Documenting temporal trends in the extent of ecosystems is essential to monitoring their status but combining this information with the degree of protection helps us assess the effectiveness of societal actions for conserving ecosystem diversity and related ecosystem services. We demonstrated indicators in the Tropical Andes using both potential (pre-industrial) and recent (~2010) distribution maps of terrestrial ecosystem types. We measured long-term ecosystem loss, representation of ecosystem types within the current protected areas, quantifying the additional representation offered by protecting Key Biodiversity Areas. Six (4.8%) ecosystem types (i.e., measured as 126 distinct vegetation macrogroups) have lost >50% in extent across four Andean countries since pre-industrial times. For ecosystem type representation within protected areas, regarding the pre-industrial extent of each type, a total of 32 types (25%) had higher representation (>30%) than the post-2020 Convention on Biological Diversity (CBD) draft target in existing protected areas. Just 5 of 95 types (5.2%) within the montane Tropical Andes hotspot are currently represented with >30% within the protected areas. Thirty-nine types (31%) within these countries could cross the 30% CBD 2030 target with the addition of Key Biodiversity Areas. This indicator is based on the Essential Biodiversity Variables (EBV) and responds directly to the needs expressed by the users of these countries.

En este artículo de investigación científica se da a conocer a la comunidad interesada en el procesamiento digital de imágenes, una aplicación inédita de la transformada de Radon para segmentar imágenes en escala de grises, lo que permite la identificación y clasificación de regiones u objetos, misma que puede extenderse a imágenes en color. Los resultados obtenidos se compararon con los resultados de dos algoritmos clásicos de segmentación: el algoritmo de umbralización Otsu optimizado, y el algoritmo de crecimiento de regiones Seeded Region Growing.

Eucalyptus grandis and E. dunnii have high productive potential in the South of Brazil, Uruguay, and central Argentina. This is based on the similarity of the climate and soil of these areas, which form an eco-region called Campos. However, previous results show that these species have differences in their distribution caused by the prioritization of Uruguayan soils for forestry, explained by the particular conditions of each site. In this study, the site variables (climate, soil, and topography) that better explain the distribution of both species were identified, and prediction models of current and future distribution were adjusted for different climate change scenarios (years 2050 and 2070). The distribution of E. grandis was associated with soil parameters, whereas for E. dunnii a greater effect of the climatic variables was observed. The ensemble biomod2 model was the most precise with regard to predicting the habitat for both species with respect to the simple models evaluated. For E. dunnii, the average values of the AUC, Kappa, and TSS index were 0.98, 0.88, and 0.77, respectively. For E. grandis, their values were 0.97, 0.86, and 0.80, respectively. In the projections of climatic change, the distribution of E. grandis occurrence remains practically unchanged, even in the scenarios of temperature increase. However, current distribution of E. dunnii shows high susceptibility in a scenario of increased temperature, to the point that most of the area currently planted may be at risk. Our results might be useful to political government and foresters for decision making in terms of future planted areas.