Contrasting short- and long-term effects of warming and precipitation on ecosystem multifunctionality in a semiarid grassland

Abstract

Ecosystem multifunctionality (EMF) reflects an ecosystem's capacity to sustain multiple functions simultaneously and is highly sensitive to climate change. However, whether short-term EMF responses to climate change reliably predict long-term trends—and whether the underlying mechanisms remain consistent through time—remains unclear. Here, we analyzed 12 ecosystem functions, primarily related to productivity and nutrient cycling, to quantify ecosystem multifunctionality (EMF) in a decade-long warming and increased-precipitation experiment conducted between 2013 and 2024 in a semi-arid grassland in Inner Mongolia, China. We found that short-term increases in precipitation and warming significantly enhanced aboveground multifunctionality (Above-MF), thereby increasing EMF in the context of warming. However, neither treatment produced a marked effect on the belowground multifunctionality (Below-MF) in short- or long-term observations. These results suggest that short-term climate changes do not reliably forecast the long-term impacts of climate change on EMF. Notably, Above-MF exerts greater regulatory influence over EMF during the initial years, whereas the role of Below-MF becomes increasingly prominent over time. Longer experimental durations are important when investigating the regulatory mechanisms governing ecosystem multifunctionality. We identified limitations inherent in extrapolating short-term responses to predict long-term ecosystem outcomes and report an increased influence of abiotic soil functions on ecosystem multifunctionality under prolonged climate change. Short-term EMF responses do not reliably predict outcomes under extended climate manipulation, highlighting a critical temporal dependency in ecosystem responses. Although plants can drive short-term EMF adjustments, soil elements and microbes are more stable and, thus, crucial for sustaining multifunctionality over time. In future research on the impact of climate change on grassland ecosystems, it is necessary to incorporate temporal dynamics and underground processes into climate change prediction models and grassland management measures.