Project 1. Ecological impacts of species invasions on nutrient dynamics (S. Ramaswami, Computer Science & A.L. González, Biology)
Background. Biological invasions are one of the major drivers of environmental change (Vitousek 1997, Simberloff et al. 2012, Katsanevakis 2014). Considerable research has attempted to uncover the ecosystem-level consequences of invasive organisms, particularly plants (Liao et al. 2007, Vilà et al. 2011). Invasive organisms may cause severe impacts on ecosystem nutrient dynamics, however, different results suggest that a trait-based approach may be key for a comprehensive study of ecosystem-level responses to bio-invasions (Suding et al. 2008,Ehrenfeld 2010, Simberloff et al. 2012). Meta-analysis approach has become a powerful tool for knowledge synthesis (Osenberg et al. 1999, Lortie et al. 2012), and especially useful when studies show contrasting results.
Research. In this project the student will perform a meta-analysis on the effects of invasive invertebrates and vertebrates on a wide range of ecosystem processes: pools and cycles of carbon, nitrogen, and phosphorus pools. Specifically, the REU student will conduct a meta-analysis to examine: (1) To what extend carbon (C), nitrogen (N), and phosphorus (P) dynamics are altered by invasive species (vertebrates and invertebrates) in comparison with native species (or in comparison with no invasion); (2) Whether the impact of invasive species on C, N and P cycling vary across main functional groups (vertebrates vs. invertebrates) and habitats (freshwater vs. terrestrial); and (3) Relate stoichiometric traits to the impact on ecosystem processes.
Student activities. In this project, the REU student would learn how to design, implement, and manage computerized databases, prepare databases for statistical analysis, and perform a quantitative meta-analysis to compare ecosystem-level impacts of invasive species. Specifically, the student will be exposed to principles of meta-analysis technique; protocol development; search strategies; data mining methods; large database quality assessment; meta-analytic methods; and applications of meta-analysis in ecology and evolution.