Spatial patterns of dominant species and their implication for natural secondary forest ecosystem dynamics in a reserved forest of north China

Lv, Xizhi; Zuo, Zhiyan; Sun, Juan; Ni, Yongxin; Dong, Guotao

doi:10.1016/j.ecoleng.2018.12.023

Cited by 5 publications

(6 citation statements)

References 31 publications

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“…dead vs living). For all analysis types, positive, negative, or absence of departure from the null model simulation envelopes occurs at a given scale r (Continued) Iszkuło et al 2012;Zhang et al 2013;Navarro-Cerrillo et al 2013;Ebert et al 2015;Wehenkel et al 2015;Jácome-Flores et al 2016;Jia et al 2016;Zhang et al 2016;Owen et al 2017;Gradel et al 2017;Zheng et al 2017;Nguyen et al 2018b;Omelko et al 2018;Muvengwi et al 2018;Vandekerkhove et al 2018;Kazempour Larsary et al 2018;Lv et al 2019;Baran et al 2020 Patterns 1 and 2 are segregated Riginos et al 2005;Hao et al 2007;De Luis et al 2008;Batllori et al 2010;Navarro-Cerrillo et al 2013, Kang et al 2014Cordero et al 2016;Hu et al 2017;Miao et al 2018;Bassil et al 2018; Wang et al 2010a;Zhang et al 2010;Martínez et al 2010;Lan et al 2012;Liu et al 2014;Petritan et al 2014Petritan et al , 2015Wang et al 2015;…”

Section: Second-order Summary Statisticsmentioning

confidence: 99%

“…dead vs living). For all analysis types, positive, negative, or absence of departure from the null model simulation envelopes occurs at a given scale r (Continued) Kenkel 1988;Ward et al 1996;Haase et al 1996;Haase et al 1997;Pélissier 1998;Eccles et al 1999;Chen and Bradshaw 1999;Mast and Veblen 1999;Grau 2000;He and Duncan 2000;North et al 2004 ;Motta and Edouard 2005;Motta and Lingua 2005;Suzuki et al 2005;Fajardo et al 2006;Nanami et al 2011;Iszkuło et al 2012;Navarro-cerrillo et al 2013;Wehenkel et al 2015;Jia et al 2016;Zhang et al 2016;Owen et al 2017;Zheng et al 2017;Lv et al 2019 Quantitatively univariate marked analysis Mark correlation function k m1m1 (r) (Stoyan and Stoyan 1994)…”

Section: Second-order Summary Statisticsmentioning

confidence: 99%

“…Moreover, it can be evaluated by the comparison between size (or age) classes over life stages, that is, between young and adult spatial patterns. Indeed, recruits are frequently found to be aggregated at a small scale and a decrease of clustering degree can be observed with increasing plant size (from young to adult stage) indicating self-thinning process (Wiegand et al 2007b) and resulting usually in regular distribution (Yao et al 2016;Wang et al 2017;Lv et al 2019). However, the absence of detection of self-thinning may reflect very weak competition (Nguyen et al 2016).…”

Section: Qualitatively Marked Analysis: Density-dependent Effectmentioning

confidence: 99%

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Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

Ben-Said

2021

Ecol Process

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Background Ecological processes such as seedling establishment, biotic interactions, and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis (SPPA). Being widely used in plant ecology, SPPA is increasingly carried out to describe biotic interactions and interpret pattern-process relationships. However, some aspects are still subjected to a non-negligible debate such as required sample size (in terms of the number of points and plot area), the link between the low number of points and frequently observed random (or independent) patterns, and relating patterns to processes. In this paper, an overview of SPPA is given based on rich and updated literature providing guidance for ecologists (especially beginners) on summary statistics, uni-/bi-/multivariate analysis, unmarked/marked analysis, types of marks, etc. Some ambiguities in SPPA are also discussed. Results SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns. Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species. Natural processes, plant environmental conditions, and human intervention are interrelated and are key drivers of plant spatial distribution. In spite of being not recommended, small sample sizes are more common in SPPA. In some areas, periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring. Conclusion The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures. Despite the continuous progress of SPPA, some ambiguities require further clarifications.

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Section: Second-order Summary Statisticsmentioning

confidence: 99%

Section: Second-order Summary Statisticsmentioning

confidence: 99%

Section: Qualitatively Marked Analysis: Density-dependent Effectmentioning

confidence: 99%

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Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

Ben-Said

2021

Ecol Process

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“…In general, plant species distribution in natural ecosystems is less likely to occur randomly (Maestre & Cortina, 2004;Rayburn, 2011;Rayburn et al, 2011;Stoll & Prati, 2001). There are several factors which determine plant distribution such as plant-plant interactions (Valiente-Banuet et al, 2006), environmental variability (Lv et al, 2019;Perry et al, 2009), seed dispersal (Schurr et al, 2004) and disturbance (Bisigato et al, 2005;Rayburn et al, 2011). In this regard, some researchers report a non-random spatial pattern for plant species in a semiarid rangeland in western Iran.…”

Section: Distribution Pattern Of Different Plant Functional Groups In Local To Regional Scalesmentioning

confidence: 99%

Components of plant diversity as ecological indicators reflecting the effects of conservation management and degradation in different climatic conditions

et al. 2021

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Additive partitioning of species diversity is a valuable approach for quantifying the spatial patterns of biodiversity sampled in hierarchically scaled studies. This approach may provide key insights into vegetation community restoration following terrestrial ecosystems degradation in different climatic conditions. The scale-dependence of plant diversity in relation to different plant functional groups (e.g., herbaceous and woody) is still little understood. This research aims to investigate the influence of management options (protected vs. non-protected) and climatic conditions (semiarid vs. Mediterranean) on different components of diversity in both herbaceous and woody species derived from local and regional scales (i.e., plot and site, respectively).In the studied areas, a total of 64 plots (1000 m 2 ) at local scale and 128 micro-plots (1 m 2 ) among 16 sites at regional scale were selected for sampling the woody and herbaceous species data, respectively, by using a hierarchical sampling design. Diversity components of local (α1, β1) and regional (α2, β2) scales were extracted according to additive partitioning method. Differences in diversity component (α1, α21, β1 and β2) and floristic composition between management options and climatic conditions were evaluated using GLMM and DCA. The results indicate that all components of total species (both herbaceous and woody) diversity (α1, α2, β1 and β2) were significantly influenced by management options (p < 0.05) with greater values in the protected areas than the non-protected areas. However, the climatic conditions only had significant effects on β2, with greater values in the Mediterranean compared to semi-arid areas. Moreover, the separate analysis of herbaceous and woody species indicated that management options have a greater significant effect on different diversity components compared to the climatic condition. Detrended correspondence analysis showed that floristic variations along the axes are strongly affected by management in both climatic conditions. This indicates that protection measures mostly increased plant species diversity at the local and regional scales, which is independent of the climatic condition.

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“…Intra- and inter-species interactions are key processes that affect the structure and dynamics of plant communities [ 15 , 16 ]. Plant interactions include positive and negative effects, which together with environmental factors affect the spatial patterns and succession of communities [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution pattern of colonized native semi-shrubs in two artificial vegetation restoration patterns in Mu Us sandy land, North China

Hu,

Gao

2024

PLoS ONE

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Vegetation construction is a key process for restoring and rehabilitating degraded ecosystems. However, the spatial pattern and process of native plants colonized by different vegetation restoration methods in semi-arid sandy land are poorly understood. In this study, two artificial vegetation restoration patterns (P1: row belt restoration pattern of Salix matsudana with low coverage; P2: a living sand barrier pattern of Caryopteris mongolica with low coverage) were selected to analyze the spatial distribution pattern and interspecific association of the colonizing native shrubs. The effects of the two restoration models on the spatial patterns of the main native semi-shrubs of the colonies (i.e., Artemisia ordosica and Corethrodendron lignosum var. leave) were studied using single variable and bivariate transformation point pattern analysis based on Ripley’s L function. Our results showed that two restoration patterns significantly facilitated the establishment of A. ordosica and C. lignosum var. leave, with their coverage reaching 17.04% and 22.62%, respectively. In P1, the spatial distribution pattern of colonial shrubs tended to be a random distribution, and there was no spatial correlation between the species. In P2, the colonial shrub aggregation distribution was more dominant, and with the increase in scale, the aggregation distribution changed to a random distribution, whereas the interspecific association was negatively correlated. The differences in the spatial distribution patterns of colonized native semi-shrubs in these two restoration patterns could be related to the life form of planted plants, configuration methods, biological characteristics of colonized plants, and intra- and interspecific relationships of plants. Our results demonstrated that the nurse effect of artificially planted vegetation in the early stage of sand ecological restoration effectively facilitated the near-natural succession of communities. These findings have important implications for ecological restoration of degraded sandy land in the semi-arid region of northern China.

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Spatial patterns of dominant species and their implication for natural secondary forest ecosystem dynamics in a reserved forest of north China

Cited by 5 publications

References 31 publications

Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

Components of plant diversity as ecological indicators reflecting the effects of conservation management and degradation in different climatic conditions

Spatial distribution pattern of colonized native semi-shrubs in two artificial vegetation restoration patterns in Mu Us sandy land, North China

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