Phase III IUCRC at Purdue University: Center for Advanced Forestry Systems (CAFS)

高级林业系统中心(CAFS)成立于2007年，旨在应对木制品行业、土地所有者和国家林地管理者面临的挑战。在过去十年中，在CAFS下合作的7个大学站点(缅因州大学、北卡罗来纳州立大学、俄勒冈州立大学、佐治亚大学、普渡大学、爱达荷大学、华盛顿大学)成功地为森林遗传学、立地操作和生长与产量建模领域的科学合作提供了所需的结构和资源。随着CAFS进入第三阶段，重点将转向解决21世纪的技术挑战，研究问题将针对多个空间和时间尺度(包括分子、细胞、个体树木、林分和生态系统水平)。森林提供了地球上大部分的氧气，清除和储存了大量的大气二氧化碳，为世界上许多植物、动物和微生物提供了栖息地，是生物能源、生物燃料和生物材料的原料，也是经济机会的来源。CAF就维持健康森林的广泛技术能力进行的区域和国家研究，重点是决策支持工具和遥感，将通过有针对性的、应用的和协作的研究来解决问题，从而支持美国林业。先进林业系统中心(CAFS)汇集了行业和机构的科学家和从业者以及大学科学家，以解决我国人工林和天然林面临的问题。CAFS第三阶段跨学科研究方法将通过在多个时间和空间尺度上解决问题，并通过确定超越传统树种、地区和学科边界的根本解决方案，来提高美国林产品行业的竞争力。在第三阶段，CAFS将侧重于精确森林管理、森林遗传学、关键决策支持工具和遥感研究。CAFS科学家和业界之间的技术转让将促进无人机(UAV)和光探测和测距(LiDAR)等技术的采用，这些技术正在迅速改变测量、监测和管理森林的方式。来自代表性不足和传统群体的CAFS研究生将在林业科学中独树一帜，因为他们在多个范围内应用解决问题和跨学科的技能。健康的森林对世界的生态、社会和经济健康至关重要；木材是一种主要的经济商品，是建筑的原材料，也是生物能源、生物燃料和生物材料的原料；270万个工作岗位依赖森林，工资总额超过1100亿美元。中国林业基金会作为林业相关研发的领导者，将直接造福于国家森林经济。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Center for Advanced Forestry Systems (CAFS) was established in 2007 to address challenges facing the wood products industry, landowners, and managers of the nation's forestland. Over the past decade, the 7 university sites (University of Maine [lead], North Carolina State University, Oregon State University, University of Georgia, Purdue University, University of Idaho, University of Washington) that collaborate under CAFS have successfully provided the structure and resources needed for scientific collaboration in the areas of forest genetics, site manipulation, and growth & yield modeling. As CAFS moves into Phase III, focus will shift to address the technological challenges of the 21st century, with research questions aimed at multiple spatial and temporal scales (including molecular, cellular, individual-tree, stand, and ecosystem levels). Forests provide a major part of the Earth's oxygen, remove and store a substantial amount of atmospheric CO2, provide habitats for much of the world's plants, animals, and microorganisms, serve as feedstock for bioenergy, biofuels, and biomaterials, and are a source of economic opportunity. CAFS regional and national research on a wide range of technological capabilities to sustain healthy forests, with an emphasis on decision-support tools and remote sensing, will support the US forest industry by solving problems with targeted, applied, and collaborative research. The Center for Advanced Forestry Systems (CAFS) brings together industry and agency scientists and practitioners and university scientists to solve problems facing our nation's planted and natural forests. CAFS Phase III interdisciplinary research approach will enhance the competitiveness of the U.S. forest products industries by solving problems at multiple temporal and spatial scales, and by determining fundamental solutions that transcend traditional tree species, regional, and disciplinary boundaries. During Phase III, CAFS will focus on precision forest management, forest genetics, key decision-support tools, and remote sensing research. Technology transfer between CAFS scientists and industry will facilitate the adoption of technologies such as unmanned aerial vehicles (UAVs) and Light Detection and Ranging (LiDAR), which are rapidly changing how forests are measured, monitored, and managed. CAFS graduate students, recruited from underrepresented and traditional groups, will be unique in the forestry sciences because of their applied problem-solving and interdisciplinary skills across multiple scales. Healthy forests are vital to the world's ecological, social, and economic health; wood is a major economic commodity that serves as the raw material for building and as a feedstock for bioenergy, biofuels, and biomaterials; and 2.7+ million jobs depend on forests, representing a payroll of over $110 billion. CAFS, as the leader for R&D relevant to the forest industry, will directly benefit the national forest economy.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.