Diel and tidal cycles regulate larval dynamics in salt marshes and mangrove forests

Variation in the release and recruitment of larvae of estuarine invertebrates affects the distribution and abundance of adults, as well as trophic interactions in both the plankton and the benthos. Larval release and supply are often timed to environmental cycles such as the diel and tidal cycles. Here, we determined using plankton tows whether the abundance of larvae spanning salt marsh and mangrove habitats across the intertidal landscape varied with diel and tidal cycles. Using three different sampling designs across two sites and within each of two estuaries over a 12-month period, we covered a range of spatial and temporal scales. This allowed us to test the general prediction that densities of meroplankton in the water column would be greater during nocturnal ebb tides than during other phases of the diel or tidal cycle. As predicted, nocturnal ebb tides yielded the highest densities of meroplanktonic larvae and were dominated by first-stage crab zoeae and this finding was most pronounced in the salt marsh. Throughout the course of the year, greater numbers of meroplankters consistently occurred during the ebb tide compared with the flood tide. The densities of other taxa (e.g. gastropods and polychaetes) showed no clear trends with diel or tidal cycles. This study highlights the effects of these pervasive physical cycles on the timing of larval release and supply in the salt marsh–mangrove complex, and emphasises their contribution to the trophic interactions and the dynamics of benthic populations within estuaries.     

The behaviour of giant clams (Bivalvia: Cardiidae: Tridacninae)

Giant clams, the largest living bivalves, live in close association with coral reefs throughout the Indo-Pacific. These iconic invertebrates perform numerous important ecological roles as well as serve as flagship species—drawing attention to the ongoing destruction of coral reefs and their associated biodiversity. To date, no review of giant clams has focussed on their behaviour, yet this component of their autecology is critical to their life history and hence conservation. Almost 100 articles published between 1865 and 2014 include behavioural observations, and these have been collated and synthesised into five sections: spawning, locomotion, feeding, anti-predation, and stress responses. Even though the exact cues for spawning in the wild have yet to be elucidated, giant clams appear to display diel and lunar periodicities in reproduction, and for some species, peak breeding seasons have been established. Perhaps surprisingly, giant clams have considerable mobility, ranging from swimming and gliding as larvae to crawling in juveniles and adults. Chemotaxis and geotaxis have been established, but giant clams are not phototactic. At least one species exhibits clumping behaviour, which may enhance physical stabilisation, facilitate reproduction, or provide protection from predators. Giant clams undergo several shifts in their mode of acquiring nutrition; starting with a lecithotrophic and planktotrophic diet as larvae, switching to pedal feeding after metamorphosis followed by the transition to a dual mode of filter feeding and phototrophy once symbiosis with zooxanthellae (Symbiodinium spp.) is established. Because of their shell weight and/or byssal attachment, adult giant clams are unable to escape rapidly from threats using locomotion. Instead, they exhibit a suite of visually mediated anti-predation behaviours that include sudden contraction of the mantle, valve adduction, and squirting of water. Knowledge on the behaviour of giant clams will benefit conservation and restocking efforts and help fine-tune mariculture techniques. Understanding the repertoire of giant clam behaviours will also facilitate the prediction of threshold levels for sustainable exploitation as well as recovery rates of depleted clam populations.     

How complex do models need to be to predict dispersal of threatened species through matrix habitats?

Persistence of species in fragmented landscapes depends on dispersal among suitable breeding sites, and dispersal is often influenced by the "matrix" habitats that lie between breeding sites. However, measuring effects of different matrix habitats on movement and incorporating those differences into spatially explicit models to predict dispersal is costly in terms of time and financial resources. Hence a key question for conservation managers is: Do more costly, complex movement models yield more accurate dispersal predictions? We compared the abilities of a range of movement models, from simple to complex, to predict the dispersal of an endangered butterfly, the Saint Francis' satyr (Neonympha mitchellii francisci). The value of more complex models differed depending on how value was assessed. Although the most complex model, based on detailed movement behaviors, best predicted observed dispersal rates, it was only slightly better than the simplest model, which was based solely on distance between sites. Consequently, a parsimony approach using information criteria favors the simplest model we examined. However, when we applied the models to a larger landscape that included proposed habitat restoration sites, in which the composition of the matrix was different than the matrix surrounding extant breeding sites, the simplest model failed to identify a potentially important dispersal barrier, open habitat that butterflies rarely enter, which may completely isolate some of the proposed restoration sites from other breeding sites. Finally, we found that, although the gain in predicting dispersal with increasing model complexity was small, so was the increase in financial cost. Furthermore, a greater fit continued to accrue with greater financial cost, and more complex models made substantially different predictions than simple models when applied to a novel landscape in which butterflies are to be reintroduced to bolster their populations. This suggests that more complex models might be justifiable on financial grounds. Our results caution against a pure parsimony approach to deciding how complex movement models need to be to accurately predict dispersal through the matrix, especially if the models are to be applied to novel or modified landscapes.     

ERI evaluation of injectates used at a dry‐cleaning site

A former dry‐cleaning site in Jackson, Tennessee, has undergone remediation to treat dense nonaqueous‐phase liquid (trichloroethene [TCE] and tetrachloroethene [PCE]) contamination in the subsurface. The dry cleaning operation closed in 1977. In 2002, a series of injections were made at the site consisting of corn syrup, vegetable oils, and Simple Green®. In 2004, approximately 200 cubic yards of contaminated soil were excavated, and the bottom of the excavation was covered with sodium lactate. In 2009, the site was characterized using proprietary electrical resistivity imaging (ERI; commercially available as Aestus GeoTrax Surveys^TM). Follow‐up confirmation soil borings targeted anomalies detected via the geophysical work. The results indicate an extremely electrically conductive (less than 1 ohm‐m) vadose zone downgradient from the injection wells, and extremely electrically resistive areas (greater than 10,000 ohm‐m) in the phreatic zone near the injection area. The sample data indicate that the electrically resistive anomalous zones contain moderate to high concentrations of undegraded dry‐cleaning compounds. Electrically conductive anomalous zones are interpreted to be areas of biological activity generated by the amendments injected into the subsurface based on the extreme conductivity values detected, the chemical composition (i.e., PCE degradates are present), and the dominant vadose‐zone location of the conductive zones. © 2012 Wiley Periodicals, Inc.     

MBM fuel feeding system design and evaluation for FBG pilot plant

A biomass fuel feeding system has been designed, constructed and evaluated for a fluidized bed gasifier (FBG) pilot plant at the University of Saskatchewan (Saskatoon, SK, Canada). The system was designed for meat and bone meal (MBM) to be injected into the gasifier at a mass flow-rate range of 1-5 g/s. The designed system consists of two stages of screw conveyors, including a metering stage which controlled the flow-rate of fuel, a rotary airlock and an injection conveyor stage, which delivered that fuel at a consistent rate to the FBG. The rotary airlock which was placed between these conveyors, proved unable to maintain a pressure seal, thus the entire conveying system was sealed and pressurized. A pneumatic injection nozzle was also fabricated, tested and fitted to the end of the injection conveyor for direct injection and dispersal into the fluidized bed. The 150 mm metering screw conveyor was shown to effectively control the mass output rate of the system, across a fuel output range of 1-25 g/s, while the addition of the 50mm injection screw conveyor reduced the irregularity (error) of the system output rate from 47% to 15%. Although material plugging was found to be an issue in the inlet hopper to the injection conveyor, the addition of air sparging ports and a system to pulse air into those ports was found to successfully eliminate this issue. The addition of the pneumatic injection nozzle reduced the output irregularity further to 13%, with an air supply of 50 slpm as the minimum air supply to drive this injector. After commissioning of this final system to the FBG reactor, the injection nozzle was found to plug with char however, and was subsequently removed from the system. Final operation of the reactor continues satisfactorily with the two screw conveyors operating at matching pressure with the fluidized bed, with the output rate of the system estimated based on system characteristic equations, and confirmed by static weight measurements made before and after testing. The error rate by this method is reported to be approximately 10%, which is slightly better than the estimated error rate of 15% for the conveyor system. The reliability of this measurement prediction method relies upon the relative consistency of the physical properties of MBM with respect to its bulk density and feeding characteristics.     

Sex-specific patterns of lifetime reproductive success in single and repeat breeding steelhead trout (Oncorhynchus mykiss)

All other things being equal, the lifetime reproductive success (LRS) of iteroparous and semelparous individuals should scale with the number of breeding seasons. Deviations from this relationship may occur for many reasons, including age- or size-related fecundity or life history trade-offs, which may differ between sexes. We used 19 brood years of DNA parentage analysis in a small (N = 4–143 year⁻¹) wild, unexploited population of steelhead trout (Oncorhynchus mykiss) to compare the LRS of individuals that spawned only once [“one time spawners” (OTS), N = 355 male, 371 female] to those spawning twice [“repeat spawners” (RPS), N = 13 male, 49 female]. Female RPS had nearly twice the LRS of female OTS (1.17 offspring per female vs 0.91 offspring per female), whereas male RPS had nearly three times the LRS of male OTS (1.54 offspring per male vs 0.57 offspring per male). Female RPS produced slightly more adult offspring during their second breeding season than their first (0.78 vs 0.82 offspring per female); however, male RPS produced all of their adult offspring in their second breeding season (0 vs 1.54 offspring per male). The additional growth in body size of males between breeding seasons may give them an advantage in their second breeding season, but the lack of offspring produced in their first season suggests a trade-off between survival and future reproduction that was not expressed in females.     

Estimating landscape-scale species richness: reconciling frequency- and turnover-based approaches

One hypothesis for why estimators of species richness tend to underestimate total richness is that they do not explicitly account for increases in species richness due to spatial or environmental turnover in species composition (beta diversity). I analyze the similarity of a data set of native trees in Great Smoky Mountains National Park, USA, and assess the robustness of these estimators against recently developed ones that incorporate turnover explicitly: the total species accumulation method (T-S) and a method based on the distance decay of similarity. I show that the T-S estimator can give reliable estimates of species richness, given an appropriate grouping of sites. The estimator based on distance decay of similarity performed poorly. There are two main reasons for this: sample size effects and the assumption that distance decay of similarity exhibits a power law relationship. I show that estimators based on distance-decay relationships exhibit systematically lower rates of distance decay for samples with few individuals per site independent of environmental variation. Second, the data presented here and many other survey data sets exhibit exponential rather than power law distance-decay relationships. Richness estimators that explicitly incorporate beta diversity can be improved by beginning from an exponential distance-decay relationship and adjusting for the systematic errors introduced by small sample sizes.     

The development and application of a multilevel decision analysis model for the remediation of contaminated groundwater under uncertainty

A study was initiated which combined elements of stochastic hydrology, risk assessment, simulation modeling, cost analysis and decision making to define the optimum remediation choice(s) for a Superfund site in the southern United States. The effort focused upon the premise that groundwater remediation is inherently complex due to uncertainties in the geological matrix as well as in contaminant concentrations at points of compliance and/or exposure. The technical analyst should supply the decision maker with estimates of these uncertainties as well as the cost penalties required to reduce them to manageable levels. Monte Carlo transport modeling was employed to define the probability of contaminant excursions from the site, while geostatistical simulation identified a joint plume configuration and its attendant probability. Bayesian modeling was used to define the worth of additional data. These individual components were combined within a Decision Model to identify optimum remediation configurations for a given levels of risk tolerance which could be supplied by the decision maker or affected community. Sensitivity analyses were conducted to define ranges over which the decision would not be affected by variation in the respective decision parameter.