December 5, 2019
5:00 TLSB 1100
" Graduate Student Presentations "
Department of Ecology and Evolutionary Biology,
Barber Lab, UCLA
“Investigating Patterns of Larval Fish Community Dynamics Over the Past Two Decades Using a Novel Application of Environmental DNA Metabarcoding”
Plankton samples track stock biomass and ecosystem dynamics worldwide and are a critical component for monitoring and managing U.S. fisheries and marine ecosystems. Ichthyoplankton collected by the California Cooperative Oceanic Fisheries Investigations (CalCOFI) program helps inform rockfish and clupeoids stock assessments and fish ecosystem status within the California Current Ecosystem. However, traditional methods for identifying plankton are time and labor intensive, resulting in a backlog of samples that need to be processed. A promising new technique for efficiently quantifying species from plankton samples is high throughput sequencing of dissociated DNA from the ethanol-preservation buffer. This cost-effective and non-destructive technique utilizes DNA shed from plankton into the preservation buffer, thus allowing researchers to extract, amplify, sequence, identify, and potentially quantify DNA abundance of species without damaging archived samples. We use novel environmental DNA (eDNA) techniques to identify larval fish and zooplankton species from ethanol-preserved plankton samples collected by the CalCOFI program at 4 stations likely exposed to different oceanographic water masses between 1996 and 2019. Our aims are to 1) evaluate the efficacy of eDNA to accurately identify larval fishes by comparing genetic and morphologically identified samples; and 2) investigate the long-term dynamics of Southern California ichthyoplankton and zooplankton communities in response to climate forcing. We successfully amplified DNA from all stations and time points in triplicate using 4 metabarcodes targeting fish (12S), Sebastes (CytB), and zooplankton (CO1 and 16S). We test how fish and zooplankton biodiversity and assemblage structure respond to oceanographic dynamics including the 1997-98 El Niño and record-warm 2014-2016 marine heatwave. This project has the potential to greatly augment traditional ichthyoplankton processing and provide critical information on key ecosystem component dynamics in near real-time.
Department of Ecology and Evolutionary Biology,
Sack Lab, UCLA
“Functional traits predict climate distributions of species and ecosystems across the California Floristic Province”
The power of functional traits to explain and predict the range of climates in which species survive and compete has rarely been tested at wide biogeographic scales. The California Floristic Province (CA-FP) is highly diverse in its regional climates and native ecosystems, their constituent plant species, and, given increasing extreme droughts, a high vulnerability to climate change. Determining the ability of functional traits to predict native climate ranges is a necessary step toward predicting impacts of climate change on species and ecosystems. We tested the ability of functional traits to predict climate distributions of species from ecosystems across a gradient of aridity in the CA-FP. We measured 10 functional traits expected to contribute to drought tolerance, resource economics and life history: turgor loss point (pTLP), carbon isotope discrimination (D13C), height (H), leaf area (LA), leaf mass per area (LMA), wood density (WD), and foliar concentrations of nitrogen and carbon per area (Narea, Carea) and mass (Nmass, Cmass). We obtained climate envelopes for all species based on species range data from GBIF (Global Biodiversity Information Facility), using 35 environmental variables related to temperature, precipitation, ecosystem aridity, soil and topology. Traits differed strongly among ecosystems. Drought tolerance traits were strongly linked with ecosystem aridity; species from the drier sites had lower pTLP and D13C and higher WD (p<0.001). Traits related to resource economics and life history more weakly separated drier and wetter sites; species from the wettest site had larger H, LA and Cmass and lower LMA, Narea, Nmass, and Carea than species from the driest site (p<0.001). Across species, statistical models based on species’ traits predicted of the mean climate of species’ natural range, especially D13C, Cmass and Narea (R2 = 0.41-0.62; p<0.001). Further, 18-88% of the residual variance within site could be explained by the difference between the species’ mean climate and that of the sites at which traits were measured (p<0.001). Variation in aridity across the CA-FP has driven extensive trait diversification across ecosystems and convergence among species within ecosystems. Thus, traits have strong power to predict diverse species’ climate distributions across the region.
Thursday, December 5, 2019 @ 5 PM
1100 Terasaki Life Sciences Building [TLSB]