## James N. McNair, Ph.D.

### Associate Professor

Annis Water Resources Institute

Grand Valley State University

740 West Shoreline Drive Muskegon, MI 49441

*Office:* 133 Lake Michigan Center

*Phone:* 616-331-3987

*Fax:* 616-331-3864

*E-mail:* mcnairja@gvsu.edu

### Academic Background

- Ph.D., Biology (Theoretical Ecology), University of Pennsylvania, 1979
- B.S., Biology, Davidson College, 1974
- Curriculum Vitae (PDF)

### Current Research Areas

- Mechanistic models and statistical methods for estimating components of stream metabolism based on free-water dissolved-oxygen dynamics
- Stochastic models of particle transport (e.g., microorganisms, invertebrates, fine particulate organic matter) in streams
- Non-parametric, semi-parametric, and fully parametric methods of statistical time-to-event analysis as applied to data from seed germination experiments
- Evolutionary responses of invasive aquatic and terrestrial plants to herbicides
- Statistical methods for estimating abundance of stream fish
- Physiologically based models of microbial populations

### Research Approach

My three main research interests at the present time are methods of estimating components of stream metabolism based on free-water dissolved-oxygen (DO) dynamics, evolutionary ecology of invasive aquatic and terrestrial plants, and turbulent transport of suspended particles (e.g., fine particulate organic matter, microorganisms, and invertebrate larvae) in streams.

Exchange of carbon between the biosphere and atmosphere is dominated by rates of photosynthetic CO2 uptake and respiratory CO2 release by aquatic and terrestrial ecosystems worldwide. Obtaining accurate estimates of these rates is therefore important. In streams and lakes, the most common estimation method is based on a model of DO dynamics and a corresponding time series of DO concentrations measured in the water colum. O2 production and consumption are inferred from changes in DO concentration, then converted to estimates of carbon uptake and release using photosynthetic and respiratory quotients. The traditional method of this type (first used systematically by H. T. Odum in 1956) uses a simple accounting procedure to estimate daily gross primary production (GPP), total respiration (R), and net production (NP). However, it assumes that the time series of measured DO concentrations contains no error, and its estimates of R and GPP hinge on a subjectively assumed value for daytime respiration. In 1975, Hornberger and Kelly published a prediction-based statistical method that resolves these problems. I have developed several alternative extensions of the prediction-based method for estimating GPP, R, and NP in streams. These methods allow one to estimate daytime and nighttime respiration rates independently, acknowledge statistical error in the measured time series, and facilitate assessment of model adequacy. Together with my graduate students and summer interns, I am applying these new methods to high-frequency time-series data acquired with multisensor sondes in streams of West Michigan.

My work on the evolutionary ecology of invasive aquatic and terrestrial plants involves collaborative efforts with Dr. Ryan Thum of Montana State University (Eurasian watermilfoil and hybrids) and Dr. Charlyn Partridge of AWRI (baby's breath). We are exploring both purely ecological models and eco-evolutionary models that include evolution of quantitative and categorical traits in finite populations coupled by migration. The watermilfoil research is focused to a large extent on the role of hybridization in both the evolution of invasiveness and the evolution of herbicide resistance. The baby's breath research currently is focused on genetic evidence regarding population structure and spatial spread, characterizing the phenology of seed maturation, and assessing the efficacy of commonly-used management techniques such as manual removal and foliar application of herbicide (glyphosate).

My work on turbulent transport of suspended particles centers on a stochastic diffusion model called the Local Exchange Model, which I developed to describe the random-like dynamics of individual particles suspended in a turbulent fluid. The model can be applied to the transport of molecules, seston, microorganisms, and invertebrates in aquatic systems characterized by turbulent flowing water (e.g., streams, estuaries, and marine systems), and to a variety of other turbulent transport problems, as well.

A complete theory of particle transport in turbulent aquatic systems can be decomposed into at least four problems: (1) The entrainment problem how does a particle on the bottom (or other solid surface) become entrained into the water column? (2) The travel-time problem how long does a suspended particle take to hit the bottom for the first time, following release from a given initial elevation? (3) The travel-distance problem how far does a suspended particle travel before hitting the bottom for the first time, following release from a given initial elevation? And (4) the settlement problem what determines whether a particle settles on the bottom when it hits, rather than bouncing off and immediately returning to the water column? Thus far, I have derived equations governing the probability distribution and moments of the hitting time, hitting distance, settling time, and settling distance (the hitting time and distance are the travel time and distance at which a suspended particle hits the bottom for the first time; the settling time and distance are the travel time and distance at which a suspended particle settles for the first time). I have applied these theoretical results to empirical settling-distance distributions for 14C-labeled natural FPOM in streams, and I am currently applying them to data for additional types and sizes of particles in streams and flumes.

### Teaching

**BIO/NRM 480/580: Techniques for Modeling Biological Systems** (Fall semester in
even-numbered years, 3 credits). Theories based on mathematical models have long been of fundamental
importance in subdisciplines of the biological sciences. In population biology, this importance
dates at least as far as the 1700s with, for example, Euler's work in mathematical demography
and Malthus's work on population regulation. In the early to mid 20th century, there was a great
flowering of mathematical approaches in many areas of biology, including ecology, population
genetics, fisheries and wildlife management, biophysics, epidemiology, physiology, and
biochemistry. More recently, mathematical models have become important in new areas, such as
developmental biology, bioinformatics, and systems biology.

Despite the rapidly increasing importance of mathematical theories in the biological sciences, biology students often are not required to learn the mathematical and computational skills needed to understand, assess, apply, or develop mathematical models. The main purpose of this course is to partially fill this gap by providing biology students with a set of basic mathematical, computational, and computer graphics skills that will allow them to understand and critically evaluate several of the most common types of models in the biological literature, and to develop new models of their own.

The main types of models covered in this course are difference equations, matrix models, and ordinary differential equations. No prior knowledge of any of these topics is assumed. As background, the course begins by refreshing students' memories of various topics in elementary mathematics, including the basic rules of algebra and various standard mathematical functions (power functions, exponential functions, etc.). The course also provides students with an introduction to the required parts of elementary calculus, tailored to biology students and with no prior knowledge assumed.

Each modeling technique studied is illustrated by readings from the literature. Applications to various branches of modern biology are illustrated with worked examples. Specific applications examined during the course each year will be selected based on interests of the students but may include, for example, topics in animal behavior, population and community ecology, population genetics, fisheries and wildlife management, ecotoxicology, epidemiology, cell and organism physiology, biochemistry, regulation of genes and metabolism, and statistical topics such as least-squares parameter estimation.

This is not a mathematics or computer programming course. Emphasis is placed on how to apply the various techniques to biological problems rather than on mathematics or programming per se.

**NRM 582: Fisheries management** (Winter semester in odd-numbered years, with Carl Ruetz, 3 credits).
This course provides an introduction to basic fisheries science and management, with an emphasis on
freshwater systems. It assumes a basic familiarity with fish but no prior knowledge of fisheries
management. The course focuses on the process of managing fish populations and their habitat, the
required field and laboratory methods and gear, and a variety of useful modeling and statistical
tools. Specific topics include statistics for fisheries management (experimental design and
hypothesis testing, regression analysis, model selection, repeated measures), length-weight
relationships, condition, age and growth, estimating mortality, gear bias, abundance estimation,
population growth and harvest, the yield-per-recruit model, bioenergetics models, and stocking
and regulations.

**BIO 580: R programming for scientific computing** (Winter semester in even-numbered years, 3 credits).
This course uses the R programming language to introduce students to the craft of writing computer
programs for applications in the biological sciences. The emphasis is on programming concepts and
constructs common to many programming languages that are widely used in scientific applications,
though some of the most useful idiosyncratic features of R are included, as well. The course covers
basic programming techniques, various numerical methods that are useful in scientific applications
in the biological sciences, and technical graphics.

### Selected Publications

Taylor, L. L., McNair, J. N., Guastello, P., Pashnick, J., and Thum, R. A. 2017. Heritable variation for vegetative
growth rate in ten distinct genotypes of hybrid watermilfoil. *Journal of Aquatic Plant Management* 55:
51-57.

Thum, R. A., Parks, S. R., McNair, J. N., Tyning, P., Hausler, P., Chadderton, L., Tucker, A., and Monfils, A.
2017. Survival and vegetative regrowth of Eurasian and hybrid watermilfoil following operational treatment with
auxinic herbicides in Gun Lake, Michigan, USA. *Journal of Aquatic Plant Management* 55: 103-107.

Parks, S. R., McNair, J. N., Hausler, P., Tyning, P., and Thum, R. A. 2016. Divergent responses of cryptic invasive
watermilfoil to treatment with auxinic herbicides in a large Michigan lake. *Lake and Reservoir Management* 32:
366-372.

McNair, J. N., Sesselmann, M. R., Gereaux, L. C., Weinke, A. D., Kendall, S. T., and Biddanda, B. A. 2015.
Alternative methods for estimating components of lake metabolism using process-based models of dissolved-oxygen
dynamics. *Fundamental and Applied Limnology* 186: 21-44.

Ruetz, C. R. III, Harris, B. S., McNair, J. N., and Homola, J. J. 2014. Removal and mark-recapture methods for
estimating abundance: empirical and simulation results for Mottled Sculpin in streams. *North American Journal of
Fisheries Management* 35: 62-74.

McNair, J. N., Gereaux, L. C., Weinke, A. D., Sesselmann, M. R., Kendall, S. T., and Biddanda, B. A. 2013. New
methods for estimating components of lake metabolism based on free-water dissolved-oxygen dynamics. *Ecological
Modelling* 263: 251-263.

Sisson, A.J., Wampler, P.J., Rediske, R.R., McNair, J.N., and Frobish, D. 2013. Long-term field performance of the
Biosand Filter in the Artibonite Valley, Haiti. *American Journal of Tropical Medicine and Hygiene* 88:
862-867.

Homola, J.J., Scribner, K.T., Elliott, R.F., Donofrio, M.C., Kanefsky, J., Smith, K.M., and McNair, J.N. 2012.
Genetically-derived estimates of contemporary natural straying rates and historical gene flow among Lake Michigan lake
sturgeon populations. *Transactions of the American Fisheries Society* 141: 1374-1388.

McNair, J.N., and Newbold, J.D. 2012. Turbulent particle transport in streams: Can exponential settling be
reconciled with fluid mechanics? *Journal of Theoretical Biology* 300: 62-80.

McNair, J.N., Sunkara, A., and Frobish, D. 2012. How to analyze seed germination data using statistical
time-to-event analysis: nonparametric and semiparametric methods. *Seed Science Research* 22: 77-95.

McNair, J.N. 2009. Two new methods for predicting effects of landcover-related stressors on stream biotic integrity
at the catchment scale. *Proceedings of the Academy of Natural Sciences of Philadelphia* 158: 61-88.

Sieg, A.E., O'Connor, M.P., McNair, J.N., Grant, B.W., Agosta, S.J., and Dunham, A.E. 2009. Mammalian metabolic
allometry: do intraspecific variation, phylogeny, and regression models matter? *American Naturalist* 174:
720-733.

Araujo, A. and McNair, J.N. 2007. Individual- and population-level effects of antimicrobials on the rotifers,
*Brachionus calyciflorus* and *B. plicatilis*. *Hydrobiologia* 593: 185-199.

Johnson, T.E., McNair, J.N., Srivastava, P., and Hart, D.D. 2007. Stream ecosystem responses to spatially variable
landcover: a model for developing riparian restoration strategies. *Freshwater Biology* 52: 680-695.

O'Connor, M.P., Agosta, S.J., Hansen , F., Kemp, S.J., Sieg, A.E., McNair, J.N. and Dunham, A.E. 2007. Phylogeny,
regression, and the allometry of physiological traits. *American Naturalist* 170: 431-442.

O'Connor, M.P., Agosta, S.J., Hansen , F., Kemp, S.J., Sieg, A.E., Wallace, B.P., McNair, J.N. and Dunham, A.E.
2007. Size, selection, and physiology: Reconsidering the mechanistic basis of the metabolic theory of ecology.
*Oikos* 116: 1058-1072.

McNair, J.N. 2006. Probabilistic settling in the Local Exchange Model of turbulent particle transport. *Journal
of Theoretical Biology* 241: 420-437.

Srivastava, P., McNair, J.N., and Johnson, T.E. 2006. Comparison of process-based and artificial neural network
approaches for streamflow modeling in an agricultural watershed. *Journal of the American Water Resources
Association* 42: 545-563.

Fingerut, J.T., Hart, D.D. and McNair, J.N. 2006. Silk use enhances benthic invertebrate settlement.
*Oecologia* 150: 202-212.

Bram, M.R. and McNair, J.N. 2004. Seed germinability and its seasonal onset in three populations of Japanese
knotweed. *Weed Science* 52: 759-767.

McNair, J.N., and Newbold, J.D. 2001. Turbulent transport of suspended particles and dispersing benthic organisms:
the hitting-distance problem for the Local Exchange Model. *Journal of Theoretical Biology* 209: 351-369.

McNair, J.N. 2000. Turbulent transport of suspended particles and dispersing benthic organisms: the hitting-time
distribution for the Local Exchange Model. *Journal of Theoretical Biology* 202: 231-246.

Goulden, C.E., Moeller, R.E., McNair, J.N., and Place, A.R. 1999. Lipid dietary dependencies in zooplankton. Pages
91-108 in: Arts, M.T. and Wainman, B.C. (Eds.) *Lipids in Freshwater Ecosystems*. New York: Springer-Verlag.

McNair, J.N., Boraas, M.E., and Seale, D.B. 1998. Size-structure dynamics of the rotifer chemostat: a simple
physiologically structured model. *Hydrobiologia* 387/388: 469-476.

Boraas, M.E., Seale, D.B., Boxhorn, J.E., and McNair, J.N. 1998. Rotifer size distribution changes during transient
phases in open cultures. *Hydrobiologia* 387/388: 477-482.

McNair, J.N., Newbold, J.D., and Hart, D.D. 1997. Turbulent transport of suspended particles and dispersing benthic
organisms: how long to hit bottom? *Journal of Theoretical Biology* 188: 29-52.

McNair, J.N. 1995. Ontogenetic patterns of density-dependent mortality: contrasting stability effects in
populations with adult dominance. *Journal of Theoretical Biology* 175: 207-230.

McNair, J.N., Goulden, C.E., and Ziegenfuss, M.C. 1995. Is there a place for ecotoxicology? *Setac News* 15:
18-21.

McNair, J.N. and Goulden, C.E. 1991. The dynamics of age-structured populations with a gestation period:
density-independent growth and egg ratio methods for estimating the birth rate. *Theoretical Population Biology*
39: 1-29.

McNair, J.N. 1989. Stability effects of a juvenile period in age-structured populations. *Journal of Theoretical
Biology* 137: 397-422.