All posts by rhijmans

Landscape in transition? Climate change and disturbance regimes in Greater Yellowstone

Ecology and Evolution seminar / Storer Life Sciences Endownment, Major Issues in Modern Biology lecture

Monica Turner,  University of Wisconsin
Landscape in transition? Climate change and disturbance regimes in Greater Yellowstone
Thursday, February 26, 4:10 – 5:30 pm
1003 Giedt Hall

Professor Turner is internationally recognized for her precedent setting research in landscape ecology, which emphasizes causes and consequences of spatial heterogeneity in ecological systems, focusing primarily on forest ecosystems. She has conducted research on disturbance regimes, vegetation dynamics, nutrient cycling, and climate change in Greater Yellowstone for over 25 years, including long-term studies of the 1988 Yellowstone Fires. Other current research examines how climate change may alter the frequency of large fires and, in turn, change vegetation patterns and carbon storage across landscapes of the northern Rocky Mountains. Turner also studies land-water interactions in Wisconsin, effects of current and past land use on Southern Appalachian forest landscapes, and spatial patterns of ecosystem services. She has published over 220 scientific papers; authored or edited six books, including LANDSCAPE ECOLOGY IN THEORY AND PRACTICE; and is co-editor in chief of ECOSYSTEMS. Turner was elected to the US National Academy of Sciences in 2004, and she received both the ECI Prize in Terrestrial Ecology and the Ecological Society of America’s Robert H. MacArthur Award in 2008. She is currently President-elect of the Ecological Society of America.

Spatial food-web dynamics in the Serengeti ecosystem

Ecology and Evolution seminar

John Fryxell,  University of Guelph
Spatial food-web dynamics in the Serengeti ecosystem
Thursday, January 29, 4:10 – 5:30 pm
1003 Giedt Hall

My research focuses on interactions between behavior and consumer-resource dynamics. A mix of theoretical and empirical approaches is used to consider the dynamics of specific systems. Theoretical questions of interest include herbivore and carnivore movement in relation to resource availability and predation risk, optimal diet, patch selection, and dispersal patterns in heterogeneous environments, the effect of social interference and territoriality on consumer-resource interactions, and impacts of harvesting by humans on fish and mammal populations.

Empirical work has been concentrated on 3 different terrestrial ecosystems over the past decade: large herbivores and carnivores in Serengeti National Park (Tanzania), woodland caribou, wolves, and moose in boreal forests of northern Ontario (Canada), and mustelid carnivores and other small mammals in boreal forests of northern Ontario. In each case, my graduate students and I conduct detailed field and experimental studies of behavioral ecology of both predators and prey. Theoretical models are then used to assess the implications of behavioral strategies on population and community dynamics and model predictions are then tested against long-term observational data from terrestrial ecosystems.

Kevin McCann and I recently initiated a collaborative research program on spatial food web dynamics of phytoplankton and zooplankton populations in massive aquatic mesocosms in the new Limnotron facility at the Biodiversity Institute of Ontario. Initial experiments relate to resource- vs predator- and ratio-dependent functional and numerical responses, responses of predator and algal populations to pulsed versus continuous nutrient influx, resource- and density-dependent diffusion patterns by zooplankton and phytoplankton, and spatial pattern formation in relation to population fluctuations.

An ongoing applied research interest relates to sustainable harvesting of fish and mammal populations. Key questions relate to long-term stability of harvested populations due to dynamic variation in harvester effort, effects of bioeconomic dynamics on long-term stability of fish stocks and prices, and spatial processes in harvested populations with and without no-harvest reserves.

Robust, Ambiguity Faithful (RAF) classification

Paul Gader, University of Florida
Robust, Ambiguity Faithful (RAF) classification
Monday, January 26,  2:00- 3:00 PM
3001 Plant and Environmental Sciences

Researchers have demonstrated a variety of classifiers that are able to achieve excellent performance on many different standardized data sets. These classifiers are usually evaluated using the general methodology: Given a set of feature vector samples, X = {x1, …, xN}, that all have known class labels from m classes C1, …, Cm, do the following one or more times: (1) Estimate parameters of a classifier, fi, using a subset of X and (2) Evaluate the classification accuracy of fi using a different, disjoint subset of X by evaluating how often a data sample is assigned to the correct class. However, this evaluation strategy and mode of development ignore very important issues when building classifiers for fielded systems. One issue is that in fielded systems, classifiers are generally part of a larger system and binary decisions are often not required. The “Principle of Least Commitment” espoused by the computer vision pioneer David Marr in 1982 applies. Therefore, classifiers should produce more information than a class label. This information can be represented using probability or possibility distributions. Classifiers should be able to estimate possibility that an input pattern is a sample of one of the classes of interest or is an outlier. This capability is referred to here as robustness. The other issue is that some patterns are truly ambiguous; no distinction can be made between them based on the feature vectors. It is possible that contextual or multi-sensor cues can be used to resolve the ambiguities. Issues involved in designing RAF classifiers are discussed. Examples are given on real-world problems, including handwritten word recognition, landmine detection, and remote sensing.

Paul Gader has been devising pattern recognition algorithms since 1984. He received a Ph.D. in Math in 1986 for parallelizing image processing algorithms. Since then, he has focused on applying theory to real problems. He became a leading figure in the application areas of handwriting recognition and landmine detection and is becoming one in hyperspectral image analysis. He led the development of handwritten character and word recognizers that performed in the top 5 and top 1 in a NIST competition. In 1998, he and H. Frigui devised a real-time Ground Penetrating Radar landmine detection algorithm that was a top performer in blind field testing. He was Technical Director of an Army Demining MURI for 2 years. He and D. Ho developed algorithms for hand-held mine detection system currently in use by the U. S. Army. He participated led many landmine/IED detection projects using data from Acoustic/Seismic, EMI, FLIR, SAR, and LWIR and VISNIR/SWIR sensors. He led teams that studied and implemented Hidden Markov Model and Possibilistic detectors in real-time on a Husky Mine Detection System (HMDS). HMDS was fielded in Afghanistan. The HMDS with his team’s algorithms, is featured in National Geographic Television program: “Bomb Hunters: Afghanistan”.
He has been researching hyperspectral algorithms since 2002. He was general chair of the IEEE Workshop on Hyperspectral Image and Signal Processing in June 2013. Dr. Gader has published 90 journal and over 300 total papers, (was) an Associate Editor of IEEE Geoscience and Remote Sensing Letters (before becoming Chair), led an ad-hoc committee on Standardized Algorithms, Data, and Evaluation (SADE), is a U. of Florida Research Foundation Professor, Chair of the CISE department, and an IEEE Fellow.

More Data, More People, More Conflicts

Center for Science and Innovation Studies Seminar

Who: Jean-Christophe Plantin
What:  More Data, More People, More Conflicts. The Power of Visualization Technologies in a Big Data Era
When: Tuesday January 27th from 4:10 – 5:30 PM
Where: 126 Voorhies
More info


There has been recently an increase in sources of digital data available, either coming from governmental “open data,” social media companies, or crowdsourced initiatives. While these “big data” are often characterized by their massive size, another important factor is the participation of new and potentially conflicting actors in collecting, processing, and disseminating these data. Using ethnographic methods and social network analysis, this talk will explore the political and epistemological tensions emerging from this larger participation. It will present two case studies where visualization technologies play a key role in the conflict between traditional stakeholders and newcomers for control over data. The first case study focuses on mapping technologies and citizen science: it will show how, after the nuclear catastrophe at the Fukushima Daiichi power plant in Japan in March 11, 2011, activists used digital maps to challenge the control of experts and credentialed institutions in regards to radiation data, and to keep watch over the government’s crisis response and radiation measurements. The second case study uses the example of Twitter data to study big data in the humanities and social sciences. It will review how web-based data sources afford original disciplinary collaborations, but simultaneously create methodological tensions between research practices and corporate sources of data. The conclusion will present a future research agenda analyzing the social consequences of the production and circulation of online personal data.

Jean-Christophe Plantin is currently a Postdoctoral Research Fellow at the University of Michigan. His research investigates information systems and visualization technologies and their use for civic participation. He is the author of Participatory Mapping: New Data, New Cartography (Wiley, 2014).