scholarly journals Individual contributions of climate and vegetation change to soil moisture trends across multiple spatial scales

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Huihui Feng
Keyword(s):  
Soil Moisture ◽  
Vegetation Change ◽  
Spatial Scales ◽  
Multiple Spatial Scales ◽  
Individual Contributions

Influences of sociality and habitat on African mole-rat burrowing patterns

2005 ◽  
Vol 83 (8) ◽  
pp. 1051-1058 ◽  
Author(s):  
Stephanie S Romañach
Keyword(s):  
Soil Moisture ◽  
Spatial Patterns ◽  
Resource Availability ◽  
Spatial Scales ◽  
Habitat Characteristics ◽  
Subterranean Rodents ◽  
Habitat Types ◽  
Multiple Spatial Scales ◽  
Social Species ◽  
Mole Rat

The movement choices that animals make are influenced by many factors including resource availability, which in turn can affect whether the animals search for resources alone or in groups. Subterranean rodents are ideal for examining movement paths because they create burrows that persist for extended periods and thus serve as records of movement. African mole-rat species (Bathyergidae) are solitary, social, or eusocial, and inhabit a variety of habitat types. In this study, mole-rat burrowing patterns were examined by analyzing the spatial patterns of the soil mounds that they create as they burrow. Mound spatial patterns were examined for solitary and social species occurring in two habitats, which differed in rainfall, soil moisture, and vegetation availability. Examination of mound spatial patterns at multiple spatial scales revealed that mounds of single burrow systems were clustered at small spatial scales (<6 m), while mounds were not clustered at the larger spatial scales of the entire burrow systems. Spatial patterns of mounds did not differ in relation to sociality or habitat characteristics. These findings, as well as evidence from other taxa, may suggest common burrowing strategies for subterranean rodents.

Inhibition of coral settlement at multiple spatial scales by a pervasive algal competitor

2019 ◽  
Vol 612 ◽  
pp. 29-42 ◽  
Author(s):  
NR Evensen ◽  
C Doropoulos ◽  
KM Morrow ◽  
CA Motti ◽  
PJ Mumby
Keyword(s):  
Spatial Scales ◽  
Coral Settlement ◽  
Multiple Spatial Scales

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

Assessment of clogging in constructed wetlands by saturated hydraulic conductivity measurements

2019 ◽  
Vol 79 (2) ◽  
pp. 314-322 ◽  
Author(s):  
F. Licciardello ◽  
R. Aiello ◽  
V. Alagna ◽  
M. Iovino ◽  
D. Ventura ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Hydraulic Conductivity ◽  
Constructed Wetlands ◽  
Spatial Scales ◽  
Pilot Scale ◽  
Laboratory Scale ◽  
Test Method ◽  
Conductivity Measurements ◽  
Multiple Spatial Scales ◽  
Ks Values

Abstract This study aims at defining a methodology to evaluate Ks reductions of gravel material constituting constructed wetland (CW) bed matrices. Several schemes and equations for the Lefranc's test were compared by using different gravel sizes and at multiple spatial scales. The falling-head test method was implemented by using two steel permeameters: one impervious (IMP) and one pervious (P) on one side. At laboratory scale, mean K values for a small size gravel (8–15 × 10−2 m) measured by the IMP and the P permeameters were equal to 19,466 m/d and 30,662 m/d, respectively. Mean Ks values for a big size gravel (10–25 × 10−2 m) measured by the IMP and the P permeameters were equal to 12,135 m/d and 20,866 m/d, respectively. Comparison of Ks values obtained by the two permeameters at laboratory scale as well as a sensitivity analysis and a calibration, lead to the modification of the standpipe equation, to evaluate also the temporal variation of the horizontal Ks. In particular, both permeameters allow the evaluation of the Ks decreasing after 4 years-operation and 1–1.5 years' operation of the plants at full scale (filled with the small size gravel) and at pilot scale (filled with the big size gravel), respectively.

scholarly journals FORMULATION OF THE HEAT CONDUCTION EQUATION FOR HETEROGENEOUS MEDIA WITH MULTIPLE SPATIAL SCALES USING REITERATED HOMOGENIZATION

2016 ◽  
Vol 15 (1) ◽  
pp. 96
Author(s):  
E. Iglesias-Rodríguez ◽  
M. E. Cruz ◽  
J. Bravo-Castillero ◽  
R. Guinovart-Díaz ◽  
R. Rodríguez-Ramos ◽  
...  
Keyword(s):  
Heat Conduction ◽  
Small Parameter ◽  
Heat Conduction Equation ◽  
Heterogeneous Media ◽  
Spatial Scales ◽  
Conduction Equation ◽  
Small Scale ◽  
Multiple Spatial Scales ◽  
Effective Coefficients ◽  
Reiterated Homogenization

Heterogeneous media with multiple spatial scales are finding increased importance in engineering. An example might be a large scale, otherwise homogeneous medium filled with dispersed small-scale particles that form aggregate structures at an intermediate scale. The objective in this paper is to formulate the strong-form Fourier heat conduction equation for such media using the method of reiterated homogenization. The phases are assumed to have a perfect thermal contact at the interface. The ratio of two successive length scales of the medium is a constant small parameter ε. The method is an up-scaling procedure that writes the temperature field as an asymptotic multiple-scale expansion in powers of the small parameter ε . The technique leads to two pairs of local and homogenized equations, linked by effective coefficients. In this manner the medium behavior at the smallest scales is seen to affect the macroscale behavior, which is the main interest in engineering. To facilitate the physical understanding of the formulation, an analytical solution is obtained for the heat conduction equation in a functionally graded material (FGM). The approach presented here may serve as a basis for future efforts to numerically compute effective properties of heterogeneous media with multiple spatial scales.

Applying systematic conservation planning to improve the allocation of restoration actions at multiple spatial scales

2021 ◽  
Author(s):  
Ben L. Gilby ◽  
Andrew D. Olds ◽  
Christopher J. Brown ◽  
Rod M. Connolly ◽  
Christopher J. Henderson ◽  
...  
Keyword(s):  
Conservation Planning ◽  
Spatial Scales ◽  
Systematic Conservation Planning ◽  
Multiple Spatial Scales
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