|Citizen Scientist Karen Murante collects|
MeadoWatch data on Mazama Ridge in 2013
NASA's grant program seeks to find useful ecological or natural resource management applications for its Earth observation products, in combination with biological observations by citizen scientists. The grant will fund a one-year feasibility study, which could be followed by three years of additional funding if the first year produces promising results.
In our case, the project is based on four premises:
- Snow disappearance can be forecast from MODIS Snow Cover imagery, captured by satellite, in combination with SNOTEL data collected at the Paradise weather station.
- Snow disappearance influences the timing of wildflower bloom. (Previous research by Elli Theobold, beginning in 2002, has shown a strong correlation between the two.)
- Quantifying wildflower "phenology" (the dates of budding, flowering, and setting seed) is feasible through Citizen Science.
- Natural resource management and conservation would be improved by a better understanding of the dates of snow disappearance and wildflower bloom.
|NASA imagery from January 2014|
(for a comparison with 2013, see the
Cliff Mass weather blog.)
Meanwhile, volunteer will continue to be a key component of the research. This summer, MeadoWatch volunteers will return to the Paradise trails to watch and document the flowers as they bud, bloom, and set seeds. These ground-based, human-gathered data will be combined with high tech satellite imagery to come up with new ways of understanding our world.
If you'd like to participate in the MeadoWatch program, visit the project website at https://sites.google.com/a/uw.edu/meadowatch/, or contact Anna Wilson, MeadoWatch coordinator, at firstname.lastname@example.org. You can also upload your own wildflower photos to the group's Flickr page at http://www.flickr.com/groups/meadowatch/.
Here is the original project proposal that won the NASA grant:
|Snow, Montane Wildflowers, and Citizen Scientists|
HilleRisLambers, Lundquist & Rochefort
The timing of key life events like reproduction (i.e. phenology) is tightly linked to climate. For example, alpine wildflowers emerge and flower within a few weeks of snow disappearance, and complete their life‐cycles before first frost in early autumn. Because annual variability in snow disappearance is large, the timing of seasonal wildflower displays also varies annually, influencing visitation and staffing needs within parks. Additionally, as climate change causes earlier snow disappearance, wildflowers that cannot shift their phenology to match this altered “climate window” may decline. Thus, resource managers and conservation biologists need the ability to seasonally forecast snow disappearance and wildflower phenology as well as monitor their long‐term annual trends to better conserve and manage high mountain wildflower meadows.
To address these issues, we propose to combine MODIS‐based images of snow covered area (SCA), citizen science observations and models to develop decision‐making tools at Mt. Rainier National Park (Washington). Specifically, we will develop and validate snow models driven by MODIS SCA and daily observations of temperature, precipitation and snow (from a SNOTEL climate station) that generate spatially explicit forecasts of snow disappearance date. Next, we will use date‐stamped photos of wildflowers from photo‐sharing websites to develop phenological forecasts driven by snow disappearance date. Phenological models will be validated with data from an existing citizen science program, which will be expanded in scope to meet monitoring goals. Finally, we will partner with the National Park Service to create a long‐term monitoring program of snow dynamics and wildflower phenology. Operationally, these estimates will 1) help managers plan where and when trail maintenance, conservation/restoration activities, and monitoring can occur, 2) allow visitors to better plan trips to view and photograph wildflowers, and eventually, 3) help resource managers identify the climatic and biological signs of climate change.