環境因子對水生植物之影響初探-以花蓮地區為例

Abstract

濕地不僅在水質調節、碳儲存及洪水緩衝方面發揮關鍵作用。水生植物在濕地生態系中亦扮演重要角色，然而台灣目前針對水生植物與環境因子的系統性空間量化研究有限，較難掌握水生植物的分布現況。本研究以花蓮地區為例，結合現地調查資料與環境因子，採用 MaxEnt 方法進行物種分布模型 (SDM) 與疊加物種分布模型 (S-SDM)，初步建立潛在棲地預測架構，透過空間量化分析瞭解花蓮地區水生植物物種分布與環境因子的關聯性，以及潛在分布之空間。研究結果顯示，最暖季降雨量、最暖月最高溫與乾季降水量為主要影響水生植物物種分布之環境因子。潛在棲地則主要分布於吉安鄉與壽豐鄉，另於新城鄉、光復鄉、瑞穗鄉與玉里鎮交界等局部範圍亦可能為適合水生植物生長之空間。本研究為概念式驗證分析，嘗試針對花蓮地區水生植物潛在環境進行評估，並為未來濕地研究與調查提供參考方向。本研究資料雖有限制，然所建立之模型架構可作為水生植物保育空間規劃的初步依據。未來建議擴增樣本數與物種類群，納入水質、光照、底質與時序性資料，並可嘗試考量物種間交互關係進行建模，提升模型生態解釋力與預測應用潛力，進一步建立水生植物保育之空間治理基礎。Wetlands play a crucial role not only in water quality regulation, carbon storage, and flood mitigation, but also in supporting aquatic plant communities that are essential to wetland ecosystems. However, in Taiwan, systematic spatial quantitative studies on aquatic plants and their environmental drivers remain limited, making it difficult to understand the current distribution of aquatic plant species.This study focuses on the Hualien region, integrating field survey data and environmental variables to apply the MaxEnt method for Species Distribution Modeling (SDM) and Stacked Species Distribution Modeling (S-SDM). A preliminary framework for potential habitat prediction was established to quantitatively analyze the spatial relationships between aquatic plant distribution and environmental factors, as well as to identify potential distribution areas.The results indicate that precipitation of the warmest quarter, maximum temperature of the warmest month, and precipitation of the driest quarter are the primary environmental factors influencing the distribution of aquatic plant species. Potential habitats are mainly concentrated in Ji'an and Shoufeng Townships, with additional suitable areas possibly located in parts of Xincheng, Guangfu, Ruisui, and Yuli Townships. This research serves as a conceptual validation analysis, aiming to evaluate the potential environment for aquatic plants in the Hualien region and provide a reference for future wetland research and surveys. Although the data used in this study are limited, the modeling framework established can serve as a preliminary basis for spatial planning in aquatic plantconservation. Future efforts are recommended to expand the number of samples and species groups, incorporate variables such as water quality, light availability, substrate type, and temporal dynamics, and consider species interactions in modeling to enhance the ecological interpretability and predictive applicability of the models, thereby contributing to the spatial governance foundation for aquatic plant conservation.