The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication
The paper established link between phytoindication estimated environmental regimes and geomorphological predictors and built environmental spatial patterns of variation modes within the Dnipropetrovsk region. 175 geobotanical descriptions were conducted in the 2016‒2017 yy. within the Dnepropetrovsk...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Dnipro State Agrarian and Economic University
2019-01-01
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| Series: | Agrology |
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| Online Access: | http://ojs.dsau.dp.ua/index.php/agrology/article/view/1620 |
| _version_ | 1797708280767709184 |
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| author | O. V. Zhukov O. V. Potapenko |
| author_facet | O. V. Zhukov O. V. Potapenko |
| author_sort | O. V. Zhukov |
| collection | DOAJ |
| description | The paper established link between phytoindication estimated environmental regimes and geomorphological predictors and built environmental spatial patterns of variation modes within the Dnipropetrovsk region. 175 geobotanical descriptions were conducted in the 2016‒2017 yy. within the Dnepropetrovsk region (Ukraine). Phytoindication assessment of the environmental regimes was made on the basis of the geobotanical description: soil water regime, variability of damping, soil aeration, soil acidity, total salt regime, carbonate content in soil, nitrogen content in soil, radiation balance, aridity or humidity, continentality, the rigours of the winter, light regime. The phytoindication assessments of the environmental regimes are characterized by correlation of geomorphological properties. Regression models can explain 10‒31% variability of phytoindication environmental assessments modes. Most appeared to be dependent geomorphological regime nitrogen nutrition and moisture, and the least ‒ the mode of variability of moisture and ombroclimat. Edaphic regimes for environmental information and most valuable predictor is the height of the relief and direct insolation (four statistically significant regression coefficient). For most modes of climate information and valuable factor in erosion, direct insolation and height of the channel network (two statistically significant regression coefficient). Entropy of the relief diversity is statistically significant predictor for salt regime, carbonate content and termoclimat. Digital elevation models and derivative information layers of spatial data (topographic wetness index, topographic position index, mass balance index, erosion factors, geomorphological assessment of direct and diffuse insolation, vertical distance to channel network, vector ruggedness measure, Shannon diversity of terrain) is a valuable information covariates (predictors) of the environmental regimes that obtained using the synphytoindication method. Procedure of the spatial extrapolation of the phytoindication assessments at regional level can be performed based on regression models by the method of support vectors. This approach is flexible and takes into account the specific environmental interactions in the system topography and vegetation and environmental regimes. |
| first_indexed | 2024-03-12T06:19:01Z |
| format | Article |
| id | doaj.art-acf065011fd149878b34402569f09ab1 |
| institution | Directory Open Access Journal |
| issn | 2617-6106 2617-6114 |
| language | English |
| last_indexed | 2024-03-12T06:19:01Z |
| publishDate | 2019-01-01 |
| publisher | Dnipro State Agrarian and Economic University |
| record_format | Article |
| series | Agrology |
| spelling | doaj.art-acf065011fd149878b34402569f09ab12023-09-03T02:21:49ZengDnipro State Agrarian and Economic UniversityAgrology2617-61062617-61142019-01-0121102110.32819/2617-6106.2018.14012The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindicationO. V. Zhukov0O. V. Potapenko1Oles Gonchar Dnipro National University, Dnipro, UkraineDnipro State Agrarian and Economic University, Dnipro, UkraineThe paper established link between phytoindication estimated environmental regimes and geomorphological predictors and built environmental spatial patterns of variation modes within the Dnipropetrovsk region. 175 geobotanical descriptions were conducted in the 2016‒2017 yy. within the Dnepropetrovsk region (Ukraine). Phytoindication assessment of the environmental regimes was made on the basis of the geobotanical description: soil water regime, variability of damping, soil aeration, soil acidity, total salt regime, carbonate content in soil, nitrogen content in soil, radiation balance, aridity or humidity, continentality, the rigours of the winter, light regime. The phytoindication assessments of the environmental regimes are characterized by correlation of geomorphological properties. Regression models can explain 10‒31% variability of phytoindication environmental assessments modes. Most appeared to be dependent geomorphological regime nitrogen nutrition and moisture, and the least ‒ the mode of variability of moisture and ombroclimat. Edaphic regimes for environmental information and most valuable predictor is the height of the relief and direct insolation (four statistically significant regression coefficient). For most modes of climate information and valuable factor in erosion, direct insolation and height of the channel network (two statistically significant regression coefficient). Entropy of the relief diversity is statistically significant predictor for salt regime, carbonate content and termoclimat. Digital elevation models and derivative information layers of spatial data (topographic wetness index, topographic position index, mass balance index, erosion factors, geomorphological assessment of direct and diffuse insolation, vertical distance to channel network, vector ruggedness measure, Shannon diversity of terrain) is a valuable information covariates (predictors) of the environmental regimes that obtained using the synphytoindication method. Procedure of the spatial extrapolation of the phytoindication assessments at regional level can be performed based on regression models by the method of support vectors. This approach is flexible and takes into account the specific environmental interactions in the system topography and vegetation and environmental regimes.http://ojs.dsau.dp.ua/index.php/agrology/article/view/1620digital elevation modelenvironmental regimesphytoindicationlandformsspatial models |
| spellingShingle | O. V. Zhukov O. V. Potapenko The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication Agrology digital elevation model environmental regimes phytoindication landforms spatial models |
| title | The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication |
| title_full | The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication |
| title_fullStr | The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication |
| title_full_unstemmed | The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication |
| title_short | The role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication |
| title_sort | role of geomorphological predictors for modeling spatial variation of environmental regimes measured using phytoindication |
| topic | digital elevation model environmental regimes phytoindication landforms spatial models |
| url | http://ojs.dsau.dp.ua/index.php/agrology/article/view/1620 |
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