Trophic state (TSI SD ) and mixing type significantly influence pelagic zooplankton biodiversity in temperate lakes (NW Poland)

PeerJ

article

Łukasz Sługocki¹  Robert Czerniawski¹ 

[1] Faculty of Biology, University of Szczecin;University of Szczecin, Center of Molecular Biology and Biotechnology

关键词: Species richness;    Shannon index;    Zooplankton;    Rotifera;    Cladocera;    Copepoda;    Mixing type;    Lakes;    Trophic state;    Crustacea;   

DOI  :  10.7717/peerj.5731

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

BackgroundLake depth and the consequent mixing regime and thermal structure have profound effects on ecosystem functioning, because depth strongly affects the availability of nutrients, light, and oxygen. All these conditions influence patterns of zooplankton diversity. Zooplankton are a key component of the aquatic environment and are essential to maintaining natural processes in freshwater ecosystems. However, zooplankton biodiversity can be different regard to depth, mixing type and trophic state. Therefore, the aim of this study was to examine how depth and mixing regime affect zooplankton diversity in lakes. We also investigated the vertical distribution of diversity across a trophic gradient of lakes.MethodsA total of 329 zooplankton samples from 79 temperate lakes (36 polymictic and 43 dimictic) were collected. The biodiversity of zooplankton was calculated using species richness (SR) and the Shannon index (SI). An index based on Secchi disc visibility was used to determine the trophic state index (TSISD) of lakes. The one-way ANOVA with Duncan’s post hoc test were used to determine differences in zooplankton biodiversity between mictic lake types and thermal layers. To find the best predictors for zooplankton biodiversity a multiple stepwise regression was used. The rarefaction method was used to evaluate the impact of mixing types, thermal layers, and the TSISDon zooplankton biodiversity indices. A Sørensen similarity analysis and nonmetric multidimensional scaling (NMDS) were performed to describe the similarity patterns in species composition among lakes.ResultsWe identified a total of 151 taxa from 36 polymictic and 43 dimictic lakes. Lake depth and the TSISD were significantly correlated with the biodiversity of lake zooplankton. The results of ANOVA and Duncan tests show that mictic type and thermal zones had a significant effect on zooplankton biodiversity. The rarefaction curve showed significant differences in zooplankton biodiversity, which was greater in lakes with lower trophic state. Ordination by NMDS showed clustering of different mictic types, thermal layers, and composition changes throughout the TSISDprofile. Moreover, we determined that polymictic lakes are more heterogeneous than dimictic lakes in regard to zooplankton similarities.DiscussionBoth mictic lake types were characterized by varying levels of zooplankton biodiversity, which is shaped by the communities’ response to lake depth, thermal layers and TSISD values. The zooplankton SR and SI (during daylight hours) depends greatly on the mixing type. Lake type also indicates the importance of the metalimnion in shaping zooplankton biodiversity in dimictic lakes. In addition, data from NW Polish lakes indicated that the increase of the TSISD leads to taxonomic shifts and has a negative effect on the diversity of all groups of zooplankton.

【 授权许可】

CC BY