From their origin as an early alpha proteobacterial endosymbiont to their current state as cellular organelles, large-scale genomic reorganization has taken place in the mitochondria of all main eukaryotic lineages. So far, most studies have focused on plant and animal mitochondrial (mt) genomes (mtDNA), but fungi provide new opportunities to study highly differentiated mtDNAs. Here, we analyzed 38 complete fungal mt genomes to investigate the evolution of mtDNA gene order among fungi. In particular, we looked for evidence of nonhomologous intrachromosomal recombination and investigated the dynamics of gene rearrangements. We investigated the effect that introns, intronic open reading frames (ORFs), and repeats may have on gene order. Additionally, we asked whether the distribution of transfer RNAs (tRNAs) evolves independently to that of mt protein-coding genes. We found that fungal mt genomes display remarkable variation between and within the major fungal phyla in terms of gene order, genome size, composition of intergenic regions, and presence of repeats, introns, and associated ORFs. Our results support previous evidence for the presence of mt recombination in all fungal phyla, a process conspicuously lacking in most Metazoa. Overall, the patterns of rearrangements may be explained by the combined influences of recombination (i.e., most likely nonhomologous and intrachromosomal), accumulated repeats, especially at intergenic regions, and to a lesser extent, mobile element dynamics.

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We present a simple recipe to design a physically realistic and robust Lagrangian particle tracking model, paying particular attention to the pitfalls that are associated with the particle tracking if the turbulent mixing is taken as spatially nonuniform. These pitfalls are often neglected or ignored in Lagrangian biophysical particle tracking models and, using simple examples, it is shown how this may lead to physically and hence biologically unrealistic results. Issues associated with the direct particle tracking process are discussed. The choice of a suitable random walk model, in conjunction with an adequate random number generator, is discussed. Two methods are described to correctly implement the reflecting boundary condition in the random walk model, to avoid artificial accumulations at the boundaries. We also examine the more general question of whether the particle diffusivity can be assumed to equal the fluid diffusivity and briefly address the post-simulation treatment of the data.

The foraging habitats of 7 species of marine apex predators were observed simultaneously in a shallow sea, with continuous measurements taken of the detailed bio-physical water column characteristics to determine habitat preferences. We found the occurrence of small-scale 'hotspots', where 50% of all animals were actively foraging in less than 5% of the 1000 km of transects surveyed. By investigating a contrasting range of foraging strategies across a variety of fisheating seabirds and marine mammals, we determined which habitat characteristics were consistently important across species. A static habitat variable, tidal stratification, log 10 (h/U 3 ) (h = water depth, U = tidal current amplitude), was found to be the best indicator of the probability of presence and abundance of individual species. All 7 mobile top-predators preferentially foraged within habitats with small-scale (2 to 10 km) patches having (1) high concentrations of chlorophyll in the sub-surface chlorophyll maximum (CHL max ) and (2) high variance in bottom topography, with different species preferring to forage in different locations within these habitats. Patchiness of CHL max was not associated with the locations of strong horizontal temperature gradients (fronts) or high surface chlorophyll values, but instead may be related to areas of high sub-surface primary production due to locally increased vertical mixing. These small-scale areas represent a newly identified class of spatially important location that may play a critical role within the trophic coupling of shallow seas. Such subsurface hotspots may represent the limited locations where the majority of predator-prey interactions occur, despite making up only a small percentage of the marine environment.KEY WORDS: Biological hotspots · Foraging habitats · Marine top predators · Predator-prey interactions · Shallow sea · Sub-surface chlorophyll maximum · Tidal mixing · Topography 408: 207-226, 2010 Review studies on the upwelling systems of the Pacific Ocean identified spatially and temporally predictable 'biological hotspots' with distinct surface signatures (Spear et al. 2001, Bakun 2006, Ballance et al. 2006, Sydeman et al. 2006. At this large scale, the mechanistic evidence behind the creation of hotspots for marine predator foraging points directly to both topographical features (Genin 2004, Yen et al. 2004 and primary productivity (Ware & Thomson 2005, Bost et al. 2009). The general conclusion of many largescale studies is that seabirds and marine mammals are found preferentially foraging within different types of frontal region: areas of intersection between different water mass types where there are steep surface (horizontal) gradients in water density. Biological reasoning links foraging to frontal locations via the elevated levels of primary production and aggregation of planktonic organisms found at fronts (Pingree et al. 1975, Franks & Chen 1996, Durazo et al. 1998, Russell et al. 1999, Lough and Manning 2001. However, some of the studies mentioned above stress...

In this study, we present a new model of acclimation to light under nutrient-replete conditions based on the photo-acclimation model by Geider et al. (1998; Limnol Oceanogr 43:679-694). Rather than being solely carbon (C)-based, the new model employs the cell as the basic unit, which makes it more amenable for application in individual-based (Lagrangian) modelling approaches. The model differentiates between a functional C pool which also contains nitrogen (N) and an energy reserve pool which does not contain N. The cell-specific light-saturated photosynthetic rate is assumed to scale with the size of the functional pool, and the light-limited photosynthetic rate with the cellular chlorophyll content. Through the explicit inclusion of a C (energy) storage pool, an improved regulatory term for chlorophyll synthesis, and the addition of an optional acceleratory term, the dynamics of the model in comparison to the original model could be improved. This is demonstrated by observations during a light-shift experiment on the diatom Skeletonema costatum.