Understanding the causes for populations to fluctuate in space and time is of great interest to ecologists and knowledge on this topic has widespread application for conservation and environmental management. The recognition that many species live in highly fragmented landscapes led to the development of metapopulation theory, which is widely applicable to both terrestrial and marine systems. In its simplest form the concept of a metapopulation represents the idea that habitat patches suitable for local populations are either occupied or not and that connectivity among patches acts to "rescue" extinct local populations. Several recent studies on inbreeding have challenged the traditional belief that ecological factors are the primary causes of local population reduction and eventual extinction. However, to date there have been few investigations of the extent to which inbreeding depression drives local population dynamics in a metapopulation. The giant kelp, Macrocystis pyrifera, is an ideal system for testing metapopulation theory because it occurs in discrete patches that undergo frequent local extinctions and recolonizations on time scales of a few years. The investigators will test five related hypotheses aimed at determining whether the metapopulation of the giant kelp in the Southern California Bight is regulated at least in part by repeated and asynchronous episodes of inbreeding depression. This research is motivated by previous findings of the investigators on patterns of local population extinction and recolonization with respect to patch size and degree of isolation, patterns of spore dispersal and genetic connectivity, and the adverse consequences of inbreeding depression to kelp reproduction. This project will: (1) Assess the extent and pattern of inbreeding in populations of giant kelp in the Southern California Bight, and (2) Determine the extent that inbreeding depression via decreased reproduction contributes to the pattern of metapopulation patch dynamics of giant kelp in the Southern California Bight. The research will be greatly facilitated by recent developments of: (1) highly polymorphic microsatellite markers for characterizing the population genetics of giant kelp, (2) a high resolution oceanographic model for estimating connectivity among local populations of giant kelp, and (3) a novel method for estimating effective population size for all discrete patches of giant kelp in the Southern California Bight using Landsat satellite imagery. Broader Impacts: Giant kelp forests are prominent features on shallow reefs in temperate seas worldwide and are among the most productive ecosystems on Earth. Giant kelp itself provides food and habitat for a diverse assemblage of consumers many of which are commercially and recreationally important. Consequently, giant kelp forests are targeted by conservationists, resources managers and policy makers as habitats of special concern due to the high value ascribed to the ecosystems services that they provide. The principal investigators have a history of working with government agencies in developing management plans aimed at protecting these systems and findings from this research will contribute to these ongoing efforts. The proposed research will also contribute to student training and mentoring in interdisciplinary research at the undergraduate, graduate, and post doc levels spread across 3 different institutions. The principal investigators will partner with existing outreach programs at UCSC and UCSB to deliver the results of their research to k-12 and post-secondary institutions, educators, community groups and the general public.

Agency
National Science Foundation (NSF)
Institute
Division of Ocean Sciences (OCE)
Type
Standard Grant (Standard)
Application #
1233283
Program Officer
David L. Garrison
Project Start
Project End
Budget Start
2012-09-01
Budget End
2016-08-31
Support Year
Fiscal Year
2012
Total Cost
$264,575
Indirect Cost
Name
University of California Santa Barbara
Department
Type
DUNS #
City
Santa Barbara
State
CA
Country
United States
Zip Code
93106