Recultivation of abandoned agricultural lands in Ukraine: Patterns and drivers

Smaliychuk, Anatoliy; Müller, Daniel; Prishchepov, Alexander V.; Levers, Christian; Kruhlov, Ivan; Kuemmerle, Tobias

doi:10.1016/j.gloenvcha.2016.02.009

Cited by 90 publications

(62 citation statements)

References 48 publications

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“…We used a subtractive model for visualization, where the primary factors are illustrated with a pure color and the overlapping areas of influence are depicted by the intersection of colors. Although the studies have discussed the impact of climatic variation on land surface changes [33,55,56], very few of them have focused on the impact of environmental factors on land surface trends in Ukraine as opposed to management and land tenure factors [1][2][3][4][5][6][7][8]. Our results show that the changes in land surface can be partially explained by the combination of thermal and water conditions.…”

Section: Factors Of Land Surface Dynamics In Ukrainementioning

confidence: 75%

“…The reversal trend indicating trend change from increase to decrease stated the decline of ecosystem functioning. We suggest that these types of changes can be associated with the large socioeconomic disturbances followed by the collapse of the Soviet Union and associated processes of land abandonment after 1991 and land re-cultivation after the 2000s [6,7].…”

Section: Trends Of Ndvi Seriesmentioning

confidence: 94%

“…Generally, the interpretation of these trends is challenging as the trend shifts can be explained by several factors [47]. The reversal trend can be attributed to long-term increasing human pressures [48], particularly the cultivation of abandoned croplands, which was also observed by Smaliychuk et al [7]. Another abundant category of change is the increasing trend with an abrupt negative change, which can be related to the extreme events such as drought.…”

Section: Trends Of Ndvi Seriesmentioning

confidence: 94%

“…The third generation GIMMS NDVI is a 15-day Maximum Value Composite that was acquired from seven different NOAA satellites (7,9,11,14,16,17,18), which have been processed using an adaptive Empirical Mode Decomposition. NDVI3g is appropriate for long-term studies of land surface trends in vegetation, seasonality and coupling between climate variability and vegetation over the last three decades [31,32].…”

Section: Normalized Difference Vegetation Indexmentioning

confidence: 99%

“…In addition, the scale compatibility was another issue, as the datasets might be not representative for an 8 km grid [53]. To overcome this, we compared our results with the results of the previous studies [1,[4][5][6][7][8][9] and investigated the validity of the results by local experts. …”

Section: Trends Of Ndvi Seriesmentioning

confidence: 99%

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Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

et al. 2016

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Ukraine has experienced immense environmental and institutional changes during the last three decades. We have conducted this study to analyze important land surface dynamics and to assess processes underlying the changes. This research was conducted in two consecutive steps. To analyze monotonic changes we first applied a Mann-Kendall trend analysis of the Normalized Difference Vegetation Index (NDVI3g) time series. Gradual and abrupt changes were studied by fitting a seasonal trend model and detecting the breakpoints. Secondly, essential environmental factors were used to quantify their possible relationships with land surface changes. These factors included soil moisture as well as gridded air temperature and precipitation data. This was done using partial rank correlation analysis based on annually aggregated time-series. Our results demonstrate that positive NDVI trends characterize approximately one-third of Ukraine's land surface, located in the northern and western areas of the country. Negative trends occurred less frequently, covering less than 2% of the area and are distributed irregularly across the country. Monotonic trends were rarely found; shifting trends were identified with a greater frequency. Trend shifts were seen to occur with an increased frequency following the period of the 2000s. We determined that land surface dynamics and climate variability are functionally interdependent; however, the relative influence of the drivers varies in different locations. Among the factors analyzed, the air temperature variable explains the largest portion of NDVI variability. High air temperature/NDVI correlation coefficients (r = 0.36´0.77) are observed over the entire country. The soil moisture content is of significant influence in the eastern portion of Ukraine (r = 0.68); precipitation (r = 0.65) was most influential in the central regions of the country. These results increase our understanding of ecosystem responses to climatic changes and anthropogenic activities.

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Section: Factors Of Land Surface Dynamics In Ukrainementioning

confidence: 75%

Section: Trends Of Ndvi Seriesmentioning

confidence: 94%

Section: Trends Of Ndvi Seriesmentioning

confidence: 94%

Section: Normalized Difference Vegetation Indexmentioning

confidence: 99%

Section: Trends Of Ndvi Seriesmentioning

confidence: 99%

See 3 more Smart Citations

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

et al. 2016

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The role of knowledge in supporting the revitalisation of traditional landscape governance through social innovation in Slovakia

et al. 2022

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In this paper, we determine the role of knowledge in the development and consolidation of social innovation (SI) on the revitalisation of traditional farming in marginalised rural settings. We seek to address the following questions: (i) how the co‐production of knowledge in SI initiatives for the revitalisation of traditional farming might influence its development path, and (ii) how the networking of local and external actors accelerates knowledge co‐production and triggers the reconfiguration of social practices towards sustainability transformation. To answer these questions, we applied mixed‐method approach by investigating the example of SI initiative (the case of Vlkolínec UNESCO site in Slovakia). We conducted a focus group, semi‐structured and structured interviews, historical analysis and social network analysis with the actors involved in the SI. Based on the empirical results we revealed how mix of local and external knowledge and knowledge co‐production can enhance the development of SI through the networking of numerous local stakeholders, particularly science and policy representatives. This knowledge sharing and knowledge co‐production strengthened the development path of the SI in seeking to initiate effective measures for local people to return to traditional small‐scale farming, supporting traditional crafts, creating new green jobs and conditions for improving the quality of life for local people, and new services for sustainable tourism. Our results highlight the importance of external knowledge in the expansion of bonding social capital, and the establishment of a regional knowledge network of local and external actors to trigger SI in rural areas. The analyses reveal that multi‐actor networks that support knowledge exchange play an important role in SI development paths.

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Multiple trajectories of grassland fragmentation, degradation, and recovery in Russia's steppes

et al. 2021

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Over the 20th century, the Eurasian steppes underwent drastic land-cover changes.Much progress was made studying cropland expansion and the post-1990 (i.e., post-Soviet) agricultural land abandonment in Eurasia. However, the alteration of steppe landscapes may include other disturbances, such as oil and gas development, formal and informal roads and garbage dumps, which were not systematically documented.Considering the example of the steppe Orenburg Province in Russia, we reconstructed agricultural land-cover change dynamics using Landsat and Sentinel-2 imagery from 1990 to 2018. Furthermore, we used very high-resolution imagery and assessed the patterns and determinants of other steppe landscape anthropogenic disturbances. Our study showed that, despite steppe recovery due to widespread cropland abandonment from 1990 to 2018, the steppes, including the recovered steppe patches, underwent fragmentation due to informal roads, oil and gas development, shrub encroachment, garbage dumps and quarries, as well as abandonment of settlements and buildings. Only 6.4% of the sampled 7859 1Â1 km blocks in 2018 showing grassland extent had no documented disturbances. The mapped disturbances occurred primarily near settlements and roads, while some disturbances occurred in remote areas. Given the accessibility of steppes, our study calls for a urgent need to systematically document alternatives to agricultural land uses in the steppes of Eurasia and other parts of the global grassland biome.

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Recultivation of abandoned agricultural lands in Ukraine: Patterns and drivers

Cited by 90 publications

References 48 publications

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

The role of knowledge in supporting the revitalisation of traditional landscape governance through social innovation in Slovakia

Multiple trajectories of grassland fragmentation, degradation, and recovery in Russia's steppes

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