NSF Award Abstract:
Understanding how changes in environmental conditions affect biota in the oceans is critically important for maintaining biodiversity and sustainable fisheries and projecting potential responses to future climate scenarios. The aims of this project are to determine how the distribution of fish and invertebrates has changed over time along the Texas coast and to assess the extent to which these changes are attributable to changes in local environmental conditions, such as sea surface temperature, coastal sea level, salinity, turbidity, and river discharge rate. Studies of biological systems in the Gulf of Mexico are lacking compared to coastal research in the Atlantic and Pacific oceans. Addressing these regional knowledge gaps is crucial because the Gulf of Mexico supports a wide diversity of temperate and tropical species that are ecologically and economically important. Poleward shifts in species distributions associated with increasing sea surface temperature have been observed along the Atlantic and Pacific coasts. In contrast, the northern edge of the Gulf of Mexico is bound by land that places biogeographic constraints on the potential responses of coastal organisms to changing environmental conditions. This project will use advanced statistical methods to analyze long-term species composition data for the northwestern Gulf of Mexico and characterize past relationships of species composition and local environmental conditions. These findings will help guide the development of predictive models to assess potential biological responses to projected environmental conditions. Research results will be shared with local and state resource agencies responsible for managing coastal fisheries. As an integral part of this project, a three-level (faculty-graduate-undergraduate) mentoring system will be established to promote diversity in science through undergraduate and graduate training. Undergraduate students will be recruited through the Texas A&M University Chapter of the Society for Advancement of Chicano and Native Americans in Science (SACNAS), for which the principal investigator is currently a faculty advisor. Both graduate and undergraduate students will work as a team on the project and develop quantitative data analysis and other general scientific skills. Finally, the research program will be used as a case study for establishing mentoring systems for promoting diversity in science.
The availability of long-term species composition data provides a unique opportunity to substantially improve knowledge toward understanding the effects of climate change on marine organisms in a low latitude system. This project will examine species composition data for eight bays distributed over approximately 650 km of the Texas coast; comprehensive data of this type are uncommon elsewhere. The biological data have been collected over 35-40 years as part of a long-term monitoring program and includes information on more than 1000 species of fish and invertebrates. This unique dataset will be analyzed using modern statistical approaches, including occupancy data analysis, co-integration method, and state-space vector autoregressive modeling. These methods overcome common difficulties in statistical analyses, including datasets having multi-collinearity among independent variables and those involving non-stationarity. Based on the results of the statistical analyses, models enabling the prediction of species composition under projected local environmental conditions will be developed. As part of this project, undergraduate and graduate students will acquire expertise in contemporary analytical methods, research findings will be broadly shared with both the academic and resource management communities, and computational code will be made publically available. This project will provide better understanding of the effects of environmental conditions on fish and invertebrate distribution and will provide valuable information for improved fishery management and conservation efforts under changing environmental conditions.
Dataset | Latest Version Date | Current State |
---|---|---|
Gill Net Catch Data in Bays along Texas Coast from 1986 to 2018 | 2020-12-07 | Final no updates expected |
Bag Seine Catch Data in Bays along the Texas Coast from 1982 to 2016 | 2019-07-15 | Final no updates expected |
Principal Investigator: Masami Fujiwara
Texas A&M University (TAMU)
Contact: Masami Fujiwara
Texas A&M University (TAMU)
Data Management Plan received by BCO-DMO on 13 Jun 2017 (223.44 KB)
06/13/2017