Phenological Research Methods for Environmental and Climate Change Analysis /
As climate change continues to dominate the international environmental agenda, phenology – the study of the timing of recurring biological events – has received increasing research attention, leading to an emerging consensus that phenology can be viewed as an ‘early warning system’ for climate chan...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Dordrecht :
Springer Netherlands,
2010.
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- and Overview
- Global Framework for Data Collection – Data Bases, Data Availability, Future Networks, Online Databases
- Seasonality as a Core Business of Phenology
- Societal adaptation Options to Changes in Phenology
- The Influence of Sampling Method, Sample Size, and Frequency of Observations on Plant Phenological Patterns and Interpretation in Tropical Forest Trees
- Regression and Causality
- Combining Messy Phenological Time Series
- Phenology for Topoclimatological Surveys and Large-Scale Mapping
- Spatio-Temporal Statistical Methods for Modelling Land Surface Phenology
- Climatic Influences on the Flowering Phenology of Four Eucalypts: A GAMLSS Approach
- Bayesian Methods in Phenology
- Smoothing Methods
- Accounting for Correlated Error Structure Within Phenological Data: a Case Study of Trend Analysis of Snowdrop Flowering
- Modelling the Flowering of Four Eucalypt Species Using New Mixture Transition Distribution Models
- Life History Mediated Responses to Weather, Phenology and Large-Scale Population Patterns
- Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
- Wavelet Analysis of Flowering and Climatic Niche Identification
- Singular Spectrum Analysis: Climatic Niche Identification
- Herbarium Collections and Photographic Images: Alternative Data Sources for Phenological Research
- Meta-Analysis and Its Application in Phenological Research: a Review and New Statistical Approaches.