Quantifying Fine-root Branching Response to Experimental Ecosystem Warming Utilizing Image Analysis Software

Peatlands store large amounts of soil carbon and this carbon is vulnerable to global change. Peatland carbon, if released into the atmosphere, could feedback into global warming via increased atmospheric greenhouse gases. Fine roots are adaptive and integral to biogeochemical processes due to their role in plant nutrient and water acquisition. Thus, the fine-root trait-environment relationships are key to modeling whole-ecosystem responses to climate change. For example, branching intensity (a root trait describing number of branch tips per unit length of root) can adapt to changing moisture and temperature, but the extent and mechanism of root branching in peatlands is unknown. Further, environmental responses of branching relative to other traits, such as root length and diameter, are unclear in peatlands, and can relate to plant resource allocation strategies. We sought to determine (1) if image analysis software (WinRHIZO™) can be used to evaluate branching intensity and (2) whether shrub fine-root branching intensity increases with warming (and associated drying). To address these objectives, we analyzed images of fine roots collected from cores at the "Spruce and Peatland Responses Under Changing Environments" (SPRUCE) experiment. In SPRUCE, ten experimental plots provide temperature and atmospheric CO₂ gradients. WinRHIZO™'s tip counts did not correlate with manual counts (R²= 0.56, p<0.001), especially in images with numerous roots. Thus, for objective (2), we manually counted root tips in images. We found no significant relationship between branching intensity and warming in the ambient CO₂ plots, indicating that branching may not be the first trait responsive to warming. Rather, fine-root length responded strongly to warming. Conversely, in plots with elevated CO₂, branching and temperature correlated strongly and positively (R²=0.84, p =0.03). This result suggests that branching response to warming varies by CO₂ concentrations. Our study provides valuable data on root traits for future global climate and peatland models.