scholarly journals Widespread Presence of Domestic Dogs on Sandy Beaches of Southern Chile

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 161
Author(s):  
Esteban I. Cortés ◽  
Juan G. Navedo ◽  
Eduardo A. Silva-Rodríguez

Dogs on sandy beaches are a threat to shorebirds. Managing this problem requires understanding the factors that influence the abundance of dogs in these ecosystems. We aimed to determine the proportion of beaches used by dogs and the effects of human presence on dog abundance on sandy beaches of southern Chile. We conducted dog counts and recorded the presence of tracks on 14 beaches. We used zero-inflated generalized linear mixed models to determine if the number of people, number of households, and other covariates were associated with dog abundance. We detected dog tracks on all the beaches, and dog sightings on most of them. Dogs were frequently not supervised (45%) and only 13% of them were leashed. The number of people on the beach and the number of houses near the beach were positively associated with the number of dogs on beaches. Finally, when dogs co-occurred with whimbrels (Numenius phaeopus), the probability of dog harassment was high (59%). Our work reveals that human presence determines the abundance of dogs on sandy beaches. Therefore, our study suggests that any strategy aiming at reducing dog harassment of shorebirds requires changes in those human behaviors that favor the presence of free-ranging dogs at beaches.

2021 ◽  
pp. 096228022110175
Author(s):  
Jan P Burgard ◽  
Joscha Krause ◽  
Ralf Münnich ◽  
Domingo Morales

Obesity is considered to be one of the primary health risks in modern industrialized societies. Estimating the evolution of its prevalence over time is an essential element of public health reporting. This requires the application of suitable statistical methods on epidemiologic data with substantial local detail. Generalized linear-mixed models with medical treatment records as covariates mark a powerful combination for this purpose. However, the task is methodologically challenging. Disease frequencies are subject to both regional and temporal heterogeneity. Medical treatment records often show strong internal correlation due to diagnosis-related grouping. This frequently causes excessive variance in model parameter estimation due to rank-deficiency problems. Further, generalized linear-mixed models are often estimated via approximate inference methods as their likelihood functions do not have closed forms. These problems combined lead to unacceptable uncertainty in prevalence estimates over time. We propose an l2-penalized temporal logit-mixed model to solve these issues. We derive empirical best predictors and present a parametric bootstrap to estimate their mean-squared errors. A novel penalized maximum approximate likelihood algorithm for model parameter estimation is stated. With this new methodology, the regional obesity prevalence in Germany from 2009 to 2012 is estimated. We find that the national prevalence ranges between 15 and 16%, with significant regional clustering in eastern Germany.


Biometrics ◽  
2004 ◽  
Vol 60 (4) ◽  
pp. 1043-1052 ◽  
Author(s):  
Yutaka Yasui ◽  
Ziding Feng ◽  
Paula Diehr ◽  
Dale McLerran ◽  
Shirley A. A. Beresford ◽  
...  

2011 ◽  
Vol 2 (4) ◽  
pp. 428-435 ◽  
Author(s):  
Ya–Hsiu Chuang ◽  
Sati Mazumdar ◽  
Taeyoung Park ◽  
Gong Tang ◽  
Vincent. C. Arena ◽  
...  

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