Peter, Both Kmult and its associated significance level are not effect sizes, so comparisons of these can be dicey. I would suggest examining their associated Z-score as obtained from the RRPP distribution and the observed value (see geomorph’s help file).
As to your second question, if one has species-level data, they are not independent. Thus one should take phylogeny into account, even if the phylogenetic signal is not overly strong. To that latter point (having significant phylogenetic signal but less than Brownian motion), please see the review by Adams and Collyer 2019 (Ann. Rev. Ecol. Evol. Syst.). In that we explicitly discuss that issue. One alternative not often considered by empiricists is that such patterns could be obtained when the phylogenetic signal is concentrated in one or a few trait dimensions. We show some simple simulations demonstrating this is possible, which are helpful to keep in mind when interpreting such findings. Best, Dean Dr. Dean C. Adams (he/him) Distinguished Professor of Evolutionary Biology Department of Ecology, Evolution, and Organismal Biology Iowa State University https://faculty.sites.iastate.edu/dcadams/ phone: 515-294-3834 From: morphmet2@googlegroups.com <morphmet2@googlegroups.com> On Behalf Of Peter Rühr Sent: Wednesday, August 23, 2023 9:21 AM To: Morphmet <morphmet2@googlegroups.com> Subject: [MORPHMET2] Phylegenetic Signal in Graphs Dear all, I am studying bite curve shapes of 650 insect species. The bite curve graphs are described by polynomial models with six degrees, of which I can get 100 graph point coordinates using the function predict(). Currently, I have two main questions regarding phylogenetic signal in that data: 1) Can I test for phylogenetic signal given the high non-independence of consecutive graph points? I see two possible inputs for the geomorph::physignal() function, of which the latter seems to be more problematic in that regard: I could use the six polynomials + intercept per species, or the 100 predicted coordinates per species. The difference, however, seems marginal: data p Kmult iterations polynomials 0.0001 0.105 10000 predicetd values 0.0001 0.113 10000 If you have an opinion on this, I would be very glad to hear about it. 2) As you can see, while being statistically significant, the Kmult-values are very low, indicating that species are less similar to each other than with a Brownian trait evolution. However, the Kmult-signal itself is in such a low range that some authors have decided to not take phylogeny into account (phylogenetic 'correction') in their own subsequent analyses. Should I correct for phylogeny or not? And again: would the polynomials instead of the predicted coordinates be a better choice for running phylogenetically informed analyses, or is such kind of data not suited to be phylogenetically corrected at all? Best regards and many thanks in advance, Peter -- Peter T. Rühr Bonn Institute of Organismic Biology (BIOB) Section Biodiversity of Animals University of Bonn An der Immenburg 1 53121 Bonn, Germany Phone: +49 (0) 228 73 5115 -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to morphmet2+unsubscr...@googlegroups.com<mailto:morphmet2+unsubscr...@googlegroups.com>. To view this discussion on the web visit https://groups.google.com/d/msgid/morphmet2/485d9c02-c088-477a-ab38-863316d19708n%40googlegroups.com<https://groups.google.com/d/msgid/morphmet2/485d9c02-c088-477a-ab38-863316d19708n%40googlegroups.com?utm_medium=email&utm_source=footer>. -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to morphmet2+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/morphmet2/CO6PR04MB842723EED22EE076BE9571E7A2E1A%40CO6PR04MB8427.namprd04.prod.outlook.com.