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Hersheypark Stadium is perhaps the most prominent outdoor, multi-purpose facility to be found anywhere between Philadelphia and Pittsburg. With a seated capacity of 16,000 in the stands, and a total capacity of 30,000, Hersheypark Stadium an obvious choice for those looking to host or attend any large-scale event in that area.
The Hersheypark Stadium schedule is as varied as it is impressive. A state-of-the-art synthetic grass system renders the venue ideal for hosting athletic events, while its size and acoustics cater perfectly to concerts by the likes of Bob Dylan, Dave Matthews Band, *NSYNC, U2, Bon Jovi and The Rolling Stones - just a few of the stars who have graced the stage at Hersheypark Stadium over the years. Rodeos, football, racing events, pageants and festivals have also featured in the Hersheypark Stadium schedule in the past.
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New publication ( Returning to the roots: resolution, reproducibility, and robusticity in the phylogenetic inference of Dissorophidae (Amphibia: Temnospondyli); Gee, 2021; PeerJ)
Title: Returning to the roots: resolution, reproducibility, and robusticity in the phylogenetic inference of Dissorophidae (Amphibia: Temnospondyli)
Journal: PeerJ
DOI: 10.7717/peerj.12423
General summary: Phylogenetics, the means of inferring relationships among organisms and one way of classifying them, is a timeless part of paleontology, in part because our datasets are much more limited than those for modern organisms in which genetic barcoding is both widely accessible and robustly informative. As a result, there is often a lot more uncertainty and disparity among different analyses, and people should generally be skeptical when someone says there is a strong consensus for a given group, no matter how well-known (paleo nerds will definitely recall the debate a few years back about what 'Dinosauria' constituted). Temnospondyls are generally not well-known, and this means that they are not as well-studied. This often has the effect of resulting in one or two people producing a lot of the work for a given group, which can lead to an overstated consensus when the same dataset keeps getting used. Dissorophids, the armoured dissorophoids, are a great example of this. There is a ton of work, but pretty much everyone uses the same phylogenetic matrix. As you might imagine, analyzing pretty much the same dataset a bunch of times should lead to pretty much the same result, which would not be particularly compelling as a "consensus," but, SPOILER, there is in fact no consensus among these nearly identical analyses! That's a huge issue. This study delves into why, both through a separate phylogenetic matrix and from closely scrutinizing the previous one. There is a ton of data packed into it, but the short and skinny are that (1) previous studies have been compromised by systemic errors from the original; and (2) there is a general lack of resolution / of well-supported nodes among dissorophids (i.e. we don't know a lot more than we do know). Then there's a bunch of other toss-ins like missing holotypes and chimeras. Keep reading to find out more!
This is an example of an admittedly "boring" paleontological study. There are very few pictures of fossils, none of which are particularly nice specimens; the results will never turn into some kind of remarkable paleoartistic reconstruction; and you will never hear about these findings in the news. Nonetheless, studies like this underpin the very foundations of paleontology and all of those attention-grabbing paleontology headlines, which hopefully will become apparent from this post / paper.
Phylogenetics 101
Before getting in to the details of this particular paper, I think it's important to give an overview of phylogenetics for readers who maybe don't know very much (or anything) about it. (Those familiar with phylogenetics can keep scrolling). I've touched on phylogenetics before in relation to some of my other papers, but I'll review some key terms and ideas here, beginning with "what is phylogenetics?"
What is phylogenetics: Broadly speaking, phylogeneticists study the evolutionary relationships between organisms. This is a little different than systematics/taxonomy, which is how organisms are classified and categorized (e.g., in that old Domain-Kingdom-Phylum-Order-Class-Family-Genus-Species hierarchy you learn about in grade school). Phylogeny often informs taxonomy (this is cladistics), but it is not the only way to do taxonomy.
How is phylogenetics done: In the pre-computer era, all phylogenetics was qualitative - scientists looked for what they thought were key features (e.g., limbs, feathers, teeth) and tried to find an evolutionary scheme that related organisms to each other based on whether or not they had these features. Certain features were more "generalized" (common), like teeth or limbs, while others were more "specialized" (rare), like opposable thumbs or wings. The shortcoming of this is that it's subjective - what features are considered or the relative weight attributed to them were up to the scientist. In the computer era, we have programs that have algorithms to quantitatively assess relationships. I go into more detail on this below!
Why is phylogenetics important: Phylogenetics is often overlooked for two reasons: (1) it is very tedious and not really the kind of stuff people like reading about in NYTimes headlines; and (2) it requires a very in-depth knowledge of a certain group. However, phylogenetics underpins practically all biological studies because it relates organisms to each other. Any comparison therefore requires knowledge of how a given organism is related to another. For example, comparing animals with wings requires the context that many of them are entirely unrelated to each other - consider butterflies, birds, and bats as an example. Phylogenetics also provides the evolutionary narrative for how life has changed. Differences that seem very stark in the modern day make more sense when viewed through a deep-time lens of evolution and gradual changes and divergences.
The data. Data entry is the first step in computer-assisted phylogenetics. What we do is make a character matrix with a lot of numbers. The image below is a partial screenshot of one matrix that I worked with for this study. On the left-hand side, you have all the names of the different species being studied. On the top-row, oriented diagonally, you have names of different characters (these are different features being assessed). The rest is made up of numbers, which are colour-coded in this example.
Phylogeneticists begin by sampling taxa - which species do they want to study? Without going into details, paleontologists have particular challenges because some taxa are only represented by fragments, and these tend to be very bad for phylogenetic analyses because they are scored for very few characters, so usually these are omitted. It is very rare to include every species of a group that you are interested in. Then they sample characters - which features differentiate these species? A simple example:
Limbs: present or absent.
Here we have a binary character related to the presence or absence of limbs. This is quite straightforward, but most analyses have characters that require in-depth anatomical knowledge of a group, such as "palatine partially or fully excluded from interpterygoid vacuity or not excluded at all." The different possibilities (e.g., present vs. absent) are called character states, and they are assigned numbers. An example:
Limbs: present (0) or absent (1).
These are the numbers you see above. The majority of characters are binary - oversplitting can make things overly complicated. But you will sometimes see these multistate characters. An example:
Tooth count: >50 teeth (0), 40-50 teeth (1), <40 teeth (2).
Data can be entered in other forms too. Molecular biologists use genetic sequences with base pairs (A, C, T, G, U) in place of numbers. But paleontologists only have morphological data, so we're left with these numerical schemes. Question marks, as you might imagine, represent missing data - the fossil record is not good enough to score that character for that taxon.
Parsimony. The next part of the analysis is what we call an optimality criterion. The program has all of these data. But what kind of a solution is it looking for? We would like the one that we think is the most accurate, but how do we get that? Historically, phylogeneticists (people who study the relationships between organisms) have used parsimony, which is not merely a method but more broadly a system of logic. Parsimony, often related to Occam's razor, favours a solution or explanation that requires the least assumptions (this is not exactly the same thing as the more widely disseminated "simplest is best").
In today's phylogenetic concept, we infer that snakes descended from ancestors with limbs and that they represent an uncommon example of secondary limb loss, rather than that they descended from an ancestor that never had limbs and that many other tetrapods independently evolved limbs (source: Charles Baker via Wikimedia)
For example, when observing the diversity of modern animals, it requires fewer assumptions to say that limbs evolved once, in the last common ancestor of all tetrapods, and have subsequently been lost independently in some groups than it is to say that limbs have evolved independently many times (it is not very easy to independently innovate complex features like limbs). When applied to phylogenetics, parsimony seeks the solution (a tree depicting relationships) with the fewest character transformations, or evolutionary changes. So a tree that captures a single origin of limbs is more parsimonious than one that captures multiple independent origins of limbs.
It's important to note that the simplest explanation is not always the right one. Life finds ways to do some really weird stuff. The gist is that parsimony is a workable baseline. Once we allow for more complicated solutions, the number of possible solutions increases exponentially, and it becomes both computationally expensive to search for them and difficult to actually figure out which one is the most likely (but this is where likelihood methods come in, which I'm not talking about here).
The output. A parsimony analyses will return what are called the most parsimonious trees (MPTs). There can be as few as one but are often many more. All of these MPTs have the same "length," which is given as a number of steps, which are essentially the number of evolutionary changes that had to occur to produce a tree with these relationships. If there are multiple MPTs, they will differ from each other at least slightly. In the example below, we recovered three MPTs. The red "taxa" (A–D) are ones whose relationships differ between each MPT. Note that some taxa may have the same relationships across all of the MPTs.
We then have different ways of summarizing the results (some of these are controversial).
The strict consensus will "collapse" any node that isn't found in every MPT. For example, the relationship of A + B is found in the first and the third MPTs, but not the second MPT. That node is collapsed. The relationship of (A + B) + C is found in the first and the second MPTs, but not the third MPT. That node is also collapsed. A + C and (A + B) + D are each found in only one of the MPTs, so those nodes are also collapsed. Conversely, E + F is found in all MPTs, so it stays. This consensus is overly conservative. We do not believe that A, B, C, and D all split from each other simultaneously in an evolutionary sense. But because each MPT represents an equally parsimonious solution, we cannot discern in a quantitative sense which one is more likely.
The majority-rule consensus will only collapse a node that is found in less than 50% of the MPTs (in this case, any node found in only one MPT). So while A + B is not shown in the strict consensus because it was only found in two of the three MPTs, it is shown in the majority-rule consensus. Now one of the reasons why people don't like the majority-rule consensus is because it can be somewhat misleading. For one, if you have hundreds to thousands of MPTs, the resultant majority-rule consensus might depict a tree that is not found in any MPT. In the simple example here, the majority-rule consensus is the same as MPT #1, but that doesn't always happen. Visually it can be misleading too. For example, you might be inclined to interpret the majority-rule consensus below as saying that A + B is found in 67% of MPTs and that (A + B) + C is also found in 67% of MPTs. The former is true, but the latter is not. (A + B) + C is only found in one MPT. (A + C) + B is found in one other MPT. So it is only accurate to say that A + B + C is found in 67% of MPTs.
There are other types of consensus methods (e.g., Adams, semi-strict) that I won't go over here, but you can read more about them in a pretty easy read by dinosaur paleontologist Tom Holtz here.
The actual study (finally)
Okay, we are finally to the part where I talk about the actual study! This study looked at a group of dissorophoid temnospondyls, a group mostly found in the late Carboniferous and early Permian that I worked on for my dissertation (this is not part of my dissertation though). More specifically, I was looking at the large terrestrial dissorophoids, collectively known as olsoniforms (named after E.C. Olson) and which includes two groups, dissorophids and trematopids (yes, 'dissorophid' is one letter away from 'dissorophoid' and requires careful reading to avoid confusing).
This study builds off of one of my previous phylogenetic studies, which looked specifically at trematopids. The point of that study was demonstrating that we actually don't have a good handle on the phylogeny of trematopids because all previous studies sampled only four to six of the ten known species. Excluding certain taxa is a good way to improve resolution sometimes, but it can oversimplify things too because you're intentionally excluding data. It's well-known that adding one taxon to an existing matrix can drastically alter the results (pitfall of working with morphological data is most relationships are not very well-supported).
Now what I wanted to do was to take the matrix I made for that 2020 trematopid study and expand it to include dissorophids, thereby forming an olsoniform phylogenetic matrix that comprehensively sampled all appreciably known taxa (no previous study has done this). What I ended up doing was a lot more than that, which is where the alliterative title comes in: "Returning to the roots: resolution, reproducibility, and robusticity in the phylogenetic inference of Dissorophidae (Amphibia: Temnospondyli)." I'll go through these three themes: resolution, reproducibility, and robusticity next.
Resolution predictably refers to how well-resolved the tree is. In the figure on the left, the tree on the left is not well-resolved. It has a lot of what we call polytomies, where more than two taxa share the same node (A–D is one polytomy, E–G is another). The tree on the right is fully resolved. We want the tree on the right because it gives us more precise information on relationships (e.g., that A + B are closely related). But we don't usually get the tree on the right, we get the tree on the left. Or if we get the tree on the right, it's by some sketchy fiddling.
Recent dissorophid phylogenies, shown below, display a range of resolution. There are two points of emphasis here. One is that disparity between studies. Most of these show large polytomies, but Liu (2018) nearly got the fully resolved tree that we're looking for. The second point speaks to what I commented on above - fiddling with the analysis to get resolution where none existed before. If you look at Dilkes (2020), there are two trees. The one on the left is poorly resolved. This is not very helpful for discussing relationships or evolution. The tree on the right is very resolved. We like that one! But to get that tree, Dilkes had to remove four taxa from the analysis. These taxa, often called "wildcards," are problematic in the sense that they confound resolution, whether because they are really fragmentary and have a lot of missing data or present weird combinations of features that don't line up with general trends. Removing wildcards is a common strategy to boost resolution, but like I said above, it inherently omits data that you know exist.
The problem crops up when people use the reduced-data results, which gives the more resolved tree, to talk about evolution and classification schemes, but then place omitted taxa in that framework. For example, Brevidorsum profundum is a typical dissorophid "wildcard." It's only known from one partial skull described in 1964 and is not well-preserved. Some people don't even think it's a dissorophid. Brevidorsum is either recovered within a large polytomy (uninformative) or is excluded from the analysis, but some workers constantly refer to it as being a member of a specific subfamily within dissorophids: Cacopinae (the dark green boxes). However, no recent analysis has ever demonstrated support for that, and this is where the old-school qualitative methods ("it sort of looks like that") and the modern quantitative methods ("the analysis says X") combine in a bad way.
My own analyses tended to recover very poor resolution. Sometimes this could be attributed to including a lot of pretty fragmentary taxa that aren't normally included (like the analysis shown above on left). When it looks like a giant comb...that's an uninformative tree. I could further extend that by showing that removing just a few taxa, some of which are not that badly preserved, could lead to a drastic increase in resolution (like the analysis shown above on right), similar to that example I just cited above.
Summary: Resolution is generally quite poor in olsoniform, dissorophid, and trematopid analyses. The only way to get decent resolution that allows one to create a detailed narrative of evolutionary history is to remove a fair number of taxa from the analysis, which only allows you to create a coarse-level narrative that often omits the "weird" taxa that may in fact figure prominently in a clade's evolution.
Reproducibility is one of the foundational tenets of science. If someone does an experiment again, can they get the same results? The first step in this process is that it has to be clear how to reproduce an experiment. If you run a complicated study of colour preference in spiders, but only say "we picked some spiders and not others for this experiment" in your methods, it will be impossible for someone to know the specifics of how you did the experiment. So even if someone redoes an experiment on colour preference in spiders, it will likely not be the same as your experiment. Maybe they picked the wrong spiders. Or used different colour palettes. Etc. Because of this, whether their results are the same or not ("spiders like flaming hot pink") as yours, comparing them is difficult because differences in the methods could be responsible for the outcome.
In phylogenetics, the main areas where reproducibility comes into play are (1) the character matrix; and (2) the parameters of the analysis. Most journals require people to include their character matrix in one form or another, but ambiguity in the requirements is one problem – some people include their matrices in very inaccessible formats that have to be modified or typeset before a program can analyze them (even though the software to make universally accessible formatted files is F-R-E-E and easily available). In the simplest format, all of those scores in the nice GUI display as text strings:
Example taxon A: 0000100002???0000???0
But often times people provide their scores in unhelpful fashions like this:
Example taxon A: 00001 00002 ???00 00??? 0 [block format]
Example taxon A: 0 0 0 0 1 0 0 0 0 2 ? ? ? 0 0 0 0 ? ? ? 0 [space-delimited]
Example taxon A: 0 0 0 0 1 0 0 0 0 2 ? ? ? 0 0 0 0 ? ? ? 0 [tab-delimited]
Now these formats might help you read the string when the numbers are spaced apart...or you could just use Mesquite and have them all in a nice readable interface where you can colour code different character states and see exactly which character a score is for instead of having to count everytime, as seen below.
So when people don't provide their scores in an accessible format like the NEXUS file above, that means the next person has to edit or transcribe the data, which can introduce errors (indeed, I found a few errors in older studies where they had to transcribe it from a previous study and introduced a typo). Below is an example of a very inaccessible data matrix (the dissorophid matrix of Schoch, 2012); this is a figure of a table that cannot be OCR'd (even with the original publisher's version). This means that anyone who wanted to use this matrix would have to type out all of these scores themselves! That is a big waste of time.
Reproducibility doesn't always have to be about repeating the exact same experiment though – more straightforward experiments or ones where the results are intuitive (i.e. doesn't seem like there was data manipulation or accidental error) can be a waste of time to repeat except in coursework. So an alternative way to test reproducibility is to see whether an independent approach to the same question can recover the same solution. If the same general results are recovered, this really strengthens the argument derived from them. If there are different results, that provides an opportunity for future work to figure out why there are discrepancies.
One characteristic of most previous dissorophid studies is that they all draw from the same source matrix (Schoch, 2012; this is the blue bubble in the 2012 row in the figure above). This is common practice in science – taking an existing matrix and adding taxa of interest. It saves a lot of time because creating a new matrix is a lot of work! But there are two important points here. The first is that if everyone uses the same matrix and doesn't make many changes, each derivate of that matrix is not fully independent (we call these pseudoreplicates). Each pseudoreplicate is predisposed to producing the same results as the last iteration because the underlying data are nearly the same. So getting the same general result from five pseudoreplicates is not as much of a "consensus" as getting the same general result from five independent matrices. Essentially, this can be misleading and make you think that the results are very reproducible when that is really just because the data are nearly identical. This leads to the second point, which is that the data must be solid when they're getting propagated, otherwise you're just propagating errors.
Immediately, there is a big red flag when looking at dissorophid phylogeny:
Results of recent attempts to unravel the phylogeny of dissorophids, even though they are using modified and hopefully updated versions of the same matrix, have consistently shown a lack of agreement on a broader pattern of dissorophid relationships with poor resolution and low support for most nodes that are present in a strict consensus tree." (Dilkes, 2020:26)
There is no consensus among these pseudoreplicates, in spite of being 99% similar to each other!. Not getting a consensus from a bunch of pseudoreplicates is really concerning because it indicates that relationships are not well-supported and can easily change with just the addition of one taxon or a few scoring changes!
The explanations. There are a lot of different explanators for why there are different results. Some of these are a little more towards personal preference in setting different parameters in the analysis. One probable explanation is that the taxon sample differs slightly between studies; those with more resolution tend to have omitted more of those "wildcards" that are weird or highly fragmentary. If you compare the results of Maddin et al. (part C above) and Schoch & Sues (part D above), this is a likely explanator for why the former is much less resolved - it includes historical wildcards like Brevidorsum profundum, fragmentary taxa like Broiliellus olsoni, and somewhat odd taxa like Reiszerpeton renascentis (the holotype of which was long considered to be an amphibamiform dissorophoid).
Taxon samples are low-hanging fruit for explaining topological differences. So I went deeper and started looking at specific cells in the matrix to see if there were perhaps typographic errors (I did find some of those). However, I found a lot more errors that do not seem to be typographic. I looked at the latest version of the Schoch (2012) matrix, which was the one published by Dilkes (2020). I identified over 140 scoring errors, which is a lot in a fossil matrix that only has up to 77 characters and 29 taxa. Many of these were instances where Taxon X was scored for Feature Y...except Feature Y isn't even known in Taxon X! One example is Cacops woehri from the Richards Spur locality. This taxon is only known from partial skulls, but somehow it was scored for a bunch of postcranial characters. Suspiciously, all 14 scores of this taxon that were erroneous were scored the same as Cacops morrisi, also from Richards Spur but which is fairly distinct from C. woehri. In fact, this deep dive revealed that the three species of Cacops, which are readily differentiated from each other, didn't actually differ in any scores other than their distribution of missing data (i.e. when they could be scored, they were all scored the same). This explains why all previous analyses recovered them as a single polytomy, when qualitative comparisons clearly show that C. morrisi and C. aspidephorus are much more similar to each other than to C. woehri (which might not even be Cacops).
Cacops was the most egregious example of what seems to be previous workers "assuming" scores that are not validated by the present fossil record, but other taxa also seemed to have scores here and there where a score was "assumed" based on the general affinity of that taxon (e.g., that some dissorophids with no known quadrate had a dorsal quadrate process preserved; this is a common feature in dissorophoids). This is, of course, a major problem! If you have what you think is a new species of Cacops, and you score it for a bunch of features of other species of Cacops, you have pretty much guaranteed yourself of the outcome that you are allegedly testing because you have made this new species more similar to its alleged relatives than the fossil record actually bears out. Cacops aspidephorus is the best example of this - for over a century, nobody knew what the sutures were because the specimens were so poorly preserved. You could see this if you looked at reconstructions of the skull of different dissorophids, like from Schoch (2012) below. As you can see, C. aspidephorus is just a grey blob - no sutures. Why then, were there 15 scores for C. aspidephorus for characters that require sutures to be known? The sutures of the skull, based on a few specimens that were not so bad off, would not be published for another eight years until Anderson et al. (2020). In fact, other than characters with missing data for one or two of the three species, there were no characters for which one species of Cacops was scored differently than another.
Other issues relate to how characters are defined. For example, if a character requires skull length to be known, it doesn't make sense to score a taxon only known from specimens that aren't complete longitudinally. However, taxa like these were scored for these characters. Issues with characters like these that explicitly require certain landmarks but that seem to be scored in the absence of at least one were fairly common as well. In the examples below, both Brevidorsum profundum (only one specimen; Carroll, 1964) and Reiszerpeton renascentis (only one specimen; Maddin et al., 2013) are known from incomplete specimens. Therefore, their skull length is not actually known, but characters that require a ratio invoking the skull length were scored for these taxa previously.
As one might expect, correcting a large number of errors and then rerunning an analysis leads to drastically different results. On the left of the figure below are the original results from the Dilkes' matrix, and on the right are the results when the corrected version of the matrix is analyzed. There is a major loss of resolution! This suggests that at least some of the inconsistencies between previous pseudoreplicates of this matrix result entirely from erroneous scores in the matrix.
Furthering the issue is that these systemic errors didn't just appear in the latest version of Schoch (2012), published by Dilkes (2020). In fact, none of them were introduced by Dilkes, which I feel is very important to state, lest the reader think that Dr. Dilkes produces error-riddled work. Most of the errors go back to the original matrix and were thus introduced by Schoch, although some were separately introduced as taxa were added (e.g., Holmes et al., 2013; Liu, 2018). This means that every single previous study that used this matrix has also been compromised. I suspect, though I didn't test this, that correcting the same scores in all of the previous matrices would result in a loss of resolution in all of them, but this would actually boost the similarity between studies because the resolution of wildcard nodes would be eliminated.
Summary: Previous dissorophid analyses are highly irreproducible insofar as the source matrix (Schoch, 2012) contains substantial errors, many of which seem to be based on assumed anatomy that cannot be validated from the fossil record. This has likely compromised studies that analyzed this matrix or a derivate thereof with respect to resolved relationships within Dissorophidae (unresolved relationships are probably okay).
Robusticity
Without some assessment of reliability, a phylogeny has limited value. It may still function as an efficient summary of available information on character-state distributions among taxa [...] but it is effectively mute on the evolutionary history of those taxa (Sanderson, 1995:299).
One of the challenges with strictly morphological data is that there are just not very many datapoints. Compared to thousands to millions of genetic base pairs in molecular analyses, the average fossil tetrapod matrix has between 50 and 350 characters. This means that just a few scores could be responsible for a certain recovered relationship, whether a longstanding one or an entirely new one. Sometimes, even changing just a single score can change the entire tree! This is where support metrics come in. These are statistical means of assessing how "strong" or "robust" a given node is; in other words, is this relationship likely supported by only a single score, and thus not very reliable, or are there many lines of evidence (scores) supporting it? In parsimony analyses, there are two conventional methods of assessing support.
Bootstrapping: Say you have a character matrix with 8 taxa and 14 characters. Bootstrapping is called "resampling with replacement." In one bootstrap replicate, the program will randomly select a character and its correspondent scores. Let's say it selects character #7 from the original matrix. This now becomes the new character #1 in the bootstrap. The program then picks the new #2 and the new #3 and so on. The caveat is that it can pick a character from the original matrix that was already selected. So it could pick character #7 three times in a row. It keeps picking until it has the same number of characters as the original matrix. Invariably, it is almost a given that some characters will be resampled multiple times, which means others are not sampled at all. Then you run this a lot of times (like 10,000) and calculate the percentage of these resampling replicates that nodes are found in. If you get low bootstrap support, that means very few replicates recovered that relationship and suggests that it is not well-supported because it is probably linked to one character. Bootstrap support over 50% (a node occurs in >50% of the bootstrap replicates) is considered "strong."
There is an alternative to bootstrapping, called jackknifing, which is "resampling without replacement." In this scenario, you designate a certain percent of characters to keep, and the resampling will keep that percent. So if you do a 60% cut, it will pick 60% of the characters (no duplicates like can occur in bootstrapping) and rerun the analysis, then repeat X number of times. This is rarely used in phylogenetics today, but the principle of jackknifing, termed "leave-one-out," is still common in other studies where analyses are repeated with a different data point omitted each time. This can help demonstrate the impact of outliers, for example.
Bremer decay index: Bremer support is an entirely different measure that has nothing to do with resampling. Bremer decay calculates how many additional "steps" are needed for a given node to collapse. This is exclusive to parsimony analyses as a result since it is predicated on the number of steps in the most parsimonious tree(s). Some programs have an automated way of calculating Bremer support, but the common way to do it is to get the MPTs and the number of steps among them, then get the strict consensus. Then you rerun the search and tell it to save not only the MPTs but also all trees that are +1 step longer. This will inherently be more trees and it includes trees that are not the most parsimonious. Then you get the results, compute the strict consensus, and if a node previously found is no longer found, that node has "collapsed." If it collapses at +1 steps, then its Bremer decay index is 1. You then proceed to do this search for all trees +2 steps longer, +3 steps longer, etc. >3 is considered "strong."
It is standard for scientists to report at least one if not both of these support metrics because it tells you how robust your recovered tree is. If a tree is not well-supported, then even one scoring error or dubious score could be producing this topology. Analyses with my matrix tended to recover low support for at least one of these metrics. I used a visual key to indicate whether a node was strongly supported or not by marking "weak" support in greyed-out text. You can see in the example below, which was an analysis of my matrix with the same taxon sample as Dilkes (2020), that there is a lot of grey... In fact, in this particular analysis, the only node with both strong Bremer and bootstrap support is the node for trematopids (orange circle), which was not even a focus of this analysis!
Previous dissorophid studies are a giant mixed bag. Some studies only reported one metric, and others didn't report anything. The latter is particularly bad because it emphasizes getting resolution (intentionally or not), no matter how weakly it might be supported or how few characters it might hinge on. This can lead people to "tinker" with the matrix, leaning one way when they're on the fence or specifically making modifications to certain characters or taxa until the expected or desired result comes out. It might be a reason why there were so many errors in the Schoch (2012) matrix in which one species was scored the same as another species in the same genus – scoring based on assumptions like this is a great way to boost both resolution and support. It's a reminder that even an "objective" quantitative method like computer-assisted phylogenetics is still underlain by subjective human decisions. Furthermore, when support is reported, it's often weak except for really large clades. For example, it isn't really that surprising or informative in a dissorophid-focused study that Dissorophidae is a strongly supported node unless you were suspicious about whether all dissorophids actually formed a clade (this isn't particularly controversial).
This is an example from the Dilkes (2020) analysis. As a reminder, "strong" support is Bremer > 3 (the first value) and bootstrap > 50 (the second value). Values near the bottom (more inclusive clades) are high, but they get really low as we go up the tree. Like my own analyses, trematopids (node E) have excellent support...but we're not studying trematopids in this analysis... Once you get into Dissorophidae (node J), which is what we wanted to study, no in-group node has Bremer > 1 (literally the lowest it can be) and most of them have bootstrap hovering around that 50% threshold. This isn't an indictment of the scientist, just to be really clear. But it does underscore that the topology of the tree is not the only thing that matters! Weakly supported relationships are just that – weakly supported.
Summary: Even when there is resolution achieved in dissorophid analyses, the statistical support is weak for most nodes except those that are outside of Dissorophidae. So this suggests that the inconsistent topologies between pseudoreplicates of Schoch (2012) are all insignificant insofar as one is not preferable because none is strongly supported statistically. Reporting these stats is important, even if it hinders what author(s) can say.
A few other goodies...
Having already gone way further into the weeds than I intended to for this project, a lot of the discussion is a comprehensive synthesis of where things stand with dissorophids in their entirety. I overview Cacops, which could get a little help from a revision of Parioxys, a taxon originally interpreted as an eryopoid (and thus commonly placed as one in supertrees) but that in fact seems to share many similarities with Cacops. It has not usually been compared with dissorophoids at all, but could it be one? I also commented on Broiliellus, which is a dumpster fire of a genus. Nobody has ever recovered Broiliellus as a clade except by...you guessed it...excluding taxa. My preference is to restrict Broiliellus to the type species, B. texensis, and put everything else in single quotes (e.g., 'B.' reiszi) until this can be sorted out (some of these taxa have not been described since the 60s).
Then we have two more exciting discussions, the first a missing holotype and the second a possible chimera.
These humble and extremely fragmentary osteoderms are AMNH FARB 4785. This is the holotype of "Aspidosaurus apicalis," allegedly a dissorophid and definitely a taxon that only 10 people remember on any semi-regular basis. These look kind of different from any other dissorophid, but there is a lot of diversity in this group, so...dissorophid? This specimen should not be confused with AMNH FARB 4785a, which is the holotype of Platyhystrix rugosa, the iconic sail-backed dissorophid (seen below in figure from Lewis & Vaughn, 1965) and which was split out from the original AMNH FARB 4785 once its distinctiveness was recognized.
Allegedly, AMNH FARB 4785 should not exist! Dating back to the 60's, people said this specimen was missing. But I found it! (technically I found it in 2017 and said as much in a 2018 paper). But then where is AMNH FARB 4785a, which was apparently confused for AMNH FARB 4785? Concerningly, that specimen is nowhere to be found, and there is no record of it in the museum database or in their most recent inventory. It is always bad when a specimen goes missing, let alone a holotype. However, as far as I know, this specimen has never even been figured, only described generically as spines. It certainly wouldn't be the first time that a specimen just disappeared.
The biggest problem here is that as far as I know, AMNH FARB 4785a has never been figured in any form, only described in a brief and generic fashion (at least enough to indicate that it did represent the stereotypical Platyhystrix morphology). This might be because spines of Platyhystrix are common, and many were published with figures shortly after the original description (also, photography was hard in 1910). What I suspect, though cannot prove, is that AMNH FARB 4785a was renumbered. Sublettering is not a common modern collections practice, especially when there are two totally different taxa represented by a number. It leads to a lot of confusion because the sublettering is often dropped, which is evidenced by pretty much every publication that refers to the holotype of Platyhystrix rugosa and which refers to it as only AMNH FARB 4785, not 4785a (e.g., Berman et al., 1981; Schoch & Milner, 2014).
Above is AMNH FARB 11544. These are characteristic spines of Platyhystrix rugosa (part A). Coincidentally, this specimen was collected in 1881, the same year that AMNH FARB 4785a was collected, and they were both collected by the same guy from the same bonebed in New Mexico. However, AMNH FARB 11544 was not described or figured for a century until Berman et al. (1981). However, it meets the original description of AMNH FARB 4785 ("several spines") by E.C. Case in 1910, includes several that are in line with the measurements given by Case, and even includes a partial synapsid scapulocoracoid that was also mentioned by Case. The coincidence is almost too compelling! But there is no record of a number transfer, even after I checked with the AMNH collections staff (who have no record of AMNH FARB 4785a in their database on in the most recent inventory), so at present, the holotype of P. rugosa remains the missing AMNH FARB 4785a. I put this in the paper in the hopes that someone will be able to shed more insight on this...
Chimeras are often thought of as mythical beasts with different body parts of different animals. Chimeras actually do exist in real-life, just in a genetic sense that often expresses itself in much more...subtle...fashions than having a body with different animal parts (Wikipedia is a good start for reading directions). This is not exclusive to experiments in labs either; chimerism can be natural, albeit relatively rare. In paleontology, chimeras mean something else – a composite specimen that includes elements not only from different individuals but from different species (so the Triceratops display that was made with bones from five different skeletons is not a chimera). This is usually thought to be unintentional, although with the booming market in fossil sales, intentionally doctored fossils that combine multiple species to form mindblowing (and thus attractive) combinations of features are becoming more popular. There have been several high-profile instances of intentional doctoring in this way of Chinese early birds and the Piltdown Man, allegedly an early human relative.
The "Chimera d'arezzo," a bronze sculpture thought to be made in 400 B.C.E. and on display in Florence (source: u/ Mustang Joe via Flickr).
Most examples of chimeras in paleontology are unintentional. They frequently result from assumptions that a collection of bones from the same spot, without excessive elements (e.g., five femora), belong to not only the same species but to the same individual. This is where preconceived biases can come in; everyone will have a list of "likely candidates" for a fossil when they come across it (e.g., you do not expect to find any temnospondyls in the Cretaceous Hell Creek Formation alongside Triceratops), but sometimes this list is too restrictive. A recent example is Dakotaraptor, a putative dromaeosaurid dinosaur (Velociraptor group) in which the purported wishbone turned out to be part of a turtle (see here). Another was a relatively rare report of a pterosaur pelvis from Canada that turned out to be part of a tyrannosaurid skull (see here and here). As far as I know, nobody's ever definitively identified a temnospondyl chimera.
That's where Aspidosaur binasser comes in. This taxon is based on one specimen from the Permian of Texas. It includes several skull fragments that collectively fill out most of the top of the skull and about 20 vertebral positions. This species is interesting for a couple of reasons. The first is that Aspidosaurus (like "Aspidosaurus" apicalis above) is a wastebasket taxon, encompassing a bunch of generally similar morphotypes that probably don't represent a single taxon. These morphotypes are largely isolated osteoderms that form an inverted V shape; cranial material of Aspidosaurus is practically unknown, which wasn't helped by the destruction of all material of the type species (which did include a skull), A. chiton, during an Allied bombing of Germany in WWII. So A. binasser is the best (and only) skull material we have. Then, A. binasser was described as having three different osteoderm types (shown below; figure from Berman & Lucas, 2003), which is unprecedented variation – other dissorophids only have one type, though it may change slightly in width or other minor attributes. And this is really where things start to get a little suspicious.
Despite having a good portion of the skull, including the occiput, which is the neck joint, and 20 vertebral positions from specifically the presacral (anterior to the pelvis) region, there is no articulation between anything. All three osteoderm types are found on their own; there is no block or fragment with two or three different osteoderm morphotypes on it. Then there is the peculiar question of where are the atlas and axis (the neck vertebrae)? Most dissorophids seem to have between 20 and 25 presacral vertebrae, so what are the odds of getting half the skull and 20 presacral vertebrae but not the neck vertebrae? If this holotype is a chimera, it would be really hard to prove because it's not like some composite Chinese bird that was Frankenstein'd together from different slabs, and all of the material does appear to be genuinely dissorophid in nature. And unlike how finding previously unidentified fits can positively prove association, not finding fits is not necessarily evidence for chimerism.
This is where a bunch of old, fragmentary specimens come in. These are nothing to write home about, but the key here is that they look like two of the three osteoderm morphotypes in Aspidosaurus binasser, conveniently the two that are not the most stereotypical Aspidosaurus type (the inverted V). However, these A. binasser-like osteoderms are from much lower in stratigraphic section than A. binasser. This confers some evidence that these morphotypes are not exclusive to A. binasser, and as a result, that they may not go with either the other morphotype or with the skull. I will be among the first to loudly argue that stratigraphy is not a diagnostic feature for taxonomy, but it's noteworthy that in a largely continous early Permian record of dissorophids in Texas, no species occurs outside of more than one formation. You can see that in the figure below from May et al. (2011). While A. binasser comes from the Clear Fork Group of Texas, the specimens to the left are from the Nocona and Petrolia Formations of the underlying Wichita Group Texas. They are separated by the Waggoner Ranch Formation.
Original caption: Revised stratigraphic distributions of dissorophids in the U.S. midcontinent. Asterisks represent newly reported occurrences from the Pennsylvanian of the northern midcontinent. Solid bars represent observed occurrences. Dashed bars represent inferred or approximated occurrences where specimen provenance is imprecisely constrained or poorly documented. Abbreviations: CH, China; CO, Colorado; KS, Kansas; NE, Nebraska; NM, New Mexico; OH, Ohio; OK, Oklahoma; RU, Russia; TX, Texas; UT, Utah. (Stratigraphic ranges and midcontinental chronostratigraphy were compiled and updated from the following sources: Carroll, 1964; Vaughn, 1971; Olson, 1972; Ossian, 1974; Lewis and Vaughn, 1975; Foreman and Martin, 1988; Hentz, 1988; Hook, 1989; Sumida et al., 1999; Kissel and Lehman, 2002; Reisz et al., 2009; Berman et al., 2010; Lucas et al., 2010.)
The original argument (more like assumption) for associating all of this material to a single species, let alone to a single individual, was that there was "no evidence for more than one dissorophid." This is, of course, negative evidence. Just because you don't find five femora doesn't mean that the two that you did find belonged to the same animal or species. Positive evidence would be definitive articulation. At the time, the recognized dissorophid diversity was much lower than it is now – we've had at least five new species named since then – and the interpretation that dissorophid-bearing sites only preserved one dissorophid species seemed to hold up (like with the Cacops Bone Bed). Since then, numerous examples of sites with multiple dissorophids have emerged. Especially at Richards Spur, we know that not only are there many species, but they are not equally abundant or represented by the same elements (more on this). So finding a cornucopia of dissorophid elements does not mean they all belong to one species or to one individual. Aspidosaurus is already known to be known almost only from isolated osteoderms (the same is true of Platyhystrix), so it is not unreasonable to argue that you could have some stereotypical Aspidosaurus osteoderms, possibly with an Aspidosaurus skull, mixed with random bits of other dissorophids.
So it is my suspicion that Aspidosaurus binasser is a chimera, but given the nature of its preservation, it is basically impossible to prove. Even if you found a specimen with the same skull that was articulated with vertebrae that only had one osteoderm morphotype, someone could (and probably would) argue that it's just a different species. This is a great example of the burden of dodgy taxonomy – it is very hard to undo (inertia), no matter how weak the original working assumptions were / are. At present, this is not a huge issue for phylogeny because there is no character for number of osteoderm morphotypes, but it is an issue for taxonomy because A. binasser and the functionally lost A. chiton are only differentiated on this feature.
Apples and oranges
Those who keep up with enough of my research know that one of my big themes is ontogeny, how we identify how mature temnospondyl specimens were at the time of death, and what not accounting for biases or skews in the fossil record might totally screw up our interpretations and analyses. I didn't focus on this too much with dissorophids as I did previously with trematopids, but there is a major disparity in size, which might correlate with disparity in the maturity of preserved specimens. Part of my thesis looked at Cacops and suggested, based on braincase morphology, that pretty much all known specimens of Cacops are juveniles at best, which underscores the point that just because you have a lot of the same size doesn't mean that was the largest size. This is definitely an interesting future direction though because cacopines like Cacops include the largest dissorophoids, which seem to get especially large in the middle Permian after lots of other Paleozoic temnos go extinct (including trematopids). Dissorophids are really diverse, and unlike trematopids, seem to have coexisted with other dissorophid species fairly commonly, so there could be legitimate major size differences between taxa that would lead to niche partitioning (e.g., one targets small tetrapods, one targets medium tetrapods, etc.).
Grand summary
This has been a longggg post. Hopefully it made sense if you read it all the way through, and if you did, thanks for reading! Hopefully you learned something new! This paper can really be distilled to four main points, which I also summarized at the end of the paper in a very atypical fashion for me just because of how much is packed in here.
There are systemic and widespread errors in the most widely propagated dissorophid matrix (Schoch, 2012). These are irreproducible and related to issues such as assumed scoring based on assumed close relatedness, which inherently compromises a phylogenetic analysis that is supposed to be testing hypotheses of relatedness.
People are not reporting support metrics enough, but they should be because this is equally important to the actual tree topology. A fully resolved but weakly supported tree topology is no good, and it should not be used to weave some elaborate story of evolutionary history.
You can get good resolution and decent support by cutting out taxa. This is not ideal because it is intentionally removing data that actually exist.
There is no consensus of relationships within dissorophids, within trematopids, or even within olsoniforms. People should not be using these really resolved trees when they need a phylogenetic topology as a backbone for other studies because they could contain spurious relationships and do not reflect a defensible state of dissorophoid study.
So coming back to why does anyone care. Phylogenetics relates organisms. If you don't know how things are related, it's harder to know whether their anatomy is remarkable or mundane, either in a qualitative or a quantitative sense. The flashy "big data" studies that examine really broad taxonomic swaths and big questions often use phylogenetic results because they need to – evolution guides patterns of morphology, behaviour, biogeography, etc. This puts a premium on getting good phylogenies because a bad one could lead you astray. This is why this kind of work, as well as descriptive anatomy, etc. remains really important to paleontology, even if it's considered "basic science." Without that foundation, nothing downstream makes sense (or it can be misleading or just straight-up wrong)! Especially with paleontology in which few things can be "known," constantly testing and improving these foundational datasets (which many find boring to do and some openly deride) is crucial for allowing us to reliably ask the broadest questions that we're all interested in.
How do we know...? (Part IV: Chip on your shoulder)
The limb gets a lot of attention because it's the part of the body in direct contact with the ground (or in the case of some animals, avoiding contact with the ground). But equally important is the apparatus that connects to the limbs - the girdles! What we call the shoulder girdle is scientifically termed the 'pectoral girdle,' while what we call the hip or the pelvis is termed the 'pelvic girdle.' This week's post will look at the pectoral girdle!
Temnospondyls have four to five different elements in their pectoral girdle: the interclavicle, the clavicle, the cleithrum, and the scapula + the coracoid / a composite scapulocoracoid. Stem tetrapods (like Acanthostega in the middle below) have an anocleithrum inherited from our fishy forerunners, but this is absent in all temnospondyls. Conversely, some extra bones are found in modern amphibians (like Salamandra on the right below). Several of these will sound unfamiliar to people who only know mammals because we (and other mammals) lack cleithra and interclavicles.
Comparison of the pectoral girdle and upper forelimb in (A) the living lungfish a representative extant sarcopterygian fish Neoceratodus; (B) the stem tetrapod Acanthostega; and the living salamander Salamandra (source: Molnar et al., 2017).
How do we know...? (Part III: Inner Workings)
Last week, I covered the external anatomy of limbs, which is often one key datapoint used to infer the lifestyle of temnospondyls - after all, limbs change quite a lot depending on whether you need to walk around on land or merely paddle in the water. But external anatomy isn't the only useful thing about a fossilized limb. Thin-sectioning, or the process of slicing a fossil or bone and making a thin section out of it for examination under a microscope allows us to examine microscopic structures that offer insights into how that bone grew. This in turn can be extrapolated to how the entire animal grew and is a powerful source of data for testing hypotheses about lifestyle and ecology more broadly. In today's post, I'll be covering histology and microanatomy, the two main attributes of the internal bone that we can derive from fossils.
Histological section of the femur of the Triassic metoposaurid Panthasaurus (source: Teschner et al., 2020).
Histological sections of the humerus of the Triassic capitosaur Cherninia (source: Mukherjee et al., 2020).
How do we know...? (Part II: A Leg Up)
Last week, I covered what the skull might tell us about an animal's ecology. The skull contains a lot of important sensory organs and is a major part of several major functions, like feeding and breathing, not to mention that skulls are very diagnostic in the fossil record compared to other elements. However, one important function that the skull typically does not fulfill is locomotion (the exception is animals that use their head to burrow into dirt or sand). Because locomotion is such a critical function, tetrapods have modified their limbs in a remarkable variety of ways to adapt to their local environment. Fundamentally, the same bones are present in the limbs of all tetrapods, but different ones have taken on drastically different shapes to best serve their function. For example, the limbs of swimming mammals (particularly the arms) have shortened drastically, while the fingers have become elongated, forming the distinctive paddle.
How do we know...? (Part I: Head in the Clouds)
To kick off this topical series looking at how we know what we claim to know about temnospondyls, we'll start with the most recognizable part of any animal: the head! Lots of important things happen up at the head - breathing, eating, and plenty of sensory functions from smell to hearing. So it stands to reason that the skull might offer us a good deal of insight into the lifestyle and ecology of temnospondyls.
Shapes and sizes
Temnospondyls are well-known for a diversity of skull shapes, some of which look an awful lot like other animals (which are really copycats of temnospondyls, who did it first). Often we assume that like modern tetrapods, this has something to do with what you ate and where you lived. Long-snouted crocodilian-like taxa probably ate primary smaller, agile fish; this is something that long snouts (or beaks) have evolved repeatedly to do very well. It isn't perhaps so great for sucking in a large fish, something that a wide skull with a big gape is better equipped to do. To get at the question of whether general skull shapes might line up with general ecologies, we have to come up with some categories.
Temnospondyl phylogeny showing different temnospondyl skull shapes; figure is not to scale with respect to different species' skulls (source: Schoch, 2013).

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November 2015

The Artistic Development of Children

by Colin Brooks

Scribbles (0 - 4)

It begins with something simple. A young child makes a mark, or smears paint, or mashes clay. Before fine motor control and spoken thoughts the artistic development of children is an outstretched arm into what's around them. It is about learning how materials feel, what they do when they get poked, when they're prodded, or how they taste when they end up in a mouth. At first a child's scribbles are explorations into the world around them. They are created primarily for the kinesthetic rewards "inherent in the manipulation of lines, colors, and texture" (Hurwitz & Day, 2007, p. 47). Creating marks on a page is exciting, and the process of changing how a material appears is more than enough.

As children develop further the chaotic creation of marks and colors and textures gives way to more control (Hurwitz & Day, 2007, p. 48). Different kinds of lines and colors are directed. Physical skills of manipulation become stronger. Eventually marks begin to take on distinct qualities: they become thick, thin, twirling, squiggly, and sharp. They can be organized on the page: grouped, arranged and manipulated further (Burton, 2013, p.32). At some point they begin to evoke feelings based on how they appear: this mark is angry, this one is sad. The lines become named as such, given the descriptive names they have rightly earned (Sousanis, 2014, p.1). Some lines are fast while others are slow. Lines are distinct from each other, but they can overlap, and build new shapes.

Eventually a child might make a line, but instead of stopping its path it continues back to where it began. A blob. This becomes the first step in a new kind of exploration of shapes (Burton 2013, p.33). Inside and outside become meaningful concepts. Shapes become enclosures, able to hold or exclude more shapes. Fundamentally the child has "made a place where one wasn't before" (Sousanis, 2014, p.1), a further act of creation beyond their initial marks. Not yet representation, but also more than just manipulative exploration. As Sousanis says (2014, p.1) "we are all enclosures" a realization that brings with it a new stage in artistic development.

Representations (4 - 6)

Now shapes are more than shapes: the are representations. A six-year-old might make circles and call it family. Blobs will start growing eyes, and hair, and legs. Blobs might also be houses, or cars, or food. Marks and patterns begin to become the things they increasingly resemble, and the child begins to understand a link from page to reality.

Early symbols draw a line between lived experience and visual creation. People can be represented as a face. A symbol to be used and reused. Arms and legs might stick out from a blob to form a body. Regardless of the visual language used to construct the person it is fundamentally a person in the child's conception. Work on the page can be who or what the child wants it to be.

Overtime a child will go from naming works after they are finished, to naming works while they are in progress, to naming works before they are even begun (Burton, 2013, p.34). This shift follows a change from reactionary identification of visual objects, to laying out an artistic and conceptual plan. People may go from a circle with eyes and a mouth, to one with nose and hair, to a one with arms and legs sticking out at the sides, to one with a full body beneath it and major appendages in all (or at least most) of the proper places.

A child learns to link material exploration to representations of their lived experience. Never leaving the scribbling stage entirely (Hurwitz & Day, 2007, p.50), material exploration continues unabated, but is now complemented by a greater purpose. Imagery, despite never looking exactly like what it is meant to be, can represent anything the child wants (Hurwitz & Day, 2007, p.51). This is an enormously important conceptual shift.

Awareness (6 - 11)

With an arsenal of artistic schemas at their disposal, children beginning to work through the numbered grades have both more complex tools and more complex experiences to represent. New relationships outside of family life become more apparent (Burton, 2013, p.39), symbols expand, divide, and change to suit increasingly specialized concepts (p.36), and composition and organization of objects becomes a new field of experimentation (p.39). A person might become a relative, and that relative might begin to be depicted doing different things. Differentiation increases. As Sousanis (2014) says, "children's pictures have become expressive places populated with people and events of particular significance or excitement to them" (p.4). The child's art becomes more specific.

Baselines in images start to shift. Sky and air and ground become distinct ideas of place on the page, and eventually they too give way to new perspectives (Burton, 2013, p.39). This change is matched in conceptual themes, as children move from what they do, to what they do with others, to what others do without them (Burton, 2013, p.41). New curiosity and understanding of the world is reflected in the child's works. The child begins to tell stories, to explain events. Objects begin to overlap, and be shown from multiple sides (Sousanis, 2014, p.5).

Over time truth and fact become increasingly meaningful. Accuracy of depiction matters, and through that need direct observation may become more attractive (Burton, 2013, p.44). Seeing and identifying what is true. Copying perspective, copying works. The child becomes more self-conscious. They become more socially aware. Details increase, abilities grow, and as Sousanis (2014) says, "they're on their way to adding their own chapters to the rich heritage of those who came before" (p.6).

Reference

Burton, J. (2013). A guide for teaching and learning in the visual arts. Unpublished teacher's guide.

Hurwitz, A., & Day, M. (2007). Children and their art: Methods for the elementary school. 8th ed. Belmont, CA: Thompson Higher Education.

Sousanis, N. (2008). Expansive foundations: An overview of artistic development in children. Unpublished manuscript.

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A measure of nature connectedness for children and adults: Validation, performance, and insights
sustainability-11-03250 (1).pdf
Richardson, Miles
Hunt, Anne
Bragg, Rachel
Fido, Dean
Petronzi, Dominic
Barbett, Lea
Clitherow, Theodore
White, Matthew
Natural England, York
Care Farming UK
University of Exeter Medical School
With benefits to both human well-being and pro-nature conservation behaviors, nature connectedness is emerging as an important psychological construct for a sustainable future. The growing research and applied and policy-related interests require a straightforward measure of nature connectedness that is suitable for both children and adult populations. To establish the reliability of the new Nature Connection Index (NCI) three factor analyses were conducted. One was based on a large Monitor of Engagement with the Natural Environment (MENE) dataset for adults (n = 3568) with a replication from data sets collected online (n = 553), and a third used MENE data from children (n = 351). To validate the NCI as a measure for nature connectedness an online comparison study (n = 153) included the NCI alongside other established measures. The results showed that the NCI was a reliable and valid scale that offers a short, simple alternative to other measures of nature connectedness, particularly for populations including both children and adults, measured face to face or online. The utility of the NCI is also supported, with variations associated with various pro-environmental and pro-conservation behaviors observed, and importantly the NCI also revealed changes in nature connectedness across the lifespan.
Richardson, M., Hunt, A., Hinds, J., Bragg, R., Fido, D., Petronzi, D., Barbett, L., Clitherow, T. and White, M., (2019). 'A Measure of Nature Connectedness for Children and Adults: Validation, Performance, and Insights'. Sustainability, 11(12), pp. 1-16. DOI: 10.3390/su11123250
MDPI AG
10.3390/su11123250
https://www.mdpi.com/2071-1050/11/12/3250


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Fall in mortality rate, high recovery keep active Covid-19 cases in India below 6 lakh
NEW DELHI, Nov 4: Active Covid-19 cases in India have been witnessing a steady decline and remained below six lakh for the sixth consecutive day on Wednesday due to a sustained fall in the mortality rate and a large number of patients recuperating from the disease daily, the Union health ministry said.
Sixteen states and Union Territories, including Assam, Punjab, West Bengal, Gujarat, Jharkhand, Rajasthan, Uttar Pradesh, Madhya Pradesh and Bihar, have cases per million lower than the national average, the ministry said.
"The active caseload remained below the six-lakh mark for the sixth successive day as on date," it said, adding 17 states and Union Territories have their recovery rates more than the national average.
The ministry said that 80 per cent of the new recovered cases were observed to be concentrated in 10 states and UTs, with Kerala leading the table with more than 8,000 single-day recoveries followed by Karnataka where over 7,000 people were cured of the disease in a day.
It stated that 25 states and Union Territories have better tests per million than the national average, the ministry highlighted
The health ministry further said 76 per cent of the new cases of Covid-19 were from 10 states and UTs, with Kerala and Delhi having contributed the maximum of more than 6,000 cases each. Maharashtra had over 4,000 new cases in a day.
As many as 514 fatalities have been reported in a day. Of these, nearly 80 per cent were concentrated in 10 states and UTs with Maharashtra reporting the maximum 120 deaths.
India's COVID-19 fatality rate stands at 1.49 per cent, with 21 states and UTs have deaths per million lower than the national average, the ministry said. (PTI)
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'Fraud of the Century'
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October 15, 2001 • Author Jonathan Franzen joins Fresh Air to discuss his critically acclaimed and award-winning novel, The Corrections. It is a saga about two generations of an American family; the parents and their children.
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Author James Reston Jr.
October 8, 2001 • His new book is Warriors of God: Richard the Lionheart and Saladin in the Third Crusade (Doubleday). It's the story of the battle for the Holy Land in the late 12th century. It begins as a dual biography of Saladin, the Sultan of Egypt, Syria, Arabia and Mesopotamia, and Richard I, King of England, known as the Lionheart. The two men led the battling Islamic and Christian armies. James Reston is also the author of twelve books, including The Last Apocalypse and Galileo: A Life. He is currently a scholar in residence at the Library of Congress.
Editor-in-chief of 'Gourmet' Magazine Ruth Reichl
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Chien-Chi Chang has always been fascinated by the human conditions of alienation and connection. Both are in evidence in his signature work, 'The Chain', which is a collection of portraits made of inmates in a mental asylum in Taiwan. The subjects are people who have had their bonds to the rest of society – family, community – servered. And yet, as part of their treatment, they are chained to one another, physically linked in pairs throughout their days and only unlocked to sleep. These powerful photographs, nearly life size, have been exhibited at the Taipei Fine Arts Museum (2001), La Biennale di Venezia (2001), and the Bienal de Sao Paolo (2002).
Less visible bonds were the subject of another project: A jaundiced look at the ceremony surrounding the union of two people. When his parents began pressuring him to marry, Chang responded by making pictures at weddings in Taiwan. The images are hardly festive, rather emphasizing alienated grooms and lonely brides. They have been collected in the book, 'I do I do I do'.
This meditation on the nature of the ties that bind a person to others and to society is a natural outgrowth of Chang's own experience of the divided life of an immigrant. The son of working people in central Taiwan, he received a Bachelor of Arts degree from Soochow University in Taiwan in 1984 and a Master of Science degree at Indiana University in 1990. He then became a staff photographer at The Seattle Times (1991-1993) and The Baltimore Sun (1994-1995).
Over the past decade, he has worked in New York's Chinatown, documenting the lives of immigrants there. These pictures of illegal aliens stranded on an island within an island have appeared in National Geographic magazine, as well as The New Yorker, Time and German Geo. The series earned Chang first place in the category "Daily Life Story" from World Press Photo in 1999.
That same year, Chang won a grant from the W. Eugene Smith Memorial Fund for humanistic photography and was awarded the Visa d'Or in magazine photography in Perpignan. He was named the Missouri/NPPA 1999 Magazine Photographer of the Year.
Chien-Chi Chang is a member of Magnum Photos. He resides in Taipei and in New York City.


In case you were wondering what happened to me, especially, since it has been weeks since I posted a recipe. Well, I am safe and sound. There has been too much going on in our lives. We are going to be selling our house and due to that, my cooking has taken a backseat temporarily. We have been prepping our house for the sale. Finally, we are at a point, where the house is ready to go on the market. Once we put our house on the market, the last thing I want to do is make the house smell like spices. Some prospective buyers might like and some might not like spices. So the plan is to make 3-4 recipes so that I can blog about it for the next several weeks. What will I do after that? Not sure. I will think of someway to cook after that. Maybe cook at my friend's place since they let me know that they are okay with being used as guinea pigs for my recipes! I will let you know how that goes.
Couple of weeks ago, I decided to make Palak Paneer – literally translated means Spinach Paneer. Paneer is an Indian cheese (very different tasting than Soy) that is made with whole milk that has been warmed and then vinegar is added to it to "break" the milk. It is a laborious process. You can buy it frozen from an Indian store or fresh from your local organic grocer. Paneer is very versatile and you can make innumerable dishes with it. I will post some more paneer recipes in the future.
The palak paneer (pronounced as paa-luck) that you find at Indian restaurants looks like some green stuff with white cubes in them, Not too appetizing by looks! The palak paneer that I make is a slightly modified version of the one found in one of my favorite cookbooks – Indian Home Cooking . There is more texture to it and you can see the texture of the main ingredients but also tastes really yummy. I made that last week for some of my friends and they loved it.
I like to use fresh bunches of organic spinach. You also have the option of using frozen spinach or pre-washed baby spinach. I prefer the bunches of spinach. Even though it is a little more work to wash and clean, it comes tasting much better. I definitely do not like to use frozen spinach.
The final result of making Palak Paneer. Notice the texture of the food. This dish came out excellent and very tasty. It is a easy dish to make.
*NOTE: Make sure to use the Indian coriander powder that tastes very different from the non-Indian ones. You can either order it online (the link is provided above) or buy it from an Indian store.
In a large saucepan, add water and turmeric and spinach. Cook over medium-high heat, turning spinach occasionally, until wilted, approximately 3-5 minutes. Remove from heat, drain excess water and let spinach cool. Puree the spinach in a food processor coarsely and set aside.
Rinse the saucepan with water and wipe with a paper towel. Heat the ghee and oil mixture over medium heat. Add cumin seeds and cloves and cook until fragrant, approximately 30 seconds. Add the chopped onions and salt and cook onions until translucent, approximately 5 minutes. Find the cloves and remove them.
Add the fresh chili pepper, crushed coriander seeds (or powder if seeds not found), ginger, garlic and chili powder and cook, stirring, until fragrant, approximately 2-3 minutes.
Stir in tomatoes and turmeric and cook for 5 minutes, until tomatoes are soft. Add the pureed spinach and mix well. Add paneer and stir gently to coat with sauce. Cook over medium heat for 2-3 minutes, until paneer is warmed through. Sprinkle with fenugreek leaves and stir and serve hot with naan or chappati.


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