Abstract

Terrestrial vegetation is a substantial carbon sink and plays a foundational role in regional and global climate change mitigation strategies. The state of California, USA, commits to achieving carbon neutrality by 2045 in part by managing terrestrial ecosystems to sequester more than 80 MMT of CO2. We used a 35-year net primary productivity (NPP) remote sensing product with gridded climate, soil, topography, and vegetation data to evaluate spatiotemporal drivers of NPP variation and identify drivers of NPP response to extremes in water availability in California’s major grasslands, shrublands, and woodlands. We used generalized boosted models (GBMs) and linear mixed effects models (LMMs) to identify influential predictors of NPP and characterize their relationships with NPP across seven major vegetation cover types: annual grasslands, blue oak, chamise-redshank chaparral, coastal scrub, coastal oak woodland, mixed chaparral, and montane hardwood. Climate seasonality, specifically greater precipitation and warmer minimum temperatures in early spring and winter, was associated with greater NPP across space, particularly in chaparral, blue oak, and grassland systems. Maximum annual temperature and climatic water deficit (CWD) showed a negative relationship with NPP in most vegetation cover types, particularly chaparral and coastal scrub. We found a significant decrease in NPP over time in most vegetation types, appearing to coincide with the 2012–2016 California mega-drought. However, response to water availability extremes differed by vegetation type. In most vegetation types, especially grasslands, increases in NPP in extreme wet years were greater than declines in NPP in dry years. Our analysis characterizes several climate risks and conservation opportunities in using California’s natural lands to store carbon. Namely, shifts in climate seasonality and water availability extremes threaten these systems’ ability to fix carbon, yet hotspots of NPP resilience may exist and could be enhanced through conservation and restoration. Additional mechanistic work can help illuminate these opportunities and prioritize conservation decision making.

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