ABSTRACT:

Studies in ecohydrology focusing on hydrologic transport argue that longer residence times across a stream ecosystem should consistently result in higher biological demand for carbon, nutrients, and oxygen. This consideration inadvertently disregards the potential for biologically mediated reactions to be limited by stoichiometric imbalances. Based on the relevance and co-dependences between hydrologic exchange, stoichiometry, and biological uptake, and acknowledging the limited amount of field studies available to determine their net effects on the retention and export of resources, we quantified how microbial respiration is controlled by the interactions and supply of essential nutrients needed (C, N, P) in a headwater stream in Colorado, USA, and in an agricultural canal in Iowa. At each site, we conducted two rounds of experiments, each consisting of four sets of continuous injections of Cl as a conservative tracer, resazurin as a proxy for aerobic respiration, and one of the following nutrient treatments: a) N, b) NC, c) NP, and d) CNP. Nutrient treatments were treated as known system modifications to alter metabolism, and statistical tests indicated the relationships between hydrologic transport metrics and respiration metrics.

This dataset includes conservative and reactive tracer data, as well as discharge values observed during the experiments. It also includes the tracer masses injected and the date and duration of the injections.

ABSTRACT:

These data were used in the following publication. Please cite accordingly:

Nichols J, Khandelwal AS, Regier P, Summers B, Van Horn DJ and González-Pinzón R (2022) The understudied winter: Evidence of how precipitation differences affect stream metabolism in a headwater.
Front. Water 4:1003159. doi: 10.3389/frwa.2022.1003159

Climate change is causing pronounced shifts during winter in the US, including shortening the snow season, reducing snowpack, and altering the timing and volume of snowmelt-related runoff. These changes in winter precipitation patterns affect in-stream freeze-thaw cycles, including ice and snow cover, and can trigger direct and indirect effects on in-stream physical, chemical, and biological processes in ∼60% of river basins in the Northern Hemisphere. We used high-resolution, multi-parameter data collected in a headwater stream and its local environment (climate and soil) to determine interannual variability in physical, chemical, and biological signals in a montane stream during the winter of an El Niño and a La Niña year. We observed ∼77% greater snow accumulation during the El Niño year, which caused the formation of an ice dam that shifted the system from a primarily lotic to a lentic environment. Water chemistry and stream metabolism parameters varied widely between years. They featured anoxic conditions lasting over a month, with no observable gross primary production (GPP) occurring under the ice and snow cover in the El Niño year. In contrast, dissolved oxygen and GPP remained relatively high during the winter months of the La Niña year. These redox and metabolic changes driven by changes in winter precipitation have significant implications for water chemistry and biological functioning beyond the winter. Our study suggests that as snow accumulation and hydrologic conditions shift during the winter due to climate change, hot-spots and hot-moments for biogeochemical processing may be reduced, with implications for the downstream movement of nutrients and transported materials.

ABSTRACT:

Citation:

This tool has been published in a peer-reviewed journal. Please cite this work as:

González-Pinzón, R., J. Dorley, J. Singley, K. Singha, M. Gooseff, and T. Covino. 2022. TIPT: The Tracer Injection Planning Tool. Environmental Modelling & Software 156: 105504. doi:10.1016/j.envsoft.2022.105504

Abstract:

Despite their frequent use, there are few simple and readily accessible tools to help guide the logistical planning of tracer injections in streams and rivers. We combined the widely used advection-dispersion-reaction equation, peak concentration estimates based on a meta-analysis of hundreds of tracer injections carried out in streams and rivers, and simple mass balances in a dynamic Excel Workbook to 1) help users decide how much tracer mass should be added to achieve a specific dynamic concentration range that reduces known issues associated with breakthrough curve tail truncation, and 2) generate tables and graphs that can be readily used to plan the deployment of resources. Our Tracer Injection Planning Tool, TIPT, handles instantaneous and continuous tracer injections and assumes steady-state and uniform flow conditions, as well as first-order decay or production. While those assumptions do not strictly apply to natural streams and rivers, they help simplify the planning of tracer injections with a predictive ability that is disproportionally favorable with respect to the few inputs required. TIPT is a versatile, user-friendly, and graphical tool that can help design tracer injections and solute transport experiments that are more easily replicated within and across sites. Thus, TIPT contributes directly to advancing Integrated, Coordinated, Open, and Networked (ICON) principles. Similarly, TIPT can help generate datasets that more closely follow Findable, Accessible, Interoperable, and Reusable (FAIR) principles.

ABSTRACT:

The Resazurin (Raz) – Resorufin (Rru) tracer system is widely used in hydrological studies. In most field experiments a lack of mass balance closure is reported and, to date, it is still unclear what drives incomplete recovery. We designed controlled laboratory experiments varying the initial concentrations of Raz, the test durations, and the type of microorganisms present to quantify mass balances of Raz and Rru in the absence of other suspected causes of incomplete recovery in field experiments (e.g., sorption to sediments and photodecay) in order to test if microbial activity alone could explain incomplete recovery. We used the summation of Raz and Rru concentrations over time to assess mass recovery and variability. The uploaded datasets present Raz and Rru concentrations measured during our experiments.
Results are published in Dallan et al. (2020) - doi: 10.1029/2019JG005435

Files organization:
“EXP_DESCRIPTION.docx” describes experimental set up, sampling and measurement methods.
“DATASET.xlsx” contains data concentrations of Raz and Rru obtained for the 4 experiments. Each sheet refers to one experiment. Table A summarizes experiment set up. Table B shows Raz concentration for the 18 flasks at the different sampling times. Table C shows Rru concentration for the 18 flasks at the different sampling times. Times are expressed in hours [hh], measured from the time of initial Raz addition to the flasks. Concentrations are expressed in micromol per liter [umol/L]
“RECOVERY_DATA.xlsx” contains data calculated from measured concentrations ("DATASET.xlsx"). Each sheet refers to one experiment. Tables S2-S5 summarizes main results about total recovery (Raz + Rru): for each series (50, 100, 200, 300, 400 ppb) and each sampling time k, we reported:
- the average concentration for the 3 replicates of each series [umol/L];
- the standard deviation of the concentrations associated at the 3 replicates [umol/L];
- the recovery percentage at each sampling time k.
In the last two rows, for each i series, we reported:
- the averaged total concentration [umol/L];
- the variability (standard deviation) associated with the recovery percentages.