, OH, MI, MN, NY, PA, WI) Lead Statistical Analyst

Developed species distribution models to predict rusty patched bumble bee (Bombus affinis) throughout the Great Lakes Region using historical and current occurrence data and landscape

U.S. Fish and Wildlife Service, Deep Fork National Wildlife Refuge Oklahoma Lead Statistical Analyst

Study to determine summer use of the proposed endangered tricolored bat (Perimyotis subflavus). Conducted foraging probability analysis using radio telemetry data to determine landscape composition contributing to species use of the colony under study.

Dr. Benjamin J. Merritt 2

U.S. Forest Service, National Forests and Grasslands in Texas, Davy Crocket National Forest, Beaver Creek Wildlife Improvement and Ecosystem Enhancement Texas Scientist

Technical assistance for preparation of an Environmental Assessment designed to improve red-cockaded woodpecker (Picoides borealis) populations. Analysis considered environmental effects of pine thinning, midstory removal, and other forest health activities across over 10,800 acres of the National Forest.

U.S. Forest Service, Ozark Big-eared Bat Foraging Study Arkansas Lead Statistical Analyst

Led statistical analysis of a two-year study to evaluate effects of forest management techniques on foraging of the Ozark big-eared bat (Corynorhinus. t. ingens) Bliss Ridge maternity colony in the Ozark- St. Francis National Forest in Arkansas. Contextualized how prescribed fire, selection cutting, and other vegetation management led to increased foraging use by individuals.

Confidential Client, Modeling Mortality Risk to Eagles Minnesota Statistics Analyst

Take assessment for golden (Aquila chrysaetos) and bald (Haliaeetus leucocephalus) eagles at a proposed wind energy site in Dodge and Steele counties. Employed U.S. Fish and Wildlife Service (USFWS) Eagle Fatality Model to provide analysis.

Lake States Forest Management HCP Michigan, Minnesota, and Wisconsin Biologist

HCP designed to allow forest management in the presence of four bat species impacted by White Nose Syndrome. Provided technical assistance on modeling and document preparation.

National Cooperative Highway Research Program, Artificial Bat Roost Mitigation Designs and Standardized Monitoring Criteria Nationwide Technical Editor

Meta-analysis of published and unpublished records of bats using artificial roosts including bridges, culverts, and stand-alone artificial roosts. Assisted with best design practices manual and revisions.

U.S. Fish and Wildlife Service, Northeast National Wildlife Refuge Northeast US Technical Writer

Technical report preparation for habitat assessments and inventories of bumble bees. Report documentation included details on current status and management recommendation to conserve and enhance identified habitat to better support bees and other pollinators at five National Wildlife Refuges in the Northeast Region.

SELECTED PUBLICATIONS

Brack, V., D. Brack, B. Merritt, and J. G. Boyles. 2025. Intra- and inter-cave temperatures and locations used by hibernating Indiana bats: contextualizing disturbance, White-nose Syndrome, climate, and optimal temperatures. Canadian Journal of Zoology 103: 1-15.

Culley, T. M., M. Philpott, R. Tunison, B. J. Merritt, J. M. Barreiro Sanchez, A. Wafer, and R. Holdren.

2021. Research inequity in the plant sciences. Applications in Plant Sciences 9: e11417.

Merritt, B. J. and S. F. Matter. In Prep. Whether climate or weather can do it better: Modeling population growth using meteorology and a climate index for the lanceleaf stonecrop, Sedum lanceolatum.

Merritt, B. J., S. Yadav, T. Whitsell, S. Kephart, and T. M. Culley. In Prep. Can we be defined by our niche? Using ecological niche models to differentiate taxa. In review with Ecology and Evolution.

Dale W. Sparks, Ph.D.

Project Advisor

4525 Este Avenue

Dr. Dale W. Sparks 1

Ph.D., Biology, Indiana State University, 2003

M.S., Biology, Fort Hays State University, 1996

B.S., Biology, Murray State University, 1993

PROFESSIONAL

CERTIFICATIONS

Certified Wildlife Biologist: The Wildlife Society

Certified Senior Ecologist:

Ecological Society of America

Qualified Bat Surveyor:

Commonwealth of Pennsylvania

Federal Native Endangered & Threatened Species Recovery Permit No. ES02373A-17

SPECIALIZED TRAINING

Indiana Department of Natural Resources, 2009, Wildland Fire Fighting and Prescribed Fire Application

USFWS Structured Decision Making, 2008, National Conservation Training Center.

PROFESSIONAL

AFFILIATIONS

American Society of Mammalogists

The Wildlife Society

Society for Conservation Biology, 1996-2006

Dr. Sparks is ESI’s Principal Scientist Project with 35 years of experience researching wildlife at the urban-rural interface. He is involved in a variety of terrestrial ecology research positions involving herpetology, ornithology, and mammalogy; and has extensively studied bats and their habitat. He is a recognized authority on the biology of bats and well-versed in interactions between multiple and intertwining levels of compliance and how the regulations fit under the NEPA umbrella. He directed long term studies in support of a Biological Assessment (BA) and Habitat Conservation Plan (HCP) associated with developments at the Indianapolis International Airport and the nearby Six Points highway project, respectively.

In many respects, Dr. Sparks bridges the gap between more traditional wildlife biologists and ecological modelers. He champions the use of mathematical techniques to develop distribution models that assess the number of bats likely to occur in a given area, and thus, with other data, a way to extrapolate impacts at three regulatory scales (direct, indirect, and cumulative). His modeling is the primary source for the three permitted Bats and Forestry HCPs in the range of Indiana bats that provide coverage for forestry and habitat management (including prescribed fire) on land across Michigan, Missouri, Minnesota, Pennsylvania, and Wisconsin.

PROJECTS

Seasonal Use of Ohio Department of Transportation (ODOT) Bridges Ohio Principal Investigator

Comprehensive review of bats using bridges in both Ohio and nationwide.

Using these data, developed a model that ranked ODOT bridges from most to least likely to support bats. Designed a field study to determine effectiveness of the model by sampling 504 bridges throughout Ohio.

Results of the field study were then used to refine the model and provide ODOT with a quantitative and spatially explicit ranking of ODOT’s more than 20,000 bridges. A simplified tool was also developed to help bridge inspectors understand those factors most associated with use of bridges by bats. Report available at https://rosap.ntl.bts.gov/view/dot/59870.

American Electric Power Multi-state Multi-species HCP 11 States including Ohio Technical Lead, Protected Species

HCP designed to allow electrical utility to meet ESA compliance for multiple species for new construction and line rebuild activities.

Responsible for developing take estimates and mitigation planning for covered species.

Mid-States Corridor Project Indiana Project Manager

Provided support for Tier 1 EIS and expected Biological Assessment.

https://rosap.ntl.bts.gov/view/dot/59870

Dr. Dale W. Sparks 2

Sunday River Mitigation Site Ohio Lead Technical Scientist

Evaluation of potential of existing stream mitigation site to provide suitable mitigation for the endangered Indiana bat. Provided analysis of best available science which included confidential distributional data maintained by the U.S. Forest Service and the Ohio Department of Natural Resources, publicly available mine maps, field surveys to locate and observe bat activity at mine openings, as well as evaluation of extensive acoustic monitoring.

National Cooperative Highway Research Panel 25-63 Ohio, California, and Florida Principal Investigator

Handbook on deterring and excluding bats from transportation structures: Led development of in-field experiments comparing and contrasting the use of physical barriers to exclude bats from bridges to the use of acoustic devices deterring bats from using bridges.

National Cooperative Highway Research Panel 25-25 Artificial Bat Roost Mitigation Designs and Standardized Monitoring Criteria Nationwide Lead Technical Scientist

Handbook on deterring and excluding bats from transportation structures: Led development of in-field National Cooperative Highway Research Panel 25-25, Task 102, Artificial Bat Roost Mitigation Designs and Standardized Monitoring Criteria: 2018-2019. Completed meta-analysis of published and unpublished records of bats using artificial roosts including bridges, culverts, and stand-along artificial roosts (like bat boxes). Results provide new insight into the techniques to develop successful mitigation efforts aimed at bats (https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4098).

Lake States Forest Management HCP Michigan, Minnesota, and Wisconsin Lead Technical Scientist

HCP designed to allow forest management (including prescribed fire) in the presence of four bat species impacted by White Nose Syndrome. Responsible for developing landscape-level models to determine how these species are impacted by forest management practices

Missouri Department of Conservation Bats and Habitat Management HCP Missouri Lead Technical Scientist

Identified and quantified projected management activities including prescribed fire and timber harvest over the next 30 years that might impact five species of bats and developed distribution models to assess number of bats likely to occur in an area and a way to extrapolate impacts on three regulatory scales -direct, indirect, and cumulative.

Northeast Utility Working Group, Multi-State, Multi-Species HCP 7 States (CT, MA, ME, NH, NY, RI, VT) Project Principal

Low effects HCP addressing operations and maintenance activities for electrical, telecommunications, and gas infrastructure across 1.5 million acres of rights-of-way owned by eight utilities across northeastern states. Goal is to develop a fifteen-year low effects HCP to provide utilities coverage for bats under and proposed for federal protection.

Midwest Energy HCP EIS 8 States (IL, IN, IA, MI, MN, MO, OH, WI) Project Manager

Evaluated potential impacts of developing more than 51,000 megawatts of wind energy across an eight-state region on three species of bats covered by the HCP, as well as all other bats in the region.

Evaluation included development of models to estimate mortality of bats that were used to compare four alternatives. Further managed biologists responsible for completing similar analyses for aquatic macroinvertebrates and surface waters.

https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4098