A methodology for parameter estimation in seaweed productivity modelling

This paper presents a combined approach for parameter estimation in models of primary production. The focus is on gross primary production and nutrient assimilation by seaweeds. A database of productivity determinations, biomass and mortality measurements and nutrient uptake rates obtained over one year for Gelidium sesquipedale in the Atlantic Ocean off Portugal has been used. Annual productivity was estimated by harvesting methods, and empirical relationships using mortality/ wave energy and respiration rates have been derived to correct for losses and to convert the estimates to gross production. In situ determinations of productivity have been combined with data on the light climate (radiation periods, intensity, mean turbidity) to give daily and annual productivity estimates. The theoretical nutrient uptake calculated using a 'Redfield ratio' approach and determinations of in situ N and P consumption by the algae during incubation periods have also been compared. The results of the biomass difference and incubation approaches are discussed in order to assess the utility of coefficients determined in situ for parameter estimation in seaweed production models

Geographic variation in plant community structure of salt marshes: species, functional and phylogenetic perspectives.

In general, community similarity is thought to decay with distance; however, this view may be complicated by the relative roles of different ecological processes at different geographical scales, and by the compositional perspective (e.g. species, functional group and phylogenetic lineage) used. Coastal salt marshes are widely distributed worldwide, but no studies have explicitly examined variation in salt marsh plant community composition across geographical scales, and from species, functional and phylogenetic perspectives. Based on studies in other ecosystems, we hypothesized that, in coastal salt marshes, community turnover would be more rapid at local versus larger geographical scales; and that community turnover patterns would diverge among compositional perspectives, with a greater distance decay at the species level than at the functional or phylogenetic levels. We tested these hypotheses in salt marshes of two regions: The southern Atlantic and Gulf Coasts of the United States. We examined the characteristics of plant community composition at each salt marsh site, how community similarity decayed with distance within individual salt marshes versus among sites in each region, and how community similarity differed among regions, using species, functional and phylogenetic perspectives. We found that results from the three compositional perspectives generally showed similar patterns: there was strong variation in community composition within individual salt marsh sites across elevation; in contrast, community similarity decayed with distance four to five orders of magnitude more slowly across sites within each region. Overall, community dissimilarity of salt marshes was lowest on the southern Atlantic Coast, intermediate on the Gulf Coast, and highest between the two regions. Our results indicated that local gradients are relatively more important than regional processes in structuring coastal salt marsh communities. Our results also suggested that in ecosystems with low species diversity, functional and phylogenetic approaches may not provide additional insight over a species-based approach

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

Optimal foraging and community structure: implications for a guild of generalist grassland herbivores

A particular linear programming model is constructed to predict the diets of each of 14 species of generalist herbivores at the National Bison Range, Montana. The herbivores have body masses ranging over seven orders of magnitude and belonging to two major taxa: insects and mammals. The linear programming model has three feeding constraints: digestive capacity, feeding time and energy requirements. A foraging strategy that maximizes daily energy intake agrees very well with the observed diets. Body size appears to be an underlying determinant of the foraging parameters leading to diet selection. Species that possess digestive capacity and feeding time constraints which approach each other in magnitude have the most generalized diets. The degree that the linear programming models change their diet predictions with a given percent change in parameter values (sensitivity) may reflect the observed ability of the species to vary their diets. In particular, the species which show the most diet variability are those whose diets tend to be balanced between monocots and dicots. The community-ecological parameters of herbivore body-size ranges and species number can possibly be related to foraging behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47765/1/442_2004_Article_BF00377109.pd