Minimizing biodiversity loss in the Brazilian Cerrado

Recent study proposes new approach to spatial prioritization in protected area conservation efforts

Banisteriopsis campestris
Banisteriopsis campestris observed in Brasília, Brazil by Douglas. Photo via iNaturalist (CC BY-NC 4.0)

Covering more than 2 million square kilometers and nearly a quarter of Brazil, the tropical ecoregion known as the Cerrado is a designated biodiversity hotspot—yet less than 10 per cent is protected. Scenic beauty and recreational value have a history of playing an important role in conservation planning, sometimes resulting in the protection of unproductive landscapes with steep slopes and infertile soil.

To avoid this and to improve spatial prioritization in protected areas with a limited budget, this study used GBIF-mediated occurrences to model plant distributions. Coupled with land-use models, these helped evaluate the impact of four simulated conservation scenarios: implemented now or sequentially—and—either focusing on maximizing species representation or conservation impact as defined by beneficial environmental outcomes arising from protection.

Their evaluation revealed little difference between the four scenarios in average species' range protected, however, focusing on conservation impact predicted vegetation losses significantly higher than in the representation-based approaches. These findings, the authors suggest, can serve as a guideline for a collaborative social, political and institutional effort to achieve the common goal of minimizing the loss of biodiversity.

Link to original article

Monteiro LM, Brum FT, Pressey RL, Morellato LPC, Soares-Filho B, Lima-Ribeiro MS and Loyola R (2018) Evaluating the impact of future actions in minimizing vegetation loss from land conversion in the Brazilian Cerrado under climate change. Biodiversity and Conservation. Springer Nature. Available at:

  • {{'resourceSearch.filters.countriesOfResearcher' | translate}}:
  • Brazil
  • Australia
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  • Brazil
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  • Climate change
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  • GBIF network
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  • Data analysis