Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model

Verburg, Peter H.; Overmars, Koen P.

doi:10.1007/s10980-009-9355-7

Cited by 675 publications

(506 citation statements)

References 73 publications

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“…This assumption was often used in land-use modelling to identify areas that are likely to become abandoned in the coming years (Verburg and others 2006;Lesschen and others 2007;Verburg and Overmars 2009). The followed approach generally consisted of estimating the statistical likelihood for the occurrence of agricultural activity based on a set of factors such as soil type, slope, and population density.…”

Section: Introductionmentioning

confidence: 99%

Abandonment and Expansion of Arable Land in Europe

2011

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Abandonment of arable land is often assumed to happen mostly in marginal areas where the conditions for arable cultivation are relatively unfavorable, whereas arable expansion is expected to occur mostly in areas with favorable conditions. This assumption, used in many land-use change forecasts, was never properly tested, mainly because the relatively short period of full-coverage land-use inventories did not allow a systematic analysis of the phenomena. With the recent release of CORINE 2006 this has changed. In this article, we explore the typical locations of abandonment and expansion of arable land in Europe during the period 1990-2006 by means of logistic regressions. More specifically, we test whether or not locations of abandonment and expansion can be inferred from the location characteristics of arable land in 1990. If the above assumption holds, this should be the case. We demonstrate that although arable expansion indeed happens in locations that resemble the bulk of arable land in 1990 (the presumably favorable locations), arable abandonment does not necessarily happen in locations that resemble the bulk of uncultivated land (that is, the presumably unfavorable locations). In other words, the assumption does not hold. Particularly, areas close to the road network were found to be associated with both high abandonment rates and high expansion rates, which suggest that abandonment is not limited to areas that are marginal in terms of agricultural production.

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Section: Introductionmentioning

confidence: 99%

Abandonment and Expansion of Arable Land in Europe

2011

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“…The changes in national land use claims mentioned above are spatially allocated using the Dyna-CLUE model based on dynamic simulation of competition between land uses (Verburg and Overmars 2009). Spatial allocation rules can be specified based on empirical analysis, user-specified decision rules, and neighborhood characteristics.…”

Section: Methodsmentioning

confidence: 99%

“…Spatial allocation rules can be specified based on empirical analysis, user-specified decision rules, and neighborhood characteristics. A detailed description of the Dyna-CLUE model is given by Verburg and Overmars (2009). The actual allocation accounts for constraints defined by the model user based on the processes and constraints relevant to the scenarios and characteristics of land use types (Verburg and Overmars 2009).…”

Section: Methodsmentioning

confidence: 99%

“…A detailed description of the Dyna-CLUE model is given by Verburg and Overmars (2009). The actual allocation accounts for constraints defined by the model user based on the processes and constraints relevant to the scenarios and characteristics of land use types (Verburg and Overmars 2009). The settings and data inputs can be classified into four categories: (1) land use requirements, (2) location suitability, (3) conversion rules, and (4) spatial policies and restrictions.…”

Section: Methodsmentioning

confidence: 99%

“…Unfortunately, they failed to estimate the spatial pattern of land use change and ESVs in the future, which may provide useful information for land use planning and the enhancement of ESVs. The CLUE model, a dynamic model to simulate the spatial pattern of land use change, has been successfully used across countries and even continents (Jiang et al 2015;Verburg and Overmars 2009;Zheng et al 2015). It helps explore future land use patterns.…”

Section: Introductionmentioning

confidence: 99%

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Potential impact of land use change on ecosystem services in China

Wang

Sun

2016

Environ Monit Assess

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Land use change can greatly alter spatial pattern and overall ecosystem service values (ESV). The goal of this study was to explore the likely effects of land use change on ESV in China. In this paper, the spatially explicit land use changes across China from 2010 to 2020 under the 2000s trend scenario and the planning scenario were projected using the Dyna-CLUE model. The ESV evaluation method was improved by adjusting the ESV coefficients using biomass data to reduce the generalization error of proxy-based method. The results revealed that between 2010 and 2020, total ESV increased by 1798 and 2215 billion RMB a −1 under the 2000s trend scenario and the planning scenario, respectively. The spatial pattern of ESV in 2010 and 2020 presented a logical geographic distribution. The areas with ESV of 50,000 RMB ha −1 a −1 and higher occurred primarily in northeastern and southern China, while the areas with ESV of 5000 RMB ha −1 a −1 and lower were mainly located in northwestern China. The spatial differences between the two scenarios were insignificant except that the increase of ESV in southwestern China was more prominent in the planning scenario than that in the 2000s trend scenario, while the total ESV in 2020 under the planning scenario was larger than that in the 2000s trend scenario. The increase of ESV occurred mainly in northeastern, southern, and southeastern China due to forest growth and woodland expansion in 2020 compared with 2010. The results of this study can provide useful information for the public and land managers to consider.

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Increased influence of nitrogen limitation on CO₂ emissions from future land use and land use change

Meiyappan

House

2015

Global Biogeochemical Cycles

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In the latest projections of future greenhouse gas emissions for the Intergovernmental Panel on Climate Change (IPCC), few Earth System Models included the effect of nitrogen limitation, a key process limiting forest regrowth. Few included forest management (wood harvest). We estimate the impacts of nitrogen limitation on the CO 2 emissions from land use and land use change (LULUC), including wood harvest, for the period 1900-2100. We use a land surface model that includes a fully coupled carbon and nitrogen cycle and accounts for forest regrowth processes following agricultural abandonment and wood harvest. Future projections are based on the four Representation Concentration Pathways used in the IPCC Fifth Assessment Report, and we account for uncertainty in future climate for each scenario based on ensembles of climate model outputs. Results show that excluding nitrogen limitation will underestimate global LULUC emissions by 34-52 PgC (20-30%) during the 20th century (range across three different historical LULUC reconstructions) and by 128-187 PgC (90-150%) during the 21st century (range across the four IPCC scenarios). The full range for estimated LULUC emissions during the 21st century including climate model uncertainty is 91 to 227 PgC (with nitrogen limitation included). The underestimation increases with time because (1) projected annual wood harvest rates from forests summed over the 21st century are 380-1080% higher compared to those of the 20th century, resulting in more regrowing secondary forests; (2) nitrogen limitation reduces the CO 2 fertilization effect on net primary production of regrowing secondary forests following wood harvest and agricultural abandonment; and (3) nitrogen limitation effect is aggravated by the gradual loss of soil nitrogen from LULUC disturbance. Our study implies that (1) nitrogen limitation of CO 2 uptake is substantial and sensitive to nitrogen inputs; (2) if LULUC emissions are larger than previously estimated in studies without nitrogen limitation, then meeting the same climate mitigation target would require an equivalent additional reduction of fossil fuel emissions; (3) the effectiveness of land-based mitigation strategies will critically depend on the interactions between nutrient limitations and secondary forests resulting from LULUC; and (4) it is important for terrestrial biosphere models to consider nitrogen constraint in estimates of the strength of future land carbon uptake.

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Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model

Cited by 675 publications

References 73 publications

Abandonment and Expansion of Arable Land in Europe

Abandonment and Expansion of Arable Land in Europe

Potential impact of land use change on ecosystem services in China

Increased influence of nitrogen limitation on CO₂ emissions from future land use and land use change

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Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model

Cited by 675 publications

References 73 publications

Abandonment and Expansion of Arable Land in Europe

Abandonment and Expansion of Arable Land in Europe

Potential impact of land use change on ecosystem services in China

Increased influence of nitrogen limitation on CO2 emissions from future land use and land use change

Contact Info

Product

Resources

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Increased influence of nitrogen limitation on CO₂ emissions from future land use and land use change