Context

While land use change is the main driver of biodiversity loss, most biodiversity assessments either ignore it or use a simple land cover representation. Land cover representations lack the representation of land use and landscape characteristics relevant to biodiversity modeling.

Objectives

We developed a comprehensive and high-resolution representation of European land systems on a 1-km² grid integrating important land use and landscape characteristics.

Methods

Combining the recent data on land cover and land use intensities, we applied an expert-based hierarchical classification approach and identified land systems that are common in Europe and meaningful for studying biodiversity. We tested the benefits of using this map as compared to land cover information to predict the distribution of bird species having different vulnerability to landscape and land use change.

Results

Next to landscapes dominated by one land cover, mosaic landscapes cover 14.5% of European terrestrial surface. When using the land system map, species distribution models demonstrate substantially higher predictive ability (up to 19% higher) as compared to models based on land cover maps. Our map consistently contributes more to the spatial distribution of the tested species than the use of land cover data (3.9 to 39.1% higher).

Conclusions

A land systems classification including essential aspects of landscape and land management into a consistent classification can improve upon traditional land cover maps in large-scale biodiversity assessment. The classification balances data availability at continental scale with vital information needs for various ecological studies.

中文翻译：

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新的欧洲土地系统表示法考虑了景观特征

语境

尽管土地使用变化是生物多样性丧失的主要驱动力，但大多数生物多样性评估要么忽略了它，要么使用简单的土地覆盖表述。土地覆盖表述缺乏与生物多样性建模有关的土地利用和景观特征的表述。

目标

我们在1 km ^2的网格上开发了欧洲陆地系统的全面高分辨率的视图，该网格整合了重要的土地利用和景观特征。

方法

结合最近有关土地覆盖和土地利用强度的数据，我们采用了基于专家的分层分类方法，并确定了欧洲常见的土地系统，对于研究生物多样性具有重要意义。与土地覆盖信息相比，我们测试了使用此地图的优势，以预测对景观和土地利用变化具有不同脆弱性的鸟类物种的分布。

结果

除了由一个土地覆盖物主导的景观之外，马赛克景观覆盖了欧洲陆地面积的14.5％。使用土地系统图时，与基于土地覆盖图的模型相比，物种分布模型显示出更高的预测能力（高出19％）。与使用土地覆被数据相比，我们的地图对试验物种的空间分布的贡献持续不断（提高3.9％至39.1％）。

结论

将土地景观和土地管理的基本方面纳入统一分类的土地系统分类可以在大规模生物多样性评估中改进传统的土地覆盖图。该分类使大陆规模的数据可用性与各种生态研究的重要信息需求之间取得了平衡。