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Toxoplasma gondii, a parasitic protozoan, may infect most warm-blooded animals, including humans and carnivores. Our study focused on alien-invasive American minks (Neogale vison) and domestic cats (Felis catus) in the Valdivian Temperate Rainforest, Chile. The main goal was to investigate the relationship between their dietary habits and T. gondii exposure in the Valdivia River watershed. To detect T. gondii exposure, blood serum samples from 49 domestic cats and 40 American minks were analyzed using an ELISA, and stable isotope analysis of 815N and 813C from vibrissae was performed to determine the dietary habits of both species. Relationships between T. gondii exposure and dietary habits were explored using generalized linear mixed-effects models. American minks that were T. gondii seropositive exhibited a broader prey range compared to seropositive domestic cats, with minimal dietary overlap between the two groups. Exposure of domestic cats to T. gondii had no significant association with any isotope value or prey item in their diet. In American minks, we found a positive and significant association between the proportion of Domestic chicken (Gallus gallus domesticus) in the diet and high 815N values with T. gondii exposure. This suggests that domestic species prey related to anthropogenic areas, and the consumption of high- trophic-level prey, may contribute to T. gondii exposure in American minks. Conversely, contrary to previous hypotheses, consumption of rodents showed no significant association with T. gondii exposure in either species. Our findings emphasize the importance of further research to investigate trophic interactions in the transmission dynamics of T. gondii in the Valdivian Temperate Rainforest. [ABSTRACT FROM AUTHOR]

Understanding the spatial distribution and sources of sedimentary organic matter (OM) in coastal environments is crucial for effective water quality management and the preservation of ecosystem health. Although extensive research has been conducted on OM dynamics, there remains a gap in understanding the ongoing biogeochemical processes in Korean coastal aquaculture zones, particularly during the summer season. To address this gap, we investigated the spatial variation of water chemical properties and isotopic composition of sedimentary OM to trace the composition, source, and reactivity of mixed OM in aquaculture systems along the Korean coast during the summer season. The isotopic approach was applied to surface sediments from five sections: western (W)-1, W-2, southern (S)-1, S-2, and eastern (E)-1. With respect to increased nutrients (mainly nitrate; 1.2 ± 0.6 mg/L) by dam-water discharge near W sections, our isotopic signatures revealed that a substantial fraction of sedimentary OM might dominantly originated from autochthonous OM source (algae; 36.5%) related to the increase of terrestrial nutrients. Simultaneously, the deposition of allochthonous OM (aquacultural feces; 44%) was predominant in the S-2 sections. The 34S-depleted patterns (approximately -7.2‰) in the S-2 section was indicative of active sulfate reduction occurring at the sedimentary boundary. Therefore, together with the precise determination of ongoing OM, our isotopic results provide valuable insights for effectively managing water-sedimentary qualities under the increase of anthropogenic contamination.

Elucidating the seasonal patterns of water sources for dominant species in the sub-tropical humid mountainous forest, analyzing the eco-hydrological complementarity and competition mechanisms among coexisting species, investigating the responses of plant water utilization to precipitation, could provide a theoretical basis for vegetation restoration and management. Based on the stable hydrogen and oxygen isotope technique, we analyzed the δ²H and δ18O characteristics of precipitation, xylem water from Pinus massoniana and Quercus variabilis, and soil water from 0-100 cm depth in Mount Lushan, China. The MixSIAR model, Levins index, and PS index were used to calculate the relative contribution rate of each water source, the hydrological niche breadth, and niche overlap of P. massoniana and Q. variabilis. The results showed that, in the wet season (March to July), P. massoniana primarily utilized soil water from the 0-20 cm and 20-40 cm depths, while Q. variabilis primarily utilized that from the 20-40 cm and 40-60 cm depths. During the dry season (August to September), P. massoniana and Q. variabilis utilized 40-60 cm and 60-80 cm of soil water, respectively, resulting in an increase in the depth of water absorption. In the early growing season ( March to April) and the late growing season ( September), there was a high hydrological niche overlap between P. massoniana and Q. variabilis, resulting in intensitive water competition. In the middle of the growing season ( May to August), the water source was adequately allocated, and the hydrological niche was segregated to meet the high transpiration demand. Q. variabilis primarily utilized soil water from a depth of 60-80 cm and 60-80 cm before a precipitation event, and from a depth of 0-20 cm and 20-40 cm after the event. In contrast, P. massoniana primarily utilized soil water from a depth of 0-20 cm and 20-40 cm both before and after a precipitation event. In conclusion, water utilization patterns of P. massoniana and Q. variabilis exhibited a seasonal trend, with shallow water uptake during the rainy season and deep water uptake during the dry season. These species are capable of efficiently allocating water resources during the peak growth season, and their root systems actively respond to change in soil moisture level. They have strong adaptability to extreme precipitation events and exhibit remarkable water conservation capabilities. [ABSTRACT FROM AUTHOR]

The aquatic ecosystem is essential for human survival and development. Food web studies on aquatic ecosystems describe many key processes, such as material cycling and energy flow processes. The results are of great significance for protecting the diversity, stability, and functionality of biological and ecological systems. However, the extreme complexity of aquatic ecosystem food webs has puzzled ecological researchers. The development of stable isotope technology has contributed significantly to our understanding of intricate feeding relationships and structure of food webs. The carbon and nitrogen-stable isotope compositions of animal tissues are closely related to their food sources, reflecting the comprehensive characteristics of all food isotopic compositions assimilated over a period of time by animal tissues. The carbon isotope composition of animals can indicate their food source, while the nitrogen-stable isotope composition can reflect the trophic structure. However, the animal diet is not composed of a single food source, and the complexity and unpredictability of food sources complicate the interpretation of carbon and nitrogen-stable isotope data regarding the contribution of food sources. In recent years, the rapid development of stable isotope mixing models (SIMMs) has provided a powerful means to solve the complexity of aquatic food webs, particularly with regard to determining the contribution of food sources and comparing consumer niches.In this study, we reviewed the historical evolution of stable isotope models, the characteristics of the most prominent models, and factors to consider when utilizing such models. This study summarized the application prospects and limitations of stable isotope mixing models in the research field of aquatic ecosystem food webs in order to provide a reference and scientific basis for subsequent research.The development of stable isotope models can roughly be divided into three stages: the early initial stage (1976–2001), which mainly involved the development of linear models; the supplementary stage (2001–2008), during which numerous uncertain factors were added to the model analysis as a result of the advancement of computer technology; the Bayesian mixed model stage (2008–current). The mixed model stage is based on mass conservation, and the Bayesian framework greatly improves the accuracy and credibility of model analysis. Simmr, MixSIAR, and SIBER have become the primary isotope models used today.Stable isotope technology has a long history of development, and the emergence of various stable isotope models has expanded the application of isotope technology in the research field of food webs. These models have powerful analytical capabilities and provide researchers with a powerful means for analyzing the structure of the food web. However, owing to the limitations of isotope analysis and models, researchers should pay more attention to the relevant prerequisites and practical ecological significance when selecting models to analyze isotope data. Researchers should also devise reasonable field investigation and experimental treatment plans based on their own experimental conditions and economic capacity in order to avoid the error analysis and misuse of isotope models and reduce the uncertainty of model analysis results as much as possible.Based on the previous research progress, the authors share their experience and understanding of the application of isotope mixing models. The purpose of this study was to assist fellow researchers in quickly understanding the development process and matters requiring the attention of isotope models, as well as to provide fundamental data and theoretical support for related research.

Food webs are complex ecological networks that reveal species interactions and energy flow in ecosystems. Prevailing ecological knowledge on forested streams suggests that their food webs are based on allochthonous carbon, driven by a constant supply of organic matter from adjacent vegetation and limited primary production due to low light conditions. Extreme climatic disturbances can disrupt these natural ecosystem dynamics by altering resource availability, which leads to changes in food web structure and functioning. Here, we quantify the response of stream food webs to two major hurricanes (Irma and María, Category 5 and 4, respectively) that struck Puerto Rico in September 2017. Within two tropical forested streams (first and second order), we collected ecosystem and food web data 6 months prior to the hurricanes and 2, 9, and 18 months afterward. We assessed the structural (e.g., canopy) and hydrological (e.g., discharge) characteristics of the ecosystem and monitored changes in basal resources (i.e., algae, biofilm, and leaf litter), consumers (e.g., aquatic invertebrates, riparian consumers), and applied Layman's community‐wide metrics using the isotopic composition of 13C and 15N. Continuous stream discharge measurements indicated that the hurricanes did not cause an extreme hydrological event. However, the sixfold increase in canopy openness and associated changes in litter input appeared to trigger an increase in primary production. These food webs were primarily based on terrestrially derived carbon before the hurricanes, but most taxa (including Atya and Xiphocaris shrimp, the consumers with highest biomass) shifted their food source to autochthonous carbon within 2 months of the hurricanes. We also found evidence that the hurricanes dramatically altered the structure of the food web, resulting in shorter (i.e., smaller food‐chain length), narrower (i.e., lower diversity of carbon sources) food webs, as well as increased trophic species packing. This study demonstrates how hurricane disturbance can alter stream food webs, changing the trophic base from allochthonous to autochthonous resources via changes in the physical environment (i.e., canopy defoliation). As hurricanes become more frequent and severe due to climate change, our findings greatly contribute to our understanding of the mechanisms that maintain forested stream trophic interactions amidst global change. [ABSTRACT FROM AUTHOR]

Nitrate (NO3–) contamination of surface water is a global environmental problem that has serious consequences for watershed ecosystems and endangers human health. It is crucial to identify influences of different sources of NO3−, especially the incoming water from upper reaches. A combination of hydrochemistry and multi-isotope tracers (δ11B, δ15N-NO3−, and δ18O-NO3–) were used to determine NO3– sources and their transformation the North Jiulong River (NJLR), Southeast China. The findings revealed that NO3–, which accounted for an average of 87.1% of dissolved inorganic nitrogen (DIN), was the main chemical form of nitrogen species. The integration of dual stable isotopes of NO3−, δ11B, and hydrochemistry showed that NO3– was primarily contributed by sewage, soil nitrogen (SN), and ammonium (NH4+) via precipitation or fertilizers. The contributions from the sewage and soil nitrate source were almost equivalent and much higher than those from other sources in the NJLR watershed. The contributions from diverse sources varied seasonally and spatially. Manure and sewage (M&S) were the leading sources in the summer and autumn, accounting for 60.9 ± 8.5% and 47.3 ± 7.9%, respectively. However, NO3− fertilizers were the predominant source in the spring and winter. The NO3− inflow from upper reaches was proposed as an additional end-member to identify its contribution in the midstream and downstream in this study. The contributions of NO3− from the upper reaches were significant sources in the midstream and downstream, accounting for 27.2 ± 17.8% and 42.9 ± 21.9%, respectively. The obvious decline in local NO3−contribution shares from midstream to downstream implied structural changes in pollutant sources and regional environmental responsibility. Therefore, tracing nitrate sources and quantifying their contributions is critical for clarifying environmental responsibilities for precise local nitrogen management in watersheds.

Sediment is an important carrier of evidence about environmental evolution which receives huge volumes of organic material originated from both anthropogenic and natural sources. In this study, based on sedimentary chronology, the vertical trends of particle size distribution, total organic carbon (TOC), total nitrogen (TN), and their stable isotopes (δ13C, δ15N) in the sediment core of the nuclear power sea in southwest Daya Bay were analyzed, and the distribution characteristics and contribution ratios of different sources of organic matter in the sedimentary environment over the past 70 years were resolved using a Bayesian mixing model (MixSIAR). TOC, TN, δ13C, and δ15N ranged from 0.89 to 1.56%, 0.09 to 0.2%, − 22.3 to − 20.6‰, and 4.38 to 6.51‰, respectively. The organic matter in the sediment is controlled by a mixture of terrestrial input and marine autochthonous, the proportion of organic matter from terrestrial sources increases, while that from marine sources decreases in the sediment core, which persists from 1960 to 2000, yet organic matter from marine sources still dominates. The first signs of increased primary productivity occurred in 1960, and it was primarily due to agricultural activity. After the 1980s, the rapid increase in population around Daya Bay, the construction of nuclear power plants, the rise of aquaculture, and the quick expansion of industrial bases were all major factors that changed the ecological environment of Daya Bay. [ABSTRACT FROM AUTHOR]

Xylem water isotopic compositions (2H, 18O; δXYLEM) can be used to estimate plant water uptake depths; however, environmental heterogeneity in these measurements may prevent reaching robust conclusions. Bayesian mixing models used to estimate plant water uptake depths often assume that measurements of δXYLEM and candidate water uptake sources are normally and identically distributed. We tested if δXYLEM measured across 30 Eastern hemlock (Tsuga canadensis (L.) Carrière) trees met these assumptions. Bootstrap simulations suggested that the distributions of hemlock δXYLEM data were non‐normal in March, April, June, and July and that between 15 and 26 hemlock δXYLEM samples were required to reject the assumption of normality. In June, July, and August, δXYLEM was significantly predicted by a multivariate linear regression with tree sapwood depth or elevation, rejecting the assumption of independently distributed observations. A comparison of dry season hemlock water uptake depth estimates between a Bayesian mixing model and a process‐based ecohydrological model calibration showed differences, with the Bayesian model estimating a substantially greater proportion of shallow water uptake. These results highlight the need for standardized field sampling protocols for δXYLEM and analytical methods that will lead to more robust estimates of plant water uptake depths. These findings also suggest that water uptake functions conditioned on landscape and tree structural variables could substantially advance the representation of plants in ecohydrological models. [ABSTRACT FROM AUTHOR]

The notion that closely related species resemble each other in ecological niche space (i.e., phylogenetic dependence) has been a long-standing, contentious paradigm in evolutionary biology, the incidence of which is important for predicting the ecosystem-level effects of species loss. Despite being examined across a multitude of terrestrial taxa, many aspects of niche conservatism have yet to be explored in marine species, especially for characteristics related to resource use and trophic behavior (Eltonian niche characteristics, ENCs). We combined ENCs derived from stable isotope ratios at assemblage- and species-levels with phylogenetic comparative methods, to test the hypotheses that benthic marine fishes (1) exhibit similar assemblage-wide ENCs regardless of geographic location and (2) display phylogenetically dependent ENCs at the species level. We used a 12-species sub-set of the monophyletic group Rajidae sampled from three independent assemblages (Central California, Gulf of Alaska, and Northwest Atlantic), which span two ocean basins. Assemblage-level ENCs implied low trophic diversity and high evenness, suggesting that Rajidae assemblages may exhibit a well-defined trophic role, a trend consistent regardless of geographic location. At the species level, we found evidence for phylogenetic dependence of ENCs relating to trophic diversity (i.e., isotopic niche width; SEAc). Whether individuals can be considered functional equivalents across assemblages is hard to ascertain because we did not detect a significant phylogenetic signal for ENCs relating to trophic function (e.g., trophic position). Thus, additional, complimentary approaches are required to further examine the phylogenetic dependence of species functionality. Our approach illustrates the potential of stable isotope-derived niche characteristics to provide insight on macroecological processes occurring across evolutionary time, which could help predict how assemblages may respond to the effects of species loss.

Nitrate (NO3−) contamination threatens the quality of groundwater in many agricultural areas, and excessive NO3− consumption may cause adverse human health implications. Determination of NO3− occurrence and its source of contamination is essential for the effective management of groundwater quality. The characteristics of NO3− in groundwater from the Anayari Catchment were analysed using hydrogeochemical and stable isotope data. Concentrations of major ions and the isotopic values of δ2H, δ18O, δ15N–NO3− and δ18O–NO3− of groundwater and δ15N–NO3− and δ18O–NO3− of potential NO3− source materials (precipitation (P), chemical fertilisers (CF), soil nitrogen (SN), and sewage or manure (S/M)) in the area were determined and used to identify groundwater NO3− sources. The Bayesian mixing model was applied to estimate the proportional contributions of NO3− load in boreholes (BH) and hand–dug wells (HDW) in the Catchment. The NO3− levels were mostly lower than the WHO guideline limit. Correlation analyses indicate that the source of NO3− was mostly livestock and septic waste. The results from δ15N–NO3− and δ18O–NO3− showed that the contribution of NO3− from potential sources is in the order of S/M > SN > CF > P, with denitrification influencing the NO3− concentration in some of the groundwater sources. The Bayesian mixing model demonstrated that by proportion, SN and S/M were the major NO3− contributors to BH and HDW, respectively. There is a need to institute and enforce proper manure application management strategies to reduce the risk of groundwater contamination from manure nutrients. [ABSTRACT FROM AUTHOR]

Clarifying the water uptake patterns and competition among riparian plants under different ecological water conveyance conditions is crucial for the stability of the riparian ecosystem in arid areas. Here, we have utilized the Bayesian isotope mixing model to quantify the plant water sources for two typical riparian plants (Tamarix ramosissima and Phragmites australis) along the Manas River in Xinjiang, Northwest China. The water competition relationship between these two typical riparian plants is evaluated using the proportional similarity index (PSI). Our findings demonstrated the following: (1) The climate in the study area is dry and strongly evaporative, and the slope and intercept of the local meteoric water line are smaller than the global meteoric water line. The interconversion between surface water and groundwater occurred mainly in the upper reaches of the river. (2) At the sample site with the long-term ecological water conveyance, the water uptake pattern for typical riparian plants is predominantly shallow soil water or the uniform use of potential water sources. Among them, the utilization rate of shallow soil water reached 30.7 ± 12.6%. At sample sites with intermittent ecological water conveyance and the non-ecological water conveyance sample site, the growth of T. ramosissima and P. australis primarily uses deep soil water and groundwater, with mean values of 34.5 ± 5.1% and 32.2 ± 1.9%, respectively. (3) The water competition between plants at the intermittent ecological water conveyance and non-ecological water conveyance sample sites was more intense. However, the long-term ecological water conveyance effectively reduced water competition among plants. Our results will provide basic theoretical support for maintaining the stability of the Manas River riparian ecosystem and determining environmental flows. [ABSTRACT FROM AUTHOR]

Despite their seemingly watery constitution, jellyfish are eaten by a diverse range of predators. However, while the role of jellyfish in marine food webs is gaining attention, the nutritional value of these gelatinous organisms and how it varies remain poorly understood. In this study, we aimed to connect jellyfish food web biology and nutrition by determining the relationship between jellyfish size, diet, and nutritional quality. We measured stable isotope (SI) and fatty acid (FA) profiles of particulate organic matter (POM), plankton size classes, and gelatinous zooplankton collected from a coastal site in British Columbia, Canada, in July and September 2019. Gelatinous zooplankton comprised 152 Aurelia labiata collected across both months (bell diameters = 19–225 mm), and 2 Aequorea victoria and approximately 30 Pleurobrachia bachei collected in July for comparison. According to FA trophic markers and chlorophyll a concentrations, the POM was a mix of phytoplankton, microzooplankton, bacteria, and detritus. According to δ15N, POM was ~1 trophic level lower than plankton. All gelatinous zooplankton had low FA content (5–6 μg/mg dry mass) compared with zooplankton (43–65 μg/mg dry mass). A Bayesian mixing model (MixSIAR) was used to assess the contributions of POM and plankton to A. labiata diet, which demonstrated a size‐based shift from 40% plankton at 19 mm to 70%–75% at 225 mm. Similarly, both δ13C and δ15N increased with size and A. labiata of 19 mm were ~1 trophic level lower than A. labiata of 225 mm. We also documented size‐based changes in nutritional quality of A. labiata, where C:N decreased with A. labiata size, and essential FAs arachidonic acid (ARA) and docosahexaenoic acid (DHA) increased with size while eicosapentaenoic acid (EPA) did not change. A. labiata were elevated in ARA compared with other zooplankton, ranging from 1% to 9%. The changes in C:N and DHA of A. labiata with size mirrored the changes in their diet, but changes in ARA and EPA did not. Overall, these findings emphasize the importance of considering jellyfish size and taxonomy when evaluating nutritional pathways through jellyfish in marine food webs, and support that diet is one important driver of jellyfish biochemical composition. [ABSTRACT FROM AUTHOR]

This study examines the question of how much information one can extract from a tracer-based hydrograph separation in a remote and minimally gaged alpine catchment in Chile. We combine PCA-based endmember mixing analysis to identify the sources of flow contribution to the Diguillín River with a hierarchical Bayesian mixing model to integrate spatial and temporal variability in endmember concentration and quantify the source contributions to streamflow over time. The PCA-analysis shows that precipitation isotopes do not vary by elevation (e.g. snow and rainfall had identical signatures) but vary significantly by season, and that a third endmember is necessary to bound streamflow variability at the basin outlet, which was not captured by our field sampling. One of the main advantages of Bayesian methods is the quasi-machine learning capabilities, where we treated the third endmember as a parameter from which the mixing model could both estimate proportional contributions as well as posterior estimates for the tracer concentrations. The two tracer, three endmember hydrograph separation revealed groundwater to be the largest and precipitation (rain and snow) to be the smallest contributor, on average, to streamflow with the third unknown endmember contributing around 40% of streamflow during the Winter wet season. We hypothesize that interflow is occurring as the third endmember in the Alto Diguillín subwatershed, based on inferred tracer values and the presence of alluvium atop impermeable bedrock along certain reaches. More work is necessary to observe and sample these flowpaths, which was not possible during this study. The results of this work have implications for water resource management, since groundwater sustains the majority of streamflow in the Diguillín, and climate change will impact the timing and quantity of baseflow and interflow. Overall, we demonstrate the utility of combining PCA with Bayesian statistical modeling and inference to extract maximum information from a limited field dataset in a remote alpine catchment. The findings of this work can guide future water management in the Diguillín, but also provide clear questions for future research.

This study examines the question of how much information one can extract from a tracer-based hydrograph separation in a remote and minimally gaged alpine catchment in Chile. We combine PCA-based endmember mixing analysis to identify the sources of flow contribution to the Diguillín River with a hierarchical Bayesian mixing model to integrate spatial and temporal variability in endmember concentration and quantify the source contributions to streamflow over time. The PCA-analysis shows that precipitation isotopes do not vary by elevation (e.g. snow and rainfall had identical signatures) but vary significantly by season, and that a third endmember is necessary to bound streamflow variability at the basin outlet, which was not captured by our field sampling. One of the main advantages of Bayesian methods is the quasi-machine learning capabilities, where we treated the third endmember as a parameter from which the mixing model could both estimate proportional contributions as well as posterior estimates for the tracer concentrations. The two tracer, three endmember hydrograph separation revealed groundwater to be the largest and precipitation (rain and snow) to be the smallest contributor, on average, to streamflow with the third unknown endmember contributing around 40% of streamflow during the Winter wet season. We hypothesize that interflow is occurring as the third endmember in the Alto Diguillín subwatershed, based on inferred tracer values and the presence of alluvium atop impermeable bedrock along certain reaches. More work is necessary to observe and sample these flowpaths, which was not possible during this study. The results of this work have implications for water resource management, since groundwater sustains the majority of streamflow in the Diguillín, and climate change will impact the timing and quantity of baseflow and interflow. Overall, we demonstrate the utility of combining PCA with Bayesian statistical modeling and inference to extract maximum information from a limited field dataset in a remote alpine catchment. The findings of this work can guide future water management in the Diguillín, but also provide clear questions for future research.

Understanding the biogeochemical processes of particulate organic matter occurring in the river under anthropogenic disturbances and its transport to the coastal system is important for environmental resource management. In this study, we investigated the sources and distribution of particulate organic matter (POM) from the upper reaches of the Iyidere River, Türkiye, to the coastal water of the Black Sea during the fall and spring seasons using the elemental (POC and PON (%), C/N), isotopic (δ13C and δ15N), and Bayesian mixing model (MixSIAR) analysis. The POC (%), PON (%), and C/N of POM varied seasonally, indicating that the composition of POM varied with river hydrology, which varies depending on the climate of the region. Both the mixing model and the isotopic and elemental ratios of POM have revealed that the organic matter sources contributing to the riverine of POM, during the fall season, when the precipitation is severe, exhibited a uniform distribution. Heavy rain increased soil erosion along the high-slope land, and as a result, soil and bacteria were identified as the main contributor of POM along the Iyidere River. The results showed that the organic matter sources contributing to POM in the spring season showed significant spatial variation. Terrestrial vegetation, soil OM, and bacteria were the main contributors of POM depending on sites, and these contributions did not show a regular trend along the river. δ15N of POM had significant spatial variation in both seasons that was likely caused by nitrogen inputs derived from anthropogenic activities along the river. The anthropogenic activities and cascade dams causing variations in the contribution of organic matter to the POM are the likely important driving factors in this river-coastal system.

Abstract Despite their seemingly watery constitution, jellyfish are eaten by a diverse range of predators. However, while the role of jellyfish in marine food webs is gaining attention, the nutritional value of these gelatinous organisms and how it varies remain poorly understood. In this study, we aimed to connect jellyfish food web biology and nutrition by determining the relationship between jellyfish size, diet, and nutritional quality. We measured stable isotope (SI) and fatty acid (FA) profiles of particulate organic matter (POM), plankton size classes, and gelatinous zooplankton collected from a coastal site in British Columbia, Canada, in July and September 2019. Gelatinous zooplankton comprised 152 Aurelia labiata collected across both months (bell diameters = 19–225 mm), and 2 Aequorea victoria and approximately 30 Pleurobrachia bachei collected in July for comparison. According to FA trophic markers and chlorophyll a concentrations, the POM was a mix of phytoplankton, microzooplankton, bacteria, and detritus. According to δ15N, POM was ~1 trophic level lower than plankton. All gelatinous zooplankton had low FA content (5–6 μg/mg dry mass) compared with zooplankton (43–65 μg/mg dry mass). A Bayesian mixing model (MixSIAR) was used to assess the contributions of POM and plankton to A. labiata diet, which demonstrated a size‐based shift from 40% plankton at 19 mm to 70%–75% at 225 mm. Similarly, both δ13C and δ15N increased with size and A. labiata of 19 mm were ~1 trophic level lower than A. labiata of 225 mm. We also documented size‐based changes in nutritional quality of A. labiata, where C:N decreased with A. labiata size, and essential FAs arachidonic acid (ARA) and docosahexaenoic acid (DHA) increased with size while eicosapentaenoic acid (EPA) did not change. A. labiata were elevated in ARA compared with other zooplankton, ranging from 1% to 9%. The changes in C:N and DHA of A. labiata with size mirrored the changes in their diet, but changes in ARA and EPA did not. Overall, these findings emphasize the importance of considering jellyfish size and taxonomy when evaluating nutritional pathways through jellyfish in marine food webs, and support that diet is one important driver of jellyfish biochemical composition.

The capacity for coastal river networks to transport and transform dissolved organic matter (DOM) is widely accepted. However, climate‐induced shifts in stormwater runoff and tidal extension alter fresh and marine water source contributions, associated DOM, and processing rates of nutrients entering coastal canals. We investigate how time‐variable interactions among coastal water source contributions influence the concentrations of dissolved organic carbon (DOC), nutrients, and DOM composition in urban canals. We quantified the spatiotemporal variability of DOM quality and nutrient concentrations to determine contributions of tidal marine water, rainwater, stormwater runoff, and groundwater to three coastal urban canals of Miami, Florida (USA). We created a Bayesian Monte Carlo mixing model using measurements of fluorescent DOM (fDOM), DOC concentrations, δ18O and δ2H isotopic signatures, and chloride (Cl−). Fractional contributions of groundwater averaged 17% in the dry season and 26% at peak high tide during the subtropical wet season (September–November). The canal‐to‐marine head difference (CMHD) was a primary driver of groundwater contributions to coastal urban canals and monthly patterns of fDOM/DOC. High tide (>1 m) and discharge events were found to connect canals to upstream sources of terrestrial DOM. Loading of terrestrially sourced DOC and DOM is pulsed to urban canals, shunted downstream and supplemented by microbially sourced DOM during the wet season at high tide. Overall, we demonstrate that a combined tracer approach with isotopes and fDOM can help identify groundwater contributions to coastal waterways and that autochthonous fDOM may prime the degradation of carbon or nutrients as the CMHD pushes inland. Key Points: A combined tracer approach with isotopes and fluorescent dissolved organic matter (fDOM) can help identify time‐variable groundwater contributions to urban coastal waterwaysShallow groundwater can be a significant source of bioavailable carbon and nutrients to surface waters following high tide or runoff eventsAutochthonous fDOM may prime the degradation of carbon or nutrients as the canal‐to‐marine head difference pushes inland [ABSTRACT FROM AUTHOR]

Stable isotope mixing models (SIMMs) are widely used for characterizing wild animal diets. Such models rely upon using accurate trophic discrimination factors (TDFs) to account for the digestion, incorporation, and assimilation of food. Existing methods to calculate TDFs rely on controlled feeding trials that are time‐consuming, often impractical for the study taxon, and may not reflect natural variability of TDFs present in wild populations.We present TDFCAM as an alternative approach to estimating TDFs in wild populations, by using high‐precision diet estimates from a secondary methodological source—in this case nest cameras—in lieu of controlled feeding trials, and provide a framework for how and when it should be applied.In this study, we evaluate the TDFCAM approach in three datasets gathered on wild raptor nestlings (gyrfalcons Falco rusticolus; peregrine falcons Falco perigrinus; common buzzards Buteo buteo) comprising contemporaneous δ13C & δ15N stable isotope data and high‐quality nest camera dietary data. We formulate Bayesian SIMMs (BSIMMs) incorporating TDFs from TDFCAM and analyze their agreement with nest camera data, comparing model performance with those based on other relevant TDFs. Additionally, we perform sensitivity analyses to characterize TDFCAM variability, and identify ecological and physiological factors contributing to that variability in wild populations.Across species and tissue types, BSIMMs incorporating a TDFCAM outperformed any other TDF tested, producing reliable population‐level estimates of diet composition. We demonstrate that applying this approach even with a relatively low sample size (n < 10 individuals) produced more accurate estimates of trophic discrimination than a controlled feeding study conducted on the same species. Between‐individual variability in TDFCAM estimates for ∆13C & ∆15 N increased with analytical imprecision in the source dietary data (nest cameras) but was also explained by natural variables in the study population (e.g., nestling nutritional/growth status and dietary composition).TDFCAM is an effective method of estimating trophic discrimination in wild animal populations. Here, we use nest cameras as source dietary data, but this approach is applicable to any high‐accuracy method of measuring diet, so long as diet can be monitored over an interval contemporaneous with a tissue's isotopic turnover rate. [ABSTRACT FROM AUTHOR]

A synoptic gulf-wide isoscape of carbon (δ13C) and nitrogen (δ15N) in the Gulf of Mexico based on mesozooplankton (335-1000 um) was used as a proxy for the isotopic baseline and for calculating regional contributions of dissolved inorganic nitrogen sources. Mesozooplankton were sampled at 0-200 m (depth permitting) during the XIXIMI-06 and GOMECC-3 cruises held during the summer of 2017. A striking latitudinal gradient was found in δ15N values of zooplankton, with the highest values (10.4 ± 1.2‰) found over the northern shelf, and lowest values in the central, oligotrophic gulf (1.9 ± 0.5‰). To estimate the fractional contribution of potential nitrogen sources, the gulf was divided into six regions based on the spatial distribution of surface Chl-a, SST from remote sensing products and likely region-specific source contributions. A literature survey of (δ13C and δ15N values of particulate organic matter was used to characterize region-specific endpoint isotope ratios for use in a Bayesian isotope mixing model. Regional differences in δ15N values and the results of mixing models indicated nitrogen fixation is most likely an important source (45-74% contribution) of new nitrogen in the oceanic regions of the Gulf, the Loop Current and the Yucatan Shelf. In the oligotrophic gulf, the potential input of relatively light nitrate that reflects remineralization of surface layer POM or the excretion of light nitrogen by heterotrophs was insufficient to explain the low δ15N values found in the central Gulf, although it could account for about 40% of the N supporting secondary production. The high nitrogen isotope ratios found in the northern shelf were attributed to denitrified N (60%) and the inflow of heavy nitrogen from the Mississippi-Atchafalaya river system. Our results support the potential importance of fixed nitrogen in the deep waters of the Gulf of Mexico during the summer, characteristic for its highly stratified surface waters.

We introduce a Bayesian stable isotope mixing model for estimating the relative contributions of different dietary components to the tissues of consumers within food webs. The model is implemented with the probabilistic programming language Stan.The model incorporates isotopes of multiple elements (e.g. C, N, H) for two trophic levels, when the structure of the food web is known. In addition, the model allows inclusion of latent trophic levels (i.e. for which no empirical data are available) intermediate between sources and measured consumers. Running the model in simulations driven by a real dataset from Finnish lakes, we tested the sensitivity of the posterior distributions by altering critical prior parameters and assumptions in the data‐generating process.Importantly, we found that the model estimations were particularly sensitive to the assigned prior value for ω (the fraction of H in aquatic consumer tissue that is derived from environmental water rather than diet) so that reliable empirical data for this parameter are required. When reliable information is not available for ω, we suggest that an uninformative prior should be used.The proposed model and inferences are suitable for studies where resources for collecting new data are limited, but useful prior information for each specific trophic level is available from earlier studies. [ABSTRACT FROM AUTHOR]

Understanding how intraspecific variation in the use of prey resources impacts energy metabolism has strong implications for predicting long-term fitness and is critical for predicting population-to-community level responses to environmental change. Here, we examine the energetic consequences of variable prey resource use in a widely distributed marine carnivore, juvenile sand tiger sharks (Carcharias taurus). We used carbon and nitrogen isotope analysis to identify three primary prey resource pools—demersal omnivores, pelagic forage, and benthic detritivores and estimated the proportional assimilation of each resource using Bayesian mixing models. We then quantified how the utilization of these resource pools impacted the concentrations of six plasma lipids and how this varied by ontogeny. Sharks exhibited variable reliance on two of three predominant prey resource pools: demersal omnivores and pelagic forage. Resource use variation was a strong predictor of energetic condition, whereby individuals more reliant upon pelagic forage exhibited higher blood plasma concentrations of very low-density lipoproteins, cholesterol, and triglycerides. These findings underscore how intraspecific variation in resource use may impact the energy metabolism of animals, and more broadly, that natural and anthropogenically driven fluctuations in prey resources could have longer term energetic consequences. [ABSTRACT FROM AUTHOR]

• PM 2.5 nitrate concentrations increased with PM 2.5 pollution level. • δ18O-NO 3 − and δ15N-NO 3 − values were higher in winter than those in summer. • PM 2.5 nitrate in winter were largely from P N2O5 , while from P OH in summer. • Coal combustion and biomass burning were the main sources in winter and summer. Nitrate (NO 3 −) has been the dominant ion of secondary inorganic aerosols (SIAs) in PM 2.5 in North China. Tracking the formation mechanisms and sources of particulate nitrate are vital to mitigate air pollution. In this study, PM 2.5 samples in winter (January 2020) and in summer (June 2020) were collected in Jiaozuo, China, and water-soluble ions and (δ15N, δ18O)-NO 3 − were analyzed. The results showed that the increase of NO 3 − concentrations was the most remarkable with increasing PM 2.5 pollution level. δ18O-NO 3 − values for winter samples (82.7‰ to 103.9‰) were close to calculated δ18O-HNO 3 (103‰ ± 0.8‰) values by N 2 O 5 pathway, while δ18O-NO 3 − values (67.8‰ to 85.7‰) for summer samples were close to calculated δ18O-HNO 3 values (61‰ ± 0.8‰) by OH oxidation pathway, suggesting that PM 2.5 nitrate is largely from N 2 O 5 pathway in winter, while is largely from OH pathway in summer. Averaged fractional contributions of P N2O5+H2O were 70% and 39% in winter and summer sampling periods, respectively, those of P OH were 30% and 61%, respectively. Higher δ15N-NO 3 − values for winter samples (3.0‰ to 14.4‰) than those for summer samples (-3.7‰ to 8.6‰) might be due to more contributions from coal combustion in winter. Coal combustion (31% ± 9%, 25% ± 9% in winter and summer, respectively) and biomass burning (30% ± 12%, 36% ± 12% in winter and summer, respectively) were the main sources using Bayesian mixing model. These results provided clear evidence of particulate nitrate formation and sources under different PM 2.5 levels, and aided in reducing atmospheric nitrate in urban environments. [Display omitted] [ABSTRACT FROM AUTHOR]

We tested an integrated multi-isotopic analysis framework to quantitatively estimate anthropogenic organic matter (OM) loads in different land-use types of a watershed (Lake Shihwa, South Korea). The isotopic signatures of increased bulk-element abundances in urban areas and industrial complexes may reflect the mixed contributions of natural and anthropogenic sources. Together with the predominant abundance of n-alkanes and polycyclic aromatic hydrocarbons at both boundaries, specific indices derived from their abundance may be indicative of mixed contributions from terrestrial plants, petroleum, and combustion deposited through various pathways (e.g., atmospheric deposition, outfall pipes, and surface runoff). Based on these properties, compound isotopic signatures (δ 13 C C27+C29+C31 , δ 13 C Fl , δ 13 C Pyr , δ 13 C BaA+Chry , δ 13 C IcdP , δ 13 C BghiP ,) for both land-use types may provide significant evidence of an increase in anthropogenic derived-OM loads (> 90 %) in Lake Shihwa. This approach suggests that total organic carbon-weighted source apportionments can provide useful quantitative estimates of OM loads within complex river systems., Competing Interests: Declaration of competing interest The authors declare that they have no competing financial interests or personal relationships that appear to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Global water resources affected by excessive nitrate (NO 3 - ) have caused a series of human health and ecological problems. Therefore, identification of NO 3 - sources and transformations is of pivotal significance in the strategic governance of widespread NO 3 - contaminant. In this investigation, a combination of statistical analysis, chemical indicators, isotopes, and MixSIAR model approaches was adopted to reveal the hydrochemical factors affecting NO 3 - concentrations and quantify the contribution of each source to NO 3 - concentrations in surface water and groundwater. The findings revealed that high groundwater NO 3 - concentration is concentrated in the southwestern region, peaking at 271 mg/L. NO 3 - concentration in the Wei River and Yuxian River exhibited an increase from upstream to downstream, but in the Shidi River and Luowen River, its concentration was highest in the upstream. Groundwater NO 3 - has noticeable correlation with Na + , Ca 2+ , Mg 2+ , Cl - , HCO 3 - , TDS, EC, and ORP. In surface water, NO 3 - level is significantly correlated with NH 4 + and ORP. Major sources of NO 3 - in surface and groundwater comprise manure & sewage and soil nitrogen. Source contribution for surface water was calculated by MixSIAR model to obtain soil nitrogen (57.7%), manure & sewage (23.8%), chemical fertilizer (12%), and atmospheric deposition (6.4%). In groundwater, soil nitrogen and manure & sewage accounted for 19% and 63.8% of nitrate sources, respectively. Both surface water and groundwater exhibited strong oxidation, with nitrification the primary process. It is expected that this study will provide insights into the dynamics of NO 3 - and contribute to the development of effective strategies for mitigating NO 3 - contaminant, leading to sustainable management of water resources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Urban growth often results in changes in the urban hydrological cycle, causing impacts on water availability in densely populated regions. The water isotopologues can provide relevant information about the origin of water under different hydrogeological scenarios, aiding to implement better strategies for water conservation in coupled natural-urbanized environments. In this study, the isotopic compositions of multiple water sources were assessed in a pristine (Ipanema National Forest, FLONA) and an urbanized (Lavapés catchment, SOR) watershed located in the Sorocaba River basin (State of São Paulo, Southeastern Brazil), seeking to understand the causes of isotopic variability and to determine the relative contribution from different sources to streamflow, using the Bayesian mixing model approach. Differences in isotopic composition were observed, as FLONA yielded the most depleted water (ca. −7.5 ‰ δ 18O for surface and groundwater and ca. + 11.0 ‰ d-excess), while SOR yielded the most enriched water (ca. −5.5‰ δ 18O for surface and groundwater and −3.8‰ δ 18O for the water supply system), with evidence of evaporation (ca. + 8.2 ‰ d-excess). The differences observed in isotopic compositions are related to a combination of different factors, such as geological framework, groundwater recharge, and evaporation associated with the Itupararanga water reservoir. Both in FLONA and SOR, groundwater discharge is the most important factor that regulates streamflow. However, in SOR, losses from the water supply system were almost constant along the year, representing an important contribution. The results presented here highlight the use of isotope hydrology techniques to solve problems related to urban hydrology. [ABSTRACT FROM AUTHOR]

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Clarifying the water uptake patterns and competition among riparian plants under different ecological water conveyance conditions is crucial for the stability of the riparian ecosystem in arid areas. Here, we have utilized the Bayesian isotope mixing model to quantify the plant water sources for two typical riparian plants (Tamarix ramosissima and Phragmites australis) along the Manas River in Xinjiang, Northwest China. The water competition relationship between these two typical riparian plants is evaluated using the proportional similarity index (PSI). Our findings demonstrated the following: (1) The climate in the study area is dry and strongly evaporative, and the slope and intercept of the local meteoric water line are smaller than the global meteoric water line. The interconversion between surface water and groundwater occurred mainly in the upper reaches of the river. (2) At the sample site with the long-term ecological water conveyance, the water uptake pattern for typical riparian plants is predominantly shallow soil water or the uniform use of potential water sources. Among them, the utilization rate of shallow soil water reached 30.7 ± 12.6%. At sample sites with intermittent ecological water conveyance and the non-ecological water conveyance sample site, the growth of T. ramosissima and P. australis primarily uses deep soil water and groundwater, with mean values of 34.5 ± 5.1% and 32.2 ± 1.9%, respectively. (3) The water competition between plants at the intermittent ecological water conveyance and non-ecological water conveyance sample sites was more intense. However, the long-term ecological water conveyance effectively reduced water competition among plants. Our results will provide basic theoretical support for maintaining the stability of the Manas River riparian ecosystem and determining environmental flows.

Fifty-seven riverine samples in three typical regions, namely, upper mountainous (zone 1), middle hilly (zone 2), and lower plain (zone 3) regions, were collected in May (low flow) and August (high flow) of 2016, and chemical parameters and isotopes were analyzed to enrich the knowledge of riverine nitrate sources and transformations in the Taizi River basin. Results showed that NO3− concentrations in zone 3 were the highest, followed by zones 2 and 1. NO3−/Cl− molar ratios and nitrate dual isotopes indicated that NO3− was mainly from chemical fertilizer (CF) in zones 1 (57.0%) and 2 (43.1%) according to a Bayesian mixing model (SIAR) and mixed sources of CF, nitrification of soil organic nitrogen (SON), and manure and sewage (M&S) in zone 3 (92.8%), during the high-flow season. NO3− was mainly from CF and SON in zones 1 (76.7%) and 2 (74.0%), during the low-flow season. NO3−sources were different in the three rivers of zone 3 mainly due to various urban inputs. Contributions of CF, SON, and M&S increased by 13%, 8.3%, and 7.5% in zones 1, 2, and 3, respectively, from the low-flow to the high-flow season. NO3− in the Taizi River was mainly influenced by nitrification in soils, while no significant denitrification was found in the three zones. Measures for reducing NO3− inputs to rivers should be considered by improving effectively utilizing rate of chemical fertilizer and inhibit nitrification. [ABSTRACT FROM AUTHOR]

The role of soil‐forming factors (time, parent material, climate, biota, and topography) on soil processes has commonly been studied using soil sequences where only one factor varies between sites. However, when multiple factors change, it becomes difficult to partition the importance of different soil‐forming factors for soil formation. We show for an altitudinal gradient how proximal sensing (portable XRF, Fourier‐Transform Infrared [FTIR]), multivariate statistics, and Bayesian mixing modeling can help to quantify the importance of two soil‐forming factors. First, we confirmed the existing qualitative soil‐landscape model of concomitant shifts in parent material (greywacke loess to mafic volcanics) and climate (higher precipitation) with altitude, leading to increases in pedogenic oxides, soil carbon, and soil Fe, while Si concentrations and pH declined. Second, we applied a mixing model using immobile elements as parent material tracers to quantify the parent material contribution in soils across our gradient. Third, we conducted a variation analysis to determine how much variation in the soil FTIR spectra could be explained by parent material and climate. We found that parent material explained a larger proportion of the variation than climate. However, because of the strong spatial correlation between climate and parent material, a large proportion of the variation in the FTIR data could be explained by either parent material or climate, potentially concealing the leading role of parent material. Given that parent material is often omitted in modern digital soil mapping, our results emphasize the importance of parent material as a predictor of spatial soil distribution. Plain Language Summary: The type of soil that exists in a landscape depends on the multiple factors like climate, rock type, or topography. Teasing these factors apart in their contribution to shape the characteristics of the soil is difficult. However, this knowledge is important to understand the processes in soil and make predictions about where soils occur in a landscape. In our study, we analyzed soils that differed by climate and rock type to determine which of the two factors was more important for the soil characteristics. We obtained soil chemical data of thousands of variables, and used statistical methods that were specifically developed to understand such large data sets. We found that rock type could explain the differences between our soils better than climate. Our work is an example of how to use and understand large data sets in soil science. It also gives evidence for the importance of rock type for soil characteristics. Highlighting this is important because rock type is often not considered when predicting the characteristics of soils in a landscape. Key Points: Quantifying the importance of different soil‐forming factors that change concomitantly at landscape scale (climate, parent material)Utilizing soils of an elevation gradient combined with proximal soil sensing data, multivariate statistics, and Bayesian mixing modelingParent material explains more soil data variation than climate despite being frequently omitted in modern digital soil mapping [ABSTRACT FROM AUTHOR]

Information on the feeding habits of species is essential to develop appropriate conservation actions. This study aimed to assess spatial and temporal variation in the diet of the Eurasian otter, Lutra lutra in the Anzali Wetland, through fecal and stable isotope analysis. Seven main prey items were observed in the analysis of 300 fresh spraints. The highest feeding index was observed for fish, followed by snakes. Among the fish species consumed, the index of preponderance of Prussian carp (Carassius gibelio) was the highest followed by pike (Esox lucius) and white bream (Blicca bjoerkna). Results of Shannon diversity index suggest spatial variation of species diversity within and between feeding items (p < 0.05); snakes, frogs, and oriental river prawn (Macrobrachium nipponense) showed a seasonal variation. The otter's trophic level (TL) (3.79) was higher than the TLs of other Anzali Wetland predators, such as pike. Bayesian mixing model showed source proportion contributions of fish 49.5%, reptiles 16.7%, insects 14.8%, crustacean 10.5%, amphibians 4.3%, birds 4.1%, and mollusks 0.1%. When considering only fish species in the Bayesian mixing model, Prussian carp was the main fish prey in the otters' diet accounting for 47%. Based on the results of this study, the Eurasian otter plays an important role in the ecology of the Anzali Wetland ecosystem even though it preys on exotic species, such as the Prussian carp and the oriental river prawn. [ABSTRACT FROM AUTHOR]

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management. This work applied an approach integrated zonal mapping, stable isotopes (δ18O H2O , δ15N nitrate , δ18O nitrate , and δ13C-DIC) and a Bayesian isotope model to analyze regional and seasonal differences in the contribution and sources of nitrogen to a well-protected reservoir. The values of δ18O nitrate and the positive relationship between NO 3 − and δ13C-DIC suggested that nitrification was the primary NO 3 − production in the rivers. While Denitrification was present at only a few sites. Results of the MixSIAR model coupled the NO 3 −/Cl− indicator revealed that the domestic sewage contributed high riverine NO 3 − loading (68.6 ± 10.6 %) in the dry season. In the wet season, the main nitrate sources of upper watershed were ammonia and carbamide fertilizers (47.5 % and 40.3 %). While the domestic sewage was still the major contributor of downstream region (a dense residential area), indicating possible problems with rainwater and sewage drainage networks. The results implied that the colleting and treatment of sewages were the priority in downstream region, and non-point source pollution control and wastewater treatment plant upgrading were essential to control nitrate pollution in the two upstream regions. These findings provide new insights into precise nitrogen pollution traceability and identification of treatment priorities in the sub-region, and promote the management other well-protected watershed in similar need of further nitrogen contamination control. [Display omitted] • Sources and fate of nitrate were investigated in a well-protected basin. • Hydrochemistry, multi-isotopes and Mixsiar models were applied. • Microbial activity weakly affected nitrogen biogeochemical processes. • Manure and domestic sewage were primary driving forces of nitrate loading to the basin. [ABSTRACT FROM AUTHOR]

Ecohydrological processes in tropical rainforests are insufficiently understood, and existing studies yield contradictory results. We investigated relative contributions of different soil depths to tree water uptake of 83 trees and possible species‐specific differences in a 50 × 50 m forest plot at four dates in a tropical montane forest in Kenya using stable water isotopes and the Bayesian mixing model framework MixSIAR. We found distinct individual tree differences (e.g. Drypetes gerrardii taking 75% of its water from <0.5 m, or a rather large shift in uptake patterns based on the climatic conditions, that is the fourth sampling date), but no consistent species‐specific or small‐scale spatiotemporal patterns in water uptake and depth contributions. Soil water δ18O showed a lateral variation of up to 6‰, which was accounted for by a spatial interpolation of soil water isotopes and enabled us to improve allocations of water uptake sources to individual trees. Our results show that ignoring the lateral variability of water isotope signatures in soils complicates the applicability of a mixing model in this context and might be a widespread constraint reducing the validity and comparability of mixing model results. Further research on underlying processes of water fluxes in forest ecosystems is urgently needed and we point out the need for considering large individual differences in water uptake patterns and small‐scale variability of soil water isotopic composition despite homogeneous soil characteristics. [ABSTRACT FROM AUTHOR]

Rapid anthropogenic environmental change is expected to impact a host of ecological parameters in Southern Ocean ecosystems. Of critical concern are the consequences of these changes on the range of species that show fidelity to migratory destinations, as philopatry is hypothesized to help or hinder adaptation to climate change depending on the circumstances. Many baleen whales show philopatry to feeding grounds and are also capital breeders that meet migratory and reproductive costs through seasonal energy intake. Southern right whales (Eubalaena australis, SRWs) are capital breeders that have a strong relationship between reproductive output and foraging success. The population dynamics of South Africa's population of SRWs are characterized by two distinct periods: the 1990s, a period of high calving rates; and the late 2010s, a period associated with lowered calving rates. Here we use analyses of stable carbon (δ13C) and nitrogen (δ15N) isotope values from SRW biopsy samples (n = 122) collected during these two distinct periods to investigate foraging ecology of the South African population of SRWs over a time period coincident with the demographic shift. We show that South African SRWs underwent a dramatic northward shift, and diversification, in foraging strategy from 1990s to 2010s. Bayesian mixing model results suggest that during the 1990s, South African SRWs foraged on prey isotopically similar to South Georgia/Islas Georgias del Sur krill. In contrast, in the 2010s, South African SRWs foraged on prey isotopically consistent with the waters of the Subtropical Convergence, Polar Front and Marion Island. We hypothesize that this shift represents a response to changes in preferred habitat or prey, for example, the decrease in abundance and southward range contraction of Antarctic krill. By linking reproductive decline to changing foraging strategies for the first time in SRWs, we show that altering foraging strategies may not be sufficient to adapt to a changing ocean. [ABSTRACT FROM AUTHOR]

Abstract The notion that closely related species resemble each other in ecological niche space (i.e., phylogenetic dependence) has been a long‐standing, contentious paradigm in evolutionary biology, the incidence of which is important for predicting the ecosystem‐level effects of species loss. Despite being examined across a multitude of terrestrial taxa, many aspects of niche conservatism have yet to be explored in marine species, especially for characteristics related to resource use and trophic behavior (Eltonian niche characteristics, ENCs). We combined ENCs derived from stable isotope ratios at assemblage‐ and species‐levels with phylogenetic comparative methods, to test the hypotheses that benthic marine fishes (1) exhibit similar assemblage‐wide ENCs regardless of geographic location and (2) display phylogenetically dependent ENCs at the species level. We used a 12‐species sub‐set of the monophyletic group Rajidae sampled from three independent assemblages (Central California, Gulf of Alaska, and Northwest Atlantic), which span two ocean basins. Assemblage‐level ENCs implied low trophic diversity and high evenness, suggesting that Rajidae assemblages may exhibit a well‐defined trophic role, a trend consistent regardless of geographic location. At the species level, we found evidence for phylogenetic dependence of ENCs relating to trophic diversity (i.e., isotopic niche width; SEAc). Whether individuals can be considered functional equivalents across assemblages is hard to ascertain because we did not detect a significant phylogenetic signal for ENCs relating to trophic function (e.g., trophic position). Thus, additional, complimentary approaches are required to further examine the phylogenetic dependence of species functionality. Our approach illustrates the potential of stable isotope‐derived niche characteristics to provide insight on macroecological processes occurring across evolutionary time, which could help predict how assemblages may respond to the effects of species loss.

Elucidating the seasonal patterns of water sources for dominant species in the sub-tropical humid mountainous forest, analyzing the eco-hydrological complementarity and competition mechanisms among coexisting species, investigating the responses of plant water utilization to precipitation, could provide a theoretical basis for vegetation restoration and management. Based on the stable hydrogen and oxygen isotope technique, we analyzed the δ 2 H and δ 18 O characteristics of precipitation, xylem water from Pinus massoniana and Quercus variabilis , and soil water from 0-100 cm depth in Mount Lushan, China. The MixSIAR model, Levins index, and PS index were used to calculate the relative contribution rate of each water source, the hydrological niche breadth, and niche overlap of P. massoniana and Q. variabilis . The results showed that, in the wet season (March to July), P. massoniana primarily utilized soil water from the 0-20 cm and 20-40 cm depths, while Q. variabilis primarily utilized that from the 20-40 cm and 40-60 cm depths. During the dry season (August to September), P. massoniana and Q. variabilis utilized 40-60 cm and 60-80 cm of soil water, respectively, resulting in an increase in the depth of water absorption. In the early growing season (March to April) and the late growing season (September), there was a high hydrological niche overlap between P. massoniana and Q. variabilis , resulting in intensitive water competition. In the middle of the growing season (May to August), the water source was adequately allocated, and the hydrolo-gical niche was segregated to meet the high transpiration demand. Q. variabilis primarily utilized soil water from a depth of 60-80 cm and 60-80 cm before a precipitation event, and from a depth of 0-20 cm and 20-40 cm after the event. In contrast, P. massoniana primarily utilized soil water from a depth of 0-20 cm and 20-40 cm both before and after a precipitation event. In conclusion, water utilization patterns of P. massoniana and Q. variabilis exhibited a seasonal trend, with shallow water uptake during the rainy season and deep water uptake during the dry season. These species are capable of efficiently allocating water resources during the peak growth season, and their root systems actively respond to change in soil moisture level. They have strong adaptability to extreme precipitation events and exhibit remarkable water conservation capabilities.

Water use by anthropogenic activities in the face of climate change invokes a better understanding of headwater sources and lowland urban water allocations. Here, we constrained a Bayesian mixing model with stable isotope data (2018–2019) in rainfall (N = 704), spring water (N = 96), and surface water (N = 94) with seasonal isotope sampling (wet and dry seasons) of an urban aqueduct (N = 215) in the Central Valley of Costa Rica. Low δ18O rainfall compositions corresponded to the western boundary of the study area, whereas high values were reported to the northeastern limit, reflecting the influence of moisture transport from the Caribbean domain coupled with strong orographic effects over the Pacific slope. The latter is well-depicted in the relative rainfall contributions (west versus east) in two headwater systems: (a) spring (68.7 ± 3.4 %, west domain) and (b) stream (55.8 ± 3.9 %, east domain). The aqueduct exhibited a spatial predominance of spring water and surface water during a normal wet season (78.7 %), whereas deep groundwater and spring water were fundamental sources for the aqueduct in the dry season (69.4 %). Our tracer-based methodology can help improve aqueduct management practices in changing climate, including optimal water allocation and reduced evaporative losses in the dry season. [ABSTRACT FROM AUTHOR]

Headwaters are generally assumed to contribute the majority of water to downstream users, but how much water, of what quality and where it is generated are rarely known in the humid tropics. Here, using monthly monitoring in the data scarce (2,370 km2) San Carlos catchment in northeastern Costa Rica, we determined runoff‐area relationships linked to geochemical and isotope tracers. We established 46 monitoring sites covering the full range of climatic, land use and geological gradients in the catchment. Regression and cluster analysis revealed unique spatial patterns and hydrologically functional landscape units. These units were used for seasonal and annual Bayesian tracer mixing models to assess spatial water source contributions to the outlet. Generally, the Bayesian mixing analysis showed that the chemical and isotopic imprint at the outlet is throughout the year dominated by the adjacent lowland catchments (68%) with much less tracer influence from the headwaters. However, the headwater catchments contributed the bulk of water and tracers to the outlet during the dry season (>50%) despite covering less than half of the total catchment area. Additionally, flow volumes seemed to be linearly scaled by area maintaining a link between the headwaters and the outlet particularly during high flows of the rainy season. Stable isotopes indicated mean recharge elevations above the mean catchment altitude, which further supports that headwaters were the primary source of downstream water. Our spatially detailed "snap‐shot" sampling enabled a viable alternative source of large‐scale hydrological process knowledge in the humid tropics with limited data availability. [ABSTRACT FROM AUTHOR]

Nitrate (NO 3 –) contamination of surface water is a global environmental problem that has serious consequences for watershed ecosystems and endangers human health. It is crucial to identify influences of different sources of NO 3 −, especially the incoming water from upper reaches. A combination of hydrochemistry and multi-isotope tracers (δ11B, δ15N-NO 3 −, and δ18O-NO 3 –) were used to determine NO 3 – sources and their transformation the North Jiulong River (NJLR), Southeast China. The findings revealed that NO 3 –, which accounted for an average of 87.1% of dissolved inorganic nitrogen (DIN), was the main chemical form of nitrogen species. The integration of dual stable isotopes of NO 3 −, δ11B, and hydrochemistry showed that NO 3 – was primarily contributed by sewage, soil nitrogen (SN), and ammonium (NH 4 +) via precipitation or fertilizers. The contributions from the sewage and soil nitrate source were almost equivalent and much higher than those from other sources in the NJLR watershed. The contributions from diverse sources varied seasonally and spatially. Manure and sewage (M&S) were the leading sources in the summer and autumn, accounting for 60.9 ± 8.5% and 47.3 ± 7.9%, respectively. However, NO 3 − fertilizers were the predominant source in the spring and winter. The NO 3 − inflow from upper reaches was proposed as an additional end-member to identify its contribution in the midstream and downstream in this study. The contributions of NO 3 − from the upper reaches were significant sources in the midstream and downstream, accounting for 27.2 ± 17.8% and 42.9 ± 21.9%, respectively. The obvious decline in local NO 3 −contribution shares from midstream to downstream implied structural changes in pollutant sources and regional environmental responsibility. Therefore, tracing nitrate sources and quantifying their contributions is critical for clarifying environmental responsibilities for precise local nitrogen management in watersheds. [Display omitted] • NO 3 − concentrations in the North Jiulong River varied seasonally and spatially. • Integration of δ15N, δ18O, δ11B and hydrochemistry was used to identify NO 3 – source. • Sewage-dominant manure/sewage and soil nitrate were major NO 3 − source. • Upper reach inflow was proposed as NO 3 − source. • Contributions from upper reaches were important sources in the mid- and downstream. [ABSTRACT FROM AUTHOR]

(1) Background: The degree to which local precipitation is supplied by recycled moisture is a reflection of land surface–atmosphere interactions and a potentially significant climate feedback mechanism. This study tries to figure out the water cycle and precipitation mechanism at a mountainous region and then provides a reference for similar mountainous regions outside China. (2) Methods: The dual-isotopes and Bayes-based program MixSIAR is used to assess contributions of advected, transpirated and evaporated vapor to local precipitation. (3) Results: The average percent contribution of recycled moisture (i.e., the sum of surface evaporated vapor and transpirated vapor) to local precipitation at the Qilian Mountains during 2017 plant growing season is about 37% (the upper quartile and the lower quartile was 30% and 43%, respectively). (4) Conclusions: Although the contribution of advection vapor dominated during the plant growing season, the contribution of recycled moisture is also important in such an alpine region. Furthermore, the commonly used simple linear mixing models often yield contributions greater than 100% or less than 0% and are likely to underestimate the contribution of recycled moisture to local precipitation. Although the alternative Bayesian model is not perfect, either, it is still a big improvement.

Carbonaceous aerosols are an important component of fine particulate matter (PM 2.5 ) in the atmosphere, having great impacts on air quality, human health, and the climate. In this study, PM 2.5 samples were collected from November 2017 to October 2018 in a background site of Guangxi Province to investigate the potential impacts of biomass burning, an essential source of carbonaceous aerosols, on carbonaceous aerosols. Further, the composition of carbonaceous aerosols, sugar compounds, and the light absorption coefficient ( b ) of water-soluble brown carbon (BrC) were also conducted. Considering the effect of the degradation of atmospheric levoglucosan (LG), the concentration of the corrected LG was quantified using the aging of air masses (AAM) index. Then, the contribution of biomass burning (BB) to organic carbon (OC) [BB-OC] was quantified using the corrected LG-derived molecular tracer method combined with the Bayesian mixing model. Here, we further explored the potential sources of water-soluble BrC using correlation analysis. In this research, the mean AAM index was 0.40±0.28 during the study period, indicating that the atmospheric LG had undergone a photochemical degradation process. The characteristic ratio combined with the Bayesian mixing model indicated that the crop straw (i.e., corn, rice, and sugarcane straw) was the dominant biomass fuel type in the Guangxi Region, contributing 22%, 23%, and 18% of OC without the correction of LG and 16%, 21%, and 17% with the corrected LG concentration, respectively. The neglection of LG degradation led to the underestimation of BB-OC, in which the BB-OC values with and without correction were 49.0% and 21.1%, respectively. Here, the annual mean abs ) of water-soluble brown carbon (BrC) were also conducted. Considering the effect of the degradation of atmospheric levoglucosan (LG), the concentration of the corrected LG was quantified using the aging of air masses (AAM) index. Then, the contribution of biomass burning (BB) to organic carbon (OC) [BB-OC] was quantified using the corrected LG-derived molecular tracer method combined with the Bayesian mixing model. Here, we further explored the potential sources of water-soluble BrC using correlation analysis. In this research, the mean AAM index was 0.40±0.28 during the study period, indicating that the atmospheric LG had undergone a photochemical degradation process. The characteristic ratio combined with the Bayesian mixing model indicated that the crop straw (i.e., corn, rice, and sugarcane straw) was the dominant biomass fuel type in the Guangxi Region, contributing 22%, 23%, and 18% of OC without the correction of LG and 16%, 21%, and 17% with the corrected LG concentration, respectively. The neglection of LG degradation led to the underestimation of BB-OC, in which the BB-OC values with and without correction were 49.0% and 21.1%, respectively. Here, the annual mean b abs of water-soluble BrC was (8.7±10.7) Mm -1 , and its main sources were BB, fossil fuel combustion, and vegetation emission.

It is generally accepted that urban vegetation absorbs air pollutants resulting in improved air quality. However, limited work has provided experimental data that can be used to quantify this. In this study, Sophora japonica in the near-road environment was studied, and stable isotopes were used to estimate the proportional contributions of different nitrogen sources to the trees. δ15N and δ18O values were quantified for plant (n = 254) and soil samples (n = 86) collected from 12 sampling sites in Beijing. The elemental composition (total nitrogen (TN) and total carbon (TC)) of both samples types, and the ionic concentration (NO 3 − and NH 4 +) of soil samples were also measured. δ15N in S. japonica sampled near the road was significantly lower than in samples collected far from the road. Variation of δ18O, TN, and TC in plant samples could not be explained by the road distance. Using the SIAR Bayesian isotope mixing model and the mixing polygon method, the average proportional contributions of three nitrogen sources for the tree samples among all experiment sites were estimated, with the proportion for each nitrogen source following the order: soil (69.2%) > traffic-related NO x (19.3%) > dry deposition (11.5%). In addition, the results of the Bayesian model revealed that the nitrogen contribution of traffic-related NO x at road-adjacent sites (23.0%) was higher than the contribution of traffic-related NO x at sites far from the road (16.4%). These results indicated that the S. japonica in near-road green spaces was significantly influenced by traffic-related NO x emissions that were characterized by lower δ15N values. We found that using the SIAR Bayesian isotope mixing model and mixing polygon method, the potential nitrogen sources of plants could be estimated and the proportional contributions estimated by the model can reflect the plant's ability to absorb air-borne NO x. Unlabelled Image • The ability of the S. japonica to absorb air pollutants was studied. • Stable isotopes were used to estimate various nitrogen source contributions. • Variation of δ15N in S. japonica indicated the influence of traffic-related NO x . • Order of source contributions: soil > traffic-related NO x > dry deposition. [ABSTRACT FROM AUTHOR]

Aquatic fungi are increasingly recognized for their contribution to carbon cycling in aquatic ecosystems, both as saprotrophs and parasites. Their quantification in mixed communities is crucial to assess their ecological significance but remains challenging. We characterized the phospholipid-derived fatty acid (PLFA) composition of fifteen aquatic fungal isolates from Chytridiomycota (chytrids) and Dikarya. Additionally, we identified PLFA patterns of chytrids infecting phytoplankton and their zoospores. PLFA composition of zoospores was highly similar among different taxa, but were distinct from their respective sporangial life-stage. Finally, we applied a fatty acid-based Bayesian mixed model (FASTAR) and tested its potential to quantify fungi in complex mixtures with bacteria and phytoplankton using PLFA profiles. While the quantification of chytrid biomass in low quantities was rather imprecise, the model predicted the contribution of filamentous fungi and other components with fair accuracy, supporting the suitability of this approach to quantify fungal biomass in aquatic environments. • PLFA patterns of fungi can be applied to quantify them in mixed aquatic communities. • Zoospores and sporangia of Chytridiomycota differ in their PLFA patterns. • PLFA patterns of phytoplankton infected by fungal parasites change significantly. • Quantifying aquatic fungi with a Bayesian mixed model based on PLFA is generally recommended. • Quantification of Chytridiomycota based on PLFA patterns remains difficult. [ABSTRACT FROM AUTHOR]

• Bayesian hydrograph separation performed in alpine catchment in central Chile. • Groundwater contributed around 50% of streamflow in winter and 75% in summer. • Interflow hypothesized as third endmember from PCA, contributes up to 40% in winter. This study examines the question of how much information one can extract from a tracer-based hydrograph separation in a remote and minimally gaged alpine catchment in Chile. We combine PCA-based endmember mixing analysis to identify the sources of flow contribution to the Diguillín River with a hierarchical Bayesian mixing model to integrate spatial and temporal variability in endmember concentration and quantify the source contributions to streamflow over time. The PCA-analysis shows that precipitation isotopes do not vary by elevation (e.g. snow and rainfall had identical signatures) but vary significantly by season, and that a third endmember is necessary to bound streamflow variability at the basin outlet, which was not captured by our field sampling. One of the main advantages of Bayesian methods is the quasi-machine learning capabilities, where we treated the third endmember as a parameter from which the mixing model could both estimate proportional contributions as well as posterior estimates for the tracer concentrations. The two tracer, three endmember hydrograph separation revealed groundwater to be the largest and precipitation (rain and snow) to be the smallest contributor, on average, to streamflow with the third unknown endmember contributing around 40% of streamflow during the Winter wet season. We hypothesize that interflow is occurring as the third endmember in the Alto Diguillín subwatershed, based on inferred tracer values and the presence of alluvium atop impermeable bedrock along certain reaches. More work is necessary to observe and sample these flowpaths, which was not possible during this study. The results of this work have implications for water resource management, since groundwater sustains the majority of streamflow in the Diguillín, and climate change will impact the timing and quantity of baseflow and interflow. Overall, we demonstrate the utility of combining PCA with Bayesian statistical modeling and inference to extract maximum information from a limited field dataset in a remote alpine catchment. The findings of this work can guide future water management in the Diguillín, but also provide clear questions for future research. [ABSTRACT FROM AUTHOR]

Despite PCBs being banned since the 1980's, some European peri-alpine lakes, and consequently their fish populations, are still contaminated by these xenobiotics. We investigated the relative contribution of physiological and trophic factors that could be implicated in fish PCB bioaccumulation in Lake Bourget (France), one of the most contaminated in Europe, by collecting Arctic char (n = 55) and European whitefish (n = 89) from 2013 to 2016. Concentrations of 7 indicator PCBs were 9–168 ng.g w.w−1 in whitefish and 90–701 ng.g w.w−1 in Arctic char. The fish trophic positions calculated from δ 15N values were positively correlated with PCB concentrations (r2 = 0.45; p < 0.001). A biomagnification model relying on TP and lipid content of fish was then designed, and it confirmed this result. A Bayesian mixing model based on δ 13C and δ 15N values was used to estimate the relative contribution of preys in the fish diet, which explained a significant proportion of the biomagnification model residuals (i.e., 17%). Zooplankton consumption was negatively correlated with PCB concentrations, whereas consumption of chironomids enhanced the PCB burden in fish. Correction of the biomagnification model for individual diets of fish increased the correlation between the predicted and measured fish PCB contents (R2 = 0.71; p < 0.001), highlighting the importance of fish feeding habits in the bioaccumulation process. Unlabelled Image • Lipid content and trophic position explained most of fish PCB contamination • A Bayesian mixing model based on δ 13C and δ 15N was used to estimate the relative contribution of preys in the fish diet • A biomagnification model compared measured and predicted PCB concentration in fish and showed good agreement (r2 adj = 0.64) • Contribution of preys in the model improved the correlation, showing the importance of feeding habits in PCB burden in fish [ABSTRACT FROM AUTHOR]

To gain a better understanding of the trophic ecology of Pacific blue marlin Makaira nigricans off eastern Taiwan, nitrogen and carbon stable isotopes (δ15N and δ13C) and Bayesian mixing models were used to explore trophic dynamics and potential ontogenetic feeding shifts across M. nigricans of different size classes. Makaira nigricans samples from east of Taiwan (n = 213) and Palau (n = 37), as well as their prey (n = 70), were collected during 2012 and 2013. Results indicated increases in δ15N with size, with values of larger size classes (> 200 cm eye‐to‐fork length; LEF) significantly higher than those < 200 cm LEF. Values of δ13C were negatively correlated with size. Makaira nigricans > 200 cm LEF had the highest estimated trophic position (4.44) and also exhibited ontogenetic changes in trophic position. Large M. nigricans fed more on dolphinfish Coryphaena hippurus and hairtail Trichiurus lepturus, while smaller M. nigricans consumed smaller forage fish (e.g., moonfish Mene maculata) and cephalopods. These changes may relate to greater swimming speeds and vertical habitat use in larger M. nigricans, allowing capture and consumption of larger prey items at higher trophic positions. The high trophic level of M. nigricans east of Taiwan confirms its important role as an apex predator in marine food webs and how ecological role changes with size. [ABSTRACT FROM AUTHOR]

Abstract Water sources used for plant identification coupled with stable isotopes are essential to improving the understanding of eco-hydrological processes and ecological management in water-limited ecosystems. Many approaches associated with stable isotopes have been used to determine plant water source apportionment. However, inter-comparisons of different methods are still limited, especially for Bayesian mixing models. In this study, we tested linear mixing models (IsoSource) and Bayesian models (SIAR, MixSIR and MixSIAR) to identify sources of water absorbed by Vitex negundo and Sophora viciifolia (shrubs) and Artemisia gmelinii (subshrub) during the growing season in the semiarid Loess Plateau. The results showed that there was no significant difference in the predicted plant water source fractions using only stable hydrogen isotope (δ2H) and only stable oxygen isotope (δ18O) with the IsoSource model. No significant difference was found in plant water source apportionment by the three Bayesian mixing models combined with δ2H and δ18O except for individual months. The SIAR and MixSIAR models detected no pronounced seasonal variations in plant water uptake, while the MixSIR model did detect seasonal variations. Overall, the SIAR and MixSIAR models exhibited relatively better water source apportionment performances than that of the MixSIR model. This discrepancy may be attributed to the difference in the post distribution simulation algorithm. This study provides critical insights into choosing a suitable method for identifying plant water source apportionment in arid and semiarid regions. Graphical abstract Unlabelled Image Highlights • The performances of four methods for plant water source partitioning were investigated. • The results had no significant difference using only δ2H and only δ18O by IsoSource model. • SIAR and MixSIAR model had better water source partitioning performance. • The post distribution simulation algorithm caused the predicted discrepancy with Bayesian models [ABSTRACT FROM AUTHOR]

Abstract Reliable quantitative information about sediment sources is a key requirement for river catchment management, especially in settings with high sediment loads. This study explores the potential for using source fingerprinting techniques to establish the relative contribution of three sub-basins to the sediment deposited in a reservoir impounded by an earth dam located at the outlet of the Lavar watershed, in Hormozgan Province, southern Iran. The three sub-basins feeding the reservoir are characterized by complex topography and underlying geology. The source material and target sediment samples were analyzed for 53 potential geochemical tracers, including trace elements and rare earth elements (REEs) and their ratios. Stepwise discriminant function analysis (DFA) was applied to select optimum composite fingerprints from those fingerprint properties passing the range test and we compared two different modelling procedures to estimate the relative contribution of the three sub-basins to the sediment deposited in the reservoir. The first involves a Bayesian mixing model within a Markov Chain Monte Carlo framework (BM) and, the second, an un-mixing model within a Monte Carlo simulation framework (UM). The latter model permits the use of ratio properties, which represents a novel aspect of our study. Particular attention was directed to the uncertainty associated with the source contribution estimates provided by the two models. A goodness of fit estimator was employed to evaluate the results of the UM. Both modelling procedures demonstrated that the southern sub-basin was the main source of the majority of samples we collected from the reservoir. The BM model indicated that the central sub-basin was the dominant source of two samples (S6 and S8). Overall, the results provided by the BM model for the source of seven sediment samples (S1, S2, S3, S4, S5, S7 and S9) are compatible with those provided by the UM model and the central sub-basin was recognized as the most important source supplying sediment in the study area. Both approaches offer potential for using geochemical fingerprinting to quantify spatial sediment source contributions and the uncertainty associated with those estimates. Graphical abstract Unlabelled Image Highlights • This study demonstrates the successful use of two different modelling approaches to estimate the source contribution of sediment deposited in an earth dam reservoir. • The REE ratio tracers applied in the UM model. • The central sub-basin (Ss) recognized as the main source supplying sediment in the study area by both modelling approaches. [ABSTRACT FROM AUTHOR]