Profiling prolific plant hunters provides insight as to strategy for collecting undiscovered plant species.

The gist is: the current situation is dire.

“Plant collecting is a specific part of the three-step process of plant species discovery (collection, recognition and publication), and as the numbers of professional taxonomists who classify plants decline, there has been a massive increase in the utilization of non-professionals to aid in this work. This study suggests that as science pushes for more rapid documentation of the world’s flora, policy makers and funders must examine how best to develop the experience and skills of selected individuals to catalog undiscovered plants more efficiently.

“One way for institutions to encourage the development of these skills is in performance evaluations, rewarding effective field work on an equal footing with number of papers published and grants obtained,” notes Davidse.”

In other words, there’s no money to do field botany, institutions aren’t encouraging it, we aren’t training new field botanists, and we aren’t hiring them. And that’s why we need to do what we can quickly and on a shoe-string budget.

Inductive reasoning works by taking some set of observations and generalizing their characteristics to a larger set of phenomena. A typical example is this–How do we know the sun will rise again tomorrow? It has always done so in the past, so it will do so again tomorrow. We can take a step back and ask–How do we know that, just because something has always happened in a certain way in the past, that it will also happen that way in the future? Or, more generally, how do we know that we can take observations of some subset of a class of phenomena and then assume that the observed characteristics also hold for the whole class? Hume’s contention was that any answer to this question will, itself, rely on inductive reasoning (e.g.–Yesterday I predicted, on the basis of past events, that the sun would rise today, and it did! Therefore, the same reasoning will work again tomorrow.), and that’s circular, so we can’t get anywhere. Apparently, no one has found a way out of Hume’s problem of induction. We simply have to take inductive reasoning on faith, or give it up.

The alternative to inductive reasoning is deductive reasoning, in which we simply work in the opposite direction. We infer the characteristics of a particular individual from characteristics known to hold for the class of individuals to which it belongs. A typical example is this–All men are mortal; Socrates is a man; therefore, Socrates is mortal. Responses to Hume’s problem of induction focus on trying to provide a deductive proof for inductive reasoning. Nobody seems to have any qualms about deductive reasoning itself; there is no corresponding “problem of deduction” to complement the “problem of induction”. But we might ask:

So, OK, we can’t provide a deductive argument establishing that inductive reasoning works. What about the opposite? Can we provide an inductive argument establishing that deductive reasoning works? It is not intuitively obvious how we would go about this. For instance, we might pull out the old chestnut about Socrates and say, “Well, he died, so the deductive argument for his mortality works!” However, all this tells us is that the conclusion of that particular argument happens to be true, not that the reasoning works. If we followed that line, we’d end up having to say that any reasoning that happens to lead to a true conclusion is valid, and any reasoning that leads to a false conclusion is invalid… but that is in direct opposition to the operations of deductive reasoning. I can’t really think of a way around this problem. Maybe someone has done it, I don’t know. Maybe deductive reasoning just feels so right that we can’t imagine giving it up; but, then, we’re in no danger of giving up inductive reasoning, either, whether it can be justified or not.

It is also worth mentioning that I’ve always found NOAA’s website hopelessly baffling. They seem to be improving that; water.weather.gov is surprisingly easy to navigate to from either weather.gov or noaa.gov, but the cpc.ncep.noaa.gov side is hopeless. Suppose you start at the CPC’s “Monitoring and Data” page. Then you click on “United States Climate Data and Maps”, then “Precipitation and Temperature”, then “Recent Precipitation Maps”… and that sends you to http://www.cpc.ncep.noaa.gov/products/precip/realtime/, where you are redirected to http://www.cpc.ncep.noaa.gov/products/Global_Monsoons/gl_obs.shtml, which is apparently intended for global monsoon monitoring. Huh?

Someone who’s taken the courses available at NMSU (Rangeland Plants, Rangeland Grasses, Plant Taxonomy), done well and studied conscientiously, should be able to sight-ID a fair number of the common species (but few of those uncommon species that make up most of the biodiversity), and should be able to key out most plants assuming there is flowering and/or fruiting material available (and there often isn’t, but field crews don’t tend to have the luxury of waiting for good conditions). But that’s it. Don’t expect or rely on sight-IDs of most of the plants in the area, and don’t expect that any kind of identification will be possible for most species if the plants are in poor shape and many or most of the diagnostic characters are absent.

Suppose you want to answer a simple question: is plant diversity higher in grasslands or shrublands in southern New Mexico? Well, if you want reliable data, you need a field crew of people who already have several years of experience–probably voluntary / recreational since, AFAICT, no one will pay you to learn plants–botanizing in the area. Those people are scarce, and most of them have Masters or PhD degrees (and many are retired!); you probably can’t (and, ethically, shouldn’t) hire them for crappy minimum or near-minimum wage temporary positions. If, on the other hand, you hire a field crew of people fresh from their undergrad degrees whose experience is limited to two or three courses in plant ID or taxonomy, either that crew is going to be spending 90% of its time learning plant ID, or you’re going to get crappy, unreliable data. (As for the simple question, so far as I know there is no reliable answer! More on that some time later.)

One way to minimize the expertise required is to only focus on a few of the dominant plant species (as in the vegetation maps discussed in the post below). It is better to recognize one’s limitations and work within them, but this approach means you’re ignoring most of the botanical diversity in the area… not exactly ideal, in my opinion.

The gist is, if you try to fill botanical field crews on the cheap, rather than hiring highly trained botanists with extensive experience, you have a few options, none of them particularly good: deal with poor accuracy of identifications; get very little data back because your field crews are spending most of their time learning the plants; adopt a very myopic view of plant communities.

Gibbens, R.P., R.P. McNeely, K.M. Havstad, R.F. Beck, and B. Nolen, 2005. Vegetation changes in the Jornada Basin from 1858 to 1998. Journal of Arid Environments 61: 651-668.

So, I thought, I’ll just pull the maps from there. Unfortunately, it is not that simple. One problem is common to almost all published vegetation maps: you can’t just look at the map and say, “OK, all this is grassland, and here it is quite extensive in 1918, and then there’s not much of it in 1998,” because the color system used is fairly confusing and you’d have to spend a minute pointing out that yellow, light pink, dark tan, etc., are grassland while light green, light blue, light tan, etc., are shrubland. There has to be a better way to do this! Here’s the figure (just for the JER; there’s a separate figure for the CDRRC), see how long it takes you to figure out the extent of grasslands at any point in time:

Looking at the map more closely I realized that, in this case, there are further difficulties. The map legend does not match the colors used. Here’s a comparison of the colors used in the legend and in each map:

That dark pink for “other grasses” never occurs in the maps; two different browns not in the legend are used. Presumably those browns mean “other grasses”, but I don’t know. It is odd that most, but not all of the areas of Scleropogon brevifolius (burrograss; light pink) in the 1918-19 map become brown in the 1928-29 and 1998 maps. It’s hard to tell if this is supposed to indicate a change in vegetation, or is simply an error in producing the map. I assume the latter, because similar maps were produced again, in:

Havstad, K.M, L.F. Huenneke, and W.H. Schlesinger (editors), 2006. Structure and Function of a Chihuahuan Desert Ecosystem. Oxford University Press, New York, NY.

Here, that difficulty seems to be solved. So far as I can tell, the legend matches the maps, and all those areas of Scleropogon brevifolius in 1918-19 are still Scleropogon brevifolius in 1928-29 and 1998 (as they continue to be today). However, this map is more precise about what the dominant species is (e.g., listing Sporobolus airoides, Sporobolus flexuosus, Sporobolus nealleyi and Sporobolus spp. instead of just “Sporobolus spp.”), which is good, but exacerbates the problem of colors that are difficult to distinguish to the point that much of the map is unusable. Worse, the maps are small and resolution is poor; and I have a physical copy of the map rather than a .pdf. There is no way, AFAICT, to use these as workable images in a powerpoint presentation. Luckily the GIS layers are available on the Jornada website, so I can make my own maps (which I may do as time goes by).

So, that’s frustrating. Here’s another difficulty: “Plant nomenclature follows Allred (2003).” Except, it doesn’t. For instance, Allred recognizes Gutierrezia microcephala and Gutierrezia sarothrae, while the Jornada literature uniformly lumps both as Gutierrezia sarothrae. And then there are the big questions that remain even if we leave this niggling behind us:

1) How exactly do we determine what the dominant species is in the first place? The standard has always been that you look out at a landscape and guess (and the methods of the 2005 paper are consistent with this). In clear cases, this should work. In other cases, it won’t, and you’ll get different answers depending on who’s doing the fieldwork (or, for that matter, what time of year, how wet the year is, etc.). An objective measure, and some account of seasonal / yearly variation as well, is needed.

2) How much does that tell you, anyways? If we want to understand the distribution of vegetation, don’t we want to know more than just one (or two–the 2006 book includes separate maps for the second most abundant species) of the species at a site? This is a constant frustration of mine with ecologists and land management agencies. Interest is almost always focused on the most abundant species and, due to the Endangered Species Act, the least abundant species. The other 95% of the biodiversity is uniformly overlooked.

Lest you think I am singling out the Jornada for criticism, I also searched for vegetation mapping information for the Sevilleta LTER. Results were worse. A vegetation map was created, but never published. At one point it was online, but at present it is not available through the Sevilleta website; you can find a fairly illegible jpeg through archive.org, but that’s it. Despite 25 years of research and three long-term NSF grants at the Sevilleta LTER, so far as I can tell there simply is no published account of the vegetation, nor one available online. This is disappointing. Poking around online also led me to this article:

Weiss, J.L., D.S. Gutzler, J.E. Allred Coonrod, C.N. Dahm, 2004. Long-term vegetation monitoring with NDVI in a diverse semi-arid setting, central New Mexico, USA. Journal of Arid Environments 58: 249-272.

From which I quote:

“The objective of this study is to examine 11 years (1990-2000) of seasonal and inter-annual variability of NDVI in a diverse semi-arid setting in central New Mexico, USA, that includes six different vegetation communities: Great Plains / desert grassland (GPGrslnd), Chihuahuan Desert (ChiDes), piñon-juniper woodland (PJWdlnd), juniper savanna (JunSav), Colorado Plateau shrub-steppe (CPShbStp), and Colorado Plateau grassland (CPGrslnd) (Moore, 1989-2001).”

OK, we have six different kinds of vegetation. You might ask: How are they different, exactly? How do we know that they’re different? And just how much of the variation in vegetation at these sites is captured by those designations (e.g., does “juniper savanna” mean just any kind of juniper with any kind of grass, or is it always Juniperus monosperma with Bouteloua gracilis; and what about the other 95% of the plants in that habitat)? In particular, I was curious what exactly the difference between Great Plains grassland and Colorado Plateau grassland is at the Sevilleta. However, in the paper there is no explanation of any of these points, nor any citation indicating how you could find that information (the Moore citation is for meteorological data). Near as I can tell, “Great Plains grassland” must refer to communities dominated by Bouteloua gracilis east of the Rio Grande, and “Colorado Plateau grassland” must refer to communities dominated by Bouteloua gracilis west of the Rio Grande, but is that a meaningful distinction? Are these actually distinct plant communities or just different names for the same thing? I don’t know, but it’s the kind of basic knowledge I can’t imagine conducting ecological research that relies on vegetation classifications (nevermind running an LTER site) without. And yet… well, maybe it’s all in that unpublished vegetation study.

Araceae:

Anthurium, unknown cultivar (purchased for the NMSU Plant Taxonomy course; usually I kill these things but the last two have survived, so far)

Aspleniaceae:

Asplenium platyneuron

Asteraceae:

Senecio articulatus
Senecio stapeliiformis

Bromeliaceae (I have a particular fondness for terrestrial bromeliads, as you may notice):

Acanthostachys pitcairnoides
Acanthostachys strobilacea
Aechmea sp. (not one of the obnoxious cultivars; alas, I’ve lost the tag indicating which species)
Billbergia chiapensis
Billbergia zebrina (thought this thing was dead for a good while!)
Deuterocohnia brevifolia
Dyckia platyphylla
Fosterella kroemeri (or perhaps F. windischii; I need to wait for flowers to tell; sold to me as Fosterella albicans)
Fosterella latifolia (sold as Fosterella villosula; Fosterella latifolia is placed in synonymy of Fosterella penduliflora in a revision by Jule Peters but it looks different so, what the hell, I’ll list it separately)
Fosterella penduliflora (I’ve had these for something like 15 years; they reseed readily and are hard to kill)
Fosterella petiolata (I think)
Fosterella spectabilis
Neoregelia sp. (not one of the obnoxious cultivars; alas, I’ve lost the tag indicating which species)
Orthophytum gurkenii
Orthophytum saxicola
Pitcairnia flammea
Pitcairnia cf. punicea

Cactaceae (I don’t particularly like cacti, but somehow I end up with them anyways!):

x Disophyllum, unknown cultivar
Echinops, unknown hybrid
Mammillaria elongata
Rhipsalis baccifera
Rhipsalis paradoxa
Schlumbergera, unknown cultivar (white flowers)
Stenocactus zacatecasensis

Commelinaceae:

Tradescantia spathacea

Crassulaceae:

Sedum wrightii

Euphorbiaceae:

Euphorbia horrida
Euphorbia obesa (although it doesn’t look particularly happy…)

Gesneriaceae:

Saintpaulia, unknown cultivar (single purple flowers)

Hypnaceae:

Hypnum sp.

Isoëtaceae:

Isoëtes chapmanii
Isoëtes louisianensis

Marchantiaceae:

Marchantia polymorpha
Conocephalum conicum

Marsileaceae:

Marsilea vestita

Moraceae:

Dorstenia foetida
Ficus sansibarica

mosses (unknown family):

two species that I have not identified

Ophioglossaceae:

Botrychium obliquum
Ophioglossum engelmannii

Polypodiaceae:

Davallia sp.

Polytrichaceae:

Atrichum sp. (sold as a Mnium, of all things… hard to figure, given that Mnium and Atrichum are among the most easily identified mosses, and rather dissimilar from each other)
Polytrichum sp.

Porellaceae:

Porella sp.

Psilotaceae:

Psilotum nudum

Pteridaceae:

Adiantum capillus-veneris
Astrolepis sinuata (it volunteered in a terrarium, of all things)
Bommeria hispida
Cheilanthes lindheimeri
Cheilanthes wootonii

Selaginellaceae:

Selaginella rupincola

Sphagnaceae:

Sphagnum sp. (not really sure why I bought this… online biological supply stores are dangerous)

Vitaceae:

Cissus quadrangularis

Welwitschiaceae:

Welwitschia mirabilis

Xanthorrhoeaceae:

Haworthia herbacea

[updated 19 Feb 2012]

Out of curiosity, I decided to find out how many taxa (species + varieties or subspecies as applicable) are recorded from each of the counties of New Mexico. I searched the herbarium records at swbiodiversity.org & ran the results through the ASU taxonomic database, which will keep the same taxon from showing up multiple times if it’s listed under several synonyms. Of course, the taxonomic filter only works if the ASU database contains the appropriate names and synonymies; generally speaking it probably does, but there are certainly omissions and errors as well. There’s also some error in specimens being recorded for the wrong county due either to error when databasing, the collector not really knowing where he or she was, or changing county boundaries. So, the numbers are quite approximate but as good as can be done without devoting considerable time to the project. That said, here are the results on a map:

Now, one reason for doing this is that I had heard, from Dr. Heil at San Juan College, that Rio Arriba was the most diverse county in the state botanically. I was skeptical, but didn’t really know any better, but now I at least have some basis to believe otherwise; Grant County appears to be most diverse, with Rio Arriba in seventh. My initial guess was that Doña Ana or Hidalgo County would come out on top; with Doña Ana in third I guess that’s not bad, though Hidalgo’s a bit further down. Differing results between myself and Dr. Heil may be due to his use of the NMBCC (New Mexico Biodiversity Consortium) database at nmbcc.org; this database includes only the holdings of New Mexico herbaria, while swbiodiversity.org includes New Mexico holdings from the Arizona herbaria and a few others.

It’s also worth mentioning that there are some obvious biases in collecting. The eastern counties, in particular, are poorly collected. However, this alone is unlikely to account for their low diversity. For instance, there have been at least one or two floristic inventory projects in Roosevelt County (including a flora of Milnesands by Rob Strahan), and so it has about twice as many species recorded from it as most of the surrounding counties. However, the total of 651 is still unimpressive.

I’ve been reading a few papers recently on the evolution of sex and it seems to me that an important distinction is often overlooked, the distinction between sex and gonochorism. Theoretical work on the evolution of sex often contrasts gonochoristic sexuality, i.e., having separate male and female individuals, with asexuality. If females have a constant number of offspring in gonochoristically sexual and asexual lineages, the asexual lineage will have twice the reproductive output. Suppose all females have four offspring; a gonochoristically sexual female will have two sons and two daughters, while an asexual female will have four daughters. Those four daughters will have four daughters, while the gonochoristically sexual female’s two daughters will each have two daughters. There are some simplifying assumptions here that may not hold–i.e., the sex ratio is 1:1, males are assumed to make only a genetic and not a material contribution to reproduction, and it is assumed that no physiological reliance on sexuality exists. The second is apparently the most problematic; if males provide food or other resources that can increase the per-female reproductive rate in a gonochoristically sexual species, a competing asexual female will not be able to achieve the theoretical doubling in reproductive rate. This is likely to be a factor to some extent among many mammals and birds, but presumably not in reptiles & insects. The third assumption has also been shown not to hold in some cases. Whiptail lizards (genus Aspidoscelis) have a hormonal reliance on mating behavior, and engage in pseudosexual behavior. This apparently reduces the efficiency of reproduction and prevents asexual whiptails from maintaining an equal per-female reproductive rate compared to their gonochoristically sexual relatives.

In any case, apart from the violations of simplifying assumptions that mitigate the potential doubling reproductive output of asexuals in some cases, the potential reproductive inequality between gonochoristically sexual and asexual lineages presents presents a significant challenge to any account of how sexuality could have evolved and how it could be maintained. Resolving this difficulty has been the focus of extensive research. However, as I suggested initially, I think the problem is in part poorly framed. The reproductive inequality that papers on the evolution of sex seek to address is not specifically one relating to sexuality vs. asexuality, but a result of the division of the sexes into separate individuals, i.e., gonochorism. If we compare hermaphroditic (loosely speaking… in plants this term and ‘gonochoristic’ can be misleading, see the post regarding Pollan’s “Botany of Desire” on PBS) lineages with asexual lineages there isn’t any general theoretical reason to expect a strong reproductive inequality between the two. All offspring in each case will be reproductive. We might expect marginally lower reproduction in hermaphrodites because some of their energy is devoted to male functionality, but, as the biological cliché goes, sperm are cheap; this should not be a major factor. We might still expect asexuality to be favored under certain circumstances, particularly if gamete (or, in flowering plants, pollen) transfer is inefficient. If populations are sparse and encountering other individuals of the species is infrequent or energy-intensive (or, in flowering plants, if pollinators are scarce or inefficient)–i.e., if it is difficult to engage in sexual activity–this should tend to favor asexuality. That aside, in general it seems to me that the arguments already advanced to explain the evolution of sex, which focus in various different ways on the fact that sex encourages genetic diversity, both in terms of numbers of alleles present and in their ability to be assorted in offspring independently of each other. Genetic diversity provides the substrate on which natural selection can act, and is thus a prerequisite for an evolutionary response to selective pressure. If either abiotic or biotic conditions change, a sexual species should be able to adapt to that change much more quickly and effectively.

Sexuality seems to me to be relatively easy to explain. Gonochorism, on the other hand, is very difficult to explain. Compare a gonochoristic and a hermaphroditic lineage; the latter should have twice (more or less) the reproductive output, but both have the genetic advantages of sexuality. The hermaphrodites should win easily. So, why are there so many gonochoristic species? I’m sure there must be literature that addresses this specific point, although I haven’t run across any in my own fairly cursory reading in the field, but I think many miss this point and simply take gonochoristic sexuality and asexuality to be the two available options. They are not.

(Parenthetically, a further confusion that I’m ignoring for present purposes is that between self-fertilization (or self-pollination…) and outcrossing. Self-fertilization is sexual, but has broadly similar detrimental genetic consequences to those asexuality. In plants, the evolutionary dynamics of self-compatibility / self-pollination vs. self-incompatibility are subject to some of the same general considerations as the evolution of asexuality vs. sexuality (which in plants is generally ‘hermaphroditic’, but occasionally ‘gonochoristic’…), but of course it isn’t quite the same. The main complication added is that selfing plants can be either facultatively or obligately selfing… anyways, enough for one day.)