Re: [R-sig-phylo] Comparative Methods and Pseudo-Traits
Hi All, This is an interesting discussion. I'll draw your attention to two papers, one new and the other old. This is the new one: Grandcolas, P., R. Nattier, F. Legendre, and R. Pellens. 2011. Mapping extrinsic traits such as extinction risks or modelled bioclimatic niches on phylogenies: does it make sense at all? Cladistics 27:181-185. It is written from a somewhat different perspective than we usually have on this list. This is the old one, and I am taking the liberty of pasting in the relevant passage: Garland, T., Jr., P. H. Harvey, and A. R. Ives. 1992. Procedures for the analysis of comparative data using phylogenetically independent contrasts. Systematic Biology 41:18-32.Pages 29-30:WHAT KINDS OF TRAITSCAN BE ANALYZED? The independent contrasts approach isdesigned to investigate the correlated evolutionof traits that are inherited from ancestors,whatever the cause of that heritability.Thus, the phenotypic data for tipspecies are generally assumed to reflect underlyinggenetic differences among species,as could be verified through common-garden experiments (Garland and Adolph,1991). The tip species for one set of contrastscan even be different from those forthe other set, as long as the phylogenetictrees are isomorphic. This realization makesit possible to use independent contrasts toexamine coevolution of phenotypic traitssuch as body size and life span in coevolvedhost-parasite systems (see Harveyand Keymer, 1991). In addition to the usual phenotypic traits(e.g., body size, metabolic rate), cultural(see Cavalli-Sforza and Feldman, 1981), environmental(e.g., soil or water pH, meanannual temperature), and other traits thatare difficult to categorize (e.g., home rangearea) can be studied as long as they arepassed on from ancestral to descendentspecies (or populations) and have a continuousdistribution. For example, many environmentalproperties, such as latitude ormean annual rainfall, are not inherited inthe conventional (genetic) sense. Nevertheless,they are inherited in the sense thatorganisms are born into environmentalconditions and locations experienced bytheir parents at the time of birth. Thus, theancestor of two species living in a desertmay also have lived in a desert (cf. Huey,1987), or the ancestor of one high-latitudeand one equatorial species may have livedat midlatitude. Similarly, if an environmentalcharacteristic is determined solely(without externally imposed constraints)through a process of habitat selection, andif species differences in habitat selectionare genetically based, then species differencesin the environmental trait will begenetically based as well. Alternatively, ifvariation in some (genetically based) phenotypictrait can be used as a precise indicatorof some environmental characteristic,then that phenotypic trait may be usedas a surrogate for the environmental characteristic.For example, toe fringes in lizardsmight indicate occupancy of sandyhabitats. Unfortunately, this is not unfailinglythe case; some species that glidethrough the air or that run across wateralso possess toe fringes (Luke, 1986). Finally,paleoclimatological and historicalbiogeographical data might be used in conjunctionto indicate environmental characteristicsof hypothetical ancestral (as opposedto tip) species, but this takes us intothe realm of other comparative methods,such as those based on minimum evolutionreconstructions of ancestors (Huey, 1987;Harvey and Pagel, 1991; Maddison, 1991;Martins and Garland, 1991). In any case,techniques for correlating phenotypes withenvironmental characteristics require furtherstudy. Cheers,Ted Theodore Garland, Jr. Professor Department of Biology University of California, Riverside Riverside, CA 92521 Office Phone: (951) 827-3524 Wet Lab Phone: (951) 827-5724 Dry Lab Phone: (951) 827-4026 Home Phone: (951) 328-0820 Facsimile: (951) 827-4286 = Dept. office (not confidential) Email: tgarl...@ucr.edu http://www.biology.ucr.edu/people/faculty/Garland.html Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments Edited by Theodore Garland, Jr. and Michael R. Rose http://www.ucpress.edu/book.php?isbn=9780520261808 (PDFs of chapters are available from me or from the individual authors) From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on behalf of David Bapst [dwba...@uchicago.edu] Sent: Monday, November 14, 2011 12:54 PM To: Liam J. Revell; Joe Felsenstein; pasquale.r...@libero.it Cc: R Sig Phylo Listserv Subject: Re: [R-sig-phylo] Comparative Methods and Pseudo-Traits Liam, Joe, Pasquale, all- Thank you for your kind input.It seems that I am not the only one who considers this issue at length. There is just one point I'd like clarification of. Liam, in my first example which you used, the inherited trait is the response and the not-directly-inheritable trait the predictor, such that:
Re: [R-sig-phylo] Comparative Methods and Pseudo-Traits
Hi David. Poaching Intensity = beta0 + beta1*Body Size + e I think it depends on how the residual error in the model is distributed (esp. correlated) among species. It seems possible to invent hypothetical scenarios (as I did in my previous email) about how the residual error in poaching intensity given body size could be phylogenetically autocorrelated, but this is fundamentally an empirical question. If the residual error of poaching intensity given body size is phylogenetically correlated and we ignore this then we risk overestimating the predictive value of our model. In addition, the residual error is likely/guaranteed to be non-Brownian if the response variable is binary (e.g., extant v. extinct). For these type of data the tree should not be ignored, but simple GLS regression is probably not appropriate. One option might be the phylogenetic logistic regression of Ives Garland (2009), but I'm not too familiar with this method. All the best, Liam -- Liam J. Revell University of Massachusetts Boston web: http://faculty.umb.edu/liam.revell/ email: liam.rev...@umb.edu blog: http://phytools.blogspot.com On 11/14/2011 3:54 PM, David Bapst wrote: Liam, Joe, Pasquale, all- Thank you for your kind input.It seems that I am not the only one who considers this issue at length. There is just one point I'd like clarification of. Liam, in my first example which you used, the inherited trait is the response and the not-directly-inheritable trait the predictor, such that: Growth Rate = beta0 + beta1*Habitat Degradation + e What if we were to switch these? It seems to me this is the only real difference in the extinction example. To make a neontological example, let's say we were interested in whether larger mammals were more likely to experience higher levels of poaching. The response here would be the poaching intensity and body size the predictor, such that: Poaching Intensity = beta0 + beta1*Body Size + e Would your argument still apply? (It seems to me that it should.) If so, then it would seem your explanation should equally apply to extinction selectivity cases. -Dave On 11/10/2011 3:36 PM, David Bapst wrote: Hello all, A recent discussion set my mind thinking on a particular issue and, once again, I decided to ask for the general opinion of R-Sig-Phylo denizens. It may be easier to start with an example. Let's say that there exists a worker who is measuring several different traits across a number of species and then testing for correlations among these traits. The first test is body size versus growth rate and they use independent contrasts or PGLS to test for a the correlation, accounting for phylogeny. Both of these traits are inherited, evolving variables. Now let's say they'd like to test for the relationship between growth rate and some metric of the anthropogenic degradation of that species' habitat. Now what? It is even valid to apply PIC to the habitat degradation metric even though it is not an inherited, evolving trait? It's unclear to me. Let's consider a paleontological example, one which I have found myself both strongly agreeing and disagreeing with at times. Essentially, how should we test for extinction selectivity on some trait at a mass extinction event? Let's say we think body size is a predictor of the risk of extinction during that event and so we want to test for a correlation between them (please ignore that extinction would be a discrete variable for the moment). Do we treat these variable with PIC or PGLS? Is it really proper to refer to the probability of going extinct during a mass extinction as an evolving trait? Let's say we did and we got different results than when we used an analysis which did not account for the phylogenetic covariance. How should we interpret these results? One explanation I know of is that when we apply phylogenetic comparative methods to these quasi-traits to consider their relationship to another trait, we are assuming that these variables are actually the result of some underlying, unobserved set of traits which are evolving along the phylogeny. This makes sense, maybe in the extinction event case, which would mean that any PCM analysis would be testing for an evolutionary relationship between body size and these unobserved traits which predict extinction. Of course, if extinction risk is largely a function of non-inherited traits, then the initial assumption may be incorrect (that extinction risk itself is an evolving trait). Regardless, I don't
Re: [R-sig-phylo] Comparative Methods and Pseudo-Traits
Liam Revell wrote: Poaching Intensity = beta0 + beta1*Body Size + e I think it depends on how the residual error in the model is distributed (esp. correlated) among species. It seems possible to invent hypothetical scenarios (as I did in my previous email) about how the residual error in poaching intensity given body size could be phylogenetically autocorrelated, but this is fundamentally an empirical question. If the residual error of poaching intensity given body size is phylogenetically correlated and we ignore this then we risk overestimating the predictive value of our model. In addition, the residual error is likely/guaranteed to be non- Brownian if the response variable is binary (e.g., extant v. extinct). For these type of data the tree should not be ignored, but simple GLS regression is probably not appropriate. One option might be the phylogenetic logistic regression of Ives Garland (2009), but I'm not too familiar with this method. The real problem would come if the characters evolved to respond to the poaching intensity, and that evolution was inherited along the tree. Then our uncertainty about the poaching intensity in the past would be a big problem. But if poaching is only a present-day phenomenon, it would (presumably) respond to only today's characters, and they would not yet have responded to it, so there would be no problem. But I do think it is a Big Mistake (and apparently a frequent one), when people measure the residual of a character regressed on environmental variables, then casually assume that it is undergoing Brownian Motion, when the environmental variables may have been different in the past. That's probably not an issue here. Joe Joe Felsenstein j...@gs.washington.edu Dept of Genome Sciences and Dept of Biology, Univ. of Washington, Box 5065, Seattle Wa 98195-5065 [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
