Reconstruction of native vegetation based upon integrated landscape approaches

Reconstructing the vegetation landscape, as an indicator of climatic oscillations, has been often based upon pollen records guided by the so-called paleoecolocical approach. Outcomes of this approach, however, have limited chorological implications. The main objective of this manuscript is to develop an integrative method of approaches (bioclimatic and geographical) for the chorological reconstruction of the vegetation at the Purepecha region in central Mexico. The bioclimatic indexes were calculated from the raster layers of the Digital Climatic Atlas of Mexico and were analyzed via a Geographic Information System. The raster were reclassified into isobioclimates. The isobioclimates were overlapped with the current land cover, vertical dissection and rocks types to find correlation patterns. Originally, native vegetation types were forested, whereas currently these were replaced by agricultural encroachment. Correlations among isobioclimate, land form and rock type were used to reconstruct plant communities in polygons where native vegetation was vanished. The reconstruction was verified with 216 vegetation surveys and literature information, so that remaining vegetation elements and earlier reports were used as ground truth validation. On the whole, six vegetation types were recognized. The Tropical dry broadleaved sub-deciduous of Albizia - Senna - Bursera forest was the most outstanding and the one that occupied the largest surface with 51%. On the other hand, the Tropical dry spiny-succulent evergreen-sub-deciduous of Randia - Opuntia - Stenocereus shrubland was the least represented with 1%. The integration of landscape approaches, hierarchically analyzed, were key to reconstruct the native vegetation. Our results contribute to the understanding of plant communities in a region with a large degree of vegetation transformation. The above may further serve to enrich ongoing research about the chorological reconstruction of the historical landscape.