Methods:
Study site and design
The study will be conducted at the University of Michigan Biological Station in northern Michigan in Emmet County (45°35′N, 84°43′W). The average environmental conditions in Emmet County are 5.5 degrees Celsius average annual temperature and mean annual precipitation of 817mm with 295mm of rainfall. The study site has a history of extensive logging of pre-existing Pinus and Tsugae species up until the early 1900s, which have been replaced by Populus and Betula expanses due to extensive cutting and burning of those conifers. These early-successional forests are now becoming mid-successional, varying in species composition: Quercus, Pinus (once again) and Acer. It will be based off of the Forest Accelerated Succession Experiment (FASET henceforth), initiated in 2008. FASET, as in its name, accelerated the succession of these early-successional forest through stem-girdling (simulating phloem-disrupting insects and diseases) making it the source for numerous ecological studies. The experimental design consists of paired plots between US with an average canopy defoliation of 40% among all plots (depending on tree density in the forest).
Stem diameter measurements
Stem diameter measurements will be achieved by the monitoring and reinstallation of dendrometer bands on FASET/Ameriflux canopy trees. This monitoring and reinstallation will occur two times in 2024, during the summer and in the fall in the paired stands and subsequent plots to assess interannual variability in growth. Utilizing aluminum tape, dendrometers with 1/10 of an inch increments will be constructed and fastened to trees at DBH using coil springs with a modulus of elasticity of 2 to 4 inches per pound (Liming, 1957). Incremental growth is measured by observing the lining up of the bottom sticker increments with the top sticker increments. Diameter increments measured in inches will be converted to cm. Diameter measurements will be converted to mass by site-specific allometric equations and wood C density data. ANPPw estimates per stand will be achieved by taking mass estimations and scaling them to the plot level and then stand level ANPPw, measured in kg/ha/yr. Same will be done for each individual species.
Estimation of wood net primary production
ANPPw will be extrapolated to stand-scale using species and site-specific allometric equations from the yearly cm increments (Gough et al. 2008). Species ANPPw will be calculated per species using site-specific allometric equations from the yearly cm increments. Time series of ANPPw will be calculated for each stand to include all years (2007-2024), where 2007 is a baseline year before FASET was initiated.
Environmental data
Ameriflux tower data will be downloaded for 2024 from the server to add to the 17-year dataset for FASET/Ameriflux. Type of climate data: Photosynthetically active radiation (PAR) measured in umol/m^2*s^1; Average annual air temperature measured in degrees Celsius; Yearly precipitation in cm; Soil temperature at 7.5 cm in degrees Celsius and soil moisture content (vol/vol) as measured in previous study by Wales et al., 2018. These variables provide light, water, air temperature and soil variability, a complete measurement of the abiotic components of the ecosystem. Time series of each variable as in the Appendix, will be recalculated for each stand to include all years (2007-2024), where 2007 is a baseline year before FASET was initiated. The yearly average of each variable will also be calculated.
Data analysis
The first part of the data analysis is to provide published and updated time series on environmental variables, stand ANPPw and species ANPPw for FASET/Ameriflux, as in Figure 1 in the appendix.
The second part entails addressing the first and second objectives and their respective hypotheses. The formula utilized for the coefficient of variance of ANPPw will be Where the standard deviation per year will be divided by the mean per year.
Yearly averages of each individual variable will be correlated with their respective ANPPw values for each paired plot to observe direct climatic effects. Linear regression will be used to ascertain statistical significance. Correlation and the corresponding linear regression between temporal stability and %BA girdled will also be conducted to observe the relationship between these other two variables. More statistical tests will be generated as better acquaintance is made with the data.