Progress 10/01/19 to 09/30/20
Outputs
Target Audience:Forest managers, forestry consultants, wildlife managers, forest and wildlife scientists Changes/Problems:We had a PhD student who worked on the Deer-Forest project for two years but failed to make progress on his research. Unfortunately, the time and resources put into working with him did not yield much in the way of products. What opportunities for training and professional development has the project provided?Three graduate students (2 MS and 1 PhD) worked and were trained under the program. How have the results been disseminated to communities of interest?One peer-reviewed research paper, noted elsewhere, was published. What do you plan to do during the next reporting period to accomplish the goals?Goal 1. Using data from the Deer-Forest permanent plots, we will develop models of forest vegetation distribution and demographics (colonization, regeneration, growth and mortality) in northeastern forests that account for climate, landscape position, soils, and plant and animal interactions, including deer browsing, and use these models to develop decision support tools to help forest managers better achieve target future forest conditions. Work with the post-doc will focus on modeling the impact of micro-exclosures on one subplot out of fiveon 200 permanent plots that have been monitored for seven years. We plan to compare the dynamics of tree seedlings and indicator species within the micro-exclosureswith their dynamics on the un-fenced plots. We also have a subset of the plots (24 plots) where a full-factorial experiment was conducted to look at three treatments 1) fencing, 2) herbicides, and 3) liming. These plots have been measured once before treatment, and twice after treatment (oneyear and threeyears). Goal 2. Using data from the Deer-Forest treatment areas, we will develop models of forest vegetation demographics(colonization, regeneration, growth and mortality) following herbicide treatments and use these models to develop decision support tools to help forest managers better achievefuture target forest conditions. Work will continue with Autumn Sabo on modeling the dynamics of tree seedlings and indicator species on plots following herbicide treatments. Goal 3. Using data from the Oak Regeneration Project Assessments, develop models of tree seedling demographics(regeneration, growth and mortality) following harvest and use these models to develop decision support tools to help forest managers better achieve future target forest conditions. We expect Jennifer Nieves will complete her thesis on stump sprouting quantity and survival. Following that, we will work on writing a journal article about her results.
Impacts
What was accomplished under these goals?
Impact: Forest and wildlife managers need both 1) a better understanding of the dynamics of forest ecosystems and the complex interactions among the many factors driving these dynamics and 2) research-based tools to help them predict how management interventions will influence the future state of the forest. This project focuses on better understanding two general components of these dynamics in eastern hardwood forests: 1) deer-vegetation-soils interactions, and 2) tree regeneration, with a focus on oak regeneration. One goal of this project is to develop a better measure of deer impact on forest ecosystems that accounts for the complex interactions of the unique factors of a given site. Such a measure will better inform wildlife managers' decisions related toallocating hunting permits to regulate deer populations. It will also be useful to forest managers who can apply to programs such as the Deer Management Assistance Program (DMAP) in Pennsylvania for additional hunting permits to be issued for use on their properties. Another goal is to develop better tools to help forest managers 1) assess advance regeneration on a site to better project future species composition following harvests, and 2) assess tree regeneration following harvest to determine whether long-term species composition goals are likely to be met. Goal 1. Progress on this objective was limited due to failure of the graduate student to make adequate progress toward his degree. We also did not have a field season for this part of the project this year due to the COVID-19 pandemic. Funds that would have gone toward the field season and to pay the graduate student were re-directed to hiring a post-doc. The new post-doc started at the beginning of October 2020. Goal 2.We have been collaborating with Autumn Sabo, a faculty member from Penn State's Beaver Campus, to accomplish this objective. Autumn has focused on initial data cleaning at this pointand has just begun to organize the data for analysis. Goal 3.Field work forthis objective was paused this year due to the COVID-19 pandemic. Lake Graboski, a master's student, completed his thesis and published one paper. In this study, we used direct observations of oak seedling dominance in the stem exclusion stage of stand development (mean age=17.4 years) to model the probability of successful regeneration during stand initiationas a function of stand conditions before and after harvest (ages −1, 1, 4, and 7 years). For pre-harvest conditions,the most predictive model was based solely on the aggregate height of advance regeneration oak seedlings15 cm in sample plots. As expected, post-harvest models were morepredictive, and increasingly morepredictive with the passage of time;and they were optimized by contrasting the height of the plot-dominant oakseedling with the heights of competing tree species. The predictive power of post-harvest models increased most between ages 1 and 4 years and only slightly between ages 4 and 7, indicating that age 4 is an optimal time toevaluate opportunities to favor oak regeneration with early silvicultural interventions. Of the two most commoncompetitors, black birch (Betula lenta) had the more inhibitory effect on the success of oak regeneration when itwas present. However, red maple (Acer rubrum) was the more important competitor because of its very highfrequency of occurrence in plots occupied by oak seedlings. In addition, Jennifer Nieves, another master's student, has been focusing on stump sprouting.In her study, the effects of (1) location, (2) original tree diameter at breast height (DBH), (3) harvest treatment, (4) site moisture regime, (5) species, and (6) time on sprouting frequency and sprout growth and survival were evaluated for 13 species in Connecticut (CT), Missouri (MO), Pennsylvania (PA), Tennessee (TN), and Wisconsin (WI);although species composition varied among locations and not all variable comparisons could be made for all species. Sprouting probability was significantly affected by location forAcer rubrum,Acer saccharum,Betula lenta,Caryaspp.,Fraxinus americana,Quercus alba, andQuercus montana, DBH for all species exceptBetula lenta,andharvest treatment forAcer rubrumand oak species. The number of sprouts produced was significantly affected by location forAcer saccharum,Fagus grandifolia, andQuercus velutinaand DBH for two species. Sprouting percentages forAcer saccharum,Fagus grandifolia, andQuercus montanastumps in PA were also significantly affected by moisture regime. ForCaryaspp. andQuercus albastumps located in PA, TN, and MO, dominant sprout height and sprout numbers during the first fouryears after cutting were significantly related to location. In PA stands, sprout numbers were reduced to no more than fivesprouts 15 years after cutting for all species;and the dominant sprout height ofAcer rubrumand oak species both reached ~11m after 20 years. The models presented in this study aid in our understanding of sprouting predictors and the various intricacies of regeneration dynamics between species in the eastern United States.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Graboski, L.E., K.C. Steiner, M.E. McDill, and J.C. Finley. 2020. Predicting oak regeneration success at the stem exclusion stage of stand development in upland hardwood forests. Forest Ecology and Management 465(2020) DOI: 10.1016/j.foreco.2020.118093.
- Type:
Theses/Dissertations
Status:
Other
Year Published:
2019
Citation:
Graboski, L.E. 2019. A quantitative analysis of oak seedling success in regenerating stands. Unpublished Master's Thesis. The Pennsylvania State University.
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