OOS 32 - Advancing Conservation Ecology through Integrative Modeling Approaches

Thursday, August 10, 2017: 8:00 AM-11:30 AM
Portland Blrm 254, Oregon Convention Center
Organizer:
Elise Zipkin, Michigan State University
Co-organizer:
Sarah Saunders, Michigan State University
Moderator:
Elise Zipkin, Michigan State University
Biodiversity loss is one of the most pressing environmental problems, impacting ecosystem functions, human and wildlife health, and community dynamics. Assessing the impacts of ongoing climate and anthropogenic-induced changes on wildlife populations requires understanding species distributions, abundances, and declines across large spatial and temporal scales. Yet, estimating the precise ecological and environmental reasons for changes in population dynamics is challenging because such species tend to be rare, which makes obtaining sufficient data for traditional analyses difficult. In particular, demographic data on small or declining populations are often scarce because collection is intermittent and typically necessitates long study periods, and sample sizes are naturally low. These conditions result in limited longitudinal data to model population viability, extrapolate inference at large scales, and detect significant changes in region-wide population trends within time frames for appropriate conservation actions. Integrative models provide a powerful method for overcoming issues of sparse, fragmentary data by utilizing all available information on a target population. Integrative modeling generally refers to the incorporation of multiple (1) data types on a single target population, (2) analytical models or methods, or (3) predictions from multiple theories into a model, thus ‘integrating’ several goals into a single modeling framework. The primary advantages of integrative frameworks are (1) the ability to compensate for variability in data collection by reducing biases inherent in a single dataset, and (2) improved precision of parameter estimates than can be obtained from separate analyses. In this session, we present emerging methods to estimate population trajectories and demographic rates for species of conservation concern using modern integrative modeling approaches. Recent applications of integrative models have led to critical advancements in population management and greater understanding of the drivers of population dynamics and declines. Our session examines the elements, advantages, novel insights, and recent extensions of integrative modeling approaches for enhancing inference on the ecology of threatened and endangered populations. Speakers will present on a variety of integrative modeling approaches applied to conservation-focused case studies, including integrated population modelling (IPM), coupled agent-based modelling, and hierarchical Bayesian modelling incorporating citizen science data. Individual talks will demonstrate how integrative models allow for better detection of population declines, prioritization of populations of conservation concern, improvement of monitoring schemes, and adjustment of management strategies. This organized oral session will serve as a general overview of options for researchers interested in applying or extending integrative modeling approaches.
8:00 AM
 Synthesizing multiple data types for biological conservation using integrated population models
Sarah P. Saunders, Michigan State University; Elise Zipkin, Michigan State University
8:20 AM
 Use of integrated population models to assess timing and intensity of density dependence in population vital rates
Todd Arnold, University of Minnesota; David N. Koons, Utah State University; Michael Schaub, Swiss Ornithological Institute
8:40 AM
 Integrated population models uncover cryptic drivers of population dynamics in migratory birds
Mitch D. Weegman, University of Missouri; Todd Arnold, University of Minnesota; David J. Hodgson, University of Exeter, Cornwall Campus; Stuart Bearhop, University of Exeter Cornwall; Anthony David Fox, Aarhus University; Russell D. Dawson, University of Northern British Columbia; David W. Winkler, Cornell Lab of Ornithology; Robert G. Clark, Environment and Climate Change Canada
9:00 AM
 IPM²: Combining integral projection and integrated population models
Floriane Plard, Swiss Ornithological Institute; Daniel Turek, Williams College; Michael Schaub, Swiss Ornithological Institute
9:40 AM
9:50 AM
 Study design considerations for integrated population models: Improving conservation and management of polar bears
Nathan J. Hostetter, USGS Patuxent Wildlife Research Center; Sarah J. Converse, USGS Washington Cooperative Fish and Wildlife Research Unit, University of Washington; Eric V. Regehr, Polar Science Center - Applied Physics Laboratory, University of Washington
10:10 AM
 Data integration to decompose detection probability and improve abundance estimation
Beth Gardner, University of Washington; Nathan J. Hostetter, USGS Patuxent Wildlife Research Center; Scott Sillett, Smithsonian Conservation Biology Institute; Theodore R. Simons, U.S. Geological Survey/North Carolina State University
10:30 AM
 Challenges and opportunities for uniting citizen science and planned surveys for predicting species distributions
Robert J. Fletcher Jr., University of Florida; Trevor Heffley, Kansas State University; Robert A. McCleery, University of Florida
10:50 AM
 Spatially hierarchical occupancy models for between-patch and within-patch dynamics
Morgan W. Tingley, University of Connecticut; Andrew N. Stillman, University of Connecticut; Robert L. Wilkerson, Institute for Bird Populations; Christine A. Howell, USDA Forest Service; Rodney B. Siegel, Institute for Bird Populations
11:10 AM
 Modeling metapopulation dynamics in coupled natural-human systems: Integrating rails, wetlands, landowners, drought, and disease
Steven R. Beissinger, University of California at Berkeley; Nathan van Schmidt, UC Berkeley; Laurie A. Hall, University of California at Berkeley; Sean M. Peterson, UC Berkeley; Lynn Huntsinger, University of California Berkeley; Tracy V, Hruska, UC Berkeley; Jose L. Oviedo, Consejo Superior de Investigaciones Científicas, Madrid; Norman L. Miller, University of California Berkeley; Tony Kovach, University of California Santa Cruz; A. Marm Kilpatrick, University of California, Santa Cruz