From January 2014 to December 2016, I conducted monthly field trips in three different areas of Dhaka city, Bangladesh to investigate how butterflies survive in an inner-city habitat. I have found that the species richness (I did not count the species abundance) is declining with time.
Presently, I have:
* monthly species-specific data of three continuous years (36 continuous months) of the three different areas
* Four environmental variables (temperature, rainfall, humidity and sunshine hours)
* Pollution level
* IUCN Red List status
* Land-use analysis of these three different areas
Now, I am really confused considering the proper way to link these pieces of information! Could anyone of you please share some ideas?
As I understand from your question you have three sets of data. Each set contains more than one variable. In the data set for species you only have presences and absences (with perhaps 0 for absence and 1 for presence). If this is correct then the optimum technique would be stepwise Manly matrix correlation. The essentials of this are to create a matrix of the similarities between collection sites based on species presences and absences (call it S), another one based on environmental variables (E) and a third based on land use (L). The you correlated S with L and S with E and also S with L correcting for E and S with E correcting for S. Then repeat this process separately for the Red List and the non Red List species. These are the essentials but the analysis can be taken further.
Canonical Correlation Analysis (CaCoA) would have been an option if you also had the abundances of the species.
good luck, Andrew
First I would do a time series analysis to look for cyclic patterns in the richness of moths. You can also explore the relationship between moth richness and your environmental variables, using linear models or you can explore the data with multivariate techniques. However, you need clear question and predictions after doing any kind of analysis.
Hello dear Shawan, hope you have a nice day.
There are several studies about butterflies on urban systems that could help you to give a better way to your data.
Here are some examples that could help you:
Article Butterflies in the city: a review of urban diurnal Lepidoptera
Article City "Green" Contributions: The Role of Urban Greenspaces as...
Article Tales of urban conservation: Eumaeus butterflies and their t...
I hope you find them useful.
Best regards,
Cristian
If you have sampled your sites all in the same way and have counted the population of each species the a Principal Component Analysis will show relationships. Factors can be added and subtracted to their overall effect. See some of my papers (on RG) for examples.
Three years' data are usually considered insufficient reliably to detect trend. You could fit a statistical model, but for time (year) you have only one degree of freedom. Even if you can select the best statistical model, or carry out a test of "significance", the interpretation is clouded by the fact that each year will be different and you will not be able to distinguish signal from noise with just the three years. I suggest that you have a baseline study, which would need to be continued, or repeated some time in the future, to stand a chance of detecting trend. As for attributing any trend to those environmental variables, forget it - you will suffer from gross overfitting.
Look at the Material and Methods section. Perhaps it could help?
Best,
Guy
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