The species-area relationship (SAR) is one of the most investigated patterns in ecology and conservation biology, yet there is no study testing how different levels of urbanization influence its shape. Here we tested the impact of urbanization on avian SARs along a rural-urban gradient using the breeding birds of Rome (Central Italy). We divided the city into 360 cells of 1 km². Each cell was classified as rural, suburban or urban using the proportion of impervious surface calculated from remote sensing data. For each of these three landscape categories, we constructed a SAR as a species accumulation curve (Gleason function) using bird species distribution data. SAR intercepts (i.e. the number of species per unit area) decreased from rural to urban areas, which indicates that urbanization depressed the number of species, reflecting the loss of specialized species strictly associated with natural habitats. The slope was highest for the rural curve, indicating that natural landscapes have the highest turnover due to their higher habitat heterogeneity. A higher slope for the urban cells, compared to the suburban ones, can be explained by the presence of green spaces embedded in the built-up matrix which host different avian communities. Previous studies that compared whole cities with natural areas failed to find differences in the respective SARs. Our study, which constructed SARs for different levels of urbanization, indicated significant changes in the SARs along the rural-urban gradient. Further analyses in other cities and taxa will be useful to test how general are our findings.

物种-面积关系（SAR）是生态学和保护生物学中研究最多的模式之一，但尚无研究测试不同水平的城市化如何影响其形状。在这里，我们使用罗马（意大利中部）的繁殖鸟类，测试了城市化对沿农村-城市梯度的鸟类SAR的影响。我们将城市分为1 km ^2的360个单元。使用根据遥感数据计算得出的不透水表面的比例，将每个单元划分为农村，郊区或城市。对于这三个景观类别中的每一个，我们都使用鸟类物种分布数据将SAR构建为物种累积曲线（格里森函数）。SAR截获量（即每单位面积的物种数量）从农村到城市减少，这表明城市化进程抑制了物种数量，这反映了与自然栖息地严格相关的专业物种的流失。农村曲线的斜率最高，表明自然景观由于栖息地的异质性较高而具有最高的周转率。与郊区相比，城市小区的坡度更高，可以用内置矩阵中嵌入的绿色空间来解释，这些绿色空间承载着不同的鸟类群落。先前将整个城市与自然区域进行比较的研究未能发现各自的特区之间存在差异。我们的研究构建了针对不同城市化水平的SAR，表明SAR沿城乡梯度发生了显着变化。在其他城市和分类单元中进行进一步的分析将有助于检验我们的发现有多普遍。