New USA-NPN Data products, Phenology Week, protocol updates, and more

Dear USA-NPN,

Oh my, what a spring it has been! If you are in the East, you never really saw much winter, and if you're in the West, things have been way behind schedule. We are excited that many news outlets took advantage of our Spring Index maps this year to illustrate this "tale of two springs," including the TODAY Show, The Wall Street Journal, USA Today, and many more. The Washington Post created a really cool interactive tool where you can look up where you live.

In addition, be sure to check out Samantha's interview on the In Defense of Plants podcast, Erin on the In This Climate podcast, Alyssa on Yale Climate Connections, and Ellen on Maine Public Radio! I also was very fortunate to join Dr. David Inouye (University of Maryland emeritus) on Science Friday, what a delight!

We also celebrated Phenology Week -- a virtual celebration of the seasonal cycles of plants and animals -- the first week of spring. Check out the webinar recordings, daily emails, Local Phenology Program shout-outs, and more on the Phenology Week page, and stay tuned for an even bigger event next year!

And finally, our 2022 Annual Report is here! See highlights from last year, including new research by Dr. Lin Meng and coauthors on the impact of artificial light on phenology and by Dr. Dan Katz and colleagues on promising results using Nature's Notebook flowering data to inform pollen forecasts! We also highlight 2021 PhenoChampions, the Tree Spotters, based at Arnold Arboretum, as well as collaborations around Indigenous data sovereignty with Great Lakes Indian Fish and Wildlife Commission.

It's been a fantastic first few months, we are excited for more pheno-fun in the remainder of 2023!

Warmly,

What's new at the USA National Phenology Network

Updates to USA-NPN protocols published

Since the USA-NPN phenology monitoring protocols were published (Denny et al. 2014), we have made refinements to reduce confusion in the phenophase definitions, added new taxonomic groups, and expanded protocols to more fully capture certain life cycle stages. In a new publication, we describe changes that have been made to the original protocols. Going forward, the current version of the protocols will be maintained in the University of Arizona Research Data Repository.

Read the updated protocols publication »

Lessons learned in knowledge coproduction

Several USA-NPN staff and colleagues are authors on a new paper that reflects on our experiences in knowledge coproduction, in which both creators and users of information work together to produce actionable science. We found that who is at the table and how involved and invested they are is key to success. We offer suggestions that may help other scientists seeking to support decision-making.

Read the article »

More than 100 species added to Nature's Notebook

Each winter, we work to develop protocols for species requested to be added to Nature's Notebook in the previous year. This spring, we added 94 plants, nine insects (including five fireflies!), and three birds, bringing the total number of species available for monitoring to 1,756.

Explore the plant and animals to observe »

Data and Data Products

BEST-based Spring Index layers updated through 2021

Spring Leaf and Bloom Index layers calculated using the Berkeley Earth Surface Temperature data product are now available 1880-2021. These layers, at 1 degree resolution, can be accessed using USA-NPN's geo web services or downloaded using the Geoserver Request Builder.

Learn more »

Enhanced Emerald Ash Borer Pheno Forecast

In collaboration with partners at Oregon State University, we recently released an enhanced forecast of activity in emerald ash borer. We now offer forecasts of both egg laying and adult emergence. The forecasts encompass the entire year, representing our first long-lead forecast product.

A companion learning module, available at learning.usanpn.org, covers the basics of identifying and observing emerald ash borer phenology.

See the new Emerald Ash Borer Pheno Forecast »

See all USA-NPN Pheno Forecasts »

Red brome Pheno Forecast is live!

In a collaboration with the US Geological Survey, we also recently launched a Pheno Forecast indicating when red brome (Bromus rubens) flowers and senesces. This information can support grazing rotations as well as estimating wildfire risk.

We also offer a one-time reporting form for both red brome and cheatgrass (B. tectorum) leaf, flower, and fruit status. Records reported through this form will be used to validate and improve forecasts for both species.

See the red brome Pheno Forecasts »

Red brome and cheatgrass one-time report form »

Research Spotlight

Closing the loop with "falling leaves"

A new study focuses on the creation of litter – the patterns by which trees contribute to the rich layer of decomposing material that is the foundation of the forest. A better understanding of litter creation helps fill out our understanding of the carbon cycle. With this work we are learning that your observations of fruit and leaf fall have more potential than we realized.

Opportunities

Datasets for macrosystems research

The Macrosystems Ecology For All Research Coordination Network (MEFA RCN) is a diverse and welcoming community for faculty in teaching-focused positions to gain the training necessary to become full participants in macrosystems science. At their upcoming event July 25-27, four macrosystems ecologists will share their projects and details about useful datasets, engage in thinking about what types of datasets may be most appropriate for your research topics of interest, and learn all about the MEFA RCN and upcoming events!

Learn more and register »

Lilac-based lab exercise...and broader opportunity

Jonathan Auerbach, co-lead of the Cherry Blossom Prediction Competition, recently shared a data science exercise focused on predicting the timing of flowering in lilacs. The host of the exercise, Real World Data Science, invites related examples using data science to predict bloom dates.

See the lilac flowering data science exercise »

Learn more about RWDS »