37 research outputs found
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
Effects of sharp eyespot (Rhizoctonia cerealis) on yield and grain quality of winter wheat
Single-molecule techniques in biophysics : a review of the progress in methods and applications
Single-molecule biophysics has transformed our understanding of the
fundamental molecular processes involved in living biological systems, but also
of the fascinating physics of life. Far more exotic than a collection of
exemplars of soft matter behaviour, active biological matter lives far from
thermal equilibrium, and typically covers multiple length scales from the
nanometre level of single molecules up several orders of magnitude to longer
length scales in emergent structures of cells, tissues and organisms.
Biological molecules are often characterized by an underlying instability, in
that multiple metastable free energy states exist which are separated by energy
levels of typically just a few multiples of the thermal energy scale of kBT,
where kB is the Boltzmann constant and T the absolute temperature, implying
complex, dynamic inter-conversion kinetics across this bumpy free energy
landscape in the relatively hot, wet environment of real, living biological
matter. The key utility of single-molecule biophysics lies in its ability to
probe the underlying heterogeneity of free energy states across a population of
molecules, which in general is too challenging for conventional ensemble level
approaches which measure mean average properties. Parallel developments in both
experimental and theoretical techniques have been key to the latest insights
and are enabling the development of highly-multiplexed, correlative techniques
to tackle previously intractable biological problems. Experimentally,
technological developments in the sensitivity and speed of biomolecular
detectors, the stability and efficiency of light sources, probes and
microfluidics, have enabled and driven the study of heterogeneous behaviours
both in vitro and in vivo that were previously undetectable by ensemble
methods..
Modelling the impact of aquaculture on early diagenetic processes in sea loch sediments
We present a novel approach for the simulation of the impacts of finfish aquaculture on
sedimentary redox dynamics, based on the coupling of a fish farm waste deposition model (DEPOMOD)
and a knowledge-based reactive transport model (RTM) of early diagenesis. The integrated
model was applied to a salmon fish farm located in a Scottish fjordic sealoch. The major diagenetic
processes of the reaction network were first identified on the basis of literature information and historic
data. Next, the organic carbon (OC) flux at a pristine site near the farm was estimated by fitting
the vertical profiles of pore water and solid-state chemical species measured in the field. DEPOMOD
was then used to predict the fluxes of OC due to the release of uneaten feed and faeces at various distances
away from the farm. These fluxes were added to the background ‘natural’ fluxes and used as
forcing functions for the RTM. Comparison of the simulated transient profiles with data collected at
an impacted site revealed that the RTM model satisfactorily predicted the transient dynamics of the
system. We discuss the use of the model for cost-effective environmental impact assessments, site
selection and the optimization of husbandry practices
Marine Ecology Progress Series 388:63
ABSTRACT: We present a novel approach for the simulation of the impacts of finfish aquaculture on sedimentary redox dynamics, based on the coupling of a fish farm waste deposition model (DEPO-MOD) and a knowledge-based reactive transport model (RTM) of early diagenesis. The integrated model was applied to a salmon fish farm located in a Scottish fjordic sealoch. The major diagenetic processes of the reaction network were first identified on the basis of literature information and historic data. Next, the organic carbon (OC) flux at a pristine site near the farm was estimated by fitting the vertical profiles of pore water and solid-state chemical species measured in the field. DEPOMOD was then used to predict the fluxes of OC due to the release of uneaten feed and faeces at various distances away from the farm. These fluxes were added to the background 'natural' fluxes and used as forcing functions for the RTM. Comparison of the simulated transient profiles with data collected at an impacted site revealed that the RTM model satisfactorily predicted the transient dynamics of the system. We discuss the use of the model for cost-effective environmental impact assessments, site selection and the optimization of husbandry practices