Background: Alex was born in St. Petersburg, Russia. He attended school in Russia and majored in Physical Geography. Alex came to the U.S. because he won a fellowship to the University of Arizona to work on a master’s degree in natural resources. While attending school he also worked in the U.S. Geological Survey in Tucson developing a spatially explicit decision support system for resources. However, he has always been interested in landscape ecology; therefore, he came to ASU. He has a wife and 2 kids that were able to come over 6 months after he arrived in the U.S.

Research interest: Modeling ecosystem primary productivity using Geographic Information Systems (GIS) and studying the difference in productivity between an urban ecosystem and its surrounding “natural” ecosystem (a desert ecosystem in this case).

Why he studies urban ecology: Alex sort of “fell” into urban ecology because he wanted to study landscape ecology and he likes the work that Dr. Wu, his advisor, does in landscape ecology. Since Dr. Wu applies landscape ecology concepts to urban ecosystems, Alex now studies landscape ecology in an urban system.

His research: Since plant growth is very important in an ecosystem, Alex wants to find out how the development of the Phoenix metropolitan area affects the amount and pattern of primary productivity in the Sonoran desert ecosystem. He hypothesizes that urbanization does have an effect on the amount and pattern of primary productivity in a desert because humans bring in water from other places, build many structures, and plant different kinds of plants all over the city. Alex predicts that urbanization in the Sonoran Desert will: 1) increase the amount of primary productivity as compared to the desert and 2) and will change the spatial and temporal pattern of primary productivity as compared to the desert. To study primary productivity, Alex uses remote sensing data to create a model that will be used to predict primary productivity based on soil and meteorological data such as temperature and moisture availability. The data Alex gets from remote sensing is a bird’s eye-view “picture” of the Phoenix metropolitan landscape made up of 6 layers of different colored 30x30-m pixels. See Figure 1 for an example. He studies and interprets the colors, shapes, and patterns of the differently colored objects to determine primary productivity. Because most plants and other objects are smaller than 900-m2, it is hard work to interpret the colors of the pixels. To help him with this problem, the handling of his data, and building his model, Alex uses several computer programs. After he builds his model, Alex will have to visit various parts of the city and verify that his classification of the Phoenix metropolitan landscape was correct. For example, make sure that a square patch of color in the satellite picture that he thought was an agriculture field really is an agriculture field.

What they do not tell you in science class about doing research: Every research project has its own peculiarities. Here is what Alex has learned about doing his research in a city.

Best part of research: Learning new techniques and applying them to a difficult–to-study system.

Worst part of research: Sitting in front of the computer all day. There is not a lot of fieldwork because almost everything is more efficiently done via computers.

Unexpected obstacle: Having to try new techniques that can take months to figure out how to apply to a desert ecosystem but also may or may not work—there is a lot of trial and error. Also, it is hard trying to classify desert plants such as succulents (e.g., cacti) and plants with no leaves (e.g., palo verde) is difficult.

Weirdest part of research: He has to deal with weird plants compared to what he grew up with in Russia and some peculiar people.

Interesting information: People have been trying to increase plant productivity of this desert region for thousands of years via agriculture and canals that bring in water. So people, their settlements, and changing plant productivity is not a new phenomenon.

Figure 1. This is a Landsat spectral map of Tempe Town Lake and the surrounding area. It is made up of 3 layers of colors: blue, red, and green. The colors and variations in the colors are interpreted to be different objects.