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Forest Structural Complexity and Biomass Predict First-Year Carbon Cycling Responses to Disturbance

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Abstract

The pre-disturbance vegetation characteristics that predict carbon (C) cycling responses to disturbance are not well known. To address this gap, we initiated the Forest Resilience Threshold Experiment, a manipulative study in which more than 3600 trees were stem girdled to achieve replicated factorial combinations of four levels (control, 45, 65, and 85% gross defoliation) of disturbance severity and two disturbance types (targeting upper or lower canopy strata). Applying a standardized stability framework in which initial C cycling resistance to disturbance was calculated as the first-year natural log response ratio of disturbance and control treatments, we investigated to what extent pre-disturbance levels of species diversity, aboveground woody biomass, leaf area index, and canopy rugosity—a measure of structural complexity—predict the initial responses of subcanopy light-saturated leaf CO2 assimilation (Asat), aboveground wood NPP (ANPPw), and soil respiration (Rs) to phloem-disrupting disturbance. In the year following stem girdling, we found that above-ground C cycling processes, Asat and ANPPw, were highly resistant to increases in disturbance severity, while Rs resistance declined as severity increased. Disturbance type had no effect on first-year resistance. Pre-disturbance aboveground woody biomass, and canopy rugosity were positive predictors of ANPPw resistance and, conversely, negatively related to Rs resistance. Subcanopy Asat resistance was not related to pre-disturbance vegetation characteristics. Stability of C uptake processes along with Rs declines suggest the net C sink was sustained in the initial months following disturbance. We conclude that biomass and complexity are significant, but not universal, predictors of initial C cycling resistance to disturbance. Moreover, our findings highlight the utility of standardized stability measures when comparing functional responses to disturbance.

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Data and Code Availability

Data used in this analysis are available via the R FoRTE data package: https://fortexperiment.github.io/fortedata/. Derived data products and statistical analysis are available via: https://doi.org/10.5281/zenodo.3779040.

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ACKNOWLEDGEMENTS

Our work was funded by the National Science Foundation, Division of Environmental Biology, Award 1655095. We thank the University of Michigan Biological Station for logistical and technical support, and the use of research infrastructure. We appreciate comments supplied by two anonymous reviewers and the Subject Editor, Dr. Seidl.

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Correspondence to Christopher M. Gough.

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CMG and BBL conceived and designed the study; CMG, JWA, BBL, KRD, RTF, MSG, LTH, KCM, SCP, ANS, and JMT performed research and analyzed data; CMG led and all others contributed to the writing of the paper.

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Gough, C.M., Atkins, J.W., Bond-Lamberty, B. et al. Forest Structural Complexity and Biomass Predict First-Year Carbon Cycling Responses to Disturbance. Ecosystems 24, 699–712 (2021). https://doi.org/10.1007/s10021-020-00544-1

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