Macrozoobenthos diversity in an oxygen minimum zone off northern Namibia

A benthological survey in the Benguela upwelling area off northern Namibia (located at 17.3°S and water depth ranging between 26 and 117 m) showed the concentration of dissolved oxygen and the accumulation of organic-rich sediments to control macrozoobenthic community patterns. In contrast to highly biodiverse nearshore areas with well-structured shell deposits of the brachiopod Discinisca tenuis (Sowerby 1847), the benthic community in the oxygen minimum zone (OMZ) decreased strongly in species numbers. Nevertheless, a well-established community ranging from 13 to 31 species persisted. Species densities (300–3,350 ind m⁻²) and biomass (4–109 g afdw/m²) were surprisingly high for areas with near bottom oxygen concentrations from 0.06 to 0.88 ml l⁻¹. In contrast to OMZ’s of other upwelling areas, where the benthic macrofauna is generally dominated by small-bodied polychaetes, off Namibia larger key organisms like the bivalve Nuculana bicuspidata (Gould 1845) and the snail Nassarius vinctus (Marrett 1877) accounted for a large proportion of the macrozoobenthos >1 mm. This is supposed to have a distinct effect on the functional properties of the sediments.

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Testing homogeneity of capture probabilities of animals in a removal experiment

Consider the removal experiment used to estimate population sizes. Statistical methods towards testing the homogeneity of capture probabilities of animals, including a graphical diagnostic and a formal test, are presented and illustrated by real biological examples. Simulation is used to assess the test and compare it with the χ² test.

The swimming crab Charybdis smithii: distribution, biology and trophic role in the pelagic ecosystem of the western Indian Ocean

Surface “swarms” of the swimming crabs Charybdis smithii are still considered as an unusual phenomenon in the open Indian Ocean, although their dense pelagic aggregations were already reported in waters off the Indian coast and in the northern Arabian Sea. Based on an extensive large-scale data series taken over 45 years, we demonstrate that C. smithii is common in the pelagic provinces of the western Indian Ocean driven by the wind monsoon regime. Swimming crabs are dispersed by the monsoon currents throughout the equatorial Indian Ocean. They aggregate at night in the upper 150-m layer, where their estimated biomass derived from pelagic trawling data can exceed 130 kg km⁻². Abundance of C. smithii can reach >15,000 ind. km⁻² in July (i.e. the peak of the south-west monsoon), declines by 50-fold in March and is negligible in May. C. smithii is an important prey for more than 30 species of abundant epipelagic top predators. In turn, it feeds on mesopelagic species. This swimming crab is a major species of the intermediate trophic levels and represents a crucial seasonal trophic link in the open ocean ecosystem of the western Indian Ocean. Outbursts in pelagic waters of huge biomasses of ordinarily benthic crustaceans (C. smithii and Natosquilla investigatoris) are a remarkable feature of the Indian Ocean, although similar, but smaller, events are reported in the Pacific and Atlantic Oceans.

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Development of the nasal olfactory organs in the larvae, settlement-stages and some adults of 14 species of Caribbean reef fishes (Labridae, Scaridae, Pomacentridae)

Larval fishes likely use a variety of settlement cues to locate and navigate toward the habitats they will inhabit as juveniles. Information about the morphology and state of development of the sensory organs of larval stages of fishes provides insight into their capabilities at the time of settlement. The peripheral olfactory organ of wild-caught late-stage larvae and early juveniles and some adults of 14 species of the Caribbean reef fishes wrasses (Labridae), parrot fishes (Scaridae) and damselfish (Pomacentridae) were examined using scanning electron microscopy and compared in terms of settlement specificity. Ages in days after hatching and days post-settlement were determined from the otoliths. Morphology of the nares and the olfactory epithelium are described for these species by stage. The separation of the anterior and posterior nares occurred before settlement in the labrids but in some specimens of scarids this separation was not complete by the time of settlement. Densities of ciliated and microvillous receptor cells and non-sensory ciliated epithelial cells were calculated. Densities of ciliated receptor cells ranged from 0.389 μm⁻² in a specimen of Thallasoma bifasciatum to 0.0057 μm⁻² in Bodianus rufus and of microvillous receptor cells from 0.038 μm⁻² in a Clepticus parrae juvenile to 0.266 μm⁻² in a juvenile Doratonotus megalepis. Densities of non-sensory cilia, also associated with high olfactory ability, were also high. The olfactory organ in wrasses is well developed prior to settlement and is comparable to that of adult fishes. The possible role of olfaction in larval schooling, reef cue detection and orientation toward habitat at settlement is discussed.

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Behavior of yellowfin (<Emphasis Type="Italic">Thunnus albacares</Emphasis>) and bigeye (<Emphasis Type="Italic">T. obesus</Emphasis>) tuna in a network of fish aggregating devices (FADs)

The influence of multiple anchored fish aggregating devices (FADs) on the spatial behavior of yellowfin (Thunnus albacares) and bigeye tuna (T. obesus) was investigated by equipping all thirteen FADs surrounding the island of Oahu (HI, USA) with automated sonic receivers (“listening stations”) and intra-peritoneally implanting individually coded acoustic transmitters in 45 yellowfin and 12 bigeye tuna. Thus, the FAD network became a multi-element passive observatory of the residence and movement characteristics of tuna within the array. Yellowfin tuna were detected within the FAD array for up to 150 days, while bigeye tuna were only observed up to a maximum of 10 days after tagging. Only eight yellowfin tuna (out of 45) and one bigeye tuna (out of 12) visited FADs other than their FAD of release. Those nine fish tended to visit nearest neighboring FADs and, in general, spent more time at their FAD of release than at the others. Fish visiting the same FAD several times or visiting other FADs tended to stay longer in the FAD network. A majority of tagged fish exhibited some synchronicity when departing the FADs but not all tagged fish departed a FAD at the same time: small groups of tagged fish left together while others remained. We hypothesize that tuna (at an individual or collective level) consider local conditions around any given FAD to be representative of the environment on a larger scale (e.g., the entire island) and when those conditions become unfavorable the tuna move to a completely different area. Thus, while the anchored FADs surrounding the island of Oahu might concentrate fish and make them more vulnerable to fishing, at a meso-scale they might not entrain fish longer than if there were no (or very few) FADs in the area. At the existing FAD density, the ‘island effect’ is more likely to be responsible for the general presence of fish around the island than the FADs. We recommend further investigation of this hypothesis.

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Distribution and abundance of penaeid shrimps in a hypersaline lagoon in northwestern Mexico,emphasizing the brown shrimp <Emphasis Type="Italic">Farfantepenaeus californiensis</Emphasis> life cycle

Life histories of penaeid shrimp have been classified according to the preferred habitats of postlarval, juvenile, and adult stages, ranging from exclusively estuarine to exclusively offshore waters. Brown shrimp Farfantepenaeus californiensis migrate to an offshore habitat at the juvenile stage or even a smaller body size. This paper presents results of monthly samplings from 24 stations over 1 year in the Agiabampo Lagoon complex, a hypersaline lagoon in northwestern Mexico. Five species of penaeid shrimp were identified, with brown shrimp the most abundant during the year of sampling. Results suggest that residency of brown shrimp inside this lagoon is longer than reported in previous studies. An interaction between length and environmental variables (near-surface temperature, salinity, and rainfall) appear to be cues concerning migration.

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A note on data augmentation and iterative simulation for survival rate estimation

In this paper we examine the use of data augmentation techniques for simplifying iterative simulation in the context of both Bayesian and classical statistical inference for survival rate estimation. We examine two distinct model families common in population ecology to illustrate our ideas, ring-recovery models and capture–recapture models, and we present the computational advantage of this approach. We discuss also the fact that problems associated with identifiability in the classical framework can be overcome using data augmentation, but highlight the dangers in doing so under both inferential paradigms.

Vertical distribution of macroplankton at the Charlie-Gibbs Fracture Zone (North Atlantic), as observed from the manned submersible “Mir-1”

Direct observations of the plankton vertical distribution performed from a manned submersible were made in the Charlie-Gibbs Fracture Zone (Atlantic Ocean). Plankton was counted using a standard 3-m² frame in the depth layer from 170 to 4361 m and plotted for every 50 m. The most abundant components of the macroplankton were pelagic shrimps, chaetognaths and gelatinous animals, with peak of densities corresponding to the main pycnocline. Mucous houses of appendicularians were abundant at 150 m above the seabed—up to 0.07–0.09 m^–3, compared to 0–0.006 m^–3 in the upper layers. The new observations confirm that the near-bottom peak of appendicularian abundance is characteristic of at least the entire Central Atlantic, and it is not associated with certain biotopes on the bottom.Communicated by O. Kinne, Oldendorf/Luhe

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Trap mortality in mark-recapture studies

When animals die in traps in a mark-recapture study, straightforward likelihood inferences are possible in a class of models. The class includes M₀, M_t, and M_b as reported by White et al. (Los Alamos National Laboratory, LA-8787-NERP, pp 235, 1982), those that do not involve heterogeneity. We include three Markov chain “persistence” models and show that they provide good fits in a trapping study of deer mice in the Cascade-Siskiyou National Monument of Southern Oregon where trapping mortality was high.

Replace the NOAEL and LOAEL with the BMDL01 and BMDL10

Although benchmark-dose methodology has existed for more than 20 years, benchmark doses (BMDs) still have not fully supplanted the no-observed-adverse-effect level (NOAEL) and lowest-observed-adverse-effect level (LOAEL) as points of departure from the experimental dose–response range for setting acceptable exposure levels of toxic substances. Among the issues involved in replacing the NOAEL (LOAEL) with a BMD are (1) which added risk level(s) above background risk should be targeted as benchmark responses (BMRs), (2) whether to apply the BMD methodology to both carcinogenic and noncarcinogenic toxic effects, and (3) how to model continuous health effects that aren’t observed in a natural risk-based context like dichotomous health effects. This paper addresses these issues and recommends specific BMDs to replace the NOAEL and LOAEL.

Flexible hierarchical mark-recapture modeling for open populations using WinBUGS

Hierarchical mark-recapture models offer three advantages over classical mark-recapture models: (i) they allow expression of complicated models in terms of simple components; (ii) they provide a convenient way of modeling missing data and latent variables in a way that allows expression of relationships involving latent variables in the model; (iii) they provide a convenient way of introducing parsimony into models involving many nuisance parameters. Expressing models using the complete data likelihood we show how many of the standard mark-recapture models for open populations can be readily fitted using the software WinBUGS. We include examples that illustrate fitting the Cormack–Jolly–Seber model, multi-state and multi-event models, models including auxiliary data, and models including density dependence.

Bootstrap methods for simultaneous benchmark analysis with quantal response data

A primary objective in quantitative risk assessment is the characterization of risk which is defined to be the likelihood of an adverse effect caused by an environmental toxin or chemcial agent. In modern risk-benchmark analysis, attention centers on the “benchmark dose” at which a fixed benchmark level of risk is achieved, with a lower confidence limits on this dose being of primary interest. In practice, a range of benchmark risks may be under study, so that the individual lower confidence limits on benchmark dose must be corrected for simultaneity in order to maintain a specified overall level of confidence. For the case of quantal data, simultaneous methods have been constructed that appeal to the large sample normality of parameter estimates. The suitability of these methods for use with small sample sizes will be considered. A new bootstrap technique is proposed as an alternative to the large sample methodology. This technique is evaluated via a simulation study and examples from environmental toxicology.

Comparing model averaging with other model selection strategies for benchmark dose estimation

Model averaging (MA) has been proposed as a method of accommodating model uncertainty when estimating risk. Although the use of MA is inherently appealing, little is known about its performance using general modeling conditions. We investigate the use of MA for estimating excess risk using a Monte Carlo simulation. Dichotomous response data are simulated under various assumed underlying dose–response curves, and nine dose–response models (from the USEPA Benchmark dose model suite) are fit to obtain both model specific and MA risk estimates. The benchmark dose estimates (BMDs) from the MA method, as well as estimates from other commonly selected models, e.g., best fitting model or the model resulting in the smallest BMD, are compared to the true benchmark dose value to better understand both bias and coverage behavior in the estimation procedure. The MA method has a small bias when estimating the BMD that is similar to the bias of BMD estimates derived from the assumed model. Further, when a broader range of models are included in the family of models considered in the MA process, the lower bound estimate provided coverage close to the nominal level, which is superior to the other strategies considered. This approach provides an alternative method for risk managers to estimate risk while incorporating model uncertainty.

Social network analysis and valid Markov chain Monte Carlo tests of null models

Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.

Determining the optimum number of increments in composite sampling

Composite sampling can be more cost effective than simple random sampling. This paper considers how to determine the optimum number of increments to use in composite sampling. Composite sampling terminology and theory are outlined and a method is developed which accounts for different sources of variation in compositing and data analysis. This method is used to define and understand the process of determining the optimum number of increments that should be used in forming a composite. The blending variance is shown to have a smaller range of possible values than previously reported when estimating the number of increments in a composite sample. Accounting for differing levels of the blending variance significantly affects the estimated number of increments.

Sustainable coastal communities in the age of coastal storms: Reconceptualising coastal planning as ‘new’ naval architecture

Hurricanes devastated the Gulf coast of the USA in 2005. Hurricane Katrina, in particular, highlighted the compelling need to build more sustainable and hazard-resilient communities. Much can be learned from recovery efforts to rebuild the Gulf coast. Personal observations and interviews with planners, academics and others involved in recovery efforts inform this analysis, which focuses on New Orleans. A conceptual framework is developed and principles and operational imperatives outlined to guide action for building sustainable, hazard-resilient communities. Such communities will remain elusive unless ‘business as usual’ is confronted by a transformational process of developmental planning. Sustainable, hazard-resilient coastal communities are founded upon robust ‘critical infrastructure’ that is secured by planning and decision-making processes that enable coastal communities to build ‘layers of resilience’ to overcome ‘waves of adversity’. Planners need to take on a redefined role—as ‘new naval architects’—to design and build communities that are ‘sea-worthy’ in this age of coastal storms.

Fiat boundaries: some implications for interpretation,decision-support,and multi-temporal analysis

Polygon-based thematic maps can be composed of boundaries that exist by definition—i.e., bona fide boundaries—or those that exist relative to a specific interpretation of a spatial phenomenon—i.e., fiat boundaries. The construction of maps composed of fiat boundaries is usually based on a subjective interpretive methodology that is affected by the data used to construct the map and the minimum mapping unit employed. That fiat boundaries are not the same as bona fide boundaries affects their use in computer-based spatial decision support tools. This is discussed both in terms of an analysis conducted at one specific moment, and in respect to increasingly common multi-temporal analysis.

Reproductive biology of the tiger shark (Galeocerdo cuvier) in Hawaii

The tiger shark (Galeocerdo cuvier) is the largest shark in the family Carcharhinidae and the only carcharhinid with aplacental viviparous (ovoviviparous) reproduction. Despite its size and prevalence, many details of tiger shark reproductive biology are unknown. Size at maturity and litter size have been reported by several authors, but a lack of large numbers of pregnant females has made it difficult to determine gestation period, seasonality, and timing of the female reproductive cycle. Here we analyze data from shark control program fishing and incidental catches in Hawaii (n = 318) to construct the most complete picture of tiger shark reproduction to date. Males reached maturity at approximately 292 cm total length (TL) based on clasper calcification, whereas females matured between 330 and 345 cm TL based on oviducal gland and uterus widths. Litter sizes ranged from 3 to 57 with a mean of 32.6 embryos per litter. Data from 23 litters from various months of the year indicate that tiger sharks are usually 80–90 cm TL at birth, and that the gestation period is 15–16 months. Mating scars were observed in January–February and sperm is presumably stored for 4–5 months until ovulation takes place in May–July. Gestation begins in June–July and pups are born in September–October of the following year. Our data suggest that female tiger sharks in Hawaii give birth only once every three years. This could have major implications for conservation and management of this species, as it suggests that tiger shark fecundity is 33% lower than previously thought. This could greatly reduce the ability of this species to rebound from fishing pressure.

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Hierarchical modeling for extreme values observed over space and time

We propose a hierarchical modeling approach for explaining a collection of spatially referenced time series of extreme values. We assume that the observations follow generalized extreme value (GEV) distributions whose locations and scales are jointly spatially dependent where the dependence is captured using multivariate Markov random field models specified through coregionalization. In addition, there is temporal dependence in the locations. There are various ways to provide appropriate specifications; we consider four choices. The models can be fitted using a Markov Chain Monte Carlo (MCMC) algorithm to enable inference for parameters and to provide spatio–temporal predictions. We fit the models to a set of gridded interpolated precipitation data collected over a 50-year period for the Cape Floristic Region in South Africa, summarizing results for what appears to be the best choice of model.