Geographical distribution of the dispersal ability of alien plant species in China and its socio-climatic control factors

Zhou, Quanlai; Wu, Jing; Cui, Xue; Li, Xuehua; Liu, Zhimin; Musa, Ala; Ma, Qun; Yu, Haibin; Liang, Wenju; Jiang, Shaoyan; Wang, Yongcui

doi:10.1038/s41598-021-85934-8

Cited by 12 publications

(7 citation statements)

References 51 publications

(60 reference statements)

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“…Previous studies showed that the combination of environmental and anthropogenic factor variables can effectively predict the distribution pattern of invasive alien plants [ 15 , 31 , 32 , 33 , 37 , 50 ]. For example, Li and Shen selected seven climatic variables and three socio-economic variables to analyze their role in shaping the distribution patterns of IAPs [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

Distribution Patterns and Determinants of Invasive Alien Plants in China

Chen

Zhang

Liu

et al. 2023

Plants

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In recent years, invasive alien plants (IAPs) have caused serious ecological disasters and economic losses in China. This study combined three IAP species richness-related indices (species richness of IAPs, first records of IAPs, and the relative species richness of IAPs), as well as indices reflecting distribution and dispersal patterns (average similarity coefficient of IAPs) and invasiveness (average risk score of IAPs), to conduct an integrated regional-invasion risk assessment based on the principal component analysis (PCA) method. Partial least-squares (PLS) regression was conducted to explore the explanatory power of 12 environmental and anthropogenic factors on different invasion indices. The results indicated that coastal provinces and Yunnan had high IAP introduction risk, as well as high synthetic-risk scores. The dispersal of IAPs in mid-latitude provinces should be particularly prevented. For species richness of IAPs, more environmental factors with variable importance for the project (VIP) values higher than 1 were retained in the optimal model, reflecting the importance of environmental filtering on IAPs. Visitors were the most important predictor for first records of IAPs. Compared to species richness (R2 = 79.5%), first records were difficult to predict (R2 = 60.4%) and were influenced by anthropogenic factors. There was spatial distribution congruence of various families of IAPs. Generally, the correlations of the residuals of species richness were still significant, with 0.421 (p < 0.05) as the lowest Pearson correlation coefficient, which indicated that external factors could not fully explain the spatial distribution congruence. These findings could enrich the relevant research on IAP invasion mechanisms and provide suggestions for regional IAP detection and response.

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Section: Methodsmentioning

confidence: 99%

Distribution Patterns and Determinants of Invasive Alien Plants in China

Chen

Zhang

Liu

et al. 2023

Plants

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“…However, to the best of our knowledge, very few seed datasets are publicly available. Most of its publicly available datasets are plant species, pest and disease datasets 11 , 12 . Many scholars have also done a lot of research on seed image classification.…”

Section: Background and Summarymentioning

confidence: 99%

A dataset for fine-grained seed recognition

Yuan,

Lv,

Dong

et al. 2024

Sci Data

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The research of plant seeds has always been a focus of agricultural and forestry research, and seed identification is an indispensable part of it. With the continuous application of artificial intelligence technology in the field of agriculture, seed identification through computer vision can effectively promote the development of agricultural and forestry wisdom. Data is the foundation of computer vision, but there is a lack of suitable datasets in the agricultural field. In this paper, a seed dataset named LZUPSD is established. A device based on mobile phones and macro lenses was established to acquire images. The dataset contains 4496 images of 88 different seeds. This dataset can not only be used as data for training deep learning models in the computer field, but also provide important data support for agricultural and forestry research. As an important resource in this field, this dataset plays a positive role in modernizing agriculture and forestry.

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“…It is well known that the geographic ranges of species can span 12 orders of magnitude, and closely related species may vary enormously in their range (Brown et al, 1996). Many factors contribute to this variation, although dispersal ability and energy requirements associated with establishment and persistence in varying habitats have been considered to be the two most important ones (Morin and Chuine, 2006;Zhou et al, 2021). Given that seeds are the predominately mobile stage of sessile plants and seed mass generally reflects the amount of energy that a seed contains and its mobility (Coomes and Grubb, 2003), it seems likely that seed mass could play an important role in governing the geographic ranges of seed plants.…”

Section: Introductionmentioning

confidence: 99%

Seed traits and phylogeny explain plants' geographic distribution

Chen

Burgess²,

He³

et al. 2022

Biogeosciences

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Abstract. Understanding the mechanisms that shape the geographic distribution of plant species is a central theme of biogeography. Although seed mass, seed dispersal mode and phylogeny have long been suspected to affect species distribution, the link between the sources of variation in these attributes and their effects on the distribution of seed plants are poorly documented. This study aims to quantify the joint effects of key seed traits and phylogeny on species distribution. We collected the seed mass and seed dispersal mode from 1426 species of seed plants representing 501 genera of 122 families and used 4 138 851 specimens to model species distributional range size. Phylogenetic generalized least-squares regression and variation partitioning were performed to estimate the effects of seed mass, seed dispersal mode and phylogeny on species distribution. We found that species distributional range size was significantly constrained by phylogeny. Seed mass and its intraspecific variation were also important in limiting species distribution, but their effects were different among species with different dispersal modes. Variation partitioning revealed that seed mass, seed mass variability, seed dispersal mode and phylogeny together explained 46.82 % of the variance in species range size. Although seed traits are not typically used to model the geographic distributions of seed plants, our study provides direct evidence showing seed mass, seed dispersal mode and phylogeny are important in explaining species geographic distribution. This finding underscores the necessity to include seed traits and the phylogenetic history of species in climate-based niche models for predicting the response of plant geographic distribution to climate change.

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Geographical distribution of the dispersal ability of alien plant species in China and its socio-climatic control factors

Cited by 12 publications

References 51 publications

Distribution Patterns and Determinants of Invasive Alien Plants in China

Distribution Patterns and Determinants of Invasive Alien Plants in China

A dataset for fine-grained seed recognition

Seed traits and phylogeny explain plants' geographic distribution

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