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Morphological responses of six plant species to patchy habitat with different nitrogen concentrations using in-growth core methods

Du F., Sui Y., Xu X., Zhang X., Hao W., Shao M., Hu L., Shan L.

Polish Journal of Ecology

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2013

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Vol. 61, nr 2

257--269

EN

Soil nutrient pattern can be a functional tool for grassland restoration. In order to promote the growth of a specific or group of expected plant species, it is necessary to measure the responses of different species to nutrient – rich patches and detect the differences among them. In this article, we measured aboveground biomass and morphological traits of six species as dry weight, length, surface area, specific root length and diameter of fine roots in response to nitrogen addition patches using ingrowth core method. The six species are Artemisia scoparia, Stipa bungeana, Artemisia sacrorum, Artemisia giraldii, Lespedeza dahurica and Astragalus melilotoides. All are the dominant species in different stages of secondary succession of loess hilly region, China. Twelve individuals of each species were selected to install ingrowth cores. Six of the individuals were used as treatment group, they were treated to install with four cores of no (addition’s control), low, medium and high levels of nitrogen additions. Another six of them were used as species’ control group, the four installed cores around them had no nitrogen addition. The results showed that: 1) After 105 days in situ, for all the six species, summed dry weight, length and surface area measured in the four cores of the treatment group were significantly greater than the corresponding values in species’ control group. In aboveground biomass, however, only A. scoparia in the treatment group had significantly outweighed that in the species’ control group. 2) Irrespective of nitrogen additions levels, significant differences of length, diameter and surface area existed among the six species, which implied that species had their intrinsic species specific morphological traits. 3) In dry weight, length and surface area, the responses of all the six species to nitrogen addition levels were positive, significantly more roots were grew into the cores with higher nitrogen additions; while in specific root length, the responses were negative. 4) Perhaps the six species had a special nitrogen requirement, as interaction effects of species and addition levels in surface area were found significant. 5) The foraging precision of the six species to nutrient-rich patches had positive but insignificant correlation with root system size; there existed a significant positive correlation between the precision and the sensitivity to the designed patchy habiats. 6) Among the six species, A. scoparia, A. sacrorum and S. bungeana have higher sensitivity and precision than L. dahurica and A. melilotoides in terms of foraging the nitrogen addition cores or patches. It seems that fast growing species that dominate in early successional stage, like A. scoparia and S. bungeana in our case, obtained more benefits from nutrient patchy habitat. We advised that, in infertile lands, fertiliser be applied in a patchy way to accelerate the restoration of old fields as early as possible once they were abandoned.

2

Relational Operations and Uncertainty Measure in Rough Relational Database

Jiang F., Sui Y., Cao C., Wan X., Du J.

Fundamenta Informaticae

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2013

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Vol. 123, nr 4

401--416

EN

The traditional relational database model (RDM) is not effective for dealing with imprecise and uncertain data as it deals with precise and unambiguous data. Hence, Beaubouef et al. proposed the rough relational database model (RRDM) for the management of uncertainty in relational databases. Beaubouef et al. defined the corresponding rough relational operators in rough relational databases as in ordinary relational databases. And to give an effective measure of uncertainty in rough relational databases, they defined the rough relation entropy. In this paper, we further discuss the issues of relational operations and uncertainty measure in rough relational databases. We give some new definitions for rough relational operators and rough relation entropy in rough relational databases. Furthermore, we discuss the basic properties of rough relational operators and rough relation entropy, as well as the connections between rough relational operators and rough relation entropy.

3

The relationships between aboveground biomass and Voronoi area of coexisting species in an old-field community

Du F., Xu X., Zhang X., Sui Y., Shao M., Hu L., Shan L.

Polish Journal of Ecology

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2012

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Vol. 60, nr 3

479-489

EN

Voronoi area of coexisting species in a community has an important role in determining their performances as it is related with the available resources around individuals. Biomass formed within certain Voronoi area probably can be a mark of species that characterised resource competition ability of coexisting species in natural community. In this article, we tried to probe the subject in the following three aspects: 1) what is the apparent relationship between individuals' aboveground biomass and their available Voronoi area for species in natural community? 2) what is the possible theoretic relationship between them? 3) additionally, whether there are any possible indices that can be elicited from species' occupied Voronoi area to reflect species' competitive ability. Using individual-based investigation of aboveground biomass and their corresponding positions, Voronoi area of all individuals of coexisting species in an old field community were computed. The growth of an individual could be regard as a process to compete for resources that is limited by the available area or volume encompassed by the neighborhood individuals. We extended logistic growth model to describe the relationship between Voronoi area and aboveground biomass of coexisting species by relating limiting rhizospheral resource with the Voronoi area around an individual. Theoretically, the individuals aboveground biomass is also controlled by factor-ceiling effects of Voronoi area. So the extended model was fitted with boundary analysis method. And also, their linear relationship was fitted. Under the prediction that competive ability is one of the main driving factors of community succession, two parameters as the Voronoi area of coexisting species and the Voronoi area per unit of aboveground biomass were used to check whether they can designate species' competitive abilities and competitive hierarchies. This was presented by fitting the two parameters with the successional niche positions that was represented by the ordination values along abandonment ages of old field communities in the local area. The results showed that: 1) For most species, the linear regression demonstrated that Voronoi area of an individual that occupied larger Voronoi area tended to have greater aboveground biomass. The nonlinear regression of showed that the relationship might depend upon species' growth characteristics, like shade tolerance and root proliferation. Generally, the relationship could be better fitted by the extended logistic growth model using boundary analysis method than by the linear regression, except for some shade-preferring or clone species. If factor-ceiling effects were considered, at the highest, about 48% of the variation of aboveground biomass could be interpreted by Voronoi area. For some other species with light preference or clone proliferation, the determination coefficient was around zero. 2) Species. averaged Voronoi area had significant and positive Kendall's tau-b and Spearman correlations with successional niches, and species' per-unit aboveground biomass positions of Voronoi area has significantly negative rank correlation with successional niche positions. These indicate that both of them can reflect species' competitive ability and hierarchy to some extent.

4

Relational Contexts and Relational Concepts

Jiang F., Sui Y., Cao C.

Fundamenta Informaticae

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2010

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Vol. 99, nr 3

293-314

EN

Formal concept analysis (FCA) is a mathematical description and theory of concepts implied in formal contexts. And the current formal contexts of FCA aim to model the binary relations between individuals (objects) and attributes in the real world. In the real world we usually describe each individual by some attributes, which induces the relations between individuals and attributes. But there also exist many relations between individuals, for instance, the parent-children relation in a family. In this paper, to model the relations between individuals in the real world, we propose a new context - relational context for FCA, which contains a set U of objects and a binary relation r on U. Corresponding to the formal concepts in formal contexts, we present different kinds of relational concepts in relational contexts, which are the pairs of sets of objects. First we define the standard relational concepts in relational contexts. Moreover, we discuss the indirect relational concepts and negative relational concepts in relational contexts, which aim to concern the indirection and negativity of the relations in relational contexts, respectively. Finally, we define the hybrid relational concepts in relational contexts, which are the combinations of any two different kinds of relational concepts. In addition, we also discuss the application of relational contexts and relational concepts in the supply chain management field.

5

Normalized-scale Relations and Their Concept Lattices in Relational Databases

Lei Y., Sui Y., Cao C.

Fundamenta Informaticae

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2009

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Vol. 93, nr 4

393-409

EN

Formal Concept Analysis (FCA) is a valid tool for data mining and knowledge discovery, which identifies conceptual structures from (formal) contexts. As many practical applications involve non-binary data, non-binary attributes are introduced via a many-valued context in FCA. In FCA, conceptual scaling provides a complete framework for transforming any many-valued context into a context, in which each non-binary attribute is given a scale, and the scale is a context. Each relation in relational databases is a many-valued context of FCA. In this paper, we provide an approach toward normalizing scales, i.e., each scale can be represented by a nominal scale and/or a set of statements. One advantage of normalizing scales is to avoid generating huge (binary) derived relations. By the normalization, the concept lattice of a derived relation is reduced to a combination of the concept lattice of a derived nominal relation and a set of statements. Hence, without transforming a relation into a derived relation, one can not only determine concepts of the derived relation from concepts of given scales, but also determine concepts of the derived relation from concepts of a derived nominal relation and a set of statements. The connection between the concept lattice of a derived nominal relation and the concept lattice of a derived relation is also considered.

6

Modification of the Acid-base and Catalytic Properties of CuCl2-KCl-LaCl3/-Al2O3 by MgAl2O4 in Ethane Oxychlorination

Liu J., Sui Y., Zhou G., Zhen K., Zhang X., Cheng T.

Polish Journal of Chemistry

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2007

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Vol. 81, nr 1

95-101

EN

Effect of MgAl2O4 on the structure, acidity as well as catalytic activity of CuCl2-KCl-LaCl3/gamma-Al2O3 catalyst in ethane oxychlorination was studied. Impregnation of gamma-Al2O3 with Mg and Al nitrates formed magnesium aluminate spinel on the support. TPR results showed that Cu species were located on both -Al2O3 and MgA gamma2O4 phases. With modification of -Al2O3 by MgAl2O4, the interaction between Cu species and support weakened and the surface active species CuCl2 increased. Formation of MgA gamma2O4 leads to a decrease of strong acid sites and an increase of weak acid sites. Much larger quantities of coke were deposited on the CuCl2-KCl-LaCl3/gamma-Al2O3 than on the modified catalyst, which was attributed to its more strong acid sites. Based on these factors CuCl2-KCl-LaCl3/MgAl2O4-Al2O3 catalyst exhibits better catalytic activity and stability than gamma-Al2O3 supported catalyst, and the highest vinyl chloride selectivity reached 46.8% and was still 40.6% after 210 h reaction.

7

Formal Concept Analysis in Relational Database and Rough Relational Database

Jiang F., Sui Y., Cao C.

Fundamenta Informaticae

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2007

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Vol. 80, nr 4

435-451

EN

Since its foundation in the early 1980's, Formal Concept Analysis (FCA) has been used in many applications in data analysis, information retrieval, and knowledge discovery. In this paper, we suggest to exploit the framework of relational database model (RDM) and rough relational database model (RRDM) for Formal Concept Analysis. The basic idea is as follows. We firstly treat any relation (R,A) of RDM as a many-valued context of FCA. But for the rough relations of RRDM, we define a special kind of many-valued context - rough-relational context in FCA (In this kind of context, every attribute value is a subset, but not an element, of the corresponding attribute domain), and treat any rough relation (R,A) of RRDM as a rough-relational context of FCA. Correspondingly, the definitions for concepts or rough concepts in context or rough-relational context (R,A) are given. The basic properties about these concepts or rough concepts in (R,A) are also discussed.