Herpetological Microbiogeography of Colorado I

Colorado Herpetological Society's

Guide to the Reptiles and Amphibians of Colorado

About this Guide

Naming Conflicts,
Documenting,
& References

INDEX OF SPECIES
By Common Name
By Scientific Name
Grouped By Family

Index of Counties
Map of Counties

IDENTIFICATION KEYS
Amphibians
Turtles
Lizards
Snakes

List of Subspecies

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Herpetological Microbiogeography of Colorado I:

Numerical Summary

Todd Duncan (2), Kirk Reichard (1), Lauren J. Livo (1), Hobart M. Smith (1), and David Chiszar (3)

(1) EPO Biology, University of Colorado, Boulder, CO 80309 USA
(2) Department of Geography, University of Colorado, Boulder, CO 80309 USA
(3) Department of Psychology, University of Colorado, Boulder, CO 80309 USA

Livo (1995) updated Hammerson's (1986) distribution maps for all taxa of herpetozoa in Colorado. To this information we add predictions regarding additional county records likely to be found in our state. For each county we list the number of taxa (species and subspecies) now documented and the number of taxa not currently documented but likely to occur there. Our predictions are based on the proximity of verified collecting localities and on knowledge of topography and climate in each of the Colorado counties (Table 1). Although this work is speculative, we regard our thinking to be conservative in the sense that each prediction is associated with nearby records, contemporary or historical. We consider only taxa already known to occur in Colorado, although several new state records are possible (e.g., the rubber boa Charina bottae in Moffat County). The bull frog (Rana catesbeiana), though introduced into Colorado, is so firmly established that we treat it as a component of our herpetofauna (see Livo et al., 1996).

County Type Documented Probable County Type Documented Probable

Adams E 24 4 La Plata W 23 5

Alamosa M 13 3 Lake M 4 2

Arapahoe E 22 6 Larimer M 25 5

Archuleta M 18 5 Las Animas E 42 8

Baca E 41 8 Lincoln E 28 4

Bent E 39 9 Logan E 25 6

Boulder M 26 4 Mesa W 29 1

Chaffee M 7 2 Mineral M 3 11

Cheyenne E 25 11 Moffat W 22 3

Clear Creek M 8 2 Montezuma W 27 4

Conejos M 11 6 Montrose W 22 8

Costilla M 10 7 Morgan E 24 4

Crowley E 20 22 Otero E 42 7

Custer M 12 22 Ouray M 11 7

Delta W 23 7 Park M 7 0

Denver E 20 6 Phillips E 18 13

Dolores W 16 13 Pitkin M 8 1

Douglas M 20 7 Prowers E 31 15

Eagle M 9 0 Pueblo E 32 10

El Paso E 23 9 Rio Blanco W 18 7

Elbert E 26 11 Rio Grande M 11 6

Fremont M 25 11 Routt M 9 3

Garfield W 25 2 Saguache M 10 6

Gilpin M 6 3 San Juan M 4 11

Grand M 9 1 San Miguel W 17 13

Gunnison M 11 9 Sedgwick E 18 13

Hinsdale M 6 8 Summit M 5 1

Huerfano M 22 16 Teller M 7 19

Jackson M 6 0 Washington E 19 11

Jefferson M 23 4 Weld E 28 2

Kiowa E 25 18 Yuma E 29 1

Kit Carson E 21 11

Table 1.
Number of herpetological taxa currently documented from each of the 63 counties of Colorado plus the number of additional taxa that probably occur in each county but are currently undocumented. E = eastern plains counties, M = mountain counties, W = western border counties.

The bottom line is that 454 county records are predicted for the state, a substantial number considering that Colorado presently contains 1,189 such records. Hence, we project that the total will be approximately 1,643 and that 28% of these remain to be documented. Eighteen counties are each expected to yield ten or more records, with Crowley and Custer counties being our "hottest spots" (22 records expected from each). Thus, glancing at Table 1 will help you decide on the profitability of various herping destinations in Colorado.

Figure 1.
Scatter diagram plotting the number of taxa expected (but not yet known) for Colorado counties against the number of taxa currently documented for those counties. Raw data are in table 1. No significant correlation exists between the two variables (r = 0.14, df = 61, p > 0.05)

Figure 1 plots the two columns of Table 1, with the number of taxa known from each county represented on the X axis and the number of taxa expected from each county represented on the Y axis. If collecting effort already devoted to the counties of Colorado is the primary determinate of variance in the expected values, then the points should line up along a line with a downward slope, as is the case for data from Kansas (Figure 2; reprinted from Reichard et al., 1995). In that state, counties with relatively few documented taxa are generally expected to harbor many additional records, whereas counties known to possess rich herpetofaunal assemblies are expected to harbor few additional taxa that have not yet been discovered. In short, the number of taxa expected for a Kansas county is inversely proportional to the effort already devoted to that county. We take Figure 2 to represent a relatively mature stage in the microbiogeographical analysis of an area.

Figure 2.
Scatter diagram plotting the number of taxa expected (but not yet known) for Kansas counties against the number of taxa currently documented for those counties. Raw data are tabled in Reichard et all. (1995). The negative relationship apparent in this scatter diagram is quite significant (r = -0.;54, df = 1-3, p < 0.01).

Clearly, the situation in Colorado is not so neat and clear as that in Kansas. The points in Figure 1 scatter about, exhibiting no clear pattern. Certainly there is no negative slope as is present in Figure 2. Figure 1 might be taken to represent a relatively primitive stage in the accretion of microbiogeographical data. However, it is reasonable to partition Colorado into several sections: the eastern plains counties, the mountain counties, and the western border counties (as indicated in Table 1). Figure 3 and Figure 4 and 5 present separate graphs for each subset of counties, and it turns out that a Kansas like appearance shows up in the eastern plains counties and in the western border counties. In both cases, a negative slope is visible such that counties known to have substantial herpetological diversity (presumably because a lot of fieldwork has been done in these areas) are not expected to yield many new records, but counties currently with few records are expected to contain a fair number of taxa yet undiscovered. If the correlations present in Figure 3 and Figure 5 are combined using the methods of Winer (1971, pp. 49 50), the aggregated result is a quite significant negative relationship (c2 = 20.99, df = 4, p < 0.01).

The mountain counties present an entirely different picture (Figure 4). Here is the source of the chaos noticed in Figure 1, owing partly to the fact that some mountain counties are herpetologically depauperate while others harbor relatively large species assemblages (especially those counties containing deep valleys continuous with eastern, western or southern faunal areas). Because of difficult access to key habitats, some of the latter counties have been under explored (e.g., Custer, Gunnison, Mineral, San Juan and Teller), leaving plenty of taxa yet to be documented. The upshot is that the number of expected taxa ranges from zero in the case of depauperate counties to over twenty for others, even though many of the mountain counties have about the same number of current records (i.e., between five and ten). Such variability mitigates against a significant correlation in Figure 4 and serves as a special challenge to Colorado herpetologists. Indeed, we think the situation depicted in Figure 4 probably occurs nowhere else in the United States. Figure 2, 3 and 5 likely represent the herpetological microbiogeographical state of affairs in the majority of states.

To facilitate county record hunting in Colorado, we will soon publish our lists of taxa expected but not yet documented for each county. It is our hope that this information will be useful in planning field trips, and in promoting the necessary exploration remaining to be done in our state. Many of the predicted county records are for species that are secretive or have highly localized distributions. For example, we anticipate as many as 11 new county records for the night snake (Hypsiglena torquata), a small nocturnal snake that is difficult to find even in prime collecting localities. On the other hand, some new records, such as the racer (Coluber constrictor) in Phillips County, may be rather easily obtained. Good hunting and do not hesitate to contact the authors for advice on reporting your new records.

Figure 3.
Scatter diagram plotting the number of taxa expected (but not yet known) for eastern plains counties of Colorado against the number of taxa currently documented for those counties. Raw data are shown in Table 1. A negative slope is visible in this figure (Y = 13.4 - 0.16X), though the relationship fell short of significance (r = -0.24, df = 21, p > 0.05)

Figure 4.
Scatter diagram plotting the number of taxa expected (but not yet known) for the mountain counties of Colorado against the number of taxa currently documented for those counties. Raw data are shown in Table 1. As in Figure 1, wide variability is evident, and no significant correlation exists (r = 0.17, df = 28, p > 0.05).

Figure 5.
Scatter diagram plotting the number of taxa expected (but not yet known) for the western border counties against the number of taxa currently documented for those counties. Raw data are shown in Table 1. As in Figures 2 and 3, a negative slope is evident (Y = 25.3 - 0.86X; r = -0.87,df = 8, p < 0.05). Hence, a "Kansas-like appearance" is visable in the eastern plains and the western border of Cololrado

References:

Hammerson, G.A. 1986. Amphibians and reptiles in Colorado. Denver, CO, Colorado Division of Wildlife.

Livo, L.J. 1995. Colorado amphibian and reptile records by county. Special publication of the Colorado Herpetological Society, Inc. Pp. 1 20.

Livo, L.J., Hammerson, G.A., and Smith, H.M. 1996. Summary of amphibians and reptiles introduced into Colorado. Under review.

Reichard, K., Duncan, T., Smith, H.M., and Chiszar, D. 1995. Herpetological microbiogeography of Kansas I: Ouantitative summary. KHS Newsletter, No. 102, 6 10.

Winer, B.J. 1971. Statistical principles in experimental design. New York: McGraw Hill.

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