Modeling Future Land Use Development: A Lithuanian Case

Mozgeris, Gintautas; Juknelienė, Daiva

doi:10.3390/land10040360

Cited by 5 publications

(4 citation statements)

References 34 publications

(36 reference statements)

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“…To date, the main factors and drivers of land-use-related GHG emissions and removals in Lithuania are considered to be land-use changes due to political and economic factors. Land-use changes were induced by the restructuring of the agricultural sector after the restoration of independence, followed by support allocated for rural development after joining the EU, intensive afforestation of abandoned land or land not suitable for agriculture [31,32], strict governmental control of deforestation and preservation of domestic forest resources [33,34].…”

Section: Introductionmentioning

confidence: 99%

Impact of Land-Use Changes on Climate Change Mitigation Goals: The Case of Lithuania

Dagiliūtė,

Kazanavičiūtė

2024

Land

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The land-use, land-use change and forestry (LULUCF) sector is receiving increasing attention in climate change mitigation and greenhouse gas (GHG) emission offsetting. The sector itself and measures applied to mobilize this sector in order to tackle climate change are dominant in nationally determined contributions under the Paris Agreement as well as in national strategies, as in the case of Lithuania. Lithuania has set the goal of becoming a carbon-neutral country in 2050, reducing GHGs by 80% compared to 1990 and offsetting the remaining 20% through the LULUCF sector. Therefore, this paper aims at analyzing historical land-use changes in 1990–2021, as reported for the United Nations Framework Convention on Climate Change (UNFCCC) secretariat, and LULUCF’s potential to achieve climate change mitigation goals, taking into account different land-use change scenarios (business as usual, forest development, forest development + additional measures and forest land 40% + additional measures) for 2030 and 2050 in Lithuania. The scenarios are based on historical and potential future policy-based land-use changes. Projections of GHG emissions/removals for different scenarios are prepared according to the Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (2006) by the Intergovernmental Panel on Climate Change (IPCC). The results indicate that land-use changes over the period 1990–2021 remained rather stable, with some increases in forest area and grassland at the expense of cropland. The whole LULUCF sector acted as a carbon sink in most cases, forests being a key category for removal. However, reaching climate neutrality in 2050 might be challenging, as the goal to offset 20% of remaining GHG emission compared to 1990 through LULUCF would not be met in any of the scenarios analyzed, even the scenario of maximal forest-area development and additional measures. Considering the high historical GHG-removal fluctuations and the uncertainties of the sector itself, caution should be taken when relying on LULUCF’s potential to reach the set goals.

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Section: Introductionmentioning

confidence: 99%

Impact of Land-Use Changes on Climate Change Mitigation Goals: The Case of Lithuania

Dagiliūtė,

Kazanavičiūtė

2024

Land

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“…Most LUCC models, such as the Markov model and cellular automata model, focus more on the research of "land" than "human" in a human-land coupled system, as such that simulating the choices of direct land-use by decision-makers is challenging [14][15][16][17][18][19][20]. As such, it is impossible to analyze the impact of the macro policy and stakeholders' participation in land use decision-making behavior and its results.…”

Section: Introductionmentioning

confidence: 99%

Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China

Guo

Zhang

Cui

et al. 2022

Land

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Recent decades have witnessed increasing human disruption and the acceleration of fragile natural habitats, especially in coal mining areas in developing countries or regions, which will inevitably lead to sharp land use and cover change (LUCC). Most LUCC models focus more on the research of “land” than “human” in human-land coupled systems, while the simulation and prediction of LUCC involving stakeholders are still deficient. Aiming to reveal the shaping process of LUCC through the stakeholders’ participation, we conducted an in-depth interview in a typical coal mining area of Shanxi, China, and developed an agent-based model by quantifying the stakeholders’ land-use decision-making rules to simulate and predict land use change in different scenarios. The analysis illustrated that the stakeholders’ participation in different periods had shaped the land use pattern in the coal mine area. The area of cultivated land has decreased from 272.34 hm2 to 118.89 hm2, while industrial and mining land increased dramatically by 78.66 hm2 from 2012 to 2019. The attitude and willingness of farmers towards land use varied greatly and were affected by livelihood capital. Part-time farmers whose agricultural income only accounted for 20–80% of the total income were in favor of farmland requisition by coal mining enterprises compared to full-time farmers. We quantified the rules between the attributes of the stakeholders at the micro level and land use changes at the macro level and proposed the multi-agent simulation model, which was effective and verified by a fitting test where the overall accuracy of the Kappa coefficient was 0.83 and could be used to predict future LUCC in research areas by setting the decision parameters in specific scenarios. These outcomes provided a scientific reference for landscape simulation and the prediction of a human-land coupling system while promoting the effectiveness of spatial planning policies.

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“…Still, legal restrictions are linked with the afforestation of land that has relatively high productivity [36]. The modelling of the future development of land use in Lithuania revealed that carbon stocks in the land use, land-use change, and forestry (LULUCF) activities should increase mainly due to the accumulation of carbon in forests [37]. Therefore, increasing the area of forest land and grassland remains an important issue to achieve the set afforestation and agricultural targets contributing to greenhouse gas absorption in the next decade.…”

Section: Introductionmentioning

confidence: 99%

Soil Organic Carbon Stocks in Afforested Agricultural Land in Lithuanian Hemiboreal Forest Zone

Varnagirytė–Kabašinskiene

Žemaitis

Armolaitis

et al. 2021

Forests

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In the context of the specificity of soil organic carbon (SOC) storage in afforested land, nutrient-poor Arenosols and nutrient-rich Luvisols after afforestation with coniferous and deciduous tree species were studied in comparison to the same soils of croplands and grasslands. This study analysed the changes in SOC stock up to 30 years after afforestation of agricultural land in Lithuania, representing the cool temperate moist climate region of Europe. The SOC stocks were evaluated by applying the paired-site design. The mean mass and SOC stocks of the forest floor in afforested Arenosols increased more than in Luvisols. Almost twice as much forest floor mass was observed in coniferous than in deciduous stands 2–3 decades after afforestation. The mean bulk density of fine (<2 mm) soil in the 0–30 cm mineral topsoil layer of croplands was higher than in afforested sites and grasslands. The clear decreasing trend in mean bulk density due to forest stand age with the lowest values in the 21–30-year-old stands was found in afforested Luvisols. In contrast, the SOC concentrations in the 0–30 cm mineral topsoil layer, especially in Luvisols afforested with coniferous species, showed an increasing trend due to the influence of stand age. The mean SOC values in the 0–30 cm mineral topsoil layer of Arenosols and Luvisols during the 30 years after afforestation did not significantly differ from the adjacent croplands or grasslands. The mean SOC stock slightly increased with the forest stand age in Luvisols; however, the highest mean SOC stock was detected in the grasslands. In the Arenosols, there was higher SOC accumulation in the forest floor with increasing stand age than in the Luvisols, while the proportion of SOC stocks in mineral topsoil layers was similar and more comparable to grasslands. These findings suggest encouragement of afforestation of former agricultural land under the current climate and soil characteristics in the region, but the conversion of perennial grasslands to forest land should be done with caution.

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Modeling Future Land Use Development: A Lithuanian Case

Cited by 5 publications

References 34 publications

Impact of Land-Use Changes on Climate Change Mitigation Goals: The Case of Lithuania

Impact of Land-Use Changes on Climate Change Mitigation Goals: The Case of Lithuania

Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China

Soil Organic Carbon Stocks in Afforested Agricultural Land in Lithuanian Hemiboreal Forest Zone

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