HRI Seminar Series - Dr. Paul Montagna

"Long-Term Benthic Data in Three Basins Can be Used For Adaptive Management of Inflow Standards"

DR. PAUL MONTAGNA
HRI CHAIR FOR HYDROECOLOGY
TEXAS A&M UNIVERSITY - CORPUS CHRISTI

A long-term dataset of benthos (i.e., bottom-dwelling) species and community data collected from Lavaca and Matagorda Bays (Lavaca-Colorado Estuary), San Antonio Bay (Guadalupe Estuary), and Nueces and Corpus Christi Bays (Nueces Estuary) was used to identify the freshwater inflow needs to maintain a “sound ecological environment.” Benthic organisms are ideal bioindicators of freshwater inflow effects on bays and estuaries because they are fixed in space and integrate ephemeral processes in the over-lying water column over long periods of time. The bay systems have different long-term characteristic fauna that reflects the long-term average salinity conditions in each bay system.  San Antonio Bay is small, so it has a lower long-term average salinity than Lavaca Bay even though they have about the same amounts of freshwater inflow.  The San Antonio Bay community has a higher contribution of mollusks, which are freshwater indicators, than Lavaca Bay, and much higher than Nueces Bay.  Within systems, the secondary bays have distinct communities compared to the primary bays because the secondary bays are more oligohaline or brackish than marine influenced primary bays.  Response after Hurricane Harvey indicates that benthos are resilient to flood disturbance and recover over time.  The relationship between salinity and community structure can be used to evaluate the effectiveness of current freshwater inflow standards in three basin-bay systems along the mid-Texas coast.

Dr. Montagna is a marine ecologist whose research focuses on how organisms regulate and respond to conditions in marine ecosystems and coastal environments.  This work is critical in guiding ocean and coastal assessment and resource management decisions.  His research tools include benthic structure and function, biogeochemistry, ecoinformatics, ecosystem modeling, and integrating natural science and socioeconomics.

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