Research in animal behaviour often involves small and idiosyncratic samples. This can constrain the generalizability and replicability of study’s results and prevent meaningful comparisons between samples. However, there is little consensus about what constitutes a replication and what makes a strong comparison in animal research. We apply a resampling definition of replication to answer these questions in Part 1 of this article, and in Part 2, we focus on the problem of representativeness in animal research. Through three case studies, we highlight how and when representativeness may be an issue in animal behavior and cognition research, and show how the representativeness problems can be viewed through the lenses of, i) replicability, ii) generalizability and external validity, iii) pseudoreplication and, iv) theory testing. Next, we discuss when and how researchers can improve their ability to learn from small sample research through, i) increasing heterogeneity in experimental design, ii) increasing homogeneity in experimental design, and, iii) statistically modeling variation. Finally, we describe how the strongest solutions will vary depending on the goals and resources of individual research programmes and discuss some barriers towards implementing them.
Animal cognition research often involves small and idiosyncratic samples. This can constrain the generalizability and replicability of a study’s results and prevent meaningful comparisons between samples. However, there is little consensus about what makes a strong replication or comparison in animal research. We apply a resampling definition of replication to answer these questions in Part 1 of this article, and, in Part 2, we focus on the problem of representativeness in animal research. Through a case study and a simulation study, we highlight how and when representativeness may be an issue in animal behavior and cognition research and show how the representativeness problems can be viewed through the lenses of, i) replicability, ii) generalizability and external validity, iii) pseudoreplication and, iv) theory testing. Next, we discuss when and how researchers can improve their ability to learn from small sample research through, i) increasing heterogeneity in experimental design, ii) increasing homogeneity in experimental design, and, iii) statistically modeling variation. Finally, we describe how the strongest solutions will vary depending on the goals and resources of individual research programs and discuss some barriers towards implementing them.
Advanced, well organized, and operated urban water supply systems existed in Greece from the Bronze Age (ca. 3200–1100 BC). At the dawn of human history, surface water and groundwater, principally springs, were the most common water supply sources. As the population grew, periodic water shortages occurred. In Early Minoan times (ca. 3200–2100 BC), these water shortages led to the development of sophisticated hydraulic structures for importing water and for the harvesting and storage of rainwater. In addition, the water treatment technologies and water distribution techniques developed at that time served as the basis for the advanced technological progress in the development of the urban water supply systems in the centuries that followed. In this paper, an overview of the evolution of public water supplies and water treatment technologies in the Hellenic world through the centuries up to modern times is presented. Some of the most significant innovations in the provision of water, its treatment, and distribution are highlighted. The overview is followed by a discussion of the contemporary situation, emerging trends, and future challenges, and parallels are drawn between historical developments and the water supply problems faced today.
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