Data Package Metadata   View Summary

Food-chain length in desert streams of central and southern Arizona, USA

General Information
Data Package:
Local Identifier:edi.1074.2
Title:Food-chain length in desert streams of central and southern Arizona, USA
Alternate Identifier:DOI PLACE HOLDER
Abstract:
## overview Food chain length (FCL) is a key measure of the vertical structure of food webs that determines energy flow through ecosystems, carbon exchange between freshwater ecosystems and the atmosphere, and rates of nutrient cycling. FCL also has a strong bearing on the biomass of green plants in ecosystems and hence on water quality in aquatic ecosystems. Broad-scale syntheses of controls on FCL in stream ecosystems indicate that FCL declines with discharge variation but, counter to theory, does not vary significantly with energy supply. The mechanisms linking discharge and energy to FCL are largely unresolved in streams. We propose that lack of a relationship between energy supply and FCL may be due to variation in efficiency of energy transfer caused by constraints of food quality, or to a temporal mismatch between measures of energy inputs and FCL. Alternatively, the effects of flow variation on FCL may simply be paramount to energy supply, but potential mechanisms linking flow to FCL remain untested. Regime shifts—punctuated change between strings of high- and low-flow events—may cause comprehensive faunal replacement across trophic levels and collapse of the vertical structure of food webs. FCL may change as a result of loss (or gain) of an apex predator, or as a result of changes in feeding relationships leading to apex predators that eat higher on the food chain. Finally, flow variation may indirectly influence FCL through inputs of limiting nutrients during floods. In desert streams, algae typically provide the primary source of energy, and algal production is limited by nitrogen (N). N loading from terrestrial ecosystems is strongly related to flow variation, particularly to the inter-flood interval (IFI) or duration of baseflow between floods. Long IFI leads to larger N pulses and potentially greater net ecosystem production (NEP), thereby providing an indirect effect of flow variation on FCL. Specific aims of the research include: 1) Quantify the effect of food quality, energy supply and energetic efficiencies on FCL and trophic structure, 2) Quantify the effects of IFI on FCL and trophic structure caused by episodic stimulation of NEP by N inputs, and 3) Quantify the effect of flow regime shifts on FCL and trophic structure via direct mortality, shifts in the trophic base of production, and reassembly of the vertical structure of the food web. ## streamwater chemistry Water chemistry was monitored in quarterly in 11 desert streams of Arizona for two to three years. Sample collection occurred at an approximately monthly resolution in two of the streams, with additional sample collection following storms. Six streams were also sampled during fertilization experiments during which nitrate was added to a target concentration of 0.3 mg N/L. ## whole-stream metabolism Whole-stream metabolism was modeled from dissolved oxygen, light, and water temperature in 11 desert streams at a quarterly frequency for 1-3 years. In addition, metabolism of six streams was monitored during 12-14 d fertilization experiments, conducted once each in spring and autumn. During experiments, a control reach was paired with a reach fertilized with nitrate at a target concentration of 0.3 mg N/L. ## benthic organic matter Coarse and fine particulate benthic organic matter were collected and analyzed from 10 desert streams during baseflow conditions. All samples were analyzed for organic matter content, and fine particulate organic matter samples were analyzed for carbon:nitrogen ratio and delta-C-13. ## nutrient-diffusing substrata Nutrient-diffusing substrata (NDS) were incubated in nine streams in Arizona. Replicates (4) of control (no nutrient addition), nitrogen, phosphorus, and nitrogen + phosphorus additions were incubated for three weeks in each stream. NDS were incubated during summer baseflow (June 2017) and in autumn (October 2018). Samples were frozen until extraction and measurement of chlorophyll a concentration.
Publication Date:2022-06-08
Language:english
For more information:
Visit: https://sustainability.asu.edu/caplter/data/data-catalog/view/edi.1074.1/xml/
Visit: DOI PLACE HOLDER

Time Period
Begin:
2017-06-13
End:
2018-12-21

People and Organizations
Contact:Data Manager (Julie Ann Wrigley Global Institute of Sustainability and Innovation, Arizona State University) [  email ]
Creator:Harms, Tamara (University of Alaska Fairbanks)
Creator:Sabo, John (Tulane University)
Creator:Gaines-Sewell, Leah (Arizona State University)

Data Entities
Data Table Name:
1074_coarse_benthic_organic_matter.csv
Description:
mass of coarse benthic organic matter in 10 desert streams
Data Table Name:
1074_fine_benthic_organic_matter.csv
Description:
mass; C:N; delta-C-13; and delta-N-15 of fine benthic organic matter (FBOM) in 10 desert streams
Data Table Name:
1074_nutrient_diffusing_substrata.csv
Description:
standing stocks of chlorophyll on nutrient-diffusing substrata incubated in nine desert streams of Arizona
Data Table Name:
1074_water_chemistry.csv
Description:
water chemistry in 10 desert streams
Data Table Name:
1074_whole_stream_metabolism.csv
Description:
measurements for the calculation of in situ whole-system metabolism in 10 desert streams
Detailed Metadata

Data Entities


Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/edi/1074/2/1f22719386c9ba40001645cede94c866
Name:1074_coarse_benthic_organic_matter.csv
Description:mass of coarse benthic organic matter in 10 desert streams
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Number of Columns:5

Table Structure
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Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/edi/1074/2/015baa7beeff7d8214d6e78c148b58df
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Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/edi/1074/2/4810aa5427dbe6d16c199ff45b428726
Name:1074_nutrient_diffusing_substrata.csv
Description:standing stocks of chlorophyll on nutrient-diffusing substrata incubated in nine desert streams of Arizona
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Table Structure
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Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/edi/1074/2/8f512938a44357c771ebaaf53f03775b
Name:1074_water_chemistry.csv
Description:water chemistry in 10 desert streams
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Reach  
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Time  
location  
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SRP_uM  
NH4_uM  
Fluoride_uM  
Chloride_uM  
Sulfate_uM  
Bromide_uM  
Sodium_uM  
Potassium_uM  
Magnesium_uM  
Calcium_uM  
DOC_uM  
TN_uM  
NO3_uM  
Definition:stream namecontrol or fertilized reachdate of sample collectiontime of sample collectionsample location (if not specified by site coordinates)distance along reach (meter or description)soluble reactive phosphorus concentrationammonium concentrationfluoride concentrationchloride concentrationsulfate concentrationbromide concentrationsodium concentrationpotassium concentrationmagnesium concentrationcalcium concentrationdissolved organic carbon concentrationtotal dissolved nitrogen concentrationnitrate concentration
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Accuracy Report:                                      
Accuracy Assessment:                                      
Coverage:                                      
Methods:                                      

Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/edi/1074/2/f428ee51f8ac819c265503a4c8949ba8
Name:1074_whole_stream_metabolism.csv
Description:measurements for the calculation of in situ whole-system metabolism in 10 desert streams
Number of Records:1132
Number of Columns:41

Time Period
Begin:
2016-02-27
End:
2019-06-04

Table Structure
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Table Column Descriptions
 
Column Name:siteID  
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reach  
type  
location  
date  
expt  
GPP_mean  
GPP_min  
GPP_max  
ER_mean  
ER_min  
ER_max  
K600_daily_mean  
K600_min  
K600_max  
ltmod_vs_ltobs  
depth_m  
discharge_m3s  
DO.obs_mean  
DO.obs_median  
DO.obs_max  
DO.obs_min  
DO.sat_mean  
DO.sat_median  
DO.sat_max  
DO.sat_min  
temp.water_mean  
temp.water_median  
temp.water_max  
temp.water_min  
light_mean  
light_median  
light_max  
DO.mod_mean  
DO.mod_median  
DO.mod_max  
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RMSE  
Rsquared  
MAE  
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Accuracy Report:                                                                                  
Accuracy Assessment:                                                                                  
Coverage:                                                                                  
Methods:                                                                                  

Data Package Usage Rights

This data package is released to the "public domain" under Creative Commons CC0 1.0 "No Rights Reserved" (see: https://creativecommons.org/publicdomain/zero/1.0/). The consumer of these data ("Data User" herein) has an ethical obligation to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or coauthorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is". The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. Thank you.

Keywords

By Thesaurus:
LTER controlled vocabularyalgae, streams, nitrogen, phosphorus, chlorophyll, chlorophyll a, nutrients, benthos, carbon, carbon to nitrogen ratio
Creator Defined Keyword Setcoarse benthic organic matter, fine particulate organic matter
CAPLTER Keyword Set Listarizona, az, arid land

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package
Description:
## streamwater chemistry Water was filtered upon collection (maximum pore size 0.7 μm, glass fiber filters), transported to the laboratory on ice, and frozen until analysis. Samples were analyzed for dissolved organic carbon and total dissolved nitrogen via non-dispersive infrared gas analysis and chemiluminescence, respectively, on a Shimadzu TOC/TN-L. Concentrations of major anions and cations were analyzed via ion chromatography on a Thermo ion chromatograph with AS-18 or HC-11 columns for anions and CS-16 columns for cations. Soluble reactive phosphorus was measured colorimetrically using the molybdate method on a Smartchem autoanalyzer. Ammonium was typically measured colorimetrically using the phenol hypochlorite method on a Smartchem autoanalyzer, and was additionally measured by ion chromatography. Measured concentrations less than the lowest value used in calibration were replaced with half of the limit of quantitation for each analyte (shown below). | Analyte | Limit of quantitation (uM) | |-----------------------------|----------------------------| | ammonium | 0.132 | | bromide | 0.134 | | calcium | 0.46 | | dissolved organic carbon | 8.8 | | chloride | 0.952 | | fluoride | 0.198 | | magnesium | 0.1 | | nitrate | 0.118 | | total dissolved nitrogen | 1.938 | | soluble reactive phosphorus | 0.05 | | potassium | 0.2 | | sodium | 0.204 | | sulfate | 0.314 | Water chemistry was additionally monitored during experimental nitrate fertilization in six streams. Six streams were fertilized by continuous addition of fertilizer for 12-14 d during the dry period preceding summer and winter rains (Table 1). The target nitrate concentration was 0.3 mg N/L. Dates of fertilizer addition are detailed below. | Site | Date | Fertilization | |------------|------------|---------------| | Agua Fria | 04/13/2016 | start | | Agua Fria | 04/27/2016 | end | | Agua Fria | 10/19/2016 | start | | Agua Fria | 10/31/2016 | end | | Sycamore | 04/19/2017 | start | | Sycamore | 05/03/2017 | end | | Bonita | 10/19/2018 | start | | Bonita | 11/02/2018 | end | | Eagle | 10/21/2018 | start | | Eagle | 11/04/2018 | end | | Eagle | 04/27/2019 | start | | Eagle | 05/11/2019 | end | | Bonita | 04/26/2019 | start | | Bonita | 05/18/2019 | end | | San Pedro | 04/20/2018 | start | | San Pedro | 05/04/2018 | end | | Santa Cruz | 04/19/2018 | start | | Santa Cruz | 05/03/2018 | end | | San Pedro | 10/08/2017 | start | | San Pedro | 10/22/2017 | end | | Santa Cruz | 10/07/2017 | start | | Santa Cruz | 10/21/2017 | end | ## whole-stream metabolism Whole-stream metabolism was modeled from dissolved oxygen concentration, light incident to the stream, and water temperature, all monitored at 15-min intervals. Oxygen and temperature were monitored at 1-2 stations per reach for 2-14 days, four times per year. Estimates of gross primary production, ecosystem respiration, and gas evasion were modeled using the streamMetabolizer package available for R (Appling et al. 2018). The package’s default priors were applied. Rate of gas evasion was estimated by partially pooling daily estimates within binned ranges in stream discharge, measured at the nearest USGS gauging station. The dataset includes metabolism monitored during experimental nitrate fertilization in six streams. Six streams were fertilized by continuous addition of fertilizer for 12-14 d during the dry period preceding summer and winter rains (Table 1). The target nitrate concentration was 0.3 mg N/L. Monitoring of metabolism during fertilization experiments typically included two stations within an upstream, control (unfertilized) reach; one station immediately above the fertilizer addition; and one station ~50-100 m downstream of fertilizer addition. | Site | Date | Fertilization | |------------|------------|---------------| | Agua Fria | 04/13/2016 | start | | Agua Fria | 04/27/2016 | end | | Agua Fria | 10/19/2016 | start | | Agua Fria | 10/31/2016 | end | | Sycamore | 04/19/2017 | start | | Sycamore | 05/03/2017 | end | | Bonita | 10/19/2018 | start | | Bonita | 11/02/2018 | end | | Eagle | 10/21/2018 | start | | Eagle | 11/04/2018 | end | | Eagle | 04/27/2019 | start | | Eagle | 05/11/2019 | end | | Bonita | 04/26/2019 | start | | Bonita | 05/18/2019 | end | | San Pedro | 04/20/2018 | start | | San Pedro | 05/04/2018 | end | | Santa Cruz | 04/19/2018 | start | | Santa Cruz | 05/03/2018 | end | | San Pedro | 10/08/2017 | start | | San Pedro | 10/22/2017 | end | | Santa Cruz | 10/07/2017 | start | | Santa Cruz | 10/21/2017 | end | Appling, A. P.; Hall, R. O.; Yackulic, C. B.; Arroita, M. Overcoming Equifinality: Leveraging Long Time Series for Stream Metabolism Estimation. J. Geophys. Res. Biogeosci. 2018, 123 (2), 624–645. https://doi.org/10.1002/2017JG004140. ## benthic organic matter Benthic organic matter was sampled within a standardized surface area using an open-ended cylinder pressed into the streambed. Five replicate samples of each of coarse (greater than 1 mm; CBOM) and fine (less than 1 mm; FBOM) benthic organic matter were collected from each stream during the dry period (May-June) preceding the summer monsoon season. Larger CBOM was manually removed from the streambed and suspended CBOM was retrieved using an aquarium net. FBOM was sampled by stirring the sediment followed by immediate collection of two 125-mL bottles of the suspension. Samples were transported on ice to the laboratory and refrigerated until processing. CBOM was dried at 105 degrees C for three days, then weighed, and expressed as mass per area streambed. Volume of FBOM samples was measured prior to filtering through pre-combusted and weighed GF/F filters (0.7 um, glass fiber). FBOM was then dried for three days at 105 degrees C, weighed (dry mass), ashed for 4 h at 450 degrees C, then dried for 3 days at 105 degrees C and reported as ash-free dry mass. A separate subsample of FBOM was processed for carbon and nitrogen content and stable isotopes. These subsamples were dried at 60 degrees degrees degrees degrees degrees degrees degrees degrees degrees C before elemental analysis coupled to an isotope-ratio mass spectrometer. ## nutrient-diffusing substrata Nutrient diffusing substrata were prepared and deployed following Tank et al. 2006. Agar was prepared using N<sub>H</sub>4Cl and KNO<sub>3</sub> (equal concentration N from each form) and KH<sub>2</sub>PO<sub>4</sub> at 0.5 M. Controls included unamended agar. Agar was poured into plastic cups and capped with a fritted glass disc (surface area = 5 cm<sup>2</sup>). Four replicate cups of each nutrient treatment were affixed to steel bars and anchored to the bed of each of eleven streams. Cups were incubated for three weeks, in Jun-Jul 2017 and Nov-Dec 2018. Upon retrieval, fritted glass disks were removed from the cups and transported to the laboratory on dry ice, where they were frozen at -80 degrees C. Chlorophyll a was extracted from biomass on each fritted glass disk in hot ethanol. Samples were held in the dark until analysis. Each disk was placed in 95% ethanol and heated to 79 degrees C in a water bath for 5 minutes, followed by cooling in a refrigerator for 24 h. Absorbance of the extractant was then measured at 665 and 750 nm on a spectrophotometer. Hydrochloric acid (0.1 M) was added and samples were incubated for 90 s before reading absorbance a second time. Chlorophyll a and phaeophytin were then calculated as follows: Chlorophyll a (mg m<sup>–2</sup>) = 28.78\*(665<sub>0</sub> - 665<sub>a</sub>)\*v/(A\*l) Phaeophytin (mg m<sup>–2</sup>) = 28.78\*[1.72\*(665<sub>a</sub>) - 665<sub>0</sub>]\*v/(A\*l) where 665<sub>0</sub> = absorbance at 665 before acid addition minus absorbance at 750 nm, 665<sub>a</sub> = absorbance at 665 nm after acid addition minus absorbance at 750 nm, v = volume of extractant used (L), A = area of benthos sampled (m<sup>2</sup>) and l = path length of cell (1 cm). ## literature cited - Appling, A. P.; Hall, R. O.; Yackulic, C. B.; Arroita, M. Overcoming Equifinality: Leveraging Long Time Series for Stream Metabolism Estimation. J. Geophys. Res. Biogeosci. 2018, 123 (2), 624–645. https://doi.org/10.1002/2017JG004140. - APHA (American Public Health Association). 2005. Standard methods for examination of water and wastewater, 19th ed. American Public Health Association, Washington, DC. - Parker, S.P., W.B. Bowden, and M.B. Flinn. 2016. The effect of acid strength and postacidification reaction time on the determination of chlorophyll a in ethanol extracts of aquatic periphyton. Limnology and Oceanography: Methods 14:839-852. - Sartory, D.P., and J. U. Grobbelaar. 1984. Extraction of chlorophyll a from freshwater phytoplankton for spectrophotometric analysis. Hydrobiologia 114:177-187. - Tank, J.L., M.J. Bernot, E.J. Rosi-Marshall. 2006. Nitrogen limitation and uptake. In: Methods in Stream Ecology, 2nd edition, p. 213-238, F. Hauer & G. Lamberti, editors.

People and Organizations

Publishers:
Organization:Environmental Data Initiative
Email Address:
info@edirepository.org
Web Address:
https://edirepository.org
Id:https://ror.org/0330j0z60
Creators:
Individual: Tamara Harms
Organization:University of Alaska Fairbanks
Email Address:
tamara.harms@alaska.edu
Id:https://orcid.org/0000-0001-7845-1109
Individual: John Sabo
Organization:Tulane University
Email Address:
jsabo1@tulane.edu
Id:https://orcid.org/0000-0001-5259-0709
Individual: Leah Gaines-Sewell
Organization:Arizona State University
Email Address:
Leah.gaines-sewell@asu.edu
Id:https://orcid.org/0000-0001-9352-0766
Contacts:
Organization:Julie Ann Wrigley Global Institute of Sustainability and Innovation, Arizona State University
Position:Data Manager
Address:
Arizona State University,
Global Institute of Sustainability and Innovation,
Tempe, AZ 85287-5402 USA
Email Address:
caplter.data@asu.edu
Web Address:
https://researchdata.asu.edu/
Metadata Providers:
Individual: Tamara Harms
Organization:University of Alaska Fairbanks
Email Address:
tamara.harms@alaska.edu
Id:https://orcid.org/0000-0001-7845-1109

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:

Time Period
Begin:
2017-06-13
End:
2018-12-21
Sampling Site: 
Description:Agua Fria
Site Coordinates:
Longitude (degree): -112.0733Latitude (degree): 34.3179
Sampling Site: 
Description:Babacomari
Site Coordinates:
Longitude (degree): -110.4257Latitude (degree): 31.6362
Sampling Site: 
Description:Bonita
Site Coordinates:
Longitude (degree): -109.5334Latitude (degree): 32.9572
Sampling Site: 
Description:Eagle
Site Coordinates:
Longitude (degree): -109.4417Latitude (degree): 33.0654
Sampling Site: 
Description:Ramsey
Site Coordinates:
Longitude (degree): -110.3137Latitude (degree): 31.4458
Sampling Site: 
Description:San Francisco
Site Coordinates:
Longitude (degree): -109.2984Latitude (degree): 33.072
Sampling Site: 
Description:San Pedro
Site Coordinates:
Longitude (degree): -110.1606Latitude (degree): 31.6064
Sampling Site: 
Description:Santa Cruz
Site Coordinates:
Longitude (degree): -110.8508Latitude (degree): 31.3444
Sampling Site: 
Description:Sycamore
Site Coordinates:
Longitude (degree): -111.5058Latitude (degree): 33.7537
Sampling Site: 
Description:Verde
Site Coordinates:
Longitude (degree): -112.4013Latitude (degree): 34.8681
Sampling Site: 
Description:Wet Beaver
Site Coordinates:
Longitude (degree): -111.714Latitude (degree): 34.6685

Temporal, Geographic and/or Taxonomic information that applies to Data Table: 1074_whole_stream_metabolism.csv


Time Period
Begin:
2016-02-27
End:
2019-06-04

Project

Parent Project Information:

Title:Collaborative Research: Effects of Flow Regime Shifts, Anticendent Hydrology, Nitrogen Pulses and Resource Quantity and Quality on Food Chain Length in Rivers
Personnel:
Individual: Tamara Harms
Organization:University of Alaska Fairbanks
Email Address:
tkharms@alaska.edu
Id:https://orcid.org/0000-0001-7845-1109
Role:Co-Principal Investigator
Abstract:The pattern of water flow in a river can affect the abundance of plants and animals and the food web that supports fisheries. Severe floods that scour the riverbed can potentially displace or kill plants and animals, however, little is known about how floods (or droughts) or the timing of these across years affects the complexity and diversity of food webs. Some work suggests that river flow is a stronger determinant than the quantity of plant production on the flow of energy through the food web, but little is known about how the quality of plant food affects food chains and biodiversity. The study will provide fundamental information on how the timing of floods and droughts across years influences water quality (nitrate inputs to rivers), primary production, and the production of animals higher in the food web, such as fish. The researchers will produce a synthesis of research in hydrology and ecology to improve the management of arid land rivers. This work will reach across fundamental knowledge to education, from kindergarten to graduate levels. The project will have numerous broader impacts including training of several undergraduates, graduate students, and a postdoc. Researchers will work with a non-profit group to integrate project findings into an existing citizen science program on river drying sponsored by The Nature Conservancy, and develop an environmental education program for grades K-5. Finally, the research team will establish an innovative open source, distributed graduate seminar on application of statistical methods in ecology. Researchers will study streams spanning a gradient in the timing of rainfall to examine the role of changing hydrologic regimes in altering nitrogen supply, energy supply and food web structure in arid land streams. This proposal will: 1) Quantify the effect of food quality, energy supply and energetic efficiencies on trophic structure, 2) Quantify the effects of time between floods on stimulation of plant production and trophic structure, and 3) Quantify the effect of changes in flow regime on trophic structure via direct mortality, shifts in plants at the base of the food web, and the structure of the food web. Proposed research activities include characterization of the hydrologic regime, analysis of food webs across a hydroclimate gradient, and manipulation of nitrogen supply. Extreme event statistics and spectral analyses will characterize properties of flood intervals and flow regime shifts across 12 study sites spanning a gradient in timing of rainfall and hydrologic variation (monsoon vs. winter precipitation dominance) in Arizona. Derived hydrologic metrics will be used in combination with measures of ecosystem metabolism, N supply, secondary consumer energetic efficiencies, resource stoichiometry, and the proportion of autochthonous energy sources as predictor variables of food chain length and trophic structure to understand the mechanisms linking energetics and hydrology to food chain length. This comparative study includes 12 streams within the same biogeographic province that feature an algal-dominated food source and similar ecosystem size (1st-3rd order streams). Additionally researchers will conduct a nitrogen enrichment experiment in 6 streams to disentangle the indirect effects of water flow on nitrogen cycling versus the direct effects on plants and animals.
Funding: - NSF 1457567 - NSF 1457689
Additional Award Information:
Funder:National Science Foundation
Funder ID:https://ror.org/021nxhr62
Number:1457689
Title:Collaborative Research: Effects of Flow Regime Shifts, Anticendent Hydrology, Nitrogen Pulses and Resource Quantity and Quality on Food Chain Length in Rivers
URL:https://nsf.gov/awardsearch/showAward?AWD_ID=1457689&HistoricalAwards=false
Related Project:
Title:Collaborative Research: Effects of Flow Regime Shifts, Anticendent Hydrology, Nitrogen Pulses and Resource Quantity and Quality on Food Chain Length in Rivers
Personnel:
Individual: John Sabo
Organization:Tulane University
Email Address:
jsabo1@tulane.edu
Id:https://orcid.org/0000-0001-5259-0709
Role:Co-Principal Investigator
Abstract:The pattern of water flow in a river can affect the abundance of plants and animals and the food web that supports fisheries. Severe floods that scour the riverbed can potentially displace or kill plants and animals, however, little is known about how floods (or droughts) or the timing of these across years affects the complexity and diversity of food webs. Some work suggests that river flow is a stronger determinant than the quantity of plant production on the flow of energy through the food web, but little is known about how the quality of plant food affects food chains and biodiversity. The study will provide fundamental information on how the timing of floods and droughts across years influences water quality (nitrate inputs to rivers), primary production, and the production of animals higher in the food web, such as fish. The researchers will produce a synthesis of research in hydrology and ecology to improve the management of arid land rivers. This work will reach across fundamental knowledge to education, from kindergarten to graduate levels. The project will have numerous broader impacts including training of several undergraduates, graduate students, and a postdoc. Researchers will work with a non-profit group to integrate project findings into an existing citizen science program on river drying sponsored by The Nature Conservancy, and develop an environmental education program for grades K-5. Finally, the research team will establish an innovative open source, distributed graduate seminar on application of statistical methods in ecology. Researchers will study streams spanning a gradient in the timing of rainfall to examine the role of changing hydrologic regimes in altering nitrogen supply, energy supply and food web structure in arid land streams. This proposal will: 1) Quantify the effect of food quality, energy supply and energetic efficiencies on trophic structure, 2) Quantify the effects of time between floods on stimulation of plant production and trophic structure, and 3) Quantify the effect of changes in flow regime on trophic structure via direct mortality, shifts in plants at the base of the food web, and the structure of the food web. Proposed research activities include characterization of the hydrologic regime, analysis of food webs across a hydroclimate gradient, and manipulation of nitrogen supply. Extreme event statistics and spectral analyses will characterize properties of flood intervals and flow regime shifts across 12 study sites spanning a gradient in timing of rainfall and hydrologic variation (monsoon vs. winter precipitation dominance) in Arizona. Derived hydrologic metrics will be used in combination with measures of ecosystem metabolism, N supply, secondary consumer energetic efficiencies, resource stoichiometry, and the proportion of autochthonous energy sources as predictor variables of food chain length and trophic structure to understand the mechanisms linking energetics and hydrology to food chain length. This comparative study includes 12 streams within the same biogeographic province that feature an algal-dominated food source and similar ecosystem size (1st-3rd order streams). Additionally researchers will conduct a nitrogen enrichment experiment in 6 streams to disentangle the indirect effects of water flow on nitrogen cycling versus the direct effects on plants and animals.
Funding: - NSF 1457567 - NSF 1457689
Additional Award Information:
Funder:National Science Foundation
Funder ID:https://ror.org/021nxhr62
Number:1457567
Title:Collaborative Research: Effects of Flow Regime Shifts, Anticendent Hydrology, Nitrogen Pulses and Resource Quantity and Quality on Food Chain Length in Rivers
URL:https://nsf.gov/awardsearch/showAward?AWD_ID=1457567&HistoricalAwards=false

Maintenance

Maintenance:
Description:this dataset is complete and or updates are not anticipated
Frequency:notPlanned
Other Metadata

Additional Metadata

additionalMetadata
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        |     |     |     |  \___attribute 'multiplierToSI' = 'unknown'
        |     |     |     |  \___attribute 'name' = 'perDay'
        |     |     |     |  \___attribute 'parentSI' = 'unknown'
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        |     |     |     |___element 'description'
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        |     |___text '\n    '
        |___text '\n  '

EDI is a collaboration between the University of New Mexico and the University of Wisconsin – Madison, Center for Limnology:

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