The long and winding road of evolutionary demography: preface. Issue 1 (29th May 2018)

• Record Type: Journal Article
• Authors: Takada, Takenori; Shefferson, Richard
• Is Part Of: Population ecology. Volume 60:Issue 1/2(2018)
• Page Start: 3
• Page End: 7
• Publication Date: 2018-05-29
• Subjects: Eco‐evolutionary dynamics -- Evolutionary demography -- Fitness -- Special issue; Animal populations -- Periodicals; Insect populations -- Periodicals; 591.788
• DOI: 10.1007/s10144-018-0622-9
• Languages: English
• ISSNs: 1438-3896

Abstract

Abstract: Fitness can be calculated using demographic parameters such as survival and fecundity, which are normally used to examine population dynamics in ecology. This concept is at the heart of Darwin's thinking on natural selection. Natural selection optimizes survival and fertility schedules through differential fitness, and these optimal schedules drive changes in population dynamics. Therefore, there must exist an interaction between ecology and evolution. One of the disciplines that focus on the interaction is "Evolutionary demography". It uses age‐ or stage‐specific demographic parameters throughout the whole life history to explore the evolution of life histories. Data throughout the life history of a species is indispensable to study evolutionary demography. To this end, two large‐scale databases of plant and animal life history are now available online, the COMPADRE Plant Matrix Database and the COMADRE Animal Matrix Database. We are now in a revolutionary era in the demographic research of plant and animal populations (including human populations). Many skills and approaches are needed to answer questions on evolutionary demography including bodies of theory and analytical toolkits. This special issue covers a wide array of subjects: (1) Demographic analysis of populations (including human populations) from the point of view of evolutionary ecology, (2) Meta‐analysis using big databases of populations, (3) Eco‐evolutionary studies at the population and/or community level and (4) Theoretical studies and the development of mathematical models of life history evolution. 14 collected papers are published to answer a variety of questions using original ideas, new tools, and big data.