| 多情景模拟下陕西省土地利用变化及生物多样性变化 |
| 摘要点击 554 全文点击 6 投稿时间：2025-06-11 修订日期：2025-09-23 |
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| 中文关键词 土地利用变化 生物多样性 情景模拟 FLUS-Biodiversity模型 平均物种丰度（MSA） |
| 英文关键词 land use change biodiversity scenario simulation FLUS-Biodiversity model mean species abundance （MSA） |
| DOI 10.13227/j.hjkx.202506125 |
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| 中文摘要 |
| 人类对于土地资源的过度开发利用所导致的土地利用变化造成全球生态空间缩减，给生物多样性保护带来巨大挑战. 为推动黄河流域生态保护与高质量发展目标协同实现，兼顾陕西省生物多样性保护需求与社会经济发展诉求，基于土地利用类型、扰动程度与生物多样性的内在关联，设计基线（自然演进）、美丽陕西（生态优先）及和谐陕西（协调发展）这3类情景方案，并运用 GeoSoS-FLUS与FLUS-Biodiversity模型，模拟2035年及2050年土地利用格局演变及平均物种丰度（MSA）的空间分异特征，再通过XGBoost-SHAP模型进行MSA的驱动因素分析. 结果表明：①陕西省多数土地利用类型发生结构转变，3类情景下中度扰动林地面积均显著增长，旱地面积缩减最为明显；②在自然发展趋势下，陕西省MSA值从2020年的0.533增至2050年的0.539，而在美丽陕西与和谐陕西情景下，2050年MSA值分别提升至0.546和0.544，印证了这两种情景对生物多样性提升的积极效应；③生物多样性空间分布呈现显著区域差异，人口经济密集区MSA值较低，而自然资源富集区域MSA值相对较高； ④驱动因子对MSA贡献呈显著异质性：人口密度为关键负向因子，年均潜在蒸散发与气温则为正向主导因子. 研究证实，科学统筹土地利用变化与生物多样性保护、落实针对性保护政策、强化生物多样性治理效能，是达成生物多样性保护目标的有效路径. |
| 英文摘要 |
| Excessive exploitation of land resources has driven global land-use changes that diminish ecological spaces， posing significant challenges to biodiversity conservation. To synergize ecological protection with high-quality development in the Yellow River Basin while balancing biodiversity conservation and socioeconomic needs in Shaanxi Province， this study designed three scenarios—Baseline （natural evolution）， Beautiful Shaanxi （ecological priority）， and Harmonious Shaanxi （coordinated development）—based on intrinsic linkages among land-use types， disturbance intensity， and biodiversity. Using the GeoSoS-FLUS and FLUS-Biodiversity models， we simulated land-use patterns and spatial heterogeneity of Mean Species Abundance （MSA） for 2035 and 2050. XGBoost-SHAP modeling further deciphered MSA drivers. Key findings reveal that： ① Structural shifts in most land-use types occurred， with moderately disturbed forests expanding significantly across all scenarios while dryland areas decreased most markedly. ② Under natural trends， Shaanxi's MSA rose from 0.533 （2020） to 0.539 （2050）， whereas the Beautiful and Harmonious scenarios elevated MSA to 0.546 and 0.544 by 2050， confirming their positive biodiversity effects. ③ MSA exhibited pronounced regional disparities—lower in densely populated economic zones and higher in natural resource-rich areas. ④ Driver contributions to MSA exhibited significant heterogeneity： Population density was the dominant negative factor， while annual potential evapotranspiration and temperature acted as primary positive drivers. This study demonstrates that scientifically coordinating land-use changes with biodiversity conservation， implementing targeted protection policies， and enhancing governance efficacy constitute effective pathways to achieve biodiversity targets. |
