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The Season of the Snake

  • Writer: Chuck Smith
    Chuck Smith
  • Apr 15, 2017
  • 2 min read

Jones, Lawrence L. C.

Southwest Zoologists' League

Tucson, AZ USA

As part of a larger project to unravel patterns of surface activity for amphibians and reptiles across the American Southwest, the behavior of snake taxa along the U.S.-Mexican borderlands is scrutinized. It has long been known how snakes generally respond to a temperature range, but surface activity due to moisture patterns and rainfall events is less clear. Along the border (primarily considering lowlands), reptiles respond differently to the diverse climate patterns, of which there are many classification systems; however, these do not align well with patterns of seasonal rainfall, temperature regimes, or reptile distribution and activity. From a herp-centric point of view, going from west to east, snakes are variously influenced by several climate regimes, including Mediterranean-maritime (coastal California), summer drought (western Sonoran Desert), bimodal with North American Monsoon (eastern Sonoran and Chihuahuan deserts), and humid subtropical (South and East Texas). Activity patterns of some species of snakes within these climate “zones” are well-studied, although there is a general dearth of information in the literature about most. Many reptiles are only surveyed during an active season assumed on an a priori basis, so negative patterns may be little more than hearsay. Because seasonal activity patterns are intrinsically linked with temperature and precipitation, climate change would likely affect activity, distribution, and survival of our native snake fauna, which is the most diverse in the U.S. However, trends in climate change are not clear for all climate regimes. For example, virtually all climatologists agree that the hottest, driest Southwest deserts will become hotter and drier, but while mean winter precipitation is decreasing, rainfall patterns during the Monsoon are uncertain. An emphasis of this project is to solicit long-term data sets to better predict activity patterns and effects of climate change.


 
 
 

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