Evolutionary Dynamics of Life Span
- Project Leader
- Shripad D. Tuljapurkar
Morrison Professor of Population Studies
Department of Biological Sciences Stanford University
454 Herrin Labs, Stanford University, Stanford, CA 94305
- Dates of Entire Project Period
- 7/1/2003 - 6/30/2008
Project Objectives
The specific aims of this project are:
- Assemble a database that will be unique in including:
- high-quality time series of individual observations on many natural populations of different species;
- high quality data on captive breeding primates;
- a large collection of estimated age or size specific demographic rates (many published, some not) on many species of plants and animals.
- Analyze the database to estimate mortality hazards and age patterns of fertility. The project will analyze individual level covariation between survival and the timing and level of reproduction. The project will exploit long time series of data to estimate temporal variance in survival and reproduction, and covariances between life history components. These analyses will be carried out on individual data sets. The project will also carry out a range of comparative analyses in the context of previous studies on related groups of species.
- Extend the theory of evolution in structured populations to develop testable hypotheses about the age pattern and correlation structure of mortality and fertility (and other life history components) and the maintenance of variation in these components.
- Use the theoretical results to formulate testable hypotheses appropriate to the different populations in our database. Use the database to test and evaluate the theoretical hypotheses.
- Performance Site
- Fresh Pond Research Institute, Cambridge, MA 02140
Biological Sciences, Stanford University, Stanford, CA 94305
Department of Biology, University of Miami, Coral Gables, FL 33124
- Key Personnel
-
Top Five (5) Findings: (updated November 2008)
Our central finding is that variance between individuals (in age at death, lifetime reproduction, life history transitions) provides decisive information about the ecology and evolution of life span.
- Human variance in age at death describes the distribution and causes of mortality inequality, and trends in mortality patterns.
- In animals, observed life histories were shown to be characterized by dynamic heterogeneity: variance between individuals in the sequencing of reproduction, and hence in survivorship and fitness. This variation is driven by changes over time in observed phenotypes including reproductive success.
- We developed analytical tools that reveal (i) parallel aggregate age-patterns of mortality in plants and animals that are generated by similar sources of variation; (ii) transitions in phenotypic traits within and between generations and selective forces that act on them; (iii) selection resulting from environmental variability and the response of phenotypes to environments.
- Honeybees and other social insects display striking variation in lifespan between, e.g., queens and workers. We showed that hierarchical selection (within and between population units such as colonies or groups) is the key to understanding such life histories.
- We developed two theories for the evolution of post-reproductive life, showing that selection against rare deleterious mutations falls gradually and not catastrophically with age. Mating between older males and younger females can transfer fitness to older individuals. An alternative mechanism is intergenerational transfers of resources from old to young. We have shown using microsimulations of prehistoric populations that realistic U-shaped mortality patterns do evolve as a result of transfers.
- Progress/Data/Papers/Development
-
We are currently analyzing the animal and plant data sets that are in our data base. We are also starting theoretical analyses of senescence and life span evolution in structured populations inhabiting temporally variable environments.
Progress Report
See also combined progress report under P01 Progress Reports (2003-2008) link.