Merge pull request #276 from arfon/patch-1

Minor typo fixes.

paper/paper.md

@@ -47,7 +47,7 @@ bibliography: paper.bib
 
 # Summary
 
-The portalcasting package provides a model development, deployment, and evaluation system for forecasting how ecological systems change through time, with a focus on a widely used long-term study of mammal population and community dynamics, the Portal Project [@brown1977competition; @brown1998desert; @Ernest:2018b]. The software is designed to encourage the active engagement of the broad ecological modeling community in understanding the dynamics of this well-sampled empirical system and forecasting future changes. The initial infrastructure for continuous analysis and forecasting at the site provided a functional system for running existing models repeatedly [@White:2018]. However, it did not facilitate the development and evaluation of new models. The portalcasting package combines existing R packages for modeling (eg JAGS), forecasting (eg forecast) and data management (eg portalr) into a continuous pipeline that produces new forecasts and allows for new model development.
+The portalcasting package provides a model development, deployment, and evaluation system for forecasting how ecological systems change through time, with a focus on a widely used long-term study of mammal population and community dynamics, the Portal Project [@brown1977competition; @brown1998desert; @Ernest:2018b]. The software is designed to encourage the active engagement of the broad ecological modeling community in understanding the dynamics of this well-sampled empirical system and forecasting future changes. The initial infrastructure for continuous analysis and forecasting at the site provided a functional system for running existing models repeatedly [@White:2018]. However, it did not facilitate the development and evaluation of new models. The portalcasting package combines existing R packages for modeling (e.g., JAGS), forecasting (e.g., forecast) and data management (e.g., portalr) into a continuous pipeline that produces new forecasts and allows for new model development.
 
 The process of code development and exploration outside of a production pipeline is known as sandboxing and is key to scientific progress in a forecasting setting, as it substantially lowers the effort required for new users to contribute models. The portalcasting R package [@RCoreTeam2020] simultaneously provides the engine for production forecasting for this system and a portable sandbox that allows users to set up a fully-functioning replica of the production system on their own computer for testing new models. The package also leverages a container based approach to enable fully reproducible models to be developed and tested for the production system. The associated Docker image is automatically rebuilt with each portalcasting release.