NSF Org:	DEB Division Of Environmental Biology
Recipient:	MICHIGAN STATE UNIVERSITY
Initial Amendment Date:	September 30, 1999
Latest Amendment Date:	September 29, 2004
Award Number:	9981397
Award Instrument:	Standard Grant
Program Manager:	Samuel Scheiner DEB  Division Of Environmental Biology BIO  Directorate for Biological Sciences
Start Date:	November 1, 1999
End Date:	September 30, 2005 (Estimated)
Total Intended Award Amount:	$4,050,077.00
Total Awarded Amount to Date:	$4,050,077.00
Funds Obligated to Date:	FY 1999 = $4,050,077.00
History of Investigator:	Richard Lenski (Principal Investigator) lenski@msu.edu Margaret Riley (Co-Principal Investigator) Christoph Adami (Co-Principal Investigator)
Recipient Sponsored Research Office:	Michigan State University 426 AUDITORIUM RD RM 2 EAST LANSING MI  US  48824-2600 (517)355-5040
Sponsor Congressional District:	07
Primary Place of Performance:	Michigan State University 426 AUDITORIUM RD RM 2 EAST LANSING MI  US  48824-2600
Primary Place of Performance Congressional District:	07
Unique Entity Identifier (UEI):	R28EKN92ZTZ9
Parent UEI:	VJKZC4D1JN36
NSF Program(s):	POPULATION DYNAMICS, Nanoscale Interactions Program, OFFICE OF MULTIDISCIPLINARY AC, STATISTICS, BIOCOMPLEXITY, BIOCHEMICAL & BIOMASS ENG, THEORY OF COMPUTING, INFORMATION & KNOWLEDGE MANAGE
Primary Program Source:	app-0199
Program Reference Code(s):	1366, 9169, 9183, BIOT, EGCH
Program Element Code(s):	117400, 117900, 125300, 126900, 136600, 140200, 286000, 685500
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.074

ABSTRACT

Lenski et al.
9981397

The principal investigators define biocomplexity as the dynamic web of interactions among genes, organisms, and environments. They will investigate the emergence of biocomplexity and examine its consequences for the performance of living organisms and ecological communities. Parallel experiments will be performed with two very different systems, in order to study general principles. One system employs bacteria, and the other system is digital. The latter consists of special computer programs that self-replicate, mutate, and evolve novel sequences of instructions to solve problems. One set of experiments will monitor the evolution of ecosystem complexity, in which a single progenitor diverges into multiple types that perform distinct functions by exploiting different resources. Follow-up experiments will examine the effects of removing member species on the remainder of the community. Another project will develop the software used for studying digital organisms into an educational tool.
This project, which is being supported by the Directorates for Biological Sciences, Computer Information Science and Engineering, Engineering, and by the division of Mathematical Sciences and the MPS Office of Multidisciplinary Activities, will impact several scientific fields, and the findings may provide basic information useful for both environmental and biotechnological applications. For example, ecologists may find principles useful for improving the performance of beneficial organisms in the environment. Computer scientists may discover computational strategies, evolved by real organisms that can be employed in developing more complex software.

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