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This text describes the data presented in the paper: Estimating the abundance of endospores of sulfate-reducing bacteria in environmental samples by inducing germination and exponential growth.

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Introductory information
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Files included in the data deposit (include a short description of what data are contained): 

1) deRezende_etal_2016.m - MATLAB programme to fit an exponential function to measured SRR data (included in the file) and estimate SRB endospore abundance.
2) deRezende_etal_2016.xlsx - Raw data and SRR calculation.


Explain the relationship between multiple data sets, if required:
SRR were calculated as presented in the .xlsx file and used as input data for the .m file.


Key words used to describe the data:
MATLAB, exponential model, SRR, SRB endospore abundance


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Methodological information
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A brief method description – what the data is, how and why it was collected or created, and how it was processed:
The data results from incubation at 50 degrees Celsius of surface sediment from Aarhus Bay, Denmark, in a slurry made with artificial seawater medium, with and without organic substrate amendment. Subsamples were removed from master slurry and incubated with radioactive sulfate tracer for ca. 1h. Sulfate reduction rates (SRR_ were determined as described by R¿y et al. 2014. See further details in the main text.


Instruments, hardware and software used: 
- Packard Tri-Carb 2900 TR liquid scintillation analyzer.
- MATLAB (MathWorks)


Date(s) of data collection: 
January 2009


Geographic coverage of data:
Aarhus Bay, Denmark


Data validation (how was the data checked, proofed and cleaned):
Duplicate incubations with radioactive sulfate tracer; bootstrapping 10,000x for estimation of the probability density distribution of each parameter calculated.


Overview of secondary data, if used:
N/A


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Data-specific information
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Definitions of names, labels, acronyms or specialist terminology uses for variables, records and their values: 



Explanation of weighting and grossing variables: 



Outline any missing data:



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Contact
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Please contact rdm@ncl.ac.uk for further information