Final Technical Report: Soil Moisture Flux Sensor Using Machine Intelligence
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47 OTHER INSTRUMENTATION↗
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Estimation of effective hydrologic properties of soils from observations of vegetation density
An existing one-dimensional model of the annual water balance is reviewed. Slight improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate-soil system, is verified through comparisons with observed data and is employed in the annual water balance of watersheds in Clinton, Ma., and Santa Paula, Ca., to estimate effective areal average soil properties. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides excellent verification of the soil-selection procedure. This method of parameterization of the land surface should be useful with present global circulation models, enabling them to account for both the non-linearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.
Tellers, T. E.↗
Estimation of effective hydrologic properties of soils from observations of vegetation density
A one-dimensional model of the annual water balance is reviewed. Improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate soil system, is verified through comparisons with observed data. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides verification of the soil-selection procedure. This method of parameterization of the land surface is useful with global circulation models, enabling them to account for both the nonlinearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.
Tellers, T. E.↗
Effects of vegetation on soil moisture distribution and flux with implications for the global hydrologic cycle
Recent climate modeling experiments have identified the critical need for a better understanding of land surface - atmosphere interactions. An important issue in global climate modeling is to be able to relate land surface and atmospheric processes. In the past this link has been inadequately represented due to the lack of understanding of the interaction between the processes and also due to the large spatial variability of the hydrological and soil properties. A project was initiated at the Marshall Space Flight Center (MSFC) in FY-90 under the Center's Directorate Discretionary Fund (CDDF) to study small-scale effects of vegetation on the distribution and fluxes of soil moisture. Installation of a large array of instruments was accomplished during that first year (FY-90). During this second year of the project, the instrumentation and data collection systems were improved and data has begun to be taken. Preliminary analysis of the data show that the equipment has been functioning properly. Some of the preliminary results that have recently been analyzed are given.
Macari, Emir Jose↗
Assimilation of Surface Temperature in Land Surface Models
Hydrological models have been calibrated and validated using catchment streamflows. However, using a point measurement does not guarantee correct spatial distribution of model computed heat fluxes, soil moisture and surface temperatures. With the advent of satellites in the late 70s, surface temperature is being measured two to four times a day from various satellite sensors and different platforms. The purpose of this paper is to demonstrate use of satellite surface temperature in (a) validation of model computed surface temperatures and (b) assimilation of satellite surface temperatures into a hydrological model in order to improve the prediction accuracy of soil moistures and heat fluxes. The assimilation is carried out by comparing the satellite and the model produced surface temperatures and setting the "true"temperature midway between the two values. Based on this "true" surface temperature, the physical relationships of water and energy balance are used to reset the other variables. This is a case of nudging the water and energy balance variables so that they are consistent with each other and the true" surface temperature. The potential of this assimilation scheme is demonstrated in the form of various experiments that highlight the various aspects. This study is carried over the Red-Arkansas basin in the southern United States (a 5 deg X 10 deg area) over a time period of a year (August 1987 - July 1988). The land surface hydrological model is run on an hourly time step. The results show that satellite surface temperature assimilation improves the accuracy of the computed surface soil moisture remarkably.
Lakshmi, Venkataraman↗
An overview of the measurements of soil moisture and modeling of moisture flux in FIFE
Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.
Wang, J. R.↗
Carbon Organisms Rhizosphere and Protection in Soil Environment model script and input data for soil moisture-respiration responses in tropical forests
Objectives: Climatic drying is predicted for many tropical forests, yet models remain poorly parameterized for tropical forests, hampering predictions of forest-climate feedbacks. We applied an integrated model–experiment approach, parameterizing an ecosystem model Carbon Organisms Rhizosphere and Protection in the Soil Environment (CORPSE) with tropical forest observational data, and comparing model predictions with a field drying manipulation. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We used the field data to parameterize and run tests in the model.Results: Measured CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. We used this data to parameterize the model, which then predicted increased soil CO2 fluxes in wetter and fertile forests with drying, and decreased fluxes in drier, infertile forests. In contrast to model predictions, a chronic throughfall exclusion experiment in the forests initially suppressed soil CO2 fluxes across forests, with sustained suppression after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season), as predicted by the model. The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Code files:CORPSE_array.py: Defines the equations of the CORPSE modelCORPSE_solvers: Functions for running the CORPSE model using either iterative or ordinary differential equation (ODE) solversrun_Panama_sims.py: Read in datasets and run the model simulations for this studyInput data:PanamaGradientEcosystemChem_BT_CPools_20152016CO2_DC_20190615.xlsx: Plot characteristics used in running model simulationsLiCor compiled surface flux only to 2020_03 DC_20200825.xlsx: Surface gas exchange fluxes used in model-data comparisonsPARCHED litterfall data for Ben Sulman LD 20200902.xlsx: Litterfall data used to drive model simulationsInitialization data:state_500y_20190823.csv: Initial state of model pools based on previous spinup runsOutput data:Outputs/prev_moisture_response.csv: Simulations of multiple sites using original model moisture response function.Outputs/updated_moisture_response.csv: Simulations of multiple sites using updated model moisture response function.Outputs/dry15_prev_moisture_response.csv: Simulations with soil moisture reduced by 15%, using original moisture response function.Outputs/dry15_updated_moisture_response.csv: Simulations with soil moisture reduced by 15%, using updated moisture response function.Outputs/dry30_prev_moisture_response.csv: Simulations with soil moisture reduced by 30%, using original moisture response function.Outputs/dry30_updated_moisture_response.csv: Simulations with soil moisture reduced by 30%, using updated moisture response function.Outputs/latestart_prev_moisture_response.csv: Simulations with extended dry season, using original moisture response function.Outputs/latestart_updated_moisture_response.csv: Simulations with extended dry season, using updated moisture response function.Outputs/[site name]_oneyear.csv: One-year simulation for each site in expanded site list using original moisture response function.Outputs/[site name]_oneyear_dried.csv: One-year simulation for each site in expanded site list using original moisture response function, with soil moisture reduced by 25%.Outputs/[site name]_oneyear_updated_moisture_response.csv: One-year simulation for each site in expanded site list using updated moisture response function.Outputs/[site name]_oneyear_updated_moisture_response_dried.csv: One-year simulation for each site in expanded site list using updated moisture response function, with soil moisture reduced by 25%.Field plot location data:There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site).
54 ENVIRONMENTAL SCIENCES↗
Abrupt permafrost thaw drives spatially heterogeneous soil moisture and carbon dioxide fluxes in upland tundra
Permafrost thaw causes the seasonally thawed active layer to deepen, causing the Arctic to shift toward carbon release as soil organic matter becomes susceptible to decomposition. Ground subsidence initiated by ice loss can cause these soils to collapse abruptly, rapidly shifting soil moisture as microtopography changes and also accelerating carbon and nutrient mobilization. The uncertainty of soil moisture trajectories during thaw makes it difficult to predict the role of abrupt thaw in suppressing or exacerbating carbon losses. Here, in this study, we investigated the role of shifting soil moisture conditions on carbon dioxide fluxes during a 13-year permafrost warming experiment that exhibited abrupt thaw. Warming deepened the active layer differentially across treatments, leading to variable rates of subsidence and formation of thermokarst depressions. In turn, differential subsidence caused a gradient of moisture conditions, with some plots becoming consistently inundated with water within thermokarst depressions and others exhibiting generally dry, but more variable soil moisture conditions outside of thermokarst depressions. Experimentally induced permafrost thaw initially drove increasing rates of growing season gross primary productivity (GPP), ecosystem respiration (R eco ), and net ecosystem exchange (NEE) (higher carbon uptake), but the formation of thermokarst depressions began to reverse this trend with a high level of spatial heterogeneity. Plots that subsided at the slowest rate stayed relatively dry and supported higher CO 2 fluxes throughout the 13-year experiment, while plots that subsided very rapidly into the center of a thermokarst feature became consistently wet and experienced a rapid decline in growing season GPP, R eco , and NEE (lower carbon uptake or carbon release). These findings indicate that Earth system models, which do not simulate subsidence and often predict drier active layer conditions, likely overestimate net growing season carbon uptake in abruptly thawing landscapes.
54 ENVIRONMENTAL SCIENCES↗
Improved Representations of Land‐Atmosphere Interactions Over the Continental U.S. Through Dynamic Root Modeling
Previous studies have identified the oversimplified root system representation as a key factor leading to inaccuracies in vegetation‐atmosphere feedbacks. In this study, a dynamic root water uptake scheme in the Noah‐MP land surface model has been coupled to the Weather Research and Forecasting (WRF) model to investigate its impact on the surface hydroclimate variables and land‐atmosphere interactions. To evaluate the impact of the dynamic root, two coupled simulations were conducted, one with the dynamic root water uptake scheme (DynRt) and one with the static root water uptake scheme (StcRt), which is based on the default root representation in Noah‐MP, with slight modifications, primarily in vegetation‐related parameters. Both DynRt and StcRt simulations were conducted with a small ensemble of three members to account for variations in physical parameterizations, initial and boundary forcing and model setup. When compared with reference data sets, the DynRt simulations show improved results than the StcRt simulations, reducing biases in the simulated leaf area index, surface energy fluxes, soil moisture and precipitation. Two different mechanisms through which roots affect land‐atmosphere coupling have been identified. Over the transitional climate zone between the dry and wet climate, the dynamic root scheme affects surface climate and land‐atmosphere coupling mainly through changes in soil moisture through hydraulic redistribution by plant root system. Over the energy‐limited mesic zone, the dynamic root affects regional land‐atmosphere coupling mainly through changes in carbon allocation. This work highlights the importance of dynamic root representation in improving vegetation‐atmosphere simulations by enhancing predictions of water, energy, and carbon fluxes.
54 ENVIRONMENTAL SCIENCES↗
Data from: Lowland Tropical Forests Remain a Methane Sink Under Warming and Long-Term Hurricane Disturbance Recovery
The repository folder contains spreadsheets and script for soil greenhouse gas (GHG) fluxes, soil moisture, soil temperature, air temperature, and precipitation measurements collected from the Tropical Responses to Altered Climate Experiment (TRACE) at the Sabana Research Field Station, El Yunque National Forest (USDA Forest Service; 18°19′28.74″ N, 65°43′50.09″ W) — an open-air field warming experiment located in a lowland tropical forest in Puerto Rico within the Luquillo Experimental Forest (LEF) — six to seven years after Hurricanes Irma and Maria (2017). All spreadsheets for soil and air microclimate data, as well as soil greenhouse gas data, are included as csv files. Air temperature data are also included as Excel spreadsheets (.xlsx). The script is built in R Studio, which is the only software required to run data analysis. This dataset is associated with the manuscript “Larocca Conte G ; Zuvela L ; Cruz-Pérez R ; Barreto-Vélez T ; Becerra-Santillan N ; Campbell S ; Chu H ; Dam T ; Grullón-Penkova I ; Kleit M ; Ortiz-Iglesias D ; Rubio-Lebrón L ; Cavaleri M ; Reed S ; Sihi D ; Wood T ; O'Connell C., 2026. Lowland Tropical Forests Remain a Methane Sink Under Warming and Long-Term Hurricane Disturbance Recovery. Agricultural and Forest Meteorology. In review". The dataset was used to test the effect of warming on soil CH4 dynamics following long-term legacy effects of hurricane disturbance. The dataset includes: - An overall README file in word and pdf format describing methodology and spreadsheets’ structure. - Continuous measurements of soil temperature and moisture from January 2023 to July 2024 measured with Campbell CS655 probes (“TRACE_soil_temperature_and_moisture_2023_cleaned(in).csv” and “TRACE_soil_temperature_and_moisture_2024_cleaned. csv”). - Air temperature data measured with a HOBO MX23O1A data logger (“Hobo air temperature 2023 Sep 2024” and “Hobo air temperature 2023 Sep 2024” – “CSV FILES folders”). - Precipitation data from a nearby weather tower downloaded from González et al. (2025; “sabana_2020-2025.csv”). - Soil CH4 and CO2 effluxes measured intermittently in two summer campaigns (June – August 2023 and June – July 2024) with a LI-COR 8200-01S Portable Smart Chamber coupled with a LI-COR LI-7810 CH4/ CO2/H2O Trace Gas Analyzer (“23_24COMBO2.0.csv”). - R markdown script for data analysis (“Trace new_PLOTS.Rmd”).
54 ENVIRONMENTAL SCIENCES↗
Effect of Assimilating SMAP Soil Moisture on CO2 and CH4 Fluxes through Direct Insertion in a Land Surface Model
Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.
SMAP↗
Isolating the Impacts of Soil Moisture Initialization on Land Carbon Fluxes at the Sub-Seasonal to Seasonal Scale
Soil moisture, through its impact on transpiration, plays a significant role in controlling the productivity of terrestrial vegetation. Initial soil moisture conditions in a seasonal forecast may therefore affect the forecast of land carbon uptake. Here we investigate the relative impacts of soil moisture initialization and carbon reservoir initialization on forecasts of land carbon fluxes at the sub-seasonal to seasonal (S2S) scale. The bias-corrected, retrospective meteorology of NASA Global Modeling and Assimilation Office (GMAO)’s S2S ensemble forecast was used to force the stand-alone Catchment-CN model and thereby estimate terrestrial carbon responses out to nine lead months. Our results show that soil moisture initialization is a major contributor (approximately 44%) to the high global carbon uptake forecast skill seen during the first three lead months. The carbon reservoir initialization explains roughly another half of the monthly carbon forecast skill during this period and becomes relatively more important at longer leads (while the overall forecast skill decreases after the 3 lead month), suggesting a slower but longer-lasting influence of carbon reservoir initialization on carbon fluxes. Our results highlight the significance of a good soil moisture initialization for improved forecasts of carbon fluxes at leads of several months, further support for the usefulness of assimilating the satellite based soil moisture information into terrestrial biosphere models and of a short term carbon forecast to understand current events with often a lag in the availability of flux estimates.
Land carbon↗
Throughfall-Reduction Drying Effects on Soil Respiration, Moisture, and Temperature in Four Distinct Lowland Panamanian Forests from 2015-2022
Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that throughfall reduction (i.e. chronic drying) would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We conducted a field study in four distinct lowland Panamanian forests that vary in background rainfall and soil fertility. In each forest we constructed throughfall reduction structures that reduce moisture inputs to plots by ~50% (see methods). In drying and paired control plots we measured soil CO2 fluxes, soil moisture (volume/volume), soil temperature (°C), air temperature (°C), and forest floor biomass during wet-dry cycles (2015 – 2022). We also collected litterfall biomass and surveyed all tree species for diameter at breast height (dbh), and identified tree species in 2018 and 2019.Results:We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Chronic throughfall exclusion also suppressed soil moisture across the four forests, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks. Datasets included: Datasets included here include .csv and .xls files for soil respiration (carbon dioxide flux) collected using the LiCor (see methods), air temperature °C , soil moisture (vl/vl), and soil temperature °C. Soil moisture and soil temperature were collected at 0-10cm depths using hand-held probes (see methods). Data are on ~3 week timescales from 2015-2022 with some gaps. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.
54 ENVIRONMENTAL SCIENCES↗
Throughfall-Reduction Drying Effects on Soil Moisture and Soil Temperature at 30-Minute Intervals Four Lowland Panamanian Forests
Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We also surveyed all tree species and identified to species in 2018 and 2019.Results: We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Chronic throughfall exclusion also suppressed soil moisture across the four forests, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (Cusack et al. 2023). Datasets included: Datasets here include .csv and .xls files for volumetric soil moisture (volume/volume) and soil temperature (°C). Data were taken at 30-minute intervals at 5cm and 20cm depths using permanent probes and data loggers (see methods). Data presented are from 2018-2019. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.
54 ENVIRONMENTAL SCIENCES↗
Throughfall-Reduction Drying Effects on Gravimetric Soil Moisture at Two Depths in Four Lowland Panamanian Forests from 2015-2022
Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We also surveyed all tree species and identified to species in 2018 and 2019.Results: We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Chronic throughfall exclusion also suppressed soil moisture across the four forests to 20cm depths, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Datasets included here include .csv and .xls files for gravimetric soil moisture (weight/weight). Soil moisture was collected on a quarterly basis from 0-10 cm and 10-20 cm depths using hand-held constant-volume soil corers. Data are on ~3 month timescales from 2015-2022 with some gaps. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.
54 ENVIRONMENTAL SCIENCES↗
Throughfall-Reduction Drying Effects on Forest Floor Plant Tissue Biomass (Oi+Oe soil horizons) and Moisture Content in Four Lowland Panamanian Forests
Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We also surveyed all tree species and identified to species in 2018 and 2019.Results: We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Forest floor biomass peaked in the dry season, in contrast. Chronic throughfall exclusion also suppressed soil moisture across the four forests to 20cm depths, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Datasets included here include .csv and .xls files for forest floor biomass (equivalent to the Oi+Oe soil horizons), and a subset include forest floor biomass moisture content (weight/weight) in the study plots. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.
54 ENVIRONMENTAL SCIENCES↗