Vegetation timing and nutrient peaks

Context

Migratory herbivores and other Arctic species depend on seasonal plant growth. If peak plant quality shifts in time, animals may arrive too early or too late.

This project focused on estimating when vegetation reaches important growth stages and how those dates may change in the future.

Approach

I combined satellite vegetation data, reanalysis products, and CMIP6 projections to model seasonal plant development across the Arctic.

Part of the work involved linking different vegetation indicators, such as NDVI and LAI, so that present-day observations could be used to interpret future model output.

Key components

• Satellite data: vegetation signals from Arctic land surfaces.
• Climate data: reanalysis and CMIP6 projections for present and future conditions.
• Model fitting: statistical relationships between vegetation indicators.
• Timing metrics: dates of key seasonal growth stages and nutrient peaks.

Results

The project produced maps and scenario-based estimates of when vegetation reaches important seasonal thresholds.

It also showed how different datasets can be combined to track likely shifts in food timing across Arctic regions.

Why it matters

Plant timing is a key part of Arctic food webs. When plant growth shifts, the effects can move upward through herbivores, birds, and whole ecosystems.

This project helps connect climate change to food availability in a way that is easier to compare across species and regions.

Tools

Python, NDVI and LAI datasets, ERA5, CMIP6, spatial analysis, and statistical modelling.