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1. Florida mangrove saltmarsh reference surface soils

   https://doi.org/10.6073/pasta/0e08cbe07c84488cb7b9dd16669946d0  

   Lewis, David Bruce ( January 2021 , Environmental Data Initiative)

   Site description. This data package consists of data obtained from sampling surface soil (the 0-7.6 cm depth profile) in black mangrove (Avicennia germinans) dominated forest and black needlerush (Juncus roemerianus) saltmarsh along the Gulf of Mexico coastline in peninsular west-central Florida, USA. This location has a subtropical climate with mean daily temperatures ranging from 15.4 °C in January to 27.8 °C in August, and annual precipitation of 1336 mm. Precipitation falls as rain primarily between June and September. Tides are semi-diurnal, with 0.57 m median amplitudes during the year preceding sampling (U.S. NOAA National Ocean Service, Clearwater Beach, Florida, station 8726724). Sea-level rise is 4.0 ± 0.6 mm per year (1973-2020 trend, mean ± 95 % confidence interval, NOAA NOS Clearwater Beach station). The A. germinans mangrove zone is either adjacent to water or fringed on the seaward side by a narrow band of red mangrove (Rhizophora mangle). A near-monoculture of J. roemerianus is often adjacent to and immediately landward of the A. germinans zone. The transition from the mangrove to the J. roemerianus zone is variable in our study area. An abrupt edge between closed-canopy mangrove and J. roemerianus monoculture may extend for up to several hundred meters in some locations, while other stretches of ecotone present a gradual transition where smaller, widely spaced trees are interspersed into the herbaceous marsh. Juncus roemerianus then extends landward to a high marsh patchwork of succulent halophytes (including Salicornia bigellovi, Sesuvium sp., and Batis maritima), scattered dwarf mangrove, and salt pans, followed in turn by upland vegetation that includes Pinus sp. and Serenoa repens. Field design and sample collection. We established three study sites spaced at approximately 5 km intervals along the western coastline of the central Florida peninsula. The sites consisted of the Salt Springs (28.3298°, -82.7274°), Energy Marine Center (28.2903°, -82.7278°), and Green Key (28.2530°, -82.7496°) sites on the Gulf of Mexico coastline in Pasco County, Florida, USA. At each site, we established three plot pairs, each consisting of one saltmarsh plot and one mangrove plot. Plots were 50 m^2 in size. Plots pairs within a site were separated by 230-1070 m, and the mangrove and saltmarsh plots composing a pair were 70-170 m apart. All plot pairs consisted of directly adjacent patches of mangrove forest and J. roemerianus saltmarsh, with the mangrove forests exhibiting a closed canopy and a tree architecture (height 4-6 m, crown width 1.5-3 m). Mangrove plots were located at approximately the midpoint between the seaward edge (water-mangrove interface) and landward edge (mangrove-marsh interface) of the mangrove zone. Saltmarsh plots were located 20-25 m away from any mangrove trees and into the J. roemerianus zone (i.e., landward from the mangrove-marsh interface). Plot pairs were coarsely similar in geomorphic setting, as all were located on the Gulf of Mexico coastline, rather than within major sheltering formations like Tampa Bay, and all plot pairs fit the tide-dominated domain of the Woodroffe classification (Woodroffe, 2002, "Coasts: Form, Process and Evolution", Cambridge University Press), given their conspicuous semi-diurnal tides. There was nevertheless some geomorphic variation, as some plot pairs were directly open to the Gulf of Mexico while others sat behind keys and spits or along small tidal creeks. Our use of a plot-pair approach is intended to control for this geomorphic variation. Plot center elevations (cm above mean sea level, NAVD 88) were estimated by overlaying the plot locations determined with a global positioning system (Garmin GPS 60, Olathe, KS, USA) on a LiDAR-derived bare-earth digital elevation model (Dewberry, Inc., 2019). The digital elevation model had a vertical accuracy of ± 10 cm (95 % CI) and a horizontal accuracy of ± 116 cm (95 % CI). Soil samples were collected via coring at low tide in June 2011. From each plot, we collected a composite soil sample consisting of three discrete 5.1 cm diameter soil cores taken at equidistant points to 7.6 cm depth. Cores were taken by tapping a sleeve into the soil until its top was flush with the soil surface, sliding a hand under the core, and lifting it up. Cores were then capped and transferred on ice to our laboratory at the University of South Florida (Tampa, Florida, USA), where they were combined in plastic zipper bags, and homogenized by hand into plot-level composite samples on the day they were collected. A damp soil subsample was immediately taken from each composite sample to initiate 1 y incubations for determination of active C and N (see below). The remainder of each composite sample was then placed in a drying oven (60 °C) for 1 week with frequent mixing of the soil to prevent aggregation and liberate water. Organic wetland soils are sometimes dried at 70 °C, however high drying temperatures can volatilize non-water liquids and oxidize and decompose organic matter, so 50 °C is also a common drying temperature for organic soils (Gardner 1986, "Methods of Soil Analysis: Part 1", Soil Science Society of America); we accordingly chose 60 °C as a compromise between sufficient water removal and avoidance of non-water mass loss. Bulk density was determined as soil dry mass per core volume (adding back the dry mass equivalent of the damp subsample removed prior to drying). Dried subsamples were obtained for determination of soil organic matter (SOM), mineral texture composition, and extractable and total carbon (C) and nitrogen (N) within the following week. Sample analyses. A dried subsample was apportioned from each composite sample to determine SOM as mass loss on ignition at 550 °C for 4 h. After organic matter was removed from soil via ignition, mineral particle size composition was determined using a combination of wet sieving and density separation in 49 mM (3 %) sodium hexametaphosphate ((NaPO_3)_6) following procedures in Kettler et al. (2001, Soil Science Society of America Journal 65, 849-852). The percentage of dry soil mass composed of silt and clay particles (hereafter, fines) was calculated as the mass lost from dispersed mineral soil after sieving (0.053 mm mesh sieve). Fines could have been slightly underestimated if any clay particles were burned off during the preceding ignition of soil. An additional subsample was taken from each composite sample to determine extractable N and organic C concentrations via 0.5 M potassium sulfate (K_2SO_4) extractions. We combined soil and extractant (ratio of 1 g dry soil:5 mL extractant) in plastic bottles, reciprocally shook the slurry for 1 h at 120 rpm, and then gravity filtered it through Fisher G6 (1.6 μm pore size) glass fiber filters, followed by colorimetric detection of nitrite (NO_2^-) + nitrate (NO_3^-) and ammonium (NH_4^+) in the filtrate (Hood Nowotny et al., 2010,Soil Science Society of America Journal 74, 1018-1027) using a microplate spectrophotometer (Biotek Epoch, Winooski, VT, USA). Filtrate was also analyzed for dissolved organic C (referred to hereafter as extractable organic C) and total dissolved N via combustion and oxidation followed by detection of the evolved CO_2 and N oxide gases on a Formacs HT TOC/TN analyzer (Skalar, Breda, The Netherlands). Extractable organic N was then computed as total dissolved N in filtrate minus extractable mineral N (itself the sum of extractable NH_4-N and NO_2-N + NO_3-N). We determined soil total C and N from dried, milled subsamples subjected to elemental analysis (ECS 4010, Costech, Inc., Valencia, CA, USA) at the University of South Florida Stable Isotope Laboratory. Median concentration of inorganic C in unvegetated surface soil at our sites is 0.5 % of soil mass (Anderson, 2019, Univ. of South Florida M.S. thesis via methods in Wang et al., 2011, Environmental Monitoring and Assessment 174, 241-257). Inorganic C concentrations are likely even lower in our samples from under vegetation, where organic matter would dilute the contribution of inorganic C to soil mass. Nevertheless, the presence of a small inorganic C pool in our soils may be counted in the total C values we report. Extractable organic C is necessarily of organic C origin given the method (sparging with HCl) used in detection. Active C and N represent the fractions of organic C and N that are mineralizable by soil microorganisms under aerobic conditions in long-term soil incubations. To quantify active C and N, 60 g of field-moist soil were apportioned from each composite sample, placed in a filtration apparatus, and incubated in the dark at 25 °C and field capacity moisture for 365 d (as in Lewis et al., 2014, Ecosphere 5, art59). Moisture levels were maintained by frequently weighing incubated soil and wetting them up to target mass. Daily CO_2 flux was quantified on 29 occasions at 0.5-3 week intervals during the incubation period (with shorter intervals earlier in the incubation), and these per day flux rates were integrated over the 365 d period to compute an estimate of active C. Observations of per day flux were made by sealing samples overnight in airtight chambers fitted with septa and quantifying headspace CO_2 accumulation by injecting headspace samples (obtained through the septa via needle and syringe) into an infrared gas analyzer (PP Systems EGM 4, Amesbury, MA, USA). To estimate active N, each incubated sample was leached with a C and N free, 35 psu solution containing micronutrients (Nadelhoffer, 1990, Soil Science Society of America Journal 54, 411-415) on 19 occasions at increasing 1-6 week intervals during the 365 d incubation, and then extracted in 0.5 M K_2SO_4 at the end of the incubation in order to remove any residual mineral N. Active N was then quantified as the total mass of mineral N leached and extracted. Mineral N in leached and extracted solutions was detected as NH_4-N and NO_2-N + NO_3-N via colorimetry as above. This incubation technique precludes new C and N inputs and persistently leaches mineral N, forcing microorganisms to meet demand by mineralizing existing pools, and thereby directly assays the potential activity of soil organic C and N pools present at the time of soil sampling. Because this analysis commences with disrupting soil physical structure, it is biased toward higher estimates of active fractions. Calculations. Non-mobile C and N fractions were computed as total C and N concentrations minus the extractable and active fractions of each element. This data package reports surface-soil constituents (moisture, fines, SOM, and C and N pools and fractions) in both gravimetric units (mass constituent / mass soil) and areal units (mass constituent / soil surface area integrated through 7.6 cm soil depth, the depth of sampling). Areal concentrations were computed as X × D × 7.6, where X is the gravimetric concentration of a soil constituent, D is soil bulk density (g dry soil / cm^3), and 7.6 is the sampling depth in cm. 

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2. Coherent Mechanistic Patterns of Tropical Land Hydroclimate Changes

   https://doi.org/10.1029/2022GL102285  

   Duan, Suqin Q. ; Findell, Kirsten L. ; Fueglistaler, Stephan A. ( April 2023 , Geophysical Research Letters)

   Changes in tropical (30 S–30 N) land hydroclimate following CO₂‐induced global warming are organized according to climatological aridity index (AI) and daily soil moisture (SM) percentiles. The transform from geographical space to this novel process‐oriented phase space allows for interpretation of local, daily mechanistic relationships between key hydroclimatic variables in the context of time‐mean and/or global‐mean energetic constraints and the wet‐get‐wetter/dry‐get‐drier paradigm. Results from 16 CMIP models show coherent patterns of change in the AI/SM phase space that are aligned with the established soil‐moisture/evapotranspiration regimes. We introduce an active‐rain regime as a special case of the energy‐limited regime. Rainfall shifts toward larger rain totals in this active‐rain regime, with less rain on other days, resulting in an overall SM reduction. Consequently, the regimes where SM constrains evapotranspiration become more frequently occupied, and corresponding hydroclimatic changes align with the position of the critical SM value in the AI/SM phase space.

    

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3. ENSO‐Influenced Drought Drives Methane Flux Dynamics in a Tropical Wet Forest Soil

   https://doi.org/10.1029/2018JG004832  

   Aronson, E. L. ; Dierick, D. ; Botthoff, J. K. ; Oberbauer, S. ; Zelikova, T. J. ; Harmon, T. C. ; Rundel, P. ; Johnson, R. F. ; Swanson, A. C. ; Pinto‐Tomás, A. A. ; et al ( July 2019 , Journal of Geophysical Research: Biogeosciences)

   Global atmospheric methane growth rates have wildly fluctuated over the past three decades, which may be driven by the proportion of tropical land surface saturated by water. The El Niño/Southern Oscillation Event (ENSO) cycle drives large‐scale climatic trends globally, with El Niño events typically bringing drier weather than La Niña. In a lowland tropical wet forest in Costa Rica, we measured methane flux bimonthly from March 2016 to June 2017 and using an automated chamber system. We observed a strong drying trend for several weeks during the El Niño in 2016, reducing soil moisture below normal levels. In contrast, soil conditions had high water content prior to the drought and during the moderate La Niña that followed. Soil moisture varied across the period studied and significantly impacted methane flux. Methane consumption was greater during the driest part of the El Niño period, while during La Niña and other time periods, soils had lower methane consumption. The mean methane flux observed was −0.022 mg CH₄‐C m⁻²hr⁻¹, and methane was consumed at all timepoints, with lower consumption in saturated soils. Our data show that month studied, and the correlation between soil type and month significantly drove methane flux trends. Our data indicate that ENSO cycles may impact biogenic methane fluxes, mediated by soil moisture conditions. Climate projections for Central America show dryer conditions and increased El Niño frequency, further exacerbating predicted drought. These trends may lead to negative climate feedbacks, with drier conditions increasing soil methane consumption from the atmosphere.

    

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4. Multivariate Assimilation of Remotely Sensed Soil Moisture and Evapotranspiration for Drought Monitoring

   https://doi.org/10.1175/JHM-D-20-0057.1  

   Gavahi, Keyhan ; Abbaszadeh, Peyman ; Moradkhani, Hamid ; Zhan, Xiwu ; Hain, Christopher ( October 2020 , Journal of Hydrometeorology)

   null (Ed.)

   Abstract Soil moisture (SM) and evapotranspiration (ET) are key variables of the terrestrial water cycle with a strong relationship. This study examines remotely sensed soil moisture and evapotranspiration data assimilation (DA) with the aim of improving drought monitoring. Although numerous efforts have gone into assimilating satellite soil moisture observations into land surface models to improve their predictive skills, little attention has been given to the combined use of soil moisture and evapotranspiration to better characterize hydrologic fluxes. In this study, we assimilate two remotely sensed datasets, namely, Soil Moisture Operational Product System (SMOPS) and MODIS evapotranspiration (MODIS16 ET), at 1-km spatial resolution, into the VIC land surface model by means of an evolutionary particle filter method. To achieve this, a fully parallelized framework based on model and domain decomposition using a parallel divide-and-conquer algorithm was implemented. The findings show improvement in soil moisture predictions by multivariate assimilation of both ET and SM as compared to univariate scenarios. In addition, monthly and weekly drought maps are produced using the updated root-zone soil moisture percentiles over the Apalachicola–Chattahoochee–Flint basin in the southeastern United States. The model-based estimates are then compared against the corresponding U.S. Drought Monitor (USDM) archive maps. The results are consistent with the USDM maps during the winter and spring season considering the drought extents; however, the drought severity was found to be slightly higher according to DA method. Comparing different assimilation scenarios showed that ET assimilation results in wetter conditions comparing to open-loop and univariate SM DA. The multivariate DA then combines the effects of the two variables and provides an in-between condition. 

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5. Consistent microbial and nutrient resource island patterns during monsoon rain in a Chihuahuan Desert bajada shrubland

   https://doi.org/10.1002/ecs2.4475  

   Darrouzet‐Nardi, Anthony ; Asaff, Isabel Siles ; Mauritz, Marguerite ; Roman, Kathleen ; Keats, Eleanor ; Tweedie, Craig E. ; McLaren, Jennie R. ( April 2023 , Ecosphere)

   In dryland soils, spatiotemporal variation in surface soils (0–10 cm) plays an important role in the function of the “critical zone” that extends from canopy to groundwater. Understanding connections between soil microbes and biogeochemical cycling in surface soils requires repeated multivariate measurements of nutrients, microbial abundance, and microbial function. We examined these processes in resource islands and interspaces over a two‐month period at a Chihuahuan Desert bajada shrubland site. We collected soil inProsopis glandulosa(honey mesquite),Larrea tridentata(creosote bush), and unvegetated (interspace) areas to measure soil nutrient concentrations, microbial biomass, and potential soil enzyme activity. We monitored the dynamics of these belowground processes as soil conditions dried and then rewetted due to rainfall. Most measured variables, including inorganic nutrients, microbial biomass, and soil enzyme activities, were greater under shrubs during both wet and dry periods, with the highest magnitudes under mesquite followed by creosote bush and then interspace. One exception was nitrate, which was highly variable and did not show resource island patterns. Temporally, rainfall pulses were associated with substantial changes in soil nutrient concentrations, though resource island patterns remained consistent during all phases of the soil moisture pulse. Microbial biomass was more consistent than nutrients, decreasing only when soils were driest. Potential enzyme activities were even more consistent and did not decline in dry periods, potentially helping to stimulate observed pulses in CO₂efflux following rain events observed at a co‐located eddy flux tower. These results indicate a critical zone with organic matter cycling patterns consistently elevated in shrub resource islands (which varied by shrub species), high decomposition potential that limits soil organic matter accumulation across the landscape, and nitrate fluxes that are decoupled from the organic matter pathways.

    

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