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At least 145 records · Page 8

Legacy Effects of Intercropping and Nitrogen Fertilization on Soil N Cycling, Nitrous Oxide Emissions, and the Soil Microbial Community in Tropical Maize Production

Maize-forage grasses intercropping systems have been increasingly adopted by farmers because of their capacity to recycle nutrients, provide mulch, and add C to soil. However, grasses have been shown to increase nitrous oxide (N 2 O) emissions. Some tropical grasses cause biological nitrification inhibition (BNI) which could mitigate N 2 O emissions in the maize cycle but the reactions of the N cycle and the microbial changes that explain the N 2 O emissions are little known in such intercropping systems. With this in mind, we explored intercropping of forage grasses ( Brachiaria brizantha and Brachiaria humidicola ) with distinct BNI and yield potential to increase N cycling in no-till maize production systems compared to monocrop with two N rates (0 and 150 kg ha −1 ) applied during the maize season. These grasses did not strongly compete with maize during the period of maize cycle and did not have a negative effect on grain yield. We observed a legacy of these grasses on N mineralization and nitrification through the soil microbiome during maize growth. We observed that B. humidicola , genotype with higher BNI potential, increased net N mineralization by 0.4 mg N kg −1 day −1 and potential nitrification rates by 1.86 mg NO 3 -N kg −1 day −1 , while B. brizantha increased the soil moisture, fungi diversity, mycorrhizal fungi, and bacterial nitrifiers, and reduced saprotrophs prior to maize growth. Their legacy on soil moisture and cumulative organic inputs (i.e., grass biomass) was strongly associated with enhanced mineralization and nitrification rates at early maize season. These effects contributed to increase cumulative N 2 O emission by 12.8 and 4.8 mg N 2 O-N m −2 for maize growing after B. brizantha and B. humidicola , respectively, regardless of the N fertilization rate. Thus, the nitrification inhibition potential of tropical grasses can be outweighed by their impacts on soil moisture, N recycling, and the soil microbiome that together dictate soil N 2 O fluxes.

Canisares, Lucas P.↗

Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil

Abstract. The microbial community composition in subsoils remains understudied, and it is largely unknown whether subsoil microorganisms show a similar response to global warming as microorganisms at the soil surface do. Since microorganisms are the key drivers of soil organic carbon decomposition, this knowledge gap causes uncertainty in the predictions of future carbon cycling in the subsoil carbon pool (> 50 % of the soil organic carbon stocks are below 30 cm soil depth). In the Blodgett Forest field warming experiment (California, USA) we investigated how +4 ∘C warming in the whole-soil profile to 100 cm soil depth for 4.5 years has affected the abundance and community structure of microorganisms. We used proxies for bulk microbial biomass carbon (MBC) and functional microbial groups based on lipid biomarkers, such as phospholipid fatty acids (PLFAs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs). With depth, the microbial biomass decreased and the community composition changed. Our results show that the concentration of PLFAs decreased with warming in the subsoil (below 30 cm) by 28 % but was not affected in the topsoil. Phospholipid fatty acid concentrations changed in concert with soil organic carbon. The microbial community response to warming was depth dependent. The relative abundance of Actinobacteria increased in warmed subsoil, and Gram+ bacteria in subsoils adapted their cell membrane structure to warming-induced stress, as indicated by the ratio of anteiso to iso branched PLFAs. Our results show for the first time that subsoil microorganisms can be more affected by warming compared to topsoil microorganisms. These microbial responses could be explained by the observed decrease in subsoil organic carbon concentrations in the warmed plots. A decrease in microbial abundance in warmed subsoils might reduce the magnitude of the respiration response over time. The shift in the subsoil microbial community towards more Actinobacteria might disproportionately enhance the degradation of previously stable subsoil carbon, as this group is able to metabolize complex carbon sources.

54 ENVIRONMENTAL SCIENCES↗

ERTS-1 MSS imagery: Its use in delineating soil associations and as a base map for publishing soils information

ERTS 1 imagery is a useful tool in the identification and refinement of soil association areas and an excellent base map upon which soil association information can be published. Prints of bands 5 and 7 were found to be most useful to help delineate major soil and vegetation areas. After delineating major soil areas, over 4800 land sale prices covering a period of 1967-72 were located in the soil areas and averaged. The soil association then were described as soil association value areas and published on a 1:1,000,000 scale ERTS mosaic of South Dakota constructed using negative prints of band 7. The map is intended for use by state and county revenue officers, by individual buyers and sellers of land and lending institutions, and as a reference map by those planning road routes and cable lines and pipelines.

Westin, F. C.↗

A multi-frequency measurement of thermal microwave emission from soils: The effects of soil texture and surface roughness

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz during July - September of 1981. Three bare fields with different surface roughnesses and soil textures were prepared for the experiment. Ground truth acquisition of soil temperatures and moisture contents for 5 layers down to the depths of 15 cm was made concurrently with radiometric measurements. The experimental results show that the effect of surface roughness is to increase the soils' brightness temperature and to reduce the slope of regression between brightness temperature and moisture content. The slopes of regression for soils with different textures are found to be comparable, and the effect of soil texture is reflected in the difference of regression line intercepts at brightness temperature axis. The result is consistent with laboratory measurement of soils' dielectric permittivity. Measurements on wet smooth bare fields give lower brightness temperatures at 5 GHz than at 1.4 GHz.

Wang, J. R.↗

A multi-frequency measurement of thermal microwave emission from soils - The effect of soil texture and surface roughness

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz during July September of 1981. Three bare fields with different surface roughneses and soil textures were prepared for the experiment. Ground truth acquisition of soil temperatures and moisture contents for 5 layers down to the depth of 15 cm was made concurrently with radiometric measurements. The experimental results show that the effect of surface roughness is to increase the soils' brightness temperature and to reduce the slope of regression between brightness temperature and moisture content. The slopes of regression for soils with different textures are found to be comparable, and the effect of soil texture is reflected in the difference of regression line intercepts at brightness temperature axis. The result is consistent with laboratory measurement of soils' dielectric permittivity. Measurements on wet smooth bare fields give lower brightness temperatures at 5 GHz than at 1.4 GHz. Previously announced in STAR as N82-24550

Wang, J. R.↗

Effects of soil tillage on the microwave emission of soils

In order to understand the interactions of soil properties and microwave emission better, a series of field experiments were conducted in 1984. Small plots were measured with a truck-mounted passive microwave radiometer operating at 1.4 GHz. These data were collected concurrent with ground observations of soil moisture and bulk density. Treatment effects studied included different soil moisture contents and bulk densities. Evaluations of the data have shown that commonly used models of the dielectric properties of wet soils do not explain the observations obtained in these experiments. This conclusion was based on the fact that the roughness parameters determined through optimization were significantly larger than those observed in similar investigations. These discrepancies are most likely due to the soil structure. Commonly used models assume a homogeneous three phase mixture of soil solids, air and water. Under tilled conditions the soil is actually a two phase mixture of aggregates and voids. Appropriate dielectric models for this tilled condition were evaluated and found to explain the observations. These results indicate that previous conclusions concerning the effects of surface roughness in tilled fields may be incorrect, and they may explain some of the inconsistencies encountered in roughness modeling.

Jackson, T. J.↗

Development of remote sensing techniques capable of delineating soils as an aid to soil survey

Eighty-one benchmark soils from Alabama, Georgia, Florida, Tennessee, and Mississippi were evaluated to determine the feasibility of spectrally differentiating among soil categories. Relationships among spectral properties that occur between soils and within soils were examined, using discriminant analysis. Soil spectral data were obtained from air-dried samples using an Exotech Model 20C field spectroradiometer (0.37 to 2.36 microns). Differentiating among the orders, suborders, great groups, and subgroups using reflectance spectra achieved varying percentages of accuracy. Six distinct reflectance curve forms were developed from the air-dried samples based on the shape and presence or absence of adsorption bands. Iron oxide and organic matter content were the dominant soil parameters affecting the spectral characteristics for differentiating among and between these soils.

Coleman, T. L.↗

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Kim, Edward↗

Hydrobiological Mechanism Controlling the Synergistic Effects of Unsaturated Flow and Soil Organic Matter on the Degradation of Emerging Organic Contaminants in Soils

We report hydrology is a key factor influencing microbial degradation of emerging organic contaminants (EOCs) in soils, but the underlying mechanisms are not clear. In this study, biotic and abiotic column experiments were performed to investigate the removal and degradation of five EOCs in soils with different soil organic matter (SOM) contents under saturated and unsaturated flow conditions. In biotic experiments, 54–90% of bisphenol A (BPA) and 9–22% of ibuprofen (IBU) were removed from the aqueous phase of saturated columns due to adsorption and biodegradation. The biodegradation removed 26–65% of BPA and 1–22% of IBU. Decreasing soil pore water saturation from 100 to 80% increased BPA removal to 97–100% and IBU removal to 42–43% due to increased biodegradation (67–81% for BPA and 36–39% for IBU). No significant removal of BPA and IBU was observed in SOM-removed soils under saturated and unsaturated flow conditions. The desaturation did not influence sorptive losses of BPA (< 27%) and IBU (< 7%), suggesting their negligible adsorption at air–water interfaces but increased biodegradation of BPA and IBU sorbed at SOM–water interfaces. The study shows that soil drying and SOM can synergistically degrade BPA and IBU but have no effect on recalcitrant carbamazepine, tetracycline, and ciprofloxacin.

54 ENVIRONMENTAL SCIENCES↗

1H-NMR characterization of soil dissolved organic matter from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory Terrestrial Ecosystem Science Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM (soil organic matter) decomposition and stabilization. This package contains metabolite data obtained through 1H nuclear magnetic resonance (NMR) spectroscopy on water-extracted soils. Soil samples were collected in 2014/06/03 and 2018/06/04 from 3 replicated paired plots that had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. The following files are included: (1) nmr_h2o_data_raw.csv: raw data, (2) nmr_h2o_data_processed.csv: computed compound concentrations and metadata, (3) nmr_h2o_compound_metadata.csv: compound metadata, (4) nmr_h2o_sample_metadata.csv: sample metadata

1H-NMR (nucleic magnetic resonance) spectroscopy↗

Soil and soil fraction radiocarbon, C and N from the Enriched Background Isotope Study, Oak Ridge National Laboratory, Tennessee, USA

A large accidental 14CO2 release at the Oak Ridge Reservation in Tennessee, USA provided a strong label pulse into adjacent, well-studied oak forests, resulting in highly elevated Δ14C values in leaf litter (~1000‰) and roots (~260–450‰). A four-year manipulative study was conducted to provide insight into mechanisms underlying soil Organic matter dynamics, specifically to determine the relative contribution of litter versus roots to the bulk mineral soil C pool, as well as to free light, occluded light and heavy fractions. The heavy fraction was further split into fractions with densities of 1.7–2.4 g cm-3 and >2.4 g cm-3 to test the homogeneity of the mineral-associated fraction of C. Substantial concentrations of label were detected in all soil fractions within a year of the 14CO2 release, indicating rapid incorporation of newly fixed photosynthates in all fractions of soil organic C, regardless of differences in stability inferred by previous work. This rapid incorporation of label occurred only in treatments where roots were labeled, indicating that roots are the major source of inputs to mineral soil C stocks at these sites. Separation of the heavy fraction into subfractions of intermediate (1.7–2.4 g cm -3) and high (>2.4 g cm-3) density indicated that both subfractions incorporated label at similar rates, despite significant differences in degree of microbial processing.

54 ENVIRONMENTAL SCIENCES↗

High resolution characterization of soil dissolved organic matter with FTICR-MS (Fourier-transform ion cyclotron resonance mass spectrometry) from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.This package contains Fourier transform ion cyclotron resonance mass spectrometry (21 Tesla FTICR-MS) data measured in negative and positive ionization mode from water and methanol soil extracts. Soil samples were collected in 2014/06/03 and 2018/06/04 from 3 replicated paired plots that had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. The following files are included: (1) fticr_neg_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (2) fticr_neg_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (3) fticr_neg_metadata.csv: metadata for samples/measurements in negative ion mode, (4) fticr_pos_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (5) fticr_pos_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (6) fticr_pos_metadata.csv: metadata for samples/measurements in positive ion mode.

54 ENVIRONMENTAL SCIENCES↗

Land use-land cover gradient demonstrates the importance of perennial grasslands with intact soils for building soil carbon in the fertile Mollisols of the North Central US

The impact of land use change and agricultural management on the cycling of soil organic carbon (SOC) is not well understood, limiting our ability to manage for, and accurately model, soil carbon changes at both local and regional scales. To address this issue, here we combined long-term soil incubations with acid-hydrolysis and dry combustion to parse total SOC (C t ) into three operationally defined SOC pools (active, slow, and recalcitrant) from 9 long-term sites with varying land uses on current and former tallgrass prairie soil. Land uses represented a gradient of soil disturbance histories including remnant prairie, restored prairie, grazed pasture, annual crop rotations, and continuous maize. Dry combustion was used to estimate total carbon (C t , physical), while acid hydrolysis of both the active (C a ) and slow (C s ) pools was used to estimate a recalcitrant carbon pool (C r , chemical). Non-linear modeling of CO 2 efflux data from the long-term incubations was then used to estimate C a , and the decomposition rates of both C a and C s (k a and k r , biological). The size of the slow pools C s was then defined mathematically as C t- (C a + C r ). Remnant prairie had the highest C t , while cool-season pasture and a 35-y-old restored prairie had higher C t than the other agricultural systems. All agricultural systems, including pasture, had the highest fraction of C t as C r (~50%), whose mean residence time (MRT) in these soils is ≥500 years (Paul et al., 2001a) demonstrating that this fraction persists, while the more labile fractions were lost over the course of a few months (C a ) to a few decades (C s ) as a result of tillage-intensive agriculture. The two- to four-decade MRT time of C s indicated a pool likely to be more responsive to the 20 to 40 years of land-use practices used at some of the sites. The C s pool was largest in the remnant- and 35-y-old prairies indicating significant C accrual and stabilization compared to the agricultural ecosystems. Interestingly, the remnant prairie maintained the highest C a pool as well, demonstrating the strong connection between the quantity of fresh C inputs and the potential for long-term C stabilization and accrual. The accumulation of C in active (≈labile) pools as a first step toward long-term stabilization highlights the tenuous nature of early carbon gains, which can be quickly lost in response to climate change or poor management.

54 ENVIRONMENTAL SCIENCES↗

Comparison of automated chemical-guided segmentation and human annotation of soil organic matter in X-ray microcomputed tomography imaging in contrasted soil types

Soil organic matter (OM) formation and persistence is strongly influenced by the spatial distribution of organic substrates and microscale soil heterogeneity by dictating OM accessibility to microorganisms. However, traditional size and/or density fractionation techniques disrupt aggregate architecture, eliminating spatial information needed to fully understand intra-aggregate OM distribution. To quantify three-dimensional OM spatial distribution and automate segmentation in X-ray microcomputed tomography (µCT) imaging without human annotation bias, we developed an iodine gas vapor (I2) based staining workflow that eliminates labor-intensive manual annotation while maintaining segmentation accuracy, using aggregates from four taxonomically diverse soils (Xerofluvent, Haploxeroll Sphagnofibrist, Palehumult) with an 8-fold range of soil organic carbon. Human annotation of 10 µCT slices by the experienced and inexperienced annotators resulted in variations up to 3% in the Dice similarity coefficient (DSC), reflecting a degree of inherent subjectivity of manual labeling. Such inconsistencies are expected to compound as the number of manually annotated slices increases. Dual-energy µCT imaging at 33.1 keV (below the iodine (I) K-edge) and 33.2 keV (above the I K-edge) was used to resolve aggregate microstructure following I2 staining. The automated image subtraction pipeline identified OM regions by the I Kedge induced brightness increases, achieving DSC values of 0.58–0.83 relative to an experienced annotator. Sensitivity analyses revealed that the reconstruction alpha value—optimized via the open-source tool TomocuPy—and the 3D registration slice count were the primary determinants of accuracy, providing a novel benchmark for dual-energy soil imaging. The pipeline without GPU acceleration achieved 9.6 to 43.2 times faster than manual annotation. Using GPU-accelerated image post-processing and affine transformation matrices, the pipeline successfully segmented OM elements for large-scale datasets (3232×3232 pixel, 2048 slices) within ~5200 s from raw file acquisition to segmented output. The high-throughput approach enables the quantification of OM spatial distribution across diverse and heterogeneous soil.

Soil microbial biomass↗

A holistic framework integrating plant-microbe-mineral regulation of soil bioavailable nitrogen

Abstract Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Environmental Sciences & Ecology↗

Enhancing climate-smart crop performance in arid agrivoltaics systems: effects of photovoltaic shading and soil amendments on tepary bean growth, yield, and associated soil microbiome

As climate change expands the world’s arid and semiarid regions, sustainable systems that integrate food and energy production are becoming increasingly critical. Agrivoltaics—co-locating crops with photovoltaic (PV) panels—offers a dual land-use strategy that mitigates environmental stress by shading crops, conserving soil moisture, and enhancing PV efficiency. While climate-smart crops like the tepary bean ( Phaseolus acutifolius ) are well adapted to heat and drought, little is known about how these crops and their associated soil microbiomes respond to the unique microclimates created by PV shading. This study evaluated tepary bean performance and plant–microbial interactions under PV-shade vs. no shade across three soil amendment treatments at two experimental sites. We assessed plant traits including germination, phenology, biomass, height, as well as yield and bean morphology, alongside shifts in soil microbial composition and functional potential. Plants grown under PV-shade were generally taller, with extended reproductive periods and higher yields: 42% of shaded plants produced beans compared to only 8% under full sun. Shaded plants also produced rounder, higher-quality beans, whereas non-shaded plants yielded flatter, less developed beans. Microbial community composition was more strongly influenced by amendment and site conditions than by shading alone. Key microbial taxa (e.g., Glomeromycetes, Desulfobacterota ) and predicted functions (e.g., denitrification, nitrogen-respiration, sulfate reduction) were associated with differences in plant performance. Finally, combining agrivoltaic systems with targeted soil amendments can enhance crop yield and soil microbial functionality—offering a promising strategy for sustainable agriculture in arid landscapes.

14 SOLAR ENERGY↗

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. A systematic evaluation of the interaction between coastal catchment properties and carbon dioxide (CO2) emission by soil respiration is significant for assessing carbon dynamics and predicting the future trajectory of atmospheric CO2 concentrations in coastal TAIs. The soil CO2 efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation index (kNDVI), climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, there is no one-size-fits-all approach to modeling carbon fluxes in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

54 ENVIRONMENTAL SCIENCES↗