INVESTIGADORES
MARTINEZ PASTUR Guillermo Jose
artículos
Título:
Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern
Autor/es:
SILVEIRA, EDUARDA M.O.; RADELOFF, VOLKER C.; MARTINUZZI, SEBASTIAN; MARTÍNEZ PASTUR, GUILLERMO J.; RIVERA, LUIS O.; POLITI, NATALIA; LIZARRAGA, LEONIDAS; FARWELL, LAURA S.; ELSEN, PAUL R.; PIDGEON, ANNA M.
Revista:
REMOTE SENSING OF ENVIRONMENT
Editorial:
ELSEVIER SCIENCE INC
Referencias:
Año: 2021 vol. 258
ISSN:
0034-4257
Resumen:
Over the course of a year, vegetation and temperature have strong phenological and seasonal patterns, respectively,and many species have adapted to these patterns. High inter-annual variability in the phenology ofvegetation and in the seasonality of temperature pose a threat for biodiversity. However, areas with high spatialvariability likely have higher ecological resilience where inter-annual variability is high, because spatial variabilityindicates presence of a range of resources, microclimatic refugia, and habitat conditions. The integrationof inter-annual and spatial variability is thus important for biodiversity conservation. Areas where spatialvariability is low and inter-annual variability is high are likely to limit resilience to disturbance. In contrast, areasof high spatial variability may be high priority candidates for protection. Our goal was to develop spatiotemporalremotely sensed indices to identify hotspots of biodiversity conservation concern. We generatedindices that capture the inter-annual and spatial variability of vegetation greenness and land surface temperatureand integrated them to identify areas of high, medium, and low biodiversity conservation concern. We appliedour method in Argentina (2.8 million km2), a country with a wide range of climates and biomes. To generate theinter-annual variability indices, we analyzed MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature(LST) time series from 2001 to 2018, fitted curves to obtain annual phenological and seasonal metrics,and calculated their inter-annual variability. To generate the spatial variability indices, we calculated standarddeviation image texture of Landsat 8 EVI and LST. When we integrated our inter-annual and spatial variabilityindices, areas in the northeast and parts of southern Argentina were the hotspots of highest conservation concern.High inter-annual variability poses a threat in these areas, because spatial variability is low. These are areaswhere management efforts could be valuable. In contrast, areas in the northwest and central-west are whereprotection should be strongly considered because the high spatial variability may confer resilience to disturbance,due to the variety of conditions and resources within close proximity. We developed remotely sensedindices to identify hotspots of high and low conservation concern at scales relevant to biodiversity conservation,= which can be used to target management actions in order to minimize biodiversity loss.