Increasing water use and droughts, along with climate variability and land use change, have seriously altered vegetation growth patterns and ecosystem response in several regions alongside the Andes Mountains. Thirty years of the new generation biweekly normalized difference vegetation index (NDVI3g) time series data show significant land cover specific trends and variability in annual productivity and land surface phenological response. Productivity is represented by the growing season mean NDVI values (July to June). Arid and semi-arid and sub humid vegetation types (Atacama desert, Chaco and Patagonia) across Argentina, northern Chile, northwest Uruguay and southeast Bolivia show negative trends in productivity, while some temperate forest and agricultural areas in Chile and sub humid and humid areas in Brazil, Bolivia and Peru show positive trends in productivity. The start (SOS) and length (LOS) of the growing season results show large variability and regional hot spots where later SOS often coincides with reduced productivity. A longer growing season is generally found for some locations in the south of Chile (sub-antarctic forest) and Argentina (Patagonia steppe), while central Argentina (Pampa-mixed grasslands and agriculture) has a shorter LOS. Some of the areas have significant shifts in SOS and LOS of one to several months. The seasonal Multivariate ENSO Indicator (MEI) and the Antarctic Oscillation (AAO) index have a significant impact on vegetation productivity and phenology in southeastern and northeastern Argentina (Patagonia and Pampa), central and southern Chile (mixed shrubland, temperate and sub-antarctic forest), and Paraguay (Chaco).

Land-use and land-cover (LULC) changes are major drivers of biodiversity loss in semi-arid regions, such as the Caatinga biome located in the Northeast of Brazil. We investigated landscape dynamics and fragmentation in an area of the São Francisco Valley in the Brazilian Caatinga biome and measured the effect of these dynamics on ecological, functional and structural connectivity over a 33-year period (1985–2018). We calculated landscape connectivity indices based on graph theory to quantify the effect of further agricultural expansion on ecological connectivity at the landscape scale. We used a multicriteria decision analysis that integrates graph-based connectivity indices at the habitat patch scale, combined with an index of human disturbance to identify patches that, if conserved and restored, preserve the connectivity of the landscape most effectively. In the period studied, agriculture increased at a rate of 2104 ha/year, while native Caatinga vegetation decreased at a rate of 5203 ha/year. Both dense and open Caatinga became more fragmented, with the number of fragments increasing by 85.2% and 28.6%, respectively, whilst the average fragment size decreased by 84.8% and 6.1% for dense and open Caatinga, respectively. If agriculture patches were to expand by a 300 m buffer around each patch, the overall ecological connectivity could be reduced by 6–15%, depending on the species’ (small- to mid-size terrestrial vertebrates) mobility characteristics for which the connectivity indices were calculated. We provided explicit spatial connectivity and fragmentation information for the conservation and restoration of the Caatinga vegetation in the studied area. This information helps with conservation planning in this rapidly changing ecosystem.

Las imágenes satelitales son una poderosa herramienta para describir estructuras espaciales a meso y macroescala, ayudando de esta manera en la comprensión de los procesos físicos-biológicos que ocurren en el océano. El objetivo de este estudio fue establecer la variabilidad espacial (horizontal) y temporal (estacional) de la biomasa autotrófica medida como concentración de clorofila satelital (Clo-a) en el Mar Interior de Chiloé (41,0-43,5ºS). Aproximaciones de percepción remota (MODIS) y geoestadísticas (Variogramas) fueron usadas para caracterizar la estructura espacial de la Clo-a en la capa superficial por estimación afototrópica de valores promedios de Clo-a. Un total de 27 imágenes fueron analizadas y agrupadas en estaciones de verano, primavera, invierno y otoño para el Mar Interior de Chiloé durante el periodo de enero 2003-diciembre 2005. El análisis de imágenes apunta a un patrón clásico para la dinámica de la biomasa autotrófica de áreas costeras temperadas, con altos valores de Clo-a en las estaciones de primavera-verano y ocurrencia de bajos valores durante las estaciones de otoño-invierno. El análisis espacial indica que la Clo-a se distribuye en parches mayores a 50 km los cuales son más homogéneos durante las estaciones de otoño-invierno, mientras que parches más pequeños que 30 km y más heterogéneos fueron observados durante primavera-verano. El análisis de anisotropía muestra un ángulo predominante de orientación en la dirección este-oeste, sugiriendo el rol de la estratificación de la columna de agua como un proceso modulador de la variabilidad espacial superficial de la Clo-a en el Mar Interior de Chiloé.

The usual approaches to describing and understanding ecological processes in a landscape use patch-mosaic models based on traditional landscape metrics. However, they do not consider that many of these processes cannot be observed without considering the multiple interactions between different land-use patches in the landscape. The objective of this research was to provide a synthetic overview of graph metrics that characterize landscapes based on patch-mosaic models and to analyze the ecological meaning of the metrics to propose a relevant selection explaining biodiversity patterns and ecological processes. First, we conducted a literature review of graph metrics applied in ecology. Second, a case study was used to explore the behavior of a group of selected graph metrics in actual differentiated landscapes located in a long-term socioecological research site in Brittany, France. Thirteen landscape-scale metrics and 10 local-scale metrics with ecological significance were analyzed. Metrics were grouped for landscape-scale and local-scale analysis. Many of the metrics were able to identify differences between the landscapes studied. Lastly, we discuss how graph metrics offer a new perspective for landscape analysis, describe the main characteristics related to their calculation and the type of information provided, and discuss their potential applications in different ecological contexts.