Review of “The distribution pattern of desert riparian forests and its relationship with soil moisture and soil properties in the low reaches of Heihe River, China”, by Ding and co-authors

2016 ◽  
Author(s):  
Anonymous
Keyword(s):  
Soil Moisture ◽  
Soil Properties ◽  
Distribution Pattern ◽  
Riparian Forests ◽  
Heihe River ◽  
Desert Riparian Forests

scholarly journals The distribution pattern of desert riparian forests and its relationship with soil moisture and soil properties in the low reaches of Heihe River Basin, China

2016 ◽  
Author(s):  
Jingyi Ding ◽  
Wenwu Zhao ◽  
Stefani Daryanto ◽  
Lixin Wang ◽  
Hao Fan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Physical Properties ◽  
Soil Properties ◽  
Soil Physical Properties ◽  
River Channel ◽  
Riparian Forests ◽  
Heihe River ◽  
Community Characteristics ◽  
Soil Nutrition ◽  
Desert Riparian Forests

Abstract. Desert riparian forests are critical habitats that provide a variety of ecosystem services in arid environments. They are also endangered ecosystem types that are sensitive to disturbance and threatened by desertification. Despite of previous studies stressed on the interactions between desert riparian forests and water availability, the lack of comprehensive information on the forests distribution range and their relationship with soil properties constraints further conservation efforts of this community under a changing climate. In this study, vegetation community characteristics, soil moisture and soil properties were investigated within a 3000 m radius around the river channel in the low reaches of Heihe River Basin, northwest China to determine the distribution pattern of desert riparian forests and their relationship with environmental factors. We found that desert riparian forests mainly distributed within the range of 2500 m from the river channel and the first 1000 m was regarded as the optimum range. Five types of vegetation communities were identified based on Two-way Indicator Species Analysis (TWINSPAN) and they gradually shifted from the riparian tree-shrub-herb communities to riparian-desert shrubs with increasing distance from the river channel. Vegetation community coverage and diversity indices formed bimodal patterns while community height and density declined significantly as the distance from the river increased. Soil moisture, soil physical properties, and soil nutrition explained 53.6 % of the variance in community characteristics and different environment variables influenced different community characteristics. Soil moisture, accounting for 62.7 % of the total explanation, mainly influenced the community coverage and density. Soil physical properties (e.g., bulk density, soil particle composition) exerted influence on shrub layer, while soil nutrition mainly affected community richness. With surface (0–30 cm) and deep (100–200 cm) soil moisture, bulk density and total phosphorus regarded as major determining factors in the community structure and diversity, conservation measures that protect the soil structure and prevent soil moisture deficiency (e.g., artificial soil cover and water conveyance channel) were suggested to better protect the desert riparian forests under climate change and intensive human disturbance.

scholarly journals The spatial distribution and temporal variation of desert riparian forests and their influencing factors in the downstream Heihe River basin, China

2017 ◽  
Vol 21 (5) ◽  
pp. 2405-2419 ◽  
Author(s):  
Jingyi Ding ◽  
Wenwu Zhao ◽  
Stefani Daryanto ◽  
Lixin Wang ◽  
Hao Fan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Soil Moisture ◽  
Temporal Variation ◽  
Remote Sensing Data ◽  
River Channel ◽  
Riparian Forests ◽  
Heihe River ◽  
Annual Average ◽  
Desert Riparian Forests

Abstract. Desert riparian forests are the main restored vegetation community in Heihe River basin. They provide critical habitats and a variety of ecosystem services in this arid environment. Since desert riparian forests are also sensitive to disturbance, examining the spatial distribution and temporal variation of these forests and their influencing factors is important to determine the limiting factors of vegetation recovery after long-term restoration. In this study, field experiment and remote sensing data were used to determine the spatial distribution and temporal variation of desert riparian forests and their relationship with the environmental factors. We classified five types of vegetation communities at different distances from the river channel. Community coverage and diversity formed a bimodal pattern, peaking at the distances of 1000 and 3000 m from the river channel. In general, the temporal normalized difference vegetation index (NDVI) trend from 2000 to 2014 was positive at different distances from the river channel, except for the region closest to the river bank (i.e. within 500 m from the river channel), which had been undergoing degradation since 2011. The spatial distribution of desert riparian forests was mainly influenced by the spatial heterogeneity of soil properties (e.g. soil moisture, bulk density and soil particle composition). Meanwhile, while the temporal variation of vegetation was affected by both the spatial heterogeneity of soil properties (e.g. soil moisture and soil particle composition) and to a lesser extent, the temporal variation of water availability (e.g. annual average and variability of groundwater, soil moisture and runoff). Since surface (0–30 cm) and deep (100–200 cm) soil moisture, bulk density and the annual average of soil moisture at 100 cm obtained from the remote sensing data were regarded as major determining factors of community distribution and temporal variation, conservation measures that protect the soil structure and prevent soil moisture depletion (e.g. artificial soil cover and water conveyance channels) were suggested to better protect desert riparian forests under climate change and intensive human disturbance.

scholarly journals Characterizing Soil Physical Properties for Soil Moisture Monitoring with the North Carolina Environment and Climate Observing Network

2012 ◽  
Vol 29 (7) ◽  
pp. 933-943 ◽  
Author(s):  
Weinan Pan ◽  
R. P. Boyles ◽  
J. G. White ◽  
J. L. Heitman
Keyword(s):  
North Carolina ◽  
Soil Moisture ◽  
Physical Properties ◽  
Soil Properties ◽  
Water Content ◽  
Bulk Density ◽  
Soil Physical Properties ◽  
The North ◽  
Wide Range ◽  
Soil Moisture Monitoring

Abstract Soil moisture has important implications for meteorology, climatology, hydrology, and agriculture. This has led to growing interest in development of in situ soil moisture monitoring networks. Measurement interpretation is severely limited without soil property data. In North Carolina, soil moisture has been monitored since 1999 as a routine parameter in the statewide Environment and Climate Observing Network (ECONet), but with little soils information available for ECONet sites. The objective of this paper is to provide soils data for ECONet development. The authors studied soil physical properties at 27 ECONet sites and generated a database with 13 soil physical parameters, including sand, silt, and clay contents; bulk density; total porosity; saturated hydraulic conductivity; air-dried water content; and water retention at six pressures. Soil properties were highly variable among individual ECONet sites [coefficients of variation (CVs) ranging from 12% to 80%]. This wide range of properties suggests very different behavior among sites with respect to soil moisture. A principal component analysis indicated parameter groupings associated primarily with soil texture, bulk density, and air-dried water content accounted for 80% of the total variance in the dataset. These results suggested that a few specific soil properties could be measured to provide an understanding of differences in sites with respect to major soil properties. The authors also illustrate how the measured soil properties have been used to develop new soil moisture products and data screening for the North Carolina ECONet. The methods, analysis, and results presented here have applications to North Carolina and for other regions with heterogeneous soils where soil moisture monitoring is valuable.

scholarly journals A Comparison of the Attributes of Pine Straw from Southern Pine Species

2021 ◽  
Vol 39 (3) ◽  
pp. 115-122
Author(s):  
Zachary Singh ◽  
Adam Maggard ◽  
Rebecca Barlow ◽  
John Kush
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Soil Properties ◽  
Soil Nutrients ◽  
Longleaf Pine ◽  
Pinus Palustris ◽  
Pinus Elliottii ◽  
Slash Pine ◽  
Weed Growth ◽  
Pine Straw

Abstract Longleaf pine (Pinus palustris Mill.), and slash pine (Pinus elliottii Engelm.) are two southern pine species that are popular for producing pine straw for landscaping. The objective of this research was to determine the response of soil properties and weed growth to the application of pine straw. Longleaf pine, slash pine, and two non-mulched controls (with and without chemical weed control) were tested. Volumetric soil water content, soil nutrients, soil temperature, weed biomass, and seedling growth were measured. Compared to non-mulched controls, both longleaf and slash pine plots had a greater soil moisture during extended periods without rainfall in the full sun environment. When soil temperatures increased, mulched plots had lower soil temperature relative to non-mulched plots. Soil pH and soil nutrients were generally similar between pine straw types with few significant differences in measured variables. Both pine straw treatments reduced weed growth and longleaf pine maintained a greater straw depth over the study period compared to slash pine, but no differences were observed for decomposition. These results indicate that longleaf pine straw and slash pine straw perform equally as well in terms of increasing soil moisture, moderating soil temperature, and reducing weed growth compared to not using mulch. Index words: Pinus elliottii, Pinus palustris, organic mulch, soil properties, landscaping. Species used in this study: Shumard oak, Quercus shumardii Buckl., Eastern redbud, Cercis canadensis L.

Combined effects of site preparation, soil properties, and sowing date on the establishment of Pinus sylvestris and Picea abies from seeds

2003 ◽  
Vol 33 (5) ◽  
pp. 931-945 ◽  
Author(s):  
Michelle de Chantal ◽  
Kari Leinonen ◽  
Hannu Ilvesniemi ◽  
Carl Johan Westman
Keyword(s):  
Soil Moisture ◽  
Picea Abies ◽  
Pinus Sylvestris ◽  
Soil Properties ◽  
Seedling Emergence ◽  
Growing Season ◽  
Sowing Date ◽  
Site Preparation ◽  
Winter Mortality ◽  
Frost Heaving

The aim of this study is to determine the effect of site preparation on soil properties and, in turn, the emergence, mortality, and establishment of Pinus sylvestris L. (Scots pine) and Picea abies (L.) Karst. (Norway spruce) seedlings sown in spring and summer along a slope with variation in soil texture and moisture. Three site preparation treatments of varying intensities were studied: exposed C horizon, mound (broken L–F–H–Ae–B horizons piled over undisturbed ground), and exposed Ae–B horizons. Seedling emergence was higher in the moist growing season than in the dry one. During a dry growing season, mounds and exposed C horizon had negative effects on soil moisture that increased mortality. Moreover, frost heaving was an important cause of winter mortality on mounds and exposed C horizon, whereas frost heaving was low on exposed Ae–B horizons, even though soil moisture and the content of fine soil particles (<0.06 mm) were high. Frost heaving mortality was higher for summer-sown than for spring-sown seedlings and for P. abies than for P. sylvestris. Growing season mortality was high following a winter with frost heaving, suggesting that roots were damaged, thereby making seedlings more susceptible to desiccation.

Mapping of tank silt application using Sentinel-2 images over the Berambadi catchment (India).

2021 ◽  
Author(s):  
Cécile Gomez ◽  
Dharumarajan Subramanian ◽  
Philippe Lagacherie ◽  
Jean Riotte ◽  
Sylvain Ferrant ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Properties ◽  
South India ◽  
Surface Soil ◽  
Soil Surface ◽  
Calibration Data ◽  
Surface Soil Moisture ◽  
Soil Color ◽  
Color Changes ◽  
Sentinel 2

&lt;p&gt;Mapping soil properties is becoming more and more challenging due to the increase in anthropogenic modification of the landscape, calling for new methods to identify these changes. A striking example of anthropogenic modifications of soil properties is the widespread practice in South India of applying large quantities of silt from dry river dams (or &amp;#8220;tanks&amp;#8221;) to agricultural fields. Whereas several studies have demonstrated the interest of tank silt for soil fertility, no assessment of the actual extent of this age-old traditional practice exists. Over pedological contexts characterized by Vertisol, Ferralsols and Chromic Luvisols in sub-humid and semi-arid Tropical climate, this practice is characterized by an application of black-colored tank silt providing from Vertisol, to red-colored soils such as Ferralsols. The objective of this work was to evaluate the usefulness of Sentinel-2 images for mapping tank silt applications, hypothesizing that observed changes in soil surface color can be a proxy for tank silt application.&lt;/p&gt;&lt;p&gt;We used data collected in a cultivated watershed (Berambadi, Karnataka state, South India) including 217 soil surface samples characterized in terms of Munsell color. We used two Sentinel-2 images acquired on February 2017 and April 2017. The surface soil color over each Sentinel-2 image was classified into two-class (&amp;#8220;Black&amp;#8221; and &amp;#8220;Red&amp;#8221; soils). A change of soil color from &amp;#8220;Red&amp;#8221; in February 2017 to &amp;#8220;Black&amp;#8221; in April 2017 was attributed to tank silt application. Soil color changes were analyzed accounting for possible surface soil moisture changes. The proposed methodology was based on a well-balanced Calibration data created from the initial imbalanced Calibration dataset thanks to the Synthetic Minority Over-sampling Technique (SMOTE) methodology, coupled to the Cost-Sensitive Classification And Regression Trees (Cost-Sensitive CART) algorithm. To estimate the uncertainties of i) the two-class classification at each date and ii) the change of soil color from &amp;#8220;Red&amp;#8221; to &amp;#8220;Black&amp;#8221;, a bootstrap procedure was used providing fifty two-class classifications for each Sentinel-2 image.&lt;/p&gt;&lt;p&gt;The results showed that 1) the CART method allowed to classify the &amp;#8220;Red&amp;#8221; and &amp;#8220;Black&amp;#8221; soil with overall accuracy around 0.81 and 0.76 from the Sentinel-2 image acquired on February and April 2017, respectively, 2) a tank silt application was identified over 97 fields with high confidence and over 107 fields with medium confidence, based on the bootstrap results and 3) the identified soil color changes are not related to a surface soil moisture change between both dates. With the actual availability of the Sentinel-2 and the past availability of the LANDSAT satellite imageries, this study may open a way toward a simple and accurate method for delivering tank silt application mapping and so to study and possibly quantify retroactively this farmer practice.&lt;/p&gt;

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