Environmental Management

, Volume 59, Issue 6, pp 1017–1033

Keystone Species, Forest and Landscape: A Model to Select Protected Areas

  • Daniela Barbosa da Silva Lins
  • Fernando Ravanini Gardon
  • João Frederico da Costa Azevedo Meyer
  • Rozely Ferreira dos Santos
Article
  • 185 Downloads

Abstract

The selection of forest fragments for conservation is usually based on spatial parameters as forest size and canopy integrity. This strategy assumes that chosen fragments present high conservation status, ensuring biodiversity and ecological functions. We argue that a well-preserved forest fragment that remains connected by the landscape structure, does not necessarily hold attributes that ensure the presence of keystone species. We also discuss that the presence of keystone species does not always mean that it has the best conditions for its occurrence and maintenance. We developed a model to select areas in forest landscapes to be prioritized for protection based on suitability curves that unify and compare spatial indicators of three categories: forest fragment quality, landscape quality, and environmental conditions for the occurrence of a keystone species. We use a case study to compare different suitability degrees for Euterpe edulis presence, considered an important functional element in Atlantic Forest (São Paulo, Brazil) landscapes and a forest resource for local people. The results show that the identification of medium or advanced stage fragments as singular indicator of forest quality does not guarantee the existence or maintenance of this keystone species. Even in some well-preserved forest fragments, connected to others and with palm presence, the reverse J-shaped distribution of the population size structure is not sustained and these forests continue to be threatened due to human disturbances.

Keywords

Forest conservation Keystone species Spatial parameters 

Supplementary material

267_2017_832_MOESM1_ESM.docx (10.1 mb)
Supplementary Information

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Water, Energy and Environmental ResourcesUniversity of CampinasCampinasBrazil
  2. 2.Department of EcologyUniversity of São Paulo, Rua do MatãoSão PauloBrazil
  3. 3.Institute of Mathematics, Statistics, and Scientific ComputationUniversity of CampinasCampinasBrazil

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