塔里木荒漠河岸林不同生境群落物种多度分布格局

doi:10.17520/biods.2020416

摘要/Abstract

摘要：

为解释塔里木荒漠河岸林群落构建和物种多度分布格局形成的机理, 本文以塔里木荒漠河岸林2个不同生境(沙地、河漫滩) 4 ha固定监测样地为研究对象, 基于两样地物种调查数据, 采用统计模型(对数级数模型、对数正态模型、泊松对数正态分布模型、Weibull分布模型)、生态位模型(生态位优先占领模型、断棍模型)和中性理论模型(复合群落零和多项式模型、Volkov模型)拟合荒漠河岸林群落物种多度分布, 并用K-S检验与赤池信息准则(AIC)筛选最优拟合模型。结果表明: (1)随生境恶化(土壤水分降低), 植物物种多度分布曲线变化减小, 群落物种多样性、多度和群落盖度降低, 常见种数减少。(2)选用的3类模型均可拟合荒漠河岸林不同生境群落物种多度分布格局, 统计模型和中性理论模型拟合效果均优于生态位模型。复合群落零和多项式模型对远离河岸的干旱沙地生境拟合效果最好; 对数正态模型和泊松对数正态模型对洪水漫溢的河漫滩生境拟合效果最优; 中性理论模型与统计模型无显著差异。初步推断中性过程在荒漠河岸林群落构建中发挥着主导作用, 但模型拟合结果只能作为推断群落构建过程的必要非充分条件, 不能排除生态位过程的潜在作用。

关键词: 荒漠河岸林, 生境, 物种多度分布, 模型拟合, 生态过程, 群落构建机制

Abstract

Aims: Species coexistence mechanisms and species abundance distribution patterns at different time and spatial scales have been and may continue to be key issues in community ecology, whereas species abundance distribution is one of the most powerful tools for understanding the mechanisms generating community structures and biodiversity patterns. Studying species abundance distribution patterns in different habitats of forest communities can help to reveal the mechanisms that drive the formation and maintenance of biodiversity. This study took desert riparian forest communities as the research object, and analyzed the difference of species abundance distribution patterns in different habitats, in order to understand the dominant ecological processes of species abundance distribution and reveal assembly mechanism of desert riparian forest communities in extreme arid areas.
Methods: We surveyed two 4-ha desert riparian forests with contrasting inundation regimes and soil properties. We then employed four statistical models (i.e., log-series model, log-normal model, Poisson lognormal distribution model and Weibull distribution model), two niche-based models (i.e., niche preemption model, broken stick model) and two neutrally-based models (i.e., metacommunity zero-sum multinomial distribution model, Volkov model) to fit observed patterns of species abundance distributions for the two communities. We used the K-S test and Akaike information criterion (AIC) to select the best fitting model.
Results: Our results showed that: (1) The species composition and species abundance differed significantly between the two desert riparian forest communities. In the less inundated and drier habitat, the species abundance distribution tended to have less interspecific variation, in addition to lower species diversity, abundance, forest cover, and fewer common species. (2) The statistical models and neutrally-based models performed better than the niche models in fitting species abundance distributions. The metacommunity zero-sum multinomial distribution model was the best-fitting model for the arid sandy habitat far from the river bank. The log-normal model and the Poisson lognormal model were the best-fitting models for the floodplain, whereas the neutral model (i.e., Volkov model) and the two aforementioned statistical models showed similar performance.
Conclusions: We therefore infer that a neutral process played a leading role in the assembly of the desert riparian forest communities. Since the species abundance distribution could be result of joint effect of multiple processes, we can not rule out the potential role of a niche-based process.

Key words: desert riparian forest, habitat, species abundance distribution, model fitting, ecological process, community assembly mechanism

康佳鹏, 韩路, 冯春晖, 王海珍 (2021) 塔里木荒漠河岸林不同生境群落物种多度分布格局. 生物多样性, 29, 875-886. DOI: 10.17520/biods.2020416.

Jiapeng Kang, Lu Han, Chunhui Feng, Haizhen Wang (2021) Species abundance distribution in two riparian forests under contrasting environmental regimes in the Tarim Desert. Biodiversity Science, 29, 875-886. DOI: 10.17520/biods.2020416.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2020416

https://www.biodiversity-science.net/CN/Y2021/V29/I7/875

图/表 7

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	沙地生境 Sandy habitat	河漫滩生境 Floodplain habitat	P	t
土壤质量含水率 Soil mass water content (%)	0.62 ± 0.11^A	21.95 ± 1.23^B	< 0.01	2.01
电导率 Electrical conductivity (μS/cm)	1,819.87 ± 272.90^a	1,105.93 ± 293.60^a	0.09	2.05
pH	8.02 ± 0.03^A	8.20 ± 0.03^B	< 0.01	2.05
土壤有机质 Soil organic matter (g/kg)	2.48 ± 0.30^a	2.74 ± 0.73^a	0.96	2.12
全氮 Total nitrogen (g/kg)	0.18 ± 0.03^a	0.22 ± 0.05^a	0.68	2.14
全磷 Total phosphorus (g/kg)	7.22 ± 0.50^a	7.43 ± 0.38^a	0.97	2.20
碱解氮 Available nitrogen (mg/kg)	6.46 ± 2.74^a	6.95 ± 1.06^a	0.30	2.20
有效磷 Available phosphorus (mg/kg)	105.40 ± 15.07^a	109.62 ± 6.30^a	0.68	2.12
速效钾 Available potassium (mg/kg)	203.56 ± 32.83^a	180.69 ± 34.23^a	0.54	2.12

	沙地生境 Sandy habitat	河漫滩生境 Floodplain habitat	P	t
土壤质量含水率 Soil mass water content (%)	0.62 ± 0.11^A	21.95 ± 1.23^B	< 0.01	2.01
电导率 Electrical conductivity (μS/cm)	1,819.87 ± 272.90^a	1,105.93 ± 293.60^a	0.09	2.05
pH	8.02 ± 0.03^A	8.20 ± 0.03^B	< 0.01	2.05
土壤有机质 Soil organic matter (g/kg)	2.48 ± 0.30^a	2.74 ± 0.73^a	0.96	2.12
全氮 Total nitrogen (g/kg)	0.18 ± 0.03^a	0.22 ± 0.05^a	0.68	2.14
全磷 Total phosphorus (g/kg)	7.22 ± 0.50^a	7.43 ± 0.38^a	0.97	2.20
碱解氮 Available nitrogen (mg/kg)	6.46 ± 2.74^a	6.95 ± 1.06^a	0.30	2.20
有效磷 Available phosphorus (mg/kg)	105.40 ± 15.07^a	109.62 ± 6.30^a	0.68	2.12
速效钾 Available potassium (mg/kg)	203.56 ± 32.83^a	180.69 ± 34.23^a	0.54	2.12

模型类型 Model type	模型名称 Model name	沙地生境 Sandy habitat			河漫滩生境 Floodplain habitat
模型类型 Model type	模型名称 Model name	AIC	D	P	AIC	D	P
统计模型 Statistical model	对数级数模型 Log-series model	59.80	0.20	1.00	227.10	0.36	0.46
	对数正态模型 Log-normal model	63.08	0.20	1.00	220.80	0.18	1.00
	泊松对数正态分布模型 Poisson lognormal distribution model	62.82	0.20	1.00	220.80	0.18	1.00
	Weibull分布模型 Weibull distribution model	62.57	0.20	1.00	222.70	0.18	1.00
生态位模型 Niche model	断棍模型 Broken stick model	63.31	0.40	0.87	251.40	0.55	0.07
生态位模型 Niche model	生态位优先占领模型 Niche preemption model	63.95	0.40	0.87	241.50	0.55	0.07
中性理论模型 Neutral theory model	复合群落零和多项式模型 Metacommunity zero-sum multinomial distribution model	58.70	0.20	1.00	226.10	0.36	0.48
中性理论模型 Neutral theory model	Volkov模型 Volkov model	60.44	0.20	1.00	222.50	0.18	1.00

模型类型 Model type	模型名称 Model name	沙地生境 Sandy habitat			河漫滩生境 Floodplain habitat
模型类型 Model type	模型名称 Model name	AIC	D	P	AIC	D	P
统计模型 Statistical model	对数级数模型 Log-series model	59.80	0.20	1.00	227.10	0.36	0.46
	对数正态模型 Log-normal model	63.08	0.20	1.00	220.80	0.18	1.00
	泊松对数正态分布模型 Poisson lognormal distribution model	62.82	0.20	1.00	220.80	0.18	1.00
	Weibull分布模型 Weibull distribution model	62.57	0.20	1.00	222.70	0.18	1.00
生态位模型 Niche model	断棍模型 Broken stick model	63.31	0.40	0.87	251.40	0.55	0.07
生态位模型 Niche model	生态位优先占领模型 Niche preemption model	63.95	0.40	0.87	241.50	0.55	0.07
中性理论模型 Neutral theory model	复合群落零和多项式模型 Metacommunity zero-sum multinomial distribution model	58.70	0.20	1.00	226.10	0.36	0.48
中性理论模型 Neutral theory model	Volkov模型 Volkov model	60.44	0.20	1.00	222.50	0.18	1.00