Acorn availability strongly influences wildlife and forest ecology, but production is highly erratic among years, species, locations, and individual trees. Acorns directly affect oak regeneration and populations of wildlife species that rely on them for food, but also have far-reaching, indirect effects on ecosystems. For example, acorn crop size affects rodent populations; rodents, in turn affect songbird nest success by eating eggs, gypsy moths by eating pupae, and lyme disease by carrying the disease and host ticks that spread it. Acorn crop size also affects deer populations that in turn affect forest structure and tree regeneration by browsing. Because of the importance of acorns to wildlife and oak regeneration, land managers and researchers devote a lot of effort to estimating both current-year acorn crop size (hard mast indexing), and landscape-level acorn production capability for planning purposes.
We are conducting a landscape-scale, long-term study on acorn production. This study monitors acorn production by over 500 individual trees of five common eastern oak species throughout Bent Creek Experimental Forest and the greater Pisgah National Forest. Despite a plethora of studies on acorn production, most are short-term, have low sample sizes, and cannot be easily applied by land managers. These data have been used to characterize acorn production patterns among species, locations, and years. These results are used by land managers to determine how many and what species of oaks to leave in harvested stands to maintain mast production. We also have begun to develop a “toolkit” of methods to simplify and standardize hard mast index methods, and to apply estimates of the number of acorns produced to stands or landscapes.
We developed predictive equations for hard mast indices based on the proportion of oak trees bearing acorns (PBA). We confirmed that the PBA oaks alone was also an indicator of crop size, and developed a statistical method that would allow land managers to “translate” PBA into a hard mast index value that was compatible and comparable with values generated by their traditionally used method. By substituting this faster and simpler hard mast index method over the labor-intensive counting of twigs and acorns used in some other methods, land managers can use the time savings to sample more trees to improve hard mast index accuracy. Because PBA can also be used as a stand-alone index of acorn production, state and federal agencies can standardize their hard mast surveys, thus ensuring that acorn production data are comparable at local and regional scales.
We used our long-term acorn production data to develop predictive models of potential average annual hard mast production by five common eastern oak species, based on tree diameter and estimated crown area. Our predictive models provide a tool for estimating potential acorn production that land managers and forest planners can apply to oak inventory data to tailor estimates of potential average annual acorn production to different forest management scenarios and multiple spatial scales.
These models have been incorporated in the Forest Vegetation Simulator, the US Forest Service’s nationally supported framework for growth and yield modeling. This provides a tool for land managers and planners to compute average acorn production for dynamic forest stands or landscapes through time, and analyze trade-offs with other considerations under different management alternatives.
We plan to further develop application of potential average acorn production models to forested landscapes, as a tool for land managers and forest planners for estimating acorn production under different management scenarios.
- Greenberg, C.H., Keyser, T.L., Zarnoch, S.J., Connor, K, Simon, D.M. 2012. Acorn Viability Following Prescribed Fire in Upland Hardwood Forests. Foresty Ecology and Management 275 (0378-1127 2012) 79-86.
- Greenberg, C.H., Keyser, C.E., Rathbun, L.C., Rose, A.K., Fearer, T.M., McNab, W.H., 2013. Forecasting Long-Term Acorn Production With and Without Oak Decline Using Forest Inventory Data. Forest Science.
- Greenberg, C.H., B.R. Parresol. 2000. Acorn production characteristics of southern Appalachian Oaks: A simple method to predict within-year acorn crop size. USFS Res. Pap. SRS-20.
- Greenberg, C.H. 2000. Individual variation in acorn production by five species of southern Appalachian oaks. For. Ecol. Manage. 132(2000):199-210.
- Greenberg, C.H., B.R. Parresol. 2002. Dynamics of acorn production by five species of southern Appalachian oaks. Pp. 149-172 In: W.J. McShea, W.M. Healy (eds.). Oak Forest Ecosystems: Ecology and Management for Wildlife. Johns Hopkins University Press, Baltimore, MD.
- Greenberg, C.H., G.S. Warburton. 2007. A rapid hard-mast index from acorn presence-absence tallies. J. Wildl. Manage. 71(5):1654-1661.
- Speer, J.H., H.D. Grissino-Mayer, K.H. Orvis, C.H. Greenberg. 2009. Climate response of five oak species in the eastern deciduous forest of the southern Appalachian mountains, USA. Can. J. For. Res.39:507-518.
- Lashley, M.A., J. M. McCord, C.H. Greenberg, C.A. Harper. 2010. Masting characteristics of white oaks: Implications for management. 2009 Proc. Annu. Conf. Southeast. Assoc. Fish and Wildl. Agencies 63:21-26.
- Greenberg, C.H., T.L. Keyser, J.H. Speer. 2011. Temporal patterns of oak mortality in a southern Appalachian forest (1991 – 2006). Nat. Areas J. 31(3):131-137.
- Greenberg, C.H., R.W. Perry, C.A. Harper, D.J. Levey, J.M. McCord. 2011. The role of recently disturbed upland hardwood forest as high quality food patches. Pp. 121-141 in: Greenberg, C.H., B. Collins, F.R. Thompson III (eds.). Sustaining Young Forest Communities: Ecology and Management of Early Successional Habitats in the Central Hardwood Region, USA. Managing Forest Ecosystems, 2011, Vol. 21.
- Rose, A.K., C.H. Greenberg, T.M. Fearer. 2012 (EarlyView online 11-18-2011). Acorn production prediction models for five common oak species of the eastern United States. J. Wildl. Manage.
Cathryn H. Greenberg, Southern Research Station, RWU 4157
Research Partners and Collaborators
- Gordon Warburton, North Carolina Wildlife Resources Commission
- Bernard Parresol, Southern Research Station
- Anita Rose, Southern Research Station, Forest Inventory and Analysis
- Todd Fearer, Partners in Flight
- Chad Keyser, National Forest, Forest Vegetation Simulator
- James Speer, Indiana State University