Spatial variation of global surface soil rock fragment content and its roles on hydrological and ecological patterns

Abstract NASA’s Soil Moisture Active Passive (SMAP) mission provides global surface soil moisture retrievals with a revisit time of 2–3 days and a latency of 24 h. Here, to enhance the utility of the SMAP data, an approach is presented for improving real-time soil moisture estimates (nowcasts) and for forecasting soil moisture several days into the future. The approach, which involves using an estimate of loss processes (evaporation and drainage) and precipitation to evolve the most recent SMAP retrieval forward in time, is evaluated against subsequent SMAP retrievals themselves. The nowcast accuracy over the continental United States is shown to be markedly higher than that achieved with the simple yet common persistence approach. The accuracy of soil moisture forecasts, which rely on precipitation forecasts rather than on precipitation measurements, is reduced relative to nowcast accuracy but is still significantly higher than that obtained through persistence.

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Seasonal and spatial variation of nitrogen dynamics in the litter and surface soil layers on a tropical dry evergreen forest slope

Forest Ecology and Management ◽

10.1016/j.foreco.2010.01.026 ◽

2010 ◽

Vol 259 (8) ◽

pp. 1502-1512 ◽

Cited By ~ 17

Author(s):

Naoyuki Yamashita ◽

Seiichi Ohta ◽

Hiroyuki Sase ◽

Jesada Luangjame ◽

Thiti Visaratana ◽

...

Keyword(s):

Spatial Variation ◽

Surface Soil ◽

Nitrogen Dynamics ◽

Evergreen Forest ◽

Soil Layers ◽

Dry Evergreen Forest ◽

Tropical Dry Evergreen Forest

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Direct radiative effects of tropospheric aerosols on changes of global surface soil moisture

Climatic Change ◽

10.1007/s10584-016-1611-7 ◽

2016 ◽

Vol 136 (2) ◽

pp. 175-187 ◽

Cited By ~ 6

Author(s):

Shaoqing Liu ◽

Min Chen ◽

Qianlai Zhuang

Keyword(s):

Soil Moisture ◽

Surface Soil ◽

Surface Soil Moisture ◽

Radiative Effects ◽

Tropospheric Aerosols ◽

Global Surface

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Temporal and spatial variation of surface soil water content on karst slopes in dry season

Acta Ecologica Sinica ◽

10.5846/stxb201402280349 ◽

2015 ◽

Vol 35 (19) ◽

Cited By ~ 1

Author(s):

张川 Zhang Chuan ◽

张伟 Zhang Wei ◽

陈洪松 Chen Hongsong ◽

聂云鹏 Nie Yunpeng ◽

叶莹莹 Ye yingying ◽

...

Keyword(s):

Spatial Variation ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Surface Soil ◽

Dry Season ◽

Temporal And Spatial Variation ◽

Temporal And Spatial

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Spatial variation in soil physical properties and effects on soil NO3– production on forest hillslopes

10.5194/egusphere-egu2020-6463 ◽

2020 ◽

Author(s):

Tomoki Oda ◽

Megumi Kuroiwa ◽

Naoya Fujime ◽

Kazuo Isobe ◽

Naoya Masaoka ◽

...

Keyword(s):

Spatial Distribution ◽

Soil Moisture ◽

Physical Properties ◽

Spatial Variation ◽

Volcanic Ash ◽

Surface Soil ◽

Soil Physical Properties ◽

Slope Position ◽

Surface Soil Moisture ◽

Slope Bottom

Ammonium (NH4+) and nitrate (NO3&#8211;) concentrations and production rates in forest soil vary by hillslope position due to variation in ammonia-oxidizing microorganism concentrations, soil chemistry, and surface soil moisture. These spatial distributions have a significant effect on nutrient cycles and streamwater chemistry. Soil moisture conditions significantly restrict microbial activity, influencing the spatial distribution of NO3&#8211; concentrations on forest hillslopes. However, studies linking forest hydrological processes to nitrogen cycling are limited. Therefore, we investigated the determinants of spatial variation in soil moisture and evaluated the effects of soil moisture fluctuations on spatial variation in NO3&#8211; concentration and production rate.The study sites were the Fukuroyamasawa Experimental Watershed (FEW) and Oyasan Experimental Watershed (OEW) in Japan. The two have similar topographies, climates, and tree species. In each watershed, a 100 m transect was set up from the ridge to the base of the slope, and soil moisture sensors were installed at soil depths of 10 cm and 30 cm at both the top and bottom of the slope. We collected surface soil samples at a depth of 10 cm at the top, middle, and bottom of the slopes using 100 cm3 cores, and measured soil physical properties, particle size distribution, volcanic ash content, chemical properties (pH, NO3&#8211;, NH4+, nitrification rate, and mineralization rate), and microbial content (archaeal content). Spatial and temporal changes in soil moisture on the hillslope were calculated using HYDRUS-2D to examine contributing factors of soil moisture.At FEW, high NO3&#8211; concentrations and nitrification rates were observed only at the slope bottom and middle, and no NO3&#8211; concentrations were detected at up slope. By contrast, at OEW, high NO3&#8211; concentrations and nitrification rates were observed at all points. NH4+ concentrations were similar at all points in both watersheds. At FEW, 10 cm surface soil moisture fluctuated within 25&#8211;40% at the slope top but was within 40&#8211;50% at the slope bottom. At OEW, surface soil moisture was 30&#8211;40% at both the slope top and bottom, with no significant differences according to slope position. It was confirmed that soil moisture was significantly involved in NO3&#8211; concentration and nitrification rates. Model simulations showed that the difference in soil moisture fluctuations between FEW and OEW was mainly explained by the spatial variation in soil physical properties. In particular, volcanic ash influenced soil moisture along the entire slope at OEW, resulting in high water retention, but only influenced soil moisture at the slope bottom at FEW. These findings indicate that spatial variability in soil physical properties has a significant effect on soil moisture fluctuation and leads to a spatial distribution of NO3&#8211; production.

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Comment on Soil organic stocks are systematically overestimated by misuse of the parameters bulk density and rock fragment content (Poeplau et al., 2017, SOIL, 3, 61–66)

10.5194/soil-2017-23 ◽

2018 ◽

Author(s):

Eleanor U. Hobley ◽

Brian Murphy ◽

Aaron Simmons

Keyword(s):

Bulk Density ◽

Rock Fragment ◽

Rock Fragment Content

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Rock Fragment Content in Soils Shift Root Foraging Behavior in Xerophytic Species

10.21203/rs.3.rs-1165085/v1 ◽

2021 ◽

Author(s):

Hui Hu ◽

Weikai Bao ◽

David M. Eissenstat ◽

Long Huang ◽

Fanglan Li

Keyword(s):

Root Hair ◽

Fine Root ◽

Root Hairs ◽

Root Traits ◽

Rock Fragment ◽

Hair Density ◽

Root Branching ◽

Root Hair Density ◽

Branching Intensity ◽

Rock Fragment Content

Abstract Aims Root traits associated with resource foraging, including fine-root branching intensity, root hair and mycorrhiza, may change in soils with various physical structure indicated by rock fragment content (RFC), while how these traits covariate at the level of individual root branching order is largely unknown.Methods We subjected two xerophytic species, Artemisia vestita (subshrub) and Bauhinia brachycarpa (shrub), to increasing RFC gradients (0%, 25%, 50% and 75%, v v-1) in an arid environment and measured fine-root traits related to resource foraging.Results Root hair density and mycorrhizal colonization of both species decreased with increasing root order, but increased in 3rd- and 4th-order roots at high RFCs (50% or 75%). The two species tend to produce more root hairs than mycorrhizas under the high RFCs. For both species, root hair density and mycorrhizal colonization intensity were negatively correlated with root length and root diameter. Rockiness reduced root branching intensity in both species comparing with rock-free soil. At the same level of RFC, A. vestita had thicker roots and lower branching intensity than B. brachycarpa, and tended to produce more root hairs.Conclusion Our results suggest the high RFC soil conditions stimulated greater foraging functions in higher root orders. We found evidence for a greater investment in root hairs and mycorrhizal symbioses as opposed to building an extensive root system in rocky soils. The subshrub and shrub species took different approaches to foraging in the rocky soil through distinctive trait syndromes of fine-root components.

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