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Geology topics

Benjamin M. Bolker

Publications and source records attributed to Benjamin M. Bolker.

2 recordsLinked to original sources

Moving beyond too little, too late: managing emerging infectious diseases in wild populations requires international policy and partnerships

Emerging infectious diseases (EIDs) are on the rise due to multiple factors, including human facilitated movement of pathogens, broad-scale landscape changes, and perturbations to ecological systems (Jones et al. 2008; Fisher et al. 2012). Epidemics in wildlife are problematic because they can lead to pathogen spillover to new host organisms, erode biodiversity and threaten ecosystems that sustain human societies (Fisher et al. 2012; Kilpatrick 2011). There have been recent calls for large-scale research approaches to combat threats EIDs pose to wildlife (Sleeman 2013). While it is true that developing new analytical models, diagnostic assays and molecular tools will significantly avance outr abilities to respond to disease threats, we also propose that addressing difficult problems in EIDs will require considerable shofts in international health policy and infrastructure. While there are currently international organizations responsbile for rapidly initiating and coordinating preventative measures to control infectious diseases in human, livestock, and arable systems, there are few comparable instiutions that have the authority to implement transnational responses to EIDs in wildlife. This absence of well-developed infastructure hampers the rapid responses necessary to mitigate international spread of EIDs.

EcoHealth

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

Methods in Ecology and Evolution