Macroecology Lab

New! Postdoctoral position in Tropical Forest Ecology, Trait-based ecology, and Macroecology at the University of Arizona. Starting late 2015/2016 A two-year post-doctoral position is available (start date flexible, can start as early as Fall 2016) in the group of Dr. Brian Enquist (https://brianjenquist.wordpress.com) in the Department of Ecology and Evolutionary Biology at the University of Arizona as part of an NSF Ecosystems Grant to study impacts of drought and climate change in the Amazon. The post-doc’s main responsibility will be to lead the implementation of new field experiments in the Andes and Amazon in Peru, as well as manage and analyze the data from these experiments. He/She will work closely with other post-docs and PIs on the project from UCLA (Dr. Van Savage), Carnegie Institution (Stanford/Carnegie Insituttion – Global Ecology Labs; Dr. Greg Asner), and the University of Oxford (United Kingdom; Dr. Yadvinder Mahli). As such, work may also involve theory development for trait-based models, analysis of large datasets for plant traits, as well as numerical simulations for how plant traits determine forest dynamics, carbon production. Results from this project will: (1) lead to a deeper understanding of how climate change and individual plant traits influence forests and forest ecosystems and (2) allow for projections of future productivity, diversity, and the functioning of tropical forests. Candidates are expected to be collaborative yet independent, highly motivated problem solvers who communicate well and enjoy working both in the field and in a […]

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Source: A Big Database and Big Models Pave the Way for Big Questions in Ecology

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Angert AL, SN Sheth, and JR Paul. 2011. Incorporating population variation in thermal performance into geographic range shift predictions. Integrative and Comparative Biology,  “Therefore, species-level projections of distribution might overestimate the species’ ability to persist at any given location. However, current approaches to modeling distributions often do not consider variation among populations. Here, we estimated genetically-based differences in thermal performance curves for growth among 12 populations of the scarlet monkeyflower, Mimulus cardinalis, a perennial herb of western North America. We inferred the maximum relative growth rate (RGRmax), temperature optimum (Topt), and temperature breadth (Tbreadth) for each population. We used these data to test for tradeoffs in thermal performance, generate mechanistic population-level projections of distribution under current and future climates” 

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