@article{sakin_yanardağ_ramazanoglu_dari_sihi_2024, title={Biochar applications and enzyme activity, carbon dioxide emission, and carbon sequestration in a calcareous soil}, url={https://doi.org/10.1080/01904167.2024.2354215}, DOI={10.1080/01904167.2024.2354215}, journal={Journal of Plant Nutrition}, author={Sakin, Erdal and Yanardağ, İbrahim Halil and Ramazanoglu, Emrah and Dari, Biswanath and Sihi, Debjani}, year={2024}, month={May} }
 @article{wang_kumar_weintraub‐leff_todd‐brown_mishra_sihi_2024, title={Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning}, url={https://doi.org/10.1029/2023JG007702}, DOI={10.1029/2023JG007702}, abstractNote={Abstract Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose a framework that combines unsupervised multivariate geographic clustering (MGC) and supervised Random Forests regression, improving SOC maps by capturing heterogeneous relationships with SOC drivers. We first used MGC to divide the U.S. into 20 SOC regions based on the similarity of covariates (soil biogeochemical, bioclimatic, biological, and physiographic variables). Subsequently, separate Random Forests models were trained for each SOC region, utilizing environmental covariates and SOC observations. Our estimated SOC stocks for the U.S. (52.6 ± 3.2 Pg for 0–30 cm and 108.3 ± 8.2 Pg for 0–100 cm depth) were within the range estimated by existing products like Harmonized World Soil Database, HWSD (46.7 Pg for 0–30 cm and 90.7 Pg for 0–100 cm depth) and SoilGrids 2.0 (45.7 Pg for 0–30 cm and 133.0 Pg for 0–100 cm depth). However, independent validation with soil profile data from the National Ecological Observatory Network showed that our approach ( R 2 = 0.51) outperformed the estimates obtained from Harmonized World Soil Database ( R 2 = 0.23) and SoilGrids 2.0 ( R 2 = 0.39) for the topsoil (0–30 cm). Uncertainty analysis (e.g., low representativeness and high coefficients of variation) identified regions requiring more measurements, such as Alaska and the deserts of the U.S. Southwest. Our approach effectively captures the heterogeneous relationships between widely available predictors and the current SOC baseline across regions, offering reliable SOC estimates at 1 km resolution for benchmarking Earth system models.}, journal={Journal of Geophysical Research: Biogeosciences}, author={Wang, Zhuonan and Kumar, Jitendra and Weintraub‐Leff, Samantha R. and Todd‐Brown, Katherine and Mishra, Umakant and Sihi, Debjani}, year={2024}, month={Feb} }
 @article{hu_hartemink_desai_townsend_abramoff_zhu_sihi_huang_2023, title={A Continental‐Scale Estimate of Soil Organic Carbon Change at NEON Sites and Their Environmental and Edaphic Controls}, url={https://doi.org/10.1029/2022JG006981}, DOI={10.1029/2022JG006981}, abstractNote={Abstract Current carbon cycle models focus on the effects of climate and land‐use change on primary productivity and microbial‐mineral dependent carbon turnover in the topsoil, while less attention has been paid to vertical soil processes and soil‐dependent response to land‐use change along the profile. In this study, a spatial‐temporal analysis was used to estimate soil organic carbon (SOC) change in topsoil/A horizon and subsoil/B horizon at National Ecological Observatory Network (NEON) sites, USA over 30 years. To separate the effects of land‐use, environmental, and edaphic factors on SOC change, space‐for‐time substitution was used in combination with the Continuous Change Detection and Classification algorithm and Structural Equation Modeling. Results showed that (a) under natural vegetation, Spodosols and Inceptisols found in the eastern NEON sites had substantial topsoil SOC accumulation (+0.4 to +1.2 Mg C ha −1 year −1 ), while Inceptisols and Andisols in the west had a comparable magnitude of topsoil SOC loss (−0.5 to −1.8 Mg C ha −1 year −1 ); (b) Mollisols and Alfisols in the Central Plains sites were susceptible to significant SOC loss under farming and grazing; (c) Runoff/erosion and leaching potential, vertical translocation, and mineral sorption were the most important factors controlling SOC variation across the NEON sites. Our work could be used to parameterize ecosystem models simulating SOC change.}, journal={Journal of Geophysical Research: Biogeosciences}, author={Hu, Jie and Hartemink, Alfred E. and Desai, Ankur R. and Townsend, Philip A. and Abramoff, Rose Z. and Zhu, Zhe and Sihi, Debjani and Huang, Jingyi}, year={2023}, month={May} }
 @article{lacroix_aeppli_boye_brodie_fendorf_keiluweit_naughton_noël_sihi_2023, title={Consider the Anoxic Microsite: Acknowledging and Appreciating Spatiotemporal Redox Heterogeneity in Soils and Sediments}, url={https://doi.org/10.1021/acsearthspacechem.3c00032}, DOI={10.1021/acsearthspacechem.3c00032}, abstractNote={Reduction-oxidation (redox) reactions underlie essentially all biogeochemical cycles. Like most soil properties and processes, redox is spatiotemporally heterogeneous. However, unlike other soil features, redox heterogeneity has yet to be incorporated into mainstream conceptualizations of soil biogeochemistry. Anoxic microsites, the defining feature of redox heterogeneity in bulk oxic soils and sediments, are zones of oxygen depletion in otherwise oxic environments. In this review, we suggest that anoxic microsites represent a critical component of soil function and that appreciating anoxic microsites promises to advance our understanding of soil and sediment biogeochemistry. In sections 1 and 2, we define anoxic microsites and highlight their dynamic properties, specifically anoxic microsite distribution, redox gradient magnitude, and temporality. In section 3, we describe the influence of anoxic microsites on several key elemental cycles, organic carbon, nitrogen, iron, manganese, and sulfur. In section 4, we evaluate methods for identifying and characterizing anoxic microsites, and in section 5, we highlight past and current approaches to modeling anoxic microsites. Finally, in section 6, we suggest steps for incorporating anoxic microsites and redox heterogeneities more broadly into our understanding of soils and sediments.}, journal={ACS Earth and Space Chemistry}, author={Lacroix, Emily M. and Aeppli, Meret and Boye, Kristin and Brodie, Eoin and Fendorf, Scott and Keiluweit, Marco and Naughton, Hannah R. and Noël, Vincent and Sihi, Debjani}, year={2023}, month={Sep} }
 @article{weintraub‐leff_hall_craig_sihi_wang_hart_2023, title={Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale}, url={https://doi.org/10.1029/2022EF003224}, DOI={10.1029/2022EF003224}, abstractNote={Abstract Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial–temporal scales. Here, we introduce a continentally distributed, publicly available data set collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. First, we detail the sampling design and methods used to collect and analyze soil inorganic N pool and net flux rate data from 47 terrestrial sites. We address methodological challenges in generating a standardized data set, even for a network using uniform protocols. Then, we evaluate sources of variation within the sampling design and compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2). We observed wide spatiotemporal variation in inorganic N pool sizes and net transformation rates. Site explained the most variation in NEON’s stratified sampling design, followed by plots within sites. Organic horizons had larger pools and net N transformation rates than mineral horizons on a sample weight basis. The majority of sites showed some degree of seasonality in N dynamics, but overall these temporal patterns were not matched by CESM2, leading to poor correspondence between observed and modeled data. Looking forward, these data can reveal new insights into controls on soil N cycling, especially in the context of other environmental data sets provided by NEON, and should be leveraged to improve predictive modeling of the soil N cycle.}, journal={Earth's Future}, author={Weintraub‐Leff, Samantha R. and Hall, Steven J. and Craig, Matthew E. and Sihi, Debjani and Wang, Zhuonan and Hart, Stephen C.}, year={2023}, month={May} }
 @article{wang_kumar_weintraub-leff_todd-brown_mishra_sihi_2023, title={Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning}, url={https://doi.org/10.22541/essoar.168881822.23298383/v1}, DOI={10.22541/essoar.168881822.23298383/v1}, abstractNote={Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose an upscaling framework that combines unsupervised multivariate geographic clustering (MGC) and supervised random forest regression, improving SOC maps by capturing heterogeneous relationships with SOC drivers. We first used MGC to divide the U.S. into 20 SOC regions based on the similarity of covariates (soil biogeochemical, bioclimatic, biological, and physiographic variables). Subsequently, separate random forest models were trained for each SOC region, utilizing environmental covariates and SOC observations. Our estimated SOC stocks for the U.S. (52.6 + 3.2 Pg for 0-30 cm and 108.3 + 8.2 Pg 0-100 cm depths) were within the range estimated by existing products like HWSD (46.7 Pg for 0-30 cm and 90.7 Pg 0-100 cm depth) and SoilGrids 2.0 (45.7 Pg for 0-30 cm and 133.0 Pg 0-100 cm depth). However, independent validation with soil profile data from the National Ecological Observatory Network showed that our approach (R2 = 0.51) outperformed the estimates obtained from Harmonized World Soil Database (R2 = 0.23) and SoilGrids 2.0 (R2 = 0.39) for the topsoil (0-30 cm). Uncertainty analysis (e.g., low representativeness and high coefficients of variation) identified regions requiring more measurements, such as Alaska and the deserts of the U.S. Southwest. Our approach effectively captures the heterogenous relationships between widely available predictors and SOC across regions, offering reliable gridded SOC estimates for benchmarking Earth system models.}, author={Wang, Zhuonan and Kumar, Jitendra and Weintraub-Leff, Samantha Rose and Todd-Brown, Katherine and Mishra, Umakant and Sihi, Debjani}, year={2023}, month={Jul} }
 @article{sihi_gerber_2021, title={Challenges of using microbial explicit models for evaluating organic matter decomposition in predominantly organic soils&#160;}, url={https://doi.org/10.5194/ismc2021-57}, DOI={10.5194/ismc2021-57}, abstractNote={<p class=&quot;rolelistitem&quot;>Models of soil organic matter (SOM) decomposition are critical for predicting the fate of soil carbon (and nutrient) under changing climate. Traditionally, models have used a simple set-up where the substrate is divided into conceptual pools to represent their resistance to microbial degradation, and decomposition rates are often proportional to the amount of substrate in each pool. Emerging models now consider explicit microbial dynamics and show that SOM loss under warming may be fundamentally different from the classical models. Microbial explicit models use reaction kinetics, represented on a concentration basis. However, when the substrate makes up most of the volume of soils (e.g., the organic horizon in forest soils or peat), an increase or decrease in SOM does not, or only very little, affect concentrations of microbes and substrate. Consequently, reduction in SOM does not reduce the amount of substrate the microbial biomass encounters. This problem does not occur in classical models like CENTURY. We incorporated the effect of organic matter on soil volume in several microbial models. If microbes are solely limited by enzymes, organic soils or peats are decomposed very quickly as there is no mechanism that stops the positive feedback between microbial growth and SOM concentration until the substrate is gone. Alternative formulations that account for carbon limitation or microbial &#8216;cannibalism&#8217; display a sweet spot of soil carbon concentration. Interestingly, a response to warming will depend on the amount of organic vs. mineral materials. Apparent Q<sub>10</sub> was higher in fully organic soil than in mineral soils, which was pronounced when small to moderate amounts of the mineral matter was present that diluted the substrate for microbes. We suggest that model formulations need to be clear about the assumption in key processes, as each of the steps in the cascade of biogeochemical reaction can produce surprising results.</p>}, author={Sihi, Debjani and Gerber, Stefan}, year={2021}, month={Apr} }
 @article{renchon_drake_macdonald_sihi_hinko‐najera_tjoelker_arndt_noh_davidson_pendall_2021, title={Concurrent Measurements of Soil and Ecosystem Respiration in a Mature Eucalypt Woodland: Advantages, Lessons, and Questions}, volume={126}, url={http://dx.doi.org/10.1029/2020jg006221}, DOI={10.1029/2020jg006221}, abstractNote={Abstract Understanding seasonal and diurnal dynamics of ecosystem respiration (R eco ) in forests is challenging, because R eco can only be measured directly during night‐time by eddy‐covariance flux towers. R eco is the sum of soil respiration (R soil ) and above‐ground respiration (in theory, R AG = R eco − R soil ). R soil can be measured day and night and can provide a check of consistency on R eco , as the difference in magnitude and time dynamic between R eco and R soil should be explained by R AG . We assessed the temporal patterns and climatic drivers of R soil and R eco in a mature eucalypt woodland, using continuous measurements (only at night for R eco ) at half‐hourly resolution over 4 years (2014–2017). Our data showed large seasonal and diurnal (overnight) variation of R eco , while R soil had a low diurnal amplitude and their difference (R eco − R soil, or R AG ) had a low seasonal amplitude. This result implies at first glance that seasonal variation of R eco was mainly influenced by R soil while its diurnal variation was mainly influenced by R AG . However, our analysis suggests that the night‐time R eco decline cannot realistically be explained by a decline of R AG . Chamber measurements of autotrophic components at half‐hourly time resolution are needed to quantify how much of the R eco decline overnight is due to declines in leaf or stem respiration, and how much is due to missing storage or advection, which may create a systematic bias in R eco measurements. Our findings emphasize the need for reconciling bottom‐up (via components measured with chambers) and direct estimates of R eco (via eddy‐covariance method).}, number={3}, journal={Journal of Geophysical Research: Biogeosciences}, publisher={American Geophysical Union (AGU)}, author={Renchon, A. A. and Drake, J. E. and Macdonald, C. A. and Sihi, D. and Hinko‐Najera, N. and Tjoelker, M. G. and Arndt, S. K. and Noh, N. J. and Davidson, E. and Pendall, E.}, year={2021}, month={Mar} }
 @article{raj_mandal_golui_sihi_dari_kumari_ghosh_ganguly_2021, title={Determination of Suitable Extractant for Estimating Plant Available Arsenic in Relation to Soil Properties and Predictability by Solubility-FIAM}, volume={232}, url={http://dx.doi.org/10.1007/s11270-021-05215-y}, DOI={10.1007/s11270-021-05215-y}, abstractNote={Abstract Extractant for estimating plant available arsenic (As) in soil has not been universally established. Moreover, to assess and monitor the complex chemical behaviour of arsenic (As) in soil and subsequently its transfer in crops, a suitable extraction protocol considering the soil properties in relation to crop uptake is required. For this purpose, a pot experiment was conducted to evaluate the suitability of the extractants for determination of extractable As in soil and risk assessment by solubility-free ion activity model (FIAM) with rice (variety: Sushk Samrat) as the test crop. Soil in bulk was collected from six locations of Indo-Gangetic Plain of Bihar, India, varying in physicochemical properties to conduct the pot experiment using five doses of As (0, 10, 20, 40 and 80 mg kg −1 ). Six extractants namely 0.2 (M) NH 4 -oxalate, 0.05 (N) HCl + 0.025 (N) H 2 SO 4 , 0.5 (M) KH 2 PO 4 , 0.5 (N) NH 4 F, 0.5 (M) NaHCO 3 and 0.5 (M) EDTA were used. The results revealed that 0.5 (M) KH 2 PO 4 gave the best correlation with the soil properties and crop uptake and can be considered a suitable extractant of As. Regardless of the As dose and the soil type used, in rice tissue, concentration of As followed the order root > straw > leaf and grain. As high as 94% variation in As content in rice grain could be explained, when 0.5 (M) KH 2 PO 4 extractable As is being used as input for solubility-FIAM. Extractable As cannot be determined by atomic absorption spectrophotometer (AAS) coupled with vapour generation accessory (VGA) when 0.5 (M) EDTA was used as an extractant.}, number={6}, journal={Water, Air, & Soil Pollution}, publisher={Springer Science and Business Media LLC}, author={Raj, Akanksha and Mandal, Jajati and Golui, Debasis and Sihi, Debjani and Dari, Biswanath and Kumari, Preety Bala and Ghosh, Mainak and Ganguly, Pritam}, year={2021}, month={Jun} }
 @article{nagy_balch_bissell_cattau_glenn_halpern_ilangakoon_johnson_joseph_marconi_et al._2021, title={Harnessing the NEON data revolution to advance open environmental science with a diverse and data‐capable community}, volume={12}, url={http://dx.doi.org/10.1002/ecs2.3833}, DOI={10.1002/ecs2.3833}, abstractNote={Abstract It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building.}, number={12}, journal={Ecosphere}, publisher={Wiley}, author={Nagy, R. Chelsea and Balch, Jennifer K. and Bissell, Erin K. and Cattau, Megan E. and Glenn, Nancy F. and Halpern, Benjamin S. and Ilangakoon, Nayani and Johnson, Brian and Joseph, Maxwell B. and Marconi, Sergio and et al.}, year={2021}, month={Dec} }
 @article{hollinger_davidson_fraver_hughes_lee_richardson_savage_sihi_teets_2021, title={Multi‐Decadal Carbon Cycle Measurements Indicate Resistance to External Drivers of Change at the Howland Forest AmeriFlux Site}, volume={6}, url={http://dx.doi.org/10.1029/2021jg006276}, DOI={10.1029/2021jg006276}, abstractNote={Abstract A long‐standing goal of ecology has been to understand the cycling of carbon in forests. This has taken on new urgency with the need to address a rapidly changing climate. Forests serve as long‐term stores for atmospheric CO 2 , but their continued ability to take up new carbon is dependent on future changes in climate and other factors such as age. We have been measuring many aspects of carbon cycling at an unmanaged evergreen forest in central Maine, USA, for over 25 years. Here we use these data to address questions about the magnitude and control of carbon fluxes and quantify flows and uncertainties between the different pools. A key issue was to assess whether recent climate change and an aging tree population were reducing annual C storage. Total ecosystem C stocks determined from inventory and quantitative soil pits were about 23,300 g C m −2 with 46% in live trees, and 48% in the soil. Annual biomass increment in trees at Howland Forest averaged 161 ± 23 g C m −2 yr −1 , not significantly different from annual net ecosystem production (NEP = −NEE) of 211 ± 40 g C m −2 y −1 measured by eddy covariance. Unexpectedly, there was a small but significant trend of increasing C uptake through time in the eddy flux data. This was despite the period of record including some of the most climate‐extreme years in the last 125. We find a surprising lack of influence of climate variability on annual carbon storage in this mature forest.}, journal={Journal of Geophysical Research: Biogeosciences}, publisher={American Geophysical Union (AGU)}, author={Hollinger, D. Y. and Davidson, E. A. and Fraver, S. and Hughes, H. and Lee, J. T. and Richardson, A. D. and Savage, K. and Sihi, D. and Teets, A.}, year={2021}, month={Jun} }
 @article{jha_kankarla_mclennon_pal_sihi_dari_diaz_nocco_2021, title={Per- and Polyfluoroalkyl Substances (PFAS) in Integrated Crop–Livestock Systems: Environmental Exposure and Human Health Risks}, volume={18}, url={http://dx.doi.org/10.3390/ijerph182312550}, DOI={10.3390/ijerph182312550}, abstractNote={Per- and polyfluoroalkyl substances (PFAS) are highly persistent synthetic organic contaminants that can cause serious human health concerns such as obesity, liver damage, kidney cancer, hypertension, immunotoxicity and other human health issues. Integrated crop-livestock systems combine agricultural crop production with milk and/or meat production and processing. Key sources of PFAS in these systems include firefighting foams near military bases, wastewater sludge and industrial discharge. Per- and polyfluoroalkyl substances regularly move from soils to nearby surface water and/or groundwater because of their high mobility and persistence. Irrigating crops or managing livestock for milk and meat production using adjacent waters can be detrimental to human health. The presence of PFAS in both groundwater and milk have been reported in dairy production states (e.g., Wisconsin and New Mexico) across the United States. Although there is a limit of 70 parts per trillion of PFAS in drinking water by the U.S. EPA, there are not yet regional screening guidelines for conducting risk assessments of livestock watering as well as the soil and plant matrix. This systematic review includes (i) the sources, impacts and challenges of PFAS in integrated crop-livestock systems, (ii) safety measures and protocols for sampling soil, water and plants for determining PFAS concentration in exposed integrated crop-livestock systems and (iii) the assessment, measurement and evaluation of human health risks related to PFAS exposure.}, number={23}, journal={International Journal of Environmental Research and Public Health}, publisher={MDPI AG}, author={Jha, Gaurav and Kankarla, Vanaja and McLennon, Everald and Pal, Suman and Sihi, Debjani and Dari, Biswanath and Diaz, Dawson and Nocco, Mallika}, year={2021}, month={Nov}, pages={12550} }
 @article{jha_ulery_lombard_vanleeuwen_brungard_dari_sihi_2021, title={Portable X-ray Fluorescence (PXRF) Analysis of Total Metal(loid)s and Sequential Extraction of Bioavailable Arsenic in Agricultural Soils of Animas Watershed}, volume={232}, url={https://doi.org/10.1007/s11270-021-05249-2}, DOI={10.1007/s11270-021-05249-2}, abstractNote={Abstract The Animas River provides irrigation water in northwestern New Mexico and the Navajo Nation. Concerns regarding the river water quality arose on August 5, 2015, when approximately 11.35 million liters of heavy metal contaminated water was accidentally released from the Gold King Mine into the Animas River. This study sought to determine the total concentrations of 7 heavy metal(loid)s (As, Pb, and Zn as metals of concern and Fe, Mn, Ca, and Cu as metals of interest) using portable X-ray fluorescence (PXRF) in two agricultural fields and compare these values to Environmental Protection Agency (EPA) regional screening levels (RSL). Total concentrations of 6 out of 7 metals were below the RSL; only As exceeded the soil screening value of 7.07 mg kg −1 at some locations in the agricultural fields. We also determined water-soluble (WS) and exchangeable fractions (Ex) of As that might be available for agricultural crop uptake using sequential extractions. The WS-As ranged from 0.014 to 0.074 mg kg −1 and Ex-As ranged from 0.135 to 0.248 mg kg −1 and thus were less than 1 and 3% of the total As concentration respectively (ranging from 5.62 to 14.79 mg kg −1 ) and not considered a threat for plant tissue accumulation. While the concentrations of As observed in the agricultural fields may have exceeded screening levels, the As was not apparently plant available and its risk to crops was determined to be low.}, number={7}, journal={Water, Air, & Soil Pollution}, publisher={Springer Science and Business Media LLC}, author={Jha, Gaurav and Ulery, April L. and Lombard, Kevin and VanLeeuwen, Dawn and Brungard, Colby and Dari, Biswanath and Sihi, Debjani}, year={2021}, month={Jul} }
 @article{jha_sihi_dari_kaur_nocco_ulery_lombard_2021, title={Rapid and inexpensive assessment of soil total iron using Nix Pro color sensor}, volume={6}, url={https://doi.org/10.1002/ael2.20050}, DOI={10.1002/ael2.20050}, abstractNote={Abstract In this study, an inexpensive Nix Pro (Nix Sensor Ltd.) color sensor was used to develop prediction models for soil iron (Fe) content. Thirty‐eight soil samples were collected from five agricultural fields across the Animas watershed to develop and validate soil Fe prediction models. We used color space models to develop three different parameter sets for Fe prediction with Nix Pro. The different color space sets were used to develop three new predictive models for Nix Pro‐based Fe content against the lab‐based inductively coupled plasma analyzed Fe content. The model performances were assessed using the coefficient of determination, root mean square error, and model p ‐value. Three models (International Commission on Illumination's lightness, ±a axis (redness to greenness), and ± b axis (yellowness to blueness) [CIEL*a*b]; red, green, blue [RGB]; and cyan, magenta, yellow, key [black] [CMYK]) were significant in predicting the Fe content using colorimetric variables with R 2 ranging from 0.79 to 0.81. The mean square prediction error (MSPE) and Kling–Gupta efficiency (KGE) Index were calculated to validate models and CMYK was predicted to be a better model (MSPE = 0.13; KGE = 0.601) than CIEL*a*b and RGB models. The results suggest Nix Pro is useful in predicting soil Fe content.}, number={3}, journal={Agricultural & Environmental Letters}, publisher={Wiley}, author={Jha, Gaurav and Sihi, Debjani and Dari, Biswanath and Kaur, Harpreet and Nocco, Mallika Arudi and Ulery, April and Lombard, Kevin}, year={2021}, month={Jan} }
 @article{baatz_franssen_euskirchen_sihi_dietze_ciavatta_fennel_beck_lannoy_pauwels_et al._2021, title={Reanalysis in Earth System Science: Toward Terrestrial Ecosystem Reanalysis}, volume={59}, url={https://doi.org/10.1029/2020RG000715}, DOI={10.1029/2020RG000715}, abstractNote={Abstract A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation. High computational costs for modeled processes and assimilation algorithms has led to Earth system specific reanalysis products for the atmosphere, the ocean and the land separately. Recent developments include the advanced uncertainty quantification and the generation of biogeochemical reanalysis for land and ocean. Here, we review atmospheric and oceanic reanalyzes, and more in detail biogeochemical ocean and terrestrial reanalyzes. In particular, we identify land surface, hydrologic and carbon cycle reanalyzes which are nowadays produced in targeted projects for very specific purposes. Although a future joint reanalysis of land surface, hydrologic, and carbon processes represents an analysis of important ecosystem variables, biotic ecosystem variables are assimilated only to a very limited extent. Continuous data sets of ecosystem variables are needed to explore biotic‐abiotic interactions and the response of ecosystems to global change. Based on the review of existing achievements, we identify five major steps required to develop terrestrial ecosystem reanalysis to deliver continuous data streams on ecosystem dynamics.}, number={3}, journal={Reviews of Geophysics}, publisher={American Geophysical Union (AGU)}, author={Baatz, R. and Franssen, H. J. Hendricks and Euskirchen, E. and Sihi, D. and Dietze, M. and Ciavatta, S. and Fennel, K. and Beck, H. and Lannoy, G. De and Pauwels, V. R. N. and et al.}, year={2021}, month={Sep} }
 @article{mclennon_dari_jha_sihi_kankarla_2021, title={Regenerative agriculture and integrative permaculture for sustainable and technology driven global food production and security}, volume={7}, url={https://doi.org/10.1002/agj2.20814}, DOI={10.1002/agj2.20814}, abstractNote={Abstract A growing world population and increases in food and energy consumption have placed production agriculture in a difficult situation. The rapid growth in food production through specialized operations such as monoculture cropping systems has aligned to satisfy increases in demand for food and fiber. However, its adverse impacts on natural resources pose huge challenges for the sustainability of food production. The situation is direr for developing countries or rural regions of the world due to the limited resources available to farming communities in these regions. To avoid production agriculture being at the proverbial crossroads we suggest an alternate approach. One that involves the sustainable use of natural resources without adverse environmental impacts by relying less on production inputs whether it be agrochemicals or machineries. We examined the extent to which regenerative agriculture, permaculture, and smart technology have evolved in response to sustainable agricultural production, agricultural decision support system, and overall global food security. Collectively, regenerative agriculture and permaculture are semi‐closed holistic systems approach designed to reduce or eliminate dependence on external inputs (e.g., chemicals) which restores and maintains natural systems (e.g., soil quality, biodiversity, and ecosystem services). We suggest that fully embracing modern regenerative agriculture as well as integrated permaculture will improve soil health, ecosystem biodiversity, land and resource conservation, agricultural sustainability, and food security. Identifying and implementing practices towards regenerative agriculture, integrated permaculture, digital agriculture, and sustainable agricultural management utilizing modern agricultural technologies infused with data science (artificial intelligence [AI] or machine learning [ML]) is critical.}, journal={Agronomy Journal}, publisher={Wiley}, author={McLennon, Everald and Dari, Biswanath and Jha, Gaurav and Sihi, Debjani and Kankarla, Vanaja}, year={2021}, month={Nov} }
 @article{toward a generalizable framework of disturbance ecology through crowdsourced science_2021, volume={9}, url={https://www.frontiersin.org/article/10.3389/fevo.2021.588940}, DOI={10.3389/fevo.2021.588940}, abstractNote={Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably to refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.}, journal={Frontiers in Ecology and Evolution}, year={2021}, pages={76} }
 @article{sihi_dari_yan_sharma_pathak_sharma_nain_2020, title={Assessment of Water Quality in Indo-Gangetic Plain of South-Eastern Asia under Organic vs. Conventional Rice Farming}, volume={12}, url={https://www.mdpi.com/2073-4441/12/4/960}, DOI={10.3390/w12040960}, abstractNote={Water contamination is often reported in agriculturally intensive areas such as the Indo-Gangetic Plain (IGP) in south-eastern Asia. We evaluated the impact of the organic and conventional farming of basmati rice on water quality during the rainy season (July to October) of 2011 and 2016 at Kaithal, Haryana, India. The study area comprised seven organic and seven conventional fields where organic farming has been practiced for more than two decades. Water quality parameters used for drinking (nitrate, NO3; total dissolved solids (TDS); electrical conductivity (EC) pH) and irrigation (sodium adsorption ratio (SAR) and residual sodium carbonate (RSC)) purposes were below permissible limits for all samples collected from organic fields and those from conventional fields over the long-term (~15 and ~20 years). Importantly, the magnitude of water NO3 contamination in conventional fields was approximately double that of organic fields, which is quite alarming and needs attention in future for farming practices in the IGP in south-eastern Asia.}, number={4}, journal={Water}, author={Sihi, Debjani and Dari, Biswanath and Yan, Zhengjuan and Sharma, Dinesh Kumar and Pathak, Himanshu and Sharma, Om Prakash and Nain, Lata}, year={2020}, month={Mar} }
 @article{cosore: a community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data_2020, url={http://dx.doi.org/10.1111/gcb.15353}, DOI={10.1111/gcb.15353}, abstractNote={Abstract Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO 2 flux, commonly though imprecisely termed soil respiration ( R S ), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency R S measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured R S , the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.}, journal={Global Change Biology}, year={2020}, month={Oct} }
 @article{jian_gough_sihi_hopple_bond-lamberty_2020, title={Collar properties and measurement time confer minimal bias overall on annual soil respiration estimates in a global database}, volume={11}, url={http://dx.doi.org/10.1029/2020jg006066}, DOI={10.1029/2020jg006066}, abstractNote={Abstract Measuring the soil‐to‐atmosphere carbon dioxide (CO 2 ) flux (soil respiration, R S ) is important to understanding terrestrial carbon balance and to forecasting climate change. Such measurements are frequently made using measurement collars permanently inserted into the soil surface. However, differences in measurement duration and frequency, as well as collar properties, may lead to biases in the estimation of annual R S . Using a newly updated global R S database (SRDB‐V5), we investigated the annual R S bias associated with five methodological factors: collar height, collar coverage area, collar insertion depth, measurement duration, and measurement frequency. We found that annual R S was negatively correlated with collar insertion depth, consistent with the idea that collar insertion cuts roots and thus reduces R S . Annual R S was also negatively related with collar height and collar coverage area, perhaps because uniform head‐space mixing is difficult to achieve in larger volume chambers; however, these effects were quantitatively small (bias of ~2% to 10% of mean R S ). We found no correlation of measurement duration or measurement frequency with annual R S . These findings suggest that variation in R S methodology generally introduces minimal bias overall. Therefore, compilations of minimally adjusted annual R S measurements provide a reliable resource for synthesis studies, global annual R S modeling, and investigation of how soil carbon responds to climate change.}, journal={Journal of Geophysical Research: Biogeosciences}, publisher={American Geophysical Union (AGU)}, author={Jian, Jinshi and Gough, Christopher and Sihi, Debjani and Hopple, Anya M. and Bond-Lamberty, Ben}, year={2020}, month={Nov} }
 @article{evaluation of residue management practices on barley residue decomposition_2020, url={http://dx.doi.org/10.1371/journal.pone.0232896}, DOI={10.1371/journal.pone.0232896}, abstractNote={Optimizing barley (hordeum vulgare L.) production in Idaho and other parts of the Pacific Northwest (PNW) should focus on farm resource management. The effect of post-harvest residue management on barley residue decomposition has not been adequately studied. Thus, the objective of this study was to determine the effect of residue placement (surface vs. incorporated), residue size (chopped vs. ground-sieved) and soil type (sand and sandy loam) on barley residue decomposition. A 50-day(d) laboratory incubation experiment was conducted at a temperature of 25°C at the Aberdeen Research and Extension Center, Aberdeen, Idaho, USA. Following the study, a Markov-Chain Monte Carlo (MCMC) modeling approach was applied to investigate the first-order decay kinetics of barley residue. An accelerated initial flush of residue carbon(C)-mineralization was measured for the sieved (Day 1) compared to chopped (Day 3 to 5) residues for both surface incorporated applications. The highest evolution of carbon dioxide (CO2)-C of 8.3 g kg-1 dry residue was observed on Day 1 from the incorporated-sieved application for both soils. The highest and lowest amount of cumulative CO2-C released and percentage residue decomposed over 50-d was observed for surface-chopped (107 g kg-1 dry residue and 27%, respectively) and incorporated-sieved (69 g kg-1 dry residue and 18%, respectively) residues, respectively. There were no significant differences in C-mineralization from barley residue based on soil type or its interactions with residue placement and size (p >0.05). The largest decay constant k of 0.0083 d-1 was calculated for surface-chopped residue where the predicted half-life was 80 d, which did not differ from surface sieved or incorporated chopped. In contrast, incorporated-sieved treatments only resulted in a k of 0.0054 d-1 and would need an additional 48 d to decompose 50% of the residue. Future residue decomposition studies under field conditions are warranted to verify the residue C-mineralization and its impact on residue management.}, journal={PLOS ONE}, year={2020}, month={May} }
 @article{measuring, monitoring, and modeling ecosystem cycling_2020, url={http://dx.doi.org/10.1029/2020eo147717}, DOI={10.1029/2020eo147717}, abstractNote={Scientists leverage long-term environmental measurements, emerging satellite observations, and recent modeling advances to examine changes in ecosystem carbon and water cycling.}, journal={Eos}, year={2020}, month={Aug} }
 @article{representing methane emissions from wet tropical forest soils using microbial functional groups constrained by soil diffusivity_2020, volume={2020}, url={https://bg.copernicus.org/preprints/bg-2020-222/}, DOI={10.5194/bg-2020-222}, abstractNote={Abstract. Tropical ecosystems contribute significantly to global emissions of methane (CH4) and landscape topography influences the rate of CH4 emissions from wet tropical forest soils. However, extreme events such as drought can alter normal topographic patterns of emissions. Here we explain the dynamics of CH4 emissions during normal and drought conditions across a catena in the Luquillo Experimental Forest, Puerto Rico. Valley soils served as the major source of CH4 emissions in a normal precipitation year (2016), but drought recovery in 2015 resulted in dramatic pulses in CH4 emissions from all topographic positions. Geochemical parameters including dissolved organic carbon (C) (ridge &gg; slope &gg; valley), acetate (ridge &geq; slope > valley), and soil pH (valley &gg; slope &gg; ridge), and meteorological parameters like soil moisture (valley > slope = ridge) and oxygen (O2) concentrations (slope = ridge > valley) varied across the catena. During the drought, soil moisture decreased in the slope and ridge and O2 concentrations increased in the valley. We simulated the dynamics of CH4 emissions with the Microbial Model for Methane Dynamics-Dual Arrhenius and Michaelis Menten (M3D-DAMM) which couples a microbial functional group CH4 model with a diffusivity module for solute and gas transport within soil microsites. Contrasting patterns of soil moisture, O2, acetate, and associated changes in soil pH with topography regulated simulated CH4 emissions, but emissions were also altered by rate-limited diffusion in soil microsites. Changes in simulated available substrate for CH4 production (acetate, CO2, and H2) and oxidation (O2 and CH4) increased the predicted biomass of methanotrophs during the drought event and methanogens during drought recovery, which in turn affected net emissions of CH4. A variance-based sensitivity analysis suggested that parameters related to acetotrophic methanogenesis and methanotrophy were most critical to simulate net CH4 emissions. This study enhanced the predictive capability for CH4 emissions associated with complex topography and drought in wet tropical forest soils.}, journal={Biogeosciences Discussions}, year={2020}, pages={1–28} }
 @article{sihi_davidson_savage_liang_2020, title={Simultaneous numerical representation of soil microsite production and consumption of carbon dioxide, methane, and nitrous oxide using probability distribution functions}, volume={0}, url={https://doi.org/10.1111/gcb.14855}, DOI={10.1111/gcb.14855}, abstractNote={Production and consumption of nitrous oxide (N2 O), methane (CH4 ), and carbon dioxide (CO2 ) are affected by complex interactions of temperature, moisture, and substrate supply, which are further complicated by spatial heterogeneity of the soil matrix. This microsite heterogeneity is often invoked to explain non-normal distributions of greenhouse gas (GHG) fluxes, also known as hot spots and hot moments. To advance numerical simulation of these belowground processes, we expanded the Dual Arrhenius and Michaelis-Menten model, to apply it consistently for all three GHGs with respect to the biophysical processes of production, consumption, and diffusion within the soil, including the contrasting effects of oxygen (O2 ) as substrate or inhibitor for each process. High-frequency chamber-based measurements of all three GHGs at the Howland Forest (ME, USA) were used to parameterize the model using a multiple constraint approach. The area under a soil chamber is partitioned according to a bivariate log-normal probability distribution function (PDF) of carbon and water content across a range of microsites, which leads to a PDF of heterotrophic respiration and O2 consumption among microsites. Linking microsite consumption of O2 with a diffusion model generates a broad range of microsite concentrations of O2 , which then determines the PDF of microsites that produce or consume CH4 and N2 O, such that a range of microsites occurs with both positive and negative signs for net CH4 and N2 O flux. Results demonstrate that it is numerically feasible for microsites of N2 O reduction and CH4 oxidation to co-occur under a single chamber, thus explaining occasional measurement of simultaneous uptake of both gases. Simultaneous simulation of all three GHGs in a parsimonious modeling framework is challenging, but it increases confidence that agreement between simulations and measurements is based on skillful numerical representation of processes across a heterogeneous environment.}, number={ja}, journal={Global Change Biology}, author={Sihi, Debjani and Davidson, Eric A. and Savage, Kathleen E. and Liang, Dong}, year={2020}, month={Jan} }
 @inbook{soil biogeochemistry_2020, url={http://dx.doi.org/10.1007/978-3-030-31082-0_8}, DOI={10.1007/978-3-030-31082-0_8}, abstractNote={Depending upon type and pedogenic stage, soils are subject to biotic and abiotic interactions of complex nature depending on type, nature and specific properties. Soil biogeochemistry involves the study of elemental cycling as mediated by complex and inseparable interactions between the biotic (living) and abiotic (non-living) components of soils. Human activities have substantially altered biogeochemical cycling of several key elements including carbon, nitrogen, phosphorus, potassium, and other secondary and minor nutrients over the past few decades, which, in turn, had serious environmental consequences. The present chapter outlines the soil biogeochemical investigations conducted within Indian subcontinent in both natural ecosystems and managed agricultural systems and addresses the state-of-the-art in order to understand the undergoing biogeochemical reactions. Here, we sought to clarify complex interactions generally occurred during biogeochemical transformations of an element (or compound) of interest within the type-specific soil. Further, we emphasized the importance of advancing our understanding of feedback loops in soil biogeochemical processes as altered by anthropogenic perturbations in tropical and sub-tropical soils of India. Overall, this chapter is broadly focused on the nutrient cycling, which is followed by more specific topics like “soil microbiology,” “soil biodiversity,” and “soil biotechnology.”}, booktitle={The Soils of India}, year={2020} }
 @article{buchkowski_shaw_sihi_smith_keiser_2019, title={Constraining carbon and nutrient flows in soil with ecological stoichiometry}, volume={7}, url={https://www.frontiersin.org/articles/10.3389/fevo.2019.00382/abstract}, DOI={10.3389/fevo.2019.00382/abstract}, journal={Frontiers in Ecology and Evolution}, publisher={Frontiers}, author={Buchkowski, Robert Walter and Shaw, Alanna N and Sihi, Debjani and Smith, Gabriel R and Keiser, Ashley D}, year={2019}, month={Sep}, pages={382} }
 @article{weintraub_flores_wieder_sihi_cagnarini_gonçalves_young_li_olshansky_baatz_et al._2019, title={Leveraging Environmental Research and Observation Networks to Advance Soil Carbon Science}, volume={0}, url={https://doi.org/10.1029/2018JG004956}, DOI={10.1029/2018JG004956}, abstractNote={Abstract Soil organic matter (SOM) is a critical ecosystem variable regulated by interacting physical, chemical, and biological processes. Collaborative efforts to integrate perspectives, data, and models from interdisciplinary research and observation networks can significantly advance predictive understanding of SOM. We outline how integrating three networks—the Long‐Term Ecological Research with a focus on ecological dynamics, the Critical Zone Observatories with strengths in landscape/geologic context, and the National Ecological Observatory Network with standardized multiscale measurements—can advance SOM knowledge. This integration requires improved data dissemination and sharing, coordinated data collection activities, and enhanced collaboration between empiricists and modelers within and across networks.}, number={ja}, journal={Journal of Geophysical Research: Biogeosciences}, author={Weintraub, Samantha R. and Flores, Alejandro N. and Wieder, William R. and Sihi, Debjani and Cagnarini, Claudia and Gonçalves, Daniel Ruiz Potma and Young, Michael H. and Li, Li and Olshansky, Yaniv and Baatz, Roland and et al.}, year={2019}, month={May} }
 @article{sihi_inglett_inglett_2019, title={Warming rate drives microbial nutrient demand and enzyme expression during peat decomposition}, volume={336}, url={http://www.sciencedirect.com/science/article/pii/S0016706118305792}, DOI={https://doi.org/10.1016/j.geoderma.2018.08.027}, abstractNote={Recent developments of enzyme-based decomposition models highlight the importance of enzyme kinetics with warming, but most modeling exercises are based on studies with a step-wise warming. This approach may mask the effect of temperature in controlling in-situ activities as in most ecosystems the rate of warming is more gradual than these step warming studies. We conducted an experiment to test the effects of contrasting warming rates on the kinetics of carbon (C), nitrogen (N), and phosphorus (P) degradation enzymes in subtropical peat soils. We also wanted to evaluate if the stoichiometry of enzyme kinetics shifts under contrasting warming rates and if so, how does it relate to the stoichiometry in microbial biomass. Contrasting warming rates altered microbial biomass stoichiometry leading to differing patterns of microbial demand for C vs. nutrient (N and P) and enzyme expression following the optimum foraging strategy. Activity (higher Vmax) and efficiency (lower Km) of C acquisition enzymes were greater in the step treatment; however, expressions of nutrient (N and P) acquiring enzymes were enhanced in the ramp treatment at the end of the experiment. In the step treatment, there was a typical pattern of an initial peak in the Vmax and drop in the Km for all enzyme groups followed by later adjustments. On the other hand, a consistent increase in Vmax and decline in Km of all enzyme groups were observed in the ramp treatment. These changes were sufficient to alter microbial identity (as indicated by enzyme Km and biomass stoichiometry) with two apparently different endpoints under contrasting warming rates. This observation resembles the concept of alternate stable states and highlights a need for improved representation of warming effects on enzymes in decomposition models. Using peat soils of Florida Everglades, here we have demonstrated that contrasting warming rates can influence the dynamics of microbial and enzymatic kinetics. Hence, we suggest that future laboratory and field warming studies could consider our approach to accurately represent microbial and enzymatic kinetics in biogeochemical models.}, journal={Geoderma}, author={Sihi, Debjani and Inglett, Patrick W. and Inglett, Kanika S.}, year={2019}, pages={12–21} }
 @article{sihi_inglett_inglett_2019, title={Warming rate drives microbial nutrient demand and enzyme expression during peat decomposition}, volume={336}, url={https://publons.com/publon/2869098/}, DOI={10.1016/J.GEODERMA.2018.08.027}, abstractNote={Recent developments of enzyme-based decomposition models highlight the importance of enzyme kinetics with warming, but most modeling exercises are based on studies with a step-wise warming. This approach may mask the effect of temperature in controlling in-situ activities as in most ecosystems the rate of warming is more gradual than these step warming studies. We conducted an experiment to test the effects of contrasting warming rates on the kinetics of carbon (C), nitrogen (N), and phosphorus (P) degradation enzymes in subtropical peat soils. We also wanted to evaluate if the stoichiometry of enzyme kinetics shifts under contrasting warming rates and if so, how does it relate to the stoichiometry in microbial biomass. Contrasting warming rates altered microbial biomass stoichiometry leading to differing patterns of microbial demand for C vs. nutrient (N and P) and enzyme expression following the optimum foraging strategy. Activity (higher Vmax) and efficiency (lower Km) of C acquisition enzymes were greater in the step treatment; however, expressions of nutrient (N and P) acquiring enzymes were enhanced in the ramp treatment at the end of the experiment. In the step treatment, there was a typical pattern of an initial peak in the Vmax and drop in the Km for all enzyme groups followed by later adjustments. On the other hand, a consistent increase in Vmax and decline in Km of all enzyme groups were observed in the ramp treatment. These changes were sufficient to alter microbial identity (as indicated by enzyme Km and biomass stoichiometry) with two apparently different endpoints under contrasting warming rates. This observation resembles the concept of alternate stable states and highlights a need for improved representation of warming effects on enzymes in decomposition models. Using peat soils of Florida Everglades, here we have demonstrated that contrasting warming rates can influence the dynamics of microbial and enzymatic kinetics. Hence, we suggest that future laboratory and field warming studies could consider our approach to accurately represent microbial and enzymatic kinetics in biogeochemical models.}, journal={Geoderma}, author={Sihi, Debjani and Inglett, Patrick W. and Inglett, Kanika S.}, year={2019}, pages={12–21} }
 @article{dari_sihi_2018, title={A Decadal Overview of Biochar Research in Agriculture}, volume={18}, url={http://www.agrophysics.in/admin/adminjournalpdf/20190516115521993431154/journal-470660694.pdf}, number={1}, journal={Journal of Agricultural Physics}, author={Dari, B. and Sihi, D.}, year={2018}, month={Feb}, pages={14–20} }
 @inbook{dari_sihi_2018, place={Singapore}, title={Future of Rice Crop Under Enriched CO2 Environment}, url={https://doi.org/10.1007/978-981-13-1861-0_17}, DOI={10.1007/978-981-13-1861-0_17}, booktitle={Advances in Crop Environment Interaction}, publisher={Springer Singapore}, author={Dari, Biswanath and Sihi, Debjani}, editor={Bal, Santanu Kumar and Mukherjee, Joydeep and Choudhury, Burhan Uddin and Dhawan, Ashok KumarEditors}, year={2018}, pages={425–437} }
 @article{sihi_davidson_chen_savage_richardson_keenan_hollinger_2018, title={Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern USA}, volume={252}, url={https://publons.com/publon/1568965/}, DOI={10.1016/J.AGRFORMET.2018.01.026}, abstractNote={Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO2), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs. The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.}, journal={Agricultural and Forest Meteorology}, author={Sihi, D. and Davidson, E.A. and Chen, M. and Savage, K.E. and Richardson, A.D. and Keenan, T.F. and Hollinger, D.Y.}, year={2018}, pages={155–166} }
 @article{sihi_davidson_chen_savage_richardson_keenan_hollinger_2018, title={Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern {USA} }, volume={252}, url={https://www.sciencedirect.com/science/article/pii/S0168192318300261}, DOI={https://doi.org/10.1016/j.agrformet.2018.01.026}, abstractNote={Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO2), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs. The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.}, journal={Agricultural and Forest Meteorology}, author={Sihi, Debjani and Davidson, Eric A. and Chen, Min and Savage, Kathleen E. and Richardson, Andrew D. and Keenan, Trevor F. and Hollinger, David Y.}, year={2018}, pages={155–166} }
 @article{yan_chen_dari_sihi_chen_2018, title={Phosphorus transformation response to soil properties changes induced by manure application in a calcareous soil}, volume={322}, url={https://publons.com/publon/2105143/}, DOI={10.1016/J.GEODERMA.2018.02.035}, abstractNote={Management of phosphorus (P) loss in soils with heavy manure application requires improved understanding of the transformation characteristics of soil P. Influences of manure application on the forms and sorption-desorption characteristics of P in surface (0–30 cm) and subsurface (30–60 cm) layer of a calcareous soil were investigated in a six-year field trial in comparison to chemical fertilizer application. Hedley fractionation and P K-edge X-ray absorption near-edge structure spectroscopy were used to determine the soil P forms. Manure (M) and chemical fertilizer (F) treatments resulted in P accumulation in two soil depths, but the total P accumulation in surface soil with M treatment was significantly lower than F treatment with similar P surplus. Compared to control, M and F treatments were significantly increased the proportion of labile P at both depths. In surface soil, M treatment significantly decreased stable Ca-associated P proportion and increased Fe-associated P and inositol hexakisphosphate proportions. The accumulation and transformation of P in M treatment distinctly decreased P sorption maximun, sorption coefficient and buffer capacity, and increased the degree of P saturation and P desorption relative to F treatment. The soil properties of pH, organic carbon (OC), total nitrogen (TN), Mehlich-3 extractable Ca and Fe, and phytase in surface soil and pH, OC, TN, Mehlich-3 extractable Ca and dehydrogenase in subsurface soil had significant effects on the compositions of soil P (P < 0.05), respectively. Lowered pH due to manure application mainly contributed to P transformation and release in the calcareous soil.}, journal={Geoderma}, author={Yan, Zhengjuan and Chen, Shuo and Dari, Biswanath and Sihi, Debjani and Chen, Qing}, year={2018}, pages={163–171} }
 @article{yan_chen_dari_sihi_chen_2018, title={Phosphorus transformation response to soil properties changes induced by manure application in a calcareous soil }, volume={322}, url={https://www.sciencedirect.com/science/article/pii/S0016706117315896}, DOI={https://doi.org/10.1016/j.geoderma.2018.02.035}, abstractNote={Management of phosphorus (P) loss in soils with heavy manure application requires improved understanding of the transformation characteristics of soil P. Influences of manure application on the forms and sorption-desorption characteristics of P in surface (0–30 cm) and subsurface (30–60 cm) layer of a calcareous soil were investigated in a six-year field trial in comparison to chemical fertilizer application. Hedley fractionation and P K-edge X-ray absorption near-edge structure spectroscopy were used to determine the soil P forms. Manure (M) and chemical fertilizer (F) treatments resulted in P accumulation in two soil depths, but the total P accumulation in surface soil with M treatment was significantly lower than F treatment with similar P surplus. Compared to control, M and F treatments were significantly increased the proportion of labile P at both depths. In surface soil, M treatment significantly decreased stable Ca-associated P proportion and increased Fe-associated P and inositol hexakisphosphate proportions. The accumulation and transformation of P in M treatment distinctly decreased P sorption maximun, sorption coefficient and buffer capacity, and increased the degree of P saturation and P desorption relative to F treatment. The soil properties of pH, organic carbon (OC), total nitrogen (TN), Mehlich-3 extractable Ca and Fe, and phytase in surface soil and pH, OC, TN, Mehlich-3 extractable Ca and dehydrogenase in subsurface soil had significant effects on the compositions of soil P (P < 0.05), respectively. Lowered pH due to manure application mainly contributed to P transformation and release in the calcareous soil.}, journal={Geoderma}, author={Yan, Zhengjuan and Chen, Shuo and Dari, Biswanath and Sihi, Debjani and Chen, Qing}, year={2018}, pages={163–171} }
 @article{sihi_inglett_gerber_inglett_2018, title={Rate of warming affects temperature sensitivity of anaerobic peat decomposition and greenhouse gas production}, volume={24}, url={https://publons.com/publon/759163/}, DOI={10.1111/GCB.13839}, abstractNote={Abstract Temperature sensitivity of anaerobic carbon mineralization in wetlands remains poorly represented in most climate models and is especially unconstrained for warmer subtropical and tropical systems which account for a large proportion of global methane emissions. Several studies of experimental warming have documented thermal acclimation of soil respiration involving adjustments in microbial physiology or carbon use efficiency (CUE), with an initial decline in CUE with warming followed by a partial recovery in CUE at a later stage. The variable CUE implies that the rate of warming may impact microbial acclimation and the rate of carbon‐dioxide (CO 2 ) and methane (CH 4 ) production. Here, we assessed the effects of warming rate on the decomposition of subtropical peats, by applying either a large single‐step (10°C within a day) or a slow ramping (0.1°C/day for 100 days) temperature increase. The extent of thermal acclimation was tested by monitoring CO 2 and CH 4 production, CUE, and microbial biomass. Total gaseous C loss, CUE, and MBC were greater in the slow (ramp) warming treatment. However, greater values of CH 4 –C:CO 2 –C ratios lead to a greater global warming potential in the fast (step) warming treatment. The effect of gradual warming on decomposition was more pronounced in recalcitrant and nutrient‐limited soils. Stable carbon isotopes of CH 4 and CO 2 further indicated the possibility of different carbon processing pathways under the contrasting warming rates. Different responses in fast vs. slow warming treatment combined with different endpoints may indicate alternate pathways with long‐term consequences. Incorporations of experimental results into organic matter decomposition models suggest that parameter uncertainties in CUE and CH 4 –C:CO 2 –C ratios have a larger impact on long‐term soil organic carbon and global warming potential than uncertainty in model structure, and shows that particular rates of warming are central to understand the response of wetland soils to global climate change.}, number={1}, journal={Global Change Biology}, author={Sihi, D and Inglett, PW and Gerber, S and Inglett, KS}, year={2018}, pages={e259–e274} }
 @article{the fate of root carbon in soil: data and model gaps_2018, url={http://dx.doi.org/10.1029/2018eo112593}, DOI={10.1029/2018eo112593}, abstractNote={Root Trait and Soil Carbon Workshop; Oak Ridge National Laboratory, Oak Ridge, Tennessee, 31 July to 1 August 2018}, journal={Eos}, year={2018}, month={Dec} }
 @article{sihi_dari_sharma_pathak_nain_sharma_2017, title={Evaluation of soil health in organic vs. conventional farming of basmati rice in North India}, volume={180}, url={https://publons.com/publon/899241/}, DOI={10.1002/JPLN.201700128}, abstractNote={Abstract Conventional agricultural practices that use excessive chemical fertilizers and pesticides come at a great price with respect to soil health, a key component to achieve agricultural sustainability. Organic farming could serve as an alternative agricultural system and solve the problems associated with the usage of agro‐chemicals by sustainable use of soil resources. A study was carried out to evaluate the impact of organic vs . conventional cultivations of basmati rice on soil health during Kharif (rainy) season of 2011 at Kaithal district of Haryana, India, under farmers' participatory mode. Long‐term application of organic residues in certified organic farms was found to improve physical, chemical, and biological indicators of soil health. Greater organic matter buildup as indicated by higher soil organic carbon content in organic fields was critical to increase soil aggregate stability by increasing water holding capacity and reducing bulk density. Proper supplementation of nutrients (both major and micro nutrients) through organic residue addition favored biologically available nutrients in organic systems. Further, the prevalence of organic substrates stimulated soil microorganisms to produce enzymes responsible for the conversion of unavailable nutrients to plant available forms. Most importantly, a closer look at the relationship between physicochemical and biological indicators of soil health evidenced the significance of organic matter to enzyme activities suggesting enhanced nutrient cycling in systems receiving organic amendments. Enzyme activities were very sensitive to short‐term (one growing season) effects of organic vs . conventional nutrient management. Soil chemical indicators (organic matter and nutrient contents) were also changed in the short‐term, but the response was secondary to the biochemical indicators. Taken together, this study indicates that organic farming practices foster biotic and abiotic interactions in the soil which may facilitate in moving towards a sustainable food future.}, number={3}, journal={Journal of Plant Nutrition and Soil Science}, author={Sihi, D and Dari, Biswanath and Sharma, Dinesh K. and Pathak, Himanshu and Nain, Lata and Sharma, Om Parkash}, year={2017}, pages={389–406} }
 @article{dari_sihi_bal_kunwar_2017, title={Performance of direct-seeded rice under various dates of sowing and irrigation regimes in semi-arid region of India}, volume={15}, url={https://publons.com/publon/820707/}, DOI={10.1007/S10333-016-0557-8}, number={2}, journal={Paddy and Water Environment}, author={Dari, B. and Sihi, D. and Bal, S.K. and Kunwar, S.}, year={2017}, pages={395–401} }
 @article{sihi_inglett_inglett_2016, title={Carbon quality and nutrient status drive the temperature sensitivity of organic matter decomposition in subtropical peat soils}, volume={131}, url={https://publons.com/publon/899242/}, DOI={10.1007/S10533-016-0267-8}, number={1-2}, journal={Biogeochemistry}, author={Sihi, D and Inglett, Patrick W. and Inglett, Kanika Sharma}, year={2016}, pages={103–119} }
 @article{sihi_gerber_inglett_sharma inglett_2016, title={Comparing models of microbial-substrate interactions and their response to warming}, volume={13}, url={http://www.biogeosciences.net/13/1733/2016/}, DOI={10.5194/bg-13-1733-2016}, abstractNote={Abstract. Recent developments in modelling soil organic carbon decomposition include the explicit incorporation of enzyme and microbial dynamics. A characteristic of these models is a positive feedback between substrate and consumers, which is absent in traditional first-order decay models. With sufficiently large substrate, this feedback allows an unconstrained growth of microbial biomass. We explore mechanisms that curb unrestricted microbial growth by including finite potential sites where enzymes can bind and by allowing microbial scavenging for enzymes. We further developed a model where enzyme synthesis is not scaled to microbial biomass but associated with a respiratory cost and microbial population adjusts enzyme production in order to optimise their growth. We then tested short- and long-term responses of these models to a step increase in temperature and find that these models differ in the long-term when short-term responses are harmonised. We show that several mechanisms, including substrate limitation, variable production of microbial enzymes, and microbes feeding on extracellular enzymes eliminate oscillations arising from a positive feedback between microbial biomass and depolymerisation. The model where enzyme production is optimised to yield maximum microbial growth shows the strongest reduction in soil organic carbon in response to warming, and the trajectory of soil carbon largely follows that of a first-order decomposition model. Modifications to separate growth and maintenance respiration generally yield short-term differences, but results converge over time because microbial biomass approaches a quasi-equilibrium with the new conditions of carbon supply and temperature.}, number={6}, journal={Comparing models of microbial-substrate interactions and their response to warming}, author={Sihi, D. and Gerber, S. and Inglett, P.W. and Sharma Inglett, K.}, year={2016}, month={Mar}, pages={1733–1752} }
 @article{renchon_drake_macdonald_sihi_hinko-najera_tjoelker_arndt_noh_davidson_pendall, title={Concurrent measurements of soil and ecosystem respiration in a mature eucalypt woodland: advantages, lessons, and questions}, volume={n/a}, url={https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020JG006221}, DOI={https://doi.org/10.1029/2020JG006221}, abstractNote={Abstract Understanding seasonal and diurnal dynamics of ecosystem respiration (R eco ) in forests is challenging, because R eco can only be measured directly during night‐time by eddy‐covariance flux towers. R eco is the sum of soil respiration (R soil ) and above‐ground respiration (in theory, R AG = R eco − R soil ). R soil can be measured day and night and can provide a check of consistency on R eco , as the difference in magnitude and time dynamic between R eco and R soil should be explained by R AG . We assessed the temporal patterns and climatic drivers of R soil and R eco in a mature eucalypt woodland, using continuous measurements (only at night for R eco ) at half‐hourly resolution over 4 years (2014–2017). Our data showed large seasonal and diurnal (overnight) variation of R eco , while R soil had a low diurnal amplitude and their difference (R eco − R soil, or R AG ) had a low seasonal amplitude. This result implies at first glance that seasonal variation of R eco was mainly influenced by R soil while its diurnal variation was mainly influenced by R AG . However, our analysis suggests that the night‐time R eco decline cannot realistically be explained by a decline of R AG . Chamber measurements of autotrophic components at half‐hourly time resolution are needed to quantify how much of the R eco decline overnight is due to declines in leaf or stem respiration, and how much is due to missing storage or advection, which may create a systematic bias in R eco measurements. Our findings emphasize the need for reconciling bottom‐up (via components measured with chambers) and direct estimates of R eco (via eddy‐covariance method).}, note={e2020JG006221 2020JG006221}, number={n/a}, journal={Journal of Geophysical Research: Biogeosciences}, author={Renchon, A. A. and Drake, J. E. and Macdonald, C.A. and Sihi, D. and Hinko-Najera, N. and Tjoelker, M. G. and Arndt, S. K. and Noh, N. J. and Davidson, E. and Pendall, E.}, pages={e2020JG006221} }