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Landscape Structural Complexity of High‐Mountain Polylepis australis Forests: A New Aspect of Restoration Goals
Author(s) -
Renison Daniel,
Hensen Isabell,
Suarez Ricardo
Publication year - 2011
Publication title -
restoration ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.214
H-Index - 100
eISSN - 1526-100X
pISSN - 1061-2971
DOI - 10.1111/j.1526-100x.2009.00555.x
Subject(s) - abundance (ecology) , coarse woody debris , canopy , ecological succession , trampling , ecology , forest restoration , geography , habitat , restoration ecology , ecosystem , tree canopy , vegetation (pathology) , seral community , forest ecology , environmental science , agroforestry , forestry , grazing , biology , medicine , pathology
Forest restoration efforts should aim at creating landscapes with a balanced array of forest stands at varying successional stages, thus providing habitat for a wealth of species and multiple ecosystem services. In most high‐mountain ecosystems of South America, long‐term livestock rearing activities that include fires, browsing, and trampling have delayed or stopped forest succession resulting in simplified landscapes. To determine appropriate restoration goals for Polylepis australis mountain forests of Central Argentina, we established 146 plots of 900 m 2 plots throughout five river basins with different historic livestock stocking rates. In each plot, we measured tree heights, canopy cover, estimated age of oldest tree, volume of standing and fallen dead wood, fern cover, and abundance of shade tolerant Maytenus boaria trees. K‐means cluster analysis using tree heights and canopy cover as classificatory variables yielded four biologically meaningful clusters. Clusters 1, 2, 3, and 4 comprising 68, 10, 13, and 9% of the plots, respectively, showed increasing amounts of standing and fallen dead wood, fern cover, and abundance of shade tolerant M. boaria trees. Plots in clusters 1 and 2 were proportionally more abundant in basins with high human impact and at the altitudinal extremes of P. australis distribution, whereas plots in clusters 3 and 4 were relatively more abundant in well‐preserved basins and at the optimum of their altitudinal distribution. We interpret clusters 1, 2, 3, and 4 as degraded, regenerating, young, and mature forests, respectively. Restoration goals should focus on attaining an even distribution of forest types similar to that found in our best‐preserved basins.