Взаимоотношения между видовыми особ

Взаимоотношения между видовыми особенностями и свойствами окружающей среды обычно оцениваются непрямо с помощью двухшагового анализа. Во-первых, обилие видов связывается с условиями окружающей среды, а реакция видов на изменчивость свойств среды соотносится затем с биологическими или физиологическими особенностями видов (Thuiller et al., 2004; Santoul et al., 2005; Brind'Amour et al., 2011). Анализ RQL позволяет соотнести экологические особенности видов с условиями окружающей среды (Doledec et al. 1996). Этот анализ исследует совместную структуру между трех таблиц данных: R-таблица (содержит переменные окружающей среды), Q-таблица (содержит видовые особенности) и L-таблица (обилие видов) (Doledec et al., 1996; Dray et al., 2002). L-таблица выполняет функцию связи между таблицами R и Q и измеряет интенсивность связи между ними. Перед собственно анализом, проводятся три отдельных анализа. Анализ соответствий применяется для L-таблицы, в результате чего получают оптимальную корреляционную структуру между сайтами и весами численности видов. Ординация таблиц R и Q выполняется с помощью анализа главных ком-понент. Таким образом, RQL выполняет анализ коинерции кросс-матриц R, Q и L. Этот анализ максимизирует ковариацию между весами изучаемых сайтов с учетом свойств окружающей среды, выраженных таблицей R, и весами видов с учетом их экологических свойств, выраженных таблицей Q (Minden et al., 2012). В результате может быть получена лучшая совместная комбинация ординации сайтов по их характеристикам окружающей среды, ординации видов по их свойствам и одновременно ординация видов и сайтов (Thuiller et al., 2006). RQL-анализ объединяет три отдельных ординационных решения с максимизацией ковариации между особенностями видов и свойствами окружающей среды посредством анализа коинерции (Bernhardt-Romermann et al., 2008). Далее, иерархический кластерный анализ весов видов по двум осям RQL по методу Варда дает функциональные группы (Minden et al., 2012). Оптимальное число групп можно получить с помощью критерия Калинского (Calinski, Harabasz, 1974). Кластеры показывают распределение видов в пространстве особенности видов – эко-логическое пространство (Minden et al., 2012).

Результаты (английский) 1:

The relationship between species characteristics and environmental properties are evaluated normally Wednesday indirectly using the two step analysis. Firstly, the abundance of species associated with environmental conditions Wednesday, but the reaction of the species on the variability of properties Wednesday relates then with biological or physiological features of the species (Thuiller et al., 2004; Santoul et al., 2005; Brind'Amour et al., 2011). RQL allows to correlate analysis environmental peculiarities of species with environmental conditions Wednesday (Doledec et al. 1996). This analysis explores the joint structure between three data tables: R-table (which contains the environment variables Wednesday), Q-table (contains specific features) and L-table (abundance) (Doledec et al., 1996; Dray et al., 2002). L-table performs a liaison function between the tables R and Q, and measures the intensity of links between them. Before the actual analysis, conducted three separate analysis. Analysis correspondences is used for L-table, and as a result receive optimal correlation structure between sites and scales the number of species. Ordination tables R and Q is done through the analysis of the main component. Thus, koinercii parses the RQL cross-matrix R, Q and l. this analysis maximizes the covariance between the weights of the studied sites taking into account environmental properties Wednesday expressed table R, and weights of species, taking into account their environmental properties expressed by table Q (Minden et al., 2012). The result can be obtained best joint combination ordination sites on their environmental characteristics, species ordination Wednesday on their properties and at the same time ordination of species and sites (Thuiller et al., 2006). RQL-analysis combines three separate ordinacionnyh decision, maximizing the covariance between the peculiarities of species and environmental properties Wednesday through the analysis of koinercii (Bernhardt-Romermann et al., 2008). Further, hierarchical cluster analysis of weights on two axes RQL species according to the method of WARDA gives functional groups (Minden et al., 2012). The optimal number of groups can be obtained by using the criterion of Kale (Calinski, Harabasz, 1974). Clusters show the distribution of species in space features species-eco-logical space (Minden et al., 2012).

Результаты (английский) 2:

The relationship between the species characteristics and properties of the environment are usually evaluated indirectly using the two-step analysis. First, the abundance of species associated with the environmental conditions and the types of reaction to the changing environment then the properties relates to biological or physiological characteristics of species (Thuiller et al, 2004;.. Santoul et al, 2005; Brind'Amour et al, 2011. ). Analysis RQL allows correlate ecological characteristics of species to environmental conditions (Doledec et al. 1996). This assay examines the joint structure between the three data tables: R-Table (containing environment variables), Q-table (containing species characteristics) and L-table (abundant species) (Doledec et al., 1996; Dray et al., 2002 ). L-table performs a liaison function between the tables R and Q, and measures the intensity of the connection between them. Before the actual analysis, conducted three separate analysis. Concordance analysis used for L-tables, thereby producing an optimal correlation structure between sites and the number of kinds of weights. Ordination tables R and Q is performed by analyzing the main com-ponents. Thus, RQL analyzes koinertsii cross-matrices R, Q, and L. This analysis maximizes the covariance between the weights of the studied sites, taking into account, denominated R table properties of the environment, and weights of species based on their ecological properties, expressed Q table (Minden et al ., 2012). The result could be obtained by a combination of the best co-ordination in their environmental performance sites environment, coordination of species on their properties and simultaneously ordination of species and sites (Thuiller et al., 2006). RQL-analysis combines three separate ordination solutions maximizing the covariance between the features of species and properties of the environment by analyzing koinertsii (Bernhardt-Romermann et al., 2008). Next, a hierarchical cluster analysis of the balance of species in two axes by RQL Ward method enables functional groups (Minden et al., 2012). The optimal number of groups can be obtained by Kale criterion (Calinski, Harabasz, 1974). The clusters show the distribution of species in space, especially species - eco-logical space (Minden et al, 2012.).

Результаты (английский) 3:

the relationship between the видовыми characteristics and properties of the environment typically непрямо by двухшагового analysis. first, the abundance of species is associated with environmental conditions, and the reaction of the variability properties of the environment compares then with biological or physiological characteristics of the species (Thuiller et al., 2004; Santoul et al., 2005; Brind "amour et al., 2009). analysis of RQL allows correlating the ecological characteristics of species to environmental conditions (Doledec et al. 1996). this analysis explores the joint structure between the three tables of data: r - table (which contains the variables of the environment), the q table (which contains the species characteristics) and the table (all types) (Doledec et al., 1996; Dray et al., 2002). the table serves as a connection between tables r and q and measures the intensity of the connection between them. before the actual analysis, there are three separate analysis. correspondence analysis applied to the matrix, which are the optimal корреляционную structure between sites, and the balance of species. ordination of tables r and q is performed through the analysis of the main component. thus, the RQL performs analysis of the коинерции cross matrices r, q and l analysis. this maximizes the ковариацию between scale of sites, taking into account the characteristics of the environment, expressed as the r, and the balance of species according to their environmental properties expressed by the matrix q (minden et al., 2012). the result could be obtained by the combination of the best coordination sites on their characteristics of the environment, coordination of their properties and, at the same time, ordination of species and sites (Thuiller et al., 2006). RQL analysis consists of three separate ординационных decision with the maximization of ковариации between feature types and properties of the environment through the analysis of коинерции (bernhardt - Romermann et al., 2008). further, the hierarchical clustering analysis of the weights of the two axes RQL varda method provides functional group (minden et al., 2012). the optimal number of groups can be obtained by the criterion of калинского (Calinski, Harabasz, 1974). clusters show the distribution of species in the space of particular species, eco - logical space (minden et al., 2012).