Studying seabird diet through genetic analysis of faeces: a case study on Macaroni Penguins (Eudyptes chrysolophus)

Determination of seabird diet usually relies on the analysis of stomach-content remains obtained through stomach flushing; this technique is both invasive and logistically difficult. We evaluate the usefulness of DNA-based faecal analysis in a dietary study on chick-rearing macaroni penguins (Eudyptes chrysolophus) at Heard Island. Conventional stomach-content data was also collected, allowing comparison of the approaches. Methodology/Principal Findings. Preyspecific PCR tests were used to detect dietary DNA in faecal samples and amplified prey DNA was cloned and sequenced. Of the 88 faecal samples collected, 39 contained detectable DNA from one or more of the prey groups targeted with PCR tests. Euphausiid DNA was most commonly detected in the early (guard) stage of chick-rearing, and detection of DNA from the myctophid fish Krefftichthys anderssoni and amphipods became more common in samples collected in the later (cre`che) stage. These trends followed those observed in the penguins’ stomach contents. In euphausiid-specific clone libraries the proportion of sequences from the two dominant euphausiid prey species (Euphausia vallentini and Thysanoessa macrura) changed over the sampling period; again, this reflected the trend in the stomach content data. Analysis of prey sequences in universal clone libraries revealed a higher diversity of fish prey than identified in the stomachs, but non-fish prey were not well represented. Conclusions/Significance. The present study is one of the first to examine the full breadth of a predator’s diet using DNA based faecal analysis. We discuss methodological difficulties encountered and suggest possible refinements. Overall, the ability of the DNA-based approach to detect temporal variation in the diet of macaroni penguins indicates this non-invasive method will be generally useful for monitoring population-level dietary trends in seabirds

Assessing the Health of Richibucto Estuary with the Latent Health Factor Index

The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon multimetric indices of various forms. Although indices may be numbers, many are constructed based on procedures that are highly qualitative in nature, thus limiting the quantitative rigour of the practical interpretations made from these indices. The statistical modelling approach to construct the latent health factor index (LHFI) was recently developed to express ecological data, collected to construct conventional multimetric health indices, in a rigorous quantitative model that integrates qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modelling approach allows (a) statistical inference of health for observed sites and (b) prediction of health for unobserved sites, all accompanied by formal uncertainty statements. Thus far, the LHFI approach has been demonstrated and validated on freshwater ecosystems. The goal of this paper is to adapt this approach to modelling estuarine ecosystem health, particularly that of the previously unassessed system in Richibucto in New Brunswick, Canada. Field data correspond to biotic health metrics that constitute the AZTI marine biotic index (AMBI) and abiotic predictors preconceived to influence biota. We also briefly discuss related LHFI research involving additional metrics that form the infaunal trophic index (ITI). Our paper is the first to construct a scientifically sensible model to rigorously identify the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content --- all regarded a priori as qualitatively important abiotic drivers --- towards site health in the Richibucto ecosystem.Comment: On 2013-05-01, a revised version of this article was accepted for publication in PLoS One. See Journal reference and DOI belo

Predicting consumer biomass, size-structure, production, catch potential, responses to fishing and associated uncertainties in the world's marine ecosystems

Existing estimates of fish and consumer biomass in the world’s oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (< 20 cm from species of maximum mass < 1kg) are targeted in all oceans, but the predicted yields would rarely be accessible in practice and this fishing strategy leads to the collapse of larger species if fishing mortality rates on different size classes cannot be decoupled. Our analyses show that models with minimal parameter demands that are based on a few established ecological principles can support equitable analysis and comparison of diverse ecosystems. The analyses provide insights into the effects of parameter uncertainty on global biomass and production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented. Consequently, our simple models become increasingly less useful than more complex alternatives when addressing questions about food web structure and function, biodiversity, resilience and human impacts at smaller scales and for areas closer to coasts