Climatic Drivers and Hierarchical Constraints on the Suitable Habitat of Elm Sparse Grassland in China

Elm sparse grassland, dominated by Ulmus pumila, serves as a critical ecological barrier in Northern China, yet the specific climatic mechanisms governing its distribution remain poorly quantified, hindering effective restoration. This study employed the Maximum Entropy (MaxEnt) model to disentangle the primary drivers of this ecosystem, specifically addressing whether its distribution is governed by moisture limitation or a stricter thermal regime. Analyzing 94 occurrence records and 13 climatic variables, the model achieved high predictive accuracy (AUC = 0.92) and identified the annual temperature range (ART) as the predominant determinant of macro-distribution (30.1% contribution), surpassing moisture variables such as annual precipitation (19.3%). The results demonstrate that the vegetation is strictly confined to a continental climate envelope with an ART of 46.2~50.7 °C and a coldness index of −70.1~−36.1 °C, while optimal precipitation (313~497 mm) acts as a secondary filter maintaining the open-woodland structure. These findings establish a hierarchical filtering model where a strict thermal regime acts as the primary “gatekeeper” setting absolute geographical boundaries, while moisture availability determines habitat quality within those limits. Consequently, this study advocates for a paradigm shift in ecological engineering—such as the Three-North Shelterbelt Program—from moisture-centric approaches to “climate-smart” restoration that prioritizes specific thermal constraints. Adhering to these precise climatic envelopes is essential to prevent maladaptation and ensure the long-term sustainability of restoration efforts amidst global climate change.