In:
NeoBiota, Pensoft Publishers, Vol. 78 ( 2022-11-23), p. 129-158
Abstract:
The design of successful invasive species control programs is often hindered by the absence of basic demographic data on the targeted population. Establishment of invasive Burmese pythons ( Python molurus bivittatus ) in the Greater Everglades Ecosystem, Florida USA has led to local precipitous declines ( & gt; 90%) of mesomammal populations and is also a major threat to native populations of reptiles and birds. Efforts to control this species are ongoing but are hampered by the lack of access to and information on the expected biological patterns of pythons in southern Florida. We present data from more than 4,000 wild Burmese pythons that were removed in southern Florida over 26 years (1995–2021), the most robust dataset representing this invasive population to date. We used these data to characterize Burmese python size distribution, size at maturity, clutch size, and seasonal demographic and reproductive trends. We broadened the previously described size ranges by sex and, based on our newly defined size-stage classes, showed that males are smaller than females at sexual maturity, confirmed a positive correlation between maternal body size and potential clutch size, and developed predictive equations to facilitate demographic predictions. We also refined the annual breeding season (approx.100 days December into March), oviposition timing (May), and hatchling emergence and dispersal period (July through October) using correlations of capture morphometrics with observations of seasonal gonadal recrudescence (resurgence) and regression. Determination of reproductive output and timing can inform population models and help managers arrest population growth by targeting key aspects of python life history. These results define characteristics of the species in Florida and provide an enhanced understanding of the ecology and reproductive biology of Burmese pythons in their invasive Everglades range.
Type of Medium:
Online Resource
ISSN:
1314-2488
,
1619-0033
DOI:
10.3897/neobiota.78.93788
DOI:
10.3897/neobiota.78.93788.suppl1
DOI:
10.3897/neobiota.78.93788.suppl2
DOI:
10.3897/neobiota.78.93788.suppl3
DOI:
10.3897/neobiota.78.93788.suppl4
DOI:
10.3897/neobiota.78.93788.suppl5
DOI:
10.3897/neobiota.78.93788.suppl6
Language:
Unknown
Publisher:
Pensoft Publishers
Publication Date:
2022
detail.hit.zdb_id:
2110967-9
detail.hit.zdb_id:
2628537-X
SSG:
21
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