OPUS: CRS--Experiments, Meta-analysis and Big Data in Advancing Ecological Understanding

科学依赖于理论和数据。数据提供了指导和检验理论的信息。理论和数据共同推动了我们对自然界的理解。生态数据曾经强调科学家个人的观察和受控环境实验，但发展到自然系统的实地实验，然后是多研究者研究和研究综合，最近又发展到“大数据”分析，即基于包括气候、地理、土地利用和生态数据在内的大型电子数据库的研究。实验是检验假设和理清潜在混杂因素的最严格的方法，但面临着挑战和限制。例如，在自然种群中进行的实验具有现实主义的巨大优势，但由于它们几乎总是在局部空间尺度上进行，因此受到限制。这个项目将考察在过去的50年里，个体实验如何给生态学带来不同的视角和理解，以及如何改变我们对自然界的理解。这项研究的更广泛影响将包括针对新生、研究生和专业人员的研讨会和培训、演讲以及YouTube上关于如何记录、保存、组织和使生态学中的科学数据可用和透明的视频。我们已经并将继续经历重点的重大转变，即我们如何收集用于理解自然世界的信息。我们还能通过单个研究人员进行的实验来回答重要的基本和应用问题吗？或者生态学是否最适合于多个研究人员的研究项目？在个人实验、大群体研究、荟萃分析和大型数据库分析中，问题是否有所不同？这项研究将检验五个假设，重点放在植物种群、群落和宏观生态上。H1：个体研究者野外实验在促进生态学理解方面的作用曾经是核心的，现在更加次要；H2：野外实验从1970年代中期到1990年代的高峰下降到现在；H3：使用“大数据”的观察性宏观生态观测研究在频率、资金、能见度和声望方面一致增加；H4：从1990年代末到现在，荟萃分析和研究综合的作用呈指数级增加；和H5：个人实验、大型群体实验、元分析和观测大数据分析的工作重点在空间规模、主题、提出的问题以及获得的见解和理解方面存在系统差异。该奖项反映了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。

Science relies on both theory and data. Data provide the information that guides and tests theory. Together, theory and data advance our understanding of the natural world. Ecological data once emphasized the observations and controlled environment experiments of individual scientists, but progressed to field experiments in natural systems, then to multi-investigator studies and research synthesis, and more recently, to the analysis of "big data," studies based on large electronic databases that include climate, geography, land use, and ecological data. Experiments are the most rigorous way to test hypotheses and disentangle potential confounding factors, but face challenges and limitations. For example, experiments in natural populations have the great advantage of realism, but are limited because they are almost always conducted at local spatial scales. This project will examine how individual experiments, the synthesis of data from many experiments using meta-analysis, and analyses of "big data" at large spatial scales, have brought different perspectives and understanding to ecology over the past 50 years, and changed our understanding of the natural world. Broader impacts of this research will include seminars and training for freshman, graduate students and professionals, presentations, and a YouTube video on how to record, save, organize, and make scientific data in ecology available and transparent.We have witnessed and will continue to experience a major shift in emphasis in how we gather information used to understand the natural world. Can we still answer important fundamental and applied questions through experiments carried out by individual researchers, or is ecology best situated within multi-investigator research programs? Are questions different in individual experiments, large group studies, meta-analyses and analysis of large databases? This study will examine five hypotheses, focusing on plant population, community and macro-ecology. H1: The role of individual investigator field experiments in advancing ecological understanding ecology, once central, is now more secondary; H2: Field experiments have declined from a peak from the mid-1970s to 1990s, to the present; H3: Observational macroecological observational studies using "big data" have concordantly increased in frequency, funding, visibility and prestige; H4: The role of meta-analysis and research synthesis has increased exponentially from the late 1990s to the present; and H5: The focus of work addressed by individual experiments, large group experiments, meta-analysis and the analysis of observational big data differ systematically in spatial scale, topics, questions asked, and insights and understanding gained.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.