Submission Type
Poster
Abstract
Many tree species have extremely high variability in their magnitude of reproduction over space and time. Annual seed crop variation in trees affects forest regeneration, and the seeds influence animal reproduction and wildlife population dynamics in numerous species (e.g., birds, mammals, and insects). The number of reproductive structures on trees is commonly estimated by varying visual counting methods, from categorical classifications as done by the National Phenology Network, to timed counts and counts of all visible reproductive structures. Different methods may produce different findings, and with recent multi-species databases, constructed on tree reproduction and for future projects, variation across methods should be compared. We conducted fieldwork and collected data using three different methods of counting visual structures (assigning categories based on abundance, 15-second counts, and 30-second counts) on ten different tree species, including five deciduous and five conifer species. The species included three ash species, northern red oak, paper birch, striped maple, sugar maple, balsam fir, black spruce, tamarack, white pine, and white spruce. We analyzed the data using Nonlinear least squares (nls) function to produce three models (linear, exponential and power regression) then used Akaike’s information criterion corrected (AICc) analysis to propose a best fit method and equation for each tree species studied. These counts can be used to quantify mast seeding and forest regeneration potential.
Included in
Ecology and Evolutionary Biology Commons, Forest Biology Commons, Plant Sciences Commons
Relationships Between Alternative Visual Methods To Quantify Tree Reproduction
Many tree species have extremely high variability in their magnitude of reproduction over space and time. Annual seed crop variation in trees affects forest regeneration, and the seeds influence animal reproduction and wildlife population dynamics in numerous species (e.g., birds, mammals, and insects). The number of reproductive structures on trees is commonly estimated by varying visual counting methods, from categorical classifications as done by the National Phenology Network, to timed counts and counts of all visible reproductive structures. Different methods may produce different findings, and with recent multi-species databases, constructed on tree reproduction and for future projects, variation across methods should be compared. We conducted fieldwork and collected data using three different methods of counting visual structures (assigning categories based on abundance, 15-second counts, and 30-second counts) on ten different tree species, including five deciduous and five conifer species. The species included three ash species, northern red oak, paper birch, striped maple, sugar maple, balsam fir, black spruce, tamarack, white pine, and white spruce. We analyzed the data using Nonlinear least squares (nls) function to produce three models (linear, exponential and power regression) then used Akaike’s information criterion corrected (AICc) analysis to propose a best fit method and equation for each tree species studied. These counts can be used to quantify mast seeding and forest regeneration potential.
Comments
1Riley Adams, 2Teodora Stoycheva, 2A. Sofia Rivera, 2Jalene M. LaMontagne
1Department of Science Health and Pharmacy, Roosevelt University, Chicago, IL; 2Department of Biological Sciences, DePaul University, Chicago, IL