Molecular Ecology Notes (2002) 2, 615 – 617 doi: 10.1046/j.1471-8278 .2002.00284.x © 2002 Blackwell Science Ltd Blackwell Science, Ltd PROGRAM NOTE managedpop: a computer simulation to project allelic diversity in managed populations with overlapping generations KENNETH BIRNBAUM,* PHILIP N. BENFEY,*§ CHARLES M. PETERS† and ROB DESALLE‡ *New York University, 100 Washington Square East, 1009 Main Building, New York, NY 10003, †New York Botanical Garden, Institute of Economic Botany, Bronx, New York, NY 10458, ‡American Museum of Natural History, Department of Entomology, New York, NY 10024, USA Abstract We present a Monte Carlo simulation, MANAGEDPOP, to project the loss of allelic diversity in a population with overlapping generations supported (or invaded) by a prodigious sub- population. Input parameters allow the user to account for complex life histories and crit- ical management practices, such as the frequency at which supportive breeding stocks are replaced. The simulation could also be used to examine the threat of species or population level extinction via hybridization. MANAGEDPOP merges theoretical formulations on the effective size of supported populations and of populations with overlapping generations using easily measured life history traits. Keywords: allelic diversity, effective population size, genetic drift, introgression, supportive breed- ing, simulation Received 8 May 2002; revision received 2 July 2002; accepted 2 July 2002 Loss of genetic diversity places a population at greater risk of extinction and, in domesticated species and their relatives, the potential loss of economically valuable genetic traits is increased. Small endangered populations are often aug- mented with the progeny of a captive population. Analo- gously, altered landscapes can create high gene flow from genetically uniform populations into wild populations, such as between domesticated crops and their wild relatives. In both cases, gene flow into the population of interest has the potential to alter the effective population size, with important consequences on genetic drift and neutral allelic diversity. Ryman et al. (1995) provided a method with which to estimate the variance effective population size, and by extension the random genetic drift, given the size and relative breeding contributions of a ‘captive’ and a ‘wild’ population. The formula for inbreeding effective size, which is equivalent to variance effective size when population size is stable, is shown here for simplicity: 1/N e = x 2 /N c + (1 - x) 2 /N w where N c and N w are the effective numbers of parents in the captive and wild portions of the populations, respectively, and x and (1–x) are the relative offspring contribution of the captive and wild populations, respectively. The formula illustrates the conservation problem: as x increases, the value of N e decreases and the size of the captive popu- lation, which is typically small, increasingly determines the size of the overall population as it affects genetic drift. In theory, the formula could be used on populations with overlapping generations by calculating effective popu- lation size for each subpopulation using analyses such as Hill’s (1972): N e(e.g. c or w) = 4N a L/(2 + σ a 2 ) where N e is the effective population size of an equivalent population with discrete generation intervals, N a is the number of adults entering the population each generation, σ a 2 is the variance in the number of adult progeny per adult individual, and L is the generation interval. One problem is that L and σ a are not easily estimated parameters in real popu- lations with mixed breeding systems and other complex life history traits (Orive 1992; Nunney & Elam 1994; Rockwell & Barrowclough 1995). Several existing programs avoid Correspondence: R. De Salle. Fax: 212 769 5277; E-mail: desalle@amnh.org. §Present address: Duke University, Depart- ment of Biology, Box 90338, Durham, NC 27708, USA.