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<!DOCTYPE HTML>
<!--
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Free for personal and commercial use under the CCA 3.0 license (html5up.net/license)
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<title>Species Distribution Models</title>
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<h1><a href="index.html" id="logo">Robbie Richards</a></h1>
<p>Community ecology of infectious diseases</p>
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<li class="current"><a href="index.html">About Me</a></li>
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<a href="#">Research</a>
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<li><a href="predator-parasite.html">Predator-Parasite Interactions</a></li>
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<a href="">Spatial Heterogeneity in Disease</a>
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<li><a href="dracunculus.html">Guinea Worm in Chad</a></li>
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<h2>Species Distribution Models</h2>
<p>Developing methods to model where species are, where they aren't, and why</p>
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<section>
<span class="image featured"><img src="images/pic05.jpg" alt="" /></span>
<p>
Ecologists and managers use species distribution models to make predictions
about where species are likely to be. My work in this area focuses on the development, implementation,
and evaluation of new methods for species distribution modeling. In particular, I've focused on
the comparative performance of different methods of density-ratio estimation for estimating the relative
suitability of a habitat for a given species. I am finishing up development of an R package, in collaboration with my co-PI John Drake and Cory Merow at the University of Connecticut,
which provides easy access to these methods as well as a number of others developed in the
<a href="https://daphnia.ecology.uga.edu/drakelab/">Drake Lab </a>over the past few years.
</p>
</section>
<section>
<h3>We want to know where parasites are too</h3>
<p>
In addition to the development of new methods I strive to apply existing methods to new contexts, in particular to the spatial prediction of infectious disease risk.
So far this has spanned from the application of tried and true machine learning methods to a complicated and sensitive data set on Guinea worm infection in the dogs of Chad,
to the identification of transmission dominant host species in an ungulate community on the National Bison Range. I also lead two separate groups in this area at the Center for the Ecology of Infectious Diseases at UGA.
In our Disease Mapping Working Group we aim to provide a setting in which center members can develop their spatial modelling and mapping skills. Currently this involves developping a species distribution model for
the parasite Echinoccoccus multilocularis. In our CDC Aedes Prediction Challenge team, we use stacked species distribution models to submit monthly predictions of the probability of detection of Aedes aegypti and Aedes albopictus mosquitoes in over 150 counties
across the USA.
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