Long-term monitoring of natural resources is imperative for increasing the understanding of ecosystem processes, services, and how to manage those ecosystems to maintain or improve function. Challenges with using these data may occur because methods of monitoring changed over time, multiple organizations collect and manage data differently, and monetary resources fluctuate, affecting many aspects of data. Because many species respond to changes in habitat conditions and predator-prey relationships across different spatial scales that span management boundaries, greater efforts for collaborating are essential. We demonstrate the challenges and methods for standardizing greater sage-grouse (Centrocercus urophasianus) long-term monitoring data across the species range in the western United States to inform population modeling needs identified by the Western Association of Fish and Wildlife Agencies. We used automated and repeatable methods of standardizing data via custom open-source software (grsg_lekdb) to improve the scientific integrity of future sage-grouse population assessments within and among states. Data standardization included reconciling uses of different terminology and expunging unusable data, resulting in the removal of 26% of data records due to database insertion errors and modifications to >1 million values to correct formatting and typing errors. Our approaches maximized the inclusion of usable data and identified data that could inform detection probabilities, population trends, and monitoring guidelines. Using sage-grouse databases as an example, we identified the importance of data management and how quality assurance and quality control measures can improve the usefulness of these data for future research needs. Our methods of using informatics and concluding recommendations can support similar endeavors of flora and fauna monitoring programs, whether those efforts are to use existing data or support new monitoring programs.

必须对自然资源进行长期监测，以增进对生态系统过程，服务以及如何管理这些生态系统以维持或改善功能的了解。使用这些数据可能会遇到挑战，因为监视的方法随时间而改变，多个组织收集和管理数据的方式不同，货币资源也会波动，从而影响数据的许多方面。由于许多物种对跨越管理边界的不同空间尺度上的栖息地条件和食肉动物与猎物之间的关系变化做出反应，因此必须加大合作力度。我们证明了标准化更大的鼠尾草（Centrocerercus urophasianus的挑战和方法）在美国西部整个物种范围内的长期监测数据，可为西部鱼类和野生动植物协会确定的种群建模需求提供信息。我们通过自定义的开源软件（grsg_lekdb）使用了自动化且可重复的标准化数据的方法），以提高各州内部和州之间未来的鼠尾草人口评估的科学完整性。数据标准化包括协调使用不同的术语和清除不可用的数据，由于数据库插入错误和对超过100万个值的修改以纠正格式和键入错误，导致删除了26％的数据记录。我们的方法最大程度地包含了可用数据和已识别数据，这些数据可以为检测概率，人口趋势和监测准则提供信息。以鼠尾草数据库为例，我们确定了数据管理的重要性以及质量保证和质量控制措施如何改善这些数据对未来研究需求的有用性。