ISSN 1995-4255, Contemporary Problems of Ecology, 2012, Vol. 5, No. 1, pp. 97–103. © Pleiades Publishing, Ltd., 2012. Original Russian Text © V.V. Vinogradov, 2012, published in Sibirskii Ekologicheskii Zhurnal, 2012, Vol. 19, No. 1, pp. 131–139.
Long-Term Dynamics and Structure of Shrews Association (Soricidiae) in the Mountain Taiga of the Eastern Sayan V. V. Vinogradov V. P. Astaf’ev Krasnoyarsk State Pedagogical University, ul. A. Lebedevoi 89, Krasnoyarsk, 660049 Russia E-mail:
[email protected] Abstract—The dynamics of shrews association in the mountain taiga of the Eastern Sayan was considered during the years 1981 to 2010. The work was carried out in the territory of “Stolby” reserve. The structure of the association, the duration of cyclic changes of different species, effect of succession and climatic processes on the composition and structure of the community have been studied. DOI: 10.1134/S1995425512010134 Keywords: shrews, association, long-term dynamics, environmental factors
tinguished with exponential smoothing, building up polynomial models [6] and “phase portraits” method [7]. The similarity degree for different species numbers was determined with cluster analysis on the basis of correlation matrix (with Pearson’s coefficient). To distinguish the regular component in time series of each species spectral analysis was used. To determine environmental factors effecting the dynamics of series numbers the models of multiple regression were built on the basis of indicators of factors with different nature for many years. As variables the models used amounts of temperatures for January, March, previous November, overall summer period and year; precipitation amounts for summer period and year; maximal height of snow cover; total yield of coniferous seeds (cedar, silver fir and fir) expressed in points from 0.5 to 5.0. The specified parameters of environment were obtained from annual scientific reports of ”Stolby” reserve, author’s materials and data of “Narym” meteostation located in the territory of the reserve. The reliability of the built models was determined with chi-squared test (c 2 ) and the one by Kolmogorov–Smirnov. The data omitted in calculations were extrapolated on the nearest values median. All calculations in the work and graph plotting were performed in Statistica 6.0 Program [8].
Organization and dynamics of vertebrates associations remains one of the topical problems of modern ecology [1–4]. Long-term monitoring of the number of both individual populations and the entire associations allows answering the questions on the changes occurring in fauna under the influence of factors of different nature. A convenient model group for such type of investigations is specimens of shrews’ family (Soricidae)—a numerous group with well-expressed population cycles sensitive to any changes in habitat. The work attempts to complexly analyze materials of long-term observations of shrews. At that the main objectives were determination of specific features of association structure in different years, determination of durability of cyclic variations of individual species, identification of general trends in these indicators changes and calculation of the degree of numerical characteristics dependence on the factors of different nature. MATERIALS AND METHODS In the work we used the data collected for the period from 1981 to 2010 (off and on in 1990, 1991 and 1998) in the State Natural Reserve “Stolby” within the typical mountain taiga of the Eastern Sayan. In different periods registrations were carried out by V. I. Bulavkin, A. N. Zyryanov, A. M. Khritankov, B. K. Kelbeshekov, and V. V. Vinogradov. All materials were collected and processed with unified methods. Capture of animals was performed with standard method of pitfall traps (50 m long with five cones) for the same periods, from August 1 to September 1. For species characteristic the indicators of relative numbers were used, the number of species per 100 cone days (c.d.) and domination index (d.i.) being a percentage of a species in captures [5]. Totally over 5000 c.d. have been analyzed. The overall volume of the studied material was 2857 specimens. Harmonic variations and trends in long-term series of shrew numbers were dis-
The considered territory is located in north-western spurs of the Eastern Sayan on the right bank of Yenisei River (Fig. 1). The local relief is weakly partititioned low mountains with absolute heights of 250–800 m above sea level. The climate is humid, continental with the average annual air temperature –1°C, amount of precipitations, up to 700 mm and frost-free period, up to 160 days. In the vegetation cover the prevailing is dark coniferous taiga of grass-green-moss type with Abies sibirica predominance. Pine, cedar and larch woods with admixture of small-leaved trees and developed grass and shrub layers occur. 97
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Fig. 1. Region of investigations.
RESULTS AND DISCUSSION In dark coniferous taiga of the Eastern Sayan there are 9 species of shrew family, common shrew (Sorex): small (S. minutus L.), middle (S. caecutiens Laxmann), plane (S. roboratus Hollister), isodon (S. isodon Turov), tundra (S. tundrensis Merriam), common (S. araneus L.,), tiny (S. minutissimus Zimm.) Eurasian water shrew (N. fodiens Pennat) and white-toothed shrew (Cr. suaveolins Pall.). Despite the relative stability of the species composition the indicators of species numbers significantly change over the considered period (Fig. 2). The absolute dominant is S. araneus L. The codominants are S. minutus L. and S. isodon Turov. The common in the species composition is the S. caecutiens Laxmann. Not every year S. roboratus Hollister, S. tundrensis Merriam, S. minutissimus Zimm., and N. fodiens Pennat) are found in captures. Cr. suaveolins Pall. was first registered in the territory of the reserve in 2009. Since single specimens of the later species were captured the data on its numbers are not included in the general analysis. With the use of spectral analysis duration of population cycles was determined; for different species of shrews it varies from 3 to 4 years that is specific for this group all over the boreal forests of Eurasia [9–11]. The total number of association changed from 10 to 175 species per 100 c.d. that is more than 17-fold variation. The peaks in numbers were registered in 1984, 1985, 1993, 2005 and 2010; depressions, in 1986, 1992, 1997, 1999 and 2006. Speaking on the structure of shrews association it should be noted that for 30 years different species became dominants. The most often the leading in numbers was S. araneus L., 13 years with participation up to 64.3%. Second and third were S. minutus L. and S. caecutiens Laxmann, 6 (63%) and 5 (55.6%), respectively, and then S. isodon Turov, 3 year (52%). The specified species are leading in numbers; at that their accumulated share varies from 68 to 99%.
Long-term structural changes inside the association may be easily seen from the comparison of the average rank values with the coefficient of their variation (Fig. 3). Despite significant variations of the numbers and changes in the association structure the dominating species keep their leading position (see Fig. 3, group A). High rank values and variation coefficients prove the prominent recurrence of these species with significant drops in numbers. Especially prominent this feature is in S. araneus L. and S. minutus L. Species with middle and low rank vary in this value insignificantly (see Fig. 3, group B). The species with the smallest numbers are characterized by low variation coefficients and for the most favorable years only single specimens were registered. Evaluation of the number dynamics similarity on the basis of correlation coefficients has shown that shrews are divided into three groups (Fig. 4). At 57% similarity all species in dendrogram are divided into three clusters. The first group includes three largest specimens of the family with similar parameters of long-term dynamics. Studies devoted to ecological peculiarities of sympatric species of shrews in the territory of Eurasia prove direct competition of the closest species for forage resources and shelters [4, 12–14]. Hence it may be assumed that large and aggressive species dominate and realize their potential regardless of other Sorex species but depending on the environmental factor favorability and intrapopulation mechanisms. In the second group the highest similarity is specific for S. tundrensis Merriam and S. roboratus Hollister, species that in the considered territory have suboptimal conditions and do not reach significant numbers in basic dark coniferous forests [15]. For this reason they have peak values of numbers displaced in relation to dominants. In the same cluster at some distance there is S. caecutiens Laxmann, typical inhabitant of dark coniferous green-moss forests. The third and the most distant group (>30%) is formed by two smallest specimens in the family, S. minutus L. and S. minutissimus Zimm. They have antiphased dynamics with large species and reach maximal numbers in the years of general recession in association. To determine trends in long-term dynamics of shrews numbers their time series were subjected to exponential smoothing (Fig. 5). Statistically reliable trends of the numbers changes for the majority of species is an evidence of the processes of structural transformation of association for the last decades. Sorex increases in numbers; trends for S. isodon Turov and S. caecutiens Laxmann are not clear; whereas numbers of S. roboratus Hollister, S. minutus L. and S. tundrensis Merriam decrease. Such changes may result from a diversity of facts. Specialized research has determined that in subtaiga and mountain-taiga forests of the Eastern Sayan the formation composition of forest-forming species and coenoelements of light coniferous formations are substituted
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Fig. 2. Long-term dynamics of shrews numbers in mountain dark coniferous taiga of the Eastern Sayan.
by the dark coniferous ones in the background of warming in the winter period and precipitation increase [16–18]. Besides significant areas of the traveling-excursion region of the reserve are occupied by the sec-
Fig. 3. Distribution of average rank values of individual species of shrews in mountain taiga of the Eastern Sayan for the period 1981–2010. A–B, groups of species with long-term rank in association, 1–7, Sorex: 1, S. araneus L.; 2, S. minutus L.; 3, S. caecutiens Laxmann; 4, S. isodon Turov; 5, S. roboratus Hollister; 6, S. tundrensis Merriam; 7, S. minutissimus Zimm.; 8, N. fodiens Pennat.
ondary forests in the sites of shrews capture. During succession changes the taiga vegetation is recovered and accompanied by gradual crown closure of silver fir, fir and cedar underbrush with simultaneous replacement of gramineous plants in grass cover to taiga motley grass and mosses. Due to the specified reasons the lesser “mountain-taiga” species, S. tundrensis Merriam, S. minutus L., and S. roboratus Hollister, decrease in numbers. In the background of these changes Sorex actively expands to mountain-taiga habitats that is bound with high ecological plasticity and aggressiveness of such
Fig. 4. Similarity degree of long-term dynamics of shrews numbers in mountain taiga of the Eastern Sayan.
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Fig. 5. Trends of long-term dynamics of shrews numbers in mountain taiga of the Eastern Sayan according to the results of exponential smoothing (1981–2010).
species. Such processes were registered for the entire space of the natural habitat of Sorex [14, 19, 20]. Due to the processes of structural transformation in shrews association it is necessary to consider the longterm variation of cumulative numbers of species during the considered period and determine possible cyclic component of this process. One of the efficient methods for determination of cycles in time series is the “phase portrait” method [7] by means of shifting transforming the time series to the trajectory matrix with its further investigation with factor analysis. As a result the time series is transformed into the naturally developing continuous process in multidimensional space of its states presented by main components [21] (Fig. 6).
As it is apparent the trajectory of the time series in the space of main components describes two circles standing for the time interval of 8–10 years. For this period shrews association undergoes general cyclic changes and returns to original state that agrees with certain numbers. This proves the balanced motion of all species included in association and its relative stability [22, 23]. The year 2010 noticeably stands out of the general trajectory. Analysis of original data has shown that for this year along with specific largest total numbers of association (133 species per 100 c.d.) the dominants were Sorex and S. isodon Turov (with the cumulative share of 85%) that had not been registered earlier. Thus shrews association of mountain taiga of the Eastern Sayan un-
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dergoes harmonic variations lasting 8–10 years when bursts in the numbers of different species may occur, misbalance the association and breach the overall longterm cycle. It should be noted that the same duration is specific for the “humid natural phases” caused by minor cycles of solar activity for 10–11 years [24]. For instance for the low territories in the south of Western Siberia dependence of long-term dynamics of small mammal numbers on these parameters has been detected [25–28]. As it is known population dynamics depends on the influence of the complex interacting exo- and endogenous mechanisms and detection of the most important factors often turns out to be a little promising and hard task. At selection of environmental parameters for inclusion in the regression models we often based on the idea that the temperature, humidity, forage sufficiency for a winter (the most critical) period noticeably effect the studied processes. Therefore it is possible to state with adequate certainty that the obtained results sufficiently reflect influence of selected parameters on shrews numbers. Parameters of the models of multiple regression are presented in the table. The long-term dynamics of Sorex is negatively influenced by high temperatures specific for March. Early March thaws result in formation of dense ice crust over snow being an insurmountable obstacle for animals moving under the snow cover and their coming out [29–32]. Snow sedimentation and appearance of waters
Fig. 6. Phase portrait of long-term cumulative numbers of shrews association in mountain taiga of the Eastern Sayan.
under it at frequent returns of frost result in the increased death-rate of animals [33]. Although Sorex mostly uses ground invertebrates as food their positive relation with coniferous seeds yield was found out. In winter period such fodder becomes especially significant for shrews. At the lack of invertebrates under snow the animals switch to high-caloric vegetable fodders providing for the energy requirements. The studies devoted to winter feeding of shrews show that the share of coniferous seeds in their ration may reach 60% at 100% occurrence in stomachs [30, 34, 35].
Model parameters of multiple regression of the dependence of long-term dynamics of shrew numbers in mountain taiga of the Eastern Sayan on environmental factors for the period from 1981 to 2010 Species Sorex S. araneus L.
S. isodon Turov
S. tundrensis Merriam S. roboratus Hollister S. minutus L.
Variables
BETA models
–0.40 St° of March Yield of coniferous seeds 0.32 2 Regression results: R = 0.356; F = 3.04; p < 0.0378 Yield of coniferous seeds 0.55 0.43 St° of previous autumn –0.38 St° of March Regression results: R2 = 0.484; F = 7.21; p < 0.0014 Yield of coniferous seeds 0.40 –0.39 St° of March Regression results: R2 = 0.386; F = 7.55; p < 0.0028 Yield of coniferous seeds 0.44 –0.36 St° of March 2 Regression results: R = 0.570; F = 10.19; p < 0.0001 –0.29 St° of March 2 Regression results: R = 0.265; F = 4.32; p < 0.0248
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t-test
Significance level p
–2.19 1.78
0.0382 0.0976
3.39 2.71 –1.85
0.0025 0.0125 0.0758
2.48 –2.42
0.0203 0.0232
3.01 –2.58
0.0062 0.0164
–1.49
0.1477
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The numbers of S. isodon Turov reliably depend on the temperature of previous autumn. Warm autumn positively influences the species survival rate in the most complex transition period when population experiences maximal negative influence of exo- and endogenous factors [33, 36, 37]. Besides positive influence of this indicator is related to the life style and anatomicophysiological peculiarities of the species that prove that Sorex is the most specialized shrew [10, 15]. These peculiarities are inseparable from trophic preferences: the basis of its ration is earthworms, up to 55–68% [10, 38, 39]. Thus warm autumn furthers the better survival of young animals of S. isodon Turov that can use such food resources for a longer period before the winter. For other species influence of the specified factors has been found out that proves that these are the conditions of winter and early spring that are determinant for further numbers of shrews population [9, 40, 41]. Additional tests for regression model quality (determination of remainder distribution normality on the criteria c 2 and Kolmogorov–Smirnov) have shown high reliability of the built models. It is apparent that the level of species numbers depends on a larger number of factors than it is considered in this work. CONCLUSIONS Shrews association in dark-coniferous taiga of the Eastern Sayan includes 9 species of which 8 are typical inhabitants of mountain forests of the south of Siberia. Analysis of the long-term dynamics of its numbers has shown that phases of different species numbers variation do not coincide therefore the domination structure of the association changes. The largest variation of the domination index is specific for the most numerous species whose participation changes dozens of times. This indicator is more stable for normal and rare species. The share of Sorex at all numbers phases is not lesser than 20%. The co-dominants are S. isodon Turov and S. caecutiens Laxmann. The performed analysis allowed establishing the fact that long-term dynamics of shrew numbers within the mountain forests of the Eastern Sayan is a nonstationary process with harmonic variations and trends. Gradual transformation of association and change in the numbers of individual species take place under the influence of complex factors of different nature bound with succession changes in the vegetation cover. Among the environmental factors included in regression models high average temperatures in March and coniferous seeds yields exert the most significant influence (26–57%) on the numbers of shrews for many years. Authors express sincere gratitude to B. K. Kelbeshekov, V. V. Kozhechkin (State Reserve “Stolby”) and S. A. Abramiv (ISEA SB RAS) for their assistance in collection and statistical processing of the material.
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