种子的长距离风传播模型研究进展

 植物种子的长距离传播在物种迁移、生物入侵、保护生物学等领域有重要的生态和进化意义。种子传播有很多方式，开阔草原等地区的草本植物和许多热带和温带的树木都是通过风传播种子的。风传播的方式最适合进行种子长距离传播现象的模拟研究。种子的风传播模型是传播生态研究的一个重要领域，尤其是种子的长距离风传播模型，对于外来入侵植物的扩散和破碎化景观中植物种群的基因交流等生态过程研究举足轻重，然而国内鲜见这方面的研究成果。本文综述了种子长距离风传播现象研究的背景和意义，分析了风传播种子模型的基本形式和构成原理，并分别就现象模型和机理模型的相关研究进展进行了总结，同时指出了未来发展的几个重要方向。种子的风传播模型可以分为现象模型和机理模型两类,现象模型按种子传播核心的形式包括短尾模型、偏峰长尾模型和混合传播核心模型，后两者对于长距离传播数据的模拟可以取得很好的效果。机理模型按照模拟机制可分为欧拉对流扩散模型和拉格郎日随机模型两类。本文重点介绍了种子的长距离风传播现象的形成机理和两类机理模型的参数构成和处理方式。适合种子脱落的天气和适合传播的天气的同步性可能是形成种子长距离风传播的一个重要前提，林缘和地表存在的上升气流及大风和暴风中形成的速度梯度都可能对于种子的长距离传播有重要的作用。机理模型的操作因子主要包括生物方面的因子、气象方面的因子和地形方面的因子。同时对目前几个应用比较成功的机理模型进行了简要的介绍和评价，包括倾斜羽毛模型、对流-扩散-下降模型、无掩蔽模型、背景模型、WINDISPER及其改进模型和PAPPUS模型。最后指出，目前在风传播种子的长距离模型研究中，对草本植物种子的传播模拟的投入明显不如树木种子的长距离传播模拟，对于破碎化景观中种子长距离的风传播的研究还存在很大的差距，而对提高机理模型预测能力的高分辨率物理环境数据输入技术的需求则为多学科交叉提供了很好的机会。

ADVANCES IN MODEL CONSTRUCTION OF ANEMOCHORIC SEED LONG_DISTANCE DISPERSAL

Long-distance dispersal (LDD) of plant propagules has significant ecological and evolutionary implications for plant species migrations, biological invasions, conservation biology and many other fields of research. Although seeds can disperse by many different processes, the seeds of many herbaceous species of open grasslands and tree species in temperate and tropic zones are anemochoric, i.e., wind dispersed. Modeling the dispersal of anemochoric seeds, particularly their long distance dispersal, is a major research field because of the importance of this ecological process for understanding such phenomena as the spread of invasive alien plants and gene flow among meta-populations in fragmented landscapes. Our search results indicated that there are no synthesis papers on the LDD of anemochoric seeds. This paper discusses the background and significance of long-distance dispersal of air-borne seeds, analyzes the basic formulas and structures of models of seed dispersal by wind, summarizes recent advances in phenomenological and mechanistic models, and presents future research directions in this field. LDD models of anemochoric seeds are categorized into two major classes: phenomenological models and mechanistic models. Phenomenological models include short-tailed dispersal kernels (SDK), Leptokurtic fat-tailed kernels (LFK) and mixed dispersal kernels (MDK). The LFK and MDK models are most promising for simulating long-distance dispersal of seeds. Mechanical models are categorized into Eulerian advection-diffusion models (EADM) and Lagrangian stochastic models (LSM). The mechanisms of LDD and the major parameters of these two classes of models are a major focus of this paper. Important mechanisms of LDD include synchronization of seed release with suitable weather conditions. and updrafts that occur at forest edges and on the ground surface. Also, gradients of wind speed that form during storms was speculated as being an important mechanism of LDD. Operative factors in wind LDD models include biological, meteorological and topographical factors. We introduce and evaluate a number of models that have been used successfully to model LDD by wind, including tilted plumed model (TPM), advection-diffusion-deposition model (ADDM), no-shelter model (NSM), background model (BM), WINDISPER, modified WINDISPER (MWINDISPER) and PAPPUS. Lastly, the current status of wind LDD model construction is analyzed and some gaps are pointed out. The authors advocate that more effort should be made to construct models for herbaceous species since currently there are many more wind LDD models for tree species. There are many challenges and needs for modelers to link models with empirical field data of fragmented landscapes. Finally, collaborative approaches among researches from different fields are encouraged in order to improve LDD model forecasting especially with regard to increasing the precision of inputs of attributes of the physical environment.