Between 1988 and 2014, otter trawls, seine nets, and plankton nets were deployed along the salinity gradients of 18 estuaries by the University of South Florida and the Florida Fish and Wildlife Research Institute (FWRI, a research branch of the Florida Fish and Wildlife Conservation Commission). The purpose of these surveys was to document the responses of aquatic estuarine biota to variation in the quantity and quality of freshwater inflows that were being managed by the Southwest Florida Water Management District (SWFWMD).
In the present analyses, four community types collected by these gears were compared with a diversity of habitat factors to identify the factors with the greatest influence on beta diversity, and also to identify the factors that were most influential to important prey species and economically important species. The four community types were (1) plankton-net invertebrates, (2) plankton-net ichthyoplankton, (3) seine nekton, and (4) trawl nekton. The habitat factors were (1) vertical profiles of salinity, dissolved oxygen, pH, and water temperature taken at the time of the biological collections, (2) various characterizations of local habitat associated with seine and trawl deployments, (3) chlorophyll a, color, and turbidity data obtained from the STORET database (US Environmental Protection Agency), and (4) data that characterize the effects of freshwater inflow on different estuarine zones, including factors for freshwater inflow, freshwater turnover time, and temporal instability in freshwater inflow (flashiness). Only 13 of the 18 estuaries had data that were comprehensive enough to allow habitat-factor analysis.
An existing study had performed distance-based redundancy analysis (dbRDA) and principle component analysis (PCA) for these data within 78 estuarine survey zones that were composited together (i.e., regardless of estuary of origin). Based on that study’s findings, the communities of primarily spring-fed and primarily surface-fed estuaries were analyzed separately in the present study. Analysis was also performed with the habitat factors grouped into three categories (water management, restoration, and water quality) based on their ability to be directly modified by different management sectors.
For an analysis of beta diversity interactions with habitat factors, dbRDA (called distance-based linear modeling (DistLM) in the PRIMER software) was performed using PRIMER 7 software (Quest Research Limited, Auckland, NZ). The dbRDA indicated pH, salinity, and distance to the Gulf of Mexico (distance-to-GOM) usually explained the most variation in the biotic data. These results were compared with partial dbRDA using the Akaike Information Criterion (AIC) as the model selection criterion with distance-to-GOM held as a covariate to reduce the effect of differences in the connectivity of marine-derived organisms to the different estuaries; distance-to-GOM explained between 8.46% and 32.4% of the variation in beta diversity. Even with the variation from distance-to-GOM removed, salinity was still selected as most influential factor, explaining up to an additional 23.7% of the variation in beta diversity. Factors associated with the water-management sector were most influential (primarily salinity), followed by factors associated with the restoration sector (primarily factors that describe shoreline type and bottom type).
For the analysis of individual species, canonical analysis of principal coordinates (CAP) was performed to test for significant difference in community structure between groups of sites that represented high and low levels of each factor. For those communities that were significantly different, an indicator value (IndVal) was calculated for each species for high and low levels of each factor. Among species with significant IndVal for high or low levels of at least one factor, emphasis was given to important prey species (polychaetes, copepods, mysids, shrimps, bay anchovy juveniles, and gammaridean amphipods) and to species of economic importance, including adults, larvae and juveniles of commercial and recreational fishes, pink shrimp, and blue crab. Shrimps, copepods and mysids were all associated with estuarine zones that had low percentages of wooded or lawn-type shoreline, a factor that may serve as a proxy for flood conditions, as lawns or trees were usually only sampled with seines at high water elevations and in the freshwater reaches of the estuaries. Many copepod and shrimp species were strongly associated with high flushing times, which suggests that if flushing times were too short in an estuarine zone, then these species or their prey would be flushed out.
Multiple regression analysis was performed on each of the selected indicator species, using AIC as a selection criterion and distance-to-GOM as a covariate. As might be expected, the apparent influences of different habitat factors varied from species to species, but there were some general patterns. For prey species in both spring-fed and surface-fed estuaries, pH and flushing time explained a significant amount of variation. In surface-fed estuaries, the presence of oysters on the bottom also had a positive effect for many prey species. For economically important species, depth was important in both spring-fed and surface-fed estuaries. This suggested the importance of maintaining large, shallow areas, particularly in surface-fed estuaries. Another important factor in spring-fed estuaries was the percent coverage of the bottom with sand; however, a mixture of positive and negative coefficients on this factor suggested the importance of substrate variety. In surface-fed estuaries, flashiness also often explained substantial variation for many economically important species, usually with positive coefficients, possibly due to the importance of alternation between nutrient-loading and high-primary-productivity periods. When comparing the three management sectors, the restoration sector was the most explanatory.
Several factors were averaged over entire estuaries due to data scarcity or due to the nature of the factors themselves. Specifically, the STORET data for chlorophyll, color, and turbidity was inconsistently distributed with in the survey areas and was not collected at the same time as the biological samples. Moreover, certain water-management factors such as freshwater-inflow rate and flashiness are inherently less dimensional than other factors, and could only be represented by a single observation (i.e., no spatial variation) at any point in time. Due to concern that reduced spatiotemporal concurrence/dimensionality was masking the influence of habitat factors, the community analysis was repeated after representing each estuary with a single value for each habitat factor. We found that far fewer factors were selected in this analysis; salinity was only factor selected from the water-management factors.
Overall, the factor that explained the most variation most often was the presence of emergent vegetation on the shoreline. This factor is a good proxy for urban development (more developed areas have lower levels of emergent vegetation on the shoreline). Unlike the previous analysis, the restoration sector overwhelmingly had the highest R2 values compared with other management sectors. In general, these results indicate the seeming importance of salinity in the previous analysis was likely because it had a higher resolution compared with many other factors, and that the lack of resolution homogeneity did influence the results.
Of the habitat factors determined to be most influential with the analysis of communities and individual species (salinity, pH, emergent vegetation and lawn-and-trees shoreline types, oyster and sand bottom types, depth, flashiness, and flushing time) most were part of an estuarine gradient with high values at one end of the estuary with a gradual shift to low values at the other end. Since many of the analyzed species also showed a gradient distribution across the estuary, the abundance and community patterns could be explained by any of the habitat factors with that same gradient pattern. Therefore, there is a certain limitation to determining which factors are most influential in estuaries using this type of regression-based analysis. Three selected factors that do not have a strong estuarine gradient pattern are the sand bottom type, depth, and flashiness. In particular, flashiness has a single value for each estuary so it is incapable of following the estuarine gradient. This suggests that flashiness has an important process-based role that merits further investigation of its effect on estuarine species.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-7740 |
| Date | 03 November 2016 |
| Creators | Michaud, Brianna |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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