CAREER: Scaling-up effects of biodiversity on ecosystem productivity: from local communities to landscapes

许多动植物物种正被逼灭绝。生物多样性的丧失可能会减少人们从生态系统中获得的好处。其中一些效益与植物直接相关，包括在草原上生产牲畜饲料和在森林中生产木材。在了解生物多样性丧失的后果方面取得了一些进展。但量化物种丧失如何影响大面积生态系统仍然具有挑战性。这项研究建立了新的实验，以扩大植物生产力和生物多样性的知识。该项目的主要进展是研究不同空间尺度上生产力和生物多样性之间的联系机制。数据将通过雪松溪长期生态研究网站公开提供。结果将被纳入雪松溪的K-12教育和社区参与计划。这些项目每年为10，500多名K-12学生和游客提供服务。这项研究还将有助于了解团队的多样性如何提高学习和生产力。这项研究将测试对生态系统生产力的预测。生产力取决于当地植物多样性和物种在小空间尺度上的相互作用。然而，在更大的尺度上，其他因素，如扩散和物种分类可能更重要。在这些更大的尺度上，重要的是开发新的技术来测量生物多样性，例如使用高光谱图像和激光雷达进行遥感。本研究将使用三种方法调查生产力对生物多样性的小规模依赖性。首先，扩散对草原植物群落生物多样性和生产力的影响将进行实验测试。第二，遥感技术将用于量化生物多样性如何影响从地方到景观尺度的生产力变化。第三，优势物种的作用将在几种生境类型中进行实验测试，包括草地，稀树草原，落叶林，针叶林。该假设将被测试，优势植物物种最佳排序跨异质景观。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Many species of plants and animals are being driven extinct. This loss of biodiversity is likely reducing the benefits that people obtain from ecosystems. Some of these benefits are directly related to plants, including the production of livestock forage in grasslands and wood in forests. There has been some progress in understanding the consequences of biodiversity loss. But it remains challenging to quantify how species loss affects ecosystems over large areas. This study establishes new experiments to expand knowledge of plant productivity and biodiversity. The key advance of this project is to study the mechanisms linking productivity and biodiversity at different spatial scales. Data will be made publicly available through the Cedar Creek Long Term Ecological Research website. Results will be incorporated into Cedar Creek's K-12 education and community engagement programs. These programs serve more than 10,500 K-12 students and visitors each year. The study will also help understand how the diversity of teams can enhance learning and productivity.This study will test predictions about ecosystem productivity. Productivity depends on local plant diversity and species interactions at small spatial scales. However, at larger scales, additional factors such as dispersal and species sorting are likely more important. At these larger scales, it is important to develop new techniques to measure biodiversity such as remote sensing using hyperspectral imagery and LiDAR. This study will investigate the landscape-scale dependence of productivity on biodiversity using three approaches. First, the impact of dispersal on biodiversity and productivity in grassland plant communities will be experimentally tested. Second, remote sensing techniques will be used to quantify how biodiversity effects on productivity change from local to landscape scales. Third, the role of dominant species will be experimentally tested across several habitat types, including grassland, savanna, deciduous forest, coniferous forest. The hypothesis will be tested that dominant plant species are optimally sorted across heterogeneous landscapes. This would create positive effects of landscape diversity on productivity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.