GSA Connects 2021 in Portland, Oregon

Paper No. 133-4
Presentation Time: 9:50 AM


FORTE, Adam, Geology & Geophysics, Louisiana State University, E235 Howe Russell Kniffen, Baton Rouge, LA 70803 and ROSSI, Matthew W., Earth Lab, Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado at Boulder, Campus Box 611, Boulder, CO 80309

The provocative idea that structural deformation of mountain belts is not only a driver of, but also a response to, climatically driven surface process has driven decades of research. Yet, empirical demonstration of two-way coupling between climate and tectonics has largely been equivocal. Whether the activity and location of structures are coupled to surface processes ultimately relies on there being a direct relationship between topography and erosion rates, assuming erosion tracks with rock uplift. Where erosion-topography relationships are quasi-linear, coupling between surface processes and tectonics is plausible, though still hard to test. However, an increasing number of studies show that erosion–topography relationships can become highly sublinear in many settings, thus dampening potential feedbacks between tectonics and climate. In fluvial settings, the relief structure of the landscapes is set by how bedrock rivers respond to climate. To move beyond simple inference from mean climate, better accounting for how the spatio-temporal statistics of runoff interact with thresholds for river incision is needed. If runoff magnitudes are highly variable or thresholds systematically increase with long-term erosion rates, then more linear erosion-topography relationships are favored. In contrast, low variability runoff or high incision thresholds leads to more sublinear erosion-topography relationships. While runoff statistics partially reflect precipitation statistics, the hydrologic transformation of precipitation to runoff can be highly nonlinear itself and often cannot be ignored. For example, large seasonal snow accumulation and melt tends to decrease runoff variability, regardless of precipitation inputs. As another example, the degree and type of vegetation cover can influence runoff statistics by influencing event-scale runoff response. Both vegetation and snowmelt dynamics filter the climate forcing and co-evolve with mountain ranges as they grow, but are challenging to reconstruct and thus typically poorly represented in landscape evolution models. As such, we view these ‘complications’ to be the forefront in better testing and understanding feedbacks between climate and tectonics over orogenic timescales.