Global Megatrends Impacts on the Landscape, Analysis Based on Key Drivers of the Megatrends and Landscape Change: Case Study of Danubian Lowland, Slovakia

Abstract Global megatrends (GMTs) reshape landscapes worldwide, posing challenges for sustainability. This study delves into the complex interplay between GMTs and landscape changes in the Danube Lowland region of Slovakia, a microcosm of broader trends. Leveraging the concept of representative potential geoecosystems (REPGES), we assess historical landscape transformations and correlate them with key GMT drivers. Results reveal significant urban expansion linked to GMT2, primarily impacting the Bratislava area. Simultaneously, GMT5-driven economic growth manifests in agricultural land expansion and the total loss of one REPGES type. Notably, these changes coincide with a decrease in ecological stability across the region. Spatial analysis further unravels the interplay of GMTs, highlighting areas under intense urban and agricultural pressure. Our findings not only shed light on specific GMT impacts in the Danube Lowland but also offer valuable insights for landscape management across diverse regions facing similar megatrends. By understanding these complex interactions, we can develop informed strategies to navigate the challenges and opportunities presented by a globalized world, promoting sustainable landscapes for the future.

Authors

Institutions

Publication Details

Journal
Ochrana prírody Slovenska/Ekológia
Published
2024-12-01
DOI
https://doi.org/10.2478/eko-2024-0019
Citations
2
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.57
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Global Megatrends Impacts on the Landscape, Analysis Based on Key Drivers of the Megatrends and Landscape Change: Case Study of Danubian Lowland, Slovakia

Zita Izakovičová, Andrej Raniak
2 citations
Ochrana prírody Slovenska/Ekológia
Land Use and Ecosystem Services
0.57
article

Global Megatrends Impacts on the Landscape, Analysis Based on Key Drivers of the Megatrends and Landscape Change: Case Study of Danubian Lowland, Slovakia

Zita Izakovičová, Andrej Raniak
article en
2 citations

Abstract

Abstract Global megatrends (GMTs) reshape landscapes worldwide, posing challenges for sustainability. This study delves into the complex interplay between GMTs and landscape changes in the Danube Lowland region of Slovakia, a microcosm of broader trends. Leveraging the concept of representative potential geoecosystems (REPGES), we assess historical landscape transformations and correlate them with key GMT drivers. Results reveal significant urban expansion linked to GMT2, primarily impacting the Bratislava area. Simultaneously, GMT5-driven economic growth manifests in agricultural land expansion and the total loss of one REPGES type. Notably, these changes coincide with a decrease in ecological stability across the region. Spatial analysis further unravels the interplay of GMTs, highlighting areas under intense urban and agricultural pressure. Our findings not only shed light on specific GMT impacts in the Danube Lowland but also offer valuable insights for landscape management across diverse regions facing similar megatrends. By understanding these complex interactions, we can develop informed strategies to navigate the challenges and opportunities presented by a globalized world, promoting sustainable landscapes for the future.

Ochrana prírody Slovenska/EkológiaVol. 43(2)
Institute of Landscape Ecology of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 32%
Land Use and Ecosystem Services
0.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.