scholarly journals Localized basal area affects soil respiration temperature sensitivity in a coastal deciduous forest

2020 ◽  
Vol 17 (3) ◽  
pp. 771-780 ◽  
Author(s):  
Stephanie C. Pennington ◽  
Nate G. McDowell ◽  
J. Patrick Megonigal ◽  
James C. Stegen ◽  
Ben Bond-Lamberty
Keyword(s):  
Soil Moisture ◽  
Soil Respiration ◽  
Spatial Variability ◽  
Temperature Sensitivity ◽  
Large Scale ◽  
Deciduous Forest ◽  
Basal Area ◽  
Soil Surface ◽  
Study Sites ◽  
Positive Effect

Abstract. Soil respiration (Rs), the flow of CO2 from the soil surface to the atmosphere, is one of the largest carbon fluxes in the terrestrial biosphere. The spatial variability of Rs is both large and poorly understood, limiting our ability to robustly scale it in space. One factor in Rs spatial variability is the autotrophic contribution from plant roots, but it is uncertain how the presence of plants affects the magnitude and temperature sensitivity of Rs. This study used 1 year of Rs measurements to examine the effect of localized basal area on Rs in the growing and dormant seasons, as well as during moisture-limited times, in a temperate, coastal, deciduous forest in eastern Maryland, USA. In a linear mixed-effects model, tree basal area within a 5 m radius (BA5) exerted a significant positive effect on the temperature sensitivity of soil respiration. Soil moisture was the dominant control on Rs during the dry portions of the year, while soil moisture, temperature, and BA5 all exerted significant effects on Rs in wetter periods. Our results suggest that autotrophic respiration is more sensitive to temperature than heterotrophic respiration at these sites, although we did not measure these source fluxes directly, and that soil respiration is highly moisture sensitive, even in a record-rainfall year. The Rs flux magnitudes (0.46–15.0 µmol m−2 s−1) and variability (coefficient of variability 10 %–23 % across plots) observed in this study were comparable to values observed in similar forests. Six Rs observations would be required in order to estimate the mean across all study sites to within 50 %, and 518 would be required in order to estimate it to within 5 %, with 95 % confidence. A better understanding of the spatial interactions between plants and microbes, as well as the strength and speed of above- and belowground coupling, is necessary to link these processes with large-scale soil-to-atmosphere C fluxes.

scholarly journals Tree proximity affects soil respiration dynamics in a coastal temperate deciduous forest

2019 ◽  
Author(s):  
Stephanie C. Pennington ◽  
Nate G. McDowell ◽  
J. Patrick Megonigal ◽  
James C. Stegen ◽  
Ben Bond-Lamberty
Keyword(s):  
Soil Moisture ◽  
Soil Respiration ◽  
Spatial Variability ◽  
Temperature Sensitivity ◽  
Large Scale ◽  
Deciduous Forest ◽  
Basal Area ◽  
Soil Surface ◽  
Temperate Deciduous Forest ◽  
Temperate Deciduous

Abstract. Soil respiration (Rs), the flow of CO2 from the soil surface to the atmosphere, is one of the largest carbon fluxes in the terrestrial biosphere. The spatial variability of Rs is both large and poorly understood, limiting our ability to robustly scale it in time and space. One factor in Rs spatial variability is the autotrophic contribution from plant roots, but it is uncertain how the proximity of plants affects the magnitude and temperature sensitivity of Rs. This study examined the effect of tree proximity on Rs in the growing and dormant seasons, as well as during moisture-limited times, in a temperate, coastal, deciduous forest in eastern Maryland, USA. In a linear mixed-effects model, tree basal area within 5 m (BA5) exerted a significant positive effect on the temperature sensitivity of soil respiration. Soil moisture was the dominant control on Rs during the dry portions of the year while soil moisture, temperature, and BA5 all exerted significant effects on Rs in wetter periods. Our results suggest that autotrophic respiration is more sensitive to temperature than heterotrophic respiration at these sites, although we did not measure these source fluxes directly, and that soil respiration is highly moisture-sensitive, even in a record-rainfall year. The Rs flux magnitudes (0.3–16.6 µmol m−2 s−1) and variability (coefficient of variability 10 %–22 % across plots) observed in this study were comparable to values observed over decades in similar forests. We estimate that four Rs observations were required to be within 50 % of the stand-level mean, and 311 to be within 5 %, at 90 % confidence. A better understanding of the spatial interactions between plants and microbes that results in measured Rs is necessary to link these processes with large scale soil-to-atmosphere C fluxes.

scholarly journals Historical climate controls soil respiration responses to current soil moisture

2017 ◽  
Vol 114 (24) ◽  
pp. 6322-6327 ◽  
Author(s):  
Christine V. Hawkes ◽  
Bonnie G. Waring ◽  
Jennifer D. Rocca ◽  
Stephanie N. Kivlin
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Soil Respiration ◽  
Carbon Cycling ◽  
Large Scale ◽  
Microbial Respiration ◽  
Rainfall Gradient ◽  
Soil Microbial ◽  
Historical Climate ◽  
Moisture Dependence

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40–70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration–moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.

scholarly journals Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

2018 ◽  
Vol 10 (8) ◽  
pp. 1245 ◽  
Author(s):  
Mehrez Zribi ◽  
Erwan Motte ◽  
Nicolas Baghdadi ◽  
Frédéric Baup ◽  
Sylvia Dayau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Satellite System ◽  
Area Index ◽  
Vegetation Height ◽  
Study Sites ◽  
Global Navigation Satellite ◽  
Vegetation Characteristic ◽  
Agricultural Areas

The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

scholarly journals Spatial variability and its scale dependency of observed and modeled soil moisture over different climate regions

2013 ◽  
Vol 17 (3) ◽  
pp. 1177-1188 ◽  
Author(s):  
B. Li ◽  
M. Rodell
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Land Surface ◽  
Large Scale ◽  
Warm Season ◽  
Scale Dependency ◽  
Convex Shape ◽  
Spatial Moments ◽  
Environmental Controls

Abstract. Past studies on soil moisture spatial variability have been mainly conducted at catchment scales where soil moisture is often sampled over a short time period; as a result, the observed soil moisture often exhibited smaller dynamic ranges, which prevented the complete revelation of soil moisture spatial variability as a function of mean soil moisture. In this study, spatial statistics (mean, spatial variability and skewness) of in situ soil moisture, modeled and satellite-retrieved soil moisture obtained in a warm season (198 days) were examined over three large climate regions in the US. The study found that spatial moments of in situ measurements strongly depend on climates, with distinct mean, spatial variability and skewness observed in each climate zone. In addition, an upward convex shape, which was revealed in several smaller scale studies, was observed for the relationship between spatial variability of in situ soil moisture and its spatial mean when statistics from dry, intermediate, and wet climates were combined. This upward convex shape was vaguely or partially observable in modeled and satellite-retrieved soil moisture estimates due to their smaller dynamic ranges. Despite different environmental controls on large-scale soil moisture spatial variability, the correlation between spatial variability and mean soil moisture remained similar to that observed at small scales, which is attributed to the boundedness of soil moisture. From the smaller support (effective area or volume represented by a measurement or estimate) to larger ones, soil moisture spatial variability decreased in each climate region. The scale dependency of spatial variability all followed the power law, but data with large supports showed stronger scale dependency than those with smaller supports. The scale dependency of soil moisture variability also varied with climates, which may be linked to the scale dependency of precipitation spatial variability. Influences of environmental controls on soil moisture spatial variability at large scales are discussed. The results of this study should be useful for diagnosing large scale soil moisture estimates and for improving the estimation of land surface processes.

scholarly journals Sampling density and date influence spatial representation of tree ring reconstructions

2020 ◽  
Author(s):  
Justin T. Maxwell ◽  
Grant L. Harley ◽  
Trevis J. Matheus ◽  
Brandon M. Strange ◽  
Kayla Van Aken ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Tree Ring ◽  
Tree Rings ◽  
Large Scale ◽  
The United States ◽  
Severe Drought ◽  
Ring Network ◽  
Tree Ring Data ◽  
The Us

Abstract. Our understanding of the natural variability of hydroclimate before the instrumental period (ca. 1900 in the United States; US) is largely dependent on tree-ring-based reconstructions. Large-scale soil moisture reconstructions from a network of tree-ring chronologies have greatly improved our understanding of the spatial and temporal variability in hydroclimate conditions, particularly extremes of both drought and pluvial (wet) events. However, certain regions within these large-scale reconstructions in the US have a sparse network of tree-ring chronologies. Further, several chronologies were collected in the 1980s and 1990s, thus our understanding of the sensitivity of radial growth to soil moisture in the US is based on a period that experienced multiple extremely severe droughts and neglects the impacts of recent, rapid global change. In this study, we expanded the tree-ring network of the Ohio River Valley in the US, a region with sparse coverage. We used a total of 72 chronologies across 15 species to examine how increasing the density of the tree-ring network influences the representation of reconstructing the Palmer Meteorological Drought Index (PMDI). Further, we tested how the sampling date influenced the reconstruction models by creating reconstructions that ended in the year 1980 and compared them to reconstructions ending in 2010 from the same chronologies. We found that increasing the density of the tree-ring network resulted in reconstructed values that better matched the spatial variability of instrumentally recorded droughts and to a lesser extent, pluvials. By sampling tree in 2010 compared to 1980, the sensitivity of tree rings to PMDI decreased in the southern portion of our region where severe drought conditions have been absent over recent decades. We emphasize the need of building a high-density tree-ring network to better represent the spatial variability of past droughts and pluvials. Further, chronologies on the International Tree-Ring Data Bank need updating regularly to better understand how the sensitivity of tree rings to climate may vary through time.

scholarly journals Significance of soil respiration from biological activity in the degradation processes of different types of organic matter

2020 ◽  
Vol 1 (2) ◽  
pp. 171-179
Keyword(s):  
Climate Change ◽  
Organic Matter ◽  
Soil Moisture ◽  
Soil Respiration ◽  
Soil Temperature ◽  
Temperature Sensitivity ◽  
Soil Co2 Efflux ◽  
Co2 Efflux ◽  
Soil Co2 ◽  
Total Soil

Soil respiration is a major component of global carbon cycle. Therefore, it is crucial to understand the environmental controls on soil respiration for evaluating potential response of ecosystems to climate change. In a temperate deciduous forest (located in Northern-Hungary) we added or removed aboveground and belowground litter to determine total soil respiration. We investigated the relationship between total soil CO2 efflux, soil moisture, and soil temperature. Soil CO2 efflux was measured at each plot using soda-lime method. Temperature sensitivity of soil respiration (Q10) was monitored via measuring soil temperature on an hourly basis, while soil moisture was determined monthly. Soil respiration increased in control plots from the second year after implementing the treatment, but results showed fluctuations from one year to another. The effect of doubled litter was less significant than the effect of removal. Removed litter and root inputs caused substantial decrease in soil respiration. We found that temperature was more influential in the control of soil respiration than soil moisture. In plots with no litter Q10 varied in the largest interval. For treatment with doubled litter layer, temperature sensitivity of CO2 efflux did not change considerably. The effect of increasing soil temperature is more conspicuous to soil respiration in litter removal treatments since lack of litter causes greater irradiation. When exclusively leaf litter was considered, the effect of temperature on soil respiration was lower in treatments with added litter than with removed litter. Our results reveal that soil life is impacted by the absence of organic matter, rather than by an excess of organic matter. Results of CO2 emission from soils with different organic matter content can contribute to sustainable land use, considering the changed climatic factors caused by global climate change.

scholarly journals Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

2003 ◽  
Vol 17 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Markus Reichstein ◽  
Ana Rey ◽  
Annette Freibauer ◽  
John Tenhunen ◽  
Riccardo Valentini ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Spatial Variability ◽  
Soil Water ◽  
Water Availability ◽  
Large Scale ◽  
Soil Water Availability ◽  
Vegetation Productivity ◽  
Productivity Indices

scholarly journals Surface resistance calibration for a hydrological model using evapotranspiration retrieved from remote sensing data in Nahe catchment forest area

2015 ◽  
Vol 368 ◽  
pp. 81-86
Author(s):  
W. Bie ◽  
M. C. Casper ◽  
P. Reiter ◽  
M. Vohland
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Resistance ◽  
Hydrological Model ◽  
Deciduous Forest ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Distributed Hydrological Model ◽  
Forest Regions ◽  
Daily Evapotranspiration

Abstract. In this paper, a method combining graphical and statistical techniques is proposed for surface resistance calibration in a distributed hydrological model, WaSiM-ETH, by comparing daily evapotranspiration simulated by model WaSiM-ETH with corresponding daily evapotranspiration retrieved from remote sensing images. The study area locates in Nahe catchment (Rhineland-Palatinate, Germany, 4065 km2) forest regions. The remote sensing based observations are available for a very limited number of days but representative for most soil moisture conditions. By setting canopy resistance (rc) at 150 s/m, soil surface resistance (rse) at 250 s/m or at 300 s/m for deciduous forest and setting rc at 300 s/m, rse at 600 s/m or at 650 s/m for pine forest, the model exhibits its best overall performance in space and time. It is also found that with sufficient soil moisture, the model exhibits its best performance in space scale.

scholarly journals Land surface spinup for episodic modeling

2014 ◽  
Vol 14 (15) ◽  
pp. 8165-8172 ◽  
Author(s):  
W. M. Angevine ◽  
E. Bazile ◽  
D. Legain ◽  
D. Pino
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Spatial Variability ◽  
Land Surface ◽  
Large Scale ◽  
Layer Structure ◽  
Numerical Models ◽  
Surface Fluxes ◽  
Boundary Layer Structure ◽  
Soil Variables

Abstract. Soil moisture strongly controls the surface fluxes in mesoscale numerical models, and thereby influences the boundary layer structure. Proper initialization of soil moisture is therefore critical for faithful simulations. In many applications, such as air quality or process studies, the model is run for short, discrete periods (a day to a month). This paper describes one method for soil initialization in these cases – self-spinup. In self-spinup, the model is initialized with a coarse-resolution operational model or reanalysis output, and run for a month, cycling its own soil variables. This allows the soil variables to develop appropriate spatial variability, and may improve the actual values. The month (or other period) can be run more than once if needed. The case shown is for the Boundary Layer Late Afternoon and Sunset Turbulence experiment, conducted in France in 2011. Self-spinup adds spatial variability, which improves the representation of soil moisture patterns around the experiment location, which is quite near the Pyrenees Mountains. The self-spinup also corrects a wet bias in the large-scale analysis. The overall result is a much-improved simulation of boundary layer structure, evaluated by comparison with soundings from the field site. Self-spinup is not recommended as a substitute for multi-year spinup with an offline land data assimilation system in circumstances where the data sets required for such spinup are available at the required resolution. Self-spinup may fail if the modeled precipitation is poorly simulated. It is an expedient for cases when resources are not available to allow a better method to be used.

scholarly journals Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 667
Author(s):  
J. David Urquiza Muñoz ◽  
Daniel Magnabosco Marra ◽  
Robinson I. Negrón-Juarez ◽  
Rodil Tello-Espinoza ◽  
Waldemar Alegría-Muñoz ◽  
...  
Keyword(s):  
Forest Structure ◽  
Large Scale ◽  
Tree Mortality ◽  
Basal Area ◽  
Forest Recovery ◽  
Old Growth ◽  
Study Region ◽  
Central Amazon ◽  
Old Growth Forest ◽  
Study Sites

The dynamics of forest recovery after windthrows (i.e., broken or uprooted trees by wind) are poorly understood in tropical forests. The Northwestern Amazon (NWA) is characterized by a higher occurrence of windthrows, greater rainfall, and higher annual tree mortality rates (~2%) than the Central Amazon (CA). We combined forest inventory data from three sites in the Iquitos region of Peru, with recovery periods spanning 2, 12, and 22 years following windthrow events. Study sites and sampling areas were selected by assessing the windthrow severity using remote sensing. At each site, we recorded all trees with a diameter at breast height (DBH) ≥ 10 cm along transects, capturing the range of windthrow severity from old-growth to highly disturbed (mortality > 60%) forest. Across all damage classes, tree density and basal area recovered to >90% of the old-growth values after 20 years. Aboveground biomass (AGB) in old-growth forest was 380 (±156) Mg ha−1. In extremely disturbed areas, AGB was still reduced to 163 (±68) Mg ha−1 after 2 years and 323 (± 139) Mg ha−1 after 12 years. This recovery rate is ~50% faster than that reported for Central Amazon forests. The faster recovery of forest structure in our study region may be a function of its higher productivity and adaptability to more frequent and severe windthrows. These varying rates of recovery highlight the importance of extreme wind and rainfall on shaping gradients of forest structure in the Amazon, and the different vulnerabilities of these forests to natural disturbances whose severity and frequency are being altered by climate change.

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