Multi-scale assessment and spatial modelling of agricultural land abandonment in a European peripheral region: Galicia (Spain), 1956–2004

Rico, Eduardo Corbelle; Crecente-Maseda, Rafael; Santé-Riveira, Inés

doi:10.1016/j.landusepol.2011.08.008

Cited by 102 publications

(72 citation statements)

References 31 publications

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“…The most obvious problem in regression analysis is the co-linearity among variables (Corbelle et al, 2012). Researchers are increasingly combining stochastic sampling, correlation coefficient testing, ridge regression and principal component analysis to solve the problem (Du et al, 2014;Zhang et al, 2012).…”

Section: Mathematical Statistical Methodsmentioning

confidence: 99%

Progress on quantitative assessment of the impacts of climate change and human activities on cropland change

2016

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Abstract:It is important to study the contributions of climate change and human activities to cropland changes in the fields of both climate change and land use change. Relationships between cropland changes and driving forces were qualitatively studied in most of the previous researches. However, the quantitative assessments of the contributions of climate change and human activities to cropland changes are needed to be explored for a better understanding of the dynamics of land use changes. We systematically reviewed the methods of identifying the contributions of climate change and human activities to cropland changes at quantitative aspects, including model analysis, mathematical statistical method, framework analysis, index assessment and difference comparison. Progress of the previous researches on quantitative evaluation of the contributions was introduced. Then we discussed four defects in the assessment of the contributions of climate change and human activities. For example, the methods were lack of comprehensiveness, and the data need to be more accurate and abundant. In addition, the scale was single and the explanations were biased. Moreover, we concluded a clue about quantitative approach to assess the contributions from synthetically aspect to specific driving forces. Finally, the solutions of the future researches on data, scale and explanation were proposed.

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Section: Mathematical Statistical Methodsmentioning

confidence: 99%

Progress on quantitative assessment of the impacts of climate change and human activities on cropland change

2016

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“…Certain researchers have used socio-ecological models to explore the drivers of farmland abandonment caused by collective behavior [25]. Due to the complexity and scale dependence of farmland abandonment, efforts to explore the drivers of farmland abandonment must consider the many socio-economic and natural factors [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Dynamic Mechanisms of Farmland Abandonment Based on a Spatially Explicit Economic Model for Environmental Sustainability: A Case Study in Jiangxi Province, China

2014

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Abstract:Farmland abandonment has important impacts on biodiversity and ecosystem recovery, as well as food security and rural sustainable development. Due to rapid urbanization and industrialization, farmland abandonment has become an increasingly important problem in many countries, particularly in China. To promote sustainable land-use management and environmental sustainability, it is important to understand the socioeconomic causes and spatial patterns of farmland abandonment. In this study, we explored the dynamic mechanisms of farmland abandonment in Jiangxi province of China using a spatially explicit economical model. The results show that the variables associated with the agricultural products yield are significantly correlated with farmland abandonment. The increasing opportunity cost of farming labor is the main factor in farmland abandonment in conjunction with a rural labor shortage due to rural-to-urban population migration and regional industrialization. Farmlands are more likely to be abandoned in areas located far from the villages and towns due to higher transportation costs. Additionally, farmers with more land but lower net income are more likely to abandon poor-quality farmland. Our results support the hypothesis that farmland abandonment takes place in locations in which the costs of cultivation are high and the potential crop yield is low. In addition, our study also demonstrates that a spatially explicit economic model is necessary to distinguish between the main driving forces of farmland abandonment. Policy implications are also provided for potential future policy decisions.

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“…In the study, these data have proven to be a most useful data set to identify types of agricultural land-use patterns and dynamics at the municipality level. Thus, IACS data represent an auspicious source for monitoring the patterns and dynamics in agriculture (Corbelle-Rico et al 2012). Since they are collected almost at a continental scale, IACS data could be the basis for analysing landuse change at sub-regional level for all of the area of the EU.…”

Section: Discussion Of Data Base and Methodological Approachmentioning

confidence: 99%

“…The results of this study revealed that the pattern and the dynamics of land use and land-use change vary at the spatial level of sub-regions. As a consequence, we recommend that the design of the political instruments should differ according to different sub-regions, a demand which is especially important for agri-environmental schemes (Corbelle-Rico et al 2012;Chiron et al 2013). These programmes aim at preserving nature as well as natural resources, ecosystem functioning and the cultural heritage.…”

Section: Discussion Of Types Of Agricultural Land Use Patterns and Dymentioning

confidence: 99%

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

Lüker-Jans

Simmering²,

Otte

2016

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European landscapes have featured considerable changes towards intensification and marginalisation. These major trends are expected to continue in the future. Besides, the cultivation of bioenergy crops has become an important factor in agricultural land use. A thorough understanding of land-use processes for management purposes is needed. In this study, the spatial and temporal pattern of agricultural land use and land-use change was classified at the scale of municipalities from 2005 to 2010. The study region was the German federal state Hesse. By using data of the Integrated Administration and Control System (IACS) of the European Union and with the help of k-means cluster analysis, five types of agricultural land-use patterns and dynamics (TLPDs) were detected. These TLPDs represent different sub-regions. Sub-regions with favourable physical conditions for cultivation are dominated by arable land. A progressive land-use change occurred by conversion of grassland to arable land. In sub-regions, where physical conditions are rather unfavourable, especially in mountainous areas, grassland is the predominant land use. But on the remaining arable land, there is a slight change in favour of maize. The knowledge of sub-regions with spatially and temporally different agricultural land use could be utilised to develop land management instruments like site-specific agri-environmental schemes.

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Multi-scale assessment and spatial modelling of agricultural land abandonment in a European peripheral region: Galicia (Spain), 1956–2004

Cited by 102 publications

References 31 publications

Progress on quantitative assessment of the impacts of climate change and human activities on cropland change

Progress on quantitative assessment of the impacts of climate change and human activities on cropland change

Exploring the Dynamic Mechanisms of Farmland Abandonment Based on a Spatially Explicit Economic Model for Environmental Sustainability: A Case Study in Jiangxi Province, China

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

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