Michael M. Fuller

Research Focus

My research interests includes theoretical and applied problems in population ecology and community ecology. I currently work mainly on applied problems related to forest management and invasive species. Examples include:

Current Projects


Modeling Outcomes of Management Scenarios for Post-Fire Forest Recovery

Forest fires in western North America have become larger and more frequent, and these patterns are correlated with lower precipitation, earlier onset of spring snow melt, and warmer average temperatures. The changing fire regime is thus tied to changing climate, and therefore forest ecologists have turned to climate models as an important tool for forecasting future conditions, and to devise management strategies.

Here, the overarching project was to develop computer simulations for forest fires, which combine data from climate models with simulated vegetation growth data. The goal is to better understand how climate change will alter the size, frequency, and intensity of future forest fires in the Rocky Mountains in general, and particularly in New Mexico.

As you can imagine, many diverse streams of data must be brought together for this analysis. My task was to develop a computer program which takes, as input, raw data on vegetation, forest conditions, and species communities, and generates the formatted initial communities data, and a raster of community types. These files are used as data and paramters for the LANDIS-II forest landscape simulator, which will be used to forecast changes in cover in response to changing climate and fire regimes. I used the R programming language for this task.

Las Conchas fire, 2011 (New Mexico). Photo by: Kristen Honig/US Forest Service

Recent Projects


Ecosystem Monitoring of Mining Impacts in Mongolia

The Oyu Tolgoi Mine is the third largest copper mine in the world, and the largest mine in Mongolia. Situated within the Gobi desert, and with a 50-year expected operational lifetime, the OT mine has the potential to generate substantial, long-term environmental impacts.

I worked with the Wildlife Conservation Society and OT ecologists to monitor changes to wildlife populations, vegetation, and a variety of sensitive biological resources. Our principal goal was to rigorously determine whether observed changes to these natural resources can be definitively linked to mining activities. Armed with such knowledge, we can help OT develop a strategy for managing negative impacts, and strive toward their stated goal of establishing a net positive impact on the environment.

Host-Parasite Spatial Interactions

Sugar maple is a dominant component of temperate forests in northeastern US and southeastern Canada, and is considered a significant source of wood products. Sugar maple is also the host to a tiny leaf parasite, the spindle gall mite (photo at right).

With arthropod parasites of cultivated plants, the density of parasites is often found to closely track that of the host. However, many studies of leaf-parasite systems focus on agricultural systems, characterzied by low species diversity and a homogeneous environments. Are parasites able to track their hosts as effectively when faced with high host community diversity and heterogeneous environments? To answer this question, I worked with principal investigator, Rajit Patankar, and our mutual colleagues at the University of Toronto, to study the spatial relationship of sugar maples to the the density and distribution of spindle gall mites.

The study site, which is part of a global network of research plots organized by the Center for Tropical Forest Science, is located in southcentral Ontario. On this plot, the density and diversity of trees varies greatly with location (Figure below right). We used spatially explicit methods to quantify the influence of a range of environmental factors on the galling mite's spatial distribution. We discovered that, contrary to expectations, mite density increased as host density decreased! The flip-side of this pattern is that mite density increased with an increase in tree species diversity.

We speculate that the mechanism responsible for the negative spatial relationship between the parasite and its host is parasite-induced host stress. Separate studies have established a strong negative impact of the spindle gall mite on sugar maple stem growth. We suggest that by weakening the competitive ability of its host, the parasite indirectly promotes local species diversity through competitive release. Given the high diversity and prevalence of leaf gall parasites in mixed hardwood stands, depression of host dominance by leaf parasites may represent an unexplored mechanism for the maintenance of species diversity in northern temperate forests.

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Leaf galls formed by spindle gall mites.

Nitrogen Enrichment Experiment, Boreal Forests

In separate research, I am working with environmental scientists in the US and Canada to study the effects of nitrogen pollutants on boreal forests in Alberta, Canada. The oil sands formation of Alberta has become a major source of crude oil. But growth in large-scale extraction activities carries a variety of potential environmental impacts. For example, oil sands operations have become an important source of air pollutants, such as nitrogen dioxide and sulphur dioxide. Government regulatory agencies are charged with setting standards for air pollution levels. Yet little is known about the cumulative effects of pollution on boreal forests, or what level of pollution results in adverse impacts.

To help regulatory agencies set thresholds for nitrogen deposition rates, Integral Ecology Group initiated a 5-year field experiment in a natural stand of boreal forest. The experiment employs a helicopter (photo at right) to annually spray aqueous ammonium nitrate, at five different concentrations, over a series of study plots set up in the forest. Small scale studies are being performed within the study plots to monitor changes in soil chemistry and vegetation. The experiment, now in its second year, is designed to measure the effects of nitrogen on natural communities. See the project web site for more information.

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Climatological, Ecological, and Social Processes of Organic Farms

In south-central New Mexico, I worked with members of an organic farming community, to establish water conservation methods and social frameworks that can stabilize the sustainability of small-scale operations. Farming communities depend on a range of ecosystem services for food production. In arid lands, water is typically the most important natural resource, and its capture and storage can present major challenges. Small to intermediate scale farms often represent communities of farming families, which self-organize into a mutually dependent social network. Local governance of shared, limited resources, such as water, can be the glue that ties the network together, or the stressor that threatens network disintegration.

Using several novel field experiments, we investigated methods that may promote ground water recharge and surface storage of storm water, as a means of stabilizing the seasonal availability of this essential resource. We are also addressing the social aspects of resource use, with the goal of establishing a template of criteria and protocols that can guide small-scale farming in the arid regions of the world, leading to long-term sustainability in food production.

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Modeling Long-Term Harvest Impacts, Temperate Forests

At the University of Toronto, I was involved on several projects with Sean Thomas. The principal area of research was forest dynamics and the effects of harvest systems on forest growth and yield, and ecosystem health. For example, we worked with several graduate students to determine how harvesting changes the structure and species composition of boreal and hardwood forests. Our studies required physically demanding field work, and made use of several types of computer models, including analystical models, statistical models, and individual-based models.

In one study, we used computer simulation to investigate the long-term patterns of mortality and succession in selection-managed stands. Using the SORTIE-ND forest dynamics model (Murphy 2008), we simulated single-tree selection within 20ha stands, and compared the successional patterns to those of unharvested (control) stands. The purpose of our computer experiments was to assess the multi-decadal impacts of post-harvest mortality, specific to single-tree selection, on community structure and species diversity.

Our harvest simulations projected an accelerated succession that strongly favored shade tolerant species. In contrast to controls, selection-managed stands strongly favored Eastern hemlock over American beech, the former increasing in relative basal area (RBA) by 129.6 percent, on average, after 150 years of managed growth. Increases in shade-tolerant species were accompanied by a concomitant decrease in mid-tolerant species, with yellow birch, white ash, and red oak exhibiting more drastic declines in RBA over the 150 year period, compared to controls (figure at right). Thus, the contribution of mortality among non-target stems to canopy gaps was not sufficient to stabilize the RBA of mid-tolerant and intolerant species in harvested stands. By the end of the period simulated, nearly all mid-tolerant species had declined by at least 39 percent of their original stand basal area, with white ash showing the greatest decline of 89 percent.

The take-home message of the SORTIE-ND projections is that selection harvest, using basal-area targets recommended for northeastern hardwood forests, can exert a substantial influence on long-term community structure, with an overall decline in species diversity as mid-tolerant and intolerant species fall in abundance.

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Visualization Tools for Monitoring Remote Sensor Arrays

In 2011, I worked with Dr. Marcy Litvak to develop methods for visualizing and managing high-throughput micro-meteorological (climate) data, at the University of New Mexico. Marcy and her colleagues have established eight climate towers in central New Mexico for the purpose of measuring changes in vegetation and ecosystem processes that are related to climate change.

This work revolves around the analysis of eddy-covariance data, which are measurements of the fluctuations in carbon dioxide, water, and energy at the ecosystem level.

To assist the analysis of large data files, I developed a visualization program in MATLAB that permits rapid assessment of the status of the many sensors that continuously monitor conditions at the towers. Each tower supports over 60 different sensors that record such variables as temperature, precipitation, wind speed and direction, and changes in carbon dioxide concentration over time.

Data are collected at 10Hz (10 times per second) and stored locally on data loggers. The software I developed downloads daily logger records and graphs the temporal sensor output according to data type, allowing the researchers to quickly identify faulty or inoperable sensors. This information is crucial to the task of assembling a complete, unbroken profile of conditions at each tower site.

The figure at right shows a typical plot window generated by the software. The figure contains four panels, each of which contains a plot of multiple sensors. The sensors are grouped by sensor type (e.g. "wind"). The lines show the output of the sensors over time (time period is set by the user). An empty plot, such as the lower right one, indicates that no data are available, either because a sensor is malfunctioning or there were simply no data for the period. The lower right plot is for certain error warnings, and there were no warnings for the plotted period.

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Research at The Institute for Environmental Modeling

In the mid-2000s I collaborated with Louis Gross and Suzanne Lenhart, and their students, at The Institute for Environmental Modeling, and Department of Mathematics, University of Tennessee, Knoxville.

I worked with Erika Asano and Andrew Whittle to develop a mathematical model for the spread of the Eurasian collared-dove, which has invaded North America. You can see some of the model output at right.

Estimating Uncertainty of Climate Forecasts

In addition to the dove project, I also documented the uncertainty of models used in the the Florida Everglades Restoration project. In a recent paper (Ecological Applications 18:711-723) we describe an approach called relative assessment. We use this approach to analyze the robustness of habitat management decisions in the wetlands of Southern Florida.

The technique uses random variation in input data to generate empirically-based hypothetical climate scenarios. The effect of variation on the ranking of different management alternatives can then be compared using the criteria of interest.

For example, climate scenarios can be used as inputs to habitat quality models to project the effect of climate shifts on different species in the park. Because these species differ in their habitat needs, management scenarios must balance the positive and negative impacts of water management for species that may have conflicting needs. For example, increasing water flow to a particular area will generally favor wetlands over upland habitats.

The corresponding changes to vegetation and open freshwater can have divergent impacts on wildlife: the endangered Cape Sable seaside sparrow requires upland grassland whereas the endangered snail kite depends on wetlands (see figure at right). Relative assessment involves quantifying differences in the suitability of different management options according to a specific management-related criteria.

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Computational Science and Natural Resource Management

Working with a team of computer scientists, ecologists, and geographers at UTK, I co-wrote a short article for the journal Computing in Science and Engineering, about how computers are changing the science of ecology. Advances in miniaturization, computing power, remote sensing, and modeling are revolutionizing the field of natural resource management. But these advances also bring many challenges. The need for information management and communication, dynamic models, and real-time monitoring places increasing demands on legacy data structures and over-burdened networking infrastructures. To meet these demands, natural resource managers require access to high-performance computing tools and improvements in data storage, communication, and analysis.

In the article, we encourage computer scientists to collaborate with natural resource managers and modelers to develop solutions to problems in resource management. The figure at right is from our paper (Computing in Science and Engineering 9:40-48).

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Past Research Topics

My doctoral dissertation tested the predictions of the neutral theory of biodiversity and biogeography. The neutral theory emphasizes the role of random demographic change on species diversity and abundance. Proponents of the neutral theory have shown that simple neutral models, in which individuals have an equal probability of birth, death, and dispersal, can reproduce several observed community patterns, such as species relative abundance.

The above result suggests that random processes alone can explain the structure of communities. However, many empirical studies have shown that community patterns are also influenced by variation among species in their ability to survive and reproduce. To understand the extent to which neutral models can predict species distribution and abundance, I compared the variation inspecies abundances in natural communities with that predicted by neutral models. I developed a new technique for constructing "species association networks", which permit one to analyze the role of species differences on variation in species abundances. I also analyzed data on aquatic invertebrate communities (see below).

DISSERTATION: Species Association Networks of Tropical Trees

Tropical forest is often cited as a community that may be governed by neutral dynamics (e.g. Hubbell 2001). Trees are structurally and ecologically similar, and therefore may be more similar ecologically. In two projects, I collaborated with Brian Enquist and Andreas Wagner to analyze patterns of species association in a tropical forest (see our paper, Natural Resource Modeling 21:225-247). We used data on the geographic coordinates of over 19,000 tropical dry-forest trees (106 species) to determine whether species niche differences influence community structure. In an unprecedented approach, we used the principles of graph theory to analyze the effect of tree crown overlap and body size on community structure. We constructed networks representing the spatial association of species (see bottom figure in the frame to the right). This approach revealed how species interactions in local neighborhoods influence the structure of the community.

An important goal of the project was to determine the randomness of species distributions on the forest plot. We compared species networks constructed from the empirical distribution of species to those in which the geographic coordinates of individual trees had been randomized (see figure, above). We found that the networks which represented the empirical community often differed strikingly from those of randomized communities. However, our ability to detect the effect of niche differences on community structure was sensitive to how network complexity was measured. In the future, I want to examine the effect of intraspecific spatial autocorrelation on network structure in this forest.

DISSERTATION: Community-Metacommunity Dynamics of Aquatic Invertebr/ates

To analyze the invertebrate community patterns, I collaborated with Tamara Romanuk and Jurek Kolasa. We used a 9-year dataset collected by Jurek and his collaborators that represented 50 rock pool communities and 72 species, such as the copepod shown at right. We used neutral models to predict the relative abundance of each species based on their metacommunity proportions. We then compared the predictions to empirical species proportions at the community (i.e. individual pool) and metacommunity scales.

We found that at the community scale, common species were far more variable in abundance than predicted by neutral models (lower figure at left). At the metacommunity scale, rare species were more common than predicted. In addition, variation in species diversity and abundance was strongly influenced by the relative density of predators. Trophic interactions influenced both community and metacommunity patterns. The findings of our metacommunity study are published in Community Ecology (Fuller et al. 2005, see references below).

Self-Organized Criticality in Ecological Systems

For my Master of Science research at the University of Oklahoma, I worked with Caryn Vaughn and the late Danish physicist and complexity theorist, Per Bak, along with his wife and colleague, Maya Paczuski, to test the theory of self-organized criticality (SOC), which Per co-developed. SOC is a theory from statistical physics which posits a mechanism for spontaneous self organization in complex systems. When applied to evolution and ecology, SOC asserts that extinction cascades and population correlations can arise as a consequence of intimate ecological relationships among species.

In the first empirical test of the ecological predictions of SOC, I collected time series data for 72 freshwater organisms found in vernal pools. I also monitored the physical and chemical conditions of the pools. My results neither refuted nor substantiated the predictions of SOC. Although the population trajectories were often correlated, the correlations corresponded with abiotic changes in the pools. I was therefore unable to differentiate the environmentally-driven population changes from those attributable to multivariate statistical approaches.

The above results illustrate that combining models with empirical data is a powerful approach for uncovering the influence of different factors on species patterns.

References Cited

Fuller, M.M., T.N. Romanuk, and J. Kolasa. 2005. Effects of predation and variation in species relative abundance on the parameters of neutral models. Community Ecology 6:229-240.

Fuller, M.M., D. Wang, L.J. Gross, and M.W. Berry. 2007. Current Problems and Future Directions in Computational Science for Natural Resource Management. IEEE Computing in Science and Engineering 9:40-48

Fuller, M.M., L.J. Gross, S.M. Duke-Sylvester, M. Palmer. 2008. Testing the robustness of management decisions: Everglades Restoration Scenarios. Ecological Applications 18:711-72

Fuller, M.M., B.J. Enquist, and A. Wagner. 2008. Using network analysis to characterize forest structure. Natural Resource Modeling 21:225-247

Hubbell, Stephen P. 2001. The Unified Theory of Biodiversity and Biogeography. Princeton, NJ. Princeton Univ. Press.

Murphy, L. 2008. SORTIE-ND User Manual, Version 6.09. Institute of Ecosystem Studies, Millbrook, NY.