Integrating measures of grassland function using Remote Sensing

草地提供重要的全球生态系统服务，对干扰和入侵敏感，并且容易迅速功能崩溃。至关重要的是，草地生态系统是碳汇或碳源，这主要取决于围绕种植和放牧的管理做法。近几十年来，由于强烈的人类活动和气候变化，世界各地的草原都在退化，这种退化不仅威胁到生态系统，而且对生态系统服务产生负面影响。来自退化的压力强调了理解、评估和监测草原生态系统的必要性。几十年来，研究一直使用遥感工具来确定草原生长和生产力的单独措施。这些包括叶面积指数，生物量，树冠高度和覆盖，结构异质性，燃烧和放牧的影响。虽然这种方法提高了我们对如何孤立地监测草原群落的具体要素的认识，但在评估草食动物和人类利用生态系统服务的群落影响方面继续取得进展的一个障碍是全面评估草原的脉管、非脉管、生物和非生物特征。现有的非光合植被（NPV）和生物土壤结皮（BSC）导致光学草地遥感数据的不确定性，并缺乏有效的方法量化NPV和BSC，阻碍了草地综合评价。此外，净现值是决定草食动物在冬季的承载力（HCC）的关键，然而，这是一个研究不足的领域遥感。因此，使下一个重要的进展，在大规模的草地生态系统监测和保护利用遥感工具，我建议把重点放在BSC和净现值，并将其与已建立的光谱关系。这将为通过承载能力估计在区域规模、多季测量、监测和保护方面取得巨大进展打开大门。该计划将解决三个关键的研究差距（1）评估总的影响，净现值，BSC，和裸露的土壤估计草地生产力;（2）开发一种方法，定量估计净现值生物量和BSC覆盖使用遥感在混合草原;（3）整合净现值到时空显式HCC估计使用遥感。这项研究的结果也将有助于了解碳封存（影响气候变化），草原生态和草原水文。

Grasslands provide vital global ecosystem services, are sensitive to disturbance and invasion, and prone to rapid functional collapse. Critically, grassland ecosystems are carbon sinks or sources depending upon management practices largely surrounding cropping and grazing. Grasslands worldwide have been degraded in recent decades due to intense human activity and climate change and this degradation not only threatens ecosystems but negatively affects ecosystem services. The pressures from degradation emphasize the need to understand, evaluate, and monitor grassland ecosystems. For decades, studies have used remote sensing tools to determine solitary measures of grassland growth and productivity. These include leaf area index, biomass, canopy height and cover, structural heterogeneity, and burn and grazing effects. While this approach has advanced our understanding of how to monitor specific elements of the grassland community in isolation, a barrier to continued progress in assessing community effects of herbivory and human use for ecosystem services is a comprehensive assessment of vascular, non-vascular, biotic and abiotic features of grasslands. A comprehensive grassland assessment is hindered by uncertainties of optical grassland remote sensing resulting from existing non-photosynthetic vegetation (NPV) and biological soil crust (BSC), and constrained by lack of an effective approach to quantify NPV and BSC. In addition, NPV is critical for determining herbivore carrying capacity (HCC) in winter; however, it is an understudied field for remote sensing. Thus, to make the next important advance in large scale grassland ecosystem monitoring and conservation using remote sensing tools, I propose to focus on BSC and NPV and integrate this with established spectral relationships. This will open the door to large advances in regional scale, multi-season measurement, monitoring and conservation through carrying capacity estimation. The proposed program will address three critical research gaps by (1) evaluating the total effect of NPV, BSC, and bare soil on estimating grassland productivity; (2) developing an approach for quantitatively estimating NPV biomass and BSC cover using a remote sensing in mixed grasslands; and (3) integrating NPV into spatiotemporally explicit HCC estimation using remote sensing. The results of this research will also contribute to an understanding of carbon sequestration (affecting climate change), grassland ecology, and grassland hydrology.