OPS 2-2
Challenges and opportunities in detecting phenological signals with digital imagery across diverse ecosystems
Morrisette et al., (2009) describe three ‘cross cutting challenges for phenological research’ in the 21st century as integrating observations across taxa; reconciling scales of observation and modeling phenological sequences to enable forecasting. We identify filling spatial gaps and capturing a greater diversity of ecosystems as an additional challenge, fundamental to meeting the other three. Each of these challenges may be addressed through the integration and standardization of data collection efforts across phenological observation networks which employ satellites and/or cameras. Here we describe the National Ecological Observatory Network’s (NEON) design to address these challenges and create new opportunities for phenological research.
Results/Conclusions
Standardizing hardware and protocols whenever possible will facilitate the integration of existing and future phenology networks and data sets for effective landscape coverage. By electing to adopt the hardware and protocols defined by the Phenocam Network, NEON sites will effectively expand the Phenocam Network and fill gaps in the continental United Sates. All 106 (i.e., 60 terrestrial and 46 aquatic) NEON sites will deploy StarDot digital cameras for automated near surface observations of phenology. Terrestrial NEON sites will have tower top cameras for observing phenology as well as cameras for capturing snow depth and ancillary images of understory phenology. NEON aquatic sites are designed to capture ice on and off but will also contribute phenological observations from riparian areas. New taxa will be incorporated as standardized observations are commissioned in previously unrepresented ecosystems.
Planned NEON sites are often co-located with Ameriflux tower sites, Long Term Ecological Research Sites (LTER), or existing Phenocam Network locations. Coupling phenological observations with mechanistic studies and observations of phenologically relevant ecological phenomena (e.g. temperature, precipitation, ecosystem exchange and root production and turnover) supplies the necessary range of parameters to develop, test, refine and forecast climate driven changes in phenology, and predict associated feedbacks to global climate.