Boise State University

About: Boise State University is a education organization based out in Boise, Idaho, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 3698 authors who have published 8664 publications receiving 210163 citations. The organization is also known as: BSU & Boise State.

Small soil storage capacity limits benefit of winter snowpack to upland vegetation

Abstract: In the western United States, the mountain snowpack is an important natural reservoir that extends spring and summer water delivery to downstream users and ecosystems. The importance of winter snow accumulation to upland ecosystems is not as clearly defined. This study investigates the relative contribution of winter precipitation to upland spring and summer soil moisture storage and availability in a semi-arid mountainous watershed. At this site, coarse soil textures and shallow soil depths limit soil storage capacity to 6–16 cm. Winter precipitation exceeds soil storage capacity by 2.5 times. Accordingly, soil moisture profiles at most locations in the watershed reach field capacity in early winter. With soil storage near capacity, water released by snowmelt primarily contributes to deep drainage and makes a limited contribution to the soil moisture reservoir. Water that is retained by the soil after the snowpack melts is lost to evapotranspiration in as little as 10 days. In contrast, spring precipitation extends moist soil conditions by up to 90 days into the warm season, when ecological water demand is highest. These field observations suggest that changes in spring precipitation, not winter snowpack, may have the greater impact on upland ecosystems in this environment. Furthermore, because winter precipitation is in excess compared to the soil storage capacity, soil moisture availability may be fairly insensitive to climate change-induced transitions from snow to rain. Copyright © 2011 John Wiley & Sons, Ltd.

Peatland warming strongly increases fine-root growth.

Abstract: Belowground climate change responses remain a key unknown in the Earth system. Plant fine-root response is especially important to understand because fine roots respond quickly to environmental change, are responsible for nutrient and water uptake, and influence carbon cycling. However, fine-root responses to climate change are poorly constrained, especially in northern peatlands, which contain up to two-thirds of the world's soil carbon. We present fine-root responses to warming between +2 °C and 9 °C above ambient conditions in a whole-ecosystem peatland experiment. Warming strongly increased fine-root growth by over an order of magnitude in the warmest treatment, with stronger responses in shrubs than in trees or graminoids. In the first year of treatment, the control (+0 °C) shrub fine-root growth of 0.9 km m-2 y-1 increased linearly by 1.2 km m-2 y-1 (130%) for every degree increase in soil temperature. An extended belowground growing season accounted for 20% of this dramatic increase. In the second growing season of treatment, the shrub warming response rate increased to 2.54 km m-2 °C-1 Soil moisture was negatively correlated with fine-root growth, highlighting that drying of these typically water-saturated ecosystems can fuel a surprising burst in shrub belowground productivity, one possible mechanism explaining the "shrubification" of northern peatlands in response to global change. This previously unrecognized mechanism sheds light on how peatland fine-root response to warming and drying could be strong and rapid, with consequences for the belowground growing season duration, microtopography, vegetation composition, and ultimately, carbon function of these globally relevant carbon sinks.

Extension of the Spatial Autocorrelation (SPAC) Method to Mixed-Component Correlations of Surface Waves

Abstract: Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical-radial (ZR) and radial-vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical-vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green's functions from seismic noise.