<div><p>Little Lagoon is a shallow coastal lagoon that is tidally connected to the Gulf of Mexico but has no riverine inputs. The water in the lagoon is replenished solely from precipitation and groundwater inputs primarily on the East end (Su et al. 2012). Because of the rapid development in Baldwin County, a large amount of NO3- enters the Little Lagoon system through SGD (Murgulet & Tick 2008). In this region, there can be rapid changes in the depth to groundwater (Fig. 4.1 inset) and episodic SGD inputs to the lagoon (Su et al.2013). Within the lagoon, three sites were selected (East, Mouth, and West) to represent the gradient that exists across the lagoon from the input of groundwater. Sites were sampled on a near-monthly basis from February 2012 to February 2013.</p>
<p><strong>Additional methodology can be found in:</strong></p>
<p>Bernard, Rebecca & Mortazavi, Behzad & A. Kleinhuizen, Alice. (2015). Dissimilatory nitrate reduction to ammonium (DNRA) seasonally dominates NO3− reduction pathways in an anthropogenically impacted sub-tropical coastal lagoon. Biogeochemistry. 125. 47-64. <a href="https://link.springer.com/article/10.1007%2Fs10533-015-0111-6" target="_blank">10.1007/s10533-015-0111-6</a>. </p></div>
Number of gene markers identified in sediment.
<div><p>Number of gene markers identified in sediment.</p></div>
Gene copies
<div><p>Data were flagged as below detection limits if no measurable rates were returned after calculations. See equations in methodology section of:</p>
<p>Bernard, Rebecca & Mortazavi, Behzad & A. Kleinhuizen, Alice. (2015). Dissimilatory nitrate reduction to ammonium (DNRA) seasonally dominates NO3− reduction pathways in an anthropogenically impacted sub-tropical coastal lagoon. Biogeochemistry. 125. 47-64. <a href="https://link.springer.com/article/10.1007%2Fs10533-015-0111-6" target="_blank">10.1007/s10533-015-0111-6</a>. </p>
<p><strong>Statistical Analysis</strong></p>
<p>To test the seasonal flux variability between sites in Little Lagoon, two-way ANOVAs with site and date as independent variables were performed. When data could not be transformed to meet ANOVA assumptions, Wilcoxon/Kruskal-Wallis nonparametric tests were used. When significant differences occurred, Tukey HSD or Steel-Dwass post hoc tests were used to determine significant interactions. A Principal component analysis (PCA) was conducted on all biogeochemical parameters to identify underlying multivariate components that may be influencing N fluxes. Spearman’s rho correlation analysis was used to examine the relationship between the principal components and fluxes. Statistical significance of the data set was determined at α=0.05 and error is reported as standard error. All statistical analyses were performed in SAS JMP 10 (SAS Institute Inc.).</p>
<p><strong>BCO-DMO Data Processing Notes:</strong></p>
<p>- Data reorganized into one table under one set of column names<br />
- Units removed from column names<br />
- Column names reformatted to meet BCO-DMO standards<br />
- Information captured in original column names entered under column Value_Description<br />
- Created column Year to describe to capture the metadata in the file name</p></div>
723948
Gene copies
2018-01-17T15:10:58-05:00
2018-01-17T15:10:58-05:00
2023-07-07T16:10:26-04:00
urn:bcodmo:dataset:723948
Number of gene markers identified in sediment in samples from Little Lagoon, Alabama collected from 2012-2013.
Number of gene markers identified in sediment in samples from Little Lagoon, Alabama collected from 2012-2013.
false
Mortazavi, B., Burnett, W. (2018) Number of gene markers identified in sediment in samples from Little Lagoon, Alabama collected from 2012-2013. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2018-01-16 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.723948.1 [access date]
false
1
10.1575/1912/bco-dmo.723948.1
false
2018-01-16
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