RE: [MORPHMET] Re: semilandmarks in biology

2018-11-08 Thread Benedikt Hallgrimsson
Dear Colleagues,

So I’ve been wondering whether to wade into this issue..  

There seems to be an undercurrent here of mathematics vs biology, but I suspect 
that the real issue here is probably morphometric theory versus the pragmatic 
compromises necessary when using morphometric tools to answer biological 
questions.  Others on this thread have thought (and written) much more deeply 
about the interface of morphometric theory and biology than I have, but for 
what it’s worth, here are my two cents on this issue.  Fundamentally, what is 
most important is that quantifications of morphology capture relevant 
biological variation while avoiding artifacts that can skew or mislead 
interpretation. That matters much more to than whether there is real homology 
or not. I'm not even sure what "real homology" for landmark coordinate data 
means in a biological sense, even for Type 1 landmarks.  The "identity" or 
homology of landmarks tends to become messy pretty quickly when the underlying 
developmental biology is examined closely. I think Paul O'Higgins gave a great 
talk once on that basic theme if I remember correctly. Chris Percival also did 
a nice analysis showing how apparently obviously homologous landmarks that 
occur at intersections of major components of the face can drift in terms of 
the origin of the underlying tissue during development. So, I think we may 
sometimes get too hung up on this ideal that the points that we place on 
morphological structures actually represent something real. They are simply 
intended to quantify morphology within the context of a biological question.  
It's not landmarks but rather the patterns of variation that an analysis 
generates are the objective basis of study and those patterns are only 
objective within the context of a biological question. The key issue is 
avoiding artifacts that can influence biological interpretation.

In terms of this discussion, clearly semi-landmarks present one kind of 
challenge where one has to be careful about artifacts. Another, perhaps more 
currently relevant challenge, however, is the quantification of variation in 
volumetric images or surfaces that have been nonlinearly registered to an 
atlas.  In this case, one can place landmarks anywhere and recover the 
corresponding location in every specimen or image. That correspondence is a 
sort of homology and those landmarks are not slid around like semi-landmarks. 
However, they are not placed by an observer as distinct observations either.  
These kinds of points behave fairly similarly to manually placed points (albeit 
without measurement error and with artifacts that appear as one tries to 
register increasingly dissimilar shapes).  However, I think that, driven by the 
needs of the biological questions, we are increasingly going to be using this 
kind of automated quantification of morphology in morphometric analyses, so we 
need to think carefully about how to validate such data. My own bias here is 
that appropriate validations address how well (and this can be defined 
contextually) such quantifications measure the biological effects of interest 
rather than how well they simulate the behavior of manually placed landmarks. 

I suppose this is an argument for biological pragmatism, but I hope some find 
this useful. 

Benedikt

-Original Message-
From: Adams, Dean [EEOBS]  
Sent: Wednesday, November 7, 2018 6:48 AM
To: andrea cardini ; morphmet@morphometrics.org
Subject: RE: [MORPHMET] Re: semilandmarks in biology

Folks,
 
I think it is important to recognize that the example in Andrea’s earlier post 
does not really address the validity of sliding semilandmark methods, because 
all of the data were simulated using isotropic error. Thus, the points called 
semilandmarks in that example were actually independent of one another at the 
outset.
 
Yet a major reason for using semilandmark approaches is the fact that points 
along curves and surfaces covary precisely because they are describing those 
structures. Thus, this interdependence must be accounted for before shapes are 
compared between objects. The original literature on semilandmark methods makes 
this, and related issues quite clear.
 
What that means is that evaluating semilandmark methods requires simulations 
where the points on curves are simulated with known input covariance based on 
the curve itself (difficult, but not impossible to do). But using independent 
error will not accomplish this.
 
The result is that treating fixed landmarks as semilandmarks can lead to what 
some feel are unintended outcomes, just as treating semilandmarks as fixed 
points are known to do (illustrated nicely in Figs 1-4 of Gunz et al. 2005). 
But both are mis-applications of methods, not indictments of them. 

As to the other points in the thread (the number of semilandmark points, etc.), 
earlier posts by Jim, Philipp, and Mike have addressed these.
 
Dean

Dr. Dean C. Adams
Director of Graduate Education, EEB 

[MORPHMET] 2017 Rohlf Medal

2017-08-01 Thread Benedikt Hallgrimsson





*Dennis Slice is the 2017 recipient of the  Rohlf Medal for Excellence in 
Morphometric Methods and Applications  *

Over the course of three decades Dennis E. Slice, Professor of Scientific 
Computing at Florida State University (Tallahassee), has contributed in 
many crucial ways to the development, dissemination and innovative 
application of today's best morphometric methods.  His early articles and 
reviews helped teach biologists about Procrustes analysis and its 
differences from other approaches beginning well before his actual 
doctorate was awarded.  More recently, he and his students have advanced 
novel landmark-free methods for analysis of 3D image data with important 
applications in areas such as forensic anthropology that academic 
biologists rarely explore.  Along the way, he has developed 20 open source 
software packages that are widely used for morphometric analysis across the 
full range of his application fields.

 

Slice’s contributions to the dissemination of morphometric methods include 
influential surveys, edited volumes, and symposia. Particularly important 
are the dozens of courses and scores of workshops through which he has 
expanded our morphometrics community. Another major contribution is his 
commitment to the continuing advancement of this community's collective 
skills and influence through his expansion and moderation of the 
community's main web-based news outlet and question forum, Morphmet.

 

Slice’s work has expanded the range of valid applications of morphometric 
methods. His extensive publication record includes innovative and diverse 
applications of morphometrics in, among other fields, orthodontics, 
evolutionary biology, biomedical engineering, paleoanthropology, 
evolutionary psychology, protective clothing design, and marine biology. 
His funding sources are likewise diverse, ranging well beyond the usual 
list of sponsors of basic research to such institutions as the National 
Institute of Justice and the U. S. Army.

 

The 2017 Rohlf  Medal will be presented to Prof. Slice on October 24, 2017 
at Stony Brook University. Afterwards, he will present a lecture (title to 
be announced).   Previous recipients of the Rohlf Medal are Fred Bookstein 
(University of Vienna), Paul O'Higgins (University of York), and Benedikt 
Hallgrimsson (University of Calgary).


Click here <http://life.bio.sunysb.edu/morph/RohlfMedal/travel.html> for 
notes on travel and accommodations if you plan to attend.

 

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[MORPHMET] Call for nominations for the 2017 Rohlf Medal for Excellence in Morphometrics

2017-03-20 Thread Benedikt Hallgrimsson


*2017 CALL FOR NOMINATIONS*


*The Rohlf Medal*


The Rohlf Medal was established in 2006 by the family and friends of F. 
James Rohlf to mark his 70th birthday. He has been a longtime Stony Brook 
University faculty member and is currently Emeritus Distinguished Professor 
in the Department of Ecology and Evolution, and Research Professor in the 
Department of Anthropology. 

 

Recipients of the Rohlf Medal will be recognized for excellence in their 
body of work on the development of new morphometric methods or for their 
applications in the biomedical or biological sciences, including 
evolutionary biology, population biology, physical anthropology, 
developmental biology, neurobiology, computer sciences and medicine. The 
term ‘morphometrics’ is intended to include high-dimensional pattern 
analyses of biological shape, especially those that analyze shape in a 
comprehensive way, or of covariation of shape with other variables. The 
award can recognize advances in the mathematical or statistical theory 
underlying morphometric methods, new software that implements or visualizes 
new methods, or specific new biological findings that rely crucially on 
contemporary morphometric methods and represent major advances.

 

Candidates for the Rohlf Medal may be self-nominated or nominated by 
others. They must possess a Ph.D. degree or the equivalent.

 

The winning candidate must agree to attend the award ceremony in person in 
order to accept the Rohlf Medal and then deliver the award lecture.

 

 

Nomination packages should include, 

(1) a description of the body of work (not to exceed two pages) on which 
the candidacy is based, 

(2) reprints of no more than three relevant papers and/or software 
products, 

(3) a curriculum vitae, and 

(4) three letters of support. 

 

Nominating packages should be uploaded to the Rohlf Medal website 
(http://life.bio.sunysb.edu/ee/rohlf_medal/apply.html) and received by 5 
pm, EST, 15 July 2017 to be assured of full consideration.

 

The successful candidate will receive the Rohlf Medal and a cash prize at 
Stony Brook University, planned for October 24th, 2017.  She or he will 
deliver a lecture that is appropriate for a broad audience, ranging from 
the exact sciences to the humanities, concerning the morphometric 
methodology, software, or findings for which the Rohlf Medal was awarded.

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2017-Rohlf Medal Call for Nominations Final.docx
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