Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought-induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi-day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short-term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called tree water deficit to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causality Soil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi-days) Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit

The Granger Causality (GC) statistical test explores the causal relationships between different time series variables. By employing the GC method, the underlying causal links between environmental drivers and global vegetation properties can be untangled, which opens possibilities to forecast the increasing strain on ecosystems by droughts, global warming, and climate change. This study aimed to quantify the spatial distribution of four distinct satellite vegetation products' (VPs) sensitivities to four environmental land variables (ELVs) at the global scale given the GC method. The GC analysis assessed the spatially explicit response of the VPs: (i) the fraction of absorbed photosynthetically active radiation (FAPAR), (ii) the leaf area index (LAI), (iii) solar-induced fluorescence (SIF), and, finally, (iv) the normalized difference vegetation index (NDVI) to the ELVs. These ELVs can be categorized as water availability assessing root zone soil moisture (SM) and accumulated precipitation (P), as well as, energy availability considering the effect of air temperature (T) and solar shortwave (R) radiation. The results indicate SM and P are key drivers, particularly causing changes in the LAI. SM alone accounts for 43%, while P accounts for 41%, of the explicitly caused areas over arid biomes. SM further significantly influences the LAI at northern latitudes, covering 44% of cold and 50% of polar biome areas. These areas exhibit a predominant response to R, which is a possible trigger for snowmelt, showing more than 40% caused by both cold and polar biomes for all VPs. Finally, T's causality is evenly distributed amongst all biomes with fractional covers between similar to 10 and 20%. By using the GC method, the analysis presents a novel way to monitor the planet's ecosystem, based on solely two years as input data, with four VPs acquired by the synergy of Sentinel-3 (S3) and 5P (S5P) satellite data streams. The findings indicated unique, biome-specific responses of vegetation to distinct environmental drivers.

Despite that the supplying role of cryosphere (glaciers, permafrost, and snow) in groundwater storage (GWS) in Tibetan Plateau (TP) is well-known by comparing their long-term linear trends, the question whether GWS could in turn affect the variation of cryospheric variables remains controversial, since long-term trend analysis fails to distinguish the direction of their interplay. To find evidence of GWS causally affecting cryosphere, this research resorts to the causal inference community and investigates a novel causal interaction between GWS and cryosphere in TP: nonlinear dynamic causality (NDC), based on the Nonlinear Dynamic System (NDS) theory. The specific method applied is called Convergent Cross-mapping (CCM), which detects NDC between two targeted variables X and Y from both directions (X & RARR; Y, Y & RARR; X). Important findings are summarized as follows: (1) With CCM, NDCs with similar strengths are found from glaciers retreat, snowmelt, and permafrost thaw to GWS, respectively; (2) Also in the form of NDC, GWS is proven to reversely affect permafrost, but not to glacier and snow; (3) NDCs are also found between GWS and other hydrometeorological variables in TP, including lakes, soil moisture, precipitation, and temperature; (4) Some nontraditional NDCs from glaciers and lakes towards GWS are identified. Overall, using CCM, our new findings about NDC answer the controversial question of whether GWS could in turn affect cryosphere, completing previous conclusions about how GWS interplays with cryosphere in TP, and more importantly, this research would shed light on future causality detection in hydrology.