景观分配：随机生成器和统计推断
Landscape allocation: stochastic generators and statistical inference
摘要：
在农业景观中，耕作和半自然元素的组成和空间配置强烈影响物种动态，它们之间的相互作用和栖息地的连通性。为了使景观结构分析和场景生成，我们在这里开发的统计工具，真正的景观组成的几何元素，包括二维补丁，但也一维线性元素，如树篱。我们设计了生成随机模型，结合了多重网络表示和吉布斯能量项来表征土地利用类别的景观描述符的分布行为。我们为这类新的模型实现了Metropolis-Hastings，以采样具有参数控制的空间和时间模式的农业场景（例如，几何学、连通性、作物轮作）。基于伪像的推理允许通过统计和功能验证研究模型组件在真实景观中的相关性，后者通过比较观察到的景观和模拟景观之间常用的景观指标来实现。下Durance谷（法国）的次区域拟合模型表明随机分配的强烈偏差，他们现实地捕捉小规模的景观格局。总之，我们的统计建模方法提高了农业生态系统的结构和功能方面的理解，它使基于模拟的理论分析景观格局如何塑造生物和生态过程。
英文摘要：
In agricultural landscapes, the composition and spatial configuration of cultivated and semi-natural elements strongly impact species dynamics, their interactions and habitat connectivity. To allow for landscape structural analysis and scenario generation, we here develop statistical tools for real landscapes composed of geometric elements including 2D patches but also 1D linear elements such as hedges. We design generative stochastic models that combine a multiplex network representation and Gibbs energy terms to characterize the distributional behavior of landscape descriptors for land-use categories. We implement Metropolis-Hastings for this new class of models to sample agricultural scenarios featuring parameter-controlled spatial and temporal patterns (e.g., geometry, connectivity, crop-rotation). Pseudolikelihood-based inference allows studying the relevance of model components in real landscapes through statistical and functional validation, the latter achieved by comparing commonly used landscape metrics between observed and simulated landscapes. Models fitted to subregions of the Lower Durance Valley (France) indicate strong deviation from random allocation, and they realistically capture small-scale landscape patterns. In summary, our approach of statistical modeling improves the understanding of structural and functional aspects of agro-ecosystems, and it enables simulation-based theoretical analysis of how landscape patterns shape biological and ecological processes.
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