Highly patterned primary succession after fluvial deposition of mining waste

N. Nikolic
{"title":"Highly patterned primary succession after fluvial deposition of mining waste","authors":"N. Nikolic","doi":"10.5937/univtho10-24743","DOIUrl":null,"url":null,"abstract":"This study examined early stages (3-5 years) of spontaneous primary vegetation succession on a model locality drastically altered by long term fluvial deposition of copper tailings in Eastern Serbia. In a large-scale survey, 115 samples of herbaceous vegetation (with a total of 75 species) were harvested from standardized 1m x 1m quadrates, and concomitant soil samples collected and their relevant physicochemical properties analysed. Primary succession depended on the establishment of five pioneer species (Rumex acetosella, Agrostis capillaris, Calamagrostis epigeios, Persicaria lapathifolia and Chenopodium botrys). Unconstrained ordination showed very clear vegetation gradients, significantly correlated with the key soil constraints (from Cu excess to low pH and nutrient deficiency), while the distribution of the five edificatory pioneers showed high degree of dependence on the micro-level habitat conditions. This work demonstrates that in such a complex setup with severe abiotic filtering, sufficient sampling effort can reveal strong patterns in a process commonly considered very stochastic.","PeriodicalId":22896,"journal":{"name":"The University Thought - Publication in Natural Sciences","volume":"9 1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The University Thought - Publication in Natural Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5937/univtho10-24743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This study examined early stages (3-5 years) of spontaneous primary vegetation succession on a model locality drastically altered by long term fluvial deposition of copper tailings in Eastern Serbia. In a large-scale survey, 115 samples of herbaceous vegetation (with a total of 75 species) were harvested from standardized 1m x 1m quadrates, and concomitant soil samples collected and their relevant physicochemical properties analysed. Primary succession depended on the establishment of five pioneer species (Rumex acetosella, Agrostis capillaris, Calamagrostis epigeios, Persicaria lapathifolia and Chenopodium botrys). Unconstrained ordination showed very clear vegetation gradients, significantly correlated with the key soil constraints (from Cu excess to low pH and nutrient deficiency), while the distribution of the five edificatory pioneers showed high degree of dependence on the micro-level habitat conditions. This work demonstrates that in such a complex setup with severe abiotic filtering, sufficient sampling effort can reveal strong patterns in a process commonly considered very stochastic.
在采矿废物的河流沉积后,高度图案化的初级演替
本研究考察了塞尔维亚东部铜尾矿长期河流沉积剧烈改变的一个模式地区的早期(3-5年)自发原始植被演替。在一项大规模调查中,在标准化的1m × 1m方形场地上采集了115个草本植被样本(共75个物种),并收集了伴生土壤样本并分析了其相关的理化性质。主要演替依赖于5个先锋种(Rumex acetosella、Agrostis capillaris、Calamagrostis epigeios、Persicaria lapathifolia和Chenopodium botrys)的建立。无约束排序显示出非常清晰的植被梯度,与关键土壤约束条件(从Cu过量到低pH和养分缺乏)显著相关,而5种启蒙先驱的分布对微观生境条件具有高度依赖性。这项工作表明,在这样一个复杂的设置与严重的非生物滤波,足够的采样努力可以揭示强大的模式,通常被认为是非常随机的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
审稿时长
4 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信