Geoscience Reference
In-Depth Information
how particular ecological sampling methods in different settings are com-
bined with estimation procedures that are justified by statistical theory.
1.2 The Scope and Contents of the Topic
This topic introduces ecological sampling methods and the analysis of the
data obtained with the assumption that readers start with basic knowledge
of standard statistical methods based on one or two introductory courses but
know little about how these methods are applied with ecological data and
know nothing about the more specialized methods that have been devel-
oped speciically for ecological data. The topic is only an introduction, so
that use of many of the methods described in the chapters may require read-
ing a text that is more specialized or in some cases even attending a course
on the use of a special statistical computer package.
There are ten chapters in the rest of the topic. The remainder of this chap-
ter briefly describes what is in these chapters and the reason why each chap-
ter was included in the topic.
Chapter 2, “Standard Sampling Methods and Analyses,” covers the tradi-
tional methods that have been employed with ecological and other data for
more than 50 years, plus some newer developments in this area. These meth-
ods all assume that there is a specific population of interest, and that the pop-
ulation consists of many items of interest. For example, the population could
be all of the plants of a certain species in a national park, and the interest is
in the number of plants per square meter for the entire park. In these types of
situations, it is usually the case that obtaining information for the whole pop-
ulation is not possible because this would be far too expensive. Therefore, it
is necessary to sample the population and estimate variables of interest using
the sample results. With the plant population, this could be done by sampling
meter-square plots at random throughout the national park and estimating
the density for the whole park using the observed density on the sampled
plots, with a measure of how large the difference between the observed den-
sity and the true density is likely to be. Chapter 2 discusses estimation using
random sampling methods like this and a number of variations on this that
are intended to improve the estimation, such as stratified sampling, by which
different parts of the population are sampled separately.
Chapter 3, “Adaptive Sampling Methods,” covers the methods that have
been proposed for which there is an initial sampling of a population and the
results from this are used to decide where to sample after that, with the idea
that this should lead to more efficient sampling. Adaptive cluster sampling,
which is covered in more detail than other adaptive sampling methods,
involves dividing an area of interest into quadrats, taking a random sample
of those quadrats, and then taking more samples adjacent to the quadrats
