The aggressive invasion of exotic reptiles in Florida with a focus on prominent species: A review

Abstract

Florida, along with Hawaii, has among the two worst invasive species problems in the USA, and the state is especially susceptible to establishment by alien reptiles. Besides the large numbers of established non-native reptile species in Florida, many of these species present novel difficulties for management, or have other characteristics making effective management extremely challenging. Moreover, initiation of management action requires more than recognition by experts that a potentially harmful species has become established. It also requires the political will along with concomitant resources and appropriate personnel to develop effective methods and apply them. We review the situation in Florida, including assessment of risk for establishment, and we use a subset of prominent species to illustrate in more detail the array of invasive reptile species circumstances in Florida, including routes of introduction, impacts, and potential and implemented management actions. These examples not only highlight the severity of the invasive reptile problems in the state, but they also show the diversity in resolve and response towards them and the motivating factors.

Weighing empirical and hypothetical evidence for assessing potential invasive species range limits: a review of the case of Burmese pythons in the USA

“…Because preferred optimum temperature ranges and thermal limits are undefined for most reptiles, climate matching is a commonly applied modeling technique for estimating the geographical limits and risk potential of an invasive species based on where it occurs in its native range (Engeman et al 2011). Bomford et al (2009) proposed that climate matching can be a valuable tool for assessing risk of establishment by alien herpetofauna, and many researchers have been exploring and evaluating attributes for assessing establishment risk (Bomford et al 2009;Hayes and Barry 2008;Stohlgren and Schnase 2006).…”

“…Bomford et al (2009) proposed that climate matching can be a valuable tool for assessing risk of establishment by alien herpetofauna, and many researchers have been exploring and evaluating attributes for assessing establishment risk (Bomford et al 2009;Hayes and Barry 2008;Stohlgren and Schnase 2006). As with all statistics and modeling, the data upon which a model is generated and the analytical methods used to produce the results determine the accuracy and utility of inferences (Engeman et al 2011). Thus, it is essential to accurately define the appropriate native climate data to use in range predictions.…”

“…Common sense guidelines can contribute to, but not guarantee, accuracy. Incorporating climate data from localities distant from the source population and combining native range data from multiple taxa likely lead to a propagation of errors when predicting invasive range potential (Engeman et al 2011;Jacobson et al 2012). …”

“…That is, the hypothetical range prediction with the most parsimonious assumptions (most conservative range predictions) corresponded well with the empirical observations of Burmese pythons experiencing local temperature extremes. The empirical evidence from the cold spell also demonstrated that extreme daily temperature changes rather than, or in addition to, monthly mean temperatures need to be factored into climate-based models for defining areas at risk of invasion (Avery et al 2010;Engeman et al 2011).…”

“…For example, one potential error would be to assume that a species occurs throughout the area loosely connected by boundary lines within which record locations occur, as this makes it impossible to associate with certainty a weather station to a specific area in which the species is found. Another potential trap would be to strictly consider species record locations and meteorological stations based on twodimensional map distances without also considering intervening three-dimensional altitudinal topographies, as this could greatly bias the climate data for the native range (e.g., Engeman et al 2011). Furthermore, Jacobson et al (2012) suggest developing distribution models that link spatial data with physiological responses of the species to its environment (e.g., Kearney and Porter 2009), although this approach requires information on species physiological ecology which often is not available.…”