Sea Otter (Enhydra lutris), well documented as "keystone" predators in rocky marine communities, were found to exert a strong influence on infaunal prey communities in soft—sediment habitats. Direct and indirect effects of sea otter predation on subtidal soft—bottom prey communities were evaluated along a temporal gradient of sea otter occupancy around the Kodiak Archipelago. The results indicate that Kodiak otters forage primarily on bivalve prey and dramatically reduce infaunal bivalve and green sea urchin (Strongylocentrotus droebachiensis) prey populations. Bivalve prey abundance, biomass, and size were inversely related to duration of sea otter occupancy. The relative conditions of shells discarded by otters in shallow (<10 m) vs. deep (> 20 m) water at the same sites indicate that otters first exploited Saxidomus in shallow—water feeding areas, and later switched to Macoma spp. in deeper water. Otter—cracked shells of the deep—burrowing clam Tresus capax were rarely found, even at otter foraging sites where the clam accounted for the majority of available prey biomass, suggesting that it has a partial depth refuge from otter predation. The indirect effects of otter predation included substratum disturbance and the facilitation of sea star predation on infaunal prey. Sea stars, Pycnopodia helianthoides, were attracted to experimentally dug excavations as well as natural sea otter foraging pits, where the sea stars foraged on smaller size classes of infaunal bivalves than those eaten by otters. Otters also discard clam shells on the sediment surface and expose old, buried shells during excavation. Surface shells were found to provide attachment sites for large anemones and kelp. Our study shows that sea otters can affect soft—sediment communities, not only through predation, as in rocky habitats, but also through disturbance, and thus retain a high degree of influence in two very different habitat types.

We documented number of acorns eaten, cached, and retrieved by Florida Scrub Jays (Aphelocoma coerulescens coerulescens), through one full annual cycle and part of another, in an oak scrub habitat characterized by abundant and reliable annual acorn crops. Jays consumed acorns during all months, with highest consumption from September through February and lowest in June and July. From August through December, most acorns consumed by jays were picked directly from shrubs; during the remaining 7 mo, acorns were recovered from ground stores. Acorn caching occurred throughout the fall, peaking in September and October. Data pooled across sex and age classes suggest that individual jays, on average, each cached between 6500 and 8000 acorns during fall of 1974. Only about one—third of those acorns were recovered later. Intact acorns recovered by Scrub Jays during fall usually were reburied, but by summer most recovered acorns were consumed. Acorn crops in the study area exhibit moderate annual variation but no crop failures. Acorns are available in substantial numbers every year, permitting Florida Scrub Jay territories to serve without fail as year—round warehouses of stored acorns. Those stores provide resources to carry group members through seasons of low arthropod availability, and perhaps facilitate delayed dispersal by juveniles. Use of a habitat characterized by relatively large and dependable annual acorn crops that are evenly dispersed, coupled with caching behavior, may contribute to the maintenance of permanent territoriality and cooperative breeding in this population.

Climate warming affects arctic and boreal ecosystems by interacting with numerous biophysical factors across heterogeneous landscapes. To assess potential effects of warming on diverse local-scale ecosystems (ecotypes) across northwest Alaska, we compiled data on historical areal changes over the last 25-50 years. Based on historical rates of change relative to time and temperature, we developed three state-transition models to project future changes in area for 60 ecotypes involving 243 potential transitions during three 30-year periods (ending 2040, 2070, 2100). The time model, assuming changes over the past 30 years continue at the same rate, projected a net change, or directional shift, of 6 % by 2100. The temperature model, using past rates of change relative to the past increase in regional mean annual air temperatures (1°C/30 year), projected a net change of 17 % in response to expected warming of 2, 4, and 6°C at the end of the three periods. A rate-adjusted temperature model, which adjusted transition rates (±50 %) based on assigned feedbacks associated with 23 biophysical drivers, estimated a net change of 13 %, with 33 ecotypes gaining and 23 ecotypes losing area. Major drivers included shrub and tree expansion, fire, succession, and thermokarst. Overall, projected A. R. DeGange Alaska Climate Science Center, U. S. Geological Survey, 4210 University Drive, Anchorage, AK 99508, USA changes will be modest over the next century even though climate warming increased transition rates up to 9 fold. The strength of this state-transition modeling is that it used a large dataset of past changes to provide a comprehensive assessment of likely future changes associated with numerous drivers affecting the full diversity of ecosystems across a broad region.

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