Enric Batlori

Enric Batllori Presas:  There is widespread evidence that biological systems may exhibit non-linear and divergent responses to ongoing environmental changes, and thus understanding ecosystem dynamics and feedbacks is critically important. Interactions between fire and vegetation are of particular interest because fire is a major driver of vegetation change, and vegetation properties alter fire regimes in turn. We developed a minimal fire-vegetation modeling framework to evaluate the relative influence of extrinsic and intrinsic factors on disturbance and successional dynamics in semi-arid ecosystems such as Mediterranean-type biomes.

Ke Bi: I have a broad interest in evolutionary genomics. I am passionate about understanding the relative contribution of natural selection in shaping the genetic variation and genetic basis/mechanisms of adaptive evolution. In particular, I am interested in applying next generation sequencing in population and comparative genomics to understand demographic and evolutionary response to environmental change, especially the recent climate change.

Scott Fay:  Change Forecasting

Kim La Pierre

Kim La Pierre: I am studying the relationship between invasive legumes and their associated rhizobial symbionts in the Bay Area. The goals of this project are to identify which rhizobia associate with the legumes in their native versus invasive range, whether the invaders alter the soil microbial communities, and whether common management practices can aid in returning the soil community to its native state.

Sean Maher

Sean Maher: I am building models to compare how the small mammal community of the Sierra Nevada has changed in the 20th century. Using data from the Grinnell Resurvey Project, I am analyzing the effect of climate on extinctions using a multispecies occupancy model and characterizing response patterns within the community.

Patrick McIntyre:  Berkeley EcoInformatics Engine

Stephanie Porter: Change Forecasting

Karthik Ram

Karthik Ram: I am a quantitative ecologist broadly interested in the structure and dynamics of food webs in terrestrial systems. I am also the project lead on the rOpenSci project, an effort at aimed at fostering data-driven, reproducible science in ecology and evolution.

Santiago Ramirez:  Change Forecasting

Giovanni Rapacciuolo

Giovanni Rapacciuolo: I study past and ongoing impacts of global environmental change on biodiversity and ecosystems to improve how well we can predict future impacts. My research involves developing novel approaches to harness large datasets that hold information on the historical and current state of biological systems - such as wildlife surveys and natural history museum collections - together with data on changes in climate, hydrology, and land use.

Amber Sciligo: The discovery work I've conducted has allowed our research team to utilize honeybee and bumble bee specimens from multiple museum collections across California.  With these bees, we are able to extract information about the composition of their diets, atmospheric nitrogen and water supply through isotopic quantification from their exoskeletons, as well as changes in their genetic makeup and diseases.  Our plan is to correlate these results with changes in urbanization and climate to see if we have any matches in trends between changes in the bees and changes in their landscape over a 100 year time period.

Jenn Weaver

Jenn Weaver: I am broadly interested in building models of our changing ecosystems, with a focus on invasive species, climate change and land use change, and within the larger framework of conservation and food security. Specifically, I am testing how we can build more accurate species distribution models by including species interactions, dispersal, and other variables which may affect species interactions such as phenology.

Adam Zeilinger

Adam Zeilinger: I am interested in using historical data and natural history collections to understand the responses of agricultural pest populations to climate change in California.  Improved understanding of the responses of pests to climate change in the past will improve predictions of their responses under future climate change.