Community structure and seasonal dynamics of planktonic ciliates along salinity gradients

The ciliate community structure and seasonal dynamics in a solar saltern of the Yellow Sea were studied based oil 4 sampling dates and 8 stations with salinities from 27.7 parts per thousand to 311.0 parts per thousand. The effects of the type and concentration of the fixative used (Lugol's and Bouin's) were tested at the first sampling date. Fixative type and fixative concentration had significant effects on ciliate abundance and blovolume, with 1% Lugol's giving the best results. A detailed investigation using live observations and protargol staining techniques revealed a total of 98 morphospecies from 8 sampling stations. There was obvious seasonal variation in species composition at most of the stations, but this tended to be less distinct with increasing salinity, as the dominant ciliate group shifted from oligotrichs to heterotrichs. Ciliate abundance varied from 4.40 x 10(1) to 2.11 x 10(5) cells l(-1) and biomass ranged between 2.39 and 9.87 x 10(3) mu g Cl-1 (at a salinity of 147.6 parts per thousand). Both abundance and biomass decreased abruptly when salinity exceeded 100-150 parts per thousand. Statistical analyses Suggested that the dynamics of ciliate abundance and biomass were regulated by both salinity and by season, but those of diversity and species richness were mainly controlled by salinity and both significantly decreased with increasing salinity. (C) 2009 Elsevier GmbH. All rights reserved.

Changes in the structure of a zooplankton community during a Ceratium (dinoflagellate) bloom in a eutrophic fishless pond

The community structure of zooplankton was studied in a eutrophic, fishless Japanese pond. The ecosystem was dominated by a dinoflagellate, Ceratium hirundinella, two filter-feeding cladocerans, Daphnia rosea and Ceriodaphnia reticulata, and an invertebrate predator, the dipteran Chaoborus flavicans. The midsummer zooplankton community showed a large change in species composition (the Daphnia population crashed) when a heavy Ceratium bloom occurred. It is shown that (i) the rapid density decline of D.rosea in mid-May was mainly caused by a shortage of edible phytoplankton, which was facilitated by the rapid increase in C.hirundinella abundance; (ii) the low density of D.rosea in June-July was considered to be mainly caused by the blooming of Ceratium hirundinella (which may inhibit the feeding process of D.rosea), while predation by C.flavicans larvae, the changing temperature, the interspecific competition and the scarcity of edible algae were not judged to be important; (iii) the high summer biomass of the planktonic C.flavicans larvae was maintained by the bloom of C.hirundinella, because >90% of the crop contents of C.flavicans larvae were C.hirundinella during this period. The present study indicates that the large-sized cells or colonies of phytoplankton are not only inedible by most cladocerans, but the selective effect of the blooming of these algae can also influence the composition and dominance of the zooplankton community, especially for the filter-feeding Cladocera, in a similar way as the selective predation by planktivorous fish. The large-sized phytoplankton can also be an important alternative food for ominivorous invertebrate predators such as Chaoborus larvae, and thus may affect the interactions between these predators and their zooplanktonic prey. In this way, such phytoplankton may play a very important role in regulating the dynamics of the aquatic food web, and become a driving force in shaping the community structure of zooplankton.

Efficiency Dynamics on Two Coupled Small-World Networks

We investigate the effect of clusters in complex networks on efficiency dynamics by studying a simple efficiency model in two coupled small-world networks. It is shown that the critical network randomness corresponding to transition from a stagnant phase to a growing one decreases to zero as the connection strength of clusters increases. It is also shown for fixed randomness that the state of clusters transits from a stagnant phase to a growing one as the connection strength of clusters increases. This work can be useful for understanding the critical transition appearing in many dynamic processes on the cluster networks.

EFFICIENCY DYNAMICS ON SCALE-FREE NETWORKS WITH COMMUNITIES

The simple efficiency model is developed on scale-free networks with communities to study the effect of the communities in complex networks on efficiency dynamics. For some parameters, we found that the state of system will transit from a stagnant phase to a growing phase as the strength of community decreases.

Soil microbial community analysis using terminal restriction fragment length polymorphisms

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a polymerase chain reaction (PCR)-fingerprinting method that is commonly used for comparative microbial community analysis. The method can be used to analyze communities of bacteria, archaea, fungi, other phylogenetic groups or subgroups, as well as functional genes. The method is rapid, highly reproducible, and often yields a higher number of operational taxonomic units than other, commonly used PCR-fingerprinting methods. Sizing of terminal restriction fragments (T-RFs) can now be done using capillary sequencing technology allowing samples contained in 96- or 384-well plates to be sized in an overnight run. Many multivariate statistical approaches have been used to interpret and compare T-RFLP fingerprints derived from different communities. Detrended correspondence analysis and the additive main effects with multiplicative interaction model are particularly useful for revealing trends in T-RFLP data. Due to biases inherent in the method, linking the size of T-RFs derived from complex communities to existing sequence databases to infer their taxonomic position is not very robust. This approach has been used successfully, however, to identify and follow the dynamics of members within very simple or model communities. The T-RFLP approach has been used successfully to analyze the composition of microbial communities in soil, water, marine, and lacustrine sediments, biofilms, feces, in and on plant tissues, and in the digestive tracts of insects and mammals. The T-RFLP method is a user-friendly molecular approach to microbial community analysis that is adding significant information to studies of microbial populations in many environments.

Effects of increased pCO(2) and temperature on the North Atlantic spring bloom. I. The phytoplankton community and biogeochemical response

The North Atlantic spring bloom is one of the largest annual biological events in the ocean, and is characterized by dominance transitions from siliceous (diatoms) to calcareous (coccolithophores) algal groups. To study the effects of future global change on these phytoplankton and the biogeochemical cycles they mediate, a shipboard continuous culture experiment (Ecostat) was conducted in June 2005 during this transition period. Four treatments were examined: (1) 12 degrees C and 390 ppm CO2 (ambient control), (2) 12 degrees C and 690 ppm CO2 (high pCO(2)) (3) 16 degrees C and 390 ppm CO2 (high temperature), and (4) 16 degrees C and 690 ppm CO2 ('greenhouse'). Nutrient availability in all treatments was designed to reproduce the low silicate conditions typical of this late stage of the bloom. Both elevated pCO(2) and temperature resulted in changes in phytoplankton community structure. Increased temperature promoted whole community photosynthesis and particulate organic carbon (POC) production rates per unit chlorophyll a. Despite much higher coccolithophore abundance in the greenhouse treatment, particulate inorganic carbon production (calcification) was significantly decreased by the combination of increased pCO(2) and temperature. Our experiments suggest that future trends during the bloom could include greatly reduced export of calcium carbonate relative to POC, thus providing a potential negative feedback to atmospheric CO2 concentration. Other trends with potential climate feedback effects include decreased community biogenic silica to POC ratios at higher temperature. These shipboard experiments suggest the need to examine whether future pCO2 and temperature increases on longer decadal timescales will similarly alter the biological and biogeochemical dynamics of the North Atlantic spring bloom.

Cellular automata: Simulating alpine tundra vegetation dynamics in response to global warming

This study attempts to model alpine tundra vegetation dynamics in a tundra region in the Qinghai Province of China in response to global warming. We used Raster-based cellular automata and a Geographic Information System to study the spatial and temporal vegetation dynamics. The cellular automata model is implemented with IDRISI's Multi-Criteria Evaluation functionality to simulate the spatial patterns of vegetation change assuming certain scenarios of global mean temperature increase over time. The Vegetation Dynamic Simulation Model calculates a probability surface for each vegetation type, and then combines all vegetation types into a composite map, determined by the maximum likelihood that each vegetation type should distribute to each raster unit. With scenarios of global temperature increase of I to 3 degrees C, the vegetation types such as Dry Kobresia Meadow and Dry Potentilla Shrub that are adapted to warm and dry conditions tend to become more dominant in the study area.