CONTEXT

Mediterranean peri-urban regions have changed considerably in recent decades, leading to different farming system trajectories. The high level of heterogeneity and complexity of these areas are particularly challenging in terms of understanding the ongoing processes and their drivers, including the effects of spatial interactions, in order to make an initial assessment of the possible levers for territorial management.

OBJECTIVE

We aim to show a new modeling approach to assess the factors explaining farming system trajectories on Mediterranean peri-urban areas, including an analysis of the spillover from neighboring areas, which is often neglected in these kinds of methods. The model was tested in two urban regions, located in Pisa (Italy) and Avignon (France), leading to very different perspectives, given the differences in terms of farming systems and environmental characteristics. Our model also highlights the factors acting on peri-urban farming system trajectories.

METHODS

We first analyzed the farming systems characteristics and their trajectories, based on a land parcel identification system database and agricultural census. Then, we estimated explanatory factors at the farm level applying a spatially explicit model which takes into spatial autocorrelations into account: a Spatial Autoregressive Probit model.

RESULTS AND CONCLUSIONS

Our results provide new evidence supporting the hypothesis that peri-urban farming systems trajectories are influenced by other variables than the distance to the city center and the urbanization processes. Although urban sprawl characterizes medium-sized regions, this factor is not relevant on farming systems trajectories in the region of Pisa, where structural agro-pedoclimatic drivers contribute more significantly to the probability of change and, therefore, highlighting the greater stability of these farming systems. The region of Avignon reveals different aspects: a dense road infrastructure and favorable environmental conditions (availability of irrigation water during warm periods, adequate temperatures in winter, deep soils) increase the probability of intensification within the farming system.

SIGNIFICANCE

Our methodological approach, which is based on a spatial probit model, measures the effect of the spatial dependence of the dependent variables. In addition, the preliminary classification in terms of farming systems improves our understanding of the land trajectories. The results obtained provide new insights into the processes underway in Mediterranean peri-urban areas.

中文翻译：

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模拟地中海城郊地区农业系统轨迹的驱动因素：阿维尼翁（法国）和比萨（意大利）的两个案例研究

语境

近几十年来，地中海城市周边地区发生了很大变化，导致了不同的农业系统轨迹。这些地区的高度异质性和复杂性在理解正在进行的过程及其驱动因素方面尤其具有挑战性，包括空间相互作用的影响，以便对领土管理的可能杠杆进行初步评估。

客观的

我们的目标是展示一种新的建模方法来评估解释地中海城郊地区农业系统轨迹的因素，包括分析邻近地区的溢出效应，这在这些方法中经常被忽视。该模型在位于比萨（意大利）和阿维尼翁（法国）的两个城市地区进行了测试，鉴于农业系统和环境特征方面的差异，导致了截然不同的观点。我们的模型还强调了影响城郊农业系统轨迹的因素。

方法

我们首先基于地块识别系统数据库和农业普查分析了耕作系统特征及其轨迹。然后，我们应用一个空间显式模型估计农场层面的解释因素，该模型将空间自相关考虑在内：空间自回归概率模型。

结果和结论

我们的研究结果提供了新的证据来支持这样的假设，即城郊农业系统轨迹受到其他变量的影响，而不是到市中心的距离和城市化进程。尽管城市蔓延是中等规模地区的特征，但该因素与比萨地区的农业系统轨迹无关，结构性农业气候驱动因素对变化概率的贡献更大，因此突出了这些农业系统的更大稳定性. 阿维尼翁地区揭示了不同的方面：密集的道路基础设施和有利的环境条件（温暖时期灌溉水的可用性、冬季充足的温度、深厚的土壤）增加了农业系统内集约化的可能性。

意义

我们的方法论方法基于空间概率模型，测量因变量的空间依赖性的影响。此外，根据耕作系统的初步分类提高了我们对土地轨迹的理解。获得的结果为地中海城郊地区正在进行的进程提供了新的见解。