NDLI: A Space-For-Time (SFT) Substitution Approach to Studying Historical Phenological Changes in Urban Environment

Content Provider	PubMed Central
Author	Alexander, Buyantuyev Xu, Pengyan Wu, Jianguo Piao, Shunji Wang, Dachuan
Editor	Chen, Han Yh
Copyright Year	2012
Abstract	Plant phenological records are crucial for predicting plant responses to global warming. However, many historical records are either short or replete with data gaps, which pose limitations and may lead to erroneous conclusions about the direction and magnitude of change. In addition to uninterrupted monitoring, missing observations may be substituted via modeling, experimentation, or gradient analysis. Here we have developed a space-for-time (SFT) substitution method that uses spatial phenology and temperature data to fill gaps in historical records. To do this, we combined historical data for several tree species from a single location with spatial data for the same species and used linear regression and Analysis of Covariance (ANCOVA) to build complementary spring phenology models and assess improvements achieved by the approach. SFT substitution allowed increasing the sample size and developing more robust phenology models for some of the species studied. Testing models with reduced historical data size revealed thresholds at which SFT improved historical trend estimation. We conclude that under certain circumstances both the robustness of models and accuracy of phenological trends can be enhanced although some limitations and assumptions still need to be resolved. There is considerable potential for exploring SFT analyses in phenology studies, especially those conducted in urban environments and those dealing with non-linearities in phenology modeling.
Related Links	http://dx.doi.org/10.1371/journal.pone.0051260
Starting Page	51260
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	12
Volume Number	7
Language	English
Publisher	Public Library of Science
Publisher Date	2012-12-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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