Transition in the isotopic signatures of fatty-acid soil biomarkers under changing land use: Insights from a multi-decadal chronosequence

A Novel Method to Determine the Carbon Isotopic Composition of Inositol Hexaphosphate (Phytate) in Soil by Gas Chromatography-Combustion-Isotope Ratio Mass Spectrometry

RATIONALE

Understanding the decomposition of inositol hexaphosphate (phytate), the dominant form of organic phosphorus (OP) in soil, is vital for studying phosphorus (P) cycling in terrestrial ecosystems. However, the lack of multiple stable P isotopes complicates the study of phytate dynamics under natural conditions and over long periods.

METHODS

A novel method is presented to determine the carbon isotopic composition of inositol in phytate using compound-specific isotope analysis. For this purpose, phytate was extracted from soil and purified via ion exchange chromatography, followed by dephosphorylation, derivatization, and analysis using GC-MS and GC-C-IRMS. Pure compounds were also analyzed to assess protocol efficiency, identify isotopic fractionations, and apply isotopic corrections due to derivatization.

RESULTS

Phytate extracted from soil samples was identified using GC-MS chromatograms. Replicate analyses of the pure compounds indicated that the protocol is highly reproducible. The carbon isotopic composition (δ13C) showed a high reproducibility, with values varying by less than 0.5‰ and with no detectable isotopic fractionation during sample preparation. The δ13C values of phytate in soil samples reflected the dominant vegetation type (C3 or C4) growing at the study site.

CONCLUSIONS

This study offers a novel approach of determining δ13C values of inositol of phytate in environmental samples, offering new opportunities to investigate and quantify OP dynamics based on stable carbon isotopes.

The spatio-temporal variability of soil microplastic distribution and erosion-induced microplastic export under extreme rainfall event using sediment fingerprinting and 7Be in intensive agricultural catchment

Intensive agricultural production and land management often lead to soil microplastics (MPs) accumulation and aggravated erosion consequently polluting water bodies. However, little is known about the occurrence and migration of soil MPs induced by soil erosion at the catchment scale. This study firstly reported the spatio-temporal variability in soil MPs distribution, and erosion-induced microplastic export loads under extreme rainfall events in an intensive agricultural catchment. The results indicated that microplastic abundance peaked in November 2022 and varied by land use types, among which cropland converted from forest (C(F)) and crop farmland (C) had the highest abundance, vegetable farmland (V) had the lowest abundance on average. Most MPs were < 500 μm and the primary polymers were polyamide (PA), polypropylene (PP) and polyethylene (PE). Sediment contribution and microplastic export loads were identified using compound specific stable isotope and Berillium-7 under an extreme rainfall event. F and C(F) were merged because their δ13C values were non-distinguishable and were identified as the primary sediment source (50.14 ± 0.27 %), contributing most to microplastic export loads due to land management policy shifting. Changed land uses should be the main focus for catchment erosion control and microplastic pollution prevention in intensive agriculture in China and elsewhere.

Land management policy shift influenced seasonal variation of erosion-induced nitrogen and phosphorus outputs from intensive agricultural catchment

A shift in policy to intensive agricultural production and land management often leads to excessive fertilizer application and accelerated erosion with consequent detrimental effects to water bodies. We investigated the impact of that shift by quantifying the spatial and temporal change in sediment sources and associated total nitrogen (TN) and total phosphorus (TP) pollutants output loads in an intensive agricultural catchment in North China across one year (November 2021-November 2022). We describe the implications of this work for intensive agriculture elsewhere in China and other countries. Seasonal sediment source apportionment was estimated at the catchment outlet using Berillium-7 (7Be) combined with compound-specific stable isotope (CSSI) signatures from sources and sediments. Diagnostic 'fingerprints' in MixSIAR were used to discriminate sediment sources between forest and crop farmland converted from forest (F + C(F)), crop farmland (C), and vegetable farmland (V). Our study identified F + C(F) as the dominant sediment source (mean 55.24 ± 2.91 %), intermediate on V (mean 30.06 ± 2.20 %), and least on C (mean 14.70 ± 2.13 %). Sedimentation ranged from 37.98 ± 3.02 to 89.60 ± 12.68 t·ha-1·event-1 and coincided with shifted land use policy and rainfall distribution. The TN and TP in sediment were both mainly derived from F + C(F) (averaged 22.27 ± 4.26 t·event-1 and 11.62 ± 2.28 t·event-1) and least from V (averaged 1.63 ± 0.29 and 2.09 ± 0.33 t·event-1). Despite being a significant sediment source, V contributed little sediment TN and TP input for eutrophication. Our findings imply that F + C(F) are diffuse sources of catchment pollution over the short term. These results describe the successful use of CSSI and 7Be to cost-effectively quantify the seasonal variation of sediment TN and TP loads from land-use-specific sources in the catchment under shifting land management policy in China with potential for use elsewhere. These findings enable soil conservation strategies and land management practices optimized for implementing targeted pollutant abatement initiatives in intensive agriculture in China and elsewhere.

Impacts of tracer type, tracer selection, and source dominance on source apportionment with sediment fingerprinting

Sediment fingerprinting estimates the proportional contribution of fine sediment from distinct catchment sources delivered to downstream receiving environments. Increased attention has focused on assessing the accuracy of source contribution estimates, particularly in relation to tracer selection and statistical un-mixing procedures. However, no studies have systematically tested the impact of source combination or dominance on the accuracy of source estimates. Here, we assess sensitivity to tracer type, selection, and number of sources, and examine how variations in the dominant sediment source affect the accuracy of source apportionments using numerical mixtures. Sources were sampled according to erosion process and land cover from a New Zealand catchment. Topsoil and subsoil (landslide) samples were collected from pasture, harvested pine, kānuka scrub, and native forest, while banks were sampled along the main channel. Samples were analysed for bulk geochemistry, fallout radionuclides, and compound specific stable isotopes (CSSIs). Source apportionment accuracy tended to decrease as source number increased, which reflected decreasing source discrimination. Tracer selection showed variations in accuracy but exhibited no clear pattern overall. Source combination and particularly the dominant source had the largest impact on accuracy, reflecting the level of discrimination for each source. Notably, channel bank was frequently identified as the dominant source when using CSSI tracers. While this partly reflected lower levels of discrimination, the CSSI apportionment was particularly sensitive to the use of post-unmixing corrections routinely applied to derive soil proportional contributions from isotopic proportions. This sensitivity likely related to the low organic carbon content in bank material and the assumption that source apportionments based on isotopic proportions can be corrected using a linear relationship with organic carbon content. These results indicate that the use of CSSI tracers in catchments where erosion sources exhibit large differences in soil organic carbon content may introduce significant unquantified error in source apportionments.