An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem

The development of soil quality index in the vicinity of the Van Lake pasture lands located in the Northern East Part of Turkey under semi-arid terrestrial ecosystem is very important since there are certain degradation signs indicating how their sustainability is being threatened. A total of 150 so...

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Autores principales:	Siyami Karaca, Orhan Dengiz, İnci Demirağ Turan, Barış Özkan, Mert Dedeoğlu, Füsun Gülser, Bulut Sargin, Salih Demirkaya, Abdurahman Ay
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Soil quality Pasture Fuzzy-AHP Principal component analysis REOSAVI Semi-arid ecosystem Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/7c9aa704d360424e8cb9fec76a0b99ea
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spelling	oai:doaj.org-article:7c9aa704d360424e8cb9fec76a0b99ea2021-12-01T04:32:18ZAn assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem1470-160X10.1016/j.ecolind.2020.107001https://doaj.org/article/7c9aa704d360424e8cb9fec76a0b99ea2021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20309407https://doaj.org/toc/1470-160XThe development of soil quality index in the vicinity of the Van Lake pasture lands located in the Northern East Part of Turkey under semi-arid terrestrial ecosystem is very important since there are certain degradation signs indicating how their sustainability is being threatened. A total of 150 soils in the pastures throughout the region were sampled and several soil physical, chemical and biological indicators were quantified. A minimum data set of the most sensitive indicators was chosen using principal component analyses. Linear scoring functions for these indicators were used to develop soil quality index integrated with remote sensing (RS) and geographical information system (GIS). In this current study, classes between SQIs calculated using the minimum data set (MDS) and total data set (TDS) approaches showed a parallel trend in each other and match analysis for agreement showed also a significant statistically relationship between TDSSQI/MDSSQI and REOSAVI in May and June months for pasture area. Furthermore, this study also showed that advance techniques (PCA, geostatistic, AHP-Fuzzy) and the technologies of RS and GIS, which are essential to the analysis and processing of original and generated information were used effectively by integrating each other for SQI in large area.Siyami KaracaOrhan Dengizİnci Demirağ TuranBarış ÖzkanMert DedeoğluFüsun GülserBulut SarginSalih DemirkayaAbdurahman AyElsevierarticleSoil qualityPastureFuzzy-AHPPrincipal component analysisREOSAVISemi-arid ecosystemEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107001- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Soil quality Pasture Fuzzy-AHP Principal component analysis REOSAVI Semi-arid ecosystem Ecology QH540-549.5
spellingShingle	Soil quality Pasture Fuzzy-AHP Principal component analysis REOSAVI Semi-arid ecosystem Ecology QH540-549.5 Siyami Karaca Orhan Dengiz İnci Demirağ Turan Barış Özkan Mert Dedeoğlu Füsun Gülser Bulut Sargin Salih Demirkaya Abdurahman Ay An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
description	The development of soil quality index in the vicinity of the Van Lake pasture lands located in the Northern East Part of Turkey under semi-arid terrestrial ecosystem is very important since there are certain degradation signs indicating how their sustainability is being threatened. A total of 150 soils in the pastures throughout the region were sampled and several soil physical, chemical and biological indicators were quantified. A minimum data set of the most sensitive indicators was chosen using principal component analyses. Linear scoring functions for these indicators were used to develop soil quality index integrated with remote sensing (RS) and geographical information system (GIS). In this current study, classes between SQIs calculated using the minimum data set (MDS) and total data set (TDS) approaches showed a parallel trend in each other and match analysis for agreement showed also a significant statistically relationship between TDSSQI/MDSSQI and REOSAVI in May and June months for pasture area. Furthermore, this study also showed that advance techniques (PCA, geostatistic, AHP-Fuzzy) and the technologies of RS and GIS, which are essential to the analysis and processing of original and generated information were used effectively by integrating each other for SQI in large area.
format	article
author	Siyami Karaca Orhan Dengiz İnci Demirağ Turan Barış Özkan Mert Dedeoğlu Füsun Gülser Bulut Sargin Salih Demirkaya Abdurahman Ay
author_facet	Siyami Karaca Orhan Dengiz İnci Demirağ Turan Barış Özkan Mert Dedeoğlu Füsun Gülser Bulut Sargin Salih Demirkaya Abdurahman Ay
author_sort	Siyami Karaca
title	An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
title_short	An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
title_full	An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
title_fullStr	An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
title_full_unstemmed	An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
title_sort	assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/7c9aa704d360424e8cb9fec76a0b99ea
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An assessment of pasture soils quality based on multi-indicator weighting approaches in semi-arid ecosystem

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