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.     

Understanding policing as a mechanism of cheater control in cooperating bacteria

Policing occurs in insect, animal and human societies, where it evolved as a mechanism maintaining cooperation. Recently, it has been suggested that policing might even be relevant in enforcing cooperation in much simpler organisms such as bacteria. Here, we used individual‐based modelling to develop an evolutionary concept for policing in bacteria and identify the conditions under which it can be adaptive. We modelled interactions between cooperators, producing a beneficial public good, cheaters, exploiting the public good without contributing to it, and public good‐producing policers that secrete a toxin to selectively target cheaters. We found that toxin‐mediated policing is favoured when (a) toxins are potent and durable, (b) toxins are cheap to produce, (c) cell and public good diffusion is intermediate, and (d) toxins diffuse farther than the public good. Although our simulations identify the parameter space where toxin‐mediated policing can evolve, we further found that policing decays when the genetic linkage between public good and toxin production breaks. This is because policing is itself a public good, offering protection to toxin‐resistant mutants that still produce public goods, yet no longer invest in toxins. Our work thus highlights that not only specific environmental conditions are required for toxin‐mediated policing to evolve, but also strong genetic linkage between the expression of public goods, toxins and toxin resistance is essential for this mechanism to remain evolutionarily stable in the long run.     

Estimating seed dispersal distance: A comparison of methods using animal movement and plant genetic data on two primate‐dispersed Neotropical plant species

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Measuring avian specialization

Measuring the extent to which a species is specialized is a major challenge in ecology, with important repercussions for fundamental research as well as for applied ecology and conservation. Here, we develop a multidimensional index of specialization based on five sets of ecological characteristics of breeding bird species. We used two recent databases of species traits of European birds based on foraging ecology, habitat, and breeding characteristics. The indices of specialization were calculated by applying the Gini coefficient, an index of inequality. The Gini coefficient is a measure of statistical dispersion on a scale between 0 and 1, reflecting a gradient from low to high specialization, respectively. Finally, we tested the strength of the phylogenetic signal of each specialization index to understand how the variance of such indices is shared throughout the phylogeny. The methods for constructing and evaluating a multidimensional index of bird specialization could also be applied to other taxa and regions, offering a simple but useful tool, particularly suited for global or biogeographic studies, as a contribution to comparative estimates of the degree of specialization of species.     

Does perspective matter? A case study comparing Eulerian and Lagrangian estimates of common murre (Uria aalge) distributions

Studies estimating species' distributions require information about animal locations in space and time. Location data can be collected using surveys within a predetermined frame of reference (i.e., Eulerian sampling) or from animal‐borne tracking devices (i.e., Lagrangian sampling). Integration of observations obtained from Eulerian and Lagrangian perspectives can provide insights into animal movement and habitat use. However, contemporaneous data from both perspectives are rarely available, making examination of biases associated with each sampling approach difficult. We compared distributions of a mobile seabird observed concurrently from ship, aerial, and satellite tag surveys during May, June, and July 2012 in the northern California Current. We calculated utilization distributions to quantify and compare variability in common murre (Uria aalge) space use and examine how sampling perspective and platform influence observed patterns. Spatial distributions of murres were similar in May, regardless of sampling perspective. Greatest densities occurred in coastal waters off southern Washington and northern Oregon, near large murre colonies and the mouth of the Columbia River. Density distributions of murres estimated from ship and aerial surveys in June and July were similar to those observed in May, whereas distributions of satellite‐tagged murres in June and July indicated northward movement into British Columbia, Canada, resulting in different patterns observed from Eulerian and Lagrangian perspectives. These results suggest that the population of murres observed in the northern California Current during spring and summer includes relatively stationary individuals attending breeding colonies and nonstationary, vagile adults and subadults. Given the expected growth of telemetry studies and advances in survey technology (e.g., unmanned aerial systems), these results highlight the importance of considering methodological approaches, spatial extent, and synopticity of distribution data sets prior to integrating data from different sampling perspectives.     

Genome-scale analysis of Mannheimia succiniciproducens metabolism

Mannheimia succiniciproducens MBEL55E isolated from bovine rumen is a capnophilic gram-negative bacterium that efficiently produces succinic acid, an industrially important four carbon dicarboxylic acid. In order to design a metabolically engineered strain which is capable of producing succinic acid with high yield and productivity, it is essential to optimize the whole metabolism at the systems level. Consequently, in silico modeling and simulation of the genome-scale metabolic network was employed for genome-scale analysis and efficient design of metabolic engineering experiments. The genome-scale metabolic network of M. succiniciproducens consisting of 686 reactions and 519 metabolites was constructed based on reannotation and validation experiments. With the reconstructed model, the network structure and key metabolic characteristics allowing highly efficient production of succinic acid were deciphered; these include strong PEP carboxylation, branched TCA cycle, relative weak pyruvate formation, the lack of glyoxylate shunt, and non-PTS for glucose uptake. Constraints-based flux analyses were then carried out under various environmental and genetic conditions to validate the genome-scale metabolic model and to decipher the altered metabolic characteristics. Predictions based on constraints-based flux analysis were mostly in excellent agreement with the experimental data. In silico knockout studies allowed prediction of new metabolic engineering strategies for the enhanced production of succinic acid. This genome-scale in silico model can serve as a platform for the systematic prediction of physiological responses of M. succiniciproducens to various environmental and genetic perturbations and consequently for designing rational strategies for strain improvement.     

VPMCD: variable interaction modeling approach for class discrimination in biological systems

Data classification algorithms applied for class prediction in computational biology literature are data specific and have shown varying degrees of performance. Different classes cannot be distinguished solely based on interclass distances or decision boundaries. We propose that inter-relations among the features be exploited for separating observations into specific classes. A new variable predictive model based class discrimination (VPMCD) method is described here. Three well established and proven data sets of varying statistical and biological significance are utilized as benchmark. The performance of the new method is compared with advanced classification algorithms. The new method performs better during different tests and shows higher stability and robustness. The VPMCD is observed to be a potentially strong classification approach and can be effectively extended to other data mining applications involving biological systems.     

3D-QSAR studies of Dipeptidyl peptidase IV inhibitors using a docking based alignment

Dipeptidyl peptidase IV (DPP-IV) deactivates the incretin hormones GLP-1 and GIP by cleaving the penultimate proline or alanine from the N-terminal (P1-position) of the peptide. Inhibition of this enzyme will prevent the degradation of the incretin hormones and maintain glucose homeostasis; this makes it an attractive target for the development of drugs for diabetes. This paper reports 3D-QSAR analysis of several DPP-IV inhibitors, which were aligned by the receptor-based technique. The conformation of the molecules in the active site was obtained through docking methods. The QSAR models were generated on two training sets composed of 74 and 25 molecules which included phenylalanine, thiazolidine, and fluorinated pyrrolidine analogs. The 3D-QSAR models are robust with statistically significant r², q², and values. The CoMFA and CoMSIA models were used to design some new inhibitors with several fold higher binding affinity. Figure The CoMFA contours around molecule D1T155 (a) steric contours - favored (green); disfavored (yellow) (b) electrostatic contours - electropositive (blue); electronegative (red)