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Download Article (PDF) Biologia 65/6: 1019—1027, 2010 Section Zoology DOI: 10.2478/s11756-010-0123-6 Species co-occurrences based on a presence/absence null model for Copepoda and cladocerans in Patagonia and Tierra del Fuego lakes and ponds Patricio De los Ríos1, Andrés Mancilla2 & Marcela Vega1 1Laboratorio de Limnología y Recursos Hídricos, Escuela de Ciencias Ambientales, Facultad de Recursos Naturales, Uni- versidad Católica de Temuco, Casilla 15-D, Temuco, Chile; e-mail: [email protected] 2Instituto de la Patagonia, Universidad de Magallanes, Avenida Bulnes 01855,Casilla113-D,PuntaArenas,Chile Abstract: The zooplankton assemblages in southern Chilean Patagonia are characterized by calanoid dominance and low species number that is observable under oligotrophic status and wide conductivity values, whereas at mesotrophic status the daphnids are dominant with high species number, and finally at hyper-saline environments halophilic species such as Artemia persimilis and/or the calanoid Boeckella poopensis predominate. In the present study data of different lakes and ponds between 45–53◦ S were analyzed, with the aim to determine potential structures at different sites. For this purpose a null model based in guild structure was applied, considering each guild a different kind of water body (lake, small lake, permanent pond, ephemeral pond, and saline lake). The results revealed in two simulations that guild are structured. These results are similar with other descriptions on the basis of null models that revealed a random pattern of species associations for similar ecosystems due to many species repeated in all or practically all studied sites or similarities of ecological features. Ecological and biogeographical topics were discussed. Key words: Calanoid; Daphnia; Artemia; lakes; ponds; null model Introduction Rodríguez-Fernández et al. 2006; Segurado & Figueredo 2007). These null models are more robust in comparison The zooplankton assemblages in lakes and ponds in cen- with deterministic models (Gotelli 2000, 2001). tral and southern Patagonia (44–53◦ S) have different The aim of the present study is to apply a null patterns (Soto 1990) due the heterogeneity of water model analysis based on presence-absence of species bodies. For example, in large lakes, small lakes and shal- matrix to determine the absence regulator factors for low ponds of Torres del Paine zooplankton species asso- explanation of species associations in zooplankton in ciations are regulated by conductivity and the trophic central and southern Patagonian lakes and ponds. The status (Soto & De los Ríos 2006; De los Ríos et al. aim of this procedure is the use of non-randomness test 2008a; De los Ríos & Soto 2009). This pattern is sim- to understand community ecology in inland water zoo- ilar descriptions for lakes and ponds in Argentinean plankton. Patagonia (Modenutti et al. 1998) and with descrip- tions of New Zealand lakes and ponds (Jeppensen et al. 1997, 2000). The patterns observed for zooplank- Material and methods ton assemblages in southern Chilean lakes are differ- Study area ent to Europe and North America that have high num- The studied region is located between 45–53◦ S(Aysenand ber of species which are directly associated with surface Magallanes region, Chile), and it is characterized by the (Dodson 1992), and with marked dominance of daphnid presence of large diversity of landscapes, glaciers, valleys, cladocerans (Gillooly & Dodson 2000). snowcaps, lakes and ponds (Niemeyer & Cereceda 1984). From this point of view zooplankton assemblages Within the water bodies there are numerous large and deep are not random, regulatory or deterministic factors ex- lakes, small lakes, shallow permanent and ephemeral ponds, ists to explain the community structure. The absence and saline lakes (De los Ríos 2008). The climate is charac- terized by precipitations in the north from 51◦ S, whereas in of regulatory factors and the random distribution in ◦ the south of 51 S (Niemeyer & Cereceda 1984), the climate species co-occurrence are the basis of null models, one is subpolar with less than 700 mm of precipitation a year, of these models used the presence and absence of species and between October and December there is exposition to to determine the absence of deterministic factors as strong winds of approximately 100 km h−1 (Campos et al. regulators of species co-occurrence or guild structure 1994a, b; De los Ríos & Soto 2009). The studied region has (Frutos 1998; Gotelli 2000, 2001; Abelha et al. 2006; difficult access due its marked isolation, that is an advan- c 2010 Institute of Zoology, Slovak Academy of Sciences 1020 P. De los Ríos et al. tage because these ecosystems are practically pristine, but column sums of the matrix are preserved. Thus, each ran- the disadvantage is that it is difficult to carry out system- dom community contains the same number of species as the atic field works due to geographical and climatic features original community (fixed column) and each species occurs (Campos et al. 1994a, b; De los Ríos 2008; De los Ríos & with the same frequency as in the original community (fixed Soto 2009). row). (2) Fixed-Equiprobable. In this algorithm only the row sums are fixed and the columns are treated as equiprobable. Data collection This null model considers all the sites (columns) as equally Literature revision. Meta-analysis was applied and the in- available for all species, which occur in the same proportions formation was obtained from literature, according to de- as in the original communities. (3) Fixed-Proportional. This scriptions of Luiselli et al. (2007) and Luiselli (2008a, b) model keeps the species occurrence totals the same as in the nevertheless, in the present study data of species pres- original community and the probability that a species oc- ence/absence for Chilean Patagonian lakes and ponds were curs at a site (column) is proportional to the column total considered; many of these sites are located in a zone difficult for that sample. for access and with a weather characterized by strong wind The variance ratio is the ratio of the variance of the storms (Soto et al. 1994). The information for species asso- column sum to the sum of the row variances. Unlike C- ciations in central and southern Patagonian lakes and ponds score index, the variance ratio does not measure patterns was obtained from literature (Villalobos 1999; De los Ríos of co-occurrence within the matrix, but it is determined ex- & Contreras, 2005; De los Ríos 2005; Soto & De los Ríos clusively by row and column sums of the matrix (Gotelli 2006; De los Ríos & Soto 2007; De los Ríos et al. 2008a, b; 2000). Therefore, this model is not valid for the fixed-fixed Rogers et al. 2008). null model. For this reason, the variance ratio was not tested Field works. Information obtained during field works in Oc- with this null model. The variance ratio measures the vari- tober 2001, October 2006, April 2007, January 2008, and ability in the number of species by sample. If species richness May 2009 was included. The zooplankton was collected us- is regulated by biological interactions, communities should ing horizontal hauls in shallow ponds, whereas in small converge on a relatively constant number of species per sam- lakes, and large and deep lakes, the zooplankton was col- ple (Gotelli 2000). In a competitively structured community, lected by vertical hauls from a boat, for both procedures, by the observed variance ratio should be significantly smaller µ using an Apstein net of 20 cm diameter and 100 mmesh than that expected by chance (Tiho & Johens 2007). A null size, according to the descriptions of Soto & De los Ríos model analysis was carried out using the Ecosim version 7.0 (2006) and De los Ríos & Soto (2009). Zooplankton spec- software (Tondoh 2006; Tiho & Johens 2007; De los Ríos imens were fixed with absolute ethanol, and identified us- 2008; De los Ríos et al. 2008b; Gotelli & Entsminger 2009). ing specialized literature (Araya & Zú˜niga 1985; Reid 1985; Bayly 1992a, b; Paggi 1999; De los Ríos & Zú˜niga 2000; Brték & Mura 2000; Rogers et al. 2008). This literature Results and discussion was also used to explain or confirm the taxonomic status of species found in the literature revision. The information obtained from literature and field observations was applied The results denoted low species richness in large for each site and the species / genera ratio was determined lakes and saline lakes, whereas in small lakes, shal- (Gotelli 2000, 2001). low permanent and temporal ponds a high number of species was reported (Table 1). For large and deep Data analysis lakes and small lakes, the most representative species The data obtained from literature and field works were or- were Boeckella gracilipes (Daday, 1902), B. michaelseni dered using an absence/presence matrix. A Checkerboard (Mrázek, 1901), Daphnia pulex (Scourfield, 1877), and score (“C-score”) is based on the number of checkerboard Ceriodaphnia dubia (Richard, 1894), that agree with units that can be found for each species pair. The number of ◦ checkerboard units (CU) for any species can be calculated similar results for Patagonian lakes (38–51 S; Soto & as: Zú˜niga 1991; Menu-Marque et al. 2000; De los Ríos 2008; Table 2). Whereas for shallow temporal and per- CU =(Ri − S)(Rj − S)(1)manent ponds the most representative species were B. gracilipes, B. michaelseni, B. poppei (Mrázek, 1901), where Ri and Rj are the row totals for species and i and Parabroteas sarsi (Mrázek, 1901) and Daphnia da- species j, respectively, and S is the number of sites occu- dayana (Paggi, 1999) (Table 2) that are similar to de- pied by both species. The C-score measures the degree to scriptions for sub-Antarctic counterparts (Hannson et which species pairs segregates across a set of samples, but it does not require complete segregation. The larger C-score al.
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