| Summary: | The extent and quality of estuarine habitat has a significant influence on the growth, recruitment, and survival of fish and invertebrate species. The Sustainable Fisheries Act of 1996, part of the Magnuson Stevens Fisheries Conservation and Management Act, mandated designation and monitoring of “Essential Fish Habitat” (EFH), creating the need for efficient, effective, and accurate approaches for monitoring habitat at multiple spatial scales. Because the relationships between fisheries species and their associated habitats are complex and can vary across ontogenies and regions, approaches to monitoring faunal-habitat associations are also needed to quantify the impact of EFH on fisheries stocks. However, funding limitations can prohibit monitoring fauna, habitat, and faunal-habitat associations at the multiple spatial and temporal scales necessary to accurately quantify faunal response to habitat change. The resulting information gap creates challenges to using science to inform decision making, especially in cases of reactive management decisions that are typical of state agencies. This dissertation explores the resource management potential of utilizing free, publicly available datasets to examine estuarine faunal-habitat associations at multiple spatial scales in Texas. A hierarchical approach was used to link three tiers of habitat data to faunal abundance data from Texas Parks and Wildlife Department’s (TPWD) Fisheries Independent Monitoring (FIM) program to evaluate the influence of habitat availability and quality on target species’ occurrence and abundance. Target species were selected based on their commercial and recreational importance and included Spotted Seatrout (Cynoscion nebulosus), Red Drum (Sciaenops ocellatus), Atlantic croaker (Micropogonias undulatus), Blue crab (Callinectes sapidus), Brown shrimp (Farfantepenaeus aztecus), and White shrimp (Litopenaeus setiferus). The three tiers are used to monitor fauna and associated fauna at multiple spatial and temporal scales and range from broad, ...
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