The scarcity of knowledge about both biodiversity (Linnean shortfall) and the geographic distributions of species (Wallacean shortfall) makes it hard to conduct biomonitoring programs and studies that seek to explain biodiversity patterns. One way to overcome this difficulty consists in the utilization of data with a lower taxonomic resolution, an approach called taxonomic sufficiency or Higher Taxon Approach (HTA). The main aim of this study was to evaluate, through a systematic review and meta-analysis, whether the HTA is reliable. We also evaluated whether the strength of the HTA (i.e., the relationship between datasets at high and low taxonomic resolutions) depended on different factors such as taxonomic level (genus, family, order and class), ecosystem type (aquatic and terrestrial), biological group (e.g., invertebrates, vertebrates and plants), spatial extent and higher taxa to species richness ratio (φ). We found that the HTA was a reliable approach in revealing species richness and compositional patterns independently of biological groups and ecosystem types. As expected, the strength of the HTA in describing biodiversity patterns decreased as the taxonomic resolution decreased. The strength of the HTA increased with the spatial scale of the studies. The φ was the main predictor of the HTA. Therefore, the use of higher taxonomic level (e.g., genera) is a reliable approach to save time and resources in biomonitoring programs and differs in this regard from other approaches that have already been tested in other studies (e.g., biological surrogacy). While the high HTA efficacy do not replace refined species level information which is crucial for basic and applied ecological studies, we advocate the use of the HTA especially for biological groups with high φ and for biomonitoring programs targeting large spatial extents.

关于生物多样性（林南短缺）和物种地理分布（华莱士短缺）的知识匮乏，使得难以开展旨在解释生物多样性模式的生物监测计划和研究。克服此困难的一种方法是使用具有较低分类学分辨率的数据，这种方法称为分类学充分性或高级分类法（HTA）。这项研究的主要目的是通过系统的审查和荟萃分析，评估HTA是否可靠。我们还评估了HTA的强度（即，高和低分类学分辨率下的数据集之间的关系）是否取决于不同因素，例如分类学水平（属，科，序和类），生态系统类型（水生和陆地），生物学组（例如，无脊椎动物，脊椎动物和植物），空间范围和较高的分类单元对物种的丰富度比率（φ）。我们发现，HTA是揭示物种丰富度和组成模式的可靠方法，而与生物群体和生态系统类型无关。正如预期的那样，HTA在描述生物多样性模式方面的优势随着分类分辨率的降低而降低。HTA的强度随着研究的空间规模而增加。φ是HTA的主要预测因子。因此，使用较高的分类标准（例如属）是节省生物监测程序中时间和资源的可靠方法，并且在这方面与已经在其他研究中测试过的其他方法（例如生物替代）不同。