Spatio-temporal remotely sensed indices identify hotspots of biodiversity conservation concern in Argentina

Posted 08/22/23

High inter-annual variability in the phenology of vegetation greenness and in the seasonality of temperature present a threat to the survival of many species, but areas with high spatial variability enhance resilience against this threat. Eduarda Silveira and her colleagues developed indices to identify hotspots of biodiversity conservation concern due to threats from high inter-annual variability. They applied their method in Argentina and identified where management efforts could be valuable and where protection should be considered.

Climate variability affects the phenology of vegetation and the seasonality of temperature, which can lead to mismatches between species and resources. When species are not able to track phenology and seasonal temperate changes, populations decline, posing a threat to biodiversity. Many plants and animals synchronize the timing of their life events with vegetation phenology. Mismatches in the timing of such events, can entail, for example, food limitations when the peak of bird nestling growth is not timed to occur during the annual peak in caterpillar abundance, which may affect reproductive success. In contrast, high spatial variability enhances ecological resilience to biodiversity loss from high inter-annual variability. Biodiversity should benefit from high spatial variability in vegetation greenness and land surface temperature within intact habitats, because such spatial variability is indicative of a variety of resources in close proximity and increases the likelihood that suitable conditions are available during times of extremes. Eduarda Silveira, a postdoctoral research in the SILVIS lab, recently published a study with her colleagues describing their efforts to identify hotspots of biodiversity conservation concern due to threats from high inter-annual variability (Figure 1).

Figure 1. Potential integrations of inter-annual and spatial variability in vegetation greenness and land surface temperature, and the level of conservation concern for each integration.

They generated inter-annual and spatial remotely sensed indices based on time series analysis and image texture, respectively, and integrated these indices to identify areas of high, medium and low conservation concern (Figure 2).

Figure 2. Areas of high and low conservation concern based on (1) vegetation greenness and (2) land surface temperature: (a) inter-annual variability in phenology, (b) spatial variability, (c) integration between inter-annual and spatial variability, and (d) hotspots maps.

They applied their method in Argentina. They identified hotspots of conservation concern in parts of northeastern and southern Argentina. These are sites where management efforts could be valuable (Figure 3). Eliminating existing pressures (i.e., dam construction, land use change) and improving spatial variability by increasing the abundance and diversity of natural landcover in these highly modified regions are promising approaches to increase resilience to climate extremes for native wildlife species. In contrast, areas in the northwest and central-west have high spatial variability, which may confer resilience to climate extremes, due to the variety of conditions and resources within close proximity (Figure 3). Adding protected areas in these naturally resilient regions may be effective in both protecting current patterns of biodiversity and maintaining their adaptive capacity to climate change. Eduarda Silveira hopes that her results will help Argentina’s conservation leaders to be strategic in their protection decision and to prioritize conservation management actions.

Figure 3. Hotspots of highest and lowest conservation concern in Argentina.

Story by Silveira, Eduarda