Phytoplankton are key players in the global carbon cycle, contributing about half of global primary productivity. Within the phytoplankton, functional groups (characterized by distinct traits) have impacts on other major biogeochemical cycles, such as nitrogen, phosphorus and silica. Changes in phytoplankton community structure, resulting from the unique environmental sensitivities of these groups, may significantly alter elemental cycling from local to global scales. We review key traits that distinguish major phytoplankton functional groups, how they affect biogeochemistry and how the links between community structure and biogeochemical cycles are modelled. Finally, we explore how global environmental change will affect phytoplankton communities, from the traits of individual species to the relative abundance of functional groups, and how that, in turn, may alter biogeochemical cycles.Synthesis. We can increase our mechanistic understanding of the links between the community structure of primary producers and biogeochemistry by focusing on traits determining functional group responses to the environment (response traits) and their biogeochemical functions (effect traits). Identifying trade-offs including allometric and phylogenetic constraints among traits will help parameterize predictive biogeochemical models, enhancing our ability to anticipate the consequences of global change.

Rising temperatures are expected to favour the growth of bloom-forming cyanobacteria in temperate lakes, but may also change the composition of cyanobacterial communities. To predict future community and bloom dynamics, it is therefore important to understand how bloom-forming species respond to temperature. Cylindrospermopsis raciborskii (Woloszynska) Seenayya & Subba Raju is an invasive, toxin-producing, nitrogen-fixer that may benefit from warming. To understand how changing temperatures will influence its ability to compete against native North American bloom-formers, we characterized the thermal reaction norms and temperature traits of three C. raciborskii strains, four strains of Microcystis aeruginosa (Kutzing) Kutzing and one strain of Anabaena flos-aquae (Lyng.) Breb. C. raciborskii strains had higher optimum temperatures and survived higher temperatures than toxic M. aeruginosa strains, but had no apparent advantage over the non-toxic M. aeruginosa strain or A. flosaquae. M. aeruginosa strains and A. flos-aquae tolerated lower temperatures than C. raciborskii, suggesting that fitness differences at low temperature may be important in limiting the latter's spread. Furthermore, we found that nutrient availability strongly influenced thermal reaction norm shape: nitrogen deprivation lowered growth rates and decreased both low-and high-temperature tolerance, but did not affect the optimum temperature in C. raciborskii.

Aim Ecological and evolutionary forces shape the functional traits of species within and across environments, generating biogeographical patterns in traits. We aimed to: (1) determine the extent to which temperature traits of phytoplankton are adapted to their local environment, and (2) detect and explain differences in patterns of adaptation between functional groups (reflecting evolutionary history) and across ecosystems (freshwater versus marine).

Gliding robotic fish, a hybrid of underwater gliders and robotic fish, are energy-efficient and highly maneuverable, and hold strong promise for long-duration sampling of underwater environments. In this paper a novel systematic autonomous water-column-based sampling scheme for gliding robotic fish is proposed to measure the three-dimensional spatial distributions of variables of interest in aquatic environments. The scheme exploits energy-efficient spiral-down motion to sample each water column, followed by sagittal-plane glide-up towards the direction of next water column. Once surfacing, the robot uses GPS guidance to reach the next column location through swimming. To enhance the path tracking performance, a two-degree-of-freedom controller involving H-infinity control is used in the spiral motion, and a sliding-mode controller is employed to regulate the yaw angle during glide-up. The sampling scheme has been implemented on a gliding robotic fish prototype, "Grace", and verified first in pool experiments, and then in field experiments involving the sampling of harmful algae concentration in the Wintergreen Lake, Michigan.

It takes a village to finish (marine) science these daysParaphrased from Curtis Huttenhower (the Human Microbiome project)The rapidity and complexity of climate change and its potential effects on ocean biota are challenging how ocean scientists conduct research. One way in which we can begin to better tackle these challenges is to conduct community-wide scientific studies. This study provides physiological datasets fundamental to understanding functional responses of phytoplankton growth rates to temperature. While physiological experiments are not new, our experiments were conducted in many laboratories using agreed upon protocols and 25 strains of eukaryotic and prokaryotic phytoplankton isolated across a wide range of marine environments from polar to tropical, and from nearshore waters to the open ocean. This community-wide approach provides both comprehensive and internally consistent datasets produced over considerably shorter time scales than conventional individual and often uncoordinated lab efforts. Such datasets can be used to parameterise global ocean model projections of environmental change and to provide initial insights into the magnitude of regional biogeographic change in ocean biota in the coming decades. Here, we compare our datasets with a compilation of literature data on phytoplankton growth responses to temperature. A comparison with prior published data suggests that the optimal temperatures of individual species and, to a lesser degree, thermal niches were similar across studies. However, a comparison of the maximum growth rate across studies revealed significant departures between this and previously collected datasets, which may be due to differences in the cultured isolates, temporal changes in the clonal isolates in cultures, and/or differences in culture conditions. Such methodological differences mean that using particular trait measurements from the prior literature might introduce unknown errors and bias into modelling projections. Using our community-wide approach we can reduce such protocol-driven variability in culture studies, and can begin to address more complex issues such as the effect of multiple environmental drivers on ocean biota.