The impact of the canopy structure on the spatial variability in forest floor carbon stocks

Geoderma ◽  
2010 ◽  
Vol 158 (3-4) ◽  
pp. 282-297 ◽  
Author(s):  
Carolin Penne ◽  
Bernd Ahrends ◽  
Markus Deurer ◽  
Jürgen Böttcher
Keyword(s):  
Spatial Variability ◽  
Forest Floor ◽  
Canopy Structure ◽  
Carbon Stocks ◽  
The Impact

scholarly journals Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]

2019 ◽  
Author(s):  
Elias C. Massoud ◽  
Chonggang Xu ◽  
Rosie Fisher ◽  
Ryan Knox ◽  
Anthony Walker ◽  
...  
Keyword(s):  
Land Surface ◽  
Canopy Structure ◽  
Land Surface Model ◽  
Carbon Stocks ◽  
Surface Model ◽  
Model Parameters ◽  
Growth Strategies ◽  
Community Land Model ◽  
Vegetation Models ◽  
The Impact

Abstract. Vegetation plays a key role in regulating global carbon cycles and is a key component of the Earth System Models (ESMs) aimed to project Earth's future climates. In the last decade, the vegetation component within ESMs has witnessed great progresses from simple 'big-leaf' approaches to demographically-structured approaches, which has a better representation of plant size, canopy structure, and disturbances. The demographically-structured vegetation models are typically controlled by a large number of parameters, and sensitivity analysis is generally needed to quantify the impact of each parameter on the model outputs for a better understanding of model behaviors. In this study, we use the Fourier Amplitude Sensitivity Test (FAST) to diagnose the Community Land Model coupled to the Ecosystem Demography Model, or CLM4.5(ED). We investigate the first and second order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks. While the photosynthetic capacity parameter Vc,max25 is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which are shown here to determine vegetation demography and carbon stocks through their impacts on survival and growth strategies. The results of this study highlights the importance of understanding the dynamics of the next generation of demographically-enabled vegetation models within ESMs toward improved model parameterization and model structure for better model fidelity.

scholarly journals Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

2019 ◽  
Vol 13 (11) ◽  
pp. 3045-3059 ◽  
Author(s):  
Nick Rutter ◽  
Melody J. Sandells ◽  
Chris Derksen ◽  
Joshua King ◽  
Peter Toose ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Layer Thickness ◽  
Snow Water Equivalent ◽  
Estimation Accuracy ◽  
Snow Layer ◽  
Data Set ◽  
Snow Water ◽  
Retrieval Errors ◽  
Snow Microstructure ◽  
The Impact

Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across nine trenches) collected over two winters at Trail Valley Creek, NWT, Canada, was applied in synthetic radiative transfer experiments. This allowed for robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability in total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths of layer thickness were less than a metre for all layers. Depth hoar was consistently ∼30 % of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and specific surface area (SSA) of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7 % under the median value was needed to accurately retrieve SWE. In shallow snowpacks <0.6 m, depth hoar SSA estimates of ±5 %–10 % around the optimal retrieval SSA allowed SWE retrievals within a tolerance of ±30 mm. Where snowpacks were deeper than ∼30 cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.

European beech is a net annual source of methane (CH4)

2021 ◽  
Author(s):  
Katerina Machacova ◽  
Hannes Warlo ◽  
Kateřina Svobodová ◽  
Thomas Agyei ◽  
Tereza Uchytilová ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Seasonal Dynamics ◽  
Forest Floor ◽  
Greenhouse Gas Emission ◽  
European Beech ◽  
Individual Variability ◽  
Spatiotemporal Variability ◽  
Vegetation Season ◽  
Dormant Season ◽  
The Impact

&lt;p&gt;Trees are known to be sources of methane (CH&lt;sub&gt;4&lt;/sub&gt;), an important greenhouse gas, into the atmosphere. However, still little is known about the seasonality of the tree stem CH&lt;sub&gt;4&lt;/sub&gt; fluxes, particularly for the dormant season, and about the impact of environmental parameters on this gas exchange. This makes the estimation of net annual ecosystem CH&lt;sub&gt;4&lt;/sub&gt; fluxes difficult.&lt;/p&gt;&lt;p&gt;We determined seasonal dynamics of CH&lt;sub&gt;4&lt;/sub&gt; exchange of mature European beech stems (&lt;em&gt;Fagus sylvatica&lt;/em&gt;) and of adjacent forest floor in a temperate montane forest of White Carpathians, Czech Republic, from November 2017 to December 2018. We used static chamber methods and gas chromatographic analyses. We aimed to understand the unknown role in seasonal changes of CH&lt;sub&gt;4&lt;/sub&gt; fluxes of these forests, and the spatiotemporal variability of the tree fluxes.&lt;/p&gt;&lt;p&gt;The beech stems were net annual sources for atmospheric CH&lt;sub&gt;4&lt;/sub&gt;, whereas the forest floor was a predominant sink for CH&lt;sub&gt;4&lt;/sub&gt;. The stem CH&lt;sub&gt;4&lt;/sub&gt; emissions showed high inter-individual variability and clear seasonality following the stem CO&lt;sub&gt;2&lt;/sub&gt; efflux. The fluxes of CH&lt;sub&gt;4&lt;/sub&gt; peaked during the vegetation season, and remained low but significant to the annual totals during winter dormancy. By contrast, the forest floor CH&lt;sub&gt;4&lt;/sub&gt; uptake followed an opposite flux trend with low CH&lt;sub&gt;4&lt;/sub&gt; uptake detected in the winter dormant season and elevated CH&lt;sub&gt;4&lt;/sub&gt; uptake during the vegetation season. Based on our preliminary analyses, the detected high spatial variability in stem CH&lt;sub&gt;4&lt;/sub&gt; emissions can be explained neither by the CH&lt;sub&gt;4&lt;/sub&gt; exchange at the forest floor level, nor by soil CH&lt;sub&gt;4&lt;/sub&gt; concentrations, soil water content and soil temperature, all measured in vertical soil profiles close to the studied trees.&lt;/p&gt;&lt;p&gt;European beech trees, native and widely spread species of Central Europe, seem to markedly contribute to the seasonal dynamics of the ecosystem CH&lt;sub&gt;4&lt;/sub&gt; exchange, and their CH&lt;sub&gt;4&lt;/sub&gt; fluxes should be included into forest greenhouse gas emission inventories.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Acknowledgement&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This research was supported by the Czech Science Foundation (17-18112Y), National Programme for Sustainability I (LO1415), CzeCOS (LM2015061), and SustES - Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). We thank Libor Bor&amp;#225;k and Leszek Dariusz Laptaszy&amp;#324;ski for their technical and field support.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Regionalized Terrestrial Ecotoxicity Assessment of Copper-Based Fungicides Applied in Viticulture

2018 ◽  
Vol 10 (7) ◽  
pp. 2522 ◽  
Author(s):  
Ivan Viveros Santos ◽  
Cécile Bulle ◽  
Annie Levasseur ◽  
Louise Deschênes
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Regression Models ◽  
Management Practices ◽  
Metal Speciation ◽  
Agricultural Systems ◽  
Geographical Variability ◽  
Terrestrial Ecotoxicity ◽  
The Impact ◽  
Growing Region

Life cycle assessment has been recognized as an important decision-making tool to improve the environmental performance of agricultural systems. Still, there are certain modelling issues related to the assessment of their impacts. The first is linked to the assessment of the metal terrestrial ecotoxicity impact, for which metal speciation in soil is disregarded. In fact, emissions of metals in agricultural systems contribute significantly to the ecotoxic impact, as do copper-based fungicides applied in viticulture to combat downy mildew. Another issue is linked to the ways in which the intrinsic geographical variability of agriculture resulting from the variation of management practices, soil properties, and climate is addressed. The aim of this study is to assess the spatial variability of the terrestrial ecotoxicity impact of copper-based fungicides applied in European vineyards, accounting for both geographical variability in terms of agricultural practice and copper speciation in soil. This first entails the development of regionalized characterization factors (CFs) for the copper used in viticulture and then the application of these CFs to a regionalized life-cycle inventory that considers different management practices, soil properties, and climates in different regions, namely Languedoc-Roussillon (France), Minho (Portugal), Tuscany (Italy), and Galicia (Spain). There are two modelling alternatives to determine metal speciation in terrestrial ecotoxicity: (a) empirical regression models; and (b) WHAM 6.0, the geochemical speciation model applied according to the soil properties of the Harmonized World Soil Database (HWSD). Both approaches were used to compute and compare regionalized CFs with each other and with current IMPACT 2002+ CF. The CFs were then aggregated at different spatial resolutions—global, Europe, country, and wine-growing region—to assess the uncertainty related to spatial variability at the different scales and applied in the regionalized case study. The global CF computed for copper terrestrial ecotoxicity is around 3.5 orders of magnitude lower than the one from IMPACT 2002+, demonstrating the impact of including metal speciation. For both methods, an increase in the spatial resolution of the CFs translated into a decrease in the spatial variability of the CFs. With the exception of the aggregated CF for Portugal (Minho) at the country level, all the aggregated CFs derived from empirical regression models are greater than the ones derived from the method based on WHAM 6.0 within a range of 0.2 to 1.2 orders of magnitude. Furthermore, CFs calculated with empirical regression models exhibited a greater spatial variability with respect to the CFs derived from WHAM 6.0. The ranking of the impact scores of the analyzed scenarios was mainly determined by the amount of copper applied in each wine-growing region. However, finer spatial resolutions led to an impact score with lower uncertainty.

scholarly journals Iron-bound organic carbon in forest soils: quantification and characterization

2016 ◽  
Vol 13 (16) ◽  
pp. 4777-4788 ◽  
Author(s):  
Qian Zhao ◽  
Simon R. Poulson ◽  
Daniel Obrist ◽  
Samira Sumaila ◽  
James J. Dynes ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Spatial Variability ◽  
Forest Soils ◽  
The United States ◽  
Biogeochemical Cycles ◽  
Mean Annual Temperature ◽  
Aliphatic Carbon ◽  
A Site ◽  
The Impact ◽  
X Ray Absorption

Abstract. Iron oxide minerals play an important role in stabilizing organic carbon (OC) and regulating the biogeochemical cycles of OC on the earth surface. To predict the fate of OC, it is essential to understand the amount, spatial variability, and characteristics of Fe-bound OC in natural soils. In this study, we investigated the concentrations and characteristics of Fe-bound OC in soils collected from 14 forests in the United States and determined the impact of ecogeographical variables and soil physicochemical properties on the association of OC and Fe minerals. On average, Fe-bound OC contributed 37.8 % of total OC (TOC) in forest soils. Atomic ratios of OC : Fe ranged from 0.56 to 17.7, with values of 1–10 for most samples, and the ratios indicate the importance of both sorptive and incorporative interactions. The fraction of Fe-bound OC in TOC (fFe-OC) was not related to the concentration of reactive Fe, which suggests that the importance of association with Fe in OC accumulation was not governed by the concentration of reactive Fe. Concentrations of Fe-bound OC and fFe-OC increased with latitude and reached peak values at a site with a mean annual temperature of 6.6 °C. Attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR) and near-edge X-ray absorption fine structure (NEXAFS) analyses revealed that Fe-bound OC was less aliphatic than non-Fe-bound OC. Fe-bound OC also was more enriched in 13C compared to the non-Fe-bound OC, but C ∕ N ratios did not differ substantially. In summary, 13C-enriched OC with less aliphatic carbon and more carboxylic carbon was associated with Fe minerals in the soils, with values of fFe-OC being controlled by both sorptive and incorporative associations between Fe and OC. Overall, this study demonstrates that Fe oxides play an important role in regulating the biogeochemical cycles of C in forest soils and uncovers the governing factors for the spatial variability and characteristics of Fe-bound OC.

scholarly journals Mesoscale Spatial Variability of Linear Trend of Precipitation Statistics in Korean Peninsula

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Jaehyeon Lee ◽  
Jaehyun Ahn ◽  
Eunsoo Choi ◽  
Dongkyun Kim
Keyword(s):  
Spatial Variability ◽  
Korean Peninsula ◽  
Temporal Trend ◽  
Linear Trend ◽  
Kendall Test ◽  
Characteristic Scale ◽  
Management Plans ◽  
The Impact ◽  
Mean Variance ◽  
Approximate Characteristic

This study analyzed the spatial variability of the linear trend of the precipitation mean, variance, lag-1 autocorrelation coefficient, and probability of dryness (PD) based on the precipitation data between 1981 and 2015 observed at 65 rain gages located across Korean Peninsula. While the result of the Mann-Kendall test based on the yearly statistics showed no temporal trend at most of the gage locations, the same test based on the 20-yearly statistics showed that statistically significant temporal trend exists at 54% (mean), 60% (variance), 61% (autocorrelation), and 61% (PD) among the total 65 rain gages. In addition, this study produced the map of the linear trend of the precipitation statistics. The map showed a clear regional and seasonal tendency implying that the impact of the climate change varies significantly within Korea. The variogram analysis revealed that the approximate characteristic scale of linear trend of hourly and daily precipitation statistics ranges between 50 km and 200 km and between 100 km and 250 km, respectively. This characteristic scale is significantly smaller than the spatial scale of atmospheric circulation, which suggests that future water resources management plans of Korea should consider this mesoscale variability that otherwise can be missed if it is based only on the GCM simulation results.

scholarly journals Space variability of hydrological responses of Nature-Based Solutions and the resulting uncertainty

2020 ◽  
Author(s):  
Yangzi Qiu ◽  
Igor da Silva Rocha Paz ◽  
Feihu Chen ◽  
Pierre-Antoine Versini ◽  
Daniel Schertzer ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Peak Flow ◽  
Hydrological Cycle ◽  
Green Roof ◽  
Spatial Arrangement ◽  
Intersection Theorem ◽  
Runoff Volume ◽  
Hydrological Responses ◽  
Total Runoff ◽  
The Impact

Abstract. During the last decades, the urban hydrological cycle has been strongly modified by the built environment, resulting in fast runoff and increasing the risk of waterlogging. Nature-Based Solutions (NBS), which apply green infrastructures, have been more and more widely considered as a sustainable approach for urban stormwater management. However, the assessment of NBS performance still requires further modelling development because of their hydrological responses sensitively depends on the representation of multiscale space variability of both the rainfall and the NBS distribution. Indeed, we initially argue this issue with the help of the multifractal intersection theorem. To illustrate the importance of this question, the spatial heterogeneous distributions of two series of NBS scenarios (porous pavement, rain garden, green roof, and combined) are quantified with the help of their fractal dimension. We point out consequences of their estimates. Then, a fully-distributed and physically-based hydrological model (Multi-Hydro) was applied to consider the studied catchment and these NBS scenarios with a spatial resolution of 10 m under two different types of rainfall: distributed and uniform, and for three rainfall events. These simulations show that the impact of spatial variability of rainfall on the uncertainty of peak flow of NBS scenarios ranges from about 8 % to 17 %, which is more pronounced than those of the total runoff volume. In addition, the spatial variability of the rainfall intensity at the largest rainfall peak responds almost linearly to the uncertainty of the peak flow of NBS scenarios. However, the hydrological responses of NBS scenarios are less affected by the spatial distribution of NBS. Finally, the intersection effects of the spatial variability of rainfall and the spatial arrangement of NBS seem more pronounced for the peak flow of green roof scenarios and the total runoff volume of combined scenarios.

scholarly journals Modeling relevant factors and covariates of carbon stock changes in peatlands using a hierarchical linear mixed modeling approach

2020 ◽  
Author(s):  
Kilian Walz ◽  
Kenneth A Byrne ◽  
David Wilson ◽  
Florence Renou-Wilson
Keyword(s):  
Soil Carbon ◽  
Environmental Protection Agency ◽  
Land Surface ◽  
Carbon Stock ◽  
Dimensional Space ◽  
Carbon Stocks ◽  
Carbon Distribution ◽  
Soil Carbon Stock ◽  
Modeling Approach ◽  
The Impact

&lt;p&gt;While peatlands constitute the largest soil carbon stock in Ireland with 75% of soil carbon stored in an area covering an estimated 20% of the land surface, carbon stocks of peatlands are affected by past and present disturbances related to various land uses. Afforestation, grazing and peat extraction for energy and horticultural use often are major drivers of peatland soil degradation. A comparative assessment of the impact of land disturbance on peatland soil carbon stocks on a national scale has been lacking so far. Current research, funded by the Irish Environmental Protection Agency (EPA), addresses this issue with the goal to fill various gaps related to mapping and modeling changes of soil carbon stock in Irish peatlands. Data from the first nationwide peatland survey forms the basis for this study, in which the influence of different factors and covariates on soil carbon distribution in peatlands is examined. After data exploratory analysis, a mixed linear modeling approach is tested for its suitability to explain peatland soil carbon distribution within the Republic of Ireland. Parameters are identified which are responsible for changes across the country. In addition, model performance to map peat soil carbon stock within a three-dimensional space is evaluated.&lt;/p&gt;

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