Now almost twenty years into this project, one of the first questions that comes to mind pertains to whether or not my approach is too simplified to be of any use. When I first developed this dataset, the IT world was really in its infancy. Due to time and manpower, there is a lot of information out there similar to my own perhaps. With a much larger number of people now engaged in ethnobotany research, most are more savvy about plant taxonomy than they were 15 to 30 years ago, there are more than likely loads of tables out there detailing the uses of plants.
The problems with many of the tables I find in the literature is that they usually focus on just a piece of the puzzle related to ethnobotany. They may be detailed in their approach to a particular plant family or a particular cultural group, but these tables tend to be in very different formats from one reference to the next; they are not that easy to correlate or to use in producing a much larger set of tabulated data.
One of the other problems out there is this tendency for researchers to dissect information down to its minutia. In an attempt to produce an ethnobotany table several years ago by a large ivy league university, this goal was never completed due to the ways in which the categories were to be tabulated and covered in brief essay form. Once again, the detail of the coverage made the goal exciting and interesting, but also impossible to get done in good time.
The third problem is there is such a rehash in all of these ethnobotany databases out there, all these pages on the same type of thing, many partial duplications or plagiarisms of the information provided by competitors. The goal here is not to recap what is already out there. Typically my work focuses mostly on that which no one has had the time to digest, ruminate on, and then put out there in a completely new format with new applications and new uses. My personal opinion is that when the added amount of time is used to engage in such an effort, the product is worth the wait. Unfortunately, such a concept does not match university publish or perish standards. In science, the best products take much more effort and much longer times to complete. Those that are at their best tend to be several years ahead (often about 3). Those that are the very best, are ten or twenty years ahead of their time, if they are ever actually produced by someone else. Fortunately, it appears as though my evolutionary tree of ethnobotany developed in 1985/6 and the related tables 1986/7, to help me through my work on the evolution of various phytochemical classes, kind of meet these standards.
When we look at plants uses, the main problem we deal with in terms of implementing a statistical approach to analyzing this information is the complexity of how we utilize plants and their products. If we were to try to distinguish every type of use out there for plants, including such things as how the plant is prepared for this use, how the plants parts are isolated for a particular use, how a particular plant and plant part can have multiple uses with multiple purposes by multiple cultural settings, we would probably be left with a highly detailed matrix of zeroes and ones, the zeroes standing for no use in this particular manner, the ones for a single example of this particular very unique type of use. To avoid this problem, some uses have to be merged to produce more wholesome (non-null-ridden) numerical outcomes for statistical analyses. If we then take this particular way of classifying the classes or groups of data, we can come up with a fairly useful tool for evaluating ethnobotany as a whole, in regard to the plant kingdom, how it has evolved, and how these evolutionary features relate to animals and us as a part of the natural environment, and to us as just human in search of unique anthropomorphically defined uses for plants–uses that only people can discover due to the unique needs and mindset people have. This is the methodology that my work in the statistics of plant use takes.
My review of plant uses focuses on the Genus level on up. The reasons I selected Genus as the principle smallest group identifier is as follows.
Genus Definitions and Nomenclature. Even Latin plant names for the same plant or some very close relative can vary from one place to the next. Genus is easy to cross-index, and although this problem will pop up frequently the form of ethnobotany analysis I am engaged in, it is not so problematic as having to deal with subspecies, varieties, and even smaller taxonomic group differences. We can compare plants around the world once they are identified as part of a specific monogeneric group. We have much less success, if any at all really, trying to look at plants at to highly localized species and lower grouping levels. We also cannot go up one group in the taxonomy tree. This is because there are major features that differentiate genera at the family level.
So for this analysis, the numbers start at the Genus level. All counts provided are of genera, unless otherwise noted. In many cases, these numbers are grouped together to evaluate the same data at a larger taxonomic level (Family on up), but only occasionally would species counts ever be used to analyze ethnobotanical fndings. These tables tend to provide data that tells us the answer to the utilization question in binary form, with 1=’yes’ and null =’no’.
Numbers. If this were to be produced from scratch at the species level, the amount of time (years to decades) needed to complete this kind of analysis would most likely prevent any final outcome from being derived, at least on my own behalf.
Worldwide Application. Even though important species details are missed (a lot of them in fact), the purpose of the table is to measure trends at the genus-family-order level. This method of measuring ethnobotany-chemotaxonomic trends has research values at a much broader level. This data can be further broken dow to the species levels for detailed studies, but this makes the data more than likely unable to then be related to a similar study of a completely different part of the world. Genus and Family are the two most correlatable features in plant taxonomy and statistics worldwide.
Temporal Application. Many of the rules developed through this analysis provides us with insights into the chemical evolution of fossil species, and may perhaps have some application to making predictions about where to find certain pathways evolved as a consequence of natural events, or how a plant’s chemistgry may be expected to change over time. In general, paleochemical pathways are also directly related to prior periods in animal-plant ecology development. The behavior of archaic species enable us to make reasonable guesses as to what pathways may have been developed during the Carboniferous and Triassic, Jurassic and Cretaceous periods in order to fend off herbivore activities, be they subterranean or the more commonly imagined dinosaurian in nature.
The sections in the process of being developed for this portion of my review of “The Evolution of Chemicals or Natural Products in Plants” start fairly basic and simple and build upon prior lessons. This process when completed evaluated phytochemistry in relation to ethnobotany from the Kingson level on down in increments all the way to the subfamily/tribe or “supergenus” level. However, the most functionality of this work is produced when it is applied at the Family or Order level.