A study led by Alistair W. R. Seddon and colleagues presents a novel method to assess the sensitivity of global terrestrial ecosystems to climate variability. The research introduces the Vegetation Sensitivity Index (VSI), which quantifies how sensitive vegetation productivity is to climate variables such as temperature, water availability, and cloud cover. Using MODIS-derived data, the VSI identifies regions where ecosystems are most vulnerable to climate changes, including the Arctic tundra, boreal forests, tropical rainforests, alpine regions, and specific areas in central Asia and South America. The study highlights that these regions exhibit amplified responses to climate variability, indicating a higher risk of ecological tipping points. The VSI is calculated using an autoregressive model that identifies climate drivers of vegetation productivity and memory effects in ecosystems. The results show that areas with high VSI values are those where vegetation productivity is strongly influenced by climate variables, particularly temperature and cloud cover in tropical regions. The study also reveals that water availability is a key factor in certain regions, such as the Caatinga biome in Brazil. The research underscores the importance of understanding how ecosystems respond to climate variability, as this knowledge is crucial for predicting the resilience of ecosystem services and human well-being. The study provides a quantitative framework for assessing ecological sensitivity, which is essential for identifying regions at risk of ecological change. The findings suggest that climate variability has significant impacts on ecosystem functioning, and that some regions are more sensitive to these changes than others. The study also highlights the role of memory effects in ecosystems, where past conditions influence current productivity. This is particularly evident in dryland regions, where vegetation responses are delayed due to soil-water recharge processes. The research contributes to the broader understanding of ecological resilience and the potential for critical transitions in ecosystems, emphasizing the need for further investigation into the underlying mechanisms driving these patterns. The study's methodology and findings offer valuable insights for global ecosystem assessment and management.A study led by Alistair W. R. Seddon and colleagues presents a novel method to assess the sensitivity of global terrestrial ecosystems to climate variability. The research introduces the Vegetation Sensitivity Index (VSI), which quantifies how sensitive vegetation productivity is to climate variables such as temperature, water availability, and cloud cover. Using MODIS-derived data, the VSI identifies regions where ecosystems are most vulnerable to climate changes, including the Arctic tundra, boreal forests, tropical rainforests, alpine regions, and specific areas in central Asia and South America. The study highlights that these regions exhibit amplified responses to climate variability, indicating a higher risk of ecological tipping points. The VSI is calculated using an autoregressive model that identifies climate drivers of vegetation productivity and memory effects in ecosystems. The results show that areas with high VSI values are those where vegetation productivity is strongly influenced by climate variables, particularly temperature and cloud cover in tropical regions. The study also reveals that water availability is a key factor in certain regions, such as the Caatinga biome in Brazil. The research underscores the importance of understanding how ecosystems respond to climate variability, as this knowledge is crucial for predicting the resilience of ecosystem services and human well-being. The study provides a quantitative framework for assessing ecological sensitivity, which is essential for identifying regions at risk of ecological change. The findings suggest that climate variability has significant impacts on ecosystem functioning, and that some regions are more sensitive to these changes than others. The study also highlights the role of memory effects in ecosystems, where past conditions influence current productivity. This is particularly evident in dryland regions, where vegetation responses are delayed due to soil-water recharge processes. The research contributes to the broader understanding of ecological resilience and the potential for critical transitions in ecosystems, emphasizing the need for further investigation into the underlying mechanisms driving these patterns. The study's methodology and findings offer valuable insights for global ecosystem assessment and management.