Modelling the dynamics of phytoplankton with the needs of the end user in mind

How to regulate phytoplankton growth in water supply reservoirs has continued to occupy managers and strategists for some fifty years or so, now, and mathematical models have always featured in their design and operational constraints. In recent years, rather more sophisticated simulation models have begun to be available and these, ideally, purport to provide the manager with improved forecasting of plankton blooms, the likely species and the sort of decision support that might permit management choices to be selected with increased confidence. This account describes the adaptation and application of one such model, PROTECH (Phytoplankton RespOnses To Environmental CHange) to the problems of plankton growth in reservoirs. This article supposes no background knowledge of the main algal types; neither does it attempt to catalogue the problems that their abundance may cause in lakes and reservoirs.

Abundance of harbor porpoise (Phocoena phocoena) in three Alaskan regions, corrected for observer errors due to perception bias and species misidentification, and corrected for animals submerged from view

Estimating the abundance of cetaceans from aerial survey data requires careful attention to survey design and analysis. Once an aerial observer perceives a marine mammal or group of marine mammals, he or she has only a few seconds to identify and enumerate the individuals sighted, as well as to determine the distance to the sighting and record this information. In line-transect survey analyses, it is assumed that the observer has correctly identified and enumerated the group or individual. We describe methods used to test this assumption and how survey data should be adjusted to account for observer errors. Harbor porpoises (Phocoena phocoena) were censused during aerial surveys in the summer of 1997 in Southeast Alaska (9844 km survey effort), in the summer of 1998 in the Gulf of Alaska (10,127 km), and in the summer of 1999 in the Bering Sea (7849 km). Sightings of harbor porpoise during a beluga whale (Phocoena phocoena) survey in 1998 (1355 km) provided data on harbor porpoise abundance in Cook Inlet for the Gulf of Alaska stock. Sightings by primary observers at side windows were compared to an independent observer at a belly window to estimate the probability of misidentification, underestimation of group size, and the probability that porpoise on the surface at the trackline were missed (perception bias, g(0)). There were 129, 96, and 201 sightings of harbor porpoises in the three stock areas, respectively. Both g(0) and effective strip width (the realized width of the survey track) depended on survey year, and g(0) also depended on the visibility reported by observers. Harbor porpoise abundance in 1997–99 was estimated at 11,146 animals for the Southeast Alaska stock, 31,046 animals for the Gulf of Alaska stock, and 48,515 animals for the Bering Sea stock.

No evidence of bias from fish behavior in the selectivity of size and sex of the protogynous red porgy (Pagrus pagrus, Sparidae) by hook-and-line gear

Most fisheries select the size of fish to be caught (are size selective), and many factors, including gear, market demands, species distributions, fishery laws, and the behavior of both fishermen and fish, can contribute to that selectivity. Most fishing gear is size-selective and some, such as gill nets, are more so than others. The targeting behavior of fishermen is another key reason commercial and recreational fisheries tend to be size-selective. The more successful fishermen constantly seek areas and methods that yield larger or more profitable sizes of fish. Fishery regulations, especially size limits, produce size-selective harvests. Another factor with the potential to cause selectivity in a hook-and-line fishery is the different behavioral responses of fish to the bait or lure, whether the different responses arise among different fish sizes or between the sexes.

Saline-saturated DMSO-EDTA as a storage medium for microbial DNA analysis from coral mucus swab samples

The mucus surface layer of corals plays a number of integral roles in their overall health and fitness. This mucopolysaccharide coating serves as vehicle to capture food, a protective barrier against physical invasions and trauma, and serves as a medium to host a community of microorganisms distinct from the surrounding seawater. In healthy corals the associated microbial communities are known to provide antibiotics that contribute to the coral’s innate immunity and function metabolic activities such as biogeochemical cycling. Culture-dependent (Ducklow and Mitchell, 1979; Ritchie, 2006) and culture-independent methods (Rohwer, et al., 2001; Rohwer et al., 2002; Sekar et al., 2006; Hansson et al., 2009; Kellogg et al., 2009) have shown that coral mucus-associated microbial communities can change with changes in the environment and health condition of the coral. These changes may suggest that changes in the microbial associates not only reflect health status but also may assist corals in acclimating to changing environmental conditions. With the increasing availability of molecular biology tools, culture-independent methods are being used more frequently for evaluating the health of the animal host. Although culture-independent methods are able to provide more in-depth insights into the constituents of the coral surface mucus layer’s microbial community, their reliability and reproducibility rely on the initial sample collection maintaining sample integrity. In general, a sample of mucus is collected from a coral colony, either by sterile syringe or swab method (Woodley, et al., 2008), and immediately placed in a cryovial. In the case of a syringe sample, the mucus is decanted into the cryovial and the sealed tube is immediately flash-frozen in a liquid nitrogen vapor shipper (a.k.a., dry shipper). Swabs with mucus are placed in a cryovial, and the end of the swab is broken off before sealing and placing the vial in the dry shipper. The samples are then sent to a laboratory for analysis. After the initial collection and preservation of the sample, the duration of the sample voyage to a recipient laboratory is often another critical part of the sampling process, as unanticipated delays may exceed the length of time a dry shipper can remain cold, or mishandling of the shipper can cause it to exhaust prematurely. In remote areas, service by international shipping companies may be non-existent, which requires the use of an alternative preservation medium. Other methods for preserving environmental samples for microbial DNA analysis include drying on various matrices (DNA cards, swabs), or placing samples in liquid preservatives (e.g., chloroform/phenol/isoamyl alcohol, TRIzol reagent, ethanol). These methodologies eliminate the need for cold storage, however, they add expense and permitting requirements for hazardous liquid components, and the retrieval of intact microbial DNA often can be inconsistent (Dawson, et al., 1998; Rissanen et al., 2010). A method to preserve coral mucus samples without cold storage or use of hazardous solvents, while maintaining microbial DNA integrity, would be an invaluable tool for coral biologists, especially those in remote areas. Saline-saturated dimethylsulfoxide-ethylenediaminetetraacetic acid (20% DMSO-0.25M EDTA, pH 8.0), or SSDE, is a solution that has been reported to be a means of storing tissue of marine invertebrates at ambient temperatures without significant loss of nucleic acid integrity (Dawson et al., 1998, Concepcion et al., 2007). While this methodology would be a facile and inexpensive way to transport coral tissue samples, it is unclear whether the coral microbiota DNA would be adversely affected by this storage medium either by degradation of the DNA, or a bias in the DNA recovered during the extraction process created by variations in extraction efficiencies among the various community members. Tests to determine the efficacy of SSDE as an ambient temperature storage medium for coral mucus samples are presented here.

Demersal groundfish densities in trawlable and untrawlable habitats off Washington: implications for the estimation of habitat bias in trawl surveys

Demersal groundfish densities were estimated by conducting a visual strip-transect survey via manned submersible on the continental shelf off Cape Flattery, Washington. The purpose of this study was to evaluate the statistical sampling power of the submersible survey as a tool to discriminate density differences between trawlable and untrawlable habitats. A geophysical map of the study area was prepared with side-scan sonar imagery, multibeam bathymetry data, and known locations of historical NMFS trawl survey events. Submersible transects were completed at randomly selected dive sites located in each habitat type. Significant differences in density between habitats were observed for lingcod (Ophiodon elongatus), yelloweye rockfish (Sebastes ruberrimus), and tiger rockfish (S. nigrocinctus) individually, and for “all rockfish” and “all flatfish” in the aggregate. Flatfish were more than ten times as abundant in the trawlable habitat samples than in the untrawlable samples, whereas rockfish as a group were over three times as abundant in the untrawlable habitat samples. Guidelines for sample sizes and implications for the estimation of the continental shelf trawl-survey habitat-bias are considered. We demonstrate an approach that can be used to establish sample size guidelines for future work by illustrating the interplay between statistical sampling power and 1) habitat specific-density differences, 2) variance of density differences, and 3) the proportion of untrawlable area in a habitat.