Grasslands are among the most disturbed ecosystems globally. In the areas that remain, managers must balance practices such as mowing and burning that maintain natural systems while avoiding nesting periods for grassland birds. The authors of this study used information about nest survival from scientific literature as well as climate information and the USA-NPN’s Spring Bloom Index to develop models to predict the expected nest departure timing for 36 grassland bird species. This information can provide more localized information about nesting timing to better time management actions to avoid this critical period.

Ash trees on are the decline, and the main culprit is emerald ash borer (EAB), an invasive pest that has killed millions of ash trees in the United States. Knowing where and when to expect EAB emergence gives managers an advantage in controlling this pest, helping them to know when to take actions to control the pest. In this article, Barker et al. evaluated a model that predicts activity of EAB, taking into account both phenology and locations that have suitable climate for this pest. They used observations of EAB, including those from Nature’s Notebook, to test their model and found that it correctly estimated over 99% of presence records and predicted dates of adult EAB emergence within 7 days. This paper demonstrates how your observations can be used in the realm of invasive species, helping to improve management and ultimately conserve the unique ecosystems that we care about.

Pollen alerts give allergy sufferers the potential to reduce their exposure and the negative health impacts that result. An emerging data source for alerts is observations of flowering phenology, which can be highly correlated with the presence of airborne pollen. The authors of a new study compared data from National Allergy Bureau stations on daily pollen concentrations to flowering and pollen cone data from Nature’s Notebook. They found that the strength of the relationship between open flowers and pollen cones and pollen concentration varied by the type of plant, with the best agreement for Oaks (Quercus) and walnuts (Juglans). More specific data on the timing of open flowers and pollen release, like those that you collect in Nature’s Notebook, could lead to create real-time pollen alerts with local specificity.

The ability to predict spring plant phenology has implications for ecosystem services and forest management. The amount of heat that has accumulated at a given location, called growing degree days, is one method for prediction. The authors compared phenology data collected by the Tree Spotters (a Nature’s Notebook Local Phenology Program) at an urban arboretum, to those collected in a rural forest, Harvard Forest, and found that the urban site actually required fewer GDDs than trees at the rural site, possibly due to other phenological cues such as light and a higher amount of accumulated winter chill than predicted.

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.

The authors of a new study used over 4,000 Nature’s Notebook observations of oak (Quercus) trees in the eastern US to explore the relationship between flowering and air pollen. By finding a link between temperature and open flowers, they were able to predict peak in flowering timing at pollen monitoring stations. The peak flowering timing was strongly correlated with the observed peak airborne pollen at the stations. This article is the first to explore how volunteer-collected phenology data contributed to Nature’s Notebook can be used to support better predictions of the timing and severity of allergy season.