Can the fabrication of research results be prevented?
Can the peer review process be augmented with
automated checking?
These questions become more important
with automated submission of data to archives.
The potential usefulness of automated methods of detecting at least some forms of
either intentional or unintentional 'result management' is clear.
Benford's Law is a postulated relationship on the frequency
of digits (Benford 1938). It states that the distribution of the combination of digits
in
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There are a number of ways to answer this question.
There are a rich diversity of methods to predict
species' distribution and they could be listed and described.
Alternatively, the biological relationships between
species and the environment could be emphasized, and approaches from
population dynamics used as a starting point.
A more general approach to niche modeling can be based the
statistical idea of the probability distribution.
Definition: A niche model is a probability distribution defined
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Geographic information is a major component of niche modeling in any
spatial science such as ecology.
Geographic Information Systems (GIS) are the tool of choice when
the main purpose is managing geographic information.
As in the previous chapter when R was used as a relational database,
R can be used to perform simple spatial tasks.
This both avoids the need for a separate GIS system when not necessary,
and helps to build knowledge of advanced use of the R language.
R is not very efficient for
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In this section we show how to use R as a stand-alone database for niche modeling.
Even though R is a vector programming language, R has powerful
operations that replicate relational database operations including select and join.
Using R in this way avoids the need
for setting up and for analysis and interacting with an additional piece of software.
In addition,
describing basic database operations in R helps to build knowledge of the
R's powerful indexing operations.
Loading and saving a database
One
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There is a problem in the education of children, and its nothing to do with the "No Child Left Behind" policy or funding levels. It is with the way elementary science is taught. Based on web searches of curricula around the country, science topics and examples seem to have a high profile in classroom activities. For example, weather, transportation, plants and so on are used in mini-projects to motivate journaling, thinking, communication and enriching the student's knowledge literacy of the world.
This
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Successful modeling relies heavily on a few
basic concepts in mathematics and statistics. This post summarizes
the major areas you need to know for ecological niche modeling,
illustrated with examples in the vector language R.
Elements
We assume that readers have a basic knowledge of mathematics.
For people not familiar with the R language, it is helpful to have a summary of the
major types and operations comparison.
R is a very powerful vector language
that supports the basic data types:
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How many years have I been waiting for a fast, powerful, networked geospatial client with an open data format? Maybe this time. Google Earth could wipe other suitors off the proverbial map.
Nature magazine features an article on a dynamic map of Avian Influenza developed by Decalan Butler whose blog is here.
Here is a snapshot of the Google Earth Avian Influenza map showing the surge in cases in Europe and the Middle East this year.
The visualization of avian flu outbreaks is the first
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Readers of this blog were alerted early to the gathering storm with the post "Peer-censorship and scientific fraud." Now the influential New York Times has a Health editorial on the topic entitled For Science's Gatekeepers, a Credibility Gap.
Virtually every major scientific and medical journal has been humbled recently by publishing findings that are later discredited. The flurry of episodes has led many people to ask why authors, editors and independent expert reviewers all failed to detect the
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Previously "A New Temperature Reconstruction" used random data with long term persistence (LTP) to illustrate the circular reasoning behind the 'hockey stick' reconstruction of past temperatures. This one shows the potential for false positives due to the statistics used in the 'hockey stick'. The dynamic simulation below shows future temperatures predicted using a random fractional differencing algorithm that generates realistic LTP behavior. Future temperatures and validation statistics are
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