Abstract. We explore geographic scaling of metabolism estimates derived from dissolved oxygen measurements with data from 75 sites in three corresponding ecoregions across the temperate steppes of Mongolia and the United States. We used a nested analysis with descending spatial scales (country, ecoregion, river basin, upper or lower watershed, and wide or constrained valleys) to assess spatial heterogeneity. We then linked estimates of metabolism with reach-to-watershed-scale metrics representing geomorphology, topography, climate, and anthropogenic activity to provide possible explanations for spatial scaling dependencies. We evaluated gross primary production (GPP) and ecosystem respiration (ER) at in-situ water temperature and after standardizing them to 20 °C (GPP20 and ER20). There was no significant effect of scaling on ER, and river basin explained only modest variation in GPP. In contrast, GPP20 varied significantly with ecoregion, river basin, basin position (upper vs. lower), and valley morphology (constrained vs. wide). ER20 had no significant spatial predictors. Best regression models for GPP included positive relationships with water velocity and median basin slope and for ER included mean basin air temperature, percentage of urban land use in the basin, and GPP. Best subset regression models for GPP20 included depth, water velocity, and basin slope and for ER20 included depth and mean basin air temperature. The proportion of the watershed in urban or cropland was explanatory of ER, but not GPP. We conclude that fundamental components of ecosystem metabolism respond to different watershed scales and to distinct environmental controls. Thus, macrosystem-scale studies require multi-scale assessment to predict and capture variation in aquatic metabolism. This suggests that universal models of river metabolism are unlikely to perform as well as models built to match the specific scale of inquiry or management.

Climate change profoundly alters riverine flow regimes and community composition, affecting key ecosystem functions. We used an experimental mesocosm approach to examine how gradual flow velocity reduction (Experiment 1) and flushing events (Experiment 2) influence periphyton community composition and metabolism, with and without a macroinvertebrate assemblage. We prepared eight stream mesocosms with pre‐grown periphyton, half including macroinvertebrates. Six mesocosms gradually transitioned from high (0.25 m s −1 ) to low flow velocity (0.05 m s −1 ), followed by three flushing events of increasing frequency (i.e., reducing time between events) and same intensity, raising from 0.05 to 0.25 m s −1 for 6 h before returning to base flow. Two control mesocosms (one with and one without macroinvertebrates) remained at constant flow (0.1 m s −1 ) throughout the experiment. We measured algal biovolume, taxonomic composition, and metabolic rates (gross primary production; ecosystem respiration; net ecosystem production) over time. Macroinvertebrates altered community composition and reduced algal biovolume, with stronger effects at low flow. Flow reduction had scale‐dependent effects: at the chamber scale it lowered periphyton gross primary production and net ecosystem production, while at the whole‐mesocosm scale it decreased ecosystem respiration more than production, increasing net ecosystem production. Flushing events decreased algal biovolume, but enhanced periphyton autotrophy, though this effect weakened with repeated disturbance. Macroinvertebrate assemblages, while reducing total algal biovolume, enhanced the resistance of metabolic responses to flushing. Together, these results show that hydrological variability and macroinvertebrate presence jointly regulate periphyton structure and function and provide mechanistic insight into the processes controlling carbon cycling in running waters.

Terrestrial and aquatic ecosystems are connected through the exchange of nutrients, energy, and organisms. Investigating the spatio-temporal synchronicity (i.e., coupling and decoupling) of Net Primary Productivity (NPP) across these ecosystems is essential for understanding their responses to current and future environmental changes. While tree rings provide a robust proxy for reconstructing terrestrial NPP (TNPP) and its historical fluctuations under varying climatic and environmental conditions, a comparable approach for freshwater ecosystems is hindered by the lack of long-term records of aquatic NPP (ANPP). In this study, we compared annually resolved time series of TNPP, derived from ring-width chronologies of white fir (Abies concolor) and lodgepole pine (Pinus contorta) in the Castle Lake basin (USA), with ANPP records from 1961 to 2020 collected by the long-term ecological research program at the lake. Our analysis focused on identifying patterns of synchronicity between TNPP and ANPP and their climatic drivers across high- and low-frequency domains. Our results revealed a one-year lagged negative effect of TNPP on ANPP, potentially linked to nutrient uptake by vegetation, and a delayed influence of ANPP on TNPP, with a lag of 5–10 years. In the low-frequency domain, we identified a pronounced episode of decoupling (1961–1988), followed by a phase of coupling (1989–2012). These dynamics appear to be driven by contrasting climatic sensitivities: TNPP was negatively influenced by June–July temperatures and drought stress throughout the growing season, whereas ANPP was positively associated with April temperatures and constrained by winter precipitation. This study highlights the value of long-term monitoring in disentangling the complex interactions between terrestrial and aquatic ecosystems. Our research suggests that the response of aquatic and terrestrial ecosystems to climate change might be characterized by complex patterns of synchronicity, highlighting the importance of cross-disciplinary research. Measurements that connect fundamental processes across the terrestrial to aquatic ecosystems are needed to understand the connections between lake, watershed, and climate, particularly given the certain future of warming in the region.

Terminal lakes face conservation challenges due to consumptive water use and changes in climate. We quantified the extent of the littoral and open water zones in 18 terminal lakes spanning five continents and show that lake level declines produce variable changes in littoral zone surface area. While littoral zones account for a small portion of the habitat in these lakes, 77% of the fish species inhabit these zones and 87.5% consume littoral-benthic organisms. We found that littoral zone surface area correlates with littoral zone fish species richness (P < 0.01; R-2 = 0.47) as well as the number of species relying on benthos (P < 0.01; R-2 = 0.44). However, we found (1) no correlation between the percent of the lake's surface area that is littoral and the percent of the fish community that inhabits the littoral zone (Pearson's r = 0.3; P = 0.3), and (2) no correlation between the percent of the lake's surface area that is littoral and the percent of the fish community that consumes benthic organisms (Pearson's r = -0.1; P = 0.8). Because many terminal lakes are desiccating, conservation of biodiversity in the nearshore zones of these lakes may be warranted.

Metacommunity studies have demonstrated that local macroinvertebrate communities are structured not only by local environmental conditions but also by spatial processes. Effective bioassessment tools should account for spatial processes while doing so with the least amount of cost. In this study, we applied variance partition techniques based on redundancy analysis to assess the performance of three sets of benthic invertebrate metrics in detecting agricultural land-use effects in a SE Brazil rainforest watershed. Macroinvertebrate data were analyzed separately regarding their taxonomic, functional structure and bioindicator metrics developed for the study region. We stipulated that groups of metrics most sensitive to land-use effects should have the highest amount of variance explained by the joint effects of land use and environmental variation, independently of spatial structuring. Statistical analyses were repeated removing rare taxa in order to assess the effects of their inclusion in the responsiveness of each group of metrics. Traditional bioindicator metrics were more responsive to environmental variation associated with agriculture than taxa abundances and functional attributes. Furthermore, a few common taxa drove a high proportion of the variation observed in invertebrate communities, regardless of how invertebrate data were organized. Similar analytic approaches have the potential to be useful in curtailing sorting and identification efforts when developing macroinvertebrate-based biomonitoring protocols, especially in areas where information regarding the taxonomy of benthic communities is still poorly described.

Delineating reference (i.e., baseline) riverine nutrient concentrations is essential to understand fundamental processes of biogeochemical transport from continents to the ocean, describe ecological conditions, and inform managers of best attainable conditions when attempting to control anthropogenic eutrophication. We used data from 434 Brazilian watersheds representative of major South American biomes covering over half the continental area, to estimate nutrient levels expected prior to anthropogenic development. We used a novel watershed-based approach to describe spatial patterns throughout Brazil and for the entire Amazon basin. This approach considered nitrogen (N) and phosphorus (P) independently and allowed removal of anthropogenic influences. The approach was useful where there were few unimpacted watersheds and low levels of urbanization had strong effects. We found reference total N concentrations were most closely related to biome, whereas total P levels related to percentage sand in soils in addition to climatic features influencing biomes. There was a wide range of N:P at this coarse level, suggesting P or co-limitation could occur in streams; many areas have intrinsically high background P and relatively low N, suggesting N-limitation of freshwaters could be widespread in South America, favoring nitrogen-fixing cyanobacterial blooms. We provide unique broad-scale analyses of spatial distribution of baseline nutrient levels for tropical and subtropical watersheds across continental scales.

Our study aims to investigate the longitudinal effects of two land-cover transitions on the periphytic algal community. We utilized datasets from three different studies conducted over a 5-year interval in a tropical headwater stream. The studied stream traverses two abrupt adjacent transitions from an upstream forest to a pasture and back to a downstream forest remnant. We performed a high-spatial resolution sampling and used generalized additive models (GAMs) to capture the non-linear gradient response of algal metrics to distance from land-cover transitions. Algal biomass presented a lagged response to increased light availability along the pasture section and decreased along a shorter distance in the downstream forest. Most algal metrics presented a lagged response to transitions, with chlorophyll-a taking up to 375 m to reach the maximum values inside the pasture and up to 300 m to return to reference conditions inside the downstream forest. In the downstream forested section, diatom richness and abundance were similar to the upstream forested section but did not return to reference conditions. The results were consistent across years. Our results indicate that, while riparian forest remnants can play an important role in buffering impacts related to land-cover changes in low order streams, both the magnitude and directionality of these effects might be influenced by longitudinal effects caused by the flow of water. Riparian forest remnants can have a longitudinal effect in stream conditions, influencing environmental characteristics even over non-forested reaches, to where the forest conditions can be propagated downstream by the flow of water.

River flows change on timescales ranging from minutes to millennia. These variations influence fundamental functions of ecosystems, including biogeochemical fluxes, aquatic habitat, and human society. Efforts to describe temporal variation in river flow—i.e., flow regime—have resulted in hundreds of unique descriptors, complicating interpretation and identification of global drivers of flow dynamics. Here, we used a cross-disciplinary analytical approach to investigate two related questions: 1. Is there a low-dimensional structure that can be used to simplify descriptions of streamflow regime? 2. What catchment characteristics are most associated with that structure? Using a global database of daily river discharge from 1988-2016 for 3,120 stations, we calculated 189 traditional flow metrics, which we compared to the results of a wavelet analysis. Both quantification techniques independently revealed that streamflow data contain substantial low-dimensional structure that correlates closely with a small number of catchment characteristics. This structure provides a framework for understanding fundamental controls of river flow variability across multiple timescales. Climate was the most important variable across all timescales, especially those lasting several weeks, and likely contributes as much as dams in controlling flow regime. Catchment area was critical for timescales lasting several days, as was human impact for timescales lasting several years. In addition, both methods suggested that streamflow data also contain high-dimensional structure that is harder to predict from a small number of catchment characteristics (i.e. is dependent on land use, soil structure, etc.), and which accounts for the difficulty of producing simple hydrological models that generalize well.

Quantifying the trophic basis of production for freshwater metazoa at broad spatial scales is key to understanding ecosystem function and has been a research priority for decades. However, previous lotic food web studies have been limited by geographic coverage or methodological constraints. We used compound-specific stable carbon isotope analysis of amino acids (AAs) to estimate basal resource contributions to fish consumers in streams spanning grassland, montane and semi-arid ecoregions of the temperate steppe biome on two continents. Across a range of stream sizes and light regimes, we found consistent trophic importance of aquatic resources. Essential AAs of heterotrophic microbial origin generally provided secondary support for fishes, while terrestrial carbon did not seem to provide significant, direct support. These findings provide strong evidence for the dominant contribution of carbon to higher-order consumers by aquatic autochthonous resources (primarily) and heterotrophic microbial communities (secondarily) in temperate steppe streams.

Supporting dataset for the article: "High rates of daytime river metabolism are an underestimated component of carbon cycling" by Flavia Tromboni, Erin R. Hotchkiss, Anne E. Schechner, Walter K. Dodds, Simon R. Poulson, Sudeep Chandra.

River metabolism and, thus, carbon cycling are governed by gross primary production and ecosystem respiration. Traditionally river metabolism is derived from diel dissolved oxygen concentrations, which cannot resolve diel changes in ecosystem respiration. Here, we compare river metabolism derived from oxygen concentrations with estimates from stable oxygen isotope signatures (δ 18 O 2 ) from 14 sites in rivers across three biomes using Bayesian inverse modeling. We find isotopically derived ecosystem respiration was greater in the day than night for all rivers (maximum change of 113 g O 2 m −2 d −1 , minimum of 1 g O 2 m −2 d −1 ). Temperature (20 °C) normalized rates of ecosystem respiration and gross primary production were 1.1 to 87 and 1.5 to 22-fold higher when derived from oxygen isotope data compared to concentration data. Through accounting for diel variation in ecosystem respiration, our isotopically-derived rates suggest that ecosystem respiration and microbial carbon cycling in rivers is more rapid than predicted by traditional methods.

The distance that a nutrient travels as a solute before its removal from the stream water column is known as the uptake length ( S W ), which is a functional indicator of environmental quality and integrity. Among nutrient enrichment methods, instantaneous nutrient addition (e.g., slug or pulse) have been proposed as an alternative to plateau and labeled nutrient approaches. Two approaches have been commonly used to estimate S W and its associated metrics (i.e., areal uptake rate, U ; and uptake velocity, V f ) from pulse additions: the spiraling approach, based on the longitudinal variation in nutrient concentrations, and the transport modeling approach, based on the advective and dispersive transport of solutes. However, little is known in how the choice of such analytical methods impacts the estimation of stream uptake parameters and the conclusions we draw from them. Here, we estimated the S W and V f of ammonium‐nitrogen (NH 4 ‐N) and soluble reactive phosphorus (SRP) from 16 pulsed additions conducted in four low‐order streams in southeastern Brazil. We compared metrics estimated by the Tracer Additions for Spiraling Curve Characterization (TASCC) and the One‐Dimensional Transport with Inflow and Storage (OTIS) methods, based on the spiraling‐ and transport‐based approaches, respectively. The TASCC:OTIS S W ratio averaged 0.71 for NH 4 ‐N and 1.01 for SRP, whereas the mean of TASCC:OTIS V f ratio was 2.04 for NH 4 ‐N and 1.03 for SRP. The results showed that both S W and V f estimates differed significantly between methods for NH 4 ‐N, but no statistical differences were observed in SRP estimates. In our study, we highlighted the significant effects of transient storage and variable nutrient concentration on pulsed enrichments. Such information should be considered when choosing which method is appropriate to use for a particular site. Differences between modeling approaches must be addressed when comparing methods to expand our knowledge on broad temporal and spatial patterns of in‐stream nutrient uptake.

Establishing reference conditions in rivers is important to understand environmental change and protect ecosystem integrity. Ranked third globally for fish biodiversity, the Mekong River has the world’s largest inland fishery providing livelihoods, food security, and protein to the local population. It is therefore of paramount importance to maintain the water quality and biotic integrity of this ecosystem. We analyzed land use impacts on water quality constituents (TSS, TN, TP, DO, NO3−, NH4+, PO43−) in the Lower Mekong Basin. We then used a best-model regression approach with anthropogenic land-use as independent variables and water quality parameters as the dependent variables, to define reference conditions in the absence of human activities (corresponding to the intercept value). From 2000–2017, the population and the percentage of crop, rice, and plantation land cover increased, while there was a decrease in upland forest and flooded forest. Agriculture, urbanization, and population density were associated with decreasing water quality health in the Lower Mekong Basin. In several sites, Thailand and Laos had higher TN, NO3−, and NH4+ concentrations compared to reference conditions, while Cambodia had higher TP values than reference conditions, showing water quality degradation. TSS was higher than reference conditions in the dry season in Cambodia, but was lower than reference values in the wet season in Thailand and Laos. This study shows how deforestation from agriculture conversion and increasing urbanization pressure causes water quality decline in the Lower Mekong Basin, and provides a first characterization of reference water quality conditions for the Lower Mekong River and its tributaries.

In an era of unprecedented human impacts on the planet, macrosystems biology (MSB) was developed to understand ecological patterns and processes within and across spatial and temporal scales. We used machine‐learning and qualitative literature review approaches to evaluate the thematic composition of MSB from articles published since the 2010 creation of the US National Science Foundation’s MSB Program. The machine‐learning analyses revealed that MSB articles studied scale and human components similarly to six ecology subdisciplines, indicating that MSB has deep ecological roots. A comparison with 84,841 ecological studies demonstrated that MSB has extended the knowledge space of ecology by examining large‐scale patterns and processes alongside anthropogenic factors, which was also confirmed by the qualitative literature review approach. Our analyses indicated that MSB emphasizes large scales, has deep roots in ecological disciplines, and may emerge as a new research frontier, but this last point has yet to be proven.

River metabolism modeled from diurnal dissolved oxygen (DO) has become a widely used metric of ecosystem function, yet many papers provide insufficient methodological detail for replication. Only 79% of 43 sampled papers published from 2015 to 2019 mention calibration, 44% describe sensor placement, and 34% did not describe estimation approaches such that the study could be replicated. Given spatial heterogeneity in rivers influences metabolism, and measurement sensitivities vary with sensor model, it is important to have appropriately detailed information in reported methods along with a fundamental understanding of how river heterogeneity might influence metabolism. We deployed 2–8 sensors at 92 steppe river reaches to characterize site heterogeneity, evaluating how sensor placement and type, deployment length, drift correction, data source, local vs. remotely sensed data, and calibration can affect metabolism estimates. Estimates of gross primary production (GPP) and ecosystem respiration (ER) were inconsistent and unpredictable depending on deployment location within a river reach; GPP and ER rates varied up to 131% and 69%, respectively, across a river width and up to two orders of magnitude within a reach. DO sensor brands vary in precision and accuracy; we found even when operated within stated performance range, estimates of GPP and ER could vary by 82% and 198%, respectively, if not calibrated beyond factory setting, as determined using field data from a sample site. Inaccuracies from sensor drift over weeklong deployments led to an average 48% ER overestimation, and 2% GPP overestimation comparing uncorrected with corrected field data. We suggest best practices for more comparable, precise, representative, and accurate methods.

River flow changes on timescales ranging from minutes to millennia. These variations influence fundamental functions of ecosystems, including biogeochemical fluxes, aquatic habitat, and human socie...

Macrosystems are integrated human–natural systems, in recognition of the fact that virtually every natural system on Earth influences and is influenced by human activities, even over long distances. It is therefore crucial to incorporate inherent properties of broad‐scale systems, such as human–nature connectivity and feedbacks at multi‐scales, into macrosystems biology studies. Here, we propose the “metacoupling” framework as a macrosystems biology approach. This framework incorporates the study of ecological and socioeconomic dimensions and their interactions within, between, and among adjacent and distant locations. We present examples highlighting that (1) human activities are increasing multi‐scale interactions; (2) the increase in frequency and intensity of distant interactions reduces the importance of proximity as a dominant factor connecting systems; and (3) metacoupling generates both ecological and socioeconomic feedbacks, with profound impacts. The metacoupling framework discussed here can advance macrosystems biology, create opportunities for innovative scientific discoveries, and address global challenges.

Abstract River hydrogeomorphology is a major driver shaping biodiversity and community composition. Here, we examine how hydrogeomorphic heterogeneity expressed by Functional Process Zones (FPZs) in river networks is associated with fish assemblage variation. We examined this association in two distinct ecoregions in Mongolia expected to display different gradients of river network hydrogeomorphic heterogeneity. We delineated FPZs by extracting valley‐scale hydrogeomorphic variables at 10 km sample intervals in forest steppe (FS) and in grassland (G) river networks. We sampled fish assemblages and examined variation associated with changes in gradients of hydrogeomorphology as expressed by the FPZs. Thus, we examined assemblage variation as patterns of occurrence‐ and abundance‐based beta diversities for the taxonomic composition of assemblages and as functional beta diversity. Overall, we delineated 5 and 6 FPZs in river networks of the FS and G, respectively. Eight fish species were found in the FS river network and seventeen in the G, four of them common to both ecoregions. Functional richness was correspondingly higher in the G river network. Variation in the taxonomic composition of assemblages was driven by species turnover and was only significant in the G river network. Abundance‐based taxonomic variation was significant in river networks of both ecoregions, while the functional beta diversity results were inconclusive. We show that valley‐scale hydrogeomorphology is a significant driver of variation in fish assemblages at a macrosystem scale. Both changes in the composition of fish assemblages and the carrying capacity of the river network were driven by valley‐scale hydrogeomorphic variables. River network hydrogeomorphology as accounted for in the study has, therefore, the potential to inform macrosystem scale community ecology research and conservation efforts.