菌根共生网络嵌套性判定的零模型选择

doi:10.17521/cjpe.2019.0065

摘要/Abstract

摘要：

零模型是判定网络嵌套性的重要依据, 菌根共生关系网络经常出现高度非对称性, 该文通过探究矩阵非对称变化对基于不同零模型构建方法的网络嵌套性的影响, 试图为非对称网络零模型的选择提供依据。结果表明: 不同零模型保守性不同, 增加限定条件减少零模型构建过程中的自由空间, 高度限定条件易导致第II类错误。高度非对称网络会增加基于完全随机(r00)零模型的矩阵温度(NT)偏离、降低配对重叠度(NODF)偏离, 标准化指数z-score值显示网络非对称增加后有助于NT和NODF显著性判定。行或列限定对非对称网络嵌套性判定的影响存在差异, 列限定(c0)的网络嵌套性判定对网络非对称性变化的响应规律与r00零模型的响应趋势基本一致, 具有更低的嵌套性偏离和标准差值。行限定(r0, 包括行列限定(backtrack))零模型NT值和NT偏移随矩阵非对称性的变化保持稳定, 较之c0零模型在高度非对称网络中呈现更低的NODF偏离值。选用完全随机和限定零模型相结合的方法, 有助于更加准确判断非对称网络是否具有嵌套结构。高度非对称网络嵌套性判定中对行属性特征比较敏感, 不同非对称性网络间嵌套性水平相比较时选用r0零模型要优于r00和c0零模型。

关键词: 关系网络, 嵌套性, 零模型, 网络非对称性

Abstract:

Aims Null model is an important basis for nesting judgment. Highly asymmetric structures often appear in plant symbolic fungal networks. This study aims to explore the influence of matrix asymmetric changes on network nesting judgment.
Methods The study was conducted based on various null model construction methods.
Important findings Constraints vary with changing null models, with reducing null space when additional qualifications were added during null model establishment. Highly constrained nulls are prone to causing type II errors. Highly asymmetric networks increase matrix temperature (NT) deviation based on random (Equiprobable- equiprobable, r00) null model while reducing overlap and decreasing fill (NODF) deviation. Values of z-score show that highly asymmetric networks contribute to the significant determination level of NT and NODF. The impacts on the judgment of nestedness of asymmetric networks differ between row and column fixed null models. The effects of network asymmetry change on nesting detection based on column constrained (c0) nulls are similar to that of random null model, but with smaller nesting deviation and standard deviations. No significant differences in both NT and NT deviations were observed among different asymmetry networks based on the row fixed (r0) nulls, with a lower NODF deviation in highly asymmetric network based on c0 nulls. To more accurately determine whether the asymmetric networks would have nested structures, we recommend using a combination of random and constrained null models. Our results also demonstrate that the r0 null model performs better than either the r00 null model or the c0 null model when comparing nesting level of different asymmetric networks.

Key words: interaction network, nestedness, null model, web asymmetry

林力涛, 马克明. 菌根共生网络嵌套性判定的零模型选择. 植物生态学报, 2019, 43(7): 611-623. DOI: 10.17521/cjpe.2019.0065

LIN Li-Tao, MA Ke-Ming. Selection of null models in nestedness pattern detection of highly asymmetric mycorrhizal networks. Chinese Journal of Plant Ecology, 2019, 43(7): 611-623. DOI: 10.17521/cjpe.2019.0065

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2019.0065

https://www.plant-ecology.com/CN/Y2019/V43/I7/611

图/表 10

表1 嵌套性度量指标特征

Table 1 Characteristics of various nestedness metrics

指标 Index	反映特征 Underlying feature	下限保守 Bottom boundary conservative	上限保守 Top boundary conservative	零模型保守 Null model conservative	存在上限 Top limit
矩阵温度 matrix temperature (NT)	矩阵中异常点数量、位置 Relative abundance and position of unexpected absences or presences in a matrix	是 Yes	是 Yes	否 No	是 Yes
配对重叠度 nestedness metric based on overlap and decreasing fill (NODF)	矩阵配对重叠中非子集行列的数量及位置 Percentage and position of columns (rows) overlaps with other columns (rows)	是 Yes	是 Yes	是 Yes	是 Yes
嵌套性偏移 Nestedness deviation	网络与零模型的距离 Distance deviates from null models	是 Yes	否 No	是 Yes	是 Yes
标准化指数 Standardized effect size	网络达到显著水平的难易程度 Significance of a network deviates from null models	是 Yes	否 No	是 Yes	否 No

图1 基于完全嵌套(A, B)和均匀分布(C, D)矩阵构建的不同零模型嵌套性特征(平均值±标准偏差)。Backtrack, 行列限定; c0, 列限定; IM, 初始矩阵; r0, 行限定; r00, 完全随机。***, 0.001水平显著。

Fig. 1 Absolute values of nestedness from null models constructed based on fully nested (A, B) and uniformly distributed matrices (C, D) (mean ± SD). Backtrack, fixed row-fixed column; c0, equiprobable row-fixed column; IM, initial matrix; r0, fixed row- equiprobable column; r00, equiprobable row-equiprobable column. ***, significant at 0.001 level.

图2 矩阵形状变动对矩阵嵌套性指数影响。矩阵形状, 矩阵列数/矩阵行数。Backtrack, 行列限定; c0, 列限定; r0, 行限定; r00, 完全随机。

Fig. 2 Effects of changes in matrix shape on nestedness metrics. Matrix shape, number of columns/number of rows. Backtrack, fixed row-fixed column; c0, equiprobable row-fixed column; r0, fixed row-equiprobable column; r00, equiprobable row-equiprobable column.

图3 非对称性变化对构建二分零模型矩阵温度(NT)和NT偏移的影响(平均值±标准偏差)。Backtrack, 行列限定; c0, 列限定; r0, 行限定; r00, 完全随机。IM, 初始矩阵; 5 times, 5倍列合并网络; 10 times, 10倍列合并网络。

Fig. 3 Effects of matrix asymmetric variations on matrix temperature (NT) and NT deviation based on different binary matrix construction methods (mean ± SD). Backtrack, fixed row-fixed column; c0, equiprobable row-fixed column; r0, fixed row-equiprobable column; r00, equiprobable row-equiprobable column. IM, Initial matrix; 5 times, 5 times column merge network; 10 times, 10 times column merge network.

图4 非对称性变化对矩阵温度标准化指数的影响。Backtrack, 行列限定; c0, 列限定; r0, 行限定; r00, 完全随机。IM, 初始矩阵; 5 times, 5倍列合并网络; 10 times, 10倍列合并网络。

Fig. 4 Effects of matrix asymmetric variations on the standardized effect size (z-score) of matrix temperature (NT). Backtrack, fixed row-fixed column; c0, equiprobable row-fixed column; r0, fixed row-equiprobable column; r00, equiprobable row-equiprobable column. IM, initial matrix; 5 times, 5 times column merge network; 10 times, 10 times column merge network.

图5 非对称性变化对构建二分零模型配对重叠度(NODF)和NODF偏移影响(平均值±标准偏差)。Backtrack, 行列限定; c0, 列限定; r0, 行限定; r00, 完全随机。IM, 初始矩阵; 5 times, 5倍列合并网络; 10 times, 10倍列合并网络。

Fig. 5 Effects of matrix asymmetric variations on nestedness metric based on overlap and decreasing fill (NODF) and NODF deviation based on different binary matrix construction methods (mean ± SD). Backtrack, fixed row-fixed column; c0, equiprobable row-fixed column; r0, fixed row-equiprobable column; r00, equiprobable row-equiprobable column. IM, Initial matrix; 5 times, 5 times column merge network; 10 times, 10 times column merge network.

图6 非对称性变化对矩阵配对重叠度标准化指数的影响。Backtrack, 行列限定; c0, 列限定; r0, 行限定; r00, 完全随机。IM, 初始矩阵; 5 times, 5倍列合并网络; 10 times, 10倍列合并网络。

Fig. 6 Effects of matrix asymmetric variations o z-scores of on the standardized effect size (z-score) of nestedness metric based on overlap and decreasing fill (NODF). Backtrack, fixed row-fixed column; c0, equiprobable row-fixed column; r0, fixed row-equiprobable column; r00, equiprobable row- equiprobable column. IM, Initial matrix; 5 times, 5 times column merge network; 10 times, 10 times column merge network.

图7 矩阵随机化程度对嵌套性度量指标的影响。Square, 对称网络, 行列数30/30; Asy, 非对称网络, 行列数5/55。随机化程度, 网络中无序单元格的数量/单元格总数量。随机程度包含4:100 (%)共计97水平, 每水平50个重复, 共计4 850矩阵。

Fig. 7 Effects of the level of matrix randomness on nestedness metrics. Square, symmetric networks with rows and columns 30/30; Asy, asymmetric networks with rows and columns 5/55. Randomness, percentage of disordered cells deviates from fully nested matrix. Data contains a total of 4 850 matrices, with 4:100 (%) randomness degree 97 levels of, 50 repetitions per level.

图8 矩阵温度(NT)与配对重叠度(NODF)间的相关性。Square, 对称网络, 行列数30/30; Asy, 非对称网络, 行列数5/55。随机化程度, 网络中无序单元格的数量/单元格总数量。随机程度包含4:100 (%)共计97水平, 每水平50个重复, 共计4 850矩阵。

Fig. 8 Correlation between matrix temperature (NT) and nestedness metric based on overlap and decreasing fill (NODF). Square, symmetric networks with rows and columns 30/30; Asy, asymmetric networks with rows and columns 5/55. Randomness, percentage of disordered cells deviates from fully nested matrix. Data contains a total of 4 850 matrices, with 4:100 (%) randomness degree 97 levels of, 50 repetitions per level.

图9 矩阵随机化程度对嵌套标准化指标影响。Square, 对称网络, 行列数30/30; Asy, 非对称网络, 行列数5/55。随机化程度, 网络中无序单元格的数量/单元格总数量。随机程度包含4:100 (%)共计97水平, 每水平50个重复, 共计4 850矩阵。NT, 矩阵温度; NODF, 配对重叠度。

Fig. 9 Effects of the level of matrix randomness on the standardized effect size of nestedness. Square, symmetric networks with rows and columns 30/30; Asy, asymmetric networks with rows and columns 5/55. Randomness, percentage of disordered cells deviates from fully nested matrix. Data contains a total of 4 850 matrices, with 4:100 (%) random-ness degree 97 levels of, 50 repetitions per level. NT, matrix temperature; NODF, nestedness metric based on overlap and decreasing fill.

参考文献 37

[1]	Almeida-Neto M, Guimarães P, Guimarães Jr PR, Loyola RD, Ulrich W ( 2008). A consistent metric for nestedness analysis in ecological systems: Reconciling concept and measurement. Oikos, 117, 1227-1239. DOI URL
[2]	Atmar W, Patterson BD ( 1993). The measure of order and disorder in the distribution of species in fragmented habitat. Oecologia, 96, 373-382. DOI URL PMID
[3]	Atmar W, Patterson BD ( 1995). The Nestedness Temperature Calculator: A Visual Basic Program, Including 294 Presence-absence Matrices. AICS Research, University Park, NM and Field Museum, Chicago.
[4]	Bahram M, Harend H, Tedersoo L ( 2014). Network perspectives of ectomycorrhizal associations. Fungal Ecology, 7, 70-77. DOI URL
[5]	Bahram M, Põlme S, Kõljalg U, Tedersoo L ( 2011). A single European aspen ( Populus tremula) tree individual may potentially harbour dozens of Cenococcum geophilum ITS genotypes and hundreds of species of ectomycorrhizal fungi. FEMS Microbiology Ecology, 75, 313-320. DOI URL PMID
[6]	Bascompte J ( 2010). Structure and dynamics of ecological networks. Science, 329, 765-766. DOI URL PMID
[7]	Bascompte J, Jordano P, Melian CJ, Olesen JM ( 2003). The nested assembly of plant-animal mutualistic networks. Proceedings of the National Academy of Sciences of the United States of America, 100, 9383-9387. DOI URL PMID
[8]	Beiler KJ, Simard SW, Durall DM ( 2015). Topology of tree-mycorrhizal fungus interaction networks in xeric and mesic Douglas-fir forests. Journal of Ecology, 103, 616-628. DOI URL
[9]	Bezerra ELS, Machado IC, Mello MAR ( 2009). Pollination networks of oil-flowers: A tiny world within the smallest of all worlds. Journal of Animal Ecology, 78, 1096-1101. DOI URL PMID
[10]	Blüthgen N, Menzel F, Hovestadt T, Fiala B, Blüthgen N ( 2007). Specialization, constraints, and conflicting interests in mutualistic networks. Current Biology, 17, 341-346. DOI URL PMID
[11]	Chagnon PL, U’Ren JM, Miadlikowska J, Lutzoni F, Elizabeth Arnold A ( 2016). Interaction type influences ecological network structure more than local abiotic conditions: Evidence from endophytic and endolichenic fungi at a continental scale. Oecologia, 180, 181-191. DOI URL PMID
[12]	Chen SH, Wang YJ ( 2004). Nestedness pattern of insular community assemblages and its applications. Chinese Journal of Ecology, 23, 81-87. URL PMID
	[ 陈水华, 王玉军 ( 2004). 岛屿群落组成的嵌套格局及其应用. 生态学杂志, 23, 81-87.] URL PMID
[13]	Cook RR, Quinn JF ( 1998). An evaluation of randomization models for nested species subsets analysis. Oecologia, 113, 584-592. DOI URL PMID
[14]	Dormann CF, Gruber B, Fruend J, Gruber B ( 2018). Bipartite: Analysis of bipartite ecological webs. R package version 2.11. .
[15]	Fang Q, Huang SQ ( 2012). Progress in pollination networks: Network structure and dynamics. Biodiversity Science, 20, 300-307. DOI URL
	[ 方强, 黄双全 ( 2012). 传粉网络的研究进展: 网络的结构和动态. 生物多样性, 20, 300-307.] DOI URL
[16]	Gao C, Zhang Y, Shi NN, Zheng Y, Chen L, Wubet T, Bruelheide H, Both S, Buscot F, Ding Q, Erfmeier A, Kühn P, Nadrowski K, Scholten T, Guo LD ( 2015). Community assembly of ectomycorrhizal fungi along a subtropical secondary forest succession. New Phytologist, 205, 771-785. DOI URL PMID
[17]	Gotelli NJ ( 2000). Null model analysis of species co-occurrence patterns. Ecology, 81, 2606-2621. DOI URL PMID
[18]	Inouye DW, Pyke GH ( 1988). Pollination biology in the Snowy Mountains of Australia: Comparisons with montane Colorado, USA. Australian Journal of Ecology, 13, 191-205.
[19]	Kennedy P, Nguyen NH, Cohen H, Peay K ( 2014). Missing checkerboards? An absence of competitive signal in Alnus-‌‌associated ectomycorrhizal fungal communities. Peer J, 2, e686. DOI: 10.7717/peerj.686. DOI URL PMID
[20]	Li ZC, Xu JY, Wu CY, Zhang Y ( 2011). A review of studies using ecological network analysis. Acta Ecologica Sinica, 31, 5396-5405.
	[ 李中才, 徐俊艳, 吴昌友, 张漪 ( 2011). 生态网络分析方法研究综述. 生态学报, 31, 5396-5405.]
[21]	Liu CR, Ma KP, Chen LZ ( 2002). Nestedness: Methods, mechanisms and implications for biological conservation. Acta Phytoecologica Sinica, 26, 68-72.
	[ 刘灿然, 马克平, 陈灵芝 ( 2002). 嵌套性: 研究方法、形成机制及其对生物保护的意义. 植物生态学报, 26, 68-72.]
[22]	Liu KL, Porras-Alfaro A, Kuske CR, Eichorst SA, Xie G ( 2012). Accurate, rapid taxonomic classification of fungal large-subunit rRNA genes. Applied and Environmental Microbiology, 78, 1523-1533. DOI URL PMID
[23]	Luo F, Pan Y, Lu CH ( 2013). Structural characteristics of plant-animal mutualistic networks and related affecting factors. Chinese Journal of Ecology, 32, 2179-2185.
	[ 罗芳, 潘扬, 鲁长虎 ( 2013). 动植物互惠网络结构及影响因素. 生态学杂志, 32, 2179-2185.]
[24]	Montesinos-Navarro A, Segarra-Moragues JG, Valiente-Banuet A, Verdú M ( 2012). The network structure of plant- arbuscular mycorrhizal fungi. New Phytologist, 194, 536-547. DOI URL PMID
[25]	Mosquin T, Martin JEH ( 1967). Observations on the pollination biology of plants on Melville Island, N.W.T, Canada. Canadian Field Naturalist, 81, 201-205.
[26]	Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H ( 2019). Vegan: Community ecology package. R package version 2.5-4. . Cited: 2019-03-20 DOI URL PMID
[27]	Olesen JM, Eskildsen LI, Venkatasamy S ( 2002). Invasion of pollination networks on oceanic islands: Importance of invader complexes and endemic super generalists. Diversity and Distributions, 8, 181-192. DOI URL
[28]	Poisot T, Péquin B, Gravel D ( 2013). High-throughput sequencing: A roadmap toward community ecology. Ecology and Evolution, 3, 1125-1139. DOI URL PMID
[29]	Southworth D, He XH, Swenson W, Bledsoe CS, Horwath WR ( 2005). Application of network theory to potential mycorrhizal networks. Mycorrhiza, 15, 589-595. DOI URL PMID
[30]	Thebault E, Fontaine C ( 2010). Stability of ecological communities and the architecture of mutualistic and trophic networks. Science, 329, 853-856. DOI URL PMID
[31]	Toju H, Guimarães PR, Olesen JM, Thompson JN ( 2014). Assembly of complex plant-fungus networks. Nature Communications, 5, 5273. DOI: 10.1038/ncomms6273. DOI URL PMID
[32]	Ulrich W, Almeida-Neto M, Gotelli NJ ( 2009). A consumer’s guide to nestedness analysis. Oikos, 118, 3-17. DOI URL
[33]	Ulrich W, Gotelli NJ ( 2007). Null model analysis of species nestedness patterns. Ecology, 88, 1824-1831. DOI URL PMID
[34]	Ulrich W, Gotelli NJ ( 2013). Pattern detection in null model analysis. Oikos, 122, 2-18. DOI URL PMID
[35]	Vázquez DP, Blüthgen N, Cagnolo L, Chacoff NP ( 2009). Uniting pattern and process in plant-animal mutualistic networks: A review. Annals of Botany, 103, 1445-1457. DOI URL PMID
[36]	Wright DH, Patterson BD, Mikkelson GM, Cutler A, Atmar W ( 1997). A comparative analysis of nested subset patterns of species composition. Oecologia, 113, 1-20. DOI URL PMID
[37]	Zhang XM, Han XF, Liu LW, Xu AC ( 2016). Influencing factors of the nested distribution of butterfly assemblages in the Zhoushan Archipelago, China. Biodiversity Science, 24, 321-331. DOI URL
	[ 张雪梅, 韩徐芳, 刘立伟, 徐爱春 ( 2016). 舟山群岛蝶类群落嵌套分布格局及其影响因素. 生物多样性, 24, 321-331.] DOI URL