Título:	Modeling deforestation in the state of Rondônia
Autor(es):	Piontekowski, Valderli Jorge Ribeiro, Fabiana Piontekowski Matricardi, Eraldo Aparecido Trondoli Lustosa Junior, Ilvan Medeiros Bussinguer, Angela Pereira Gatto, Alcides
ORCID:	http://orcid.org/0000-0002-1442-7772 http://orcid.org/0000-0002-5375-6368 http://orcid.org/0000-0002-5323-6100 http://orcid.org/0000-0002-3873-737X http://orcid.org/0000-0002-6375-0648 http://orcid.org/0000-0002-2663-9318
Assunto:	Solo - uso Desmatamento - Rondônia
Data de publicação:	2019
Editora:	Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
Referência:	PIONTEKOWSKI, Valderli Jorge et al. Modeling Deforestation in the State of Rondônia. Floresta e Ambiente, v. 26, n. 3, e20180441, 2019. DOI: https://doi.org/10.1590/2179-8087.044118. Disponível em: http://scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000300144. Acesso em: 23 jan. 2020.
Abstract:	This study applied a deforestation model for the entire State of Rondônia assuming three scenarios of deforestation: business as usual, optimistic and pessimistic. Those scenarios were constructed for the time-period of 2012-2050 using the Dinamica EGO software. Rondônia deforestation dataset was provided by the Agência Ambiental do Estado de Rondônia (Rondônia State Environmental Agency) and was used as input of the deforestation modeling. Based on this study results, we estimated that 32%, 37% and 47% of Rondônia’s native forest could be fully deforested by 2050 assuming the optimistic, business as usual and pessimistic scenarios, respectively. Regardless of the chosen scenario, we expect that deforestation will be spatially concentrated in Northern Rondônia in the next decades. The greatest concern, however, could be the integrity of the protected areas assuming the business as usual and/or pessimistic scenario. In addition, we expect a substantial increase of the forest fragmentation by 2050.
Licença:	(CC BY) - Creative Commons License. All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License.
DOI:	https://doi.org/10.1590/2179-8087.044118
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