Identifying hotspots for ecosystem restoration across heterogeneous tropical savannah-dominated regions.

There is high potential for ecosystem restoration across tropical savannah-dominated regions, but the benefits that could be gained from this restoration are rarely assessed. This study focuses on the Brazilian Cerrado, a highly species-rich savannah-dominated region, as an exemplar to review potential restoration benefits using three metrics: net biomass gains, plant species richness and ability to connect restored and native vegetation. Localized estimates of the most appropriate restoration vegetation type (grassland, savannah, woodland/forest) for pasturelands are produced. Carbon sequestration potential is significant for savannah and woodland/forest restoration in the seasonally dry tropics (net biomass gains of 58.2 ± 37.7 and 130.0 ± 69.4 Mg ha-1). Modelled restoration species richness gains were highest in the central and south-east of the Cerrado for savannahs and grasslands, and in the west and north-west for woodlands/forests. The potential to initiate restoration projects across the whole of the Cerrado is high and four hotspot areas are identified. We demonstrate that landscape restoration across all vegetation types within heterogeneous tropical savannah-dominated regions can maximize biodiversity and carbon gains. However, conservation of existing vegetation is essential to minimizing the cost and improving the chances of restoration success. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.

Indigenous and local communities can boost seed supply in the UN decade on ecosystem restoration.

The UN Decade of Ecosystem Restoration is poised to trigger the recovery of ecosystem services and transform structural injustices across the world in a way unparalleled in human history. The inclusion of diverse Indigenous and local communities to co-create robust native seed supply systems is the backbone to achieve the goals for the Decade. Here we show how community-based organizations have co-developed native seed supply strategies for landscape restoration from the bottom-up. We draw on the interconnections over two decades of seed networks in Brazil and the emerging Indigenous participation in native seed production in Australia. From an environmental justice perspective, we provide a participatory seed supply approach for local engagement, noting local geographical, social and cultural contexts. Meeting large-scale restoration goals requires the connection between local seed production and collaborative platforms to negotiate roles, rights and responsibilities between stakeholders. An enduring native seed supply must include a diversity of voices and autonomy of community groups that builds equitable participation in social, economic, and environmental benefits.

Mapping native and non-native vegetation in the Brazilian Cerrado using freely available satellite products.

Native vegetation across the Brazilian Cerrado is highly heterogeneous and biodiverse and provides important ecosystem services, including carbon and water balance regulation, however, land-use changes have been extensive. Conservation and restoration of native vegetation is essential and could be facilitated by detailed landcover maps. Here, across a large case study region in Goiás State, Brazil (1.1 Mha), we produced physiognomy level maps of native vegetation (n = 8) and other landcover types (n = 5). Seven different classification schemes using different combinations of input satellite imagery were used, with a Random Forest classifier and 2-stage approach implemented within Google Earth Engine. Overall classification accuracies ranged from 88.6-92.6% for native and non-native vegetation at the formation level (stage-1), and 70.7-77.9% for native vegetation at the physiognomy level (stage-2), across the seven different classifications schemes. The differences in classification accuracy resulting from varying the input imagery combination and quality control procedures used were small. However, a combination of seasonal Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (surface reflectance) imagery resulted in the most accurate classification at a spatial resolution of 20 m. Classification accuracies when using Landsat-8 imagery were marginally lower, but still reasonable. Quality control procedures that account for vegetation burning when selecting vegetation reference data may also improve classification accuracy for some native vegetation types. Detailed landcover maps, produced using freely available satellite imagery and upscalable techniques, will be important tools for understanding vegetation functioning at the landscape scale and for implementing restoration projects.