{
  "id": 13009589,
  "title": "Forest-weighted causal correlation: A scalable framework for causal inference in ecological time series",
  "url": "https://urgent.news/2026/10/08/forest-weighted-causal-correlation-a-scalable-framework-for-causal",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-08T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.01.756118v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "1. Detecting causal relationships from ecological time series remains challenging because community dynamics are often nonlinear, high-dimensional, noisy, and strongly synchronized. These characteristics can reduce the reliability of existing causal inference methods and complicate the identification of ecological interactions in complex natural systems. 2. I introduce Forest-weighted Causal…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}