Data Entry

 Data Entry

Once you have monitored your Seagrass-Watch site, you can now enter the data collected into a downloadable Microsoft Excel spreadsheet and submit via email.

To enter and submit data, follow the following steps:

1	Click on the image below to open the web data entry spreadsheet
2	Save the spreadsheet file to your computer before you begin data entry. We suggest changing the file name to the site code and the sampling date. For example, if the site was Burrum Heads 1, and it was sampled on 09 February 2005 then the filename would be “BH1_09Feb05.xls“
3	The spreadsheets are a similar layout to the standard datasheets. Each transect has it’s own worksheet. To select the appropriate worksheet, click on the tab at the bottom
4	To enter data, select each cell with your mouse. You can jump between cells by using the TAB button on your keyboard.
5	First enter the name of the observers and the sampling date.
6	Enter the location and site code. For the above example, the location is “Burrum Heads” and the site code is “BH1“.
7	Enter the time you started sampling the transect and the time you finished. Times are entered at 24 hr with the hour separated from the minutes by a colon. For example. if the time was half past one in the afternoon, the time entered would be “13:30“.
8	If you had a GPS (Global Positioning System) at the monitoring site, the latitude and longitude of the transect start
9	Enter the data for each quadrat Sediment: enter by the dominant grain size first, separating sediment categories by a forward slash. For example, if the quadrat was predominantly mud with some sand, then the data would be entered as “Mud/Sand”.  Please do not use abbreviations “M/S” when entering into the spreadsheet. Comments: Enter information (including counts) of any features which may be of interest. For example, “sea cucumbers (x2), sea urchin (x1), evidence of turtle cropping” Photograph: type in “True” if you took a photo of the quadrat % cover: enter the total percent cover of seagrass within the quadrat % cover by species: enter the percentage cover that each species contributes to the total cover CR = Cymodocea rotundataCS = Cymodocea serrulata EA = Enhalus acoroides HC = Halophila capricorni HD = Halophila decipiens HM = Halophila minor HO = Halophila ovalis HP = Halodule pinifolia HS = Halophila spinulosa HT = Halophila tricostata HU = Halodule uninervis SI = Syringodium isoetifolium TC = Thalassodendron ciliatum TH = Thalassia hemprichii ZC = Zostera capricorni Canopy: enter the three canopy heights of the dominant strap leaf species (the average will calculate automatically) % Algae: enter the percent cover of maco-algae in the quadrat. Macro-algae are seaweeds that are not attached to seagrass leaves and may even overlie the seagrass shoots. The combined seagrass and algae cover may be greater than 100%. Epi %: Enter the percentage cover of epiphytes on the total seagrass leaves.
10	Enter the latitude and longitude of the transect finish
11	Enter any general comments about the transect or site
12	Repeat steps 5 to 10 for the remaining transects
13	Ensure your file is securely saved
14	Submit a copy of the excel file via internet to Seagrass-Watch HQ (hq@seagrasswatch.org )
15	Mail original datasheets, photos and herbarium sheets to Seagrass-Watch HQ (TropWATER/FSE) James Cook University PO Box 6811 Cairns QLD 4870 AUSTRALIA For data submission checklist: Click Here

 DATA PROPERTY

All data collected in the Seagrass-Watch program is the property of the group (principal) who collected it, and Seagrass-Watch HQ is custodian. When a group submits data to HQ, it does so under the proviso that the data can be used by Seagrass-Watch HQ for condition and trend reporting at location, regional, state, national and global scales (eg, State of the Environment Queensland, State of the Environment Australia and State of the Environment GBR). Copies of raw data are provided to third parties only when permission from the principal is provided.

All data interpretation is conducted by Seagrass-Watch HQ. This ensures that the interpretation of data is consistent, unbiased and of scientific merit. Seagrass-Watch HQ also encourages peer review and assessment of published results.

Apart from the regional & statewide report cards (e.g. SoE), the data has also been used for:

• understanding and responding to impacts from catchment runoff (Campbell & McKenzie 2004), coastal developments (eg. marina constructions) and dredging proposals.

• Understanding natural levels of change and supporting marine habitat conservation (eg GSS Ramsar Wetland, Cooloola World Heritage area, and Great Sandy Marine Park

 QUALITY ASSURANCE/QUALITY CONTROL

Seagrass-Watch HQ also ensures the QAQC protocols for the program are followed and that the program is producing data of high quality, ensuring time and resources are not wasted. Quality assurance refers to the management system by which data is collected, organised, documented and evaluated. Quality control refers to the technical means by which error is controlled.

The five indicators of QAQC that the program uses are:

• Precision: This is the degree of agreement among repeated measurements. This is controlled by conducting scientific training & using calibration sheets.

• Accuracy: This measures how close results are to a true or expected value. To do this the program requests voucher specimens of seagrasses, conducts refresher scientific training & requires observers to make photographic records (ie 27% quadrats sampled are photographed)

• Representative ness is the extent to which measurements actually represent the whole population at the time an observation was made. In the program, this is controlled by choosing sites which are representative of the location.

• Completeness is the comparison between the amount of valid, or useable, data originally planned to collect, versus how much was collected. This is ensured by employing standardised scientific methods (developed in consultation with community volunteers) which are simple and easy to use.

• Comparability is the extent to which data can be compared between sample locations or periods of time within a project or between projects. This is ensured by using standardised methods and calibration sheets and conducting regular refresher scientific training.

 

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