Search Results (55)

Irrigation depth plays a critical role in regulating soil water availability and root water uptake in perennial orchards, yet its mechanistic effects remain poorly understood in subtropical red-soil hilly regions characterized by strong evaporative demand and shallow effective soil water storage. Here, a field experiment was conducted in a citrus orchard with three irrigation depths—shallow (25 cm), intermediate (50 cm), and deep (100 cm)—under a uniform irrigation amount. Soil water dynamics, root traits, and root water uptake sources across a 0–200 cm soil profile were investigated using soil moisture monitoring, root morphological analysis, dual stable isotopes (δ²H and δ¹⁸O), and the MixSIAR Bayesian mixing model. Irrigation depth markedly restructured vertical soil moisture patterns, with the 40–120 cm layer identified as the most responsive zone. Intermediate irrigation maintained the highest and most stable soil water content in this layer, whereas shallow irrigation intensified surface drying and deep irrigation failed to improve water availability within the hydraulically active root zone. Root surface area and dry mass were maximized under intermediate irrigation, indicating enhanced root–soil coupling. Isotopic analysis revealed the strongest evaporative fractionation under shallow irrigation, while intermediate irrigation substantially alleviated surface evaporation. MixSIAR results further showed that shallow irrigation progressively increased reliance on surface soil water (up to 93% in November), whereas intermediate irrigation promoted coordinated uptake from shallow, middle, and deep soil layers, with deep soil water contributing up to 30.7% in November. These results demonstrate that irrigation depth exerts a stronger control over root water uptake strategies by stabilizing water availability within the active root zone and reducing non-productive evaporative losses. Optimizing subsurface irrigation depth therefore represents an effective pathway to improve water-use efficiency in citrus orchards of subtropical hilly regions. Full article

Nitrate in Baiyangdian Lake is directly linked to the sustainability of watershed ecological functions, acting as a key priority for regional ecological protection. Subsequent to the completion of a series of ecological restoration projects, its sources have undergone inevitable shifts, rendering the original pollution control framework incompatible with the new context. Thus, accurate identification of nitrate sources and their seasonal variation characteristics constitutes a core prerequisite for enhancing the targeting of pollution management. This study integrated dual stable isotopes (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻) in water and potential source samples, along with hydrochemical data, and applied the Bayesian stable isotope mixing model (MixSIAR) to elucidate the sources of NO₃⁻ in Baiyangdian Lake. The results indicated that denitrification exerted a weak influence on the isotopic composition of NO₃⁻ in Baiyangdian Lake. Plots of the NO₃⁻/Cl⁻ versus Cl⁻ ratios for water samples and δ¹⁵N-NO₃⁻ versus δ¹⁸O-NO₃⁻ ratios for both water samples and potential sources confirmed anthropogenic sources as the primary nitrate contributors. The δ¹⁵N-NO₃⁻ vs. 1/[NO₃⁻] plot revealed that the number of NO₃⁻ sources exceeded two. The MixSIAR model demonstrated that wastewater treatment plant (WWTP) discharge was the dominant source throughout the four seasons, accounting for 49–62% with the highest contribution in winter and the lowest in summer. Soil nitrogen release contributed 19–32%, reaching its annual peak in summer. Sediment release accounted for 11–13%, maintaining a relatively low contribution across all seasons. Chemical fertilizer, manure, and sewage (M&S), and atmospheric deposition each contributed less than 6.5%, with negligible contributions. A significant reduction in the contributions of sediment release and M&S reflected the optimization effect of long-term regional ecological restoration efforts. WWTPs point source discharge and seasonal non-point source input from soil nitrogen collectively constituted the core sources of nitrate in Baiyangdian Lake. These findings provide crucial scientific support for the precise source apportionment and differentiated management of nitrate pollution in the basin. Full article

Understanding seasonal water acquisition strategies of desert plants is critical for predicting vegetation resilience under increasing hydrological stress in arid inland river basins. In hyper-arid oases, strong evaporative demand and declining groundwater levels impose tightly coupled constraints on plant water uptake across soil–plant–atmosphere continua. In this study, we combined hydrogen and oxygen stable isotopes, Bayesian mixing models, soil moisture measurements and groundwater monitoring, and leaf δ¹³C analysis to quantify monthly water-source contributions and long-term water-use efficiency of three dominant species (Reaumuria soongarica, Tamarix ramosissima, and Populus euphratica) in the Ejina Oasis. Clear ecohydrological niche differentiation was evident among the three species. R. soongarica exhibited moderate temporal flexibility by integrating shallow and deep soil water with episodic groundwater use, whereas T. ramosissima adopted a vertically integrated and hydraulically plastic strategy combining precipitation, multi-depth soil water, and groundwater. In contrast, P. euphratica followed a conservative strategy, relying predominantly on deep soil water with only minor and transient inputs from precipitation and groundwater. Across species and seasons, deep vadose-zone soil water (120–200 cm) consistently acted as the most stable and influential reservoir, buffering seasonal drought and sustaining transpiration. T. ramosissima maintained the highest intrinsic water-use efficiency, and P. euphratica exhibited consistently lower efficiency associated with sustained access to stable deep soil water. These contrasting strategies reveal multiple pathways of hydraulic stability and plasticity that underpin vegetation persistence under progressive groundwater depletion. By linking water-source partitioning with physiological regulation, this study provides a mechanistic basis for understanding plant water-use strategies and informs ecological water management and species-specific restoration in hyper-arid inland oases. Full article

Mesozooplankton play a pivotal role in marine pelagic food webs, mediating energy and matter transfer between primary producers and higher trophic levels. Daya Bay, a semi-enclosed bay located in the northern South China Sea, has undergone significant environmental changes due to anthropogenic activities, such as thermal discharge from nuclear power plants and eutrophication. This study examined the mesozooplankton community structure, feeding preferences, and food web organization through four seasonal cruises (May 2022, February 2023, August 2023, and November 2023), employing stable isotope analysis and a Bayesian Isotopic Mixing Model. Results indicate that mesozooplankton abundance and diversity were lower in regions affected by thermal discharge, suggesting a suppressive effect of elevated temperatures. Seasonal shifts in dominant species were observed: Penilia avirostris and Dolioletta gegenbauri dominated the community in spring, while Noctiluca scintillans blooms occurred in summer and winter. Isotopic analysis revealed distinct trophic strategies: copepods exhibited omnivorous habits, whereas cladocerans and tunicates showed stronger herbivorous tendencies. N. scintillans functioned as a high-trophic omnivore, preying on copepod larvae and competing for food resources. Overall, the mesozooplankton community was characterized by an omnivory-dominated trophic network, which enhanced resilience yet remains sensitive to anthropogenic disturbances. This study clarifies how human-induced environmental changes reshape trophic pathways in subtropical coastal waters, providing a valuable reference for long-term monitoring and ecosystem management in Daya Bay. Full article

Rapid urbanization has intensified nitrate pollution in megacity rivers, posing severe challenges to urban water governance and sustainable nitrate management. This study presents nitrate dual-isotope signatures (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻) from surface water samples collected during the wet season from the Yongding River (YDR) and Chaobai River (CBR) in the Beijing–Tianjin–Hebei megacity region of North China. Average concentrations of nitrate (as NO₃⁻) were 8.5 mg/L in YDR and 12.7 mg/L in CBR. The δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻ values varied from 6.1‰ to 19.1‰ and −1.1‰ to 10.6‰, respectively. The spatial distribution of NO₃⁻/Cl⁻ ratios and isotopic data indicated mixed sources, primarily sewage and manure in downstream sections and agricultural inputs in upstream areas. Isotopic evidence revealed widespread nitrification processes and could have potentially localized denitrification under low-oxygen conditions in the lower YDR. Bayesian mixing model (MixSIAR) results indicated that sewage and manure constituted the main nitrate sources (49.4%), followed by soil nitrogen (23.7%), chemical fertilizers (19.2%), and atmospheric deposition from rainfall (7.7%). The self-organizing map (SOM) further revealed three nitrate regimes, including natural and agricultural, mixed, and sewage dominated conditions, indicating a clear downstream gradient of increasing anthropogenic influence. The results suggest that efficient nitrogen management in megacity rivers requires improving biological nutrient removal in wastewater treatment, regulating fertilizer application in upstream areas, and maintaining ecological base flow for natural denitrification. This integrated framework provides a quantitative basis for nitrate control and supports sustainable water governance in highly urbanized watersheds. Full article

Nitrate (NO₃⁻) pollution in rivers within agricultural regions has become a global issue that cannot be ignored. Identifying the sources and transformation processes of NO₃⁻ is crucial for safeguarding water quality in agricultural catchment areas. This study traces the sources and transformation processes of NO₃⁻ in the Songhua River basin of Northeast China by analysing hydrochemical parameters and NO₃⁻ dual isotopes (δ¹⁵N and δ¹⁸O) in river water. It estimates the proportional contributions of NO₃⁻ sources using Bayesian modelling via the MixSIAR package (3.1.12) in the R programming language. (1) The relatively low NO₃⁻/Cl⁻ ratio and high chloride concentrations in the upstream section indicate that the primary sources of NO₃⁻ in this area are manure and sewage (M&S). (2) Dual isotope analysis of NO₃⁻ indicates that the primary sources of NO₃⁻ in the Songhua River basin are M&S, soil nitrogen (SN), and chemical fertilizers (CF). (3) Nitrification occurs throughout the entire watershed. (4) Model estimation results indicate that SN constitutes the primary source of NO₃⁻ throughout the entire watershed (48%), with no significant variation observed across the studied river sections. However, other major NO₃⁻ sources exhibit spatially significant differences, primarily manifested as follows: M&S constitute the primary upstream source of NO₃⁻ (39%), whilst downstream contributions are predominantly attributable to CF (20%). Intermediate regions experience combined impacts from both MS and CF sources. Full article

Urban development and intensive human activities have led to increasingly prominent nitrogen pollution issues in the Baiyangdian Lake basin. Accurately identifying the sources of nitrate pollution is a crucial prerequisite for implementing targeted remediation strategies, while flooding further complicates this task by exacerbating the transport and mixing of multi-source pollutants within the basin. This study, conducted from August to October 2023 (encompassing flood and post-flood periods), established 20 sampling sites in the lake area and its major inflow rivers. By integrating hydrochemical parameters, nitrate dual-isotope tracers (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻), and the Bayesian mixing model (MixSIAR), we quantitatively revealed the contributions of nitrate sources and their response mechanisms to a major flood event. The results indicate that domestic sewage and livestock wastewater (Manure & Sewage, MS) were the dominant sources of nitrate, with an average contribution of 84.0%, which further increased to 90.3% after the flood. Soil nitrogen was a secondary source (average 12.3%), while contributions from chemical fertilizers and atmospheric deposition were negligible (<4%). The results quantified a flood-driven dynamic response process of the nitrate source structure, characterized by “dilution-mixing-pollution rebound-process transformation”: the initial flood stage (August) showed multi-source mixing; the post-flood period (September) witnessed a rapid rebound of sewage sources; and during the October, nitrification persisted, but the basin’s overall denitrification capacity was limited, indicating a risk of nitrogen accumulation. Spatially, rivers like the Fu River were identified as key input pathways. This study revises the traditional understanding by emphasizing the absolute dominance of sewage sources after extreme hydrological events and the risk of insufficient denitrification capacity. The findings provide a scientific basis for water quality management in Baiyangdian and similar lakes. Full article

Biomass of the plumose anemone Metridium senile has surged in the benthic ecosystem of the North Yellow Sea in recent years. Understanding its diet and the proportional contributions of food sources is essential for assessing the ecological consequences of this expansion. The species is often characterized as a passive suspension feeder, yet laboratory feeding trials have documented shrimp consumption. Because prior dietary information from the region is scarce, conventional stable isotope approaches are poorly constrained. We developed an integrative framework coupling trophic position estimation, isotopic niche metrics, spatial point pattern analysis, and a Bayesian mixing model to improve diet attribution under limited prior information and to test whether M. senile preys on small-bodied and juvenile teleosts and invertebrates under natural conditions. Our analyses showed that: (i) M. senile occupied a high trophic position (TP = 3.09 ± 0.25), exceeding those estimated for putative predators in our dataset, implying weak top-down control; (ii) in isotopic niche analyses, M. senile showed high posterior probabilities of occurring within the niches of cephalopods and medium-sized fishes (78.30% and 63.04%, respectively), consistent with shared prey and inconsistent with a strictly suspension-feeding strategy; (iii) mixing space diagnostics informed by spatial point pattern analysis indicated that including small-sized fishes and shrimps as sources was necessary to reconcile the elevated TP; and (iv) the Bayesian mixing model estimated that small-bodied and juvenile teleosts and invertebrates supplied most long-term nutrition (posterior mean ≈ 0.65), with the remainder from suspension-derived sources, consistent with an opportunistic generalist rather than a strict suspension feeder. Sustained predation on small-bodied and juvenile teleosts and invertebrates could suppress early fish recruitment, impose top-down control on forage species, and alter the local food web structure. Management should monitor M. senile (size structure, population density, and co-occurrence with juveniles and forage biota) and consider targeted removals and seafloor litter cleanups in priority habitats. The framework is applicable to diet studies with limited prior information; adding δ³⁴S, compound-specific amino-acid isotopes (CSIA-AA), and DNA-based dietary evidence should further sharpen source discrimination. Full article

The Ulan Buh Desert represents a quintessential desert ecosystem in the arid northwest of China. As the key factor to maintain the stability of ecosystem, the chemical characteristics of groundwater and its water relationship with vegetation need to be further studied. Through field sampling, hydrochemical analysis, hydrogen and oxygen isotope testing and the Bayesian mixing model (MixSIAR), this study systematically analyzed the chemical characteristics of groundwater, spatial distribution and vegetation water sources in the study area. The results show that the groundwater is predominantly of the Cl⁻–SO₄²⁻ type, with total dissolved solids (TDS) ranging from 0.34 to 9.56 g/L (mean: 2.03 g/L), indicating medium to high salinity and significant spatial heterogeneity. These characteristics are jointly controlled by rock weathering, evaporative concentration, and ion exchange. Soil water isotopes exhibited vertical differentiation: the surface layer (0–20 cm) was significantly affected by evaporative fractionation (δD: −72‰ to −45‰; δ¹⁸O: −9.3‰ to −6.2‰), while deep soil water (60–80 cm) showed isotopic enrichment (δD: −29‰ to −58‰; δ¹⁸O: −6.8‰ to 0.9‰), closely matching groundwater isotopic signatures. Vegetation water use strategies demonstrated depth stratification: shallow-rooted plants such as Reaumuria soongorica and Kalidium foliatum relied primarily on shallow soil water (0–20 cm, >30% contribution), whereas deep-rooted plants such as Nitraria tangutorum and Ammopiptanthus mongolicus predominantly extracted water from the 40–80 cm soil layer (>30% contribution), with no direct dependence on groundwater. Full article

In comparison with conventional hydrological parameters such as water levels and temperatures, geochemical changes induced by earthquakes have become increasingly important. It should be noted that hydrogen (δ²H) and oxygen isotopes (δ¹⁸O) offer the greatest potential as precursor proxies of earthquakes. Here, we conducted high-resolution sampling (weekly, 59 samples), measuring consecutive δ²H and δ¹⁸O levels at the two sites of the WLY well and SS spring in the Yan-Huai Basin of Beijing from June 2021 to June 2022. During the period of this sampling, several small earthquakes of ML > 1.6 occurred in Beijing. We used statistical methods (analysis of variance) to test the significant differences, used Self-Organizing Maps (SOMs) for data clustering, and then used Bayesian Mixing Models (MixSIAR) to calculate the proportions of the source contributions. We found significant four-stage patterns of change processes in δ²H and δ¹⁸O at both sites. The WLY well exhibited a distinct four-stage variation pattern: initial stable development (WT1) followed by a rapid rise (WT2) and sudden fall (WT3) before the small earthquakes, and finally gradual stabilization after earthquakes (WT4). In contrast, the SS spring displayed an inverse pattern, beginning with stable development (ST1), then undergoing a rapid falling (ST2) and sudden rising (ST3) before the small earthquakes, and finally stabilizing through stepwise reduction after the earthquakes (ST4). The most likely mechanisms were differences in the time of rupture between the carbonate in WLY and granite in SS under sustained stress. The stress induced source mixing of fluid from the surface or deeper groundwater-source reservoirs. The hypothesis was supported by the MixSIAR model, calculating the variational proportion of source contributions in the four stages. This work permitted the use of high-resolution isotopic data for statistical confirmation of concomitant shifts during the earthquakes, provided the mechanisms behind them, and highlighted the potential for the consecutive monitoring of hydrogen and oxygen isotopes indicators in earthquake-prediction studies. Full article

Nitrate (NO₃⁻) pollution resulting from anthropogenic activities represents one of the most prevalent environmental issues in karst spring catchments of northern China. In June 2021, a comprehensive study was conducted in the Jinan Spring Catchment (JSC), where 30 groundwater and surface water samples were collected. The sources and spatial distribution of nitrate pollution were systematically investigated through hydrochemical analysis combined with dual-isotope tracing techniques (δ¹⁵N_NO3 and δ¹⁸O_NO3). Analytical results revealed that the predominant anion and cation sequences were HCO₃⁻ > SO₄²⁻ > Cl⁻ > NO₃⁻ and Ca²⁺ > Na⁺ > Mg²⁺ > K⁺, respectively, with HCO₃·SO₄-Ca identified as the primary hydrochemical type. Notably, the average NO₃⁻ concentration in groundwater (46.62 mg/L) significantly exceeded that in surface water (4.96 mg/L). Among the water samples, 11 locations exhibited substantial nitrate pollution, demonstrating an exceedance rate of 42%. Particularly, the NO₃⁻-N concentrations in both the upstream recharge area and downstream drainage area were markedly higher than those in the runoff area. The spatial distribution of NO₃⁻ concentrations was primarily influenced by mixing processes, with no significant evidence of denitrification observed. The isotopic compositions ranged from −1.42‰ to 12.79‰ for δ¹⁵N_NO3 and 0.50‰ to 15.63‰ for δ¹⁸O_NO3. Bayesian isotope mixing model (MixSIAR) analysis indicated that domestic sewage and manure constituted the principal nitrate sources, contributing 37.1% and 56.9% to groundwater and surface water, respectively. Secondary sources included soil organic nitrogen, rainfall and fertilizer NH₄⁺, and chemical fertilizers, while atmospheric deposition showed the lowest contribution rate. Additionally, potential mixing of soil organic nitrogen with chemical fertilizer was identified. Full article

Nitrate contamination poses a significant global environmental threat, impacting the water quality in surface and groundwater systems. Despite its considerable impact, there remains a lack of comprehensive understanding of nitrate sources and discharge patterns, particularly in the Lake Victoria basin of East Africa. To address this gap, a study was conducted in the Kagera River basin, responsible for 33% of Lake Victoria’s surface inflow. This study utilized δ¹⁵N and δ¹⁸O isotope analysis in nitrate, hydrochemistry, and the Bayesian mixing model (MixSIAR) to identify and quantify nitrate sources. Spatiotemporal data were collected across three seasons: long rains, dry season, and short rains, in areas with diverse land uses. Nitrate isotopic data from water and potential sources were integrated into a Bayesian mixing model to determine the relative contributions of various nitrate sources. Notable spatial variations were observed at sampling sites with concentrations ranging from 0.004 to 3.31 mg L⁻¹. Spatially and temporally, δ¹⁵N-NO₃⁻ values ranged from +6.0% to +10.2‰, whereas δ¹⁸O-NO₃⁻ displayed significant spatial differences with mean ranges from −1% to +7‰. MixSIAR analysis revealed important contributions from manure and sewage sources ranging between 49% and 73%. A boron analysis revealed manure was the main source of nitrates in the manure and sewage. These results show that it is necessary to implement improved manure and sewage management practices, especially through proper waste treatment and disposal systems, to enable informed policy decisions to enhance nitrogen management strategies in riparian East Africa, and to safeguard the region’s water resources and ecosystems. Full article

The source of sulfate in the groundwater of karst springs in the northern Taihang Mountains remains unclear due to the influence of multiple factors. To investigate this, 33 sampling points were selected in August 2022 across the exposed, covered, and buried areas of the spring basin, and water samples were collected. Hydrochemistry and sulfur–oxygen dual isotope methods were employed to examine the distribution characteristics of sulfate, δ¹⁸O_SO4, and δ³⁴S_SO4. Based on the distinct characteristics of sulfur isotopes from different sources, the sources of sulfate in various environments were qualitatively analyzed. Additionally, the contribution rates of each source were quantitatively determined using a Bayesian stable isotope mixing model. The results showed that the sulfate content in karst groundwater ranged from 16.68 to 156.84 mg/L, with an average of 62.22 mg/L, and indicated an increasing trend from exposed to covered to buried areas. The δ³⁴S_SO4 values in karst groundwater ranged from 3.1‰ to 13.5‰, with an average of 6.49‰, while the δ¹⁸O_SO4 values ranged from 2.9‰ to 10.3‰, with an average of 5.49‰. The δ³⁴S_SO4 values showed a general increasing trend across the exposed, covered, and buried areas, whereas the δ¹⁸O_SO4 values remained relatively stable across these areas. The analysis revealed that the primary sulfate sources in the exposed area were atmospheric precipitation, soil sulfate, chemical fertilizer, and sewage, contributing 19.6%, 63.5%, 9.4%, and 7.5%, respectively. In the covered area, the main sources were atmospheric precipitation, sulfide oxidation, soil sulfate, and gypsum dissolution, with contributions of 16.5%, 58.7%, 15.9%, and 8.9%, respectively. In the buried area, the sulfate primary originated from atmospheric precipitation, sulfide oxidation, and gypsum dissolution, contributing 11.6%, 78.5%, and 9.9%, respectively. This study provides critical insights into the sulfate sources in different environments, enhancing the understanding of groundwater sulfate pollution in the study area. These findings provide a scientific foundation for managing groundwater pollutants and resources in the karst regions of northern China. Full article

Phosphorus is the primary contributor to eutrophication in water bodies, and identifying phosphorus sources in rivers is crucial for controlling phosphorus pollution and subsequent eutrophication. Although phosphate oxygen isotopes (δ¹⁸O_P) have the capacity to trace phosphorus sources and cycling in water and sediments, they have not been used in small- to medium-sized watersheds, such as the Xiaodongjiang River (XDJ), which is located in an agricultural watershed, source–complex region of southern China. This study employed phosphate oxygen isotope techniques in combination with a land-use-based mixed end-member model and the MixSIAR Bayesian mixing model to quantitatively determine potential phosphorus sources in surface water and sediments. The δ¹⁸O_P values of the surface water ranged from 5.72‰ to 15.02‰, while those of sediment ranged from 10.41‰ to 16.80‰. In the downstream section, the δ¹⁸O_P values of the surface water and sediment were similar, suggesting that phosphate in the downstream water was primarily influenced by endogenous sediment control. The results of the land-use–source mixing model and Bayesian model framework demonstrated that controlling phosphorus inputs from fertilizers is essential for reducing phosphorus emissions in the XDJ watershed. Furthermore, ongoing rural sewage treatment, manure management, and the resource utilization of aquaculture substrates contributed to reduced phosphorus pollution. This study showed that isotope techniques, combined with multi-model approaches, effectively assessed phosphorus sources in complex watersheds, offering a theoretical basis for phosphorus pollution management to prevent eutrophication. Full article

California sea lion (CSL, Zalophus californianus) abundance has declined in different localities across this species’ Mexican distribution. However, Los Islotes rookery in the southwestern Gulf of California (GoC) deviates from this pattern. It is vital to gather ecological knowledge of this CSL settlement and its surroundings to better understand its population in the GoC. This study aimed to determine the foraging habits of different CSL sex and age classes. Sixty-five CSL samples were collected in Los Islotes and its surroundings for stable isotope analysis (δ¹³C and δ¹⁵N). The data were analyzed using a hierarchical Bayesian model, and isotopic areas were estimated using the SIBER package in R. Our findings evidenced resource partitioning. Adult females had lower δ¹⁵N values than most classes, reflecting the regional ¹⁵N-enrichment of the GoC. Conversely, subadult males showed low δ¹⁵N values, carrying foraging information from the ¹⁵N-depleted Pacific Ocean into the GoC. Adult males presented the highest δ¹⁵N values (after pups), suggesting a higher trophic position than adult females and values corresponding to the GoC. Moreover, juveniles had the most negative δ¹³C values and the largest isotopic areas, indicating offshore foraging habits and a mixed consumption of maternal milk and their first prey. Pups showed the highest mean δ¹⁵N value due to maternal milk consumption, reflecting the mother’s δ¹⁵N value and their enrichment. Our findings suggest that segregation is explained by unique life history traits and a possible strategy to avoid potential competition Full article