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The "conflict-coordination" theoretical model of regional land use transitions put forward by Long (2022) offers a fresh perspective for understanding the process of regional land use and the decision-making dynamics involved. However, being a novel theory, empirical evidence supporting this theoretical model is currently lacking. Consequently, this paper aims to validate the theoretical model using the lower Yellow River basin in China as a case study, focusing on the interconversion between cropland and rural settlements. The findings reveal that the rural land use transitions primarily manifest as an initial conversion of cropland to rural settlements, followed gradually by the reverse conversion of rural settlements back to cropland. The conversion of cropland to rural settlements prior to 2015 are regarded as the land use conflict phase, resulting in conflicts between construction departments and cropland protection departments, and deviation from national cropland protection goals. The conversion of rural settlements to cropland between 2015 and 2020 is regarded as the land use conflict-coordination phase, which mitigated pressure on cropland protection and resolved conflicts between the above-mentioned departments. The land use conflict phase was driven by socio-economic factors such as urbanization and rural economic development, whereas the land use conflict-coordination phase was primarily driven by cropland protection policies. This paper effectively elucidates the "conflict-coordination" theoretical model of regional land use transitions and provides a framework for evaluating rural land management policies in China. [ABSTRACT FROM AUTHOR]

Dramatic land cover changes related to the accelerated urbanization process have led to habitat fragmentation and loss, resulting in biodiversity loss. Ecological Networks (ENs) have been seen as an effective solution for ecological conservation targeting habitat connectedness and ecosystem functions. The EN research is, however, generally depicted by current or historical landscape data, devoid of the potential future disturbances, which is detrimental to maintaining EN's stability and sustainability. This study combines the system dynamics (SD) model and patch-generating land use simulation (PLUS) to simulate land use patterns in Wuhan urban agglomeration (WUA), China. The simulated land use data were incorporated into EN modeling to assess the long-term dynamics of EN in WUA, considering two scenarios related to human activities and climate change. In parallel, a landscape graphs approach is used to estimate the spatial priority of EN for conservation in landscape dynamics. The results show that: (1) The grassland decreased from 2000 to 2020 and is expected to increase from 2020 to 2035. The area of construction land would reach its peak in 2035 while cultivated land would hit a low point. (2) Analysis of EN reveals habitat fragmentation and reduced connectivity from 2000 to 2020. From 2020 to 2035, an increase in EN connectivity is expected to be observed in the SSP5–8.5 scenario, while SSP2–4.5 is the reduced scenario. (3) Southern and eastern WUA exhibit high conservation priority. The hotspots of local landscape changes are mainly the corridors that traverse through human activity areas and the edges of core habitats, which is critical to conserving. (4) The impact of natural and socioeconomic factors on EN exhibits spatial heterogeneity. This paper provides new insights to protect habitats and biodiversity to mitigate the challenge of human activities and climate change. [Display omitted] • Scenario simulation evaluates the impacts of human and climate change on ecological network. • The SSP5-8.5 indicates an increase in connectivity of the ecological networks. • The impact of urban development on the ecological network varies depending on urban structures. • More emphasis should be focused on the hotspot areas where the local landscape changes. • A scenario of increased connectivity does not imply that it should be prioritized. [ABSTRACT FROM AUTHOR]

Land use and land cover change (LUCC) modeling is crucial to urban planning and policy making. A well-used and effective paradigm for LUCC is the ANN-CA model which employs an artificial neural network (ANN) to calculate a transition probability over each land cell from various driving factors, and then uses a cellular automaton (CA) to evolve all cells consecutively to update their land usage and coverage according to the estimated probability distribution. This paper focuses on the effect of delays or perturbations possibly taking place between land cells on the LUCC modeling. To this end, a new ANN-CA model is proposed which adopts an asynchronous communicating cellular automaton (ACCA), rather than the conventional synchronous CA. Especially, the ACCA allows every cell to communicate with its neighbors independently at random times via a specific protocol, which offers a natural way to include stochastic delays in exchanging the current land usages between cells. As a result, every change of a cell's land use in the ACCA may not affect its neighbors immediately, but is subject to delays that might play an important role in modeling the practical LUCC. Numerical analysis of the new model are carried out over three regions of Chongqing city, China with different scales: Yongchuan District, Sanjiao Town, and Huangguashan Village, and experimental results demonstrate that the proposed ANN-ACCA model can achieve a higher accuracy for LUCC simulation as compared to conventional ANN-CA models. [ABSTRACT FROM AUTHOR]