The forest, the cicadas and the holey fluxes: Periodical cicada impacts on soil respiration depends on tree mycorrhizal type.

The emergence of billions of periodical cicadas affects plant and animal communities profoundly, yet little is known about cicada impacts on soil carbon fluxes. We investigated the effects of Brood X cicadas (Magicicada septendecim, M. cassinii and M. septendeculain) on soil CO2 fluxes (RS ) in three Indiana forests. We hypothesized RS would be sensitive to emergence hole density, with the greatest effects occurring in soils with the lowest ambient fluxes. In support of our hypothesis, RS increased with increasing hole density and greater effects were observed near AM-associating trees (which expressed lower ambient fluxes) than near EcM-associating trees. Additionally, RS from emergence holes increased the temperature sensitivity (Q10 ) of RS by 13%, elevating the Q10 of ecosystem respiration. Brood X cicadas increased annual RS by ca. 2.5%, translating to an additional 717 Gg of CO2 across forested areas. As such, periodical cicadas can have substantial effects on soil processes and biogeochemistry.

Evaluation of effects of heat released from SOC decomposition on soil carbon stock and temperature.

Heat released from soil organic carbon (SOC) decomposition (referred to as microbial heat hereafter) could alter the soil's thermal and hydrological conditions, subsequently modulate SOC decomposition and its feedback with climate. While understanding this feedback is crucial for shaping policy to achieve specific climate goal, it has not been comprehensively assessed. This study employs the ORCHIDEE-MICT model to investigate the effects of microbial heat, referred to as heating effect, focusing on their impacts on SOC accumulation, soil temperature and net primary productivity (NPP), as well as implication on land-climate feedback under two CO2 emissions scenarios (RCP2.6 and RCP8.5). The findings reveal that the microbial heat decreases soil carbon stock, predominantly in upper layers, and elevates soil temperatures, especially in deeper layers. This results in a marginal reduction in global SOC stocks due to accelerated SOC decomposition. Altered seasonal cycles of SOC decomposition and soil temperature are simulated, with the most significant temperature increase per unit of microbial heat (0.31 K J-1) occurring at around 273.15 K (median value of all grid cells where air temperature is around 273.15 K). The heating effect leads to the earlier loss of permafrost area under RCP8.5 and hinders its restoration under RCP2.6 after peak warming. Although elevated soil temperature under climate warming aligns with expectation, the anticipated accelerated SOC decomposition and large amplifying feedback on climate warming were not observed, mainly because of reduced modeled initial SOC stock and limited NPP with heating effect. These underscores the multifaceted impacts of microbial heat. Comprehensive understanding of these effects would be vital for devising effective climate change mitigation strategies in a warming world.

Warming positively promoted community appearance restoration of the degraded alpine meadow although accompanied by topsoil drying.

On-going climate warming is threatening the ecological function of grassland ecosystems. However, whether warming has positive effects on community microhabitats and appearance, especially in degraded grasslands, remains elusive. To address this issue, we conducted a 2-year field experiment on the severely degraded alpine meadow and undegraded alpine meadow with no warming and warming treatments. Community coverage and height in degraded meadow significantly increased under warming, while these changes were not significant in undegraded meadow. Two-year warming increased the community height of degraded meadow and undegraded meadow by 56.55% and 10.99%, respectively. Warming also increased community coverage by 41.88% in degraded meadow and decreased community coverage by 3.01% in undegraded meadow. Moreover, the response of topsoil temperature to warming was stronger in degraded meadow (6.89%) than in undegraded meadow (- 0.26%), while the negative response of topsoil moisture to warming was weaker in degraded meadow (- 13.95%) than in undegraded meadow (- 20.00%). The SEMs further demonstrated that warming had positive effects on topsoil temperature and community height, while had negative effects on topsoil moisture both in degraded and undegraded meadows. Our results confirm that warming-induced soil drying is an important pathway affecting the community appearance in alpine meadows. These findings highlight that warming has positive effects on community height and coverage and is particularly effective in improving community coverage appearance in severely degraded alpine meadow with topsoil drying.

Seasonal and diurnal variations in soil respiration rates at a treeline ecotone and a lower distribution limit of subalpine forests.

This study examined the seasonal and diurnal variations in soil respiration rates (RS) during a growing season at the treeline ecotone (2,800 m) and the lower distribution limit (1,600 m) of subalpine forests on a volcanic mountain in Japan. The aboveground biomass, the total RS during the growing season, and the RS per day during the growing season were lower at 2,800 m than those at 1,600 m. Seasonal RS variations positively correlated with those of soil and air temperatures at both elevations, and this tendency was more apparent at 1,600 m than 2,800 m. The mean volumetric soil water content (WS) during the growing season was much lower at 2,800 m than 1,600 m because of the scoria substrate at 2,800 m. The monthly mean diel cycle of RS was positively correlated with the soil temperature at each elevation every month, whereas that at 1,600 m was negatively correlated with that of the WS. The RS at 2,800 m decreased during the daytime especially in August, despite no changes in the WS. The decrease in RS after precipitation at 1,600 m was higher than that at 2,800 m. Seasonal and diurnal RS variations could be reproduced from soil and air temperatures, and WS. Estimating soil respiration rate from these variables will help understand the future carbon budget of forests due to global warming.

Temperature-Corrected Calibration of GS3 and TEROS-12 Soil Water Content Sensors.

The continuous monitoring of soil water content is commonly carried out using low-frequency capacitance sensors that require a site-specific calibration to relate sensor readings to apparent dielectric bulk permittivity (Kb) and soil water content (θ). In fine-textured soils, the conversion of Kb to θ is still challenging due to temperature effects on the bound water fraction associated with clay mineral surfaces, which is disregarded in factory calibrations. Here, a multi-point calibration approach accounts for temperature effects on two soils with medium to high clay content. A calibration strategy was developed using repacked soil samples in which the Kb-θ relationship was determined for temperature (T) steps from 10 to 40 °C. This approach was tested using the GS3 and TEROS-12 sensors (METER Group, Inc. Pullman, WA, USA; formerly Decagon Devices). Kb is influenced by T in both soils with contrasting T-Kb relationships. The measured data were fitted using a linear function θ = aKb + b with temperature-dependent coefficients a and b. The slope, a(T), and intercept, b(T), of the loam soil were different from the ones of the clay soil. The consideration of a temperature correction resulted in low RMSE values, ranging from 0.007 to 0.033 cm3 cm-3, which were lower than the RMSE values obtained from factory calibration (0.046 to 0.11 cm3 cm-3). However, each experiment was replicated only twice using two different sensors. Sensor-to-sensor variability effects were thus ignored in this study and will be systematically investigated in a future study. Finally, the applicability of the proposed calibration method was tested at two experimental sites. The spatial-average θ from a network of GS3 sensors based on the new calibration fairly agreed with the independent area-wide θ from the Cosmic Ray Neutron Sensor (CRNS). This study provided a temperature-corrected calibration to increase the accuracy of commercial sensors, especially under dry conditions, at two experimental sites.

Estimation of annual soil CO2 efflux under the erosion and deposition conditions by measuring and modeling its respiration rate in southern China.

Soil respiration (Rs) is a crucial ecological process of carbon (C) cycling in the terrestrial ecosystems, and soil erosion has a significant impact on its C budget and balance. However, the variations of Rs rate and their CO2 efflux induced by erosion are currently poorly understood. To this end, four landscape positions (top, up, middle and toe) with different erosional and depositional characteristics were selected on a typical eroded slope in southern China to conduct field experiments, aiming to explore the effects of erosion and deposition on Rs among various sites. From March 2021 to February 2022, the in-situ Rs were measured using an automated soil respiration system, together with soil temperature at 5 cm depth (Ts5) and water content at 10 cm depth (SWC10). We initially constructed various Rs models across a one-year period, based on its relationships with Ts5 and SWC10. Subsequently, the seasonal changes of Rs at different erosional sites were simulated by the optimum models, and their annual CO2 fluxes were further estimated. The results showed that Rs rates at all sites displayed a bimodal seasonal pattern, with the highest values in May and August. And the measured Rs of the eroding and depositional sites were 0.05-7.71 and 1.47-13.03 µmol m-2 s-1, respectively. Also, remarkably higher Ts5 and SWC10 were observed in depositional sites versus the eroding sites (P < 0.05). Additionally, Rs rates at all sites were positively correlated with SOC and Ts5, but negatively correlated with SWC10. Herein, Rs models to single- and double-variable were established at different positions, and we found that the fitted R2 and AIC differed on various sites, primarily in erosional and depositional sites. Furthermore, through the best-fitting models (higher R2 and lowest AIC) we screened, the average Rs values of 3.03 and 4.46 µmol m-2 s-1 were quantitatively estimated for the eroding and depositional sites, respectively. Finally, it could be further assessed that the mean annual soil CO2-C efflux of eroded site (1104.14 g m-2) was significantly lower than that of depositional site (1629.46 g m-2). These findings highlighted the effect of erosion and deposition on Rs, which will facilitate a better understanding of C cycling in terrestrial ecosystems.

Effects of cultural practices on soil respiration in hazelnut orchards and a comparison with an adjacent natural oak forest.

Soil respiration (RS) is one of the largest terrestrial sources of CO2 causing global warming and may vary according to land use and vegetation type. Türkiye is in the first place in the world in terms of area of hazelnut orchards that are generally converted from natural forests. The aim of this study was the comparison of the effects of cultural practices (pruning, fertilizing, and pruning+fertilizing) on RS in hazelnut orchards and that of the adjacent natural oak forest. Every trial site had a statistically similar annual mean RS, which ranged from 0.15 to 1.55 g C m-2 day-1. The RS on the sites was different only in the spring season and was similar in the other seasons. The RS of the pruned and fertilized hazelnut orchard (Hpf) in the spring was 58% greater than the unmaintained hazelnut orchard (Hc) and oak forest and 28% greater than the only fertilized hazelnut orchard (Hf). The RS of Hpf was also greater than other sites in most monthly measurements. While the positive correlation between soil moisture and RS was on an annual basis (r = 0.44), it was higher in summer (r = 0.61) and autumn (r = 0.55) seasons. The negative correlation between soil temperature and RS in the summer and autumn seasons evolved positively in winter. The results of the study suggest that the maintenance practices applied in the hazelnut garden could increase RS in the spring when soil moisture and temperature are optimal but have no effect in other seasons or on an annual basis.

Sub-regional variation in atmospheric and land variables regulates tea yield in the Dooars region of West Bengal, India.

Climatic variables can have localized variations within a region and these localized climate patterns can have significant effect on production of climate-sensitive crops such as tea. Even though tea cultivation and industries significantly contribute to employment generation and foreign earnings of several South Asian nations including India, sub-regional differences in the effects of climatic and soil variables on tea yield have remained unexplored since past studies focused on a tea-producing region as a whole and did not account for local agro-climatic conditions. Here, using a garden-level panel dataset based on tea gardens of Dooars region, a prominent tea-producing region in India, we explored how sub-regional variations in climatic and land variables might differently affect tea yield within a tea-producing region. Our analysis showed that the Dooars region harboured significant spatial variability for different climatic (temperature, precipitation, surface solar radiation) and soil temperature variables. Using graph-based Louvain clustering of tea gardens, we identified four spatial sub-regions which varied in terms of topography, annual and seasonal distribution of climatic and land variables and tea yield. Our sub-region-specific panel regression analyses revealed differential effects of climatic and land variables on tea yield of different sub-regions. Finally, for different emission scenario, we also projected future (2025-2100) tea yield in each sub-region based on predictions of climatic variables from three GCMs (MIROC5, CCSM4 and CESM1(CAM5)). A large variation in future seasonal production changes was projected across sub-regions (-23.4-35.7% changes in premonsoon, -4.2-3.1% changes in monsoon and -10.9-10.7% changes in postmonsoon tea production, respectively).

Performance of Different Crop Models in Simulating Soil Temperature.

Soil temperature is one of the key factors to be considered in precision agriculture to increase crop production. This study is designed to compare the effectiveness of a land surface model (Noah Multiparameterization (Noah-MP)) against a traditional crop model (Environmental Policy Integrated Climate Model (EPIC)) in estimating soil temperature. A sets of soil temperature estimates, including three different EPIC simulations (i.e., using different parameterizations) and a Noah-MP simulations, is compared to ground-based measurements from across the Central Valley in California, USA, during 2000-2019. The main conclusion is that relying only on one set of model estimates may not be optimal. Furthermore, by combining different model simulations, i.e., by taking the mean of two model simulations to reconstruct a new set of soil temperature estimates, it is possible to improve the performance of the single model in terms of different statistical metrics against the reference ground observations. Containing ratio (CR), Euclidean distance (dist), and correlation co-efficient (R) calculated for the reconstructed mean improved by 52%, 58%, and 10%, respectively, compared to both model estimates. Thus, the reconstructed mean estimates are shown to be more capable of capturing soil temperature variations under different soil characteristics and across different geographical conditions when compared to the parent model simulations.

Time Domain Transmissiometry-Based Sensor for Simultaneously Measuring Soil Water Content, Electrical Conductivity, Temperature, and Matric Potential.

Owing to the increasing popularity of smart agriculture in recent years, it is necessary to develop a single sensor that can measure several soil properties, particularly the soil water content and matric potential. Therefore, in this study, we developed a sensor that can simultaneously measure soil water content (θ), electrical conductivity (σb), temperature, and matric potential (ψ). The proposed sensor can determine θ and σb using time domain transmissiometry and can determine ψ based on the capacitance of the accompanying ceramic plate. A series of laboratory and field tests were conducted to evaluate the performance of the sensor. The sensor output values were correlated with the soil properties, and the temperature dependence of the sensor outputs was evaluated. Additionally, field tests were conducted to measure transient soil conditions over a long period. The results show that the developed sensor can measure each soil property with acceptable accuracy. Moreover, the root-mean-square errors of the sensor and reference values were 1.7 for the dielectric constant (which is equivalent to θ), 62 mS m-1 for σb, and 0.05-0.88 for log ψ. The temperature dependence was not a problem, except when ψ was below -100 kPa. The sensor can be used for long-term measurements in agricultural fields and exhibited sufficient lifetime and performance. We believe that the developed sensor can contribute to smart agriculture and research on heat and mass transfer in soil.

Effects of different colors of film mulch on soil temperature and rice growth in a non-flooded condition.

BACKGROUND: Rice cultivation under film mulching with no flooding is widely used as an effective water-saving technology. Different colors of film mulch have different effects on the soil hydrothermal environment and crop growth because of their different optical properties. However, the effects of different colors of film mulch on soil temperature and rice physiological growth are not clearly understood. RESULTS: Field experiments were conducted in 2019 and 2020 to investigate the effects of different color mulches on soil temperature and rice growth in a non-flooded condition. Transparent film (TM), black film (BM), two-color film (BWM, silver on the front and black on the back), and no film (NM) in a non-flooded condition were designed. Soil temperature variation at different soil depths of 0-0.25 m and rice plant height, stem thickness, dry matter, yield and quality were monitored. The results showed that compared to no mulching, the mulching treatment effectively increased the average soil temperature during the whole rice growth stage with the soil temperature ranked TM > BM > BWM. Compared with NM, the BM and BWM treatments increased rice yield by 12.1-17.7% and 6.4-14.4% in 2019 and 2020, respectively. The BWM had 18.2% and 6.8% greater gel consistency than NM in 2019 and 2020, respectively. CONCLUSION: Transparent film should be applied with care because of the high soil temperature stress. Black film and two-color film (silver on the front and black on the back) could be better option for rice yield, increasing and quality improving in a non-flooded condition. © 2023 Society of Chemical Industry.

Extreme learning machine for soil temperature prediction using only air temperature as input.

Soil temperature (TS) is a crucial parameter in many fields, especially agriculture. In developing countries like Algeria, the soil temperatures (TS) and the meteorological data are limited. This study investigates the use of Extreme Learning Machine (ELM) for the accurate prediction of daily ST at three different depths (30 cm, 60 cm, and 100 cm) using a minimal number of climatic inputs. The inputs used in this study include maximum and minimum air temperatures, relative humidity, and day of the year (DOY) as a representative of the temporal component. Five different combinations of inputs were used to develop ELM models and determine the best set of input variables. The ELM models were then compared with traditional methods such as multiple linear regression, artificial neural networks, and adaptive neuro-fuzzy inference system. Based on evaluation metrics such as R, RMSE, and MAPE, the ELM models with air temperatures and DOY as inputs (ELM-M0 and ELM-M3) demonstrated superior performance at all depths when compared to the other techniques. The most accurate predictions were found at a depth of 100 cm using the ELM-M3 model, which employed inputs of minimum and maximum air temperatures and DOY, with R value of 0.98, RMSE of 0.68 °C, and MAPE of 3.4%. The results demonstrate that the inclusion of DOY in the climatic dataset significantly enhances the performance and accuracy of machine learning models for ST prediction. The ELM was found to be a fast, simple, effective, and useful tool for TS prediction.

Preforming floral primordia converge on a narrow range of stages at dormancy despite multiple effects of temperature on development.

Phenological studies often focus on relationships between flowering date and temperature or other environmental variables. Yet in species that preform flowers, anthesis is one stage of a lengthy developmental process, and effects of temperature on flower development in the year(s) before flowering are largely unknown. We investigated the effects of temperature during preformation on flower development in Vaccinium vitis-idaea. Using scanning electron microscopy, we established scores for developing primordia and examined effects of air temperature, depth of soil thaw, time of year and previous stage on development. Onset of flower initiation depends on soil thaw, and developmental change is greatest at early stages and during the warmest months. Regardless of temperature and time during the season, all basal floral primordia pause development at the same stage before whole-plant dormancy. Once primordia are initiated, development does not appear to be influenced by air temperature differences within the range of variation among our sites. There may be strong endogenous flower-level controls over development, particularly the stage at which morphogenesis ceases before dormancy. However, the strength of such internal controls in the face of continuing temperature extremes under a changing climate is unclear.

A quantitative analysis of temperature-dependent seasonal dormancy cycling in buried Arabidopsis thaliana seeds can predict seedling emergence in a global warming scenario.

Understanding how the environment regulates seed-bank dormancy changes is essential for forecasting seedling emergence in actual and future climatic scenarios, and to interpret studies of dormancy mechanisms at physiological and molecular levels. Here, we used a population threshold modelling approach to analyse dormancy changes through variations in the thermal range permissive for germination in buried seeds of Arabidopsis thaliana Cvi, a winter annual ecotype. Results showed that changes in dormancy level were mainly associated with variations in the higher limit of the thermal range permissive for germination. Changes in this limit were positively related to soil temperature during dormancy release and induction, and could be predicted using thermal time. From this, we developed a temperature-driven simulation to predict the fraction of the seed bank able to germinate in a realistic global warming scenario that approximated seedling emergence timing. Simulations predicted, in accordance with seedling emergence observed in the field, an increase in the fraction of the seed bank able to emerge as a result of global warming. In addition, our results suggest that buried seeds perceive changes in the variability of the mean daily soil temperature as the signal to change between dormancy release and induction according to the seasons.

Diverging patterns at the forest edge: Soil respiration dynamics of fragmented forests in urban and rural areas.

As urbanization and forest fragmentation increase around the globe, it is critical to understand how rates of respiration and carbon losses from soil carbon pools are affected by these processes. This study characterizes soils in fragmented forests along an urban to rural gradient, evaluating the sensitivity of soil respiration to changes in soil temperature and moisture near the forest edge. While previous studies found elevated rates of soil respiration at temperate forest edges in rural areas compared to the forest interior, we find that soil respiration is suppressed at the forest edge in urban areas. At urban sites, respiration rates are 25% lower at the forest edge relative to the interior, likely due to high temperature and aridity conditions near urban edges. While rural soils continue to respire with increasing temperatures, urban soil respiration rates asymptote as temperatures climb and soils dry. Soil temperature- and moisture-sensitivity modeling shows that respiration rates in urban soils are less sensitive to rising temperatures than those in rural soils. Scaling these results to Massachusetts (MA), which encompasses 0.25 Mha of the urban forest, we find that failure to account for decreases in soil respiration rates near urban forest edges leads to an overestimate of growing-season soil carbon fluxes of >350,000 Mg C. This difference is almost 2.5 times that for rural soils in the analogous comparison (underestimate of <143,000 Mg C), even though rural forest area is more than four times greater than urban forest area in MA. While a changing climate may stimulate carbon losses from rural forest edge soils, urban forests may experience enhanced soil carbon sequestration near the forest edge. These findings highlight the need to capture the effects of forest fragmentation and land use context when making projections about soil behavior and carbon cycling in a warming and increasingly urbanized world.

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Cross-scale regulation of seasonal microclimate by vegetation and snow in the Arctic tundra.

Climate warming is inducing widespread vegetation changes in Arctic tundra ecosystems, with the potential to alter carbon and nutrient dynamics between vegetation and soils. Yet, we lack a detailed understanding of how variation in vegetation and topography influences fine-scale temperatures ("microclimate") that mediate these dynamics, and at what resolution vegetation needs to be sampled to capture these effects. We monitored microclimate at 90 plots across a tundra landscape in western Greenland. Our stratified random study design covered gradients of topography and vegetation, while nested plots (0.8-100 m2 ) enabled comparison across different sampling resolutions. We used Bayesian mixed-effect models to quantify the direct influence of plot-level topography, moisture and vegetation on soil, near-surface and canopy-level temperatures (-6, 2, and 15 cm). During the growing season, colder soils were predicted by shrub cover (-0.24°C per 10% increase), bryophyte cover (-0.35°C per 10% increase), and vegetation height (-0.17°C per 1 cm increase). The same three factors also predicted the magnitude of differences between soil and above-ground temperatures, indicating warmer soils at low cover/height, but colder soils under closed/taller canopies. These findings were consistent across plot sizes, suggesting that spatial predictions of microclimate may be possible at the operational scales of satellite products. During winter, snow cover (+0.75°C per 10 snow-covered days) was the key predictor of soil microclimate. Topography and moisture explained little variation in the measured temperatures. Our results not only underline the close connection of vegetation and snow with microclimate in the Arctic tundra but also point to the need for more studies disentangling their complex interplay across tundra environments and seasons. Future shifts in vegetation cover and height will likely mediate the impact of atmospheric warming on the tundra soil environment, with potential implications for below-ground organisms and ecosystem functioning.

Increased annual methane uptake driven by warmer winters in an alpine meadow.

Pronounced nongrowing season warming and changes in soil freeze-thaw (F-T) cycles can dramatically alter net methane (CH4 ) exchange rates between soils and the atmosphere. However, the magnitudes and drivers of warming impacts on CH4 uptake in different stages of the F-T cycle are poorly understood in cold alpine ecosystems, which have been found to be a net sink of atmospheric CH4 . Here, we reported a year-round ecosystem daily CH4 uptake in an alpine meadow on the Qinghai-Tibetan Plateau after a 5-year warming experiment that included a control, a low-level warming treatment (+2.4℃ at 5 cm soil depth), and a high-level warming treatment (+4.5℃ at 5 cm soil depth). We found that warming shortened the F-T cycle under the low-level warming and soils did not freeze under the high-level warming. Although both warming treatments increased the mean CH4 uptake rate, only the high-level warming significantly increased annual CH4 uptake compared to the control. The warming-induced stimulation of CH4 uptake mainly occurred in the cold season, which was mostly during spring thaw under low-level warming and during the frozen winter under high-level warming due to a longer period with thawed soil. We also found that warming significantly stimulated daily CH4 uptake mainly by reducing near-surface soil water content in the warm season, whereas both soil water content and temperature controlled daily CH4 uptake in different ways during the autumn freeze, frozen winter, and spring thaw periods of the control. Our study revealed a strong warming effect on CH4 uptake during the entire F-T cycle in the alpine meadow, especially the unfrozen winter. Our results also suggested the important roles of soil pH, available phosphorus, and methanotroph abundance in regulating annual CH4 uptake in response to warming, which should be incorporated into biogeochemical models for accurately forecasting CH4  fluxes under future climate scenarios.

Soil Heating in Fire (SheFire): A model and measurement method for estimating soil heating and effects during wildland fires.

Fire has transformative effects on soil biological, chemical, and physical properties in terrestrial ecosystems around the world. While methods for estimating fire characteristics and associated effects aboveground have progressed in recent decades, there remain major challenges in characterizing soil heating and associated effects belowground. Overcoming these challenges is crucial for understanding how fire influences soil carbon storage, biogeochemical cycling, and ecosystem recovery. In this paper, we present a novel framework for characterizing belowground heating and effects. The framework includes (1) an open-source model to estimate fire-driven soil heating, cooling, and the biotic effects of heating across depths and over time (Soil Heating in Fire model; SheFire) and (2) a simple field method for recording soil temperatures at multiple depths using self-contained temperature sensor and data loggers (i.e., iButtons), installed along a wooden stake inserted into the soil (i.e., an iStake). The iStake overcomes many logistical challenges associated with obtaining temperature profiles using thermocouples. Heating measurements provide inputs to the SheFire model, and modeled soil heating can then be used to derive ecosystem response functions, such as heating effects on microorganisms and tissues. To validate SheFire estimates, we conducted a burn table experiment using iStakes to record temperatures that were in turn used to fit the SheFire model. We then compared SheFire predicted temperatures against measured temperatures at other soil depths. To benchmark iStake measurements against those recorded by thermocouples, we co-located both types of sensors in the burn table experiment. We found that SheFire demonstrated skill in interpolating and extrapolating soil temperatures, with the largest errors occurring at the shallowest depths. We also found that iButton sensors are comparable to thermocouples for recording soil temperatures during fires. Finally, we present a case study using iStakes and SheFire to estimate in situ soil heating during a prescribed fire and demonstrate how observed heating regimes would influence seed and tree root vascular cambium survival at different soil depths. This measurement-modeling framework provides a cutting-edge approach for describing soil temperature regimes (i.e., soil heating) through a soil profile and predicting biological responses.

Effects of temperature on seed dormancy and germination of the coastal dune plant Viola grayi: germination phenology and responses to winter warming.

PREMISE: In temperate sand dunes, rising air temperature from climate change could not only further elevate surface soil temperatures during summers, but also drastically change the range of soil temperatures in other seasons. Winter warming may shift the timing of seed germination of dune species that require cold stratification for dormancy release. METHODS: We assessed the effects of temperature on dormancy and germination of Viola grayi seeds and evaluated whether winter warming could affect its germination phenology by conducting germination experiments and analyzing soil temperature data in cold and warm winters. RESULTS: Viola grayi seeds were dormant when dispersed in spring. One-month moist-chilling treatment (4°C) effectively released dormancy, while short, intermittent lower temperatures (alternating 20°/5°C) did not. Continuous higher temperatures induced secondary dormancy in nondormant seeds. During a cold, snowy winter, the surface soil temperatures of the sand dune remained at 0°-2°C for approximately 1 month owing to the accumulated snow, while the period of such stable low soil temperatures was much shorter during a warm, less-snowy winter, and the highest soil temperature reached 20°-25°C. These results suggest that dispersed seeds germinate in the following spring after winter chilling, but they may remain dormant after warm winters. CONCLUSIONS: With winter warming, seed dormancy of V. grayi seeds could be prolonged and the associated germination delayed. Assessing the minimum requirements for dormancy release and the potential to form persistent soil seed banks is important for judging the necessity and urgency of conservation efforts for temperate dune species.