Intermediate Soil Moisture Research Articles

Multi-scale assessment of a cosmic-ray neutron probe observation of soil moisture for surface layer applications in a mountainous forest environment

Soil moisture is critical to the Earth's water cycle as it influences water exchange between the land, atmosphere, and oceans. This study assessed the potential of a cosmic-ray neutron probe (CRNP) to monitor soil moisture dynamics in a forested mountain region, which is critical for water resource management and ecosystem health. Accurate soil moisture monitoring is essential for effectively managing forested mountainous areas, but various limitations exist in such environments. To overcome the complexities of soil moisture monitoring, an observatory consisting of a CRNP, automatic weather sensors, and dataloggers was established. Fifteen capacitance sensor (CS) stations were placed strategically within the CRNP's footprint to ensure strict evaluation. Although each CS measurement revealed the heterogeneity of the experimental site, temporal stability analysis determined the representative soil moisture. The validation of the CRNP and the average results of the 15 surface CS sensors revealed that they were strongly correlated (R = 0.94). It means that the CRNP can describe the dynamics of soil moisture that fluctuate according to physical properties, underscoring its reliability in estimating intermediate scale soil moisture. This correlation remained robust despite differences in rainfall patterns over three years. These findings indicate that the CRNP may be a valuable tool for monitoring soil moisture in a challenging environment. Additionally, the evaluation of the Advanced Microwave Scanning Radiometer-2 (AMSR2), Advanced Scatterometer (ASCAT), and Global Land Data Assimilation System (GLDAS) demonstrated the usefulness of CRNP in supplying reference data. The AMSR2 showed an inadequate temporal pattern (R = 0.35), and the ASCAT achieved the highest correlation agreement (R = 0.67) with the CRNP. The GLDAS also showed close agreement, although with some discrepancies (R = 0.52). The results of this study support the utilization of CRNP and provide insight into establishing and expanding a soil moisture network.

Increases and decreases in soil moisture in water‐limited plant communities cause asymmetrical responses in biomass but not in diversity

AbstractAimsChanges in precipitation patterns, such as the predicted increases in the frequency of climatic extremes, are likely to alter plant communities, but whether responses to drought or to wetter conditions respectively cause consistent, opposite responses is debated. Here, we assessed the response in biomass production and species diversity of water‐limited plant communities to the direction (increase or decrease) and magnitude (micro‐ and macro‐climatic effects) of changes in soil moisture.LocationWe reciprocally translocated soils containing seed banks from two climates (semi‐arid and mediterranean) at a micro‐climatic (opposite slopes) and a macro‐climatic scale (between climates) in Chile.ResultsBiomass production for the soils that were translocated from wetter to drier climates was unrelated to the available soil moisture. The lowest biomass was produced in the wettest climate on the wet slope. Biomass production increased after a translocation to the drier climate (representing the largest change in climate). Nonetheless, the highest overall biomass for the wet to dry translocation was produced on the mediterranean dry slope with intermediate soil moisture. However, on the same mediterranean dry slope, biomass was almost zero for soil translocated the other way round (from drier to wetter). Diversity after 24 months was unaffected by micro‐climatic change, but soils transplanted toward the drier climate yielded a plant community with increased diversity.ConclusionOur results showed direction and magnitude of climate change but also the response factor that is studied matters to detect direction‐dependent responses; i.e., species richness had a linear and reversible response. However, the response of biomass depended on the origin of the transplanted material (soil and plant community), indicating history dependence (hysteresis). This emphasizes that responses to unidirectional climate manipulation experiments may not be able to capture the entire nature of the response of plant communities to climate change.

Tree growth potential and its relationship with soil moisture conditions across a heterogeneous boreal forest landscape

Forest growth varies across landscapes due to the intricate relationships between various environmental drivers and forest management. In this study, we analysed the variation of tree growth potential across a landscape scale and its relation to soil moisture. We hypothesised that soil moisture conditions drive landscape-level variation in site quality and that intermediate soil moisture conditions demonstrate the highest potential forest production. We used an age-independent difference model to estimate site quality in terms of maximum achievable tree height by measuring the relative change in Lorey’s mean height for a five year period across 337 plots within a 68 km2 boreal landscape. We achieved wall-to-wall estimates of site quality by extrapolating the modelled relationship using repeated airborne laser scanning data collected in connection to the field surveys. We found a clear decrease in site quality under the highest soil moisture conditions. However, intermediate soil moisture conditions did not demonstrate clear site quality differences; this is most likely a result of the nature of the modelled soil moisture conditions and limitations connected to the site quality estimation. There was considerable unexplained variation in the modelled site quality both on the plot and landscape levels. We successfully demonstrated that there is a significant relationship between soil moisture conditions and site quality despite limitations associated with a short study period in a low productive region and the precision of airborne laser scanning measurements of mean height.

Evaluation of Three Soil Moisture Profile Sensors Using Laboratory and Field Experiments.

Soil moisture profile sensors (SMPSs) have a high potential for climate-smart agriculture due to their easy handling and ability to perform simultaneous measurements at different depths. To date, an accurate and easy-to-use method for the evaluation of long SMPSs is not available. In this study, we developed laboratory and field experiments to evaluate three different SMPSs (SoilVUE10, Drill&Drop, and SMT500) in terms of measurement accuracy, sensor-to-sensor variability, and temperature stability. The laboratory experiment features a temperature-controlled lysimeter to evaluate intra-sensor variability and temperature stability of SMPSs. The field experiment features a water level-controlled sandbox and reference TDR measurements to evaluate the soil water measurement accuracy of the SMPS. In both experiments, a well-characterized fine sand was used as measurement medium to ensure homogeneous dielectric properties in the measurement domain of the sensors. The laboratory experiments with the lysimeter showed that the Drill&Drop sensor has the highest temperature sensitivity with a decrease of 0.014 m3 m-3 per 10 °C, but at the same time showed the lowest intra- and inter-sensor variability. The field experiment with the sandbox showed that all three SMPSs have a similar performance (average RMSE ≈ 0.023 m3 m-3) with higher uncertainties at intermediate soil moisture contents. The presented combination of laboratory and field tests were found to be well suited to evaluate the performance of SMPSs and will be used to test additional SMPSs in the future.

Characterizing the Response of Vegetation Cover to Water Limitation in Africa Using Geostationary Satellites.

Hydrological interactions between vegetation, soil, and topography are complex, and heterogeneous in semi‐arid landscapes. This along with data scarcity poses challenges for large‐scale modeling of vegetation‐water interactions. Here, we exploit metrics derived from daily Meteosat data over Africa at ca. 5 km spatial resolution for ecohydrological analysis. Their spatial patterns are based on Fractional Vegetation Cover (FVC) time series and emphasize limiting conditions of the seasonal wet to dry transition: the minimum and maximum FVC of temporal record, the FVC decay rate and the FVC integral over the decay period. We investigate the relevance of these metrics for large scale ecohydrological studies by assessing their co‐variation with soil moisture, and with topographic, soil, and vegetation factors. Consistent with our initial hypothesis, FVC minimum and maximum increase with soil moisture, while the FVC integral and decay rate peak at intermediate soil moisture. We find evidence for the relevance of topographic moisture variations in arid regions, which, counter‐intuitively, is detectable in the maximum but not in the minimum FVC. We find no clear evidence for wide‐spread occurrence of the “inverse texture effect” on FVC. The FVC integral over the decay period correlates with independent data sets of plant water storage capacity or rooting depth while correlations increase with aridity. In arid regions, the FVC decay rate decreases with canopy height and tree cover fraction as expected for ecosystems with a more conservative water‐use strategy. Thus, our observation‐based products have large potential for better understanding complex vegetation‐water interactions from regional to continental scales.

Field scale soil water prediction based on areal soil moisture measurements using cosmic-ray neutron sensing in a karst landscape

Cosmic-ray neutron sensing (CRNS) is a newly-developed method for continuously measuring soil water content (SWC) at the hectometer horizontal scale. However, it is unknown whether CRNS-based SWC could be used for soil moisture prediction at field scale. In this study, we try to predict field scale SWC using the CRNS combined with the temporal stability analysis in a karst watershed. The CRNS was installed in a karst watershed as well as capacitance-based SWC sensors located in five land uses. The CRNS was calibrated by eighteen manual sampling procedures. A weather station was established about 200 m away from the CRNS for monitoring basic meteorological variables. The mean footprint radius and effective depth of the CRNS were 311.51 m and 11.98 cm, respectively. The CRNS can accurately estimate intermediate scale soil moisture, with a coefficient of determination (R2) of 0.89. Significant correlations (P < 0.01) were observed between SWC measured by the CRNS and Em-50 instruments. Though the SWC derived from the CRNS was significantly lower than that from Em-50 instruments in different land uses, the SWCs at field scale can be predicted accurately. The influences of landforms and land uses on prediction accuracy were not obvious from our data. The CRNS has great potential to improve water resources management in areas with greater heterogeneity.

Forest canopy mitigates soil N2O emission during hot moments

Riparian forests are known as hot spots of nitrogen cycling in landscapes. Climate warming speeds up the cycle. Here we present results from a multi-annual high temporal-frequency study of soil, stem, and ecosystem (eddy covariance) fluxes of N2O from a typical riparian forest in Europe. Hot moments (extreme events of N2O emission) lasted a quarter of the study period but contributed more than half of soil fluxes. We demonstrate that high soil emissions of N2O do not escape the ecosystem but are processed in the canopy. Rapid water content change across intermediate soil moisture was a major determinant of elevated soil emissions in spring. The freeze-thaw period is another hot moment. However, according to the eddy covariance measurements, the riparian forest is a modest source of N2O. We propose photochemical reactions and dissolution in canopy-space water as reduction mechanisms.

Correction efficiency and error characteristics for cosmic-ray soil moisture on mountainous terrain

A Cosmic-Ray Neutron Probe (CRNP) is a promising tool for obtaining reliable intermediate scale soil moisture. Although there are sound ways of correcting neutron counts and calibrating soil moisture, it is difficult to obtain all the data required for corrections and calibration in a complex environment. In this study, three major correcting variables (i.e., absolute humidity, air pressure, incoming neutron flux intensity) were evaluated to determine their impacts on the neutron counts in the Seolmacheon experimental site (SMC) located in mountainous terrain. Efficiency of correction factors for atmospheric water vapor (fwv), air pressure (fp,), and incoming neutron flux intensity (fi) was independently assessed through comparisons between the variables and a inversely calculated N0 (N0,inv). Particular attention was given to the expected biases and errors in estimated soil moisture (SMCRNP) with and without each correction factor, especially at the early stage of the calibration period. Air pressure had the greatest impact on neutron count at the SMC site, followed by absolute humidity. The dependency of neutron count on air pressure (absolute humidity) was found from the inverse relationship with N0,inv that is not corrected for air pressure (absolute humidity), with correlation coefficient −0.88 (−0.78). When fp (fwv) was applied, the dependency of neutron count on the corresponding variable was significantly reduced, with a correlation coefficient 0.06 (−0.07). On the other hand, the effect of applying fi was contrary, slightly degrading the result. When neutron count was not corrected for air pressure (absolute humidity), the performance of SMCRNP decreased, with a correlation coefficient of 0.74 (0.90) and Root Mean Square Error (RMSE) of 0.030 m3/m3 (0.026 m3/m3) at best. The best result was obtained when both of them were corrected (r = 0.95, RMSE = 0.014 m3/m3). As data accumulates, error metrics in terms of bias and variability converged at approximately one periodic cycle, implying at least one seasonal cycle is necessary for recalibration. However, in a case where a variable with large intra-seasonal variability (e.g., air pressure in this study) is missing, it is recommended to adopt a multi-point N0 method.The procedures suggested in this study allow independent evaluations of the factors for which neutron count is corrected, thus providing a basis for judging which factors are appropriate and which are not. In addition, N0 can be more efficiently tuned according to the characteristics of the errors in SMCRNP. Based on these analyses, CRNP stations will be able to selectively apply favorable correction factors under various kinds of local characteristics, making it easier to achieve target accuracy and precision.

The Indian COSMOS Network (ICON): Validating L-Band Remote Sensing and Modelled Soil Moisture Data Products

Availability of global satellite based Soil Moisture (SM) data has promoted the emergence of many applications in climate studies, agricultural water resource management and hydrology. In this context, validation of the global data set is of substance. Remote sensing measurements which are representative of an area covering 100 m2 to tens of km2 rarely match with in situ SM measurements at point scale due to scale difference. In this paper we present the new Indian Cosmic Ray Network (ICON) and compare it’s data with remotely sensed SM at different depths. ICON is the first network in India of the kind. It is operational since 2016 and consist of seven sites equipped with the COSMOS instrument. This instrument is based on the Cosmic Ray Neutron Probe (CRNP) technique which uses non-invasive neutron counts as a measure of soil moisture. It provides in situ measurements over an area with a radius of 150–250 m. This intermediate scale soil moisture is of interest for the validation of satellite SM. We compare the COSMOS derived soil moisture to surface soil moisture (SSM) and root zone soil moisture (RZSM) derived from SMOS, SMAP and GLDAS_Noah. The comparison with surface soil moisture products yield that the SMAP_L4_SSM showed best performance over all the sites with correlation (R) values ranging from 0.76 to 0.90. RZSM on the other hand from all products showed lesser performances. RZSM for GLDAS and SMAP_L4 products show that the results are better for the top layer R = 0.75 to 0.89 and 0.75 to 0.90 respectively than the deeper layers R = 0.26 to 0.92 and 0.6 to 0.8 respectively in all sites in India. The ICON network will be a useful tool for the calibration and validation activities for future SM missions like the NASA-ISRO Synthetic Aperture Radar (NISAR).

Investigating the Spatio-Temporal dynamics in the soil water storage in Alberta’s Agricultural region

Anomalous atmospheric conditions which, for the most part, manifest in the form of heavy precipitation events leading to the generation of pluvial or fluvial flooding in some years, or as extended extreme dry spells resulting in the development of severe drought conditions in other years has significant implications for subsurface moisture budgets in regional and local catchments in the Canadian Prairies. The myriad implications of these frequent and extended dry spells over Alberta’s Agricultural Region can be far reaching economically, socially and otherwise, thereby exerting substantial negative toll on agricultural productivity (crop cultivation, livestock husbandry, and pasture management) within the Province. Soil moisture dynamics both in spatial and temporal scales has critical implications for agricultural water management especially under semi-arid climate conditions that are typical of the local- and regional-scale catchments in southern Alberta. This study is focused on the assessment of the observations of the soil water storage, soil temperature and meteorological variables (precipitation and air temperature) acquired from 39 monitoring stations spanning a 12-year period with the principal objective of examining the spatial and temporal dynamics in the shallow and deep soil water storage processes across the study domain. This study revealed that the moisture anomalies in the deep soil moisture store exhibit the longest hydrologic memory relative to those in the shallow and intermediate soil moisture storages as well as those in the meteorological variables across the study domain. The anomalies computed for the soil moisture measurements undertaken in the deep soil moisture store revealed frequency features that are dominant at seasonal cycle (9-month) and at a higher periodicity of 32-month cycle. This low-frequency feature (32-month cycle) is evidently non-existent in the soil water storage measured at the shallower soil depths nor in the meteorological variables evaluated in this study. This implies that the low-frequency feature of the soil water storage wavelet spectra increases with increasing soil depth across the Agricultural Region; indicating that at deeper soil depths, the largest variances are shifted to lower frequencies. This observed dominant long-memory feature in the deep soil moisture store could have important implications for characterizing the development of temperature extremes as well as for the evaluation of the severity of the recurrent drought outbreaks over regional watersheds in Alberta and potentially for other Canadian Prairie catchments.

Land-Cover Dependent Relationships between Fire and Soil Moisture

For this study, we characterized the dependence of fire counts (FCs) on soil moisture (SM) at global and sub-global scales using 15 years of remote sensing data. We argue that this mathematical relationship serves as an effective way to predict fire because it is a proxy for the semi-quantitative fire–productivity relationship that describes the tradeoff between fuel availability and climate as constraints on fire activity. We partitioned the globe into land-use and land-cover (LULC) categories of forest, grass, cropland, and pasture to investigate how the fire–soil moisture (fire–SM) behavior varies as a function of LULC. We also partitioned the globe into four broadly defined biomes (Boreal, Grassland-Savanna, Temperate, and Tropical) to study the dependence of fire–SM behavior on LULC across those biomes. The forest and grass LULC fire–SM curves are qualitatively similar to the fire–productivity relationship with a peak in fire activity at intermediate SM, a steep decline in fire activity at low SM (productivity constraint), and gradual decline as SM increases (climate constraint), but our analysis highlights how forests and grasses differ across biomes as well. Pasture and cropland LULC are a distinctly human use of the landscape, and fires detected on those LULC types include intentional fires. Cropland fire–SM curves are similar to those for grass LULC, but pasture fires are evident at higher SM values than other LULC. This suggests a departure from the expected climate constraint when burning is happening at non-optimal flammability conditions. Using over a decade of remote sensing data, our results show that quantifying fires relative to a single physical climate variable (soil moisture) is possible on both cultivated and uncultivated landscapes. Linking fire to observable soil moisture conditions for different land-cover types has important applications in fire management and fire modeling.

Seed-bank dynamics of native and invasive Impatiens species during a five-year field experiment under various environmental conditions

Despite recent evidence on the important role of seed banks associated with plant invasions, and a large body of literature on invasive annual Impatiens species, little is known about the seed bank characteristics of Impatiens species. To bridge this gap, we conducted a five-year field experiment where we buried seeds of two invasive species (I. glandulifera and I. parviflora) and one native species (I. noli-tangere) across four localities in the Czech Republic, harbouring all three Impatiens species and differing in the environmental conditions. We found that the three Impatiens species differed in the characteristics of their seed banks. Both invasive species had a high seed germination rate of almost 100% in the first year after seed burial, while &amp;lt;50% of seeds of the native I. noli-tangere germinated during this year. In I. parviflora all seeds germinated in the first year after seed burial and later decomposed, i.e. the species had a transient seed bank. For I. glandulifera, the most invasive species, the survival of seeds differed among localities. At the first and second localities, the seeds decomposed in the first year after seed burial; in the third locality the seeds germinated in the second year; and in the fourth one, the seeds still germinated in the fourth year. The native I. noli-tangere formed a short-term persistent seed bank across all localities. Germinating or dormant seeds were found in the third year after burial in all localities, and in one locality the seeds persisted until the fifth year. The germination and dormancy in I. noli-tangere were constrained by low minimum temperatures during winter. In addition, germination was highest at intermediate soil moisture, and the most dormant seeds were recorded in soils with intermediate nitrogen concentration. The germination of I. glandulifera was slightly limited by low soil nitrogen. However, no such effect was found in I. parviflora. We suggest that in the invasive Impatiens species seed resistance to environmental factors and high germination at least partly explain their wide distribution.

Understanding the Resilience of Soil Moisture Regimes

AbstractResilience of soil moisture regimes (SMRs) describes the stability of a particular SMR and its ability to withstand disturbances. This study analyzes the resilience of SMRs with quantifiable ecological (ECO‐) and engineering (ENG‐) metrics for a stochastic dynamic soil moisture system. The SMR is defined by the stationary state, described by a stationary probability distribution function (pdf), of the soil moisture dynamical system, and further classified into arid, semiarid, semiwet, and wet classes. Applying the stationary pdf of soil moisture dynamics derived by Rodriguez‐Iturbe et al. (1999, https://doi.org/10.1098/rspa.1999.0477) and Laio, Porporato, Ridolfi, et al. (2001, https://doi.org/10.1016/S0309‐1708(01)00005‐7), the ENG‐ and ECO‐ resilience metrics of the various SMRs are quantified. We show that the recovery rate of soil moisture is a convex function of the expected soil moisture at the stationary state―the recovery rate reaches a minimum value at some intermediate soil moisture status. We also show that the maximum acceptable changes in the infiltration condition indicate the capacity of a system to avoid possible regime shifts. SMR shifts are characterized by phenomena of stagnation and hysteresis, which suggest two distinct thresholds for SMR shifts and their reversions. In particular, the semiwet SMR that is favorable to agriculture requires stricter infiltration conditions than other SMRs. This resilience analysis provides better understanding of how natural hydrological conditions control soil moisture, which helps provide guidance on maintaining SMRs suitable for agricultural activities and desertification prevention.

Data-driven stochastic model for basin and sub-grid variability of SMAP satellite soil moisture

This study focused on the utility of coarse surface soil moisture observations for applications that require high resolution surface soil moisture information. This was accomplished by quantifying the information content of average soil moisture for three different spatial scales of 81 km2, 790 km2, and 4400 km2. In situ point observations of soil moisture from 31 stations in Iowa were used to develop a spatial stochastic model that assumes hillslope-scale model parameters are independent. Soil moisture dry-downs and wetting regimes were analyzed using rain gauge and soil moisture sensor data. The statistical nature of dry-downs were parameterized using a power-law decay, and soil moisture increases due to rainfall were parameterized using a non-dimensional logistic curve that is a function of soil moisture deficit. The resulting stochastic model is used to quantify the magnitude of the standard deviation, σ(θ), and skewness G(θ) as a function of the areal average. We show that the greatest information content (small spatial standard deviation) of average observation corresponded to values near the minimum or the maximum soil moisture with σ(θ)<5%, while average observations for intermediate soil moisture values had the lowest information content with σ(θ)>20%. The differences in information content as a function of the areal average were consistent with the statistical nature of soil moisture that can be interpreted as small range bounded variable. However, this study provides quantitative estimates for the magnitude of the sub-grid and basin scale variability, documenting the utility for applications that require high resolution information. These results form the basis for the investigation of spatial runoff production in response to rainfall and to inform plot scale agriculture applications.

Cosmic ray neutrons provide an innovative technique for estimating intermediate scale soil moisture

Soil moisture is an important hydrological parameter, which is essential for a variety of applications, thereby extending to numerous disciplines. Currently, there are three methods of estimating soil moisture: ground-based (in-situ) measurements; remote sensing based methods and land surface models. In recent years, the cosmic ray probe (CRP), which is an in-situ technique, has been implemented in several countries across the globe. The CRP provides area-averaged soil moisture at an intermediate scale and thus bridges the gap between in-situ point measurements and global satellite-based soil moisture estimates. The aim of this study was to test the suitability of the CRP to provide spatial estimates of soil moisture. The CRP was set up and calibrated in Cathedral Peak Catchment VI. An in-situ soil moisture network consisting of time-domain reflectometry and Echo probes was created in Catchment VI, and was used to validate the CRP soil moisture estimates. Once calibrated, the CRP was found to provide spatial estimates of soil moisture, which correlated well with the in-situ soil moisture network data set and yielded an R2 value of 0.845. The use of the CRP for soil moisture monitoring provided reliable, accurate and continuous soil moisture estimates over the catchment area. The wealth of current and potential applications makes the CRP very appealing for scientists and engineers in various fields.Significance:&#x0D; &#x0D; The cosmic ray probe provides spatial estimates of surface soil moisture at an intermediate scale of 18 hectares.&#x0D; A single cosmic ray probe can replace a network of conventional in-situ instruments to provide reliable soil moisture estimates.&#x0D; The cosmic ray probe is capable of estimating soil moisture in previously problematic areas (saline soil, wetlands, rocky soil).&#x0D; Cosmic ray probes can provide data for hydro-meteorologists interested in land–atmosphere interactions.&#x0D; The cosmic ray probe estimates can be promising for remote sensing scientists for product calibration and validation.&#x0D;

An initial assessment of a SMAP soil moisture disaggregation scheme using TIR surface evaporation data over the continental United States

The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36–40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of −0.022 and −0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.

Using Microwave Soil Heating to Inhibit Invasive Species Seed Germination

Successful invasive plant eradication is rare, because the methods used target the adult stage, not taking into account the development capacity of a large seedbank. Heating by microwave was considered, because it offers a means to quickly reach the temperature required for loss of seed viability and inhibition of germination. Previous results were not encouraging, because homogeneous and deep-wave penetration was not achieved, and the various parameters that can affect treatment effectiveness were incompletely addressed. This study aimed to determine, under experimental conditions, the best microwave treatment to inhibit invasive species seed germination in terms of power (2, 4, 6 kW) and duration (2, 4, 8 min) of treatments and depending on soil moisture (10%, 13%, 20%, 30%) and seed burial depth (2, 12 cm). Three invasive species were tested: Bohemian knotweed, giant goldenrod, and jimsonweed. The most effective treatments required relatively high power and duration (2kW8min, 4kW4min, 6kW2min, and 6kW4min; 4kW8min and 6kW8min were not tested for technical reasons), and their effectiveness diminished with increasing soil moisture with germination percentage between 0% and 2% for the lowest soil moisture, 0% and 56% for intermediate soil moisture, and 27% and 68% in control treatments. For the highest soil moisture, only 2kW8min and 4kW4min reduced germination percentage between 2% and 19%. Occasionally, germination of seeds located at the 12-cm depth was more strongly affected. Giant goldenrod seeds were the most sensitive, probably due to their small size. Results are promising and justify further experiments before developing a field microwave device to treat large volumes of soil infested by invasive seed efficiently and with reasonable energy requirements. Other types of soil, in terms of texture and organic matter content, should be tested in future experiments, because these factors influence soil water content and, consequently, microwave heating.

Climatic effects on population declines of a rare wetland species and the role of spatial and temporal isolation as barriers to hybridization

Summary Climate change and climatic extremes may affect species directly or indirectly. While direct climatic effects have been intensively studied, indirect effects, such as increasing hybridization risk, are poorly understood. The goal of our study was to analyse the impact of climate on population dynamics of a rare habitat specialist, Chorthippus montanus, as well as the fine‐scale spatial overlap with a sympatric habitat generalist, Chorthippus parallelus and the dispersion of hybrids. We were particularly interested in the role of spatiotemporal overlap on heterospecific encounter frequencies. We conducted high‐precision mark‐recapture studies on two sites over 7 years and genotyped 702 individuals of two C. montanus generations to detect hybrids. We tested the performance of three programs (structure, newhybrids and adegenet) and accepted only hybrids detected by the two best performing programs. We then tested for correlations between yearly population trends and climatic variables. Furthermore, we analysed the spatial dispersion of both taxa and the hybrids to calculate variation in spatial and temporal overlap and infer heterospecific encounter probabilities. Our results revealed that droughts during the egg phase and rainy weather during nymphal development were strongly correlated with population declines in the habitat specialist. The highest hybridization rate (19·6%) was found in the population with lowest population size. The combined effects of spatial and temporal niche overlap decreased heterospecific encounter probabilities to 4·2–7·6% compared to 20–28% and 11–19% calculated alone from phenology or spatial overlap respectively. Hybrids were detected in areas of higher heterospecific encounter probability, mainly at the edge of the specialists’ occupied habitat in areas with intermediate soil moisture conditions compared to the parental species. This illustrates that the combination of spatial and temporal segregation provides an effective barrier to hybridization. However, the high hybridization rate in one of the populations suggests that this function may decrease with decreasing population size. This supports the hypothesis that climatic extremes threaten rare species directly by reducing reproductive success and may indirectly increase hybridization risk. A lay summary is available for this article.

Examining spectral reflectance features related to Arctic percent vegetation cover: Implications for hyperspectral remote sensing of Arctic tundra

In this study, we investigated the utility of hyperspectral remote sensing data for estimating green percent vegetation cover (PVC) for a study site in the Canadian High Arctic. A field experiment was conducted on Sabine Peninsula (76°27′ N, 108°33′ W), Melville Island, Nunavut, Canada to collect field spectra and PVC for five vegetation types, i.e., polar semi-desert (PD), dry mesic tundra (DMT), mesic tundra (MT), wet mesic tundra (WMT) and wet sedge/moss (WSM). Based on field spectra, two types of 2-band hyperspectral (i.e., Hyperion) and multispectral (i.e., WorldView-3) vegetation indices (VIs) were derived using all possible band combinations. Optimal spectral bands were identified based on their correlations with green PVC. In addition, VIs designed for other landscapes were examined for their ability to estimate green PVC in an Arctic environment. The results indicate that PVC and spectral features for Arctic vegetation types were related to moisture content: (1) vegetation types with dry to intermediate soil moisture (e.g., PD, DMT and MT) possessed large amounts of bare soil and exhibited spectral properties similar to bare soil; and (2) vegetation types with high moisture content (e.g., WMT and WSM) exhibited spectra similar to senescent vegetation given the substantial proportion of senescent vegetation in these vegetation types. The optimal Hyperion spectral bands for estimating green PVC were located at the absorption features observed in Arctic vegetation spectra, including 681.20nm (leaf pigment absorption); 721.90nm and 732.07nm (along the red-edge slope); 1174.77nm and 1184.87nm (leaf water absorption); and 1447.14nm, 1457.23nm, 2072.65nm and 2102.94nm (leaf cellulose and lignin absorption). Narrowband VIs exhibited a stronger correlation with green PVC than broadband VIs due to the finer spectral features sampled by hyperspectral data. Further, VIs designed to estimate leaf pigment and dry matter content (e.g., lignin and cellulose) showed strong correlations with green PVC.

Soil CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; efflux from two mountain forests in the eastern Himalayas, Bhutan: components and controls

Abstract. The biogeochemistry of mountain forests in the Hindu Kush Himalaya range is poorly studied, although climate change is expected to disproportionally affect the region. We measured the soil CO2 efflux (Rs) at a high-elevation (3260 m) mixed forest and a lower-elevation (2460 m) broadleaf forest in Bhutan, eastern Himalayas, during 2015. Trenching was applied to estimate the contribution of autotrophic (Ra) and heterotrophic (Rh) soil respiration. The temperature (Q10) and the moisture sensitivities of Rh were determined under controlled laboratory conditions and were used to model Rh in the field. The higher-elevation mixed forest had a higher standing tree stock, reflected in higher soil C stocks and basal soil respiration. Annual Rs was similar between the two forest sites (14.5 ± 1.2 t C ha−1 for broadleaf; 12.8 ± 1.0 t C ha−1 for mixed). Modelled annual contribution of Rh was ∼ 65 % of Rs at both sites with a higher heterotrophic contribution during winter and lower contribution during the monsoon season. Rh, estimated from trenching, was in the range of modelled Rh but showed higher temporal variability. The measured temperature sensitivity of Rh was similar at the mixed and broadleaf forest sites (Q10 2.2–2.3) under intermediate soil moisture but decreased (Q10 1.5 at both sites) in dry soil. Rs closely followed the annual course of field soil temperature at both sites. Covariation between soil temperature and moisture (cold dry winters and warm wet summers) was likely the main cause for this close relationship. Under the prevailing weather conditions, a simple temperature-driven model was able to explain more than 90 % of the temporal variation in Rs. A longer time series and/or experimental climate manipulations are required to understand the effects of eventually occurring climate extremes such as monsoon failures.