A small artificial pond (≈10 m³; 34°41^′14.5^′′ N, 135°49^′45.9^′′ E) in Nara Prefecture, Japan, served as the study site (Fig. ). The pond is surrounded by trees and receives substantial inputs of leaf litter in autumn. The bottom substrate consists primarily of gravel mixed with decomposed leaves, and no aquatic macrophytes are present. Leaf litter was not actively removed during the monitoring period and was left to decompose within and around the pond. Water depth varies spatially, exceeding 40 cm at Site A1 and A0, ranging from 20 to 40 cm at Site B, and remaining below 20 cm at Site C.

The pond is enclosed on three sides by a waterproof mortar structure that prevents lateral inflow or outflow. To promote water circulation, the open peripheral side channel shown in Fig. a was constructed in two stages: an initial manual excavation in August 2022, followed by a larger-scale mechanical excavation in May–June 2023. After channel construction, water was pumped intermittently (daytime only) using a solar-powered system. Pumping volumes measured during 26 August–14 September 2022 averaged 499 L d⁻¹ (range: 124–1300 L d⁻¹). The short-term on/off frequency of the pump was not continuously logged. Following the June 2023 excavation, sediment-laden inflow from freshly disturbed soils was observed to enter the pond (Fig. c).

From July 2022 to March 2024, water-quality monitoring was conducted weekly at four sites (A0, A1, B, and C) using portable instruments. Site A1 was monitored throughout the study period (7 July 2022 to 30 March 2024) as the primary reference site, whereas Sites A0, B, and C were monitored during partially overlapping intervals due to logistical constraints. A follow-up vertical-profile survey was additionally conducted in February 2025 using the same instrument and protocols.

At each site, measurements were taken at two depths (5 cm below the water surface and near the bottom) on a weekly basis. In addition, vertical profiles were obtained at 5 cm intervals from the water surface downward every two weeks. All measurements were performed between 10:00 and 15:00 (local time).

Measured parameters were pH, dissolved oxygen (DO), oxidation–reduction potential (ORP, reported as Eh), electrical conductivity (EC), water temperature, and water depth. pH was measured using a PRN-41 (Fujiwara Scientific Co., Ltd., Japan), and water depth was measured using a measuring stick. DO, ORP, EC, and water temperature were measured using a LAQUA-WQ310 (Horiba Scientific, Japan). The DO optode was model 300-D-2, the ORP electrode was model 9300-10D (reference electrode: 3.33 mol L⁻¹ KCl Ag / AgCl; indicator electrode: Pt), and the EC electrode was model 300-C-2 (sensor head) equipped with a 300-4C-C cartridge. Manufacturer specifications (measurement range, resolution, and stated accuracy/repeatability) for all sensors are summarized in Table . The pH and DO sensors were calibrated before each field survey following the manufacturer’s protocols. The ORP and EC sensors were checked against standard solutions prior to the start of the monitoring period, but were not routinely recalibrated thereafter. Before each survey, electrodes were rinsed with distilled water, gently agitated, and visually inspected for deposits. The same instrument and electrodes were used throughout the monitoring period. All measurements were performed in situ without sample collection to minimize redox alteration during handling. Readings were recorded only after the instrument indicated stabilization, which typically required several minutes and occasionally up to ∼ 20 min.

ORP values were converted to standard hydrogen electrode-based values (mV vs. SHE) using the manufacturer-recommended conversion for a 3.33 mol L⁻¹ KCl Ag/AgCl reference electrode and corrected for temperature: 2Eh(mV)=EAg/AgCl(mV)+206-0.7(T-25), assuming a temperature coefficient of -0.7 mV °C⁻¹ for the Ag / AgCl reference electrode. EAg/AgCl is the measured potential (mV) relative to the Ag / AgCl reference electrode and T is temperature (°C).

DO (mg L⁻¹) was converted to molar concentration using the molar mass of O₂ (31.998 g mol⁻¹), and the resulting concentration was used as a proxy for O₂ activity. The activity of O₂ was approximated by its molar concentration for all analyses, and ln⁡[O2] denotes the natural logarithm (base e). Because ln⁡[O2] requires strictly positive values, DO readings reported as 0.00 mg L⁻¹ were excluded from log-transformed analyses; all values > 0.00 mg L⁻¹ were retained.

To interpret the mechanistic meaning of an observed Eh–species relationship under mixed-potential conditions, we derive when an approximately constant sensitivity of Eh to the logarithm of a species activity can arise.

Eh represents a mixed potential arising from multiple interfacial electrochemical reactions. Under open-circuit conditions, the electrode potential adjusts so that the net interfacial current vanishes due to the balance of partial currents (Eq. ). For each reaction k, the (Nernst) equilibrium potential Ek is defined by ik(Ek)=0 under electrochemical equilibrium and follows the Nernst equation. Assuming that the partial reactions that contribute appreciably to the zero-current balance operate in a near-linear polarization range around their equilibrium potentials, we linearize the partial current about Ek (Appendix ) to obtain 3ik(E)≃Gk(E-Ek), where Gk≡(∂ik/∂E)E=Ek is the local polarization conductance of partial reaction k, defined as the slope of the partial current–potential curve near Ek; equivalently, Gk is the reciprocal of the local polarization resistance. Substituting this into the zero-current condition yields 4Emix=∑kGkEk∑kGk.

Thus, within the linear polarization regime, the mixed potential is a conductance-weighted average of the equilibrium potentials of the contributing reactions.

We emphasize that this near-linear approximation concerns the interfacial current–potential response at the electrode surface and does not imply environmental steady state or geochemical equilibrium of the pond as a whole. The surrounding water column, microbial activity, transport, and redox-species distributions may vary dynamically; such variation is reflected in changes in the effective equilibrium potentials Ek, conductances Gk, and their relative weights.

We next differentiate Eq. () with respect to x=ln⁡ax. Defining normalized conductance weights as wk=Gk/∑jGj (so that ∑kwk=1), we obtain 5∂Emix∂x=∑kwk∂Ek∂x+∑kwk(Ek-Emix)∂ln⁡Gk∂x.

Equation () decomposes the sensitivity into (i) a weighted sum of Nernst contributions, through ∂Ek/∂x, and (ii) a reweighting contribution that arises when the relative polarization conductances, and hence the relative contributions of the partial reactions, change with x. The second (reweighting) term is suppressed when the relative conductance weights are nearly invariant with x over the range of interest, i.e., when ∂ln⁡Gk/∂x is approximately common across the contributing reactions (equivalently, wk varies weakly with x). In that case, Eq. () reduces to 6∂Emix∂x≈∑kwk∂Ek∂x.

In the limiting case where a single reaction dominates the polarization conductance (wd≃1), the mixed potential approaches its equilibrium potential (Emix≃Ed) and ∂Emix/∂x≃∂Ed/∂x. From the Nernst equation, ∂Ed/∂ln⁡ax is set by (RT/ndF) multiplied by the stoichiometric coefficient of x in the reaction quotient (with the sign determined by whether x appears as an oxidant or reductant), yielding an approximately constant log-linear sensitivity. Importantly, Eq. () also shows that an approximately constant Eh sensitivity to ln⁡ax does not require single-couple dominance. It can equally reflect a multi-reaction mixed potential whose effective reaction set and relative weights remain approximately stable. Accordingly, an approximately consistent species–Eh slope can be interpreted as evidence that the effective redox-reaction set contributing to the mixed potential, and its relative weighting, remained broadly stable over the range of interest. Conversely, a systematic deviation from this slope points to disturbance-driven reorganization of the interfacial redox contributions sensed by the electrode, rather than a direct signature of the Nernst potential of a single redox couple.

We tested this interpretation using a shallow pond time series that experienced a clearly documented disturbance associated with channel excavation. Such a disturbance can affect not only oxygen availability and measured Eh, but also the effective mixed-potential response near the electrode and thereby disrupt the ln⁡[O2]–Eh relationship. We used electrical conductivity (EC) as a proxy for the excavation-related physical disturbance because sediment mobilization and the exposure of fresh mineral surfaces can enhance ion release via accelerated weathering, producing detectable EC anomalies . The EC anomaly was therefore used as an operational basis for defining pre- and post-disturbance regimes against which changes in the ln⁡[O2]–Eh relationship were evaluated.

Following the mechanical excavation of the circulation channel in May–June 2023, EC exhibited a synchronous and pronounced increase across all monitoring sites (A1, A0, B, and C; Fig. a). Because monitoring began in July 2022, we cannot fully assess whether EC showed a recurring early-summer increase in the previous year (e.g., due to evapoconcentration during warm and dry periods). Nevertheless, EC during June–August 2023 clearly exceeded the pre-disturbance reference range: values were above the pooled pre-disturbance mean and outside the mean ± 1.96 SD range calculated from all EC observations at all sites before the completion of the excavation works (7 July 2022–7 June 2023). The largest increase was observed at Site A1, which was more directly exposed to the circulation pathway and sediment-laden inflow than Site A0, whereas the response at Site A0 was less pronounced, consistent with partial hydrodynamic shielding by the pond geometry rather than a difference in water depth (Fig. a). Thereafter, EC declined and returned to the baseline range within approximately three months. Overall, the EC record suggests a three-phase trajectory consisting of disturbance onset, transient amplification, and subsequent relaxation.

To objectively identify the timing of disturbance onset, we applied change-point detection to the weekly EC time series using a two-segment Gaussian likelihood model, where each segment has its own mean and variance. For each candidate change point tchange, we computed the joint log-likelihood of the EC observations by fitting the model separately to the pre- and post-change segments. Because Sites B and C include substantial data gaps after the disturbance period, which can introduce spurious likelihood maxima, the change-point analysis was performed for Site A1 only (the primary reference site) and for the mean EC series across Sites A1 and A0, yielding consistent likelihood profiles (Fig. b). Local maxima in the likelihood profile were identified using the FindPeaks function in Wolfram Language (Mathematica 12.0; Wolfram Research, Champaign, IL, USA).

The global maximum of the likelihood corresponded to a change point separating the amplification phase from the subsequent relaxation phase (Fig. b). A second prominent peak coincided with the completion date of the channel excavation works (7 June 2023), indicating the transition from baseline conditions to the disturbance-driven EC increase. Because our primary objective is to define the onset of disturbance, we adopt this second peak as the operational change point and refer to the period prior to this date as the pre-disturbance regime and the subsequent period as the post-disturbance regime.

Dissolved oxygen (DO) tended to increase during the latter part of the post-disturbance regime relative to the same season in the previous year (Fig. c). This pattern may reflect multiple processes, including enhanced air–water gas exchange and vertical exchange associated with inflow/pumping events, as well as biological oxygen production and consumption. Over the same period, Eh exhibited an overall upward shift following the disturbance (Fig. d). Notably, during the pre-disturbance period Eh often showed vertical separation between surface and bottom waters, whereas this vertical divergence became less pronounced after the disturbance, consistent with enhanced vertical mixing.

Temperature, which can influence oxygen solubility and biological activity, showed typical seasonal cycles and vertical structure over the observation period, while pH ranged from 5.79 to 7.35 (mean 6.60) (Fig. ).

For the analyses below, DO was converted to molar concentration and used as a proxy for O₂ activity; ln⁡[O2] denotes the natural logarithm (base e). Because ln⁡[O2] is defined only for strictly positive values, DO records reported as 0.00 mg L⁻¹ were excluded from log-transformed analyses (see Methods for details).

During the pre-disturbance regime, a moderate positive relationship between ln⁡[O2] and Eh was consistently observed across sites (pooled regression: Eh=0.085ln⁡[O2]+1.18; adjusted R2=0.44; Fig. a). Site-specific slopes varied within a narrow range (0.072–0.104), and adjusted R2 values were 0.46–0.52, with the highest value at Site A1 (Table ). Despite strong seasonal variability in temperature and oxygen availability, the pre-disturbance data therefore exhibit a broadly consistent ∂Eh/∂ln⁡[O2] across sites, consistent with a relatively stable effective redox-reaction structure over this period.

When the full observation period was considered, the ln⁡[O2]–Eh relationship at Site A1 weakened. The adjusted R2 decreased by 0.153 relative to the pre-disturbance regression, indicating a loss of explanatory power. Site A1 is located closest to the inflow pathway and was most strongly affected by the sediment-mobilizing disturbance, suggesting a disturbance-driven modification of local redox conditions. Consistently, the slope at Site A1 decreased from 0.104 (pre-disturbance) to 0.067 (post-disturbance). Moreover, many post-disturbance observations at Site A1 lay above the 95 % prediction interval of the pre-disturbance regression, indicating a systematic elevation of Eh relative to the expected ln⁡[O2]–Eh relationship.

Enhanced vertical mixing after disturbance could reduce surface–bottom Eh separation and thereby shift the observed relationship. However, the persistence of elevated Eh even under low O₂ conditions suggests that the change is unlikely to be explained solely by physical mixing, indicating an altered sensitivity of Eh to oxygen availability following redox-network reconfiguration. Importantly, a follow-up vertical-profile survey in February 2025 showed that the pre-disturbance ln⁡[O2]–Eh relationship at Site A1 partially re-emerged (orange points in Fig. a), suggesting gradual recovery of the pre-disturbance redox structure.

To quantify deviations from the pre-disturbance system-level relationship, we computed residuals ΔEh=Ehobs-Ehpred,pooled, where Ehpred,pooled is the value predicted from the pooled pre-disturbance regression (Fig. b). Site A1 showed a pronounced positive shift in ΔEh after disturbance, with the largest deviation occurring approximately three months after the EC peak. To compare pre- and post-disturbance residuals, we used a two-sample Student’s t-test when residuals were approximately normally distributed with no strong evidence of unequal variances (Sites A0 and C); otherwise we used the nonparametric Mann–Whitney U test (Sites A1 and B). Significant differences were detected at Sites A1 and A0 (p<0.05), whereas Sites B and C showed no significant difference, partly reflecting reduced sampling frequency after October due to logistical constraints.

Field observations showed a relatively stable ln⁡[O2]–Eh relationship during the pre-disturbance regime across sites, followed by a disturbance-associated weakening and reorganization of the relationship, most clearly at Site A1 where sediment-laden inflow was strongest (Fig. a). Here we interpret these patterns in terms of mixed-potential control and clarify what is inferred from an observed ln⁡[O2]–Eh slope.

In the linearized mixed-potential framework (Eq.  with x=ln⁡aO2), the sensitivity ∂Eh/∂ln⁡aO2 reflects two components: a multi-reaction Nernst contribution through ∂Ek/∂ln⁡aO2 and a contribution from changes in the relative conductance weights of the reactions that collectively form the mixed potential. Importantly, an approximately constant ln⁡[O2]–Eh slope does not require that Eh be controlled by a single redox couple; it is also consistent with a multi-reaction mixed potential whose effective set of contributing reactions and their relative weights remain approximately invariant over the range of oxygen variability. Conversely, a change in slope indicates that the effective reaction set and/or its relative weighting has been reorganized, i.e., oxygen-related electron-transfer pathways have been reweighted relative to other concurrent pathways.

The ln⁡[O2]–Eh relationship at Site A1 can be translated into mixed-potential terms as follows. A weakened slope suggests a reduced relative weighting of oxygen-coupled interfacial pathways (or an increased contribution of competing pathways), so that changes in oxygen activity produce a smaller shift in the conductance-weighted balance that sets Emix. A systematic positive shift in ΔEh at a given ln⁡[O2] indicates an upward displacement of the mixed-potential baseline, consistent with a reweighting and/or replacement of the effective reaction set toward higher equilibrium-potential contributions under otherwise comparable oxygen levels. The lagged peak in ΔEh after the EC anomaly relaxed implies that this reorganization persisted beyond the transient ionic-strength/turbidity perturbation, pointing to a slowly evolving internal state that continued to modulate the reaction weights. The partial recovery observed in February 2025 is consistent with gradual re-establishment of the pre-disturbance effective reaction set and its relative weights.

Within Eq. (), such slow evolution can act through gradual changes in partial polarization conductances and thus in reaction weights, for example via sediment-associated redox buffering, evolving availability of redox-active solutes, and progressive re-establishment of pre-disturbance reaction pathways . In the next section, we examine this possibility using a minimal model that isolates the role of slowly varying reaction weights.

We note that electrode-related effects cannot be fully excluded because routine external calibration was not performed. However, the shift showed coherent timing with the documented disturbance, a spatial structure (A1 > A0), and partial recovery in the follow-up profile survey. These features are difficult to reconcile with a simple monotonic sensor-drift scenario and instead support our interpretation that the observed changes primarily reflect system-level reorganization of the interfacial redox processes supplying electrons to the electrode.

Building on the mixed-potential interpretation above, we introduce a minimal timescale-separation model to illustrate how a change in the apparent ln⁡[O2]–Eh slope can emerge with a delay relative to a fast physical disturbance signature. The model reduces Eq. () to two effective branches: an oxygen-sensitive branch and an oxygen-insensitive high-potential branch, whose relative weight varies slowly in time. This toy model is intended to demonstrate mechanistic plausibility (timescale-separated re-weighting under mixed-potential control), rather than to simulate the observed patterns.

We decompose the dynamics into (i) fast oxygen forcing, representing seasonal and short-period fluctuations in O2 (Fig. a), and (ii) a slow internal state variable, s(t), representing a pulse-like disturbance and its lingering effect that controls how strongly oxygen-dependent reactions contribute to the mixed potential (Fig. b). Here, s denotes a latent (unobserved) state variable representing slow changes in the near-electrode redox environment that modulate the relative contributions of interfacial reactions (i.e., Gk), rather than a directly measured chemical species.

The Eh dynamics are represented as follows: 7Eh(t)=(1-w(s))EO2(t)+w(s)EH,w(s)=GH(s)GO2+GH(s), where EO2(t) follows a Nernstian dependence, 8EO2(t)=EO20+γln⁡[O2(t)], whereas EH is assumed insensitive to oxygen on the timescale of interest. The weight factor w(s) increases with a slow latent state s(t) (e.g., through a logistic dependence of GH on s), so that larger s increases the contribution of the high-potential branch (the specific functional form and parameters are given in the Appendix ).

The slow variable evolves as 9dsdt=-s-s0τ+u(t), where u(t) represents a pulse-like disturbance forcing and τ is a relaxation timescale that is long relative to oxygen fluctuations.

This minimal structure yields two key behaviors that mirror our field patterns (Fig. c, d). First, the instantaneous slope with respect to oxygen is 10∂Eh∂ln⁡[O2]=γ(1-w(s)), so that an increase in w(s) produces a reduced apparent ∂Eh/∂ln⁡[O2] slope (Fig. d). Second, when w(s) becomes large, Eh can remain high even when O2 is low (Fig. b, c), because the high-potential branch dominates the mixed potential. Because s evolves slowly, both the slope reduction and the elevated-Eh residuals can persist and peak after fast disturbance indicators (such as EC) have subsided. Thus, the delayed emergence of the A1 residual shift is consistent with a gradual reconfiguration of the effective redox reaction network.

DO is a common target of routine monitoring in aquatic systems, partly because it is directly linked to key ecological processes such as organic-matter degradation and community structure . In contrast, Eh has been used far more selectively, despite the growing availability of robust, field-deployable electrodes suitable for long-term deployment . Our results show that neither DO nor Eh alone provides an indicator of system-level redox-network stability, whereas their joint behavior can provide a compact diagnostic of redox-structural change.

In this study, we propose two complementary metrics based on the co-located 21-month DO and Eh measurements. First, the stability (or breakdown) of the ln⁡[O2]–Eh slope serves as an indicator of whether the effective reaction set contributing to the mixed potential remains structurally invariant. Second, baseline-referenced residuals (here, ΔEh=Ehobs-Ehpred, with Ehpred computed from the pooled pre-disturbance regression; Fig. b) provide a practical measure of departures from the system-level relationship. Together, these metrics provide a practical way to identify departures from a site-specific DO–Ehbaseline that are consistent with disturbance-induced changes in effective redox conditions and subsequent recovery, using instrumentation that is already routinely deployed.

At the same time, the mixed-potential nature of Eh imposes clear limits on interpretation. Because multiple combinations of interfacial pathways can yield the same electrode potential, co-monitoring DO and Eh cannot identify the dominant redox couple(s), resolve aqueous speciation, or quantify individual reaction fluxes without complementary measurements of redox-active species. Furthermore, the proposed DO–Eh approach is not intended to imply that dissolved oxygen universally controls Eh. Its applicability is limited to settings where oxygen is present and variable enough for a DO–Eh relationship to be evaluated. In oxygen-depleted or strongly reducing environments, other redox-active systems may dominate the mixed potential, and complementary measurements of redox-active species would be needed to identify the underlying processes.

Because the present study was conducted in a small constructed pond, generalization to larger and more complex aquatic systems should be made cautiously. In lakes, rivers, and reservoirs, stratification, advective transport, sediment–water exchange, lateral inputs, and spatial heterogeneity may produce multiple DO–Eh regimes within the same system. Application of the proposed approach to such environments would require site-specific baseline characterization, careful spatial design of co-located DO and Eh measurements, and, where possible, complementary measurements of redox-active species.

DO–Eh co-monitoring is therefore best viewed not as a substitute for comprehensive geochemical characterization, but as a low-cost screening-level approach for detecting departures from a site-specific DO–Eh baseline that may indicate changes in effective redox conditions or in the relative contributions of redox-active processes.