Strong variability in bacterioplankton abundance and production in central and western Bay of Bengal

With large influx of freshwater that decreases sea-surface salinities, weak wind forcing of <10 m s⁻¹ and almost always warm (>28°C) sea-surface temperature that stratifies and shallows the mixed layer leading to low or no nutrient injections into the surface, primary production in Bay of Bengal is reportedly low. As a consequence, the Bay of Bengal is considered as a region of low biological productivity. Along with many biological parameters, bacterioplankton abundance and production were measured in the Bay of Bengal during post monsoon (September–October 2002) along an open ocean transect, in the central Bay (CB, 88°E) and the other transect in the western Bay (WB). The latter representing the coastal influenced shelf/slope waters. Bacterioplankton abundances (<2 × 10⁹cells l⁻¹) were similar to those reported from the HNLC equatorial Pacific and the highly productive northern Arabian Sea. Yet, the thymidine uptake rates along CB (average of 1.46 pM h⁻¹) and WB (average of 1.40 pM h⁻¹) were less than those from the northwestern Indian Ocean. These abundances and uptake rates were higher than those in the oligotrophic northwestern Sargasso Sea (<7 × 10⁸ cells l⁻¹; av 1.0 pM h⁻¹). Concentrations of chlorophyll a (chl a), primary production rates and total organic carbon (TOC) were also measured for a comparison of heterotrophic and autotrophic production. In the WB, bacterioplankton carbon biomass equaled ∼ 95% of chl a carbon than just 31% in the CB. Average bacterial:primary production (BP:PP) ratios accounted for 29% in the CB and 31% in the WB. This is mainly due to lower primary productivity (PP) in the WB (281 mg C m⁻² d⁻¹) than in the CB (306 mg C m⁻² day⁻¹). This study indicates that bacteria–phytoplankton relationship differs in the open (CB) and coastal waters (WB). Higher abundance and contrastingly low bacterial production (BP) in WB may be because of the riverine bacteria, brought in through discharges, becoming dormant and unable to reproduce in salinities of 28 or more psu. Heterotrophic bacteria appear to utilize in situ DOC rather rapidly and their carbon demand is ∼50% of daily primary production. It is also apparent that allochthonous organic matter, in particular in the western Bay, is important for meeting their carbon demand.     

Influences of divergent behavioral strategies upon risk allocation in juvenile flatfishes

Animals balance feeding and anti-predator behaviors at various temporal scales. When risk is infrequent or brief, prey can postpone feeding in the short term and temporally allocate feeding behavior to less risky periods. If risk is frequent or lengthy, however, prey must eventually resume feeding to avoid fitness consequences. Species may exhibit different behavioral strategies, depending on the fitness tradeoffs that exist in their environment or across their life histories. North Pacific flatfishes that share juvenile rearing habitat exhibit a variety of responses to predation risk, but their response to risk frequency has not been examined. We observed the feeding and anti-predator behaviors of young-of-the-year English sole (Parophrys vetulus), northern rock sole (Lepidopsetta polyxystra), and Pacific halibut (Hippoglossus stenolepis)—three species that exhibit divergent anti-predator strategies—following exposure to three levels of predation risk: no risk, infrequent (two exposures/day), and frequent (five exposures/day). The English sole responded to the frequent risk treatment with higher feeding rates than during infrequent risk, following a pattern of behavioral response that is predicted by the risk allocation hypothesis; rock sole and halibut did not follow the predicted pattern, but this may be due to the limited range of treatments. Our observations of unique anti-predator strategies, along with differences in foraging and species-specific ecologies, suggest divergent trajectories of risk allocation for the three species.     

Information-theoretic approaches to statistical analysis in behavioural ecology: an introduction

Scientific thinking may require the consideration of multiple hypotheses, which often call for complex statistical models at the level of data analysis. The aim of this introduction is to provide a brief overview on how competing hypotheses are evaluated statistically in behavioural ecological studies and to offer potentially fruitful avenues for future methodological developments. Complex models have traditionally been treated by model selection approaches using threshold-based removal of terms, i.e. stepwise selection. A recently introduced method for model selection applies an information-theoretic (IT) approach, which simultaneously evaluates hypotheses by balancing between model complexity and goodness of fit. The IT method has been increasingly propagated in the field of ecology, while a literature survey shows that its spread in behavioural ecology has been much slower, and model simplification using stepwise selection is still more widespread than IT-based model selection. Why has the use of IT methods in behavioural ecology lagged behind other disciplines? This special issue examines the suitability of the IT method for analysing data with multiple predictors, which researchers encounter in our field. The volume brings together different viewpoints to aid behavioural ecologists in understanding the method, with the hope of enhancing the statistical integration of our discipline.     

Rapid assessment of different oxygenic phototrophs and single-cell photosynthesis with multicolour variable chlorophyll fluorescence imaging

We present a new system for microscopic multicolour variable chlorophyll fluorescence imaging of aquatic phototrophs. The system is compact and portable and enables microscopic imaging of photosynthetic performance of individual cells and chloroplasts using different combinations of blue, green, red or white light. Automated sequential exposure of microscopic samples to the three excitation colours enables subsequent deconvolution of the resulting fluorescence signals and colour marking of cells with different photopigmentation, i.e., cyanobacteria, green algae, red algae and diatoms. The photosynthetic activity in complex mixtures of phototrophs and natural samples can thus be assigned to different types of phototrophs, which can be quantified simultaneously. Here, we describe the composition and performance of the new imaging system and present applications with both natural phytoplankton and microalgal culture samples.     

Graphical spatial models: a new view on interpreting spatial pattern

Graphical models provide an important tool for facilitating communication between scientists, decision-makers, and statisticians—many complicated ecological processes can be described in terms of “box-and-arrow” conceptual diagrams (e.g., Shipley in Cause and correlation in biology: a user’s guide to path analysis, structural equations and causal inferences, Cambridge Universtiy Press, Cambridge, 2000; Clark and Gelfand TRENDS in Ecology and Evolution 21:375–380, 2006). In particular, problems in landscape ecology often involve modeling relationships among multiple physical and/or biological variables that may operate on differing spatial scales (e.g., Rossi et al. in Ecol Monographs 62:277–314, 1992; Legendre et al. in Ecography 25:601–615, 2002; Overmars et al. in Ecol Model 164:257–270, 2003; Brown and Spector in J Appl Ecol 45:1639–1648, 2008; Koniak and Noy-Meir in Ecol Model 220:1148–1158, 2008). These problems are inherently multivariate, though researchers commonly rely on univariate methods, such as spatial regression models, to address them. In this paper, we introduce a multivariate method—graphical spatial models—that extends path analysis to incorporate spatial autocorrelation in one or more variables in a directed graph. We show how both exogenous and endogenous ecological processes as defined by Legendre et al. (Ecography 25:601–615, 2002) and Lichstein et al. (Ecol Monographs 72:445–463, 2002) can be represented in a graph. Most importantly, we show how to translate graphs representing these ecological processes into statistically estimable models. We motivate our theoretical results using an example of stream health data from the Willamette Valley, Oregon. For these data we are interested in the spatial pattern within both riparian land use and an index of stream health, and whether there is an association between land use and stream health, after accounting for these spatial patterns. We use a graphical spatial model to address these ecological questions simultaneously. We find that the health of a stream decreases as the percent of developed land within a 120-m riparian buffer increases; interestingly, there is only evidence of spatial pattern within land use.     

Physiological ecology of the clonal corallimorpharian <Emphasis Type="Italic">Corynactis californica</Emphasis>

For clonal taxa, the reduced genetic variability associated with clonal proliferation is hypothesized to reduce the ability to respond to variable conditions, unless a general-purpose genotype (GPG) confers success in multiple environments. In this study, Corynactis californica (Carlgren 1936) from the subtidal of California was used as a model system to test the hypothesis that clones dampen fluctuations in fitness through a GPG that facilitates phenotypic plasticity. To achieve this goal, tissue composition, respiration, excretion, and growth were compared among clones of C. californica at one site, and a reciprocal transplant experiment was used to test the response of clones to differing conditions at two sites. All experiments were completed at Santa Catalina Island (N 33°25′, W 118°30′) between April and September 1991. Clones at a single site differed significantly in multiple traits, varying as much as 1.6-fold in protein content, 3.4-fold in respiration, and 3.5-fold in excretion. Interestingly, while tissue growth was the most labile trait (differing up to 35.4-fold among clones), polyp fission rates were not significantly different among clones, in part because fission continued even though tissue growth was unable to restore polyp size in between divisions. Partial energy budgets revealed that the majority (47–90%) of the daily energy expenditure was accounted for by respiration, 13–47% by growth, and 0.3–14% by excretion. In the transplant experiment, reaction norms revealed strong effects of the environment on some traits but not others, notably with growth differing between sites in a pattern that differed among clones, and excretion differing between sites; neither respiration nor fission were affected by transplantation. Partial energy budgets revealed that the energy allocation to respiration varied between sites in a pattern that differed among clones, and a similar trend was evident for tissue growth. Together, these results demonstrate that clones of C. californica have markedly different phenotypes and exploit phenotypic plasticity to maintain relatively constant fission rates, even though tissue growth varies greatly among clones and between environments. While these findings support the GPG hypothesis for clones of C. californica—at least based on relative fitness achieved through asexual proliferation—this conclusion depends on the extent to which polyps are successful when they have low rates of tissue growth.     

Distribution-free two-sample comparisons in the case of heterogeneous variances

Behavioral ecologists are often faced with a situation where they need to compare the central tendencies of two samples. The standard tools of the t test and Mann–Whitney U test (equivalent to the Wilcoxon rank-sum test) are unreliable when the variances of the groups are different. The problem is particularly severe when sample sizes are different between groups. The unequal-variance t test (Welch test) may not be suitable for nonnormal data. Here, we propose the use of Brunner and Munzel’s generalized Wilcoxon test followed by randomization to allow for small sample sizes. This tests whether the probability of an individual from one population being bigger than an individual from the other deviates from random expectation. This probability may sometimes be a more clear and informative measure of difference between the groups than a difference in more commonly used measures of central tendency (such as the mean). We provide a recipe for carrying out a statistical test of the null hypothesis that this probability is 50% and demonstrate the effectiveness of this technique for sample sizes typical in behavioral ecology. Although the test is not available in any commercial software package, it is relatively straightforward to implement for anyone with some programming ability. Furthermore, implementations in R and SAS are freely available on the internet.     

Carbon conversion and metabolic rate in two marine sponges

The carbon metabolism of two marine sponges, Haliclona oculata and Dysidea avara, has been studied using a ¹³C isotope pulse-chase approach. The sponges were fed ¹³C-labeled diatoms (Skeletonema costatum) for 8 h and they took up between 75 and 85%. At different times, sponges were sampled for total ¹³C enrichment, and fatty acid (FA) composition and ¹³C enrichment. Algal biomarkers present in the sponges were highly labeled after feeding but their labeling levels decreased until none was left 10 days after enrichment. The sponge-specific FAs incorporated ¹³C label already during the first day and the amount of ¹³C label inside these FAs kept increasing until 3 weeks after labeling. The algal-derived carbon captured by the sponges during the 8-h feeding period was thus partly respired and partly metabolized during the weeks following. Apparently, sponges are able to capture enough food during short periods to sustain longer-term metabolism. The change of carbon metabolic rate of fatty acid synthesis due to mechanical damage of sponge tissue was studied by feeding sponges with ¹³C isotope–labeled diatom (Pheaodactylum tricornutum) either after or before damaging and tracing back the ¹³C content in the damaged and healthy tissue. The filtration and respiration in both sponges responded quickly to damage. The rate of respiration in H. oculata reduced immediately after damage, but returned to its initial level after 6 h. The ¹³C data revealed that H. oculata has a higher metabolic rate in the tips where growth occurs compared to the rest of the tissue and that the metabolic rate is increased after damage of the tissue. For D. avara, no differences were found between damaged and non-damaged tissue. However, the filtration rate decreased directly after damage.     

Near-critical free-surface flows: real fluid flow analysis

An open channel flow with a flow depth close to the critical depth is characterised by a curvilinear streamline flow field that results in steady free surface undulations. Near critical flows of practical relevance encompass the undular hydraulic jump when the flow changes from supercritical (F > 1) to subcritical (F < 1), and the undular weir flow over broad-crested weirs where the flow changes from subcritical (F < 1) to supercritical (F > 1). So far these flows were mainly studied based on ideal fluid flow computations, for which the flow is assumed irrotational and, thus, shear forces are absent. While the approach is accurate for critical flow conditions (F = 1) in weir and flumes, near-critical flows involve long distances reaches, and the effect of friction on the flow properties cannot be neglected. In the present study the characteristics of near-critical free-surface flows are reanalysed based on a model accounting for both the streamline curvature and friction effects. Based on the improved model, some better agreement with experimental results is found, thereby highlighting the main frictional features of the flow profiles.     

A case for quantile regression in behavioral ecology: getting more out of flight initiation distance data

A central goal of behavioral ecology is to quantify and explain variation in behavior. While much previous work has focused on the differences in mean behavior across groups or treatments, we present a complementary approach studying changes in the distribution of the response variable. This is important because changes in the edges of a distribution may be more informative than changes in the mean if behavior at the edges of a distribution better reflects behavioral constraints. Quantile regression estimates the rate of change of conditional quantiles of a response variable and thus allows the study of changes in any part of its distribution. Although quantile regression is gaining popularity in the ecological literature, it is strikingly unused in behavioral ecology. Here, we demonstrate the usefulness of this method by analyzing the relationship between the starting distance (SD) at which an observer approach a focal animal and its flight initiation distance (FID, the distance between the observer and the animal when it decides to flee). In particular, we used a simple model of flight initiation distance to show that in most situations ordinary least-square regression cannot be used to analyse the SD–FID relationship. Quantile regression conducted on the lowest quantiles appears more robust and we applied this approach to data from four bird species. Overall, changes in the lowest FID values appeared to be the most informative to determine if a species displays a “flush early” strategy, a strategy which has been hypothesized to be a general rule. We hope this example will bring quantile regression to the attention of behavioral ecologists as a valuable tool to add to their statistical toolbox.