Fen Management Handbook - Scottish Natural Heritage

Storage of data and information on single paper copies is vulnerable to loss or
damage. Digital data storage is therefore preferable because it allows easy storage
and copying of the data whilst minimising risk of loss or damage. Computerised
analysis is also easier if data is stored digitally. Geographical Information System
packages can use data from external spreadsheets and databases and provide geostatistical
analysis methods. Quality assurance of collected data is also facilitated by
computerised storage. Spreadsheets and databases can be programmed to expect
data values within a certain range, and to alert the user if the entered values are
unexpected. Visual data plotting on graphs can help identify unexpected values.
The type of software package which is used will depend largely on the volume of
data. Spreadsheet storage (e.g. MS Excel) is often adequate for smaller volumes of
data (up to 65,000 rows of data in the 2003 version); the data can be seen easily,
there are simple options for automated data quality assurance and visualisation,
and there are powerful functions for data processing and analysis. Database (e.g.
MS Access) storage is more appropriate for larger volumes of data, such as that
produced by high-frequency automated recording of water levels using a pressuretransducer
and data-logger. The data storage capacity of databases is much higher
than that of spreadsheets, but the data visualisation and analysis functions are
less accessible to the average user. Daily observation logs and field records from
walkover surveys present some data entry problems. As far as possible these should
be entered in a standard format that can be coded.
Frequent back-ups of the computer-stored data should be made and preferably
on an automated basis. Transferring data to outside organisations can provide an
alternative back-up. The Biodiversity Action Reporting System (BARS) has valuable
features for recording the broad outcomes of monitoring surveys, and the county or
regional Biological Recording Centre can accept species records to date and place.
SSSI data should be copied to the relevant national agency (Natural England, CCW,
NIEA or SNH).
10.16 Analysis and use of monitoring data
Monitoring seeks to measure a variety of different parameters, or variables, many of
which are inter-related. A variety of techniques have been designed to help analyse
and interpret these complex inter-relationships.
Graphical techniques used to explore the relationship between variables include:
– Simple time-series graphs of two or more variables. Data with very different
absolute values can be plotted together for easy analysis either by the use of a
secondary y-axis, or by normalisation.
– Plots of one variable against another; the best-fit line through the data indicates
the relationship between the variables, and the degree to which the points cluster
around the line indicates the strength of the relationship.
More sophisticated statistical techniques can also be used to quantify the nature
and strength of relationships between variables.
Other techniques for analysis and interpretation of data include contour maps, for
example soil water levels, and cross-sections through the site.
10.17 Modelling
Modelling involves calculations involving an independent variable (or variables)
which attempt to model a dependent variable. It can be used to develop a better
(preferably quantitative) understanding of cause–effect relationships between
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