Sustainable landscapes: restoration and land use planning in an adaptive approach to climate change and desertification. Case study of Inter-Andean Valley of Cauca River in Colombia

The inter-Andean valley of Cauca River (IVCR) is one of the most industrialized regions in Colombia leading its seasonally dry tropical forest (SDTF) to a fragmented and degraded state. Changes in land cover may alter the climatic and hydrological patterns. In the period 1984 – 2014, 26% of natural areas detected remotely at IVCR have persisted in a sugarcane matrix. However, IVCR species composition and its ecological status are unknown. After reviewing several datasets, 1725 plant species were compiled. Using a modelling approach, habitat suitability was predicted with a maximum entropy algorithm implemented in Biomod2 R-Package for 14 prioritized plant species. Models were produced using as predictors, the variables selected with their Variance Inflation Factor (VIF) and for those selected with a Principal Component Analysis (PCA). Although the selected variables differed between VIF and PCA, the geographic space predicted to be suitable for the species were similar. VIF and PCA variables strongly reflect the temperature and precipitation under warm and wet periods and their seasonality. These models will help to estimate the potential restoration of SDTF at the ICVR and its vulnerability to climate change. This information will contribute to planning effectively the IVCR landscape for the future.