生物入侵的影响是否准确可知?
中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
Biological invasions: Are their impacts precisely knowable or not?
State Key Laboratory of Vegetation and Environmental Change, Chinese Academy of Sciences, Beijing 100093
通讯作者: * E-mail:weiminghe@ibcas.ac.cn
编委: 冯玉龙
责任编辑: 黄祥忠
收稿日期: 2020-01-8 接受日期: 2020-02-20 网络出版日期: 2020-02-20
基金资助: |
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Corresponding authors: * E-mail:weiminghe@ibcas.ac.cn
Received: 2020-01-8 Accepted: 2020-02-20 Online: 2020-02-20
生物入侵常常带来一系列负面影响, 如物种快速丧失、巨大经济损失、生态公益急剧降低、不可逆环境破坏等。正是这些负面影响引起科技界、政府和公众对生物入侵的极大关注。因此, 准确量化生物入侵的影响非常重要。然而, 广泛使用的生物入侵影响评估方法存在两个严重缺陷: 一是缺乏真实对照, 二是包含非入侵效应。这两个缺陷使得人们对生物入侵影响的了解相对粗略。为此, 作者提出两点建议: 一是在实验条件下设置真实对照, 二是考虑同步对照。评估方法的完善将有助于人们更加准确地理解生物入侵的影响。
关键词:
Biological invasions are ubiquitous worldwide and have demonstrable negative impacts (e.g., rapid biodiversity losses, substantial economic losses, decreased ecosystem services, and irreversible environmental damage). Quantifying the impacts of biological invasions is among the core questions in invasion biology, and also a practical issue in ecosystem management. Existing approaches have two serious shortcomings: (1) the absence of true controls and (2) the presence of confounding non-invasion effects. These approaches, therefore, cannot precisely quantify the impacts of biological invasions in the field. Here, I explicitly highlight these long-overlooked drawbacks when quantifying invasion impacts, and propose two potential solutions: (1) creating true controls at the beginning of studies and (2) considering a “synchronous control” over the course of an experiment. These solutions might help us to precisely understand the impacts of biological invasions.
Keywords:
本文引用格式
何维明 (2020)
Weiming He (2020)
生物入侵(biological invasions)是一个复杂的分阶段过程, 在这个过程中, 一种或多种外来生物在自然或人为作用下从天然分布范围进入新分布范围并逐步成为优势物种(Lockwood et al, 2013)。生物入侵常常导致一系列负面影响, 如物种快速丧失、巨大经济损失、生态公益急剧降低、不可逆环境破坏等(Richardson, 2011; Lockwood et al, 2013)。正是这些负面影响引起科技界、政府和公众对生物入侵的极大关注(Elton, 1958; Gaertner et al, 2009; Vilà et al, 2011; Powell et al, 2013; Ricciardi et al, 2013)。因此, 准确量化生物入侵影响既是一个入侵生物学研究的核心理论问题, 又是一个生态系统管理的实际问题。
总体而言, 量化生物入侵影响的思路主要有两种: 一是比较不同年份相同季节的相同地点, 二是比较相同年份相同季节的不同地点(Gaertner et al, 2009; Vilà et al, 2011; Powell et al, 2013; Ricciardi et al, 2013)。这两种思路在本质上是相似的, 即确定入侵后与入侵前可度量的特征差异(图1, 比较立地A1与立地A0)。事实上, 关于立地A0的数据是缺乏的, 这是因为自然条件下人们无法事先知晓外来生物入侵何地并开展相应调查。所以, 人们常常采取空间替代时间量化生物入侵的影响: 即比较入侵地和与其相邻的非入侵地(图1, 成对比较立地A1与立地B1)。这种替代隐含一个重要假设: 立地B1与立地A0相同。这种假设自然引出一个基本的问题: 立地B1是否可以替代立地A0 (图1, Q-I)?
图1
图1
生物入侵的影响评估示意图(左)和植物群落相似度(右)。在左图中, 单箭头表示立地A和B从时间t0到t1的转变, 双箭头表示立地之间的比较, 实线表示两个立地是否可替换这个问题。C: 比较; Q: 问题; Invader: 外来入侵生物。在右图中, 不同字母表示1 m × 1 m植物群落相似性与10 m × 10 m植物群落相似性之间存在差异(P < 0.05)。
Fig. 1
Graphic illustration of quantifying biological invasion impacts (left panel), and the related comparisons of plant community similarity coefficients between sites (right panel). At the left panel, single arrows indicate a shift of sites from t0 to t1, double arrows indicate a comparison between two sites, and solid lines indicate a question about whether two sites are substitutable. C: Comparison; Q: Question. At the right panel, different letters demonstrate a significant difference in similarity coefficients between 1 m × 1 m quadrats and 10 m × 10 m quadrats at the P < 0.05 level.
由于立地A0数据缺乏, 而立地B1可实际测量, 因此两者之间无法直接比较, 只能间接推断。为此, 作者选择刚被外来植物入侵但无入侵植物的自然立地B0作为中间变量。基于5年对12个自然立地B0的监测发现, 立地B0与立地B1之间的群落相似度在0.44-0.58之间(图1, 均值为0.51)。这种变化主要源于快速物种丢失和增加导致的物种周转(Yu & He, 2019)。因此, 立地B1不能代替立地B0 (图1, Q-II)。另外, 我们能否在入侵前确定相同立地(图1, Q-III)? 作者调查了12个1 m × 1 m的样方和16个10 m × 10 m的样方。结果表明小样方之间的群落相似度为0.25-0.92 (均值为0.48), 大样方之间的群落相似度为0.40-0.82 (均值为0.61), 前者的相似度显著小于后者(图1)。因此, A0与B0是有差异的, 人们无法事先选择完全相同的成对立地。既然立地B1不能代替立地B0, 而且立地B0也不能替代立地A0, 那么无法推断立地B1是否能够替代立地A0。因此, 当采用成对立地比较量化入侵影响时, 最大的问题是可能出现假对照。
当用立地B1粗略代替A0时, 又会出现什么问题呢? 如上分析, 立地B随时间明显变化(从立地B0转变为立地B1)。同样, 立地A本身在没有外来入侵生物的情况下也会随时间发生变化, 这种时间变化已经被广泛的生态学研究证实。在自然条件下简单比较立地A1与立地B1同时包含两种效应: 生物入侵影响和立地本身变化。通过实验直接比较入侵后与入侵前来量化生物入侵影响时面临的严重问题是实验单元的变化也包含非入侵效应。
综上所述, 广泛使用的生物入侵影响评估方法可能具有两个缺陷: 一是缺乏真实的对照(即假对照), 二是存在混合的非入侵效应。这些缺陷使得人们很难在自然条件下准确量化生物入侵的影响(即只能粗略地估计这种影响)。那么, 怎样才能准确量化生物入侵的影响呢? 实验条件下评估生物入侵影响需考虑以下两点: 第一, 在野外实验中设置相同或相似的立地A0和立地B0, 然后在立地A0中引入外来物种并连续观测。第二, 考虑“同步对照(synchronous control)”。由于立地A0为被入侵立地(invaded site)而立地B0为未被入侵立地(uninvaded site), 因此同时连续观察立地A1和立地B1, 通过比较A1与B1的差异确定生物入侵的影响。立地B1为同步对照立地, 因为立地A1和立地B1的目标特征被同步测定。通过野外实验评估生物入侵影响需要考虑以下三点: 第一, 立地同质性; 第二, 随机化设计; 第三, 增加重复数。
需要指出的是, 作者并非否定已有的关于评估生物入侵影响的研究, 而是希望通过指出相关研究中存在的一些重要但仍需完善的问题来进一步完善生物入侵影响的评估方法。全球化加剧生物入侵(van Kleunen et al, 2015), 这既是挑战也是入侵生物学进一步发展的动力。评估方法的完善有助于人们更加准确地理解生物入侵影响, 为有效防控入侵生物提供参考依据。
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