The first challenge is choosing appropriate climate metrics that are closely tied to erosional processes. For example, in fluvial landscapes, most runoff events do little to no geomorphic work due to erosion thresholds, and event-scale variability dictates how frequently these thresholds are exceeded. By analyzing dense hydroclimatic datasets in the contiguous U.S. and Puerto Rico, we show that event-scale runoff variability is only loosely related to event-scale rainfall variability. Instead, aridity and fractional evapotranspiration (ET) losses are much better predictors of runoff variability. Importantly, simple hillslope-scale soil water balance models capture major aspects of the observed relation between runoff variability and fractional ET losses. Together, these results point to the role of vegetation water use as a potential key to relating mean hydrologic partitioning with runoff variability.
The second challenge is that long-term erosion rates are expected to balance rock uplift rates as landscapes approach topographic steady state, regardless of hydroclimatic setting. This is illustrated with new data along the Main Gulf Escarpment, Baja, Mexico. Under this conceptual framework, climate is not expected to set the erosion rate, but rather the erosional efficiency of the system, or the steady-state relief required for erosion to keep up with tectonically driven uplift rates. To assess differences in erosional efficiency across landscapes experiencing different climatic regimes, we contrast new CRN data from tectonically active landscapes in Baja, Mexico and southern California (arid) with northern Honduras (very humid) alongside other published global data from similar hydroclimatic settings. This analysis shows how climate does, in fact, set functional relationships between topographic metrics like channel steepness and long-term erosion rates. However, we also show that relatively small differences in rock erodibility and incision thresholds can easily overprint hydroclimatic controls on erosional efficiency motivating the need for more field based constraints on these important variables.
The majority of trust research has focused on the benefits trust can have for individual actors, institutions, and organizations. This “optimistic bias” is particularly evident in work focused on institutional trust, where concepts such as procedural justice, shared values, and moral responsibility have gained prominence. But trust in institutions may not be exclusively good. We reveal implications for the “dark side” of institutional trust by reviewing relevant theories and empirical research that can contribute to a more holistic understanding. We frame our discussion by suggesting there may be a “Goldilocks principle” of institutional trust, where trust that is too low (typically the focus) or too high (not usually considered by trust researchers) may be problematic. The chapter focuses on the issue of too-high trust and processes through which such too-high trust might emerge. Specifically, excessive trust might result from external, internal, and intersecting external-internal processes. External processes refer to the actions institutions take that affect public trust, while internal processes refer to intrapersonal factors affecting a trustor’s level of trust. We describe how the beneficial psychological and behavioral outcomes of trust can be mitigated or circumvented through these processes and highlight the implications of a “darkest” side of trust when they intersect. We draw upon research on organizations and legal, governmental, and political systems to demonstrate the dark side of trust in different contexts. The conclusion outlines directions for future research and encourages researchers to consider the ethical nuances of studying how to increase institutional trust.