Otolith microchemistry analysis accurately reconstructed the spawning ground utilization of fish in the upper Nu-Salween River

1. Freshwater habitats face substantial degradation worldwide, threatening critical ecosystem functioning and services. Fish spawning grounds play a vital role in sustaining fish populations, biodiversity, and aquatic ecosystem health. However, high-resolution empirical data on fish habitat use in large river systems remain scarce due to limitations in tagging methodologies. This study reconstructs spawning ground utilization of a fish (Clupisoma yunnanensis) in the upper Nu-Salween River by matching otolith microchemistry signatures with high-resolution water chemistry maps (chemoscapes).2. We analyzed otolith and water element ratios (Mg:Ca, Mn:Ca, Sr:Ca, Ba:Ca) using electron probe microanalysis (EPMA) and inductively coupled plasma mass spectrometry (ICP-MS), respectively, and established their quantitative relationships. These data were then applied in a random forest (RF) model to reconstruct fish spawning ground distribution, with validation performed through environmental niche analysis assessing the overlap between microchemistry-derived spawning grounds and traditionally observed sites.3. EPMA revealed significant core-to-edge otolith microchemistry variations, paralleled by spatiotemporal water chemistry heterogeneity, demonstrating the species experienced diverse habitats. The RF model achieved 98% accuracy in identifying downstream areas as primary spawning grounds. Environmental niche analyses showed 83% concordance between microchemistry-derived spawning grounds and traditionally observed sites.4. This study establishes a novel biogeochemical framework combining otolith microchemistry, chemoscape, and machine learning to accurately reconstruct critical fish habitats. Our approach not only resolves the spawning ecology of C. yunnanensis in the Nu-Salween system but also provides a transferable methodology for conservation planning in data-scarce river basins worldwide.1. 全球范围内淡水生境正面临严重退化，严重威胁着关键生态系统功能与服务。鱼类产卵场对于维持鱼类种群、生物多样性以及水生生态系统健康至关重要。然而，受限于标记方法学的不足，大型河流系统中关于鱼类栖息地利用的高分辨率实证数据仍然匮乏。本研究通过将耳石微化学（otolith microchemistry）特征与高分辨率水化学地图（化学景观chemoscapes）进行匹配，重建了怒江-萨尔温江上游流域Clupisoma yunnanensis的产卵场利用情况。 2. 本研究分别采用电子探针显微分析（electron probe microanalysis, EPMA）与电感耦合等离子体质谱法（inductively coupled plasma mass spectrometry, ICP-MS）测定了耳石与水体的元素比值（Mg:Ca、Mn:Ca、Sr:Ca、Ba:Ca），并建立了二者的定量关联。随后将这些数据应用于随机森林（random forest, RF）模型，以重建鱼类产卵场的分布情况，并通过生态位分析验证模型效果：该分析用于评估耳石微化学反推得到的产卵场与传统观测位点之间的重叠度。 3. 电子探针显微分析结果显示，耳石微化学特征从核心到边缘存在显著变化，同时伴随水化学的时空异质性，表明该鱼类曾经历多种不同的栖息环境。随机森林模型以98%的准确率将下游区域识别为主要产卵场。生态位分析结果显示，耳石微化学反推得到的产卵场与传统观测位点的吻合度达83%。 4. 本研究构建了一套融合耳石微化学、化学景观（chemoscapes）与机器学习的新型生物地球化学框架，可精准重建关键鱼类栖息生境。该方法不仅阐明了怒江-萨尔温江流域Clupisoma yunnanensis的产卵生态特征，还为全球范围内数据匮乏的河流流域的保护规划提供了可推广的技术方案。