Thank you very much, Sir Gavin, for the opportunity to listen to your talk last June 7, 2020. It was indeed a beneficial and informative lecture, especially to a neophyte like me. I hope you will do more lecture series, and I hope you do consider making R tutorials and its usage in ecological research. Again, thank you and more power to you. -Participant from the Philippines
Thank you so much for all of the information. I have difficulty dealing with arthropod abundance data, and I don't know where to start and what analysis to choose and so on.
Thanks a lot for this. I watched the live lecture and have come back to the youtube video several times for clarification. One question regarding negative eigenvalues in PCoA: In your example (slide 56) the absolute values for the negative ones are relatively low and affect components after PC10. Thus, if you would plot PC1 vs PC2 for both the corrected and the uncorrected ordination and they looked the same, would you keep the uncorrected version or is it always advisable to maintain the corrected version?
I have a question Sir, There are just two different fields, from each field four samples(4 repeats/replications) were obtain for species abundance, similarly four samples(4 repeats/replications) from each field were taken for soil properties, how to make a dataset for this situation? Do we need to import separately and what about repeats for redundancy analysis?
Not sure what specifically you are commenting on, but if it's PCA then doing this results in fitting PCA on a correlation matrix instead of a covariance matrix.
![⭐️( ลอยกระทง 2024 ) Ver. แดนซ์ Remix BY [ ดีเจกิต รีมิกซ์ ]](http://i.ytimg.com/vi/rMWOLhgXUHc/mqdefault.jpg)
Diversity 00:09:40
Dissimilarity 00:32:20
Ordination 00:44:20
- PCA 00:52:10
- CA 01:27:45
- PCO/PCoA 01:51:45
- NMDS 01:58:00
Practical tips 02:21:29
@@ftboth Could you perhaps pin this? SUPER helpful!
Vegan basics 1:37:45
I just noticed if you click the timestamps here on the comment, it will be directly go to that specific time. Lol I just discovered
Thank you very much, Sir Gavin, for the opportunity to listen to your talk last June 7, 2020. It was indeed a beneficial and informative lecture, especially to a neophyte like me. I hope you will do more lecture series, and I hope you do consider making R tutorials and its usage in ecological research. Again, thank you and more power to you.
-Participant from the Philippines
good explained and helpful video! Thanks for summarizing the vegan package :)
Thankyou for this! Added to our VLE for my MSc students in Hull (sounds lke you hail from not a million miles away?)
Nice explanations.
Thank you very much.
Thank you so much for all of the information. I have difficulty dealing with arthropod abundance data, and I don't know where to start and what analysis to choose and so on.
Thanks a lot for this. I watched the live lecture and have come back to the youtube video several times for clarification. One question regarding negative eigenvalues in PCoA: In your example (slide 56) the absolute values for the negative ones are relatively low and affect components after PC10. Thus, if you would plot PC1 vs PC2 for both the corrected and the uncorrected ordination and they looked the same, would you keep the uncorrected version or is it always advisable to maintain the corrected version?
@@ftboth Thanks for the reply.
I have species trait variation across months what kind of ordination method should I use to see the pattern of trait variation across time
Please, it would be great if you enable subtitles.
I have a question Sir, There are just two different fields, from each field four samples(4 repeats/replications) were obtain for species abundance, similarly four samples(4 repeats/replications) from each field were taken for soil properties, how to make a dataset for this situation? Do we need to import separately and what about repeats for redundancy analysis?
Hi Professor Simpson, you mentioned that CANOCO scales the eigenvalues differently than vegan. Would you please explain it a bit? Thanks a lot! :D
@@ftboth Thanks for your reply~^^ Just wondering that if there's any scaling we can use in vegan to get the same results as in CANOCO?
@@ftboth Got it! Thank you so much~😊
Many thanks!
Normalizing and standardizing - it just sounds like we are making a Z distribution.
Not sure what specifically you are commenting on, but if it's PCA then doing this results in fitting PCA on a correlation matrix instead of a covariance matrix.