PS 38-97 - Phenology observations collected by citizen scientists directly support science and natural resource management

Wednesday, August 9, 2017
Exhibit Hall, Oregon Convention Center
Theresa M. Crimmins, National Coordinating Office, USA National Phenology Network, Tucson, AZ

The USA National Phenology Network (USA-NPN; serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns, climate, and environmental change. Data collected by citizen and professional scientists through Nature’s Notebook -- a national-scale, multi-taxa phenology observation program – are freely available in several formats for ready use by scientists and managers. Here we describe recent outcomes that have resulted from successful engagement with citizen scientists, with a focus on robust scientific products and results that would not have been possible without a coordinated national effort.


Since 2009 nearly 9,000 Nature’s Notebook participants have contributed over 9 million observation records of plants and animals across the United States. The USA-NPN also offers daily maps and short-term forecasts of accumulated growing degree days (AGDD) and AGDD anomalies, the start of spring as estimated via the Extended Spring Indices, Spring Index anomalies, and more as raster and image files. These observational data, derived products, and maps are being used in a wide range of management applications and research studies.

 This poster will highlight several recent studies and applications that leverage these data and data products. The data collected via Nature’s Notebook have been used in the past year to optimize herbicide treatment for managing invasive plants, to validate greenness estimates from remotely sensed imagery, to establish the triggers to leaf-out in key species, and more. Spring Index maps produced by the USA-NPN have recently been used to document that spring is arriving earlier in the majority of U.S. National Parks than in previous decades, to track the remarkably early progression of the 2017 spring across the continent, and to develop predictive models of leaf-out in several species.