Computational protocol: Limited evidence of declining growth among moisture-limited black and white spruce in interior Alaska

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Protocol publication

[…] The static and moving window correlation analyses are limited in the sense that they assume linear and non-interactive relationships between climate and tree growth. To examine the potential for non-linear relationships and interactions among climate variables, we conducted boosted regression tree (BRT) analyses separately for each species using the gbm and dismo packages in R 3.1.2. The same climate variables used in the moving window analyses were included in the BRT analyses. We used a tree complexity of 2, a learning rate of 0.001, a bag fraction of 0.5 and we set the maximum number of regression trees at 30000. The final models were constructed using 3850 trees for white spruce and 3575 trees for black spruce. We examined the potential for interactions among climate variables and constructed partial dependence plots, which depict the modeled relationship between each climate variable and the ring width indices for each species, while holding all other variables at their mean values. [...] Carbon isotope discrimination (Δ13C) in tree-ring alpha-cellulose was examined to provide insight into potential changes in gas exchange physiology of black and white spruce over time. Following examination of the tree-ring chronologies, five time periods of interest were identified: 1895–1904, which was a period of relatively low and stable growth, 1930–1949, when growth of both species rose to a distinct peak, 1950–1959, when growth of both species declined from the peak, 1993–2002, which was a period of recent relatively stable growth and 2003–2012, which includes one of the warmest, driest and most severe wildfire seasons in recorded history (2004). A total of 85 black and 85 white spruce trees were selected for isotopic analysis with the aim of maximizing the inter-series correlation of the selected trees, obtaining an even distribution of both species across the study area and sampling similar numbers of old and young trees. The mean inter-series correlation of the selected trees was 0.420 for black and 0.503 for white spruce. Trees were selected for isotopic analysis on all but 26 of the 109 plots. The desire to sample young trees as well as old trees reduced the sample size for the 1895–1904 period to 53 black and 51 white spruce.The time periods of interest were separated from each increment core and homogenized by slicing into fine fragments with a razor blade. The homogenized samples were then reduced to alpha-cellulose using the water-modified Brendel method,. The alpha-cellulose was dried overnight at 40 °C and 0.3 mg of each sample was weighed into a tin capsule for analysis using an elemental analyzer (Costech 4010, Costech Analytical, Valencia, CA), coupled with a continuous-flow isotope ratio mass spectrometer (Thermo-Finnigan Delta Plus XP, Thermo Electron Corp., Waltham, MA) in the Environment and Natural Resource Institute’s Stable Isotope Laboratory at the University of Alaska Anchorage. Carbon isotope discrimination (Δ13C) was calculated as1ΔC13=δCa13−δCtree131+δCtree13/1000,where δ13Ca is the isotopic value of atmospheric CO2, which has decreased progressively as a result of fossil fuel combustion since the Industrial Revolution. Annual estimates of δ13Ca were obtained from the literature. Data for 2003–2012 were estimated by linear extrapolation of the trend between 1993 and 2002.Tree-ring Δ13C may be influenced by the age (size) of a tree. When a tree is young, it is likely to show greater Δ13C because it may assimilate a larger proportion of soil-respired CO2, because shade may lead to lower photosynthesis and/or because shorter trees exhibit lower resistance to xylem water flow, potentially allowing for greater stomatal conductance. To address potential age effects on Δ13C, we conducted Random Forest regression analyses separately for each species with ring age and time period as independent variables and Δ13C as the dependent variable using the randomForest package in R 3.1.2. We then examined modeled Δ13C over time for each species with ring age held constant at 100 years, which was very close to the mean age of the trees selected for isotopic analysis.To gain further insights into changes in gas exchange physiology over time, we calculated the ratio of intercellular to atmospheric [CO2] (Ci/Ca) from modeled Δ13C:2Ci/Ca=ΔC13−ab−a,where a is fractionation associated with diffusion of CO2 through the stomata (4.4‰), and b is fractionation during carboxylation (27‰). We then used annual estimates of Ca to solve for Ci. Again, estimates of Ca for 2003 to 2012 were obtained by linear extrapolation of the trend between 1993 and 2002. The relationship between Ci/Ca and Δ13C was developed for whole leaf tissue, while our data are for tree-ring alpha-cellulose, which is enriched relative to whole wood and whole leaf tissue. To improve estimates of Ci and Ci/Ca, we applied an offset of −1.33‰ to δ13C of tree-ring alpha-cellulose,.Finally, to further examine changes in the balance between photosynthesis (A) and stomatal conductance (Gs) over time, we calculated intrinsic water-use efficiency (iWUE):3iWUE=AGs=(Ca−Ci)∗11.6. Carbon isotope discrimination in tree-rings is widely used to assess potential changes in moisture limitation to tree growth over time. Use of Δ13C in this context is complicated by two key factors. First, changes in Δ13C over time can be influenced by shifts in either A or Gs, with changes in the former potentially masking or overriding changes in the latter. Second, there is a growing awareness that the Δ13C is actually related to the chloroplast CO2 concentration (Cc), rather than Ci, meaning that Δ13C is influenced both by Gs and by mesophyll conductance (Gm). While Gm generally decreases with moisture limitation and most studies show a positive correlation between Gs and Gm , there may be instances when they are not well correlated and this may add uncertainty to interpretation of trends in Δ13C over time. […]

Pipeline specifications

Software tools dismo, randomforest
Applications Miscellaneous, Phylogenetics
Organisms Picea glauca
Chemicals Carbon, Carbon Dioxide