> ## Content Index
> Fetch the complete content index at: https://intelligence.wildlandseco.com/llms.txt
> Use this file to discover other available public pages before exploring further.

# A very accurate ecological model was predicting space far better than year-to-year change
- URL: https://intelligence.wildlandseco.com/2026-10-01-rsei-spatial-temporal-predictability/
- Published: 2026-10-01T13:53:31.000Z
- Updated: 2026-10-01T13:53:31.000Z
- Description: China’s RSEI model reached weighted R² of 0.9712, but variance decomposition showed 97.39% of the signal was between pixels and only 2.61% was within-pixel interannual variability.
- Author: Benjamin Worlund
- Tags: RSEI, interpretable machine learning, ecological monitoring, Methods, Land, Climate, #ecological-intelligence, #brief-2026-10-01, #global-radar, #peer-reviewed

Evidence

Peer-reviewed

Geography

China

System

National remote-sensing ecological condition

## WHAT THE EVIDENCE SAYS

Researchers analyzed the Remote Sensing Ecological Index across China from 2002–2024 and built one-year-ahead interpretable machine-learning models with spatial and temporal holdouts. XGBoost achieved weighted R² of 0.9712 and RMSE of 0.0262, 13.67% better than a persistence baseline. Yet 97.39% of total variance was between-pixel spatial difference and only 2.61% reflected within-pixel year-to-year change; the factors associated with spatial patterns also differed from those associated with temporal variation.

## WHY IT MATTERS / OUR READ

Headline predictive accuracy can hide what is actually being predicted. For change detection and adaptive management, a model that distinguishes persistent spatial structure from interannual dynamics is more informative than one high R² treated as evidence of temporal foresight.

## CAVEATS / UNCERTAINTY

RSEI is a composite remote-sensing index rather than a direct biodiversity or ecosystem-function measure. Associations identified by SHAP are not causal, and national-scale predictability does not guarantee local decision performance.

## SOURCE

Scientific Reports — primary study  
[View original evidence ↗](https://doi.org/10.1038/s41598-026-72438-6?ref=intelligence.wildlandseco.com)

From the Morning Brief · 2026-10-01

[Read the full Morning Brief →](https://intelligence.wildlandseco.com/morning-brief-2026-10-01/)