物种灭绝是全球最严重的生态问题之一, 直接威胁着人类社会的可持续发展(Pimm et al, 2014)。人类活动造成的物种灭绝速度已经远远超过新物种产生的速度, 人类正在对全球生物多样性产生前所未有的和毁灭性的影响(Wake & Vredenburg, 2008; Teller et al, 2015; Humphreys et al, 2019)。全球气候变化使物种面临更加严峻的生存危机(Jackson et al, 2009; Verstraete et al, 2009; Urban, 2015)。迄今为止规模最大的植物灭绝调查发现, 1900年至今全球种子植物正以每年3个物种的速率减少, 是自然条件下灭绝速率的500倍之多(Brondizio et al, 2019; Humphreys et al, 2019)。
极小种群野生植物是指野外种群数量极少、极度濒危、随时有灭绝危险; 生境要求独特、生态幅狭窄; 潜在基因价值不清楚、其灭绝将引起基因流失、生物多样性降低的种群(国政和臧润国, 2013)。据《全国极小种群野生植物拯救保护工程规划(2011- 2015)》报道, 我国受威胁的极小种群野生植物超过4,000种, 其中1,000多种处于濒危状态, 受威胁的种类占全部种类的15%-20%。我国的极小种群野生植物往往只有少数几个甚至一个种群, 且生境受到直接或者间接破坏, 种群生存受到严重威胁, 种群个体数下降, 某些种群的个体数量已经低于最小可存活种群数(minimum viable populations, MVP), 面临极大的灭绝风险(臧润国等, 2016)。一些极小种群野生植物的种群结构和生境受到严重破坏, 只生长在植物园里或极少量存在于野外, 依靠其自身的能力来恢复种群的生存力及种群数量的可能性微乎其微, 事实上已属于“功能性灭绝”。因此, 明确极小种群野生植物的致濒因素, 预测其生存动态已经成为极小种群野生植物保护的当务之急(Guisan et al, 2013)。
近年的一些研究不仅试图了解种群大小对种群维持的影响, 而且还尝试分析种群大小下降的原因, 从而掌握种群衰退的过程和机理(Beissinger & McCullough, 2002; Willi et al, 2006; Hoffmann et al, 2017)。物种濒危机制研究已从过去的现象描述以及单一的种群生态学和群体遗传学研究, 发展成为多学科相互交叉和渗透的综合性研究, 并且取得了令人鼓舞的进展(Fisher & Owens, 2004; Aguilar et al, 2006; Griffith et al, 2016; Koons et al, 2016; Lowe et al, 2017)。然而, 针对物种濒危的关键环节——种群衰退过程的研究仍然十分有限(Frankham et al, 2002)。针对濒危植物的研究大多是以单个物种为研究对象, 研究物种的一个或几个濒危环节, 如繁殖、存活、遗传多样性等(Willi & Hoffmann, 2009; Li et al, 2012; Castro et al, 2015), 整合植物种群濒危因素及灭绝概率的定量研究亟待加强。
种群生存力分析(population viability analysis, PVA)是指导保护计划制定和评估生物多样性管理的有效方法(Brigham, 2003)。基于实际调查数据与模型模拟, 种群生存力分析不仅可以对种群在一定时间内灭绝的概率进行预测, 还可评估不同致危因素对种群生存力的影响大小。种群生存力分析与物种保护策略的制定密切相关, 定量分析使得结果更加严谨可靠, 并可结合随机性因素同时处理多类别数据, 为多目标保护提供规划(Akçakaya & Sjögren- Gulve, 2000; Pe’er et al, 2013)。然而, 极小种群野生植物由于种群数量极少, 经典的种群生存力分析方法面临较大挑战。本文首先对当前种群生存力的基本方法进行简要介绍, 在此基础上分析经典种群生存力分析方法在极小种群野生植物种群研究中的局限性, 并对极小种群野生植物生存力研究中潜在的方向和研究途径进行探讨。
1 种群生存力分析的主要方法
种群生存力分析是将实际调查数据与模型相结合, 通过分析与模拟, 对种群生活史、种群增长率、种群大小和结构等进行研究, 预测种群在一定时间内的生存概率(Menges, 2000; 彭少麟等, 2002)。已有研究表明, 自然或人为因素导致的环境变化、生物间互作都可影响种群的生存力(Beissinger & McCullough, 2002; Kolb, 2008; Tang et al, 2011; Castro et al, 2015)。此外, 当种群数量下降到一定程度时, 漂变以及近亲交配的几率大大升高, 等位基因丢失、近交衰退、累积的突变负荷和种内杂交都会导致遗传变异丢失, 种群适合度降低, 影响适应力(Frankham et al, 2002; Willi et al, 2006; Li et al, 2012)。因此, 植物种群生存力受到非生物环境、生物环境及遗传等胁迫因素的影响而发生改变(表1)。根据种群所受关键胁迫的差异, 本文将种群生存力分析的经典模型归纳为以下3类: 生境模型、种群统计学模型以及遗传模型(表2)。
表1 种群生存力的影响因素
Table 1
| 影响因素 Factors | 对种群的影响 Effects on population |
|---|---|
| 生境变化 Habitat changes | |
| 温度/降水的变化 Changes in temperature or precipitation | 生境的可利用性、生物物候、种群的生长、繁殖以及迁移 Habitat availability, biological phenology, population growth, reproduction, and migration |
| 生境破碎化 Habitat fragmentation | 生存、繁殖、迁移、定植等 Survival, reproduction, migration, colonization, etc. |
| 侵蚀、滑坡、土地利用变化、富营养化 Erosion, landslides, land-use change, and eutrophication | 生境的可利用性、植被结构、种间关系 Habitat availability, vegetation structure, and interspecific relationships |
| 人为因素如滥伐、城市化、土地清理等 Artificial impacts such as deforestation, urbanization, land clearing | 生境的可利用性、植被结构、生存、繁殖、迁移、定植 Habitat availability, vegetation structure, survival, reproduction, migration, and colonization |
| 生物间互作 Biological interaction | |
| 传粉昆虫减少或环境变化导致植物花期与传粉昆虫活动时期不同步 Loss of pollinators or asynchronism between flowering period and pollinators’ activity period caused by environmental change | 繁殖 Reproduction |
| 种内竞争、共生生物的选择偏好 Intraspecific competition and preferences of symbiotic organisms | 繁殖 Reproduction |
| 外来种的入侵 Invasion of alien species | 种间关系、竞争强度、种群对生境的优先权 Interspecies relationships, competition intensity, and population priorities over habitats |
| 植食性动物的迁入 Invasion of herbivores | 生长、繁殖 Growth and reproduction |
| 遗传结构改变 Genetic structural changes | |
| 种群数量少, 分布范围狭窄 Small population and narrow distribution | 漂变、近亲交配 Drift and inbreeding |
| 等位基因丢失、近交衰退 Loss of alleles and inbreeding depression | 遗传变异丢失 Loss of genetic variation |
表2 种群生存力分析的主要方法
Table 2
| 模型 Models | 具体内容 Details |
|---|---|
| 生境模型 Habitat models | |
| 专家系统的概念模型 Conceptual models based on expert opinion | 通过专家评估种群所处环境的关键变量与种群生长适宜性的关系, 获取不同生境斑块的生境适宜性指数, 构建生境适宜性地图, 进而评估种群在整个分布区域的生存力。 Experts evaluate the relationship between the key variables of the environment and the growth suitability of the population, obtain the habitat suitability index of different habitat patches, construct a habitat suitability map, and then evaluate the population’s viability in the entire distribution area. |
| 多元关联分析方法 Multivariate association methods | 多元关联分析整合多类型数据, 寻找种群生存力与各生境要素之间的相关关系, 还可运用多元距离度量创建生境地图, 评估种群生存力。常用多元关联方法有相关分析、典范对应分析(CCA)、生态位因子分析(ENFA)等。 Multivariate association analysis integrates multiple types of data to find the correlation between population viability and habitat elements. Multivariate distance measures can also be used to create habitat maps to assess population viability. Commonly used multiple correlation methods including correlation analysis, canonical correspondence analysis (CCA), and ecological niche factor analysis (ENFA). |
| 回归分析 Regression analysis | 构建种群统计学特征与环境变量之间的线性或非线性关系, 寻找不同变量对种群特征的影响大小。回归分析主要包括广义线性模型(GLM)和广义可加模型(GAM)。 Regression analysis constructs a linear or non-linear relationship between population demographics and environmental variables, and evaluates the effects of multiple variables on population viability. Regression analysis mainly includes generalized linear model (GLM) and generalized additive model (GAM). |
| 种群统计模型 Population demographic models | |
| 扩散近似模型 Diffusion approximation model | 一种非结构的种群生存力分析方法。扩散近似模型利用时间尺度上的种群数量变化来估计种群随机增长率的均值及方差, 在此基础之上评估种群的维持概率。 An unstructured PVA approach. Diffusion approximation model uses a time series of population counts to estimate the mean and variance of the stochastic population growth rate, then predict the probability of persistence. |
| 矩阵模型 Matrix model | 植物种群生存力分析最常用的模型。此类模型关注不同年龄/大小的个体的繁殖率、死亡率的差异。矩阵模型通过存活率和繁殖率计算不同阶段间的转移概率, 可描述不同阶段的个体数量变化, 进而预测种群生存力。 The most commonly used model for plant PVA. Matrix model accounts for difference in rates of reproduction and mortality among individuals of different ages or sizes. Matrix model can describe how the number of individuals in each class changes from one year to the next by using the vital rates to calculate transition probabilities, and then predict population viability. |
| 积分投影模型 Integral projection model (IPM) | 利用个体大小、年龄、出生、死亡等种群特征来预测种群动态。与矩阵模型受限于生活史阶段划分误差不同, 积分投影模型可通过积分处理更多的、离散的种群状态及时空尺度的环境变化。 IPM uses population characteristics such as individual size, age, birth and mortality to predict population dynamics. Unlike the matrix model, IPM can accommodate more, discrete population stages and environmental changes in space and time through integration. |
| 遗传学模型 Genetic model | |
| 近交-种群大小模型 Inbreeding-population size model | 基于种群大小、遗传多样性以及适合度, 构建近交衰退与种群大小之间的迭代模型, 进而预测种群动态。 This model predicts population dynamics by constructing an iterative model between inbreeding decline and population size based on population size, genetic diversity, and fitness. |
1.1 生境模型
确定物种的适宜生境是应用生态学的基础, 也是制定保护措施的核心。监测种群生境状况可获取与种群生活史的各个阶段匹配的环境信息和数据(Foll & Gaggiotti, 2006), 这些信息有助于评估种群面临的威胁, 还可确定保育储备方案的适当与否(Schleuning & Matthies, 2009)。生境模型不仅在空间上整合了关于种群分布、生境偏好、生境斑块间扩散以及干扰发生的信息(Early et al, 2008), 而且融合了不同学科的研究方法, 从基于专家系统的概念模型(Gray et al, 1996), 到多元关联分析、回归分析模型等(Guisan et al, 1999; Hampton et al, 2013), 生境模型在逐步完善, 并为种群的有效管理与保护提供理论依据。虽然利用充足的数据对种群生存力进行精确预测较难实现, 但生境模型提供了良好的方法来整合已知信息, 用以评价管理方案以及评估生境适宜性(Wiegand et al, 2017)。
不同生境模型由于其自身的特点而适合不同的情形, 因此在模型选取时应综合考虑预测能力、模型复杂程度、估计误差以及模型的可解释性等因素。
1.2 种群统计学模型
种群生存力是种群在其生活史的各个阶段与外界干扰发生密切交互作用的共同结果(Brook et al, 2000), 建立干扰-生存力模型是量化生存力和致危因素的有效途径(Menges, 2000)。种群统计学模型关注干扰条件下种群统计学特征的变化趋势。20世纪90年代发展起来的一般模型(如扩散近似模型、年龄结构模型)通过量化不同威胁因素对种群统计学特征的影响, 对它们的重要性进行评价, 来寻找种群的关键致危因素(Dennis et al, 1991; Morris & Conservancy, 1999; Fox & Gurevitch, 2000)。随着种群统计学数据的积累, 研究者开始建立基于扩散时间的消退模型, 主要是在模型中引入出生率与死亡率在时间上的变化, 并考虑种群统计学参数的随机性, 在此基础上预测种群灭绝的概率(Morris & Conservancy, 1999; Clark, 2003; Jacquemyn et al, 2007)。
追踪种群动态的计数模型与基于个体命运预测种群动态的个体模型均为种群动态模拟提供了很好的解决方法(Thomson & Schwartz, 2006; Grimm & Railsback, 2013)。矩阵模型结合了这两种模型的优点, 被广泛用于种群动态模拟和种群生存力分析中(Pfister & Stevens, 2003)。然而, 建立矩阵模型会面临一个重要问题, 即如何准确地将个体按照年龄、大小或阶段进行划分? 积分投影模型(integral projection model, IPM)则假定种群中的个体在某一个或几个数量性状上连续分布, 避免了矩阵模型中对个体状态的随意划分, 同时还能降低参数维度(Ellner & Rees, 2006)。此外, 采用具有高斯误差项的随机指数增长过程模型可以同时对多个随机种群过程(年龄结构、密度制约以及空间结构)进行模拟, 进而预测种群的灭绝概率(Holmes et al, 2007)。
1.3 遗传学模型
濒危种群中遗传变异的减少将导致近交衰退、远交衰退以及进化可塑性丧失等一系列严重后果(Li et al, 2012; Zhang et al, 2012; Masso et al, 2016)。将遗传学信息与种群生存力分析模型相结合, 有助于从种群内在的固有特性对种群维持机制及灭绝风险进行分析及预测。Burgman和Lamont (1992)利用种群大小下降与近交效应之间的理论联系研究了近交衰退对种群稳定性的影响。该研究假定近交系数与种子数之间呈负相关, 模拟了近交衰退与种群大小之间的耦合关系。虽然此模型中存在一些不符合实际的假设, 比如假定有效种群大小为种群中的成年个体数、近交效应呈线性变化等, 但其开创性地整合并评估了遗传因素和个体数量对种群持续的影响。在种群生存力分析中, 若种群大小、遗传多样性和适合度的数据较为充足, 则可建立更为明确的遗传效应模型, 在模型中考虑繁殖、近交及其交互作用, 分析不同大小种群中各个效应的相对贡献(Hoffmann et al, 2017)。此外, 通过关联不同种群的遗传多样性与种群大小以及适合度也可评定遗传对种群稳定性与生存力的影响(Leimu et al, 2006)。
2 极小种群野生植物生存力研究面临的挑战
2.1 植物种群生存力分析困难
当前, 种群生存力的方法与模型多集中于动物种群, 而植物种群特有的一些种群生活史过程可能导致现存种群生存力分析方法存在缺陷(Menges, 2000)。例如, 当前种群生存力分析模型均假设了明晰的种群生活史循环, 但种子休眠(Kalisz & Mcpeek, 1992)、幼苗周期性增补(Menges & Dolan, 1998)、无性系增长(Ying et al, 2018)等植物种群特性可能使得此类分析方法受到一定的限制。在针对极小种群野生植物生存力与维持机制的研究中, 应重新构建整合了植物种群特殊生活史过程及其生境信息的模型。
2.2 极小种群统计学参数估计偏差
种群生存力分析的主要步骤是先对研究种群进行抽样调查, 根据抽取的样本信息对种群的生长率、繁殖率、死亡率等种群统计学参数进行估计, 并在此基础上建立模型。在估计这些参数时, 通常要求大样本、正态性、样本间相互独立等前提条件。然而, 极小种群样本数量极少, 且个体之间存在强烈的相关性, 单个关键个体的消亡可能会对整个种群的延续造成严重影响, 这导致传统参数统计方法的前提条件几乎无法满足, 盲目采用参数统计方法进行估计可能使得结果存在极大的误差。
2.3 生境破碎化造成严重隔离
在环境胁迫较弱时, 种群通过生理适应就可以承受环境变化带来的影响。在更强烈的胁迫下, 种群中的个体只能依靠自身体内的耐受基因来维持, 不具有环境胁迫耐受基因的个体将被淘汰。随着胁迫强度的增加, 环境选择作用将导致种群的基因频率发生变化。同时, 隔离将影响种群间的基因流动, 被隔离的种群由于无法获得来自相邻种群的适应性基因所产生的拯救效应而加速消亡(Zhang et al, 2012)。极小种群野生植物由于受到自身内部的遗传多样性丢失、种群间基因交流隔断和外界环境胁迫等多种因素共同作用而进入灭绝旋涡, 灭绝风险增加(Li et al, 2012; 阮咏梅等, 2012; Masso et al, 2016)。
3 极小种群野生植物生存力分析研究展望
3.1 基于小样本的非统计分析方法
由于某些极小种群野生植物的个体数量极少, 所能获取的个体信息已经无法完整地反映种群的特征。此外, 野外观测及采样过程中也会产生误差。此时, 基于参数统计的假设来构建模型可能具有较大的偏差。对于此类极小种群, 可考虑采用基于小样本的非统计分析方法, 该方法主要是对观测采样过程中个体的有关信息进行分析, 以先验概率分布为基础, 根据经验参照统计不确定度的方法对参数进行估计(夏新涛和王中宇, 2006)。非统计分析方法不以大数定律和中心极限定理为基础, 在处理实际问题时对数据的分布和样本量的大小没有特殊要求, 而且在大样本的情况下, 处理结果与参数统计方法吻合。小样本非统计分析方法主要包含灰色系统理论(邓聚龙, 1987)、贝叶斯理论(韦来生, 2016)、模糊集合理论(陈水利等, 2005)、信息熵理论(Han et al, 2012)、人工神经网络(李航, 2012)、蒙特卡洛方法以及自助法(周志华, 2015)等。下面对灰色系统理论、贝叶斯方法以及自助法进行简要介绍, 其余方法可参阅相关文献获取详细信息。
3.1.1 灰色系统理论
灰色系统理论认为虽然客观系统表象复杂, 数据凌乱, 但其本质上存在一种有规律的驱动因素, 数据间存在内在联系(邓聚龙, 1987)。通过对原始数据的适当处理(累加生成、累减生成等), 就能发现数据的内在规律。通过累加生成以后, 任意的非负数列、摆动数列均可以转化成递增数列, 从而降低了原始数据的随机性, 突出了其趋势项。例如, 在极小种群野生植物生存力分析中, 若已获取个体的N个特征(株高、胸径、叶面积等)的多年连续观测数据, 则可建立灰色系统模型GM(0, N)。在利用最小二乘法对模型的参数进行估计后, 即可运用模型对极小种群野生植物的种群动态进行预测。可以看出, 灰色系统模型对数据的样本量并无硬性要求, 因此在极小种群野生植物生存力分析中有着相比于参数统计估计方法更高的精确度。
3.1.2 贝叶斯方法
贝叶斯统计理论在估计随机分布的参数时, 认为待估参数是一个存在概率分布的随机变量。贝叶斯统计认为概率是人们对随机事件的信任程度, 故称为主观概率。具体地, 贝叶斯统计通常假设一个先验分布, 反映了人们对待估参数的主观概率。在小样本估计的过程中, 需要利用参数的历史资料或先验知识确定先验分布, 再根据先验分布和样本信息来确定后验分布(韦来生, 2016)。后验分布综合了先验分布和样本的信息, 可以做出较先验分布更加合理的估计(Johnson & Fritz, 2014)。在进行极小种群野生植物的种群统计学参数估计时, 可根据种群的历史动态确定先验分布。若缺乏历史数据, 也可利用群落中其他物种的参数分布作为先验分布。在确定先验分布以及根据样本信息获取似然函数后, 利用贝叶斯方法可确定后验分布的概率密度函数,即可对参数的均值、方差、协方差以及置信区间进行计算。
3.1.3 自助法
自助法(bootstrap)是利用现有的有限数据去模拟未知分布的一种方法。通过有放回的均匀抽样, 自助法能够对抽样估计的准确性(标准误、置信区间等)进行比较好的评价, 而且它几乎能对任何抽样分布的统计量进行估计。自助法可以分为参数自助法和非参数自助法两种。参数自助法假设总体分布或总体分布的形式已知, 利用样本估计出总体分布的参数, 再从参数化的分布中进行采样, 类似于蒙特卡洛方法。而非参数自助法则是从样本中直接进行重抽样。在极小种群野生植物的种群参数估计的过程中, 可选取一个小于样本数量n的抽样数m, 每次有放回地抽取m个个体, 重复若干次后可利用抽取的样本信息估计出总体的分布, 进而确定极小种群野生植物种群特征的均值、方差、置信区间等统计量。
3.2 环境变化下的种群适应力量化
在快速变化的环境中, 种群有3种可能的结局: 迁徙到更适合的生境中去, 通过适应当前位置的新环境来维持, 或者灭绝(Aitken et al, 2008)。植物种群由于固着生活习性, 难以在短时间内迁移到适合的空间。因此, 适应力对植物种群在环境胁迫下的维持以及预测植物种群生存力具有重要意义。适应力是指生物对特定的环境变化的响应能力, 通常包含两部分: 首先是个体水平上的表型可塑性导致生理上的适应变化, 其次是自然选择使得种群的遗传结构发生变化(Willi et al, 2006; Willi & Hoffmann, 2009; Hansen et al, 2012)。种群可以通过改变表型表达或调整其遗传结构来适应环境的变化(Bay et al, 2017)。可塑性适应只能在有限的范围内应对环境的变化, 而遗传适应能够容许种群在更广的范围上维持(Chevin et al, 2010)。
种群的适应力由表型变异、选择的强度、繁殖力、种间竞争等因素决定。目前, 生态学家和进化生物学家已经开始尝试量化生态因素和遗传驱动因素对适应力的影响(Blanquart et al, 2013; Lowe et al, 2017)。通过监测同一起源的物种在不同生态环境中的特性可评估种群的适应力, 如北半球温带乔木展示出物候学上的渐变群和沿温度梯度生长, 体现了局部适应的存在。这种方法在气候变化的大背景下极具价值, 利用气候因素在空间梯度上的变化能够模拟未来的气候变化, 通过寻找空间尺度上的变异, 可以在时间尺度上进行预测(Eizaguirre & Baltazar-Soares, 2014)。响应函数和转移函数是量化适应力的有效方法(Kurmaz et al, 2011)。响应函数描述沿气候梯度分布的种群的表现, 通过采集同一种群在不同分布点上的性状数据来分析种群在不同环境下的适应情况。然而, 此类实验不仅耗时费力, 而且成本昂贵。转移函数模型很好地弥补了响应函数的这个缺点。与响应函数比较不同分布点上的相同种群不同, 转移函数通过采用一个响应距离, 比较同一分布点上不同种群之间的差异, 这样就降低了在不同分布点采样的成本, 同时也避免了不同位点采样造成的误差。
种群的空间自相关性、迁徙历史、基因流、适应延迟以及种间竞争等因素在种群的适应过程中也扮演着重要的角色。若最优适合度的变化速率低于某一临界值, 种群可通过维持稳定的适应率存活下来。这一临界值由种群的永久性遗传变异、个体繁殖率、有效种群大小、环境随机性以及选择强度等因素共同决定(Aitken et al, 2008)。若超过这个阈值, 种群的适应速率将不能跟上最优适合度的变化速率, 适合度随着适应延迟的增加而降低, 最终导致种群灭绝。基因流、不同环境来源的迁徙、进化时间尺度上的局部气候变化都将影响种群的适应(Aitken & Whitlock, 2013)。因此, 在未来的研究中, 探索种群适应力及其弹性与环境要素之间的耦合关系有助于在时空尺度上对种群的生存力进行预测。
4 总结
极小种群野生植物的致危原因复杂多样, 内外因素的共同作用使得极小种群野生植物的生存力受到严重威胁。基于数据和模型, 种群生存力分析可了解极小种群野生植物所受关键胁迫, 预测环境变化下种群的命运, 指导种群保护决策的制定。通过对多因素、多尺度生态学过程的模拟, 可对种群濒危因素以及生存力有更加清晰的认识与估计。本文首先对经典种群生存力分析方法进行介绍, 并讨论了其潜在的适用范围和局限性。对于极小种群野生植物种群数量极少的情况, 传统统计学方法的参数估计存在较大的有偏性, 在此本文提出可以采用基于小样本的非统计分析方法对种群参数和种群动态进行模拟和预测。此外, 考虑种群的适应力也有助于更加精准地模拟环境变化下的种群动态与灭绝概率。综上, 在极小种群野生植物生存力分析中考虑小样本非统计分析方法以及环境变化下种群的适应力有利于突破传统生存力分析方法统计功效较低的缺点, 量化不同因素对极小种群野生植物生存力的影响程度, 进而预测种群生存力, 可对极小种群的保护措施提供理论指导。
致谢：感谢中国林业科学研究院森林生态环境与保护研究所臧润国研究员的支持与鼓励。
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Knowledge of genetic diversity and fine-scale spatial genetic structure (SGS) at different age stages of small isolated populations is important for understanding population dynamics and developing effective conservation measures for fragmented populations. In this study, we used a small, isolated population of Sinojackia huangmeiensi as a case study to investigate the change in the levels of genetic diversity and SGS at different age stages. We mapped and genotyped 60 adults,175 saplings, 198 seedlings using eight microsatellite markers to detect the genetic diversity, SGS and pollen and seed dispersal patterns in a 80 m × 160 m transect located in an original secondary forest surrounded by farmlands. No significant differences in genetic diversity were found among the three life stages, and a significant heterozygote deficiency in the population may result from substantial biparental inbreeding. We found significant fine-scale spatial structure at different age stages within 10 m, suggesting that seed dispersal mainly occurred near a mother tree. Seed dispersal distance and pollen dispersal distance were 9.07±13.38 and 23.81±23.60 m, respectively, and ‘L’ shaped curves were observed in both pollen dispersal and seed dispersal patterns. The spatial distribution of the different age stages is most likely the result of little overlap in seed rain, self-thinning, biparental inbreeding and limited gene flow. Our results have important implications for conservation of extant population of S. huangmeiensis. Measures for promoting pollen flow and increasing survival rate of seedlings should be considered for in situ conservation. The presence of SGS in this fragmented population implies that seeds for ex situ conservation should be collected from trees at least 10 m apart to reduce genetic similarity between neighboring individuals.
黄梅秤锤树孤立居群的遗传多样性及其小尺度空间遗传结构
DOI:10.3724/SP.J.1003.2012.10011
URL
[本文引用: 1]
Knowledge of genetic diversity and fine-scale spatial genetic structure (SGS) at different age stages of small isolated populations is important for understanding population dynamics and developing effective conservation measures for fragmented populations. In this study, we used a small, isolated population of Sinojackia huangmeiensi as a case study to investigate the change in the levels of genetic diversity and SGS at different age stages. We mapped and genotyped 60 adults,175 saplings, 198 seedlings using eight microsatellite markers to detect the genetic diversity, SGS and pollen and seed dispersal patterns in a 80 m × 160 m transect located in an original secondary forest surrounded by farmlands. No significant differences in genetic diversity were found among the three life stages, and a significant heterozygote deficiency in the population may result from substantial biparental inbreeding. We found significant fine-scale spatial structure at different age stages within 10 m, suggesting that seed dispersal mainly occurred near a mother tree. Seed dispersal distance and pollen dispersal distance were 9.07±13.38 and 23.81±23.60 m, respectively, and ‘L’ shaped curves were observed in both pollen dispersal and seed dispersal patterns. The spatial distribution of the different age stages is most likely the result of little overlap in seed rain, self-thinning, biparental inbreeding and limited gene flow. Our results have important implications for conservation of extant population of S. huangmeiensis. Measures for promoting pollen flow and increasing survival rate of seedlings should be considered for in situ conservation. The presence of SGS in this fragmented population implies that seeds for ex situ conservation should be collected from trees at least 10 m apart to reduce genetic similarity between neighboring individuals.
Habitat change and plant demography: Assessing the extinction risk of a formerly common grassland perennial
DOI:10.1111/cbi.2008.23.issue-1 URL [本文引用: 1]
Population structure of relict Metasequoia glyptostroboides and its habitat fragmentation and degradation in south-central China
DOI:10.1016/j.biocon.2010.09.003
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[本文引用: 1]
The relict dawn redwood Metasequoia glyptostroboides Hu et Cheng is endemic to the region bordering Hubei and Hunan provinces and Chongqing municipality in south-central China. It is critically endangered. We investigated its population size and age structure, and provided a comparison to the study of Chu and Cooper (1950), documenting the changes of the past 60 years. Our study included all the known wild individuals of the species as well as analyses of the floristic diversity of their habitats. In the last 41 years, habitat changes have effectively ended recruitment of M. glyptostroboides and have reduced species richness in direct response to human disturbance, as shown on several indices. The remaining specimens ranged from roughly 41 to some 265 years for an average near 95 years, with heights of 12-51 m averaging 27 m. The detrimental activities of human residents include cultivation of profitable plants in the understory, selective cutting, harvesting of wood for fuel, and thoroughgoing collection of seeds for sale on the active market. Under present environmental conditions and land use, the dawn redwood will not maintain its natural range in south-central China. Our work detailing the plant populations in the habitats of this living fossil will be useful in establishing priorities for its recovery and conservation. (C) 2010 Elsevier Ltd.
Conservation of passively dispersed organisms in the context of habitat degradation and destruction
DOI:10.1111/1365-2664.12379 URL [本文引用: 1]
Using population count data to assess the effects of changing river flow on an endangered riparian plant
DOI:10.1111/j.1523-1739.2006.00376.x URL [本文引用: 1]
Accelerating extinction risk from climate change
DOI:10.1126/science.aaa4984 URL [本文引用: 1]
Climate and desertification: Looking at an old problem through new lenses
DOI:10.1890/080119 URL [本文引用: 1]
Ar. we in the midst of the sixth mass extinction? A view from the world of amphibians
Spatiall. explicit metrics of species diversity, functional diversity, and phylogenetic diversity: Insights into plant community assembly processes
DOI:10.1146/annurev-ecolsys-110316-022936 URL [本文引用: 1]
Demographic factors and genetic variation influence population persistence under environmental change
DOI:10.1111/jeb.2008.22.issue-1 URL [本文引用: 2]
Limit. to the adaptive potential of small populations
DOI:10.1146/annurev.ecolsys.37.091305.110145 URL [本文引用: 3]
A novel non-statistical theory and its applications to hypothesis testing
非统计假设检验原理及其应用
The effects of clonal integration on the responses of plant species to habitat loss and habitat fragmentation
DOI:10.1016/j.ecolmodel.2018.06.016 URL [本文引用: 1]
Genetic footprints of habitat fragmentation in the extant populations of Sinojackia (Styracaceae): Implications for conservation
DOI:10.1111/j.1095-8339.2012.01277.x
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[本文引用: 2]
Sinojackia, a member of the family Styracaceae, is an endangered genus endemic to China. The number of populations and population size of Sinojackia have decreased sharply because of habitat fragmentation and destruction. We studied the genetic diversity of extant populations in two different cohorts (adult and seedling) using eight microsatellite markers to investigate the genetic footprints of habitat fragmentation in four recognized Sinojackia spp. and to develop appropriate conservation measures. Data on intrapopulational genetic diversity suggest that Sinojackia populations have maintained relatively high levels of genetic diversity and low levels of genetic differentiation despite severe fragmentation. The high genetic diversity may be explained by the outcrossing mating system and high longevity of Sinojackia spp. The amount of genetic variation is not associated with population size, which was also supported by bottleneck analysis. In the species studied, there was no significant difference in the genetic diversity between the two cohorts analysed. However, inbreeding increased from adult trees to seedling populations, suggesting that the higher proportion of biparental inbreeding in the recent generations of seedlings is the result of restricted current genetic flow caused by habitat fragmentation. Average seed set per population was not significantly correlated with either population size or genetic diversity. Conservation management should aim to monitor inbreeding and outbreeding depression carefully to ensure the in?situ and ex?situ conservation of Sinojackia spp. (c) 2012 The Linnean Society of London, Botanical Journal of the Linnean Society, 2012, , .
Conservation and restoration for typical critically endangered wild plants with extremely small population
典型极小种群野生植物保护与恢复技术研究
