Collaborative Research: Incorporating physiological variation in mechanistic range models for ecological forecasting

Project: Research project

Description

Aim #1: Mechanistic models of activity Currently, our collaborative group is developing mechanistic models that will be used to predict species ranges (sensu Buckley et al 2010). A major variable in such models is the potential duration of activity, which limits foraging and energetics on daily and annual bases. Currently, our models predict the potential for activity from climatic and geospatial data resolved to approximately 1-km. We assume that animals can be active when the range of operative environmental temperatures overlaps with the range of preferred body temperatures. Once the duration of activity is determined for individuals within a population, we model whether individuals can meet their energetic requirements for survival and reproduction. These estimates, in turn, determine whether a population might persist by explicitly linking energetics to demography. To date, such models (including ours) assume that habitats are thermally homogeneous, even though natural habitats exhibit substantial heterogeneity. Indeed, collaborative work with Dr. Sears suggests that the spatial heterogeneity and configuration of environmental temperatures determine the energetic consequences of activity (see Chapter 4 in Angilletta 2009). Dr. Sears will work with my group to quantify how activity might depend on the spatial resolution of climatic and geospatial data. Dr. Sears is an ideal collaborator for this endeavor because he uses computational approaches to understand how thermal heterogeneity through space and time influences thermoregulatory behavior. Typically, his models estimate environmental temperatures at fine spatial scales, such that thermal heterogeneity can be modeled within home ranges of individuals (Sears et al 2011). This approach contrasts our approach, which estimates environmental temperatures at scales much larger than home ranges. Dr. Sears will work closely with a postdoctoral researcher, Ofir Levy, to implement his fine-scale approach with our large-scale framework of modeling. Specifically, using data from our ongoing study, Dr. Sears and Dr. Levy will compare predictions about potential activity derived from data collected at various spatial scales. Moreover, they will quantify the effect of thermal heterogeneity on estimates of activity by resampling fine-scale geospatial data at coarser scales (ranging from 1 m to 1 km). From these simulations, we hope to determine the minimal spatial scale over which one can reliably estimate potential activity. Aim #2: Developing evolutionary algorithms for dynamic environments Another goal of our Macrosystems project is to produce dynamic models of species ranges that incorporate local adaptation of thermal physiology. Recent studies have examined the potential effects that such phenotypes might have on species persistence in light of ongoing climatic change (Atkins et al. 2010; Deutsch et al 2008, Tewksbury et al 2008, Sinervo et al 2010). These results suggest that the degree to which thermal physiology is adapted to local climates will determine a species risk of extinction. In light of these results, we proposed to optimize physiological parameters in our models to both contemporary and future climates, and then examine how local adaptation would affect the geographic range of a species. To optimize physiological parameters in our models, we will use evolutionary algorithms (Eiben and Smith 2003). Evolutionary algorithms are particularly useful for studying the adaption of complex traits. Yet, implementing evolutionary algorithms in changing environments can be challenging (Morrison 2010; Tomassini 2005), because models using evolutionary algorithms typically optimize parameters under static conditions (e.g., constant temperatures or predictable thermal cycles). During his participation in a recent NCEAS working group, Dr. Sears gained experience using evolutionary algorithms to explore thermal adaptation during climate change. Therefore, Dr. Sears is well positioned to collaborate with researchers in my lab and those in my Co-PIs lab at UT Austin to develop evolutionary algorithms equipped for optimization in dynamic environments. The algorithms will be based on those developed recently by computer scientists (e.g., see Morrison 2010).

Description

The purpose of our Macrosystems project is to model the factors that shape the geographic ranges of ectothermic species. Our models will be based on mechanisms that constrain activity, growth and reproduction. By parameterizing a model with data for a geographically widespread species, we hope to validate the model and predict impacts of anthropogenic climate change. A combination of field and lab work is required to parameterize the model. Field work involves sampling lizards from populations throughout the United States. Lab work involves measuring behavioral and physiological responses to temperature. Because these thermal responses drive the predictions of the model, empirical estimates for populations of interest are integral to the projects success. The undergraduate student will be actively engaged in the field and lab components of the project. First, the student will visit field sites and assist with collecting study organisms. During this early phase of the research experience, the student will learn about natural history and field methods (including capture and handling of lizards). Second, the student will assist with lab studies of digestive performance, preferred body temperatures, and thermal tolerances. During this later phase, the student will learn about animal husbandry, experimental design, thermoregulatory behavior, and data analysis. To prepare for these activities, the student will receive training from me and my graduate student. Initially, the student will assist us with all procedures; after this period of training, the student will conduct basic procedures independently. In addition to these activities, the student will design and conduct an experiment that complements the work that we have already planned. Although the student will have some flexibility to design this project, I will provide an example here to illustrate the potential outcome. The models that we are developing require knowledge of the thermal sensitivity of physiological processes. The student would be asked to consider which physiological processes should affect the fitness of an ectothermic animal. Based on the students considerations, we will design a project to quantify the thermal sensitivity of this process. For example, if the student suggests that foraging is important process, we could design a study to quantify the effect of temperature on capture success and feeding rate. We might also measure the thermal sensitivity of sprinting speed, since lizards sprint short distances to capture their food. These data would then be incorporated in our computer model of population dynamics. Because our model will predict the geographic boundaries of species, the student will learn how biologists confront theory with data to understand ecological phenomena. Assuming that the student will successfully complete the experiment, I will provide support for this student to present the results at the annual meeting of the Society for Integrative ad Comparative Biology (January 2013).

Description

The REU supplement would enable an undergraduate student to participate in field and lab research during the summer of 2013. Below, I describe the specific nature of this students involvement, my experience with mentoring students, and the events that led me to seek supplemental support from the NSF. The Nature of Undergraduate Participation The purpose of our Macrosystems project is to model the factors that shape the geographic ranges of ectothermic species. Our models will be based on mechanisms that constrain activity, growth and reproduction. By parameterizing a model with data for a geographically widespread species, we hope to validate the model and predict impacts of anthropogenic climate change. A combination of field and lab work is required to parameterize the model. Field work involves sampling lizards from populations throughout the United States. Lab work involves measuring behavioral and physiological responses to temperature. Because these thermal responses drive the predictions of the model, empirical estimates for populations of interest are integral to the projects success. The undergraduate student will be actively engaged in the field and lab components of the project. First, the student will visit field sites and assist with collecting study organisms. During this early phase of the research experience, the student will learn about natural history and field methods (including capture and handling of lizards). Second, the student will assist with lab studies of thermal tolerances. During this later phase, the student will learn about animal husbandry, experimental design, and data analysis. To prepare for these activities, the student will receive training from me and my graduate student. Initially, the student will assist us with all procedures; after this period of training, the student will conduct basic procedures independently. In addition to these activities, the student will design and conduct an experiment that complements the work that we have already planned. Although the student will have some flexibility to design this project, I will provide an example here to illustrate the potential outcome. The models that we are developing require knowledge of the thermal sensitivity of physiological processes. The student would be asked to consider which physiological processes should affect the fitness of an ectothermic animal. Based on the students considerations, we will design a project to quantify the thermal sensitivity of this process. For example, if the student suggests that foraging is important process, we could design a study to quantify the effect of temperature on capture success and feeding rate. We might also measure the thermal sensitivity of sprinting speed, since lizards sprint short distances to capture their food. These data would then be incorporated in our computer model of population dynamics. Because our model will predict the geographic boundaries of species, the student will learn how biologists confront theory with data to understand ecological phenomena. Assuming that the student will successfully complete the experiment, I will provide support for this student to present the C-2 results at the annual meeting of the Society for Integrative ad Comparative Biology (January 2014). This January, four undergraduate attended this meeting as coauthors on a talk that stemmed from their summer research in 2012. Experience of the PI in Mentoring Undergraduate Research Since earning my Ph.D. in 1999, I have mentored 41 undergraduates, including 15 women, 1 African-American, and 2 Hispanic-Americans. Many of these students have entered or completed graduate programs in biology, medicine, or veterinary science. Also, 17 undergraduate students have coauthored papers for publication in peer-reviewed journals. Process and Criteria for Selecting a Student I follow a multi-step process to identify promising student for research activities in my lab. At the beginning of each academic year, I screen undergraduates in my introductory biology course for aptitude and interest in ecological research. Of my 350 students, about 50 students will express an initial interest in a research position in my laboratory. From this set of candidates, I target those individuals who show great enthusiasm for learning or who excel in their exams. I then meet individually with these students to discuss their career goals and research interests. Those students whose interests and goals seem most compatible with my own are offered volunteer positions; the others are directed to more suitable labs. Once they begin in my lab, undergrads will shadow a graduate student or postdoctoral researcher, helping with ongoing experiments and training to perform basic lab procedures. This year, I am fortunate to have attracted an excellent student, Kwasi Boateng, who has expressed an interested in a summer research experience. Kwasi ranked 9th among 384 students in my introductory class, earning an A+ overall. He is also an African-American who was born in Ghana, and thus adds to the cultural diversity of my lab. For these reasons, I am keen to keep Kwasi engaged in research for the remainder of his time at Arizona State University.

Description

This request for supplemental funding is to cover travel expenses for a postdoctoral researcher (Ofir Levy) and a project data manager (Tim Keitt) to participate in the recent Macrosystems Biology PI Workshop. This workshop was held in Boulder, Colorado on March 11-14, 2012. Travel expenses include airfare, lodging, subsistence (per diem) and ground transporation.
StatusFinished
Effective start/end date5/1/114/30/15

Funding

  • NSF: Directorate for Biological Sciences (BIO): $608,645.00

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student
lizard
temperature
energetics
ecological phenomena
animal husbandry
African American
field method
local adaptation
body temperature
physiological response
behavioral response
home range
experiment
experimental design