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Walia Special Edition on the Bale Mountains (2011) - Zoologische ...

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scale as a balance where <strong>on</strong>e side represents intensive, expensive, and highly detailed data while <strong>the</strong><br />

o<strong>the</strong>r side has cheap, superficial, broad data. Choosing <strong>the</strong> appropriate level of scale is a matter of<br />

balancing how much effort you can afford to invest against <strong>the</strong> level of detail you require to answer<br />

<strong>the</strong> questi<strong>on</strong> (Fig. 1). In general <strong>the</strong> finer <strong>the</strong> scale, <strong>the</strong> more time c<strong>on</strong>suming and expensive <strong>the</strong><br />

m<strong>on</strong>itoring is going to be. And remember that over-ambitious projects tend to fail. It’s <strong>the</strong> simple<br />

<strong>on</strong>es that work.<br />

Figure 1. The data balance. Your data collecti<strong>on</strong> method should balance <strong>the</strong> limitati<strong>on</strong>s faced by<br />

time, effort, m<strong>on</strong>ey and resources against <strong>the</strong> level of detail required to answer <strong>the</strong> questi<strong>on</strong>. If<br />

you are unsure, <strong>the</strong>n always start with cheapest and lowest effort opti<strong>on</strong>.<br />

Finally, it is important not to lose yourself in details when collecting data. Think about what<br />

is really necessary and what is realistic in terms of time, effort and m<strong>on</strong>ey. C<strong>on</strong>versely, you do not<br />

want to run <strong>the</strong> risk of losing <strong>the</strong> intricacies and mechanisms of a potentially important result by<br />

collecting data that is too broad.<br />

What is Every<strong>on</strong>e Else Collecting?<br />

The most important aspect to remember when designing databases is to not let yourself be<br />

overwhelmed by <strong>the</strong> potentially daunting task. Most c<strong>on</strong>servati<strong>on</strong>ists have very basic knowledge<br />

about databases and <strong>the</strong>refore it makes sense to keep it as simple as possible. For example, <strong>the</strong><br />

Serengeti Database is simply a collecti<strong>on</strong> of folders that are organized by subject (you can do this<br />

even in Windows Explorer) (Fig. 2). The name of each folder is brief descripti<strong>on</strong> of what it c<strong>on</strong>tains.<br />

Each folder starts with a metadata file which describes in detail <strong>the</strong> data, <strong>the</strong>ir origin, and a c<strong>on</strong>tact<br />

pers<strong>on</strong> (see discussi<strong>on</strong> <strong>on</strong> metadata in <strong>the</strong> following secti<strong>on</strong>). The data within <strong>the</strong> folders are stored<br />

as Excel or Access spreadsheets, photos, GIS layers, satellite images, PDFs of papers, GPS points,<br />

etc. This is by far <strong>the</strong> easiest way to organize <strong>the</strong> data for a protected area and in many cases it is<br />

perfectly sufficient for an overview. It is also incredibly easy to manage and navigate.<br />

<str<strong>on</strong>g>Walia</str<strong>on</strong>g>-<str<strong>on</strong>g>Special</str<strong>on</strong>g> <str<strong>on</strong>g>Editi<strong>on</strong></str<strong>on</strong>g> <strong>on</strong> <strong>the</strong> <strong>Bale</strong> <strong>Mountains</strong> 311

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