Mapping Atlantic rainforest degradation and regeneration history with indicator species using convolutional network.

Fabien H Wagner,Marisa G Fonseca,Emanuel Gloor,André L C Rochelle,Luiz E O C Aragão,Yuliya Tarabalka,Oliver L Phillips,Marcos P M Aidar,Alber Sanchez,Judi Hewitt

doi:10.1371/journal.pone.0229448

Abstract

The Atlantic rainforest of Brazil is one of the global terrestrial hotspots of biodiversity. Despite having undergone large scale deforestation, forest cover has shown signs of increases in the last decades. Here, to understand the degradation and regeneration history of Atlantic rainforest remnants near São Paulo, we combine a unique dataset of very high resolution images from Worldview-2 and Worldview-3 (0.5 and 0.3m spatial resolution, respectively), georeferenced aerial photographs from 1962 and use a deep learning method called U-net to map (i) the forest cover and changes and (ii) two pioneer tree species, Cecropia hololeuca and Tibouchina pulchra. For Tibouchina pulchra, all the individuals were mapped in February, when the trees undergo mass-flowering with purple and pink blossoms. Additionally, elevation data at 30m spatial resolution from NASA Shuttle Radar Topography Mission (SRTM) and annual mean climate variables (Terraclimate datasets at ∼ 4km of spatial resolution) were used to analyse the forest and species distributions. We found that natural forests are currently more frequently found on south-facing slopes, likely because of geomorphology and past land use, and that Tibouchina is restricted to the wetter part of the region (southern part), which annually receives at least 1600 mm of precipitation. Tibouchina pulchra was found to clearly indicate forest regeneration as almost all individuals were found within or adjacent to forests regrown after 1962. By contrast, Cecropia hololeuca was found to indicate older disturbed forests, with all individuals almost exclusively found in forest fragments already present in 1962. At the regional scale, using the dominance maps of both species, we show that at least 4.3% of the current region's natural forests have regrown after 1962 (Tibouchina dominated, ∼ 4757 ha) and that ∼ 9% of the old natural forests have experienced significant disturbance (Cecropia dominated).

Highlights

Brazil holds 20% of Earth’s biodiversity, and its third largest biome, the Atlantic rainforest, is a biodiversity hotspot and a global priority for conservation [1,2,3,4]
We describe for each Tibouchina pulchra and Cecropia hololeuca pixels if they were inside an old or new natural forest and their minimum distance to new and old natural forest, within a maximum distance threshold of 25 m and of 50 m, respectively
Recall was higher in natural forests than in plantations, thereby indicating a lower rate of false negatives

Summary

Introduction

Brazil holds 20% of Earth’s biodiversity, and its third largest biome, the Atlantic rainforest, is a biodiversity hotspot and a global priority for conservation [1,2,3,4]. Regional scale indicators to assess recovery stage, diversity or disturbance levels of the current natural forests are still underdeveloped, thereby adding uncertainty to the estimation of the ecosystem services and their value for conservation [12,13,14]. In this context, remote sensing is a key tool to monitor biodiversity, resources, and ecosystem services, as well as the human impact on natural ecosystems at a regional/biome scale [15,16,17,18]

Methods

Results

Discussion

Conclusion