A Framework for Development and Communication of Absolute Environmental Sustainability Assessment Methods

An absolute environmental sustainability assessment (AESA) addresses whether a production or consumption activity can be considered environmentally sustainable in an absolute sense. This involves a comparison of its environmental pressure to its allocated environmental carrying capacity. AESA methods have been developed in multiple academic fields, each using their own set of concepts and terms with little communication across the fields. A recent growing interest in using AESA methods for decision support calls for a better common understanding of the constituents of an AESA method and how it can be communicated to scientific peers and to potential users. With this aim, we develop a framework for AESA methods, composed of a succession of four assessment steps and involving six methodological choices that must be made by the method developer or the user. We then use the framework to analyze and compare five selected AESA methods that focus on the release of phosphorus and nitrogen to the environment. In this manner, we show that the framework is able to systematically differentiate AESA methods that initially appear to be similar. Intended users of the framework include (1) method developers communicating new AESA methods to academic peers or potential method users and (2) researchers comparing a group of existing AESA methods and communicating their differences to their peers and to potential users looking for guidance on method selection.     

A dynamic, architectural plant model simulating resource-dependent growth

BACKGROUND AND AIMS: Physiological and architectural plant models have originally been developed for different purposes and therefore have little in common, thus making combined applications difficult. There is, however, an increasing demand for crop models that simulate the genetic and resource-dependent variability of plant geometry and architecture, because man is increasingly able to transform plant production systems through combined genetic and environmental engineering. MODEL: GREENLAB is presented, a mathematical plant model that simulates interactions between plant structure and function. Dual-scale automaton is used to simulate plant organogenesis from germination to maturity on the basis of organogenetic growth cycles that have constant thermal time. Plant fresh biomass production is computed from transpiration, assuming transpiration efficiency to be constant and atmospheric demand to be the driving force, under non-limiting water supply. The fresh biomass is then distributed among expanding organs according to their relative demand. Demand for organ growth is estimated from allometric relationships (e.g. leaf surface to weight ratios) and kinetics of potential growth rate for each organ type. These are obtained through parameter optimization against empirical, morphological data sets by running the model in inverted mode. Potential growth rates are then used as estimates of relative sink strength in the model. These and other 'hidden' plant parameters are calibrated using the non-linear, least-square method. KEY RESULTS AND CONCLUSIONS: The model reproduced accurately the dynamics of plant growth, architecture and geometry of various annual and woody plants, enabling 3D visualization. It was also able to simulate the variability of leaf size on the plant and compensatory growth following pruning, as a result of internal competition for resources. The potential of the model's underlying concepts to predict the plant's phenotypic plasticity is discussed.     

Informing conservation by identifying range shift patterns across breeding habitats and migration strategies

A species distribution combines the resources and climatic tolerances that allow an individual or population to persist. As these conditions change, one mechanism to maintain favorable resources is for an organism to shift its range. Much of the research examining range shifts has focused on dynamic distribution boundaries wheras the role of species breeding habitat or migration strategies on shift tendencies has received less attention. We expand on previous research by using a large suite of avian species (i.e., 277), analyzing observed abundance-weighted average latitudes, and categorizing species by breeding environment and migration strategy. We used the North American Breeding Bird Survey dataset to address two questions: (1) Has the center of observed abundance for individual species shifted latitudinally? (2) Is there a relationship between migration strategy or breeding habitat and range shifts? Results indicate the majority of species have experienced poleward range shifts over the last 43 years, and birds breeding in all habitat showed trends of poleward shift but only those species breeding in scrub-shrub and grassland environments were different from zero. Additionally, species that are short distance migrants are experiencing significant poleward shifts while Neotropical and permanent residents had shifts that were not different from zero. Our findings do support the general trend expected from climate driven changes (i.e., > 52 % shifting poleward), however, the proportion of species exhibiting equatorial shifts (24 %) or no significant shifts (23 %) illustrates the complex interplay between land cover, climate, species interactions, and other forces that can interact to influence breeding ranges over time. Regardless of the mechanisms driving range shifts, our findings emphasize the need for connecting and expanding habitats for those species experiencing range shifts. This research describes the patterns of breeding birds through central North America and we encourage future research to focus on the mechanisms driving these patterns.     

Assessment of two flexible and compatible SNP genotyping platforms: TaqMan SNP Genotyping Assays and the SNPlex Genotyping System

In this review we describe the principles, protocols, and applications of two commercially available SNP genotyping platforms, the TaqMan SNP Genotyping Assays and the SNPlex Genotyping System. Combined, these two technologies meet the requirements of multiple SNP applications in genetics research and pharmacogenetics. We also describe a set of SNP selection tools and validated assay resources which we developed to accelerate the cycle of experimentation on these platforms. Criteria for selecting the more appropriate of these two genotyping technologies are presented: the genetic architecture of the trait of interest, the throughput required, and the number of SNPs and samples needed for a successful study. Overall, the TaqMan assay format is suitable for low- to mid-throughput applications in which a high assay conversion rate, simple assay workflow, and low cost of automation are desirable. The SNPlex Genotyping System, on the other hand, is well suited for SNP applications in which throughput and cost-efficiency are essential, e.g., applications requiring either the testing of large numbers of SNPs and samples, or the flexibility to select various SNP subsets.