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1.

001-es BibID:BIBFORM081441
Első szerző:Deák Balázs (biológus)
Cím:Micro-topographic heterogeneity increases plant diversity in old stages of restored grasslands / Balázs Deák, Orsolya Valkó, Péter Török, András Kelemen, Tamás Miglécz, Szilárd Szabó, Gergely Szabó, Béla Tóthmérész
Dátum:2015
ISSN:1439-1791
Megjegyzések:It is a truism in ecology that environmental heterogeneity increases diversity. Supporting field studies are mostly concerned with a large-scale topographic heterogeneity, ranging from a couple of metres to landscape-scale gradients. To test the role of fine-scale micro-topography on plant diversity, we studied the initial vegetation of recently filled (1-year-old), and established vegetation on old (7-year-old) soil-filled channels in an alkali landscape, East-Hungary. We hypothesised that (i) recently filled channels are characterised by a high cover of ruderal species and high species diversity and (ii) high micro-topographic heterogeneity increases the diversity of species and plant strategy types (mixed C-S-R categories) in early stages but later on this effect diminishes. We found that diversity of species and plant strategy types was higher in recently filled channels compared to old filled channels. Micro-topographic heterogeneity had no effect on the studied vegetation parameters in recently filled channels. Conversely, in old filled channels higher micro-topographic heterogeneity resulted in higher diversity and lower cover of the dominant grass Festuca pseudovina. Higher micro-topographic heterogeneity resulted in increased ruderality and decreased stress-tolerance, but it did not increase the diversity of plant strategy types. In contrast with former studies, we found that a couple of centimetres of micro-topographic heterogeneity had no effect on vegetation in recently filled channels, but supported a high diversity in old filled channels. An important practical implication of our study is that in grassland restoration projects, micro-topographic heterogeneity has a crucial role in sustaining biodiversity.
Tárgyszavak:Természettudományok Biológiai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Alkali landscape
C-S-R strategies
Elevation
Functional diversity
Grassland restoration
Plant trait
Soil disturbance
Succession
Topography
Megjelenés:Basic And Applied Ecology. - 16 : 4 (2015), p. 291-299. -
További szerzők:Valkó Orsolya (1985-) (biológus) Török Péter (1979-) (biológus-ökológus) Kelemen András (1986-) (biológus-ökológus) Miglécz Tamás (1986-) (biológus ökológus) Szabó Szilárd (1974-) (geográfus) Szabó Gergely (1975-) (geográfus) Tóthmérész Béla (1960-) (ökológus)
Pályázati támogatás:TÁMOP-4.2.4.A/2-11-1-2012-0001
TÁMOP
TÁMOP-4.2.1./B-09/1/KONV- 2010-0007
TÁMOP
TÁMOP-4.2.2/B-10/1-2010-0024
TÁMOP
TÁMOP-4.2.2/C-11/1/KONV-2012-0010
TÁMOP
OTKA PD 100192
OTKA
OTKA PD 111807
OTKA
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2.

001-es BibID:BIBFORM065089
Első szerző:Hüse Bernadett (biológus)
Cím:Mapping an ecological network of green habitat patches and their role in maintaining urban biodiversity in and around Debrecen city (Eastern Hungary) / Bernadett Hüse, Szilárd Szabó, Balázs Deák, Béla Tóthmérész
Dátum:2016
ISSN:0264-8377
Tárgyszavak:Természettudományok Biológiai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Land Use Policy. - 57 (2016), p. 574-581. -
További szerzők:Szabó Szilárd (1974-) (geográfus) Deák Balázs (1978-) (biológus) Tóthmérész Béla (1960-) (ökológus)
Pályázati támogatás:OTKA K 116639 (BT)
Egyéb
OTKA PD 115627 (BD)
Egyéb
SROP-4.2.2.B-15/1/KONV-2015-0001
Egyéb
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3.

001-es BibID:BIBFORM085419
035-os BibID:(cikkazonosító)1468 (WOS)000543394000115 (Scopus)85085472067
Első szerző:Szabó Loránd (geográfus)
Cím:NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes-Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades / Szabó Loránd, Deák Balázs, Bíró Tibor, Dyke Gareth J., Szabó Szilárd
Dátum:2020
ISSN:2072-4292
Megjegyzések:Observing wetland areas and monitoring changes are crucial to understand hydrological and ecological processes. Sedimentation-induced vegetation spread is a typical process in the succession of lakes endangering these habitats. We aimed to survey the tendencies of vegetation spread of a Hungarian lake using satellite images, and to develop a method to identify the areas of risk. Accordingly, we performed a 33-year long vegetation spread monitoring survey. We used the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI) to assess vegetation and open water characteristics of the basins. We used these spectral indices to evaluate sedimentation risk of water basins combined with the fact that the most abundant plant species of the basins was the water caltrop (Trapa natans) indicating shallow water. We proposed a 12-scale Level of Sedimentation Risk Index (LoSRI) composed from vegetation cover data derived from satellite images to determine sedimentation risk within any given water basin. We validated our results with average water basin water depth values, which showed an r = 0.6 (p < 0.05) correlation. We also pointed on the most endangered locations of these sedimentation-threatened areas, which can provide crucial information for management planning of water directorates and management organizations.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
remote sensing
sedimentation
spectral indices
time-series analysis
vegetation change
wetland monitoring
Megjelenés:Remote Sensing. - 12 : 9 (2020), p. 1-24. -
További szerzők:Deák Balázs (1978-) (biológus) Bíró Tibor Dyke, Gareth J. Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:NKFIH-1150-6/2019
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4.

001-es BibID:BIBFORM082564
Első szerző:Szabó Loránd (geográfus)
Cím:Assessing the efficiency of multispectral satellite and airborne hyperspectral images for land cover mapping in an aquatic environment with emphasis on the water caltrop (Trapa natans) / Szabó Loránd, Burai Péter, Deák Balázs, Dyke, Gareth J., Szabó, Szilárd
Dátum:2019
ISSN:0143-1161
Megjegyzések:A number of clear issues are pertinent when considering whether, or not, to use a remotely sensed dataset. We evaluate these issues here by comparing an aerial hyperspectral image at 1.5 m geometric resolution that comprises 128 narrow bands within a spectral range between 400 nm and 1,000 nm as well as a nine-band Landsat 8 image at 30.0 m geometric resolution. We therefore applied Random Forest (RF) and Support Vector Machine (SVM) classifiers utilizing different input data sets to determine the best thematic accuracy for both types of images by involving all possible bands and then minimized them using variable selection and dimension reduction via Minimum Noise Fraction (MNF). We then compared Landsat images to an aerial hyperspectral one. The results of this analysis revealed that band selections based on variable importance and MNF-transformation improved thematic accuracy assessed as Overall Accuracy (OA). Results reveal a 1.00% improvement in OA via variable selection as 59 bands instead of 128 bands and a 1.50% via MNF-transformation of the hyperspectral image. This improvement was 4.52% in the Landsat image when using a MNFtransformation compared to the best performances without transformation or variable selection. Data also showed that application of Landsat spectral range on hyperspectral bands resulted in different outcomes; specifically, SVM resulted in a 91.50% OA while RF resulted in 95.50% OA. Landscape ecology results show that use of the Landsat image provided fewer land cover patches and that differences encompassed 6.30% of the whole area. We therefore conclude that Landsat data can be used with a number of limitations for accurate ecological mapping.
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:International Journal Of Remote Sensing. - 40 : 13 (2019), p. 5192-5215. -
További szerzők:Burai Péter (1977-) (agrármérnök) Deák Balázs (1978-) (biológus) Dyke, Gareth J. Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:EFOP-3.6.1-16-2016-00022
EFOP
4th Thematic Program of the University of Debrecen
FIKP
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5.

001-es BibID:BIBFORM079559
035-os BibID:(cikkazonosító)104187
Első szerző:Szabó Szilárd (geográfus)
Cím:Dataset for landscape pattern analysis from a climatic perspective / Szilárd Szabó, Balázs Deák, Zoltán Kovács, Ádám Kertész, Boglárka Bertalan-Balázs
Dátum:2019
ISSN:2352-3409
Megjegyzések:Revealing the driving forces of changes in landscape pattern is a key question of landscape ecology and landscape analysis. Temperature and precipitation as climatic variables have a dominant role in triggering vegetation changes; thus, a database, which contain their interaction, can support the understanding of spatio-temporal changes in vegetation patterns even on a large scale. The dataset provided in this article contain the R-squared values of bivariate linear regression analysis between the Normalized Difference Vegetation Index (target variable; as a general quantitative descriptor of surface greenness) of the TERRA satellite's MODIS sensor and the climatic variables of the CarpatClim database (predictor variables; maximum monthly temperature, aridification index, evapotranspiration and precipitation). Environmental variables are also included to support further analysis: terrain height, macro regions, land cover classes. The dataset has a spatial projection (i.e. maps) and covers the area of Hungary. Tabular version provides the possibility of traditional statistical analysis, while maps allow the investigation to involve the spatial characteristics of absolute and relative position of the data points. This data article is related to the paper "NDVI dynamics as reflected in climatic variables: spatial and temporal trends - a case study of Hungary" (Szabo et al., 2019).
Tárgyszavak:Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban
NDVI
Trend
Climatic factors
R-squared
Pattern
Megjelenés:Data in Brief. - 25 (2019), p. 1-5. -
További szerzők:Deák Balázs (1978-) (biológus) Kovács Zoltán (1988-) (geográfus) Kertész Ádám (1948-) Balázs Boglárka (1985-) (geográfus)
Pályázati támogatás:TÁMOP 4.2.4. A/2-11-1-2012-0001
TÁMOP
NKFIH 108755
Egyéb
TUDFO/51757/2019-IT Thematic Excellence Project of the University of Debrecen
Egyéb
NKFI KH 130338
Egyéb
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