Tiffany Bogich

Curriculum Vitae:

• 2009–Present: Visiting Research Fellow, Institute of Zoology, London, UK.
• 2009–Present: Senior Postdoctoral Fellow, Wildlife Trust, NY, USA.
• 2006–Present: Postgraduate student, Bill and Melinda Gates-Cambridge Scholar, University of Cambridge, UK.
• 2006: M.Sc. Ecology, Penn State University, USA.
• 2006: B.Sc. Mathematics, Schreyer Honours College, Penn State University, USA.
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Research Interests:

As a mathematician turned ecologist, my primary interest is in the application of quantitative tools to solving ecological problems. I am interested in not simply describing macroecological patterns, but also understanding the mechanisms and underlying drivers behind those patterns. Additionally, I am fascinated by questions of management, particularly under situations of uncertainty. My research interests cover three areas of application including 1) Predicting hotspots of emerging infectious diseases, 2) Re-thinking the species-area relationship for conservation, and 3) Optimising the monitoring and management of invasive species.

1) Anthropogenic drivers of emerging infectious disease

I am investigating the socio-economic and environmental factors driving the emergence of infectious diseases in humans on a global scale. Emerging Infectious Diseases (EIDs) are those that have recently entered the human population or increased in incidence, impact, or range. This work will extend initial research by Jones et al. (2008) to define hotspots of EIDs and begin to predict the conditions for future disease emergences. I am interested in moving from determining the underlying drivers of the patterns of disease emergence to the next step of building predictive models in order to determine how we can be more adaptive rather than reactive in our control and prevention of emerging infectious diseases.

Primary Collaborators: Kate Jones (Institute of Zoology, London), Peter Daszak (Wildlife Trust, New York), and Marc Levy (CIESIN, Columbia University, New York).

2) Global habitat loss and extinction risk: Re-thinking the Species-Area Relationship

The global crisis facing wild nature is driven in large part by changes in land use to meet growing human needs. Anthropogenic habitat loss has caused extinctions historically and is the most significant threat to species’ persistence today. Gauging the scale of this problem requires quantitative methods relating habitat area to biodiversity, which can predict the number of extinctions resulting from habitat loss. The most widely (though perhaps incorrectly), applied approach is the Species-Area Relationship (SAR), in which the number of species found in a sampled area, is proportional to the product of a constant and sample area raised to a constant power. The SAR has been used for relating habitat loss to extinction in studies ranging from attempts to quantify the global extinction crisis, through to reserve design. But although the SAR is cited as “one of community ecology’s few genuine laws, it was developed to describe how species numbers change with increasing area, and not to predict how many species will go extinct as habitat is lost. It has rarely been tested with data on real extinction rates; it ignores other factors such as climate change, hunting, invasive species, and disease, that contribute to extinction risk; and it assumes that species are uniform in their susceptibility to habitat loss. My work in this area is about testing the usefulness of the SAR for estimating extinction risks, and developing alternatives.

Supervisors: Andrew Balmford (University of Cambridge) and Rhys Green (RSPB and University of Cambridge).

3) Optimal monitoring and management of invasive species

Biological invasions by pest species pose a threat to the stability of ecosystems, both natural and managed. Monitoring and management efforts are conducted to both slow the spread of existing infestations and eradicate newly detected, isolated infestations. However, these efforts are not necessarily designed in the most economically or biologically efficient manner. I have focussed on the use of mathematical models of optimization to aid in the design of effective monitoring and management strategies for the control of a particular invader to North America, the gypsy moth (Lymantria dispar).

Supervisors: Katriona Shea (Penn State University), Andrew Liebhold (USDA Forest Service), Bryan Grenfell (Penn State University), and Ottar Bjornstad (Penn State University).
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Publications:

T. Bogich and K. Shea (2008) A state-dependent model for the optimal management of an invasive metapopulation. Ecological Applications 18(3): 748-761.

T. Bogich, A.M. Liebhold, and K. Shea (2008) To sample or eradicate? A cost minimization model for monitoring an invasive species. Journal of Applied Ecology 45: 1134-1142.

J. Peterson, C. Thomas, R. Thompson, D. Miller, W. Kendall, A. Tyre, T. Bogich, D. Brewer, S. Converse, J. Wood, and M. Runge. Adaptive management of bull trout populations in the Lemhi Basin. In preparation.