Over the last twenty years I have coordinated Alberta Plantwatch and led a team of about 200 volunteer observers in observing the timing of spring plant development. This has produced one of the best seasonality data sets (most observations, longest duration) for recent decades for North America.

Why is such data useful?  Inter-annual variation in the timing of spring plant development is considered to be the simplest, most sensitive, and most cost-effective method to track the biotic response to climate change. But unlike other proxy data such as tree-rings or pollen layers, this annual occurrence of plant development must be recorded by humans. By engaging the public as ‘eyes of science’, this biological response data can be gathered over a large area. Observers benefit through increased awareness of Alberta’s biodiversity and climate change issues.

 

While small data subsets have been extracted in the past for research projects, this is the start of a comprehensive analysis of two decades of phenology data for 1987 to 2006. It is time to make the data sing!

 

Questions:

 

Are these data, gathered by volunteers, of sufficient quality? Can a diversity of citizens, most with no science training and who are not paid for this work, contribute valuable information? Do observers find and accurately recognize the program’s plant species and bloom stages?  

This first round of analysis reveals interesting insights into the quality of the data.

 

Phenology: biomonitor for climate change

 

Phenology, “the study of the seasonal timing of life cycle events” (Rathcke and Lacey 1985), includes a variety of events such as first bloom of plants, timing of butterfly emergence or bird migration. Plants are a common focus, since they stay in one spot and are easier to study.

The timing of spring flowering and leafing of perennial plants in temperate parts of the earth is largely driven by temperature. The field of phenology has seen a resurgence of interest in recent decades as a source of data illustrating how the vegetation responds to climate change (Parmesan and Yohe 2003, Root et al. 2003). 

 

Trends in these data help reveal the rate of climate warming and illustrate the species-specific responses to changes in temperature.  Over recent decades a lengthening of the growing season is evident in the phenological record, and also in remote sensing data, temperature data, and CO2 records (Menzel 2003).

 

Many researchers in North America have documented advances in timing of spring onset (Beaubien and Freeland 2000, Bradley et al. 1999, Schwartz and Reiter 2000).  A flex point in graphs of temperature and phenological data is common to many phenology studies, showing faster change to warmer temperatures and earlier development starting in the mid-1970s. (Penuelas and Filella 2001, Cayan et al. 2001).

 

Why track phenology?

 

Besides their usefulness for climate change studies, phenology datasets have many scientific, industrial, and societal applications. These include remote sensing validation, as well as predictions for decision-making in agriculture (timing of seeding, pest control, and harvest), human health (shifts in pollen seasons and allergies), biodiversity conservation, and wildlife management. In forestry, the data can be used for fire prediction, insect and disease control, and as input to carbon sequestration models. This data is essential for modeling of both forest growth (Rötzer et al. 2004) and the future distribution of tree species (Chuine and Beaubien 2001).