A decision analytic model to guide early‐stage government regulatory action: Applications for synthetic biology

Synthetic biology (SB) involves the alteration of living cells and biomolecules for specific purposes. Products developed using these approaches could have significant societal benefits, but also pose uncertain risks to human and environmental health. Policymakers currently face decisions regarding how stringently to regulate and monitor various SB applications. This is a complex task, in which policymakers must balance uncertain economic, political, social, and health‐related decision factors associated with SB use. We argue that formal decision analytical tools could serve as a method to integrate available evidence‐based information and expert judgment on the impacts associated with SB innovations, synthesize that information into quantitative indicators, and serve as the first step toward guiding governance of these emerging technologies. For this paper, we apply multi‐criteria decision analysis to a specific case of SB, a micro‐robot based on biological cells called “cyberplasm.” We use data from a Delphi study to assess cyberplasm governance options and demonstrate how such decision tools may be used for assessments of SB oversight.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142416/1/rego12142.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142416/2/rego12142_am.pd

Anthropogenic Renourishment Feedback on Shorebirds: a Multispecies Bayesian Perspective

In this paper the realized niche of the Snowy Plover (Charadrius alexandrinus), a primarily resident Florida shorebird, is described as a function of the scenopoetic and bionomic variables at the nest-, landscape-, and regional-scale. We identified some possible geomorphological controls that influence nest-site selection and survival using data collected along the Florida Gulf coast. In particular we focused on the effects of beach replenishment interventions on the Snowy Plover (SP), and on the migratory Piping Plover	(PP)	(Charadrius	melodus )	and	Red	Knot	(RK)	(Calidris	canutus ).	Additionally, we investigated the potential differences between the SP breeding and wintering distributions using only regional-scale physiognomic variables and the recorded occur- rences. To quantify the relationship between past renourishment projects and shorebird species we used a Monte Carlo procedure to sample from the posterior distribution of the binomial probabilities that a region is not a nesting or a wintering ground conditional on the occurrence of a beach replenishment intervention in the same and the previous year. The results indicate that it was 2.3, 3.1, and 0.8 times more likely that a region was not a wintering ground following a year with a renourishment intervention for the SP, PP and RK respectively. For the SP it was 2.5. times more likely that a region was not a breeding ground after a renourishment event. Through a maximum entropy principle model we observed small differences in the habitat use of the SP during the breeding and the wintering season. However the habitats where RK was observed appeared quite different. While ecological niche models at the macro-scale are useful for determining habitat suitability ranges, the characterization of the species’ local niche is fundamentally important for adopting concrete multi-species management scenarios. Maintaining and creating optimal suitable habitats for SP characterized by sparse low vegetation in the foredunes areas, and uneven/low-slope beach surfaces, is the proposed conservation scenario to convert anthropic beach restorations and SP populations into a positive feedback without impacting other threatened shorebird species

Stability of a Giant Connected Component in a Complex Network

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems

IRGC Resource guide on Resilience

An edited collection of authored pieces comparing, contrasting, and integrating risk and resilience with an emphasis on ways to measure resilienc