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Terrestrial ecosystems, vital for absorbing atmospheric carbon dioxide to mitigate climate change, rely on Earth system models (ESMs) for estimating carbon uptake—a cornerstone of climate policy, carbon budgeting and land management strategies. Yet new research from the Chinese Academy of Sciences (CAS) reveals critical flaws in how these models represent a key metric of carbon absorption, raising concerns about the reliability of long-term climate projections.

Gross primary productivity (GPP)—the rate at which plants convert carbon dioxide into organic matter via photosynthesis—is highly sensitive to temperature: it declines rapidly once temperatures exceed an optimal threshold (T^eco_qpt). Accurately simulating T^eco_qpt in ESMs is essential for projecting land carbon uptakes and understanding associated climate feedbacks. However, uncertainty has long surrounded whether ESMs capture T^eco_qpt accurately.

A team led by Prof. Niu Shuli from the Institute of Geographic Sciences and Natural Resources Research of CAS, along with collaborators, set out to address this gap. The team analyzed ESM performance across global ecosystems. Their findings, in the journal One Earth, uncovered two major biases:

• Current ESMs systematically overestimated or failed to capture T^eco_qpt across 60.3% of ecosystems, especially in arid regions.
• The models fail to capture the observed increase in T^eco_qpt over the past four decades, a trend linked to ecosystem acclimation to rising global temperatures.

Further investigation pinpointed the root causes: ESMs misrepresent water limitations and vegetation structure changes under high-temperature conditions. These flaws, the researchers noted, lead models to overestimate the positive effects of warming on land carbon uptake—ultimately amplifying projected carbon-climate feedbacks in a warming world.

By linking T^eco_qpt biases to future GPP projections, the study identifies pathways to improve land carbon uptake predictions, the researchers noted. Such improvements are not only critical for enhancing the reliability of climate projections but also for sustaining ecosystem functions and services—key to supporting international efforts to mitigate climate change.