152 Plant Identification
beginning. It can help to set up your database or spreadsheet at this stage, as well (see the following section), because the field names or section headings of your template will be the same as the categories of information you need to collect.
The list will include:
•
All of the categories of information that you need for the individual species descriptions (see Chapter 3 for suggestions). By this stage you should have a clear idea of what the users are looking for. The list may cover soil type, growth characteristics, how to manage or cultivate a species, where to find it, some interesting historical information, and the uses and cultural meaning of a species. The choice of these kinds of information will depend, of course, upon the purpose and use of the manual, as explained in Chapter 2.
•
Any information that you need for the introductory sections. Again, Chapter 2
provides a list of the kinds of information that you might include in an introduction, such as an overview of the ecology of the area or group of plants; a history of their management, conservation or use; an explanation of the key characteristics that users must familiarize themselves with in order to identify plants in that category; or perhaps a description of how to reach the area.
•
Any information that you need for the glossary, index and ‘Further information’
chapter at the end of the book. Usually information in the index will already be included in the species descriptions; but you may need to consider researching sources of further information, from books, organizations or people, to be included in a final chapter.
With this list you will be able to make a plan to collect the information in a consistent and reliable way.
MANAGING INFORMATION IN A DATABASE
While you are gathering information, you will be filling notebooks, probably in chronological order. It can be difficult to find the pieces of information you need afterwards unless you organize it. The main part of the information in a field guide is centred around the individual species, so the key element here is to organize the data that you collect in the same way. You may choose to:
•
fill in standardized forms for each species, with subheadings for each category of information about that species, such as description, uses, ecology and distribution;
•
complete standardized forms in a word-processing package;
•
make a table with a separate line for each species; in this case, you can include column headings relating to each category of information, such as description, uses, ecology and distribution; or
•
use a computer database or spreadsheet.
In fact, all of these are versions of a database, and the table is the underlying structure of a database, which broadly defined is a large amount of data stored in a systematic way so that you can find and use it easily. Computers are particularly useful for storing and
Information 153
organizing information, and it is likely that most authors of field guides will have access to a computer. The value of databases, especially on computers, is that you can sort the information in different ways. On file cards, each card usually refers to one species or specimen; it becomes difficult to find out which species have yellow flowers or are used for fodder or occur on riverbanks without laboriously reading through all of the cards and making a note of the species. In a computerized table, spreadsheet or database, you can sort all of the records according to any of the subcategories of information, so this task becomes easy. Table 7.1 summarizes some of the advantages and disadvantages of these means of storing and accessing data.
Such sorting is important when it comes to deciding how to organize the species within the field guide. For example, will species be presented in alphabetical order, or grouped according to flower colour, habit or habitat? This is also useful when preparing indexes for the guide, which may help the user to find species by common name, scientific name, habitat or use.
A manual in the People and Plants Initiative series provides much more detail on botanical databases (Berjak and Grimsdell, 1999) and is available on the internet at www.peopleandplants.org/whatweproduce/Books/botanical/Databases.html. Its key recommendations are summarized in Box 7.1. Essentially, it is important to:
•
Define the information categories required for each species.
•
Set up a format for each species – even if it is not the final format, at least each piece of information will be clearly retrievable.
•
Ensure that all of the information concerning each species is linked to a unique, internationally recognized name (see Chapter 4) so that information from different sources can be combined under that species.
•
Update your information as necessary – for example, when specimens are identified, add the scientific name immediately.
•
Record the sources of your information (see Box 7.1).
Tip: Backing up your computer files
Many people working in tropical countries, especially in rural locations, will know how often power failures can occur. When a power cut happens, all of the data you have entered on the computer is lost unless you have saved it. Even saved data can be lost if the computer becomes corrupted, whether because of a virus or because of damage to the hard drive. To avoid the catastrophic situation of losing months’ of hard work, make sure that you take regular copies of your files and store them safely. Even if you do not lose data, you may change your mind about how files are structured, and it can be very useful to be able to go back to an earlier version that may turn out to be closer to your final intentions.
NOMENCLATURE
Recording local names for species is a task that falls to the authors of the field guide, and it can be a complex one (see Chapter 4). It is very rare, indeed, that all local informants agree on the same name for a given species, and even more variation is found between
154 Plant Identification
Table 7.1 Comparing methods for storing data Method Advantages
Disadvantages
Paper and
• Reliable: remains functional
• Time consuming
pencil
during power cuts.
• Inaccurate: susceptible to human error
• More personal: spending more
• Isolating: as more work is done
time processing records means
on computers, there is increasing
more familiarity with your
pressure to work in the same media as
informants and data
colleagues and sponsoring agencies
• Affordable: may be all that
you can support
Spreadsheets
• Time saving: data is entered
• Unwieldy: as more data is added, the
once and can be selectively
document expands across the screen
linked to other data to use for
• Limited sorting: all data entered is
many purposes (timesheets,
displayed at once; if you want to see
reporting hours, etc.)
the uses of a particular species, you
• User friendly: once a programme
have to sort through every
is set up, it does not require
other bit of information to find the one
extensive expertise to use
piece, or pull the selected information
• Cross-functional: data doesn’t
into another sheet
need to be translated from
• Not text friendly: text can be entered
another programme
(and lists even sorted alphabetically),
but no lengthy text such as long
accounts of local uses can be included
Pre-packaged
• Fast learning curve: not
• Inflexible: unlike a customized
databases
necessary to be a programmer
database, it is difficult or impossible to
to use the database
add new features
• Offers all of the best features
• Limited: may not offer all the functions
of a database: time saving;
you want
displays only relevant data;
• Text oriented: not as good as
multipurpose; doesn’t become
spreadsheets at managing numerical
unwieldy
information, although this is unlikely to
• Buy and use: aside from data
be a problem in field guide production
entry, no set-up required
• Built to fit: some databases are
built specifically for biodiversity
data; usually effective at
anticipating the needs of users
• Help is at hand: technical
support available if problems
occur or new needs come up
Customized
• Flexible: customized databases
• Time-consuming set-up: extensive
databases (such
can grow and change
programming is required to develop the
as that used for
• Time saving: once the initial time
database
the Flora
is put in, customized databases • Requires expertise to maintain: if no one Reserva Ducke)
are generally the most time
in the organization is familiar with the
saving of the four options
programming (because either the
• Avoids the irrelevant: because
person who set it up has left or an
‘reports’ display only the desired
outside consultant was used), the
information, you don’t have to
programme cannot be further refined
Information 155
Table 7.1 continued
Method Advantages
Disadvantages
weed through extraneous data
• Text oriented: not as adroit as
to find what you’re looking for
spreadsheets at managing numerical
• Multipurpose: can easily
information
generate the same information
in different formats (checklists,
draft field guides, etc.)
• Streamline: can grow
extensively without becoming
unwieldy
Source: adapted from Berjak and Grimsdell (1999) communities and ethnic groups. On the other hand, the same name is often used for quite distinct species, or by different groups of people for distinct species or to refer to all of the species of a given genus. Variation in names tends to be higher for plants that are less well known or that are known only in the wild. There is usually more consensus over names of cultivated and traded species because people discuss those species more in everyday conversation (Berlin, 1992).
When working with indigenous people whose languages have not traditionally been written down, there are further pitfalls. Great care must be taken in transcribing the names – in other words, deciding how to spell the name. If anthropologists or linguists have produced guidelines on this, it is important to follow them so that your field guide is standardized and others can compare it with their findings. Even slight differences in the sound of the name must be recorded as these may later be found to vary geographically, or between communities or ethnic groups, in a systematic way.
BOX 7.1 PRINCIPLES OF DATABASE DESIGN
1
Atomize your data: divide your data into their basic parts (their atoms). This makes it easy to obtain very specific results from the database, if required.
2
Keep your data in raw form. In other words, keep your original observations or measurements just as they were noted or recorded.
3
Each record must have a unique designator in at least one field. Clearly, without such a designator, some records might be the same and could not be separated from one another.
4
Standardize as far as possible. This means using standards in common use. For instance, there may be list of standard plant names for the country or region where you work; these, in turn, may follow an internationally agreed standard.
5
Be consistent. This means adhering strictly to the ways in which you decide to record data entries and the titles of databases and fields (that is, spelling, style, and the use of upper and lower case letters and any other characters on the keyboard).
6
The source of information should be recorded. This principle really applies to larger databases where data comes from various places, people and organizations. If the source of the information is noted, then one can check this material in order to judge how reliable the data is.
Source: adapted from Berjak and Grimsdell (1999)
156 Plant Identification
Most important of all is to make sure that the names you are given refer to the species you are thinking of. The only way to be certain of this is to take a voucher specimen for verification in the herbarium later.
The names that people supply when asked are affected by a range of factors – some of them intrinsic to their lives, some of them dependent upon the circumstances of the interview. People’s knowledge of plant names depends upon their daily activities and experience of the forest, fields, gardens, etc., in which they work, upon their own personalities and level of interest, and upon their position and relationship to the rest of the community. It is important to separate differences in names given by ‘knowledgeable’ and ‘less knowledgeable’ people from those given by people with varying kinds of specialist knowledge. Different names supplied by people who are equally knowledgeable are equally valid.
However, there is a further range of pitfalls to be overcome, related to the conditions under which you ask about names. In his classic work on ethnobiology, Brent Berlin (1992) noted that names depend upon people receiving correct stimulus – in other words, the diagnostic characters that they use in identification; upon the perceived knowledge of the researcher; and upon the perceived usefulness of the exercise. One study found that men in an Amazonian tribe were able to identify birds much more accurately than women; but the study was based on dead bird specimens. The women were used to hearing the birds, rather than seeing them, so specimens were not helpful to them in identifying the bird. In another study, he reports that women provided much more detail about the names of manioc varieties to female researchers than to male researchers simply because they did not perceive that men could possibly be interested in such knowledge or find it useful.
SELECTING, SAMPLING AND RECORDING YOUR
SOURCES OF INFORMATION
If your sources are real people, how do you decide whom to interview? As was the case in Chapter 3, where we explained how to interview potential users of the guide, your sources of information do not need to be a statistically representative sample of any particular group of people. Random sampling is not appropriate here. You are not treat-ing your respondents as the object of study, but as collaborators in the production of a useful consensus document. Your sources should be people who are recognized as knowledgeable about the topic in question (such as the local uses and ecology of the plants in the guide), and there should be agreement that the resulting information is correct. That means that information gathered from key sources should be presented and cross-checked with other members of the same stakeholder group, and should come from those who are considered by their peers to be the most knowledgeable.
Nevertheless, as pointed out in the section on ‘Nomenclature’, there are
different kinds of experts, and a sample should be inclusive of differences in gender, ethnic group and occupation.
Each type of ‘expert’, whether scientist, rural community member or outreach worker, has many demands on his or her time; so polite requests for interviews with explanations of the purpose, as well as flexibility are needed.
Information 157
BOX 7.2 BRAHMS AND ALICE: EXAMPLES OF SOFTWARE TO
CREATE YOUR OWN BOTANICAL DATABASES
One software tool to help with producing field guides is the BRAHMS (Botanical Research and Herbarium Management System) database (see http://herbaria.plants.ox.ac.uk/
bol/home). Species names, collection data, bibliographies and images can be assembled and formatted to create an almost limitless range of checklist styles. The concept of
‘checklist’ is treated broadly, but always has a list of species names as the central theme.
This includes inventory-type lists of taxa from a specified geographic area (a forest reserve, a park, a country, continent or any other geographical area). It also includes taxonomic lists and synopses, not necessarily geographically restricted. Lists may constitute little more than a sorted record of names, perhaps with authors. Alternatively, a list may be richly annotated with nomenclature, descriptive text, references and other facts and features about the species, including images. Checklists may vary greatly in size and content. Some examples include:
•
aquatic species found in a garden pond;
•
Shorea in the central Philippines;
•
a world checklist of conifers;
•
a checklist of vascular plants of Mount Cameroon;
•
the lianas of East Africa;
•
commercial trees of Brazil.
Alice is another database management system for the creation, management and publication of information about organisms, designed for use by small or large collaborative projects working at different locations (see www.alicesoftware.com). Databases can be constructed about species, genera, varieties or cultivars, and Alice is flexible, so those producing the database decide what information to include. The basic data types are scientific names, vernacular names, uses, geographical distribution, habitats, text and user defined descriptors, and the Alice system can be configured on request to support any taxonomic hierarchy.
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