R package for managing cafriplots network (and other inventories from Central Africa)
# CafriplotsR
> R package for managing and exploring the Central African forest plot database cafriplot network
## Overview
`CafriplotsR` provides tools for querying a PostgreSQL database containing forest inventories
data from Tropical Africa.
The package offers functions and shiny apps for (1) managing individual tree measurements on
which either taxa or stem level traits _sensus largo_ measurements (or observations) can be
aggregated, (2) standardizing taxonomic information en enrich with taxa level traits.
The advantage of this package is allow managing inventories, traits and observations under
the same taxonomic backbone, facilitating data integration, reproductibility in data analysis and
manipulation, data reusability.
**Key features:**
- Query plot data, individual tree measurements, and ecological features
- Access and aggregate species-level traits _sensus largo_
- Shiny app for standardize and correct your own list of taxonomic names
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**Version française disponible ici / French version available here**
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## Why CafriplotsR?
### The Challenge
Many researchers inventory woody vegetation in Central African forests (CAF), targeting diverse objectives: dynamics (mortality and growth), floristic and functional diversity, resource assessment and management, effects of both historical and contemporary disturbances, fauna-flora interactions, and more.
However, these initiatives and the research groups conducting them suffer from **insufficient visibility**:
- **Within the regional community**: Limited visibility among scientists and managers working on these forests restricts collaboration opportunities, experience sharing, protocol harmonization, and identification of complementarities in data and expertise.
- **At the international level**: This leads to the frequent claim that "we know almost nothing about Congo Basin forests." While there are indeed knowledge gaps compared to other major tropical forest blocks, asserting that our underst …