Identifying four phytoplankton functional types from space: An ecological approach

Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown.

An innovative statistical approach to constructing a readily comprehensible food web for a demersal fish community

Many food webs are so complex that it is difficult to distinguish the relationships between predators and their prey. We have therefore developed an approach that produces a food web which clearly demonstrates the strengths of the relationships between the predator guilds of demersal fish and their prey guilds in a coastal ecosystem. Subjecting volumetric dietary data for 35 abundant predators along the lower western Australia coast to cluster analysis and the SIMPROF routine separated the various species x length class combinations into 14 discrete predator guilds. Following nMDS ordination, the sequence of points for these predator guilds represented a 'trophic' hierarchy. This demonstrated that, with increasing body size, several species progressed upwards through this hierarchy, reflecting a marked change in diet, whereas others remained within the same guild. A novel use of cluster analysis and SIMPROF then identified each group of prey that was ingested in a common pattern across the full suite of predator guilds. This produced 12 discrete groups of taxa (prey guilds) that each typically comprised similar ecological/functional prey, which were then also aligned in a hierarchy. The hierarchical arrangements of the predator and prey guilds were plotted against each other to show the percentage contribution of each prey guild to the diet of each predator guild. The resultant shade plot demonstrates quantitatively how food resources are spread among the fish species and revealed that two prey guilds, one containing cephalopods and teleosts and the other small benthic/epibenthic crustaceans and polychaetes, were consumed by all predator guilds.

Parameterisation of bivalve functional traits for mechanistic eco-physiological dynamic energy budget (DEB) models

Mechanistic models such as those based on dynamic energy budget (DEB) theory are emergent ecomechanics tools to investigate the extent of fitness in organisms through changes in life history traits as explained by bioenergetic principles. The rapid growth in interest around this approach originates from the mechanistic characteristics of DEB, which are based on a number of rules dictating the use of mass and energy flow through organisms. One apparent bottleneck in DEB applications comes from the estimations of DEB parameters which are based on mathematical and statistical methods (covariation method). The parameterisation process begins with the knowledge of some functional traits of a target organism (e. g. embryo, sexual maturity and ultimate body size, feeding and assimilation rates, maintenance costs), identified from the literature or laboratory experiments. However, considering the prominent role of the mechanistic approach in ecology, the reduction of possible uncertainties is an important objective. We propose a revaluation of the laboratory procedures commonly used in ecological studies to estimate DEB parameters in marine bivalves. Our experimental organism was Brachidontes pharaonis. We supported our proposal with a validation exercise which compared life history traits as obtained by DEBs (implemented with parameters obtained using classical laboratory methods) with the actual set of species traits obtained in the field. Correspondence between the 2 approaches was very high (>95%) with respect to estimating both size and fitness. Our results demonstrate a good agreement between field data and model output for the effect of temperature and food density on age-size curve, maximum body size and total gamete production per life span. The mechanistic approach is a promising method of providing accurate predictions in a world that is under in creasing anthropogenic pressure.

Ecological equivalence of species within phytoplankton functional groups

1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.