Dr. Nikolay Strigul

Assistant Professor
Nick Strigul
Phone: (360) 546-9655
Located in Life Sciences (VSCI) 130J

I conduct an interdisciplinary research across traditional disciplinary boundaries, in particular my research lies at the interface of applied mathematics, statistics and biology. I am interested in projects where mathematical methods in concert with field and experimental studies can lead to better understanding of multiple scale biological phenomena. I am also interested in remote sensing of environment, in particular, I lead a research project on 3D modeling of complex objects that includes a robotics engineering component. My research has focused on environmental problems, and has included research in mathematical biology, as well as a variety of modeling, experimental and field studies in different areas such as ecotoxicology, soil, microbial and avian ecology. My current primary research project is focused on forest modeling. One of the major directions of this project is to investigate effects of climatic changes and different land-use practices on forest dynamics. My research approach is to consider forested ecological systems as complex adaptive systems, which result from self-organization on multiple levels. I also conduct research on ecotoxicology, in particular tungsten ecotoxiology, in order to provide a scientific basis for pollution regulation and environmental risk-assessment.

Undergraduate students who would like to be involved in research are very welcome in my laboratory. I have supervised numerous undergraduate research projects, and many of them resulted in research publications. Prospective graduate students are also encouraged to contact me directly. I can supervise students pursuing M.Sc. and Ph.D. degrees in mathematics and statistics as well as in environmental sciences. WSU also offers an individual interdisciplinary doctoral degree program (IIDP) that can be especially suitable for students with unique research interests across disciplines. 


Course ID Title Meeting Time Location Semester Syllabus
STAT 360 Probability and Statistics (2 sections) Fall 2012
MATH 301 Introduction to Mathematical Reasoning Spring 2013
MATH 315 Differential Equations Summer (8 week) 2013
STAT 360 Probability and Statistics (2 sections) Fall 2013
STAT 423/523 Statistical Methods for Engineers and Scientists Fall 2013
STAT 360 Probability and Statistics Summer (8 week) 2014
STAT 360 Probability and Statistics (2 sections) Fall 2014
MATH 273 Multivariate Calculus Fall 2014
STAT 360 Probability and Statistics Summer (early 6 week) 2015


My research approach is to consider biological populations and communities as complex adaptive systems, which result from self-organization on multiple levels. These levels, or scales, include: a) genomic and cellular levels, b) organs, c) individual organisms, and d) populations and ecosystem level. In experimental biology it is often necessary to concentrate on one focal level of organization, while ignoring processes at the other scales. However, the theoretical framework of complex adaptive systems allows us to study organizational patterns and processes across multiple scales. The mathematics include three major components: 1) the use of individual-based models, as they are among the most suitable and promising tools for simulating complex-adaptive systems and interactions on multiple scales, 2) the development of different scaling methods that approximate individual-based processes, and 3) the investigation of various inverse problems to connect models with empirical data. The first component involves mostly computer simulations of what are, in general, analytically intractable stochastic processes. Scaling methods allow models to be reduced to analytically tractable objects–such as different stochastic and deterministic dynamical systems–which are both more valuable for experimental scientists and, also, computationally simpler. Usually the same scaling method can be presented in several alternative mathematical forms depending on the assumptions concerning time, space and underlying processes. I work with scaling methods that are non-linear partial differential or integral equations in case of continuous models, and non-linear recursive and difference equations in case of discrete models. The mathematical problems that emerge at this stage are quite challenging including analysis of the transient dynamics, stationary states and their stability for non-linear discrete or continuous models. The third component belongs to applied-statistics, and my research involves the study of and the application of regression models, Bayesian methods, and optimal experimental designs.

 My current primary research project is focused on forest modeling. I am interested in both basic and applied problems such as forest biocomplexity, effects of climate change and different land use practices on forests and sustainable management of forested ecosystems. I have recently developed a model, called Matreshka (after the Russian nesting doll), for scaling of vegetation dynamics from individual-level to the landscape level through the ecosystem hierarchical structure (Strigul, 2012). The Matreshka model employs the recently developed Perfect Plasticity Approximation (PPA) model (Strigul et al., 2008) as an intermediate step of scaling from the individual level to the forest stand-level (or patch-level). 

Recent Publications

This list is selected recent publications, a full list of publications is available on my lab webpage. Papers in pdf format are available under request, please e-mail me.

* - indicates a postdoc or a student under my direct supervision 

 Lienard* J., Harrison J. & Strigul N.S. 2016. U.S. Forest Response to Projected Climate-Related Stress: a Tolerance Perspective. Global Change Biology, in press

Lienard* J. & Strigul N. 2016. An individual-based forest model links canopy dynamics and shade tolerances along a soil moisture gradient. Royal Society Open Science 3 (2), 150589 http://dx.doi.org/10.1098/rsos.150589

Lienard* J. & Strigul N.S. 2016. Modeling of hardwood forest in Quebec under dynamic disturbance regimes: a time‐inhomogeneous Markov chain approach. Journal of Ecology, http://dx.doi.org/10.1111/1365-2745.12540

Lienard* J., A Vogs, D Gatziolis & N. Strigul 2016. Embedded, real-time UAV control for improved, image-based 3D scene reconstruction. Measurement 81, 264-269 http://dx.doi.org/10.1016/j.measurement.2015.12.014

Talluto M., I. Boulangeat, A. Ameztegui, I. Aubin, D. Berteaux, A. Butler, F. Doyon, C. Drever, M. Fortin, T. Franceschini, J. Lienard*, D. McKenney, K.A. Solarik , N. Strigul, W. Thuiller, & D. Gravel 2016. Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework. Global Ecology and Biogeography, 25(2): 238–249. http://dx.doi.org/10.1111/geb.12395

Gatziolis D., J.F. Lienard*, A. Vogs & N.S. Strigul 2015. 3D tree dimensionality assessment   using photogrammetry and small unmanned aerial vehicles. PLOS One, 10 (9): e0137765 http://dx.doi.org/10.1371/journal.pone.0137765

Lienard* J., Gravel D. & Strigul N. 2015. Data-intensive multidimensional modeling of forest dynamics.  Environmental modelling and software, 67:138-148. http://dx.doi.org/10.1016/j.envsoft.2015.01.010                

Lienard* J., Florescu I., & Strigul N. 2015. An appraisal of the classic forest succession paradigm with the shade tolerance index. PLOS One, 10(2): e0117138. http://dx.doi.org/10.1371/journal.pone.0117138

Lienard* J.  &  Strigul N. 2015. Linking forest shade tolerance and soil moisture in North America. Ecological Indicators, 58: 332-334. http://dx.doi.org/10.1016/j.ecolind.2015.05.034

Strigul N.S. 2012. Individual-based models and scaling methods for ecological forestry: implications of tree phenotypic plasticity. Sustainable Forest Management, Diez, J.J. (Ed.), InTech, 359-384. http://dx.doi.org/10.5772/29590

 Strigul N.S., I. Florescu, A.R. Welden* & F. Michalczewski* 2012. Modeling of forest stand dynamics using Markov chains. Environmental Modeling and Software,  31:64-75.  http://dx.doi.org/10.1016/j.envsoft.2011.12.004

 Vaccari D.A. & Strigul N.S. 2011. Extrapolating phosphorus production to estimate resource reserves. Chemosphere, 84(6): 792-797. http://dx.doi.org/10.1016/j.chemosphere.2011.01.052

 Strigul N.S. 2010. Does speciation matter for tungsten ecotoxicology? Ecotoxicology and Environmental Safety, 73(6): 1099-1113.  http://dx.doi.org/10.1016/j.ecoenv.2010.05.005

Strigul N.S., A. Koutsospyros, and C. Christodoulatos. 2010. Tungsten speciation and toxicity: acute toxicity of mono- and poly- tungstates to fish. Ecotoxicology and Environmental Safety, 73(2):164-171. http://dx.doi.org/10.1016/j.ecoenv.2009.08.016

Strigul N.S.. 2009. Can Imitation Explain Dialect Origins? Ecological Modelling, 220(20): 2624-2639. http://dx.doi.org/10.1016/j.ecolmodel.2009.07.005

 Strigul N.S., H. Dette, and V.B. Melas. 2009. A Practical Guide for Optimal Designs of Experiments in the Monod Model. Environmental Modeling and Software, 24(9):1019-1026. http://dx.doi.org/10.1016/j.envsoft.2009.02.006

Strigul N.S., C. Galdun*, L. Vaccari*, T. Ryan*, W.J. Braida, and C. Christodoulatos. 2009. Influence of Speciation on Tungsten Toxicity. Desalination, 248 (1-3): 869-879.  http://dx.doi.org/10.1016/j.desal.2009.01.016

 Strigul N.S., A. Koutsospyros, and C. Christodoulatos. 2009. Tungsten in the Former Soviet Union: Review of Environmental Regulations and Related Research. Land Contamination and Reclamation, 17(1):189-216. http://dx.doi.org/10.2462/09670513.923

 Strigul N.S., L. Vaccari*, C. Galdun*, M. Wazne, F. Xi, C. Christodoulatos, and K. Jasinkiewicz. 2009. Acute Toxicity of Boron, Titanium Oxide, and Aluminum Nanoparticles to Daphnia magna and Vibrio fishery. Desalination, 248(1-3):771-782. http://dx.doi.org/10.1016/j.desal.2009.01.013

Purves D., J. Lichstein, N.S. Strigul, and S.W. Pacala. 2008. Predicting and Understanding Forest Dynamics Using a Simple Tractable Model. Proceedings of the National Academy of Sciences, 105(44):17018-17022. http://dx.doi.org/10.1073/pnas.0807754105

 Strigul N.S., D. Pristinski, D.Purves, J. Dushoff, and S.W. Pacala. 2008. Scaling from Trees to Forests: Tractable Macroscopic Equations for Forest Dynamics. Ecological Monographs, 78 (4): 523-545. http://dx.doi.org/10.1890/08-0082.1