Dataset Overview
Throughout the Northeast, the hemlock woolly adelgid (Adelges tsugae) threatens eastern hemlock (Tsuga canadensis) through direct mortality resulting from infestation followed by defoliation and indirect mortality in the form of pre-emptive logging. The efficacy of regeneration of vegetation following hemlock decline depends upon advance regeneration of seedlings and saplings, seed dispersal, and recruitment. This study investigated (1) whether the basic parameters of height of release and wind velocity affected seed dispersal distance and (2) the fit of a basic ballistic model of seed dispersal to empirical data in areas both with and without canopies. Empirical data was collected from seed dropping and seed rain experiments at Harvard Forest. Height and wind velocity only affected seed dispersal distance in open areas. Predicted values of dispersal distance generated by the basic ballistic model did not provide a good fit to observed dispersal data. Poor fits of the ballistic model to the data were due to the model’s inability to account for rare, long distance dispersal events. More complex models with additional parameters are necessary to model Non-localized seed dispersal.
- Purpose
The purpose of this study was to research the efficacy of regeneration of vegetation following hemlock decline after hemlock wooly adelgid infestation.
- Data Collection Status
-
Data collection for this dataset has been completed
- Start date
2005-01-01
- End date
2005-12-31
- Data Availability
-
This dataset is available to download from another website
- Data License
Linked - Third party determines data license
- Preferred Citation
Record S, Ellison A. 2009. Tree Seed Dispersal in Hemlock Removal Experiment at Harvard Forest 2005. Harvard Forest Data Archive: HF120. Available at: http://harvardforest.fas.harvard.edu:8080/exist/apps/datasets/showData.html?id=hf120
- Update Frequency
Unknown
- Maintenance Plan
Not provided
- Links
-
- Tree Seed Dispersal in Hemlock Removal Experiment at Harvard Forest 2005
- Harvard Forest
- Related Datasets
- Determining Dataset Similarity