Prediction of response of zooplankton biomass to climatic and oceanic changes

This paper examines the long-term variation in zooplankton biomass in response to climatic and oceanic changes, using a neural network as a nonlinear multivariate analysis method. Zooplankton data collected from 1951 to 1990 off the shore of northeastern Japan were analyzed. We considered patterns of the Kuroshio and the Oyashio, sea surface temperature, and meteorological parameters as environmental factors that affect zooplankton biomass. Back propagation neural networks were trained to generate mapping functions between environmental variables and zooplankton biomass. The performance of the network models was tested by varying the numbers of input and hidden units. Changes in zooplankton biomass could be predicted from environmental conditions. The neural network yielded predictions with smaller errors than those of predictions determined by linear multiple regression. The sensitivity analysis of networks was used to extract predictive knowledge. The air pressure, sea surface temperature, and some indices of atmospheric circulation were the primary factors for predictions. The patterns of the Kuroshio and the Oyashio demonstrated different effects among sea areas.     

Modelling the horizontal spatial structure of planktonic community in Lake Trasimeno (Umbria,Italy) using multivariate geostatistical methods

Spatial heterogeneity of ecological systems has been recognised in recent years as an important ecological feature of an ecosystem, rather than a mere statistical nuisance. However, although considerable interest has been paid to the development of statistical methods for the analysis of spatial environmental data, when in presence of more species or environmental variables common analyses still fail to recognise the necessity of a joint modelling of the whole correlation structure. In this paper, we propose to study the multivariate spatial autocorrelation of a plankton community by making explicit reference to a spatial linear factor model entailing a set of constraints for the spatial structure of the planktonic species. The data set examined come from an intensive 2-day sampling survey performed in July 1991 on Lake Trasimeno (Italy) to investigate the horizontal spatial heterogeneity and distribution of the planktonic community, from small (50 m) to large (1000–10,000 m) scale. The analysis revealed that zooplankton and phytoplankton essentially have different degrees of heterogeneity and different spatial structures which required separate modelling. On the other hand, the similarity of the spatial autocorrelation found within zooplankton and phytoplankton communities, indicates that at the investigated scales of observation the horizontal organisation of both components is not appreciably affected by species-specific behaviours. The analysis of the multivariate spatial patterns emerging from the mapping of the extracted factors suggested an interpretation of the distribution of macrozooplankton and phytoplankton assemblages in terms of planktonic responses to environmental factors of a lake-size scale.     

Structuring pelagic trophic networks from the biomass size spectra

The selection and establishment of the structure (number and compartments, aggregation criteria, and trophic links) of the food webs is a critical task in trophic modelling. The present work proposes a systematic method to structure trophic networks in pelagic food webs. The biomass-size spectrum (BSS) is a well-established approach to analyze the structure of pelagic communities, and the body size is especially related to the ecological role of the organisms in the pelagic environment. To structure food webs, this work uses detailed arrangements of the community in size classes with increasing widths (like Sheldon-type BSS) as first aggregation criteria, and BSS theory as a framework to integrate the available knowledge about feeding selectivity in order to obtain a method to identify the trophic links between compartments. Diet composition matrices were estimated through the combination of a probability of encounter for each food type and a specific probability of ingestion related to the food size selectivity and other food quality characteristics (e.g., morphology and nutritional quality). The feasibility of this approach has been illustrated through data of size-structured communities extracted from the literature including different planktonic predator guilds (nanoflagellates, cladoceran-dominated zooplankton and copepod-dominated zooplankton) in a high mountain lake (La Caldera, Spain), two subtropical wetland lakes (meso-oligotrophic Laguna Galarza and eutrophic Laguna Iberá, Argentina) and a marine microcosm (Alborán Sea, Mediterranean). The identification of “who eats whom” and “by how much” also allows for more accurate analyses of the trophic control in the BSS. Extensive analyses of the balance between top-down and bottom-up controls were developed for the feeding interactions of the study cases.     

Scale Mismatches,Conservation Planning,and the Value of Social‐Network Analyses

Many of the challenges conservation professionals face can be framed as scale mismatches. The problem of scale mismatch occurs when the planning for and implementation of conservation actions is at a scale that does not reflect the scale of the conservation problem. The challenges in conservation planning related to scale mismatch include ecosystem or ecological process transcendence of governance boundaries; limited availability of fine‐resolution data; lack of operational capacity for implementation; lack of understanding of social‐ecological system components; threats to ecological diversity that operate at diverse spatial and temporal scales; mismatch between funding and the long‐term nature of ecological processes; rate of action implementation that does not reflect the rate of change of the ecological system; lack of appropriate indicators for monitoring activities; and occurrence of ecological change at scales smaller or larger than the scale of implementation or monitoring. Not recognizing and accounting for these challenges when planning for conservation can result in actions that do not address the multiscale nature of conservation problems and that do not achieve conservation objectives. Social networks link organizations and individuals across space and time and determine the scale of conservation actions; thus, an understanding of the social networks associated with conservation planning will help determine the potential for implementing conservation actions at the required scales. Social‐network analyses can be used to explore whether these networks constrain or enable key social processes and how multiple scales of action are linked. Results of network analyses can be used to mitigate scale mismatches in assessing, planning, implementing, and monitoring conservation projects. Discordancia de Escalas, Planificación de la Conservación y el Valor del Análisis de Redes Sociales     

The social network structure of a wild meerkat population: 1. Inter-group interactions

Groups of individuals frequently interact with each other, but typically analysis of such interactions is restricted to isolated dyads. Social network analysis (SNA) provides a method of analysing polyadic interactions and is used to analyse interactions between individuals. We use a population of 12 groups (ca. 250 animals) of wild meerkats (Suricata suricatta) to test whether SNA can also be used to describe and elucidate patterns of inter-group interactions. Using data collected over 24 months, we constructed two sets of networks, based on direct encounters between groups and instances of roving males visiting other groups. We analysed replicated networks of each type of interaction to investigate similarities between networks of different social interactions as well as testing their stability over time. The two network types were similar to each other when derived from long-term data, but showed significant differences in structure over shorter timescales where they varied according to seasonal and ecological conditions. Networks for both types of inter-group interaction constructed from data collected over 3 months reliably described long-term (12- and 24-month) patterns of interactions between groups, indicating a stable social structure despite variation in group sizes and sex ratios over time. The centrality of each meerkat group in roving interactions networks was unaffected by the sex ratio of its members, indicating that male meerkats preferentially visit geographically close groups rather than those containing most females. Indeed, the strongest predictors of network structure were spatial factors, suggesting that, in contrast to analyses of intra-group interactions, analyses of inter-group interactions using SNA must take spatial factors into account.     

The effects of seston food quality on planktonic food web patterns

In planktonic food webs, the conversion rate of plant material to herbivore biomass is determined by a variety of factors such as seston biochemical/elemental composition, phytoplankton cell morphology, and colony architecture. Despite the overwhelming heterogeneity characterizing the plant–animal interface, plankton population models usually misrepresent the food quality constraints imposed on zooplankton growth. In this study, we reformulate the zooplankton grazing term to include seston food quality effects on zooplankton assimilation efficiency and examine its ramifications on system stability. Using different phytoplankton parameterizations with regards to growth strategies, light requirements, sinking rates, and food quality, we examined the dynamics induced in planktonic systems under varying zooplankton mortality/fish predation, light conditions, nutrient availability, and detritus food quality levels. In general, our analysis suggests that high food quality tends to stabilize the planktonic systems, whereas unforced oscillations (limit cycles) emerge with lower seston food quality. For a given phytoplankton specification and resource availability, the amplitude of the plankton oscillations is primarily modulated from zooplankton mortality and secondarily from the nutritional quality of the alternative food source (i.e., detritus). When the phytoplankton community is parameterized as a cyanobacterium-like species, conditions of high nutrient availability combined with high zooplankton mortality led to phytoplankton biomass accumulation, whereas a diatom-like parameterization resulted in relatively low phytoplankton to zooplankton biomass ratios highlighting the notion that high phytoplankton food quality allows the zooplankton community to sustain relatively high biomass and to suppress phytoplankton biomass to low levels. During nutrient and light enrichment conditions, both phytoplankton and detritus food quality determine the extent of the limit cycle region, whereas high algal food quality increases system resilience by shifting the oscillatory region towards lower light attenuation levels. Detritus food quality seems to regulate the amplitude of the dynamic oscillations following enrichment, when algal food quality is low. These results highlight the profitability of the alternative food sources for the grazer as an important predictor for the dynamic behavior of primary producer–grazer interactions in nature.     

Predicting fish diet composition using a bagged classification tree approach: a case study using yellowfin tuna (<Emphasis Type="Italic">Thunnus albacares</Emphasis>)

We provided a classification tree modeling framework for investigating complex feeding relationships and illustrated the method using stomach contents data for yellowfin tuna (Thunnus albacares) collected by longline fishing gear deployed off eastern Australia between 1992 and 2006. The non-parametric method is both exploratory and predictive, can be applied to varying size datasets and therefore is not restricted to a minimum sample size. The method uses a bootstrap approach to provide standard errors of predicted prey proportions, variable importance measures to highlight important variables and partial dependence plots to explore the relationships between explanatory variables and predicted prey composition. Our results supported previous studies of yellowfin tuna feeding ecology in the region. However, the method provided a number of novel insights. For example, significant differences were noted in the prey of yellowfin tuna sampled north of 20°S in summer where oligotrophic waters dominate. The analysis also identified that sea-surface temperature, latitude and yellowfin size were the most important variables associated with dietary differences. The methodology is appropriate for delineating ecosystem-level trophic dynamics, as it can easily incorporate large datasets comprising multiple predators to explore trophic interactions among members of a community. Broad-scale relationships among explanatory variables (environmental, biological, temporal and spatial) and prey composition elucidated by this method then serve to focus and lend validity to subsequent fine-scale analyses of important parameters using standard diet methods and chemical tracers such as stable isotopes.     

Do plant–pollinator interaction networks result from stochastic processes?

Plant–pollinator interaction networks are characterized by several features that cannot be obtained from a totally random network (e.g. nestedness, power law distribution of degree specialization, temporal turnover). One reason is that both plants and pollinators are active for only a part of the year, and so a plant species flowering in spring cannot interact with a pollinator species that is active only in autumn. In this paper we build a stochastic model to simulate the plant–pollinator interaction network, taking into account the duration of activity of each species. To build the model we used an empirical plant–pollinator network from a Mediterranean scrub community surveyed over four years. In our simulated annual cycle we know which plant and pollinator species are active, and thus available to interact. We can obtain simulated plant–pollinator interaction networks with properties similar to the real ones in two different ways: (i) by assuming that the frequency distribution of both plant and pollinator duration of activity follow an exponential function, and that interaction among temporally coexisting species are totally random, and (ii) by assuming more realistic frequency distributions (exponential for pollinators, lognormal for plants) and that the interaction among coexisting species is occurring on a per capita basis. In the latter case we assume that there is a positive relationship between abundance and duration of activity. In our model the starting date of the species activity had little influence on the network structure. We conclude that the observed plant–pollinator network properties can be produced stochastically, and the mechanism shaping the network is not necessarily related to size constraints. Under such conditions co-evolutionary explanations should be given with caution.     

Landsat Thematic Mapper: Detection of Shifts in Community Composition of Coral Reefs

Abstract: We assembled a time series of 20 Landsat thematic mapper images from 1982 to 1996 for Key Largo, Florida, to ascertain whether satellite imagery can detect temporal changes in coral reef communities. Selected reef and control areas were examined for changes in brightness, spectral reflectance, band ratios, spatial texture, and temporal texture (  pixel-to-pixel change over time). We compared the data to known changes in the reef ecosystem of Carysfort Reef and terrestrial sample sites. Changes in image brightness and spectral-band ratios were suggestive of shifts from coral- to algal-dominated community structure, but the trends were not statistically significant. The spatial heterogeneity of the reef community decreased in the early 1980s at scales consistent with known ecological changes to the coral community on Carysfort Reef. An analysis of pixel-scale variation through time, termed temporal texture, revealed that the shallow reef areas are the most variable in regions of the reef that have experienced significant ecological decline. Thus, the process of reef degradation, which alters both the spatial patterning and variability of pixel brightness, can be identified in unclassified thematic mapper images.     

In search of quorum effects in metacommunity structure: species co-occurrence analyses

Alternative models of community assembly emphasize regional, stochastic, dispersal-based processes or local, deterministic, niche-based processes. Community ecology's historical focus on local processes implicitly assumes that local processes surpass regional processes over time or across space to derive nonrandom metacommunity structure (i.e., a quorum effect). Quorum effects are expected late in succession among nearby sites, whereas quorum effects are not expected early in succession among distant sites. I conducted a meta-analysis of zooplankton data sets encompassing time scales of one to thousands of years and spatial scales of <1 m to thousands of kilometers. Species co-occurrence analyses statistically evaluated presence/absence patterns relative to random patterns obtained with Monte Carlo null models. A series of weighted analyses was conducted and alternative randomization algorithms and null models were evaluated. Most zooplankton metacommunities were randomly structured in unweighted analyses, and the distribution of significant structure did not follow quorum effect predictions. Weighted analyses (e.g., by habitat area) revealed significant, nonrandom structure in most zooplankton metacommunities, but the distribution of significant structure still did not adhere well to quorum effect predictions. Finally, additional weighting for study scale (number of sites) nullified most significant area-weighted structure, and again, the distribution of significant structure did not follow quorum effect predictions. Overall, a quorum effect was not supported, perhaps related to zooplankton life histories and energetics and/or the quorum effect itself. Results at the presence/absence level of resolution indicated that local processes did not generally override regional processes over time or across space to drive community structure. A full integration of dispersal- and niche-based concepts in metacommunity dynamics will be most fruitful for unraveling community assembly. Species co-occurrence analyses were scale dependent (habitat area and study size). Future analyses should use weights for important factors (e.g., habitat area), and meta-analyses should include study scale as an additional factor contributing to apparent patterns.     

Zooplankton biodiversity and lake trophic state: explanations invoking resource abundance and distribution

While empirical studies linking biodiversity to local environmental gradients have emphasized the importance of lake trophic status (related to primary productivity), theoretical studies have implicated resource spatial heterogeneity and resource relative ratios as mechanisms behind these biodiversity patterns. To test the feasibility of these mechanisms in natural aquatic systems, the biodiversity of crustacean zooplankton communities along gradients of total phosphorus (TP) as well as the vertical heterogeneity and relative abundance of their phytoplankton resources were assessed in 18 lakes in Quebec, Canada. Zooplankton community richness was regressed against TP, the spatial distribution of phytoplankton spectral groups, and the relative biomass of spectral groups. Since species richness does not adequately capture ecological function and life history of different taxa, features which are important for mechanistic theories, relationships between zooplankton functional diversity (FD) and resource conditions were examined. Zooplankton species richness showed the previously established tendency to a unimodal relationship with TP, but functional diversity declined linearly over the same gradient. Changes in zooplankton functional diversity could be attributed to changes in both the spatial distribution and type of phytoplankton resource. In the studied lakes, spatial heterogeneity of phytoplankton groups declined with TP, even while biomass of all groups increased. Zooplankton functional diversity was positively related to increased heterogeneity in cyanobacteria spatial distribution. However, a smaller amount of variation in functional diversity was also positively related to the ratio of biomass in diatoms/chrysophytes to cyanobacteria. In all observed relationships, a greater variation of functional diversity than species richness measures was explained by measured factors, suggesting that functional measures of zooplankton communities will benefit ecological research attempting to identify mechanisms behind environmental gradients affecting diversity.     

Determining association networks in social animals: choosing spatial–temporal criteria and sampling rates

Social Network Analysis has become an important methodological tool for advancing our understanding of human and animal group behaviour. However, researchers tend to rely on arbitrary distance and time measures when defining ‘contacts’ or ‘associations’ between individuals based on preliminary observation. Otherwise, criteria are chosen on the basis of the communication range of sensor devices (e.g. bluetooth communication ranges) or the sampling frequencies of collection devices (e.g. Global Positioning System devices). Thus, researchers lack an established protocol for determining both relevant association distances and minimum sampling rates required to accurately represent the network structure under investigation. In this paper, we demonstrate how researchers can use experimental and statistical methods to establish spatial and temporal association patterns and thus correctly characterise social networks in both time and space. To do this, we first perform a mixing experiment with Merino sheep (Ovis aries) and use a community detection algorithm that allows us to identify the spatial and temporal distance at which we can best identify clusters of previously familiar sheep. This turns out to be within 2–3 m of each other for at least 3 min. We then calculate the network graph entropy rate—a measure of ease of spreading of information (e.g. a disease) in a network—to determine the minimum sampling rate required to capture the variability observed in our sheep networks during distinct activity phases. Our results indicate the need for sampling intervals of less than a minute apart. The tools that we employ are versatile and could be applied to a wide range of species and social network datasets, thus allowing an increase in both the accuracy and efficiency of data collection when exploring spatial association patterns in gregarious species.     

Three-dimensional modeling of the lower trophic levels in the Ria de Aveiro (Portugal)

The water and the ecosystem dynamics of the Ria de Aveiro, a shallow, multi-branch lagoon located on the northwest coast of Portugal, are simulated using a new fully coupled 3D modeling system. This model couples the hydrodynamic model SELFE (semi-implicit Eulerian-Lagrangian finite element) and an ecological model extended from EcoSim 2.0 to represent zooplankton dynamics. The model application is based on an unstructured grid spatial discretization, which is particularly appropriate for this system given its complex geometry. The baroclinic circulation is calibrated and validated for different environmental conditions, leading to velocity errors smaller than 5 cm/s across the lagoon. Ecological simulations, focused on zooplankton dynamics represented by a site-specific formulation, are then presented and compared against field data for two contrasting environmental conditions: Autumn 2000 and Spring 2001. Results show that the fully coupled model is able to reproduce the dynamics of the ecosystem in the Spring 2001, fitting the model results inside the range of data variation. During this period zooplankton differences between data and model results are of about 0.005 mg C/l (60%), while other ecological tracers’ differences are generally smaller than 20–30% along the several branches of the lagoon. In the Autumn 2000, the model tends to overestimate zooplankton by a factor of 10 and to underestimate phytoplankton and ammonium, with discrepancies of about 0.1 mg C/l and 4.8 μmol N/l, respectively. Factors like the ecological conditions imposed at the boundaries, the input parameters of the ecological model and the simplification of the ecosystem structure, since phytoplankton is the only primary producer considered, may explain the observed differences.     

Scale-dependent response diversity of seabirds to prey in the North Sea

Functional response diversity is defined as the diversity of responses to environmental change among species that contribute to the same ecosystem function. Because different ecological processes dominate on different spatial and temporal scales, response diversity is likely to be scale dependent. Using three extensive data sets on seabirds, pelagic fish, and zooplankton, we investigate the strength and diversity in the response of seabirds to prey in the North Sea over three scales of ecological organization. Two-stage analyses were used to partition the variance in the abundance of predators and prey among the different scales of investigation: variation from year to year, variation among habitats, and variation on the local patch scale. On the year-to-year scale, we found a strong and synchronous response of seabirds to the abundance of prey, resulting in low response diversity. Conversely, as different seabird species were found in habitats dominated by different prey species, we found a high diversity in the response of seabirds to prey on the habitat scale. Finally, on the local patch scale, seabirds were organized in multispecies patches. These patches were weakly associated with patches of prey, resulting in a weak response strength and a low response diversity. We suggest that ecological similarities among seabird species resulted in low response diversity on the year-to-year scale. On the habitat scale, we suggest that high response diversity was due to interspecific competition and niche segregation among seabird species. On the local patch scale, we suggest that facilitation with respect to the detection and accessibility of prey patches resulted in overlapping distribution of seabirds but weak associations with prey. The observed scale dependencies in response strength and diversity have implications for how the seabird community will respond to different environmental disturbances.     

Ecological sexual segregation in fallow deer (Dama dama): a multispatial and multitemporal approach

We questioned the different interpretations of ecological sexual segregation from a novel perspective, i.e., by carrying out diverse temporal and spatial scale analyses within a long-term study (1984–2003). Thus we combined spatial (small/large) and temporal (small/large) scale analyses to identify the factors generating sexual segregation in fallow deer in San Rossore, Italy. The study site was divided into an eastern sector characterized by human disturbance (DS) and a western undisturbed sector (US). According to census data, human presence increased in DS from 1984, and while females gradually abandoned it, males remained—thus supporting the predation risk hypothesis (large spatial and temporal scale)—and actually increased their presence in DS, where they seemingly benefited from a lower female density. This supported the indirect competition hypothesis. The analysis of data on a large temporal and small spatial scale confirmed that intersexual competition, in particular for grass, was higher in a crowded pasture in US. Observations by means of radio-telemetry of 23 adult females and 25 adult males (1997–2001, reduced temporal and large spatial scale) showed that large scale segregation was relevant during the day and disappeared at night, when disturbance was absent and also the females reached DS. This also supported the predation risk hypothesis. Moreover, sexes showed different habitat choices inside DS at night, thus supporting the forage selection hypothesis (small spatial and temporal scale). In conclusion, failure to address the whole set of combinations of spatial and temporal scale analyses would have led to monocausal explanations of ecological sexual segregation.     

A three-trophic level estuarine model: Synergism of two mechanistic simulations

Few numerical simulations have attempted to include a high degree of biological detail for several trophic levels. Typically, in planktonic ecosystem models, if the dynamics of nutrients, phytoplankton and herbivorous zooplankton are formulated with ecological complexity, then carnivores are ignored, forced or modeled in an extremely simplified manner. Extensive mechanistic detail for important carnivores is difficult to represent because reliable and relevant ecological data are rarely available for appropriate species and local populations. Further, the wide temporal and spatial differences between life histories of lower plankton and carnivores may be technically difficult to model.In Narragansett Bay, Rhode Island, the ctenophore Mnemiopsis leidyi is an important carnivore to which these objections do not apply. A detailed carbon-based simulation model of this population of ctenophores was developed independently from an ecosystem model of Narragansett Bay which included detailed interactions between phytoplankton, primarily herbivorous zooplankton and nutrients. The interfacing of these two models without changing any of the formulations or values of the coefficients provided a test of the commonly used practice of forcing certain components. Both models were originally constructed with the biomass of a critical compartment forced according to observed data; in the plankton model, ctenophores were forced, and in the ctenophore model, zooplankton were forced.Predicted biomasses for zooplankton and ctenophores in the combined model were similar to the results of the two parent models, but improved relative to the actual field observations. From the findings it appears that the strategy of forcing is valid provided the forced patterns are appropriate and reasonable.     

Daily temporal structure in African savanna flower visitation networks and consequences for network sampling

Ecological interaction networks are a valuable approach to understanding plant-pollinator interactions at the community level. Highly structured daily activity patterns are a feature of the biology of many flower visitors, particularly provisioning female bees, which often visit different floral sources at different times. Such temporal structure implies that presence/absence and relative abundance of specific flower-visitor interactions (links) in interaction networks may be highly sensitive to the daily timing of data collection. Further, relative timing of interactions is central to their possible role in competition or facilitation of seed set among coflowering plants sharing pollinators. To date, however, no study has examined the network impacts of daily temporal variation in visitor activity at a community scale. Here we use temporally structured sampling to examine the consequences of daily activity patterns upon network properties using fully quantified flower-visitor interaction data for a Kenyan savanna habitat. Interactions were sampled at four sequential three-hour time intervals between 06:00 and 18:00, across multiple seasonal time points for two sampling sites. In all data sets the richness and relative abundance of links depended critically on when during the day visitation was observed. Permutation-based null modeling revealed significant temporal structure across daily time intervals at three of the four seasonal time points, driven primarily by patterns in bee activity. This sensitivity of network structure shows the need to consider daily time in network sampling design, both to maximize the probability of sampling links relevant to plant reproductive success and to facilitate appropriate interpretation of interspecific relationships. Our data also suggest that daily structuring at a community level could reduce indirect competitive interactions when coflowering plants share pollinators, as is commonly observed during flowering in highly seasonal habitats.     

长江口南北支浮游动物群落生态学研究

长江口特殊的生态环境使得浮游动物的种类组成、密度和时空分布等生态特征有别于其它水体。2005年秋季（丰水期）和2006年春季（枯水期）对长江口南北支浮游动物进行了2个航次的调查,沿南北支由西向东设立3个采样断面共20个采样点。共采集到浮游动物227种,其中轮虫65种,原生动物107种,枝角类15种,桡足类40种。优势种包括龟甲轮虫（Keratella）、刺簇多肢轮虫（Polyarthra trigla）、萼花臂尾轮虫（Brachionus calyciflorus）、砂壳虫（Difflugia）、表壳虫（Arcella）、砂壳纤毛虫（Tintinnid）、中华哲水蚤（Calanus sinicus）、汤匙华哲水蚤（Sinocalanus dorrii）、广布中剑水蚤（Mesocyclops leuckarti）、象鼻溞（Bosmina）等。文章对南北两支浮游动物的种类组成和结构进行了比较,南支浮游动物的种类、数量及生物多样都高于北支,南北两支的浮游动物群落相似度很低。南北两支水域环境的不同造成其浮游动物群落结构的较大差异,文章分析了环境因子与浮游动物群落结构的相关性,其中水温是重要的影响因素,水温的季节性决定了浮游动物在时间分布上的变化。盐度对浮游动物群落结构的影响主要决定了其物种生态类型及空间分布。从整体上看,南北支主要受长江径流控制,浮游动物的种类组成以淡水种为主,咸水种在断面3出现较多。     

Estimating zooplankton biomass through image analysis

Zooplankton biomass can be reliably estimated by a non-destructive method based on the statistical relationship between biovolume and the contents of carbon and nitrogen. Integrated zooplankton biovolume and the corresponding organic C and N contents were analysed in paired fresh and fixed (hexamine-buffered formalin) samples. Sample biovolume was estimated through the integration of individual volumes obtained by semi-automatic image analysis on fixed zooplankton samples. The corresponding C and N contents of paired fresh and preserved zooplankton were analysed with a Carlo-Erba C-H-N Analyser. The method allows simultaneous measurement of integrated and individual numbers and biomass (biovolume, C and N) spectrum. It is non-destructive and allows the minimization of errors and variability attributable to differences in the handling processes of samples and to the presence of particles other than zooplankton, like phytoplankton or detritus particulate matter.