Deni Murray
Utah State University;University of New Hampshire | Graduate Student
Subject Areas: | Water quality, Biogeochemistry, Beaver Ponds, Wet Deposition, Nitrogen |
Recent Activity
ABSTRACT:
Dissolved organic matter (DOM) concentrations and composition within wet deposition are rarely monitored despite contributing a large input of bioavailable dissolved organic carbon (DOC) and nitrogen (DON) to the earth’s surface. Lacking from the literature are spatially comprehensive assessments of simultaneous measurements of wet deposition DOC and DON chemistry and their dependencies on metrics of climate and environmental factors. Here, we use archived precipitation samples from the US National Atmospheric Deposition Program collected in 2017–2018 from 17 sites across ecoregions of the United States to investigate variability in the concentration and composition of depositional DOM. We hypothesize metrics of DOM chemistry vary with season, ecoregion, large-scale climate drivers, and precipitation geographic source. Findings indicate differences in DOC and DON concentrations among ecoregions with highest concentrations in the Northern Forests and lowest concentrations in Marine West Coast Forests. Summer and autumn samples contained the highest DOC concentrations and DON concentrations that were consistently above detection limit. DOC: DON ratios exhibit lower values on the west coast and higher ratios toward the east coast. Compositional trends suggest lighter DOM molecules in autumn and winter and heavier molecules in spring and summer. Climate drivers explain 62% of variation in DOM chemistry, revealing distinct influences on the concentrations of DOC versus DON. This study highlights the necessity of incorporating DOC and DON measurements into national deposition monitoring networks, and offers insights into the influence of climate change on wet deposition DOM.
ABSTRACT:
Data collection programs that monitor the Earth’s critical zone (CZ) are becoming increasingly common, aimed at measuring the flux, elemental composition, and distribution of water and matter. Programs often span various spatial and temporal scales leading to challenges for data assimilation and, as a result, limit holistic multi-scale perspectives of hydro-biogeochemical cycling. The CZDP will ultimately synchronize existing repositories of wet deposition chemistry from the National Atmospheric Deposition Program (NADP), meteorology from Daymet, stream chemistry and discharge timeseries from the United States Geological Survey (USGS). I use a data pipeline approach to develop an algorithm that will access each public data repository, pair data based on geocoordinates and timeseries overlap, extract relevant variables, and analyze data. The structure of the data pipeline works from top to bottom of the CZ such that wet deposition chemistry is the focal merging attribute. The resulting data product can be aggregated for paired wet deposition chemistry and daily meteorological variables, or paired timeseries of wet deposition inputs and river exports within the same watershed, or a combination of all data inputs. These datasets can be used by researchers in hydrology, biogeochemistry, global change biology, and Earth system science.
ABSTRACT:
The data provided here is used in the submitted manuscript "Synchrony of nitrogen wet deposition inputs and watershed nitrogen outputs using information theory" by Desneiges S. Murray1, Edom Moges2, Laurel Larsen2, Michelle D. Shattuck1, William H. McDowell1, and Adam S. Wymore1 (1Department of Natural Resources and the Environment, University of New Hampshire, Durham NH, USA; 2Department of Geography, University of California, Berkeley California, USA. Corresponding author: Desneiges Murray (desneiges.murray@unh.edu) to Water Resources Research.
Weekly, year-round, paired (e.g., < 1 km apart) wet deposition and river nitrogen (TDN, NO3, NH4, DON) time series from 2003 to 2020 from the Lamprey River Hydrological Observatory in New Hampshire, USA. Discharge data from the paired USGS site with river chemistry sampling site is also provided. This data is input to the associated Python Script, and is cleaned, paired, and weekly anomalies are calculated for input to information theory (IT) algorithms.
ABSTRACT:
The data provided here is used in the submitted manuscript "Synchrony of nitrogen wet deposition inputs and watershed nitrogen outputs using information theory" by Desneiges S. Murray1, Edom Moges2, Laurel Larsen2, Michelle D. Shattuck1, William H. McDowell1, and Adam S. Wymore1 (1Department of Natural Resources and the Environment, University of New Hampshire, Durham NH, USA; 2Department of Geography, University of California, Berkeley California, USA. Corresponding author: Desneiges Murray (desneiges.murray@unh.edu) to Water Resources Research.
Weekly, year-round, paired (e.g., < 1 km apart) wet deposition and river nitrogen (TDN, NO3, NH4, DON) time series from 2003 to 2020 from the Lamprey River Hydrological Observatory in New Hampshire, USA. Discharge data from the paired USGS site with river chemistry sampling site is also provided. This data is input to the associated Python Script, and is cleaned, paired, and weekly anomalies are calculated for input to information theory (IT) algorithms.
ABSTRACT:
The data provided here is used in the submitted manuscript "Synchrony of nitrogen wet deposition inputs and watershed exports using information theory" by Desneiges S. Murray1, Edom Moges2, Laurel Larsen2, Michelle D. Shattuck1, William H. McDowell1, and Adam S. Wymore1 (1Department of Natural Resources and the Environment, University of New Hampshire, Durham NH, USA; 2Department of Geography, University of California, Berkeley California, USA. Corresponding author: Desneiges Murray (desneiges.murray@unh.edu)
Weekly, year-round, paired (e.g., < 1 km apart) wet deposition and river nitrogen (TDN, NO3, NH4, DON) time series from 2003 to 2020 from the Lamprey River Hydrological Observatory in New Hampshire, USA. Discharge data from the paired USGS site with river chemistry sampling site is also provided. This data is input to the associated Python Script, and is cleaned, paired, and weekly anomalies are calculated for input to information theory (IT) algorithms. IT code can be provided upon request.
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Created: June 13, 2018, 4:49 p.m.
Authors: Deni Murray · Janice Brahney · Bethany Neilson
ABSTRACT:
Beavers alter stream environments by impounding flow and flooding the landscape. This project aims to test whether beaver dams alter the stream biogeochemistry and productivity. Specifically, we hypothesize that dam will be warmer, have greater productivity (measured by chlorophyll proxy), and higher DOC, turbidity, and nutrient concentrations than downstream areas. Field methods include water, periphyton and sediment sampling in paired beaver ponds and stream areas immediately downstream of the dam. Additional sites include one below all dams and one above all dams. We analyzed Spawn Creek which has current beaver activity.
ABSTRACT:
The data provided here is used in the submitted manuscript "Synchrony of nitrogen wet deposition inputs and watershed exports using information theory" by Desneiges S. Murray1, Edom Moges2, Laurel Larsen2, Michelle D. Shattuck1, William H. McDowell1, and Adam S. Wymore1 (1Department of Natural Resources and the Environment, University of New Hampshire, Durham NH, USA; 2Department of Geography, University of California, Berkeley California, USA. Corresponding author: Desneiges Murray (desneiges.murray@unh.edu)
Weekly, year-round, paired (e.g., < 1 km apart) wet deposition and river nitrogen (TDN, NO3, NH4, DON) time series from 2003 to 2020 from the Lamprey River Hydrological Observatory in New Hampshire, USA. Discharge data from the paired USGS site with river chemistry sampling site is also provided. This data is input to the associated Python Script, and is cleaned, paired, and weekly anomalies are calculated for input to information theory (IT) algorithms. IT code can be provided upon request.
Created: Sept. 18, 2023, 5:27 p.m.
Authors: Murray, Deni · Wymore, Adam · McDowell, William H · Potter, Jody · Michelle Shattuck
ABSTRACT:
The data provided here is used in the submitted manuscript "Synchrony of nitrogen wet deposition inputs and watershed nitrogen outputs using information theory" by Desneiges S. Murray1, Edom Moges2, Laurel Larsen2, Michelle D. Shattuck1, William H. McDowell1, and Adam S. Wymore1 (1Department of Natural Resources and the Environment, University of New Hampshire, Durham NH, USA; 2Department of Geography, University of California, Berkeley California, USA. Corresponding author: Desneiges Murray (desneiges.murray@unh.edu) to Water Resources Research.
Weekly, year-round, paired (e.g., < 1 km apart) wet deposition and river nitrogen (TDN, NO3, NH4, DON) time series from 2003 to 2020 from the Lamprey River Hydrological Observatory in New Hampshire, USA. Discharge data from the paired USGS site with river chemistry sampling site is also provided. This data is input to the associated Python Script, and is cleaned, paired, and weekly anomalies are calculated for input to information theory (IT) algorithms.
Created: Oct. 19, 2023, 2:47 p.m.
Authors: Murray, Deni · Wymore, Adam · McDowell, William H · Potter, Jody · Michelle Shattuck
ABSTRACT:
The data provided here is used in the submitted manuscript "Synchrony of nitrogen wet deposition inputs and watershed nitrogen outputs using information theory" by Desneiges S. Murray1, Edom Moges2, Laurel Larsen2, Michelle D. Shattuck1, William H. McDowell1, and Adam S. Wymore1 (1Department of Natural Resources and the Environment, University of New Hampshire, Durham NH, USA; 2Department of Geography, University of California, Berkeley California, USA. Corresponding author: Desneiges Murray (desneiges.murray@unh.edu) to Water Resources Research.
Weekly, year-round, paired (e.g., < 1 km apart) wet deposition and river nitrogen (TDN, NO3, NH4, DON) time series from 2003 to 2020 from the Lamprey River Hydrological Observatory in New Hampshire, USA. Discharge data from the paired USGS site with river chemistry sampling site is also provided. This data is input to the associated Python Script, and is cleaned, paired, and weekly anomalies are calculated for input to information theory (IT) algorithms.
ABSTRACT:
Data collection programs that monitor the Earth’s critical zone (CZ) are becoming increasingly common, aimed at measuring the flux, elemental composition, and distribution of water and matter. Programs often span various spatial and temporal scales leading to challenges for data assimilation and, as a result, limit holistic multi-scale perspectives of hydro-biogeochemical cycling. The CZDP will ultimately synchronize existing repositories of wet deposition chemistry from the National Atmospheric Deposition Program (NADP), meteorology from Daymet, stream chemistry and discharge timeseries from the United States Geological Survey (USGS). I use a data pipeline approach to develop an algorithm that will access each public data repository, pair data based on geocoordinates and timeseries overlap, extract relevant variables, and analyze data. The structure of the data pipeline works from top to bottom of the CZ such that wet deposition chemistry is the focal merging attribute. The resulting data product can be aggregated for paired wet deposition chemistry and daily meteorological variables, or paired timeseries of wet deposition inputs and river exports within the same watershed, or a combination of all data inputs. These datasets can be used by researchers in hydrology, biogeochemistry, global change biology, and Earth system science.
Created: Feb. 2, 2024, 4:01 p.m.
Authors: Murray, Deni · Wymore, Adam
ABSTRACT:
Dissolved organic matter (DOM) concentrations and composition within wet deposition are rarely monitored despite contributing a large input of bioavailable dissolved organic carbon (DOC) and nitrogen (DON) to the earth’s surface. Lacking from the literature are spatially comprehensive assessments of simultaneous measurements of wet deposition DOC and DON chemistry and their dependencies on metrics of climate and environmental factors. Here, we use archived precipitation samples from the US National Atmospheric Deposition Program collected in 2017–2018 from 17 sites across ecoregions of the United States to investigate variability in the concentration and composition of depositional DOM. We hypothesize metrics of DOM chemistry vary with season, ecoregion, large-scale climate drivers, and precipitation geographic source. Findings indicate differences in DOC and DON concentrations among ecoregions with highest concentrations in the Northern Forests and lowest concentrations in Marine West Coast Forests. Summer and autumn samples contained the highest DOC concentrations and DON concentrations that were consistently above detection limit. DOC: DON ratios exhibit lower values on the west coast and higher ratios toward the east coast. Compositional trends suggest lighter DOM molecules in autumn and winter and heavier molecules in spring and summer. Climate drivers explain 62% of variation in DOM chemistry, revealing distinct influences on the concentrations of DOC versus DON. This study highlights the necessity of incorporating DOC and DON measurements into national deposition monitoring networks, and offers insights into the influence of climate change on wet deposition DOM.