Dynamic process connectivity explains ecohydrologic responses to rainfall pulses and drought

Ecohydrologic fluxes within atmosphere, vegetation, and soil systems exhibit a joint variability that arises from forcing and feedback interactions. These interactions cause fluctuations to propagate between variables at many time scales. In an ecosystem, this connectivity dictates responses to climate change, land-cover change, and weather events and must be characterized to understand resilience and sensitivity. We use an information theory-based approach to quantify connectivity in the form of information flow associated with the propagation of fluctuations between variables. We apply this approach to study ecosystems that experience changes in dry-season moisture availability due to rainfall and drought conditions. We use data from two transects with flux towers located along elevation gradients and quantify redundant, synergistic, and unique flow of information between lagged sources and targets to characterize joint asynchronous time dependencies. At the Reynolds Creek Critical Zone Observatory in Idaho, a dry-season rainfall pulse leads to increased connectivity from soil and atmospheric variables to heat and carbon fluxes. At the Southern Sierra Critical Zone Observatory in California, separate sets of dominant drivers characterize two sites at which fluxes exhibit different drought responses. For both cases, our information flow-based connectivity characterizes dominant drivers and joint variability before, during, and after disturbances. This approach to gauge the responsiveness of ecosystem fluxes under multiple sources of variability furthers our understanding of complex ecohydrologic systems.

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31 years of hourly spatially distributed air temperature, humidity, and precipitation amount and phase from Reynolds Critical Zone Observatory

Earth System Science Data ◽

10.5194/essd-10-1197-2018 ◽

2018 ◽

Vol 10 (2) ◽

pp. 1197-1205 ◽

Cited By ~ 6

Author(s):

Patrick R. Kormos ◽

Danny G. Marks ◽

Mark S. Seyfried ◽

Scott C. Havens ◽

Andrew Hedrick ◽

...

Keyword(s):

Relative Humidity ◽

Air Temperature ◽

Precipitation Amount ◽

Critical Zone ◽

Dew Point ◽

Elevation Gradients ◽

Wide Range ◽

Critical Zone Observatory ◽

Reynolds Creek ◽

Spatially Distributed

Abstract. Thirty-one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed, which is part of the Critical Zone Observatory network. The air temperature, relative humidity, and precipitation amount data are spatially distributed over a 10 m lidar-derived digital elevation model at an hourly time step using a detrended kriging algorithm. This 21 TB dataset covers a wide range of weather extremes in a mesoscale basin (238 km2) that encompasses the rain–snow transition zone and should find widespread application in earth science modeling communities. Spatial data allow for a more holistic analysis of basin means and elevation gradients, compared to weather station data measured at specific locations. Files are stored in the NetCDF file format, which allows for easy spatiotemporal averaging and/or subsetting. Data are made publicly available through an OPeNDAP-enabled THREDDS server hosted by Boise State University Libraries in support of the Reynolds Creek Critical Zone Observatory (https://doi.org/10.18122/B2B59V).

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31 years of hourly spatially distributed air temperature, humidity, and precipitation amount and phase from Reynolds Critical Zone Observatory

Earth System Science Data Discussions ◽

10.5194/essd-2017-82 ◽

2017 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Patrick R. Kormos ◽

Danny G. Marks ◽

Mark S. Seyfried ◽

Scott C. Havens ◽

Andrew Hedrick ◽

...

Keyword(s):

Relative Humidity ◽

Air Temperature ◽

Precipitation Amount ◽

Critical Zone ◽

Dew Point ◽

Elevation Gradients ◽

Wide Range ◽

Critical Zone Observatory ◽

Reynolds Creek ◽

Spatially Distributed

Thirty one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed, which is part of the Critical Zone Observatory network. The air temperature, relative humidity, and precipitation amount data are spatially distributed over a 10&thinsp;m Lidar-derived digital elevation model at an hourly time step using a detrended kriging algorithm. This dataset covers a wide range of weather extremes in a mesoscale basin (237&thinsp;km<sup>2</sup>) that encompasses the rain-snow transition zone and should find widespread application in earth science modeling communities. Spatial data allows for a more holistic analysis of basin means and elevation gradients, compared to weather station data measured at specific locations. Files are stored in the NetCDF file format, which allows for easy spatiotemporal averaging and/or subsetting. Data are made publicly available through an OPeNDAP-enabled THREDDS server hosted by Boise State University Libraries in support of the Reynolds Creek Critical Zone Observatory (<a href="https://doi.org/doi:10.18122/B2B59V" target ="_blank">https://doi.org/10.18122/B2B59V</a>).

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Dataset for Observed Suspended Sediment and Particulate Organic Carbon Concentrations and Modeled Long-Term Suspended Sediment and Particulate Organic Carbon Yields (1994-2017) from the Reynolds Creek Experimental Watershed and Critical Zone Observatory in Southwestern Idaho, USA

Boise State ScholarWorks ◽

10.18122/reynoldscreek.25.boisestate ◽

2021 ◽

Author(s):

Kayla A. Glossner ◽

Kathleen A. Lohse ◽

Alison P. Appling ◽

Zane K. Cram ◽

Erin Murray ◽

...

Keyword(s):

Organic Carbon ◽

Particulate Organic Carbon ◽

Suspended Sediment ◽

Critical Zone ◽

Critical Zone Observatory ◽

Reynolds Creek ◽

Carbon Concentrations

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Data for Partitioned Carbon and Energy Fluxes Within the Reynolds Creek Critical Zone Observatory

Boise State Data Sets ◽

10.18122/b2td7v ◽

2018 ◽

Cited By ~ 3

Author(s):

Gerald N. Flerchinger ◽

Aaron W. Fellows ◽

Mark S. Seyfried ◽

Kathleen Lohse

Keyword(s):

Critical Zone ◽

Energy Fluxes ◽

Critical Zone Observatory ◽

Reynolds Creek

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Spatial pattern of soil organic carbon acquired from hyperspectral imagery at reynolds creek critical zone observatory (RC-CZO)

2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) ◽

10.1109/whispers.2016.8071812 ◽

2016 ◽

Author(s):

Aihua Li ◽

Ryan Will ◽

Nancy F. Glenn ◽

Shawn Benner ◽

Lucas P. Spaete

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Spatial Pattern ◽

Hyperspectral Imagery ◽

Critical Zone ◽

Critical Zone Observatory ◽

Reynolds Creek

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Application of Hydrogeophysical Imaging in the Reynolds Creek Critical Zone Observatory

10.18122/b22x42 ◽

2017 ◽

Author(s):

Travis Nielson

Keyword(s):

Critical Zone ◽

Critical Zone Observatory ◽

Reynolds Creek

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The Effect of Aspect and Elevation on Critical Zone Architecture in the Reynolds Creek Critical Zone Observatory: A Seismic Refraction Study

Frontiers in Water ◽

10.3389/frwa.2021.670524 ◽

2021 ◽

Vol 3 ◽

Author(s):

Travis Nielson ◽

John Bradford ◽

W. Steven Holbrook ◽

Mark Seyfried

Keyword(s):

Seismic Refraction ◽

Critical Zone ◽

Snow Accumulation ◽

P Wave ◽

The North ◽

Refraction Tomography ◽

Critical Zone Observatory ◽

Reynolds Creek ◽

The Difference ◽

Weathering Zone

In the northern hemisphere within snow-dominated mountainous watersheds north-facing slopes are commonly more deeply weathered than south-facing slopes. This has been attributed to a more persistent snowpack on the north facing aspects. A persistent snowpack releases its water into the subsurface in a single large pulse, which propagates the water deeper into the subsurface than the series of small pulses characteristic of the intermittent snowpack on south-facing slopes. Johnston Draw is an east-draining catchment in the Reynolds Creek Critical Zone Observatory, Idaho that spans a 300 m elevation gradient. The north-facing slope hosts a persistent snowpack that increases in volume up drainage, while the south-facing slope has intermittent snowpack throughout the drainage. We hypothesize that the largest difference in weathering depth between the two aspects will occur where the difference in snow accumulation between the aspects is also greatest. To test this hypothesis, we conducted four seismic refraction tomography surveys within Johnston Draw from inlet to outlet and perpendicular to drainage direction. From these measurements, we calculate the weathering zone thickness from the P-wave velocity profiles. We conclude that the maximum difference in weathering between aspects occurs ¾ of the way up the drainage from the outlet, where the difference in snow accumulation is highest. Above and below this point, the subsurface is more equally weathered and the snow accumulations are more similar. We also observed that the thickness of the weathering zone increased with decreasing elevation and interpret this to be related to the observed increase soil moisture at lower elevations. Our observations support the hypothesis that deeper snow accumulation leads to deeper weathering when all other variables are held equal. One caveat is the possibility that the denser vegetation contributes to deeper weathering on north-facing slopes via soil retention or higher rates of biological weathering.

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