3. Different types of literature
Primary sources – original materials, often empirical testing or experiments.
Examples:
- Journal articles
- Experimental data
- Communications
4. Different types of literature
Secondary sources – interpretations or summarization of primary sources
Examples:
- Reviews
- Meta-analyses
- Commentaries
5. Different types of literature
Tertiary sources – A distillation and collection of primary and secondary sources
Examples:
- Encyclopedias
- Textbooks
- Bibliographies
6. Different types of literature
Grey literature – is information or researched produced by an organization or
government.
Examples:
- Government documents
- Newsletters
- Technical reports
10. Narratives
- Reviews written about a subject that are not quantitative
- Relatively easy to write
- Biased towards authors of the article
- Typically written by experts on the subject
11. - Reviews that are based from a systematic search through the literature of a topic
- More difficult to write, requires reading many articles to make conclusions
- Less biased towards authors, but biased towards the state of the literature
- Written by any researcher
Systematic reviews
12.
13.
14.
15. - Reviews that are based from statistics conducted on multiple studies
- Difficult because it requires specific data from many articles.
- Generally unbiased, comparing effect sizes rather than studies
- Written by any researcher
Meta-analysis
16.
17.
18.
19.
20.
21.
22.
23. Choosing search terms
- Wild cards (*) to capture different spellings.
- Do not truncate
- Avoid ambiguity
- Common names and latin names
- define inclusion material
24. Refinement techniques
- Refine to English language
- Refine to empirical papers and exclude reviews for systematic
reviews/meta-analyses
- Refine to countries when targeting a geographic area
- Refine to year when targeting a time frame.
Notas do Editor
There are different types of literature. The textbooks you read and articles presented in class are often based on research that was published in other articles.
The most common type of literature for scientists are primary sources. These are often original experiments that are written up and published in journals. This is not restricted to written works though and could be experiments such as the figshares or personal communications about observations.
Secondary sources are interpretations or summarizations of primary resources. Simply, articles based on other articles. These include, reviews, meta-analyses that we will be discussing later, and commentaries.
Tertiary sources are a culmination of research on a topic written. Tertiary sources are typically very robust and reliable, based on both secondary and primary research. This is often what you classroom textbooks are considered.
Lastly, there is grey literature that is biased research that may be robust, but is produced by a specific organization or government. They are often report based that also summarizes a topic.
In regards to different types of synthesis tools (i.e. secondary or tertiary sources), there are many all with different levels of robustness. These include textbook examples, narratives, systematic reviews and meta-analyses.
How these reviews synthesis the tools is simple, but difficult to do. Often there is a specific hypothesis or problem that is apparent in the research. For instance, “how to deal with invasive species”. Then there are a number of different studies that each test this question in a different way. They may occur in different geographic areas, with different target species, etc. These studies are then amalgamated together to answer more general predictions or queires.
In regards to synthesis, they can be simplified into two general groups. First, we can summarize the knowledge from all the selected studies. The second is to combine all the data to conduct one large statistical test that effectively tests the original hypothesis or question.
In the first category and potentially the most common type of review, are narratives. Narratives are reviews written about a subject that are not quantitative. They are relatively easy to write, but typically biased towards the authors of the article. Consequently, they are typically written by experts on the subject.
Systematic reviews are not quite narratives but not meta-analyses either. They are reviews that are based from a systematic search through the literature on a topic. They are more difficult to write because it requires reading many articles to make conclusions. They are less biased towards the authors of the articles, but are biased towards the state of the literature. Can be written by any researcher willing to immersive themselves into the research.
An example from in class was the nurse plant paper that was a systematic review. In the case of this study, the different types of facilitation mechanisms were counted based on the number of studies that tested it. We can make certain deductions with these findings such as that stress amelioration is more important than pollination facilitation in structuring plant communities. However, we can not say that because the frequency of a topic being researched doesn’t necessarily correlate with its importance in ecology.
Conducted these systematic reviews can often be very time consuming. It involves going article by article and classifying it based on a certain set of criteria. This can include items such as geographic area studied, GPS coordinates, or more specific items such as ecological question being studied or target species.
A PRISMA report is a set of guidelines that help assist the systematic review process. The flowchart guides the researcher through different steps through out the systematic process to select and exclude articles relevant to the topic. This includes steps such as articles excluded, those screen or duplicate removals because of combined literature sets.
A meta-analysis simply is statistics based off other statistics. They are reviews that conduct statistics on a series of studies that test a specific question. They are often difficult because it requires specific data from many articles. Meta-analyses are generally unbiased because they are comparing effect sizes rather than studies. They can be written by any research without an in depth knowledge on the particular topic.
Here is an example comparing the traits that are most effect for invasion of trees. The number in brackets represents the number of studies that were aggregated for the mean effect size. Positive values represent a positive effect (i.e. growth rate encourages invasion) and error bars over zero mean significant. From this result, we can conclude that all of these traits significantly contribute to invasion, but certain traits such as growth rate are most responsible for invasion.
Here is another example of a meta-analysis. This figure shows the facilitation ability for restoration among different plant life forms. Numbers closer to one are a stronger effect than those closer to zero and negative values means it negatively effects. For instance, shrubs very strongly facilitate tree recruitment but less strongly facilitate herbs. Herbs negatively effect other plants likely through competition, however, shrubs can facilitate other shrub recruitment.
Now we are going to show the basics of conducting a literary search on web of science. First go to the site and it will look like this.
You can input different topic terms. The search terms refine what you are looking for. If you put AND, Web of Science tries to look for articles that have both terms. Alternatively, you can put OR, which looks for articles with either of the terms in it. There are also a series of different categories you may search in. Topic broadly searches the majority of the article for the term within the box. There are also other options such as title, author, published year, etc. Sometimes you may want to refine to specific time frames that you can do here.
In the next page after you have put in the search terms you will have the total results in the top left and all the articles often sorted by the number of citations. The top articles are generally the most important. You can sort them in a variety of ways, but often the number of citations and relevance are the most important. The next step is to refine the topics to content more relevant to your search topics. You can click on the web of science categories.
There are two options for categories. Firstly you want to refine to topics that are most relevant to you. In this case ecology would be a good example. In this case though refining will still leave in some odd categories that are not relevant. This may be because some articles may be both classified as ecology or say energy fuels. Thus, secondly you want to exclude categories that you are confident are not relevant to your research topic. After you do this for all the research topics, you will have a refined list of articles that relate to your research topic.
After complete a citation report. This report gives you the basics on the selected articles. It also provides information that can be helpful such as if the topic has been increasing over time and the average number of citations per item. This is a easy way to validate the importance of the topic.
Some important things to consider when choosing search terms.
- Wild cards (*) to capture different spellings.
- Do not truncate
- Avoid ambiguity
- Common names and latin names
- define inclusion material
Other things to consider when refining.
- Refine to English language
- Refine to empirical papers and exclude reviews for systematic reviews/meta-analyses
- Refine to countries when targeting a geographic area
- Refine to year when targeting a time frame.
