Exploring the spatiotemporal dynamics of habitat suitability to improve conservation management of a vulnerable plant species

Ongoing declines in biodiversity caused by global environmental changes call for adaptive conservation management, including the assessment of habitat suitability spatiotemporal dynamics potentially affecting species persistence. Remote sensing (RS) provides a wide-range of satellite-based environmental variables that can be fed into species distribution models (SDMs) to investigate species-environment relations and forecast responses to change. We address the spatiotemporal dynamics of species’ habitat suitability at the landscape level by combining multi-temporal RS data with SDMs for analysing inter-annual habitat suitability dynamics. We implemented this framework with a vulnerable plant species (Veronica micrantha), by combining SDMs with a time-series of RS-based metrics of vegetation functioning related to primary productivity, seasonality, phenology and actual evapotranspiration. Besides RS variables, predictors related to landscape structure, soils and wildfires were ranked and combined through multi-model inference (MMI). To assess recent dynamics, a habitat suitability time-series was generated through model hindcasting. MMI highlighted the strong predictive ability of RS variables related to primary productivity and water availability for explaining the test-species distribution, along with soil, wildfire regime and landscape composition. The habitat suitability time-series revealed the effects of short-term land cover changes and inter-annual variability in climatic conditions. Multi-temporal SDMs further improved predictions, benefiting from RS time-series. Overall, results emphasize the integration of landscape attributes related to function, composition and spatial configuration for improving the explanation of ecological patterns. Moreover, coupling SDMs with RS functional metrics may provide early-warnings of future environmental changes potentially impacting habitat suitability. Applications discussed include the improvement of biodiversity monitoring and conservation strategies.