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Can spatial data substitute temporal data in phenological modelling? A survey using birch flowering.

Susanne Jochner¹, Amelia Caffarra, Annette Menzel

¹Department of Ecology and Ecosystem Management, Ecoclimatology, Technische Universität München, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany.

Tree Physiology

|October 31, 2013

Summary

This summary is machine-generated.

Phenological responses of birch trees to warming vary between spatial and long-term studies. Spatially calibrated models may not accurately predict long-term phenological data, highlighting the need to consider study-specific factors.

Keywords:

Betula pendula Roth DORMPHOT Munich chilling linear model space-for-time substitution temperature urbanization gradient

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Area of Science:

Ecology
Phenology
Climate Change Research

Background:

Assessing phenological responses to global warming is crucial.
Spatial gradients, like urbanization, offer insights alongside long-term data analysis.
Birch (Betula pendula Roth) phenology serves as a case study for these assessments.

Purpose of the Study:

To compare phenological responses of birch to temperature variations across space and time.
To evaluate the predictive accuracy of spatially calibrated models for long-term phenological data.
To determine if time-for-space substitution is appropriate for phenological modeling.

Main Methods:

Calibration and testing of linear regression and DORMPHOT models.
Utilizing phenological and temperature data from an urbanization gradient (Munich, Ingolstadt, 2010-2011).
Analysis of long-term meteorological data (1991-2010) from the German Meteorological Service.

Main Results:

The process-based DORMPHOT model outperformed linear regression models.
Forcing and chilling sums, along with photoperiod, were identified as critical factors in the DORMPHOT model.
Models calibrated on spatial data predicted spatial data well but were less accurate for long-term data.
Temperature response rates differed significantly between spatial (-4.4 days °C⁻¹) and long-term (-1.9 days °C⁻¹) data.

Conclusions:

Time-for-space substitution in phenological studies may not always be reliable.
Generalizing findings across different study methods, spatial scales, and temporal scopes requires caution.
Methodological, spatial, and temporal peculiarities of studies must be considered for accurate interpretation.