摘要：

日益加剧的环境变化与人类活动严重威胁种群的生存, 因此预测多种胁迫下种群的命运至关重要。种群生存力分析(population viability analysis, PVA)是评估种群所受威胁、灭绝或衰退风险以及恢复可能性的有效方法。基于物种及环境数据和建模, 种群生存力分析能够整合不同类型变量, 为目标物种的保护提供建议。然而, 极小种群野生植物的个体数据难以获取, 种群参数估计困难, 这导致传统种群生存力分析方法在此类种群中的应用存在局限性。在此, 本文提出了极小种群野生植物生存力分析的潜在方法: 小样本非统计分析法及环境变化下的种群适应力分析。小样本非统计分析法有益于提高种群统计学参数的估计精度, 而立足于生态进化生物学的种群生存力研究有助于从生物学机理方面了解和预测种群动态, 为极小种群野生植物的保护提供更适宜的理论指导。

Abstract

Environmental change and anthropogenic disturbance have a significant impact on population persistence. Therefore, it is essential to predict population dynamics under multiple stresses. Population viability analysis (PVA) is an effective method for assessing threats, extinction risk and bottlenecks, and the likelihood of recovery. By combining data and models, PVA accommodates different types of variables and can offer appropriate advice for conservation. However, demographic parameters of Wild Plant with Extremely Small Populations are difficult to estimate, which makes the statistical power of these models quite low. Here, we offer some underlying PVA methods for Wild Plant with Extremely Small Populations using non-statistical theory with small sample sizes and population adaptive potential analysis. Methods based on the non-statistical theory can enhance the accuracy of parameter estimation in small populations, while the eco-evolutionary elements help to uncover mechanisms of population adaptation and predict population dynamics. These methods provide more appropriate guidance for the conservation of Wild Plant with Extremely Small Populations.

Key words: Wild Plant with Extremely Small Populations (WPESP), population viability analysis, non-statistical theory with small sample sizes, adaptive potential

陈冬东, 李镇清 (2020) 极小种群野生植物生存力分析: 方法、问题与展望. 生物多样性, 28, 358-366. DOI: 10.17520/biods.2019179 .

Dongdong Chen, Zhenqing Li (2020) Population viability analysis of Wild Plant with Extremely Small Populations (WPESP): Methods, problems and prospects. Biodiversity Science, 28, 358-366. DOI: 10.17520/biods.2019179 .

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1 种群生存力的影响因素

Table 1 Factors affecting population viability

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

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.

表2 种群生存力分析的主要方法

Table 2 General methods of population viability analysis (PVA)

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.

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