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Maps

Under Construction: These are some examples of maps or graphs I have made from my research. I have captions if you want to know what they represent, otherwise just enjoy them for aesthetic value.

Figure 1. A composition map of North American ferns north of Mexico. I experiment with mapping techniques, and geographical patterns of flora composition can be explored in many different ways. In this map I explore fern composition in the following way. First, the map below is the richness map of ferns of North America north of Mexico; Dark blue reaches 85-95 species, yellow around 1-15 while green areas are intermediate in species richness. I selected the four major richness peaks, The Northwest, Northeast, Florida or Southeast, and Southwest. The species of all floras were coded depending on their presence within any or all of these richness centers. For example, species that are only present in the South east richness center are coded red. Species that exist in more than one richness center are coded in black, and those species that exist in no richness center are coded in white. Therefore you can see the richness centers themselves lack any species coded white. A number of properties are apparent about the American fern flora, as read from this map. One, many species exist in at least two fern richness centers (black slices), and many species occur in none of the richness centers (white slices). In addition many of the species in the Northwest richness center also occur in other richness centers, whereas the Florida richness center is composed predominantly of species that exist only in that one richness center.

Figure 2. In this map regions are coded by the "dominant" fern family, or the family with the greatest number of species in the local flora.  Note the large area where the Dryopteridaceae accounts for the largest number of species. I made this map from the same distributional dataset as in many of my maps, North American ferns north of Mexico. This demonstrates the breadth of ways in which floral distributional patterns can be examined.

Figure 3. This map shows the residuals of a regression of fern family richness on fern species richness. The brown isoclines represent species richness. Blue areas have few families given the number of species or a large number of species given the number of families (and red regions have relatively many families given the number of species). Blue regions may represent regions where much speciation has occurred relatively recently, without ultimately contributing to the larger scale morphological differences associated with families. Note that there is some association between species richness and regression residual. This map is part of a manuscript I am currently working on with Maxine Watson.

Figure 4. Family richness as a function of AET or actual evapotranspiration and annual temperature (high 26 blue, low 1 yellow, green intermediate richness). Pardon the missing scales, I will enter that eventually; this is a custom graph.

Figure 5. Average genome size of North American gymnosperms. C-values are from the RBG kew c-value database. This demonstrates that many kinds of biological phenomena can be explored geographically. At the very least the geographical pattern of biological phenomena can provide suggestions of possible causal mechanisms for biological attributes such as genome size for those interested in whole genomic evolution.

Figure 6. This is an illustration of a pet goal of mine, a romantic goal of sorts. I wish to map many attributes of life on the surface of the planet a) because we can: we have the data waiting for us, b) the spatial pattern of any phenomena reveals and suggests important aspects of the function of such phenomena, c) the spatial patterns of life themselves require explanation if we are to fully understand life, and d) finally, because I understand many things by considering their spatial orientation. One day!

Figure 7. Another illustration of species distributions, these are the outlines of North American fern ranges (alphabetically A through D, all of them would be far to messy). This kind of graph resembles the actual data in a more direct way than in other geographical representations. It can provide a sense of all of the following attributes of fern flora distribution, richness, composition change, ecotones, and common barriers or ecological/floral transitions, to name a few. I am also developing new kinds of maps that illustrate spatial structure of the continental flora.

Figure 8. Graph produced for NSF grant with Leonie Moyle and Takuya Nakazato. This graph shows ecogeographical distributions of several tomato species. This data set includes in addition to distributional information, AFLP and other genetic information, and physiological data of populations in the greenhouse. These data together has allowed us to explore adaptive evolution through climate space.

Figure 9. Map of 19 of the populations from tomato data set described in figure 8. This map illustrates how ecogeographical information are extracted from climate maps. Each population exists under a particular temperature, precipitation regime, and altitude, and this is reflected in the above four maps.

Figure 10. Hypothetical distribution of a species with respect to flora composition. I have gone beyond this towards empirical documentation of "compositional range" of particular tree species.

Figure 11. This map shows the distribution of Fagus grandifolia or Beech. In addition to reflecting patterns of abundance the histograms show the relative frequencies quantities of trees by their diameter. This map was produced by using the USFS, FIADB, U.S. Forest Service Forest Inventory and Analysis Database. This database has millions of records of individual trees and is waiting to be analyzed for studies ranging from climate change to properties of species distributions.