scientific-environmental-ecology

Integrate species distribution modeling with biodiversity indices and ordination from GBIF/OBIS data.

3|1|Updated Feb 11, 2026

Search Tags:#biodiversity #ecology #ordination #sdm #gbif #obis #niche-modeling

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-environmental-ecology

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-environmental-ecology
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-environmental-ecology
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-environmental-ecology

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides an end-to-end framework for ecological data analysis, enabling researchers to combine species distribution modeling, biodiversity metrics, and community-structure analyses in a unified workflow.

Core Features & Use Cases

Species distribution modeling (SDM) and niche modeling using GBIF/OBIS data and environmental layers
Biodiversity indices (alpha, beta, gamma) across sites
Community structure analyses (NMDS, CCA, RDA)
Conservation prioritization and spatial planning
Data integration across marine/terrestrial datasets
ToolUniverse integration for external data sources

Quick Start

Supply occurrence records and environmental layers to run the integrated ecological analytics pipeline.

Frequently Asked Questions about scientific-environmental-ecology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build species distribution models using GBIF and OBIS occurrence data?▼

Species distribution modeling integrates GBIF and OBIS occurrence records with environmental layers to assess habitat suitability and estimate niches across spatial scales. You supply the occurrence data and layers to run the modular ecological analytics pipeline.

What biodiversity indices can I calculate for community composition analysis?▼

Biodiversity indices include alpha, beta, and gamma diversity measures calculated across sites. Community structure analyses use multivariate ordination techniques like NMDS, CCA, and RDA to quantify ecological patterns and community composition.

Can I combine terrestrial and marine ecological datasets in one workflow?▼

Yes, the framework supports data integration across marine and terrestrial datasets. It unifies species distribution modeling, biodiversity metrics, and community-structure analyses within a single reproducible workflow for conservation prioritization.

What is the best way to run multivariate ordination for ecological data?▼

Multivariate ordination for ecological data is performed using NMDS, CCA, and RDA methods to identify community composition patterns. The integrated pipeline processes occurrence data and environmental layers to quantify these ecological structures.

Do I need environmental layers to estimate species richness and niche models?▼

Yes, environmental layers are required alongside occurrence records to perform niche modeling and habitat suitability assessment. The framework combines these inputs to estimate species richness and support spatial conservation prioritization.