基于积分投影模型预测濒危植物景东翅子树的种群动态

doi:10.16258/j.cnki.1674-5906.2022.08.004

生态环境学报 ›› 2022, Vol. 31 ›› Issue (8): 1530-1536.DOI: 10.16258/j.cnki.1674-5906.2022.08.004

基于积分投影模型预测濒危植物景东翅子树的种群动态

袁春明¹^,²^,³(), 杨国平⁴, 耿云芬¹^,²^,³, 张珊珊¹^,²^,³^,^*()

1.云南省林业和草原科学院,云南昆明 650204
2.国家林业和草原局云南珍稀濒特森林植物保护和繁育重点实验室,云南昆明 650204
3.云南省森林植物培育与利用重点实验室,云南昆明 650204
4.中国科学院西双版纳热带植物园,云南勐腊 666303

收稿日期:2022-02-17 出版日期:2022-08-18 发布日期:2022-10-10
通讯作者: * 张珊珊（1984年生）,女,副研究员,博士,主要从事保护生物学研究工作。E-mail: lkyzss@126.com
作者简介:袁春明（1964年生）,男,研究员,博士,主要从事森林生态、保护生物学和森林防火研究。E-mail: yuanchunming1017@163.com
基金资助:
国家自然科学基金项目(31760176);国家自然科学基金项目(31960278)

Prediction of Population Dynamics of the Endangered Plant Pterospermum kingtungense Using Integral Projection Models

YUAN Chunming¹^,²^,³(), YANG Guoping⁴, GENG Yunfen¹^,²^,³, ZHANG Shanshan¹^,²^,³^,^*()

1. Yunnan Academy of Forestry and Grassland, Kunming 650204, P. R. China
2. Key Laboratory of Rare and Endangered Forest Plants of National Forestry and Grassland Administration, Kunming 650204, P. R. China
3. Key Laboratory for Forest Silviculture and Resources Development of Yunnan Province, Kunming 650204, P. R. China
4. Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla 666303, P. R. China

Received:2022-02-17 Online:2022-08-18 Published:2022-10-10

摘要/Abstract

摘要：

了解种群动态及其关键驱动因子对濒危物种的保护至关重要。景东翅子树为国家Ⅱ级重点保护野生植物,按IUCN红色名录濒危等级和标准划分为极危种。生境的丧失及其片断化是该物种濒危的主要威胁因素。该研究主要回答以下2个问题：（1）不同大小的片断和连续森林中景东翅子树的种群动态如何?（2）驱动景东翅子树种群动态变化的关键因子是什么?在不同大小片断（5 hm²和15 hm²）和连续森林中分别设立3个50 m×100 m固定样地,调查景东翅子树所有个体的胸径（幼苗和幼树为地径）、繁殖产出、个体的存活及幼苗的补充情况。基于连续3年的种群统计调查及实验数据,建立不同时间段（2018—2019、2019—2020和2020—2021年）上述3种生境中景东翅子树的积分投影模型,同时应用弹性分析方法量化种群统计参数对种群增长率的相对贡献。结果表明,（1）不同时段不同生境中景东翅子树的种群生命率（或统计过程）存在一定差异。3种生境中景东翅子树的死亡个体数为0—2 plant∙a^-1∙hm^-2,年开花个体数为0—4 plant∙a^-1∙hm^-2,新增个体数为0—1.3 plant∙a^-1∙hm^-2。（2）除5 hm²片断在2020—2021年间受人为影响导致较大下降外,3种生境中景东翅子树种群的增长率等于或趋近于1,说明其种群是稳定的。（3）3个时段3种生境中景东翅子树种群的存活和生长对种群增长率的贡献占99.2%以上,说明种群的存活和生长是驱动种群增长、维持种群稳定的关键因子。研究认为如果没有较大的人为干扰和环境的波动如严重干旱等,3种生境中景东翅子树种群可维持稳定。

关键词: 生境片断化, 濒危植物, 景东翅子树, 种群生命率, 种群动态, 积分投影模型, 弹性分析

Abstract:

Understanding population dynamics and its key drivers is vital for the protection of endangered species. Pterospermum kingtungense has been recognized as grade II national key protected plant species and listed as critically endangered species in terms of the IUCN red list categories and criteria. Habitat loss and fragmentation are the main threats to endangered species. The present study aims to answer the following questions: (1) how are the population dynamics of P. kingtungense in fragments of different sizes and continuous forests? (2) what are the key factors driving the population dynamics of P. kingtungense? We established three 50 m×100 m permanent sampling plots within each of the habitats of forest fragments of different sizes (5 hm², 15 hm²) and continuous forest. All P. kingtungense individuals were measured for DBH (diameter at breast height, but ground diameter for seedlings and saplings), reproductive outputs, survival, and seedling replenishment. Based on three-year annual censuses and experimental data, nine integral projection models were constructed for the above three habitats for three transition years (2018-2019, 2019-2020 and 2020-2021), and the relative contribution of the population demographic parameters to the population growth rate was quantified by the elastic analysis method. Our results showed that there are some certain differences in the demographic process (or vital rates) of P. kingtungense populations in different habitats and in different transition years. In the three habitats, the number of dead individuals, flowering plants and new recruitments of P. kingtungense were 0-2, 0-4 and 0-1.3 plant∙a^-1∙hm^-2, respectively. The population growth rate of P. kingtungense was equal to or approaching one, suggesting that P. kingtungense populations were stable in the different-size fragmented and continuous forests, except for the 5 hm² fragment for the transition year 2020-2021, which had a greater decrease in the population growth rate due to human disturbance. The contribution of survival and growth of P. kingtungense populations to their population growth rate accounted for more than 99.2% in the three habitats for the three transition years, suggesting that population survival and growth are the key factors driving population growth and maintaining population stability. The study suggests that if there is no large anthropogenic disturbance and environmental fluctuation (such as serious drought), the P. kingtungense populations can maintain stability in the three habitats.

Key words: habitat fragmentation, endangered plant, Pterospermum kingtungense, vital rate, population dynamics, integral projection model (IPM), elasticity analysis

中图分类号:

Q145.1
X176

袁春明, 杨国平, 耿云芬, 张珊珊. 基于积分投影模型预测濒危植物景东翅子树的种群动态[J]. 生态环境学报, 2022, 31(8): 1530-1536.

YUAN Chunming, YANG Guoping, GENG Yunfen, ZHANG Shanshan. Prediction of Population Dynamics of the Endangered Plant Pterospermum kingtungense Using Integral Projection Models[J]. Ecology and Environment, 2022, 31(8): 1530-1536.

图/表 6

参考文献 23

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模型组分 Model component	生境 Habitat	时间段* Transition year	回归模型及参数** Regression model and parameter
存活概率 Survival probability	5 hm²片断	a	s(x)=logit^-1 (2.662+0.019x)
		b	s(x)=logit^-1 (25.570)
		c	s(x)=logit^-1 (2.847-0.053x)
	15 hm²片断	a	s(x)=logit^-1 (3.000+0.271x)
		b	s(x)=logit^-1 (26.570)
		c	s(x)=logit^-1 (0.403+7.178x)
	连续森林	a	s(x)=logit^-1 (4.046+0.0647x)
		b	s(x)=logit^-1 (2.352+0.123x)
		c	s(x)=logit^-1(26.570)
生长 (时间t+1时个体大小) Growth (sizes of individuals at t+1)	5 hm²片断	a	g(y, x)=0.082+1.000x
		b	g(y, x)=0.085+1.003x
		c	g(y, x)=0.283+1.003x
	15 hm²片断	a	g((y, x)=0.066+1.007x
		b	g(y, x)=0.029+1.003x
		c	g(y, x)=0.030+1.003x
	连续森林	a	g(y, x)=0.148+1.003x
		b	g(y, x)=0.142+1.002x
		c	g(y, x)=0.104+1.002x
开花概率 Flowering probability	5 hm²片断	a	f₀(x)=logit^-1 (-5.772+0.223x)
		b	f₀(x)=logit^-1 (-5.772+0.223x)
		c	f₀(x)=logit^-1 (-5.772+0.223x)
	15 hm²片断	a	f₀(x)=logit^-1 (-5.633+0.283x)
		b	f₀(x)=logit^-1 (-5.816+0.272x)
		c	f₀(x)=logit^-1 (-5.772+0.223x)
	连续森林	a	f₀(x)=logit^-1 (-3.838+0.057x)
		b	f₀(x)=logit^-1 (-4.332+0.063x)
		c	f₀(x)=logit^-1 (-4.304+0.062x)

模型组分 Model component	生境 Habitat	时间段* Transition year	回归模型及参数** Regression model and parameter
存活概率 Survival probability	5 hm²片断	a	s(x)=logit^-1 (2.662+0.019x)
		b	s(x)=logit^-1 (25.570)
		c	s(x)=logit^-1 (2.847-0.053x)
	15 hm²片断	a	s(x)=logit^-1 (3.000+0.271x)
		b	s(x)=logit^-1 (26.570)
		c	s(x)=logit^-1 (0.403+7.178x)
	连续森林	a	s(x)=logit^-1 (4.046+0.0647x)
		b	s(x)=logit^-1 (2.352+0.123x)
		c	s(x)=logit^-1(26.570)
生长 (时间t+1时个体大小) Growth (sizes of individuals at t+1)	5 hm²片断	a	g(y, x)=0.082+1.000x
		b	g(y, x)=0.085+1.003x
		c	g(y, x)=0.283+1.003x
	15 hm²片断	a	g((y, x)=0.066+1.007x
		b	g(y, x)=0.029+1.003x
		c	g(y, x)=0.030+1.003x
	连续森林	a	g(y, x)=0.148+1.003x
		b	g(y, x)=0.142+1.002x
		c	g(y, x)=0.104+1.002x
开花概率 Flowering probability	5 hm²片断	a	f₀(x)=logit^-1 (-5.772+0.223x)
		b	f₀(x)=logit^-1 (-5.772+0.223x)
		c	f₀(x)=logit^-1 (-5.772+0.223x)
	15 hm²片断	a	f₀(x)=logit^-1 (-5.633+0.283x)
		b	f₀(x)=logit^-1 (-5.816+0.272x)
		c	f₀(x)=logit^-1 (-5.772+0.223x)
	连续森林	a	f₀(x)=logit^-1 (-3.838+0.057x)
		b	f₀(x)=logit^-1 (-4.332+0.063x)
		c	f₀(x)=logit^-1 (-4.304+0.062x)

时间段 Transition year	生境 Habitat
时间段 Transition year	5 hm²片断 5 hm² fragment	15 hm²片断 15 hm² fragment	连续森林 Continuous forest
2018-2019	0.985294	1.000000	0.999899
2019-2000	1.000573	1.000573	0.999995
2020-2021	0.908672	1.000000	1.000362

时间段 Transition year	生境 Habitat
时间段 Transition year	5 hm²片断 5 hm² fragment	15 hm²片断 15 hm² fragment	连续森林 Continuous forest
2018-2019	0.985294	1.000000	0.999899
2019-2000	1.000573	1.000573	0.999995
2020-2021	0.908672	1.000000	1.000362

时间段 Transition year	生境 Habitat
	5 hm²片断 5 hm² fragment		15 hm² 片断 15 hm² fragment		连续森林 Continuous forest
	P	F	P	F	P	F
2018-2019	1.000	0.000	1.000	0.000	1.000	0.000
2019-2000	0.999	0.001	0.999	0.001	1.000	0.000
2000-2021	0.992	0.008	1.000	0.000	0.999	0.001

基于积分投影模型预测濒危植物景东翅子树的种群动态

Prediction of Population Dynamics of the Endangered Plant Pterospermum kingtungense Using Integral Projection Models

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