are undertaken to find out what organisms exist in a given area.
The data that is gathered from these surveys is used for numerous
purposes such as:
- monitoring endangered
- evaluating conservation
priorities of an area;
Museum and herbarium
specimens provide a valuable record of the location of organisms
but such data are rarely systematic and often subjective. This
is why field surveys are so important.
Despite their importance
in biodiversity research, there are no well-defined rules as to
how to perform such surveys. This is due to the vast differences
between surveys in terms of the goals of the survey, of available
resources and time, the area to be surveyed, the organisms to
be found, and a myriad of other factors that change from survey
Still, there are some basic
questions that must be addressed before any survey is begun and these
questions are explained below.
are the objectives of the survey?
The survey's objective must
be determined: Do we want to inventory the species in a given area?
monitor the populations already known to exist there? model the processes
driving diversity in the system? These are all valid scientific objectives
for carrying out a biodiversity survey. Since it is likely that only
a sample of the actual diversity of an area can be surveyed, the goals
of the survey are extremely important to ensure that the results are
The objective will guide
the answers to the next most important questions: what kind of diversity
will we look at and how will we measure it?
kind of diversity are we measuring?
Some argue that the
fundamental unit of biodiversity is the gene. Genetic diversity
is the degree of variability of the genetic material of an organism
et al. 1994b). Species are defined by the differences
in their genes. High genetic diversity indicates populations that
can more easily adapt to changing situations and environments,
and also a greater assortment of materials that can be found,
increasing the chances of finding a useful compound.
However, exact assessment
of genetic diversity is both time-consuming and prohibitively
expensive, requiring modern laboratories and expensive chemicals.
We have so far been able to account for all the genes in just
one species of bacteria! Realistically, investigators could only
examine a minute fraction of the genetic diversity to be found
using this approach, and time is often a constraint.
diversity can be estimated by species diversity, and this has become
the standard unit of measurement in most biodiversity surveys.
have the advantage of being natural biological divisions and easily
identifiable; their diverging appearances were the basis by which
they were classified in the 18th century, and modern phylogenetic
techniques more often than not produce species divisions similar to
those of classical taxonomic divisions. For many groups of organisms,
such as birds and flowers, public interest means that identification
of many species is already known by large numbers of people.
The degree of genetic
variability at the species level, and indeed at any taxonomic
level, can be maximized by taking species that differ by one another
by as many characters as possible. If these characters represent
different genetic elements, then the divergent species should
represent greater genetic diversity.
In the case of some
groups of organisms, such as insects, the numbers of species is
so large that it is not practical to identify them all. Fully
half of the 1.5 million identified organisms are insects. Furthermore,
species of many microorganisms have not yet been identified or
named. Only identification to higher taxonomic groups, such as
to the genus or family level, may be necessary or even possible.
method works well up to families (Williams
et al. 1994a), if the species observed are more or
less similar. If the species are quite different this method is
less useful, since diversity would be underestimated.
Ecological questions can best be answered by these data if the
species within the higher taxonomic groups live in similar habitats
and pursue similar lifestyles, so that each group can be considered
as a relatively homogenous set (Danks,
1997). If the intent of the survey is to generate a
list of which particular species are to be found in an area, then
this method is unsuitable; conversely, if simply estimating the
number of species to be found is the aim, this method is acceptable (Dobson,
species may be used to select areas as priorities for conservation
and protection because it is assumed that if a given indicator
organism is protected, then a number of other organisms may be
protected as well.
Using the presence of indicator
species as representative of many species can make a survey less costly
and time-consuming. However, the complexity of most ecosystems makes
it unlikely that any one (group of) organism(s) can serve as an indicator
of community structure and function. Indicator groups must be used
cautiously at any time, especially when the relationship between
the indicator group and the target group is negative; it may be that
the two simply live in different locations that are not usually found
together at the scale of previous surveys. If the goal of the survey
is to establish some cause and effect, then the indicators may not
provide the same relationship between the cause and effect as the
target groups. Furthermore, setting conservation goals based on indicator
organisms may result in the inadvertent loss of species that were
not adequately protected (Amanda
Vincent, pers. comm.).
To estimate the number
of species in an area, surrogate measurements, such as net primary
production for plants, may be used, which, although crude, are
readily available. The major problem with this method is that
specific species are not identifiable by this method, so that
estimates of total diversity may be generated, but not the particulars.
This method works best for larger areas, where the effects of
local differences and chance are minimized.
How will the survey be carried out?
The actual methodology
of the survey depends the goal of the project, the unit of biodiversity
being measured, and how the data will be analyzed. Data collected
can be either qualitative (presence/absence, also known as binary)
or quantitative data, in which the number of individuals for each
species are counted. Small mobile animals such as insects are
usually captured using traps or nets, while plants are usually
visually identified in the field.
Assuming that the data
are to be compared or analyzed, sampling for a survey must be
kept consistent, not just between different surveyors but also
from site to site and day to day. Standardization ensures that
differences between sites are significant and not the result of
uneven sampling. One way to standardize is by making sure that
the species are being correctly identified, by having an outside
expert identify the specimens. Should the survey be a noninvasive
one dealing with visual identification in the field, the expert
identification may be performed on vouchers, which are samples
of species that are collected in the field. Replication, taking
multiple samples in a site, can also help identify irregularities
in one surveyor's technique or among different surveyors.
Determining the sampling
effort is important and difficult, because it requires a balance
between time and effort and interpretability of data, assuming
that not all organisms in the area can be correctly identified
due to time and labor constraints.
Sampling effort can
be expressed many ways: as search time per site, as search within
a given distance of a reference point or line, or as total number
of sites or replicates needed to find a pattern. For example,
the Audubon Christmas Bird Counts will select one 24-hour period
where investigators will try to find as many breeding species
in an area as possible within 24 hours. Setting a definite time
limit also allows the survey to be more standardized and results
can be compared from year to year. For a survey to be considered
scientific, it must be random; that is, the sites should be selected
independent of factors such as the number of organisms found at
a site or proximity of a site to the laboratory; although these
seem to be valid reasons for spending more effort at a site, this
only serves to make the sites unevenly sampled with the end result
that differences in diversity between sites cannot be convincingly
attributed to something other than the difference in sampling
The scale at which
the survey will be done depends upon the goals of the project
and on the unit of biodiversity being used. The scale should be
appropriate to the organisms being surveyed; a one-meter scale
would be ineffective for full-grown trees, whose bases are often
greater than a meter in area; it may be a good choice for ferns.
A large scale may also be needed for motile organisms, such as
caribou, or large oceanic fish, which have a much larger habitat.
Large areas may
be divided into biogeographic regions or landscape
types, but conducting surveys along these categories is problematic
because of the differing sizes of regions or landscapes, especially
when the variation within them is examined, or when sharp boundaries
must be delineated (Haila
and Margules, 1996). Therefore, biodiversity surveys are
usually performed using a grid of some sort, as the diversity of an
area is usually what is of concern. Point data are not as useful because
they are not consistent and the diversity at a point depends upon chance
encountering of aggregations. Linear measurements are rarely useful
because most patterns of biodiversity are two- or three-dimensional.
should cover the entire area of interest and aggregates of the
shape used should form the same shape to allow different scales
to be easily compared. Squares and hexagons are the most often
used shapes, their dimensions making it simple to sample in one
quadrat without inadvertently wandering into another. Grids superimposed
over large areas may have problems due to the curvature of the
planet (making some quadrats bigger or smaller than others), and
so equal-area or almost equal-area grids are used, where the grid
is modified such that every quadrat has the same area, although
the shape may differ somewhat (Atlas
and Margules, 1996)
is a special type of survey used extensively in conservation work.
Monitoring involves repeated surveys of an area over time, which
allows examination of effects of change through time as well as
of change through space. In fact, the implementation of long-term
monitoring of forest ecosystems, St. Lawrence River ecosystems
and species at risk is one of the major aims of the Québec Biodiversity
Strategy. Monitoring programs are being set up all over the world
and span from regional surveys (e.g. Mont St. Hilaire) to global
ones (see World
Conservation Monitoring Centre website).
Quantitative data are
better for monitoring, as they allow changes in the population
to be measured, instead of the population simply being recorded
as present or absent; it would be helpful to know if a population
were in danger before it disappears. Knowledge of the population
structure is also very important in conservation, so sex ratios
and ratios in different life stages are also needed, which is
possible if quantitative measurements are made. Monitoring allows
research into not just changes of population size and structure,
but also ranges of variation in population size and structure.
The frequency of monitoring
depends largely upon the goals of the project and the life history
of the species; population changes that may be the result of regular
cyclical fluctuations may appear drastic if the cycle is not known.
In Canada, population cycles of many larger animals follow a 10-year
period while those of small herbivores and their predators follow
a 4-year period (Ricklefs,
1990). Consideration of such natural cycles is important
to the monitoring of populations.
To prevent an area from
being overly disturbed, surveys should not repeatedly sample the same
areas, but some area should be sampled in the subsequent survey as
well, so that observed changes can be separated into the degree to
which they result from sampling new areas and the more universal changes
that have occurred since the last survey.
This section was written
by Torsten Bernhardt