A glossary for biometeorology.

Here we present, for the first time, a glossary of biometeorological terms. The glossary aims to address the need for a reliable source of biometeorological definitions, thereby facilitating communication and mutual understanding in this rapidly expanding field. A total of 171 terms are defined, with reference to 234 citations. It is anticipated that the glossary will be revisited in coming years, updating terms and adding new terms, as appropriate. The glossary is intended to provide a useful resource to the biometeorology community, and to this end, readers are encouraged to contact the lead author to suggest additional terms for inclusion in later versions of the glossary as a result of new and emerging developments in the field.

Separating temperature from other factors in phenological measurements.

Phenological observations offer a simple and effective way to measure climate change effects on the biosphere. While some species in northern mixed forests show a highly sensitive site preference to microenvironmental differences (i.e., the species is present in certain areas and absent in others), others with a more plastic environmental response (e.g., Acer saccharum, sugar maple) allow provisional separation of the universal "background" phenological variation caused by in situ (possibly biological/genetic) variation from the microclimatic gradients in air temperature. Moran's I tests for spatial autocorrelation among the phenological data showed significant (α ≤ 0.05) clustering across the study area, but random patterns within the microclimates themselves, with isolated exceptions. In other words, the presence of microclimates throughout the study area generally results in spatial autocorrelation because they impact the overall phenological development of sugar maple trees. However, within each microclimate (where temperature conditions are relatively uniform) there is little or no spatial autocorrelation because phenological differences are due largely to randomly distributed in situ factors. The phenological responses from 2008 and 2009 for two sugar maple phenological stages showed the relationship between air temperature degree-hour departure and phenological change ranged from 0.5 to 1.2 days earlier for each additional 100 degree-hours. Further, the standard deviations of phenological event dates within individual microclimates (for specific events and years) ranged from 2.6 to 3.8 days. Thus, that range of days is inferred to be the "background" phenological variation caused by factors other than air temperature variations, such as genetic differences between individuals.

Spring leaf phenology and the diurnal temperature range in a temperate maple forest.

Spring leaf phenology in temperate climates is intricately related to numerous aspects of the lower atmosphere [e.g., surface energy balance, carbon flux, humidity, the diurnal temperature range (DTR)]. To further develop and improve the accuracy of ecosystem and climate models, additional investigations of the specific nature of the relationships between spring leaf phenology and various ecosystem and climate processes are required in different environments. This study used visual observations of maple leaf phenology, below-canopy light intensities, and micrometeorological data collected during the spring seasons of 2008, 2009, and 2010 to examine the potential influence of leaf phenology on a seasonal transition in the trend of the DTR. The timing of a reversal in the DTR trend occurred near the time when the leaves were unfolding and expanding. The results suggest that the spring decline in the DTR can be attributed primarily to the effect of canopy closure on daily maximum temperature. These findings improve our understanding of the relationship between leaf phenology and the diurnal temperature range in temperate maple forests during the spring. They also demonstrate the necessity of incorporating accurate phenological data into ecosystem and climate models and warrant a careful examination of the extent to which canopy phenology is currently incorporated into existing models.