Bailu Zhao

and 9 more

ā–Ŗ Forests play a crucial role in global carbon cycling, yet their carbon sink capability and resilience are increasingly threatened by drought under climate change. The influence of plant traits on ecosystem functions and their responses to drought remains poorly understood. ā–Ŗ In this study, we analyzed the control of plant traits and climate on forest ecosystem functions and their sensitivity to water stress across eight NEON forest sites spanning diverse temperature and moisture gradients. ā–Ŗ Each site, equipped with eddy covariance flux towers, provided data on intrinsic water-use efficiency (iWUE), water-use efficiency (WUE), and light-use efficiency (LUE). We measured key photosynthetic and hydraulic traits (V c,max , K max , P 50) for the most abundant canopy species at each site, and assessed their sensitivity to soil water content (SWC) by dividing SWC into site-specific quantiles, representing dry to wet conditions. ā–Ŗ To further investigate trait-climate interactions, we integrated the measured traits into the GFDL LM4.1 Land Model and calibrated it using flux tower-derived ecosystem functions. Our findings provide critical insights into how plant traits and climate regulate ecosystem functions and their resilience under water stress, advancing our ability to predict forest responses to future climate scenarios. This project is funded by NSF #2017949. š‘Ž 1 ,š’ƒ šŸ-intercept and slope (i.e. control) that controls how plant trait š‘„ š‘– influences š›½ 1š‘– at site I šœ€ š‘–š‘— , šœ‚ 0š‘– , šœ‚ 1š‘–-random errors

Bailu Zhao

and 2 more

Northern peatlands are a large C stock and often act as a C sink, but are susceptible to climate warming. To understand the role of peatlands in the global carbon-climate feedback, it is necessary to accurately quantify their C stock changes and decomposition. In this study, a process-based model, the Peatland Terrestrial Ecosystem Model, is used to simulate pan-Arctic peatland C dynamics from 15ka BP to 1990. To improve the accuracy of the simulation, spatially-explicit water run-on and runoff processes were considered, four different pan-Arctic peatland distribution datasets were used, and a spatially-explicit peat basal date dataset was developed using a neural network approach. The model was calibrated against 2055 peat thickness observations and the parameters were interpolated to the pan-Arctic region. Using the model, we estimate that, in 1990, the pan-Arctic peatlands soil C stock is 396-421 Pg C, and the Holocene average C accumulation rate was 22.9 g Cā€¢m-2 yr-1. Our estimated peat permafrost development history generally agrees with multi-proxy-based paleo-climate datasets and core-derived permafrost areal dynamics. During 500 BP to 1990, the pan-Arctic region went through the Little Ice Age and Anthropocene warming. Under Anthropocene warming, in the freeze-thaw and permafrost-free regions, the peat C accumulation rate decreased, but it increased in permafrost regions. Our study suggests that if current permafrost regions switch to permafrost-free conditions in a warming future, the peat C accumulation rate of the entire pan-Arctic region will decrease, but the sink and source activities of these peatlands are still uncertain. permafrost. Under Anthropocene warming, in the freeze-thaw and permafrost-free regions, the peat C accumulation rate decreased, but it increased in permafrost regions. This result suggests if permafrost regions switch to permafrost-free conditions, the peat C accumulation rate of the entire pan-Arctic region will decrease.