Six-year demographic study reveals threat of stochastic extinction for remnant populations of a threatened amphibian

2013 ◽  
Vol 39 (2) ◽  
pp. 244-253 ◽  
Author(s):  
Evan John Pickett ◽  
Michelle Pirrie Stockwell ◽  
Deborah Sheena Bower ◽  
Carla Jean Pollard ◽  
James Ian Garnham ◽  
...  
2021 ◽  
Vol 7 (19) ◽  
pp. eabf8441
Author(s):  
Sarah Klassen ◽  
Alison K. Carter ◽  
Damian H. Evans ◽  
Scott Ortman ◽  
Miriam T. Stark ◽  
...  

Angkor is one of the world’s largest premodern settlement complexes (9th to 15th centuries CE), but to date, no comprehensive demographic study has been completed, and key aspects of its population and demographic history remain unknown. Here, we combine lidar, archaeological excavation data, radiocarbon dates, and machine learning algorithms to create maps that model the development of the city and its population growth through time. We conclude that the Greater Angkor Region was home to approximately 700,000 to 900,000 inhabitants at its apogee in the 13th century CE. This granular, diachronic, paleodemographic model of the Angkor complex can be applied to any ancient civilization.


2007 ◽  
Vol 4 (16) ◽  
pp. 851-863 ◽  
Author(s):  
Alun L Lloyd ◽  
Ji Zhang ◽  
A.Morgan Root

Demographic stochasticity and heterogeneity in transmission of infection can affect the dynamics of host–vector disease systems in important ways. We discuss the use of analytic techniques to assess the impact of demographic stochasticity in both well-mixed and heterogeneous settings. Disease invasion probabilities can be calculated using branching process methodology. We review the use of this theory for host–vector infections and examine its use in the face of heterogeneous transmission. Situations in which there is a marked asymmetry in transmission between host and vector are seen to be of particular interest. For endemic infections, stochasticity leads to variation in prevalence about the endemic level. If these fluctuations are large enough, disease extinction can occur via endemic fade-out. We develop moment equations that quantify the impact of stochasticity, providing insight into the likelihood of stochastic extinction. We frame our discussion in terms of the simple Ross malaria model, but discuss extensions to more realistic host–vector models.


1979 ◽  
Vol 5 (1) ◽  
pp. 180
Author(s):  
M. N. ◽  
K. K. Verma
Keyword(s):  

Author(s):  
Ketan Prajapati ◽  
Jyoti Chawda ◽  
Malvi Thakkar ◽  
Nupur Gajera ◽  
Rohit Thakkar ◽  
...  

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