# Modelling asynchrony in phenology considering a dynamic representation of meteorological variables

## TL;DR

This paper introduces new methods to study how climate change affects the timing of biological events across species and ecosystems.

## Contribution

The study introduces novel interaction indices that incorporate meteorological variables to quantify phenological synchrony and asynchrony.

## Key findings

- New indices identified asynchronies within trophic levels based on phenological events.
- The relative sliding time window analysis helps identify critical meteorological time windows preceding phenological events.
- The method combines citizen science and remote sensing data to explore species interactions.

## Abstract

Shifts in the timing of phenological events across many taxa and ecosystems are a result of climate change. Within a trophic network, phenological mismatches between interlinked species can have negative impacts for biodiversity, ecosystems, and the trophic network. Here we developed interaction indices that quantify the level of synchrony and asynchrony among groups of species in three interlinked trophic levels, as well as accounting for a dynamic representation of meteorology. Insect first flight, vegetation green-up and arrival of migrant birds were the phenological indicators, obtained from a combination of spatially and temporally explicit species observations from citizen science programmes and remote sensing platforms (i.e., Landsat). To determine phenological shifts in interlinked taxa we created and applied several phenological indices of synchrony-asynchrony, combining information from the phenological events and critical time windows of meteorological variables. To demonstrate our method of incorporating a meteorological component in our new interaction index, we implemented the relative sliding time window analysis, a stepwise regression model, to identify critical time windows preceding the phenological events on a yearly basis. The new indices of phenological change identified several asynchronies within trophic levels, allowing exploration of potential interactions based on synchrony among interlinked species. Our novel index of synchrony-asynchrony including a meteorological dimension could be highly informative and should open new pathways for studying synchrony among species and interaction networks.