Exploring Nature: Datasets and Models for Analyzing Nature-Related Disclosures

TL;DR

This paper introduces datasets and classifiers for detecting corporate nature-related disclosures, focusing on water, forest, and biodiversity, to better understand economic interactions with nature.

Contribution

It provides the first large-scale datasets and models for analyzing corporate nature communication aligned with TNFD guidelines.

Findings

Nature communication is more common in hotspot areas.

Industries like agriculture and utilities show higher disclosure levels.

The approach enables large-scale assessment of corporate nature disclosures.

Abstract

Nature is an amorphous concept. Yet, it is essential for the planet's well-being to understand how the economy interacts with it. To address the growing demand for information on corporate nature disclosure, we provide datasets and classifiers to detect nature communication by companies. We ground our approach in the guidelines of the Taskforce on Nature-related Financial Disclosures (TNFD). Particularly, we focus on the specific dimensions of water, forest, and biodiversity. For each dimension, we create an expert-annotated dataset with 2,200 text samples and train classifier models. Furthermore, we show that nature communication is more prevalent in hotspot areas and directly effected industries like agriculture and utilities. Our approach is the first to respond to calls to assess corporate nature communication on a large scale.