Quantifying patterns of complexity controlled by parent material at different spatial scales: from drainage network architecture at landscape scale to soil texture. A hydropedologic research conducted on wine regions of the Douro river basin

AbstractInternal waves (IWs) in the ocean span across a wide range of time and spatial scales and are now acknowledged as important sources of turbulence and mixing, with the largest observations having 200 m in amplitude and vertical velocities close to 0.5 m s−1. Their origin is mostly tidal, but an increasing number of non-tidal generation mechanisms have also been observed. For instance, river plumes provide horizontally propagating density fronts, which were observed to generate IWs when transitioning from supercritical to subcritical flow. In this study, satellite imagery and autonomous underwater measurements are combined with numerical modeling to investigate IW generation from an initial subcritical density front originating at the Douro River plume (western Iberian coast). These unprecedented results may have important implications in near-shore dynamics since that suggest that rivers of moderate flow may play an important role in IW generation between fresh riverine and coastal waters.

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Brain pathology recapitulates physiology: A network meta-analysis

Communications Biology ◽

10.1038/s42003-021-01832-9 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Thomas J. Vanasse ◽

Peter T. Fox ◽

P. Mickle Fox ◽

Franco Cauda ◽

Tommaso Costa ◽

...

Keyword(s):

Network Architecture ◽

Spatial Scales ◽

Meta Analysis ◽

Metabolic Cost ◽

Common Mechanism ◽

Brain Disorders ◽

Brain Pathology ◽

Structural Network ◽

Meta Analyses ◽

Function Network

AbstractNetwork architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic ‘cost’ significantly differs along this transdiagnostic/multimodal gradient.

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Western white pine development in relation to biophysical characteristics across different spatial scales in the Coeur d'Alene River basin in northern Idaho, U.S.A.

Canadian Journal of Forest Research ◽

10.1139/x02-032 ◽

2002 ◽

Vol 32 (7) ◽

pp. 1109-1125 ◽

Cited By ~ 4

Author(s):

Theresa B Jain ◽

Russell T Graham ◽

Penelope Morgan

Keyword(s):

River Basin ◽

Spatial Scales ◽

Pinus Monticola ◽

White Pine ◽

Basal Diameter ◽

Landscape Characteristics ◽

Coeur D'alene ◽

Biophysical Factors ◽

Western White Pine ◽

Northern Idaho

Many studies have assessed tree development beneath canopies in forest ecosystems, but results are seldom placed within the context of broad-scale biophysical factors. Mapped landscape characteristics for three watersheds, located within the Coeur d'Alene River basin in northern Idaho, were integrated to create a spatial hierarchy reflecting biophysical factors that influence western white pine (Pinus monticola Dougl. ex D. Don) development under a range of canopy openings. The hierarchy included canopy opening, landtype, geological feature, and weathering. Interactions and individual-scale contributions were identified using stepwise loglinear regression. The resulting models explained 68% of the variation for estimating western white pine basal diameter and 64% for estimating height. Interactions among spatial scales explained up to 13% of this variation and better described vegetation response than any single spatial scale. A hierarchical approach based on biophysical attributes is an excellent method for studying plant and environment interactions.

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Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

Sustainability ◽

10.3390/su9071246 ◽

2017 ◽

Vol 9 (7) ◽

pp. 1246 ◽

Cited By ~ 7

Author(s):

Ling Lu ◽

Chao Liu ◽

Xin Li ◽

Youhua Ran

Keyword(s):

Fuzzy Logic ◽

Data Fusion ◽

River Basin ◽

Soil Texture ◽

Heihe River Basin ◽

Heihe River ◽

The Heihe River Basin

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Mapping wildlife: integrating stakeholder knowledge with modelled patterns of deer abundance by using participatory GIS

Wildlife Research ◽

10.1071/wr08153 ◽

2009 ◽

Vol 36 (7) ◽

pp. 553 ◽

Cited By ~ 10

Author(s):

Z. Austin ◽

S. Cinderby ◽

J. C. R. Smart ◽

D. Raffaelli ◽

P. C. L. White

Keyword(s):

Community Involvement ◽

Spatial Data ◽

Spatial Scales ◽

Stakeholder Participation ◽

Landscape Scale ◽

Scientific Data ◽

Future Research ◽

Economic Damage ◽

Participatory Gis ◽

Wild Deer

Context. Some species that are perceived by certain stakeholders as a valuable resource can also cause ecological or economic damage, leading to contrasting management objectives and subsequent conflict between stakeholder groups. There is increasing recognition that the integration of stakeholder knowledge with formal scientific data can enhance the information available for use in management. This is especially true where scientific understanding is incomplete, as is frequently the case for wide-ranging species, which can be difficult to monitor directly at the landscape scale. Aims. The aim of the research was to incorporate stakeholder knowledge with data derived from formal quantitative models to modify predictions of wildlife distribution and abundance, using wild deer in the UK as an example. Methods. We use selected predictor variables from a deer–vehicle collision model to estimate deer densities at the 10-km square level throughout the East of England. With these predictions as a baseline, we illustrate the use of participatory GIS as a methodological framework for enabling stakeholder participation in the refinement of landscape-scale deer abundance maps. Key results. Stakeholder participation resulted in modifications to modelled abundance patterns for all wild deer species present in the East of England, although the modifications were minor and there was a high degree of consistency among stakeholders in the adjustments made. For muntjac, roe and fallow deer, the majority of stakeholder changes represented an increase in density, suggesting that populations of these species are increasing in the region. Conclusions. Our results show that participatory GIS is a useful technique for enabling stakeholders to contribute to incomplete scientific knowledge, especially where up-to-date species distribution and abundance data are needed to inform wildlife research and management. Implications. The results of the present study will serve as a valuable information base for future research on deer management in the region. The flexibility of the approach makes it applicable to a range of species at different spatial scales and other wildlife conflict issues. These may include the management of invasive species or the conservation of threatened species, where accurate spatial data and enhanced community involvement are necessary in order to facilitate effective management.

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Identification of Synchronicity in Deterministic Chaotic Attractors for the Downscaling Process in the Bogotá River Basin

10.5194/egusphere-egu21-14752 ◽

2021 ◽

Author(s):

Santiago Duarte ◽

Gerald Corzo ◽

Germán Santos

Keyword(s):

Time Series ◽

Time Delay ◽

River Basin ◽

Spatial Scales ◽

Climatic Variables ◽

Chaotic Attractors ◽

Multiple Attractors ◽

Nearest Neighbours ◽

Basin Scale ◽

Non Linear

Bogot&#225;&#8217;s River Basin, it&#8217;s an important basin in Cundinamarca, Colombia&#8217;s central region. Due to the complexity of the dynamical climatic system in tropical regions, can be difficult to predict and use the information of GCMs at the basin scale. This region is especially influenced by ENSO and non-linear climatic oscillation phenomena. Furthermore, considering that climatic processes are essentially non-linear and possibly chaotic, it may reduce the effectiveness of downscaling techniques in this region.&#160;In this study, we try to apply chaotic downscaling to see if we could identify synchronicity that will allow us to better predict. It was possible to identify clearly the best time aggregation that can capture at the best the maximum relations between the variables at different spatial scales. Aside this research proposes a new combination of multiple attractors. Few analyses have been made to evaluate the existence of synchronicity between two or more attractors. And less analysis has considered the chaotic behaviour in attractors derived from climatic time series at different spatial scales.&#160;Thus, we evaluate general synchronization between multiple attractors of various climate time series. The Mutual False Nearest Neighbours parameter (MFNN) is used to test the &#8220;Synchronicity Level&#8221; (existence of any type of synchronization) between two different attractors. Two climatic variables were selected for the analysis: Precipitation and Temperature. Likewise, two information sources are used: At the basin scale, local climatic-gauge stations with daily data and at global scale, the output of the MPI-ESM-MR model with a spatial resolution of 1.875&#176;x1.875&#176; for both climatic variables (1850-2005). In the downscaling process, two RCP (Representative Concentration Pathways)&#160; scenarios are used, RCP 4.5 and RCP 8.5.For the attractor&#8217;s reconstruction, the time-delay is obtained through the&#160; Autocorrelation and the Mutual Information functions. The False Nearest Neighbors method (FNN) allowed finding the embedding dimension to unfold the attractor. This information was used to identify deterministic chaos at different times (e.g. 1, 2, 3 and 5 days) and spatial scales using the Lyapunov exponents. These results were used to test the synchronicity between the various chaotic attractor&#8217;s sets using the MFNN method and time-delay relations. An optimization function was used to find the attractor&#8217;s distance relation that increases the synchronicity between the attractors.&#160; These results provided the potential of synchronicity in chaotic attractors to improve rainfall and temperature downscaling results at aggregated daily-time steps. Knowledge of loss information related to multiple reconstructed attractors can provide a better construction of downscaling models. This is new information for the downscaling process. Furthermore, synchronicity can improve the selection of neighbours for nearest-neighbours methods looking at the behaviour of synchronized attractors. This analysis can also allow the classification of unique patterns and relationships between climatic variables at different temporal and spatial scales.

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X-ray fluorescence spectrometry for rapid screening of particle size in soils

10.5194/egusphere-egu21-5307 ◽

2021 ◽

Author(s):

Maame Croffie ◽

Paul N. Williams ◽

Owen Fenton ◽

Anna Fenelon ◽

Karen Daly

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Soil Texture ◽

Particle Size Analysis ◽

Parent Material ◽

Fluorescence Spectrometry ◽

Rapid Screening ◽

Size Analysis ◽

X Ray

Soil texture is an essential factor for effective land management in agricultural production. Knowledge of soil texture and particle size at field scale can aid with on-going soil management decisions. Standard soil physical and gravimetric methods for particle size analysis are time-consuming and X-ray fluorescence spectrometry (XRF) provides a rapid and cost-effective alternative. The objective of this study was to explore the use of XRF as a predictor for particle size. An extensive archive of Irish soils with particle size and soil texture data was used to select samples for XRF analysis. Regression and correlation analyses on XRF determined results showed that the relationship between Rb and % clay varied with soil type and was dependent on the parent material. There was a strong relationship (R > 0.62, R2>0.30, p<0.05) between Rb and clay for soils originating from bedrock such as limestones and slate. Contrastingly, no significant relationship (R<0.03, R2=0.00, p>0.05) exists between Rb and % clay for soils originating from granite and gneiss. Furthermore, there was a significant negative correlation (p<0.05) between Rb and % sand. The XRF is a useful technique for rough screening of particle size distribution in soils originating from certain parent materials. Thus, this may contribute to the rapid prediction of soil texture based on knowledge of the particle size distribution.&#160;

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Soil Erosion Model Predictions Using Parent Material/Soil Texture-Based Parameters Compared to Using Site-Specific Parameters

Transactions of the ASABE ◽

10.13031/2013.39036 ◽

2011 ◽

Vol 54 (4) ◽

pp. 1347-1356 ◽

Cited By ~ 7

Author(s):

R. B. Foltz ◽

W. J. Elliot ◽

N. S. Wagenbrenner

Keyword(s):

Soil Erosion ◽

Soil Texture ◽

Parent Material ◽

Site Specific ◽

Erosion Model ◽

Model Predictions

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Evaluation and Hydrologic Validation of Three Satellite-Based Precipitation Products in the Upper Catchment of the Red River Basin, China

Remote Sensing ◽

10.3390/rs10121881 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1881 ◽

Cited By ~ 7

Author(s):

Yueyuan Zhang ◽

Yungang Li ◽

Xuan Ji ◽

Xian Luo ◽

Xue Li

Keyword(s):

River Basin ◽

Southwest China ◽

Spatial Scales ◽

Red River ◽

Low Flow ◽

Efficiency Coefficient ◽

Monthly Streamflow ◽

Red River Basin ◽

Hydrological Applications ◽

Trmm 3B42

Satellite-based precipitation products (SPPs) provide alternative precipitation estimates that are especially useful for sparsely gauged and ungauged basins. However, high climate variability and extreme topography pose a challenge. In such regions, rigorous validation is necessary when using SPPs for hydrological applications. We evaluated the accuracy of three recent SPPs over the upper catchment of the Red River Basin, which is a mountain gorge region of southwest China that experiences a subtropical monsoon climate. The SPPs included the Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 product, the Climate Prediction Center (CPC) Morphing Algorithm (CMORPH), the Bias-corrected product (CMORPH_CRT), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Climate Data Record (PERSIANN_CDR) products. SPPs were compared with gauge rainfall from 1998 to 2010 at multiple temporal (daily, monthly) and spatial scales (grid, basin). The TRMM 3B42 product showed the best consistency with gauge observations, followed by CMORPH_CRT, and then PERSIANN_CDR. All three SPPs performed poorly when detecting the frequency of non-rain and light rain events (<1 mm); furthermore, they tended to overestimate moderate rainfall (1–25 mm) and underestimate heavy and hard rainfall (>25 mm). GR (Génie Rural) hydrological models were used to evaluate the utility of the three SPPs for daily and monthly streamflow simulation. Under Scenario I (gauge-calibrated parameters), CMORPH_CRT presented the best consistency with observed daily (Nash–Sutcliffe efficiency coefficient, or NSE = 0.73) and monthly (NSE = 0.82) streamflow. Under Scenario II (individual-calibrated parameters), SPP-driven simulations yielded satisfactory performances (NSE >0.63 for daily, NSE >0.79 for monthly); among them, TRMM 3B42 and CMORPH_CRT performed better than PERSIANN_CDR. SPP-forced simulations underestimated high flow (18.1–28.0%) and overestimated low flow (18.9–49.4%). TRMM 3B42 and CMORPH_CRT show potential for use in hydrological applications over poorly gauged and inaccessible transboundary river basins of Southwest China, particularly for monthly time intervals suitable for water resource management.

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