Literature DB >> 23995622

Separating temperature from other factors in phenological measurements.

Mark D Schwartz1, Jonathan M Hanes, Liang Liang.   

Abstract

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.

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Year:  2013        PMID: 23995622     DOI: 10.1007/s00484-013-0723-2

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


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