首页> 外文期刊>The Journal of Ecology >Plant fecundity and seed dispersal in spatially heterogeneous environments: models, mechanisms and estimation
【24h】

Plant fecundity and seed dispersal in spatially heterogeneous environments: models, mechanisms and estimation

机译:空间异质环境中的植物繁殖力和种子扩散:模型,机理和估计

获取原文
获取原文并翻译 | 示例
       

摘要

1. Plant fecundity and seed dispersal often depend on environmental variables that vary in space. Hence, plant ecologists need to quantify spatial environmental effects on fecundity and dispersal. 2. We present an approach to estimate and model two types of spatial environmental effects: source effects cause fecundity and dispersal to vary as a function of a source's local environment, whereas path effects depend on all environments a seed encounters during dispersal. Path effects are described by first transforming physical space so that areas of low seed permeability are enlarged relative to others, and then evaluating dispersal kernels in this transformed 'movement space'. 3. Models for source and path effects are embedded into the established inverse modelling (IM) framework. This enables the statistical estimation of environmental effects from easily available data on the spatial distribution of seeds, seed sources and environmental covariates. 4. The presented method is applied to data from a well-studied population of the wind-dispersed Aleppo pine (Pinus halepensis). We use local tree density as an environmental covariate, model fecundity as a function of a tree's basal area, and consider four dispersal kernels: WALD (a closed-form mechanistic model for seed dispersal by wind), log-normal, exponential power and 2Dt. 5. The inclusion of source and path effects of tree density markedly improves IM performance. IM analyses and independent data agree in the parameter range of the mechanistic WALD kernel and in suggesting weak negative density-dependence of fecundity. Of 64 IMs considered, the best four involve the WALD kernel and negative source effects on its shape parameter. The best IM predicts that increasing tree density at the source shortens median dispersal distance while enhancing long-distance dispersal (LDD). Additionally, path effects lead to lower seed permeability of high density areas. These results shed light on the mechanisms by which environmental variation affects fecundity and dispersal of P. halepensis. Moreover, the predicted density-dependent dispersal causes a pronounced lag-phase in simulations of population spread. 6. Synthesis. The presented method can quantify environmental effects on fecundity and dispersal in a wide range of study systems. The movement space concept may furthermore promote a unified understanding of how various organisms move through spatially heterogeneous environments.
机译:1.植物的繁殖力和种子的传播通常取决于空间中变化的环境变量。因此,植物生态学家需要量化空间环境对繁殖力和扩散的影响。 2.我们提出了一种对两种类型的空间环境影响进行估计和建模的方法:源影响导致繁殖力和扩散随源的本地环境而变化,而路径影响取决于种子在扩散过程中遇到的所有环境。通过首先转换物理空间来描述路径效应,以使种子渗透性较低的区域相对于其他区域扩大,然后评估此转换后的“运动空间”中的分散核。 3.用于源效应和路径效应的模型被嵌入到已建立的逆建模(IM)框架中。这样就可以根据有关种子,种子来源和环境协变量的空间分布的容易获得的数据,对环境影响进行统计估计。 4.所提出的方法适用于对风散发的阿勒颇松(Pinus halepensis)进行充分研究的数据。我们使用局部树木密度作为环境协变量,将繁殖力模型作为树木基础面积的函数,并考虑四个扩散核:WALD(风对种子扩散的封闭形式力学模型),对数正态,指数幂和2Dt 。 5.包含树密度的源和路径效应可以显着提高IM性能。 IM分析和独立数据在机械WALD内核的参数范围内,并且在暗示生育力的弱负密度依赖性方面是一致的。在所考虑的64个IM中,最好的四个IM涉及WALD内核和其形状参数的负源效应。最好的IM预测源头上树木密度的增加会缩短中值散布距离,同时增强长距离散布(LDD)。另外,路径效应导致高密度区域的种子渗透性降低。这些结果揭示了环境变化影响哈利法梭菌繁殖力和扩散的机理。此外,在人口扩散的模拟中,预测的依赖密度的扩散导致明显的滞后阶段。 6.合成。提出的方法可以量化环境对繁殖力和分散在广泛的研究系统中的影响。运动空间概念可以进一步促进对各种生物如何在空间异质环境中运动的统一理解。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号