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Platform data

Overview

Detailed view

Monitoring of woody species regeneration was done in 2003, 2005 and 2007 on 48 subplots of 116 m2 on pasture, fern, and shrub sites. 
Half of the subsamples were randomly selected and manually treated by cutting back all competing herbaceous species with a machete
every 4 months from 2003 to 2005. Competing species refers to dominant, exotic and aggressive species such as grasses (S.
sphacelata) in the Pasture site, and exotic fern (P. arachnoideum) in the Bracken and Shrub sites, woody native species were not removed.

Palomeque, X.; Günter, S.; Siddons, D.; Hildebrandt, P.; Stimm, B.; Aguirre, N.; Arias, R. & Weber, M. (2017): Natural or assisted succession as approach of forest recovery on abandoned lands with different land use history in the Andes of Southern Ecuador. New Forests 1(1), 1-10
DOI: http://dx.doi.org/10.1007/s11056-017-9590-8.

We modeled forest productivity parameters by remote sensing metrics derived from a Landsat-8 image and four Aster elevation images in the mountain rainforest of Southern Ecuador. The validated model for annual litterfall accounted for 68 % in variation of productivity. The partial least square regression model has been predicted across the study area. Non-forest areas have been masked out (using the land cover classification of Göttlicher et al. (2009). Attention this is work in progress. For further information please contact.

The prediction map identifies the estimated richness of ant species in the mountain rainforest in the San Francisco Valley. The corresponding regression model explained 78% in variation of species richness. Further information about the model and sampled field data are published in Wallis et al. (2017): Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa. doi: 10.1016/j.ecolind.2017.01.022

The prediction map identifies the estimated richness of Pyraloidea species in the mountain rainforest in the San Francisco Valley. The corresponding regression model explained 72% in variation of species richness. Further information about the model and sampled field data are published in Wallis et al. (2017): Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa. doi: 10.1016/j.ecolind.2017.01.022

Tree inventory data (> 10cm; species richness, Shannon indices, tree density) and coordinates of 72 inventory plots (60m x 60m) in the dry forest.

Tree functional traits (leaf area, specific leaf area, foliar N, foliar P, leaf toughness, bark thickness, wood specific gravity, sapwood vessel density, sapwood vessel diameter, sapwood-specific conductivity) recorded in the montane forests of the San Francisco reserve.

Tree functional traits (leaf area, specific leaf area, foliar N, foliar P, leaf toughness, bark thickness, wood specific gravity, sapwood vessel density, sapwood vessel diameter, sapwood-specific conductivity) recorded in the upper montane forests of the Podocarpus National Park (Cajanuma entrance).

Tree functional traits (leaf area, specific leaf area, foliar N, foliar P, leaf toughness, bark thickness, wood specific gravity, sapwood vessel density, sapwood vessel diameter, sapwood-specific conductivity) recorded in the premontane forests of the Podocarpus National Park (Bombuscaro entrance).

Robust multifunctional land-use model for deriving multifunctional landscapes

See README in data for additional information on methodology