Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity ecosystern functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common pattems and differences in biodiversity functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.

Gliding robotic fish, which is a hybrid of underwater gliders and robotic fish, is energy efficient and highly maneuverable and holds strong promise for long-duration monitoring of underwater environments. In this paper, a novel scheme is proposed for autonomously sampling multiple water columns using gliding robotic fish. The scheme exploits energy-efficient spiral-down motion to sample each water column, followed by sagittal-plane glide-up toward the direction of the next water column. Once surfacing, the robot uses Global Positioning System 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.

Marine phytoplankton are a taxonomically and functionally diverse group of organisms that are key players in the most important biogeochemical cycles. Phytoplankton taxa show different resource utilization strategies (e.g. nutrient-uptake rates and cellular allocation) and traits. Therefore, acknowledging this diversity is crucial to understanding how elemental cycles operate, including the origin and dynamics of elemental ratios. In this paper, we focus on trait-based models as tools to study the role of phytoplankton diversity in the stoichiometric phenomenology observed in the laboratory and in the open ocean. We offer a compilation of known empirical results on stoichiometry and summarize how trait-based approaches have attempted to replicate these results. By contrasting the different ecological and evolutionary approaches available in the literature, we explore the strengths and limitations of the existing models. We thus try to identify existing gaps and challenges, and point to potential new directions that can be explored to fill these gaps. We aim to highlight the potential of including diversity explicitly in our modeling approaches, which can help us gain important knowledge about changes in local and global stoichiometric patterns.

The theories developed in ecological stoichiometry (ES) are fundamentally based on traits. Traits directly linked to cell/body stoichiometry, such as nutrient uptake and storage, as well as the associated trade-offs, have the potential to shape ecological interactions such as competition and predation within ecosystems. Further, traits that indirectly influence and are influenced by nutritional requirements, such as cell/body size and growth rate, are tightly linked to organismal stoichiometry. Despite their physiological and ecological relevance, traits are rarely explicitly integrated in the framework of ES and, currently, the major challenge is to more closely inter-connect ES with trait-based ecology (TBE). Here, we highlight four interconnected nutrient trait groups, i.e., acquisition, body stoichiometry, storage, and excretion, which alter interspecific competition in autotrophs and heterotrophs. We also identify key differences between producer-consumer interactions in aquatic and terrestrial ecosystems. For instance, our synthesis shows that, in contrast to aquatic ecosystems, traits directly influencing herbivore stoichiometry in forested ecosystems should play only a minor role in the cycling of nutrients. We furthermore describe how linking ES and TBE can help predict the ecosystem consequences of global change. The concepts we highlight here allow us to predict that increasing N:P ratios in ecosystems should shift trait dominances in communities toward species with higher optimal N:P ratios and higher P uptake affinity, while decreasing N retention and increasing P storage.

Temperature strongly affects phytoplankton growth rates, but its effect on communities and ecosystem processes is debated. Because phytoplankton are often limited by light, temperature should change community structure if it affects the traits that determine competition for light. Furthermore, the aggregate response of phytoplankton communities to temperature will depend on how changes in community structure scale up to bulk rates. Here, we synthesize experiments on 57 phytoplankton species to analyze how the growth-irradiance relationship changes with temperature. We find that light-limited growth, light-saturated growth, and the optimal irradiance for growth are all highly sensitive to temperature. Within a species, these traits are co-adapted to similar temperature optima, but light-limitation reduces a species' temperature optimum by similar to 5 degrees C, which may be an adaptation to how light and temperature covary with depth or reflect underlying physiological correlations. Importantly, the maximum achievable growth rate increases with temperature under light saturation, but not under strong light limitation. This implies that light limitation diminishes the temperature sensitivity of bulk phytoplankton growth, even though community structure will be temperature-sensitive. Using a database of primary production incubations, we show that this prediction is consistent with estimates of bulk phytoplankton growth across gradients of temperature and irradiance in the ocean. These results indicate that interactions between temperature and resource limitation will be fundamental for explaining how phytoplankton communities and biogeochemical processes vary across temperature gradients and respond to global change.