The continued global biodiversity crisis necessitates the continuation and development of new well‐designed monitoring strategies and action plans with particular focus on under‐represented countries and regions. However, limited resources in terms of budget and availability of qualified field personnel can restrict the geographical coverage of monitoring efforts. Focusing monitoring efforts on a representative subset of species and locations can improve cost‐efficiency. Optimal performance of multi‐species indicators derived from such an approach requires objective methods for species selection and a sampling design that reduces inherent sampling bias caused by regional differences in habitat availability or accessibility. To explore the performance of a multi‐species indicator across different regions within a nation, we developed a multi‐species indicator (MSI) for farmland birds in Norway using objective niche‐based selection of species. We compare the performance of this indicator at national and regional scales (Central and East regions) in Norway, and between urban and rural sites within regions. The seven‐species indicator obtained from the species selection provided similar indicator values and trends for Norway and the Central and East regions, as well as for rural sites within the combined Central + East region. All trends were defined as showing moderate decline from 2007–2016. Urban sites within the combined Central + East region provided trend estimates that showed stronger decline than rural areas in the same region during the time span. Our results emphasize the need to control for sampling bias when structuring monitoring programmes such as a Breeding Bird Survey (BBS). This is especially important if limited resources restrict the geographical coverage of the monitoring scheme. We recommend that monitoring schemes follow a stratified random sampling design that represents both the availability of different land cover types and their distribution with regard to proximity to highly populated areas. If that is not possible, statistically weighting data from different regions or landscapes is likely to be necessary.

中文翻译：

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沿城乡梯度的非随机抽样可能会降低多物种农田鸟类指标及其趋势的可靠性

持续的全球生物多样性危机有必要继续和发展精心设计的新监测战略和行动计划，尤其要关注代表性不足的国家和地区。但是，在预算和合格的现场人员的可用性方面有限的资源可能会限制监视工作的地理覆盖范围。将监视工作集中在物种和位置的代表性子集上可以提高成本效率。通过这种方法得出的多物种指标的最佳性能需要客观的物种选择方法和抽样设计，以减少因栖息地可利用性或可及性的区域差异而引起的固有抽样偏差。要探索一个国家内不同地区的多物种指标的表现，我们使用基于生态位的客观选择来开发挪威农田鸟类的多物种指标（MSI）。我们比较了该指标在挪威的国家和地区范围（中部和东部地区）以及区域内城市和农村站点之间的表现。从物种选择中获得的七种指标为挪威，中部和东部地区以及中部和东部地区合并后的农村地区提供了相似的指标值和趋势。所有趋势均定义为显示从2007年至2016年适度下降。中东部地区结合起来的城市地区提供的趋势估计显示，在这段时间内，下降的幅度比该地区的农村地区大。我们的结果强调，在构建监测程序（如“繁殖鸟调查”（BBS））时，需要控制采样偏差。如果有限的资源限制了监视方案的地理覆盖范围，则这一点尤其重要。我们建议监测方案遵循分层随机抽样设计，该设计既代表不同土地覆被类型的可用性，又代表其在人口稠密地区附近的分布。如果不可能，则可能需要对来自不同区域或地貌的数据进行统计加权。我们建议监测方案遵循分层随机抽样设计，该设计既代表不同土地覆被类型的可用性，又代表其在人口稠密地区附近的分布。如果不可能，则可能需要对来自不同区域或地貌的数据进行统计加权。我们建议监测方案遵循分层随机抽样设计，该设计既代表不同土地覆被类型的可用性，又代表其在人口稠密地区附近的分布。如果不可能，则可能需要对来自不同区域或地貌的数据进行统计加权。