Nutrient addition effects on tropical dry forests: a mini-review from microbial to ecosystem scales.

Humans have more than doubled inputs of reactive nitrogen globally and greatly accelerated the biogeochemical cycles of phosphorus and metals. However, the impacts of increased element mobility on tropical ecosystems remain poorly quantified, particularly for the vast tropical dry forest biome. Tropical dry forests are characterized by marked seasonality, relatively little precipitation, and high heterogeneity in plant functional diversity and soil chemistry. For these reasons, increased nutrient deposition may affect tropical dry forests differently than wet tropical or temperate forests. Here, we review studies that investigated how nutrient availability affects ecosystem and community processes from the microsite to ecosystem scales in tropical dry forests. The effects of N and P addition on ecosystem carbon cycling and plant and microbial dynamics depend on forest successional stage, soil parent material, and rainfall regime. Responses may depend on whether overall productivity is N- vs. P-limited, although data to test this hypothesis are limited. These results highlight the many important gaps in our understanding of tropical dry forest responses to global change. Large-scale experiments are required to resolve these uncertainties

Unilateral versus coordinated effects:comparing the impact on consumer welfare of alternative merger outcomes

The nature of tacitly collusive behaviour often makes coordination unstable, and this may result in periods of breakdown, during which consumers benet from reduced prices. This is allowed for by adding demand uncertainty to the Compte et al. (2002) model of tacit collusion amongst asymmetric rms. Breakdowns occur when a rm cannot exclude the possibility of a deviation by a rival. It is then possible that an outcome with collusive behaviour, subject to long/frequent break downs, can improve consumer welfare compared to an alternative with sustained unilateral conduct. This is illustrated by re-examining the Nestle/Perrier merger analyzed by Compte et al., but now also taking into account the potential for welfare losses arising from unilateral behaviour

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Assessing innovations for upscaling forest landscape restoration

There is an increasing urgency to implement large-scale ecosystem restoration to mitigate the biodiversity and climate crises. These efforts must be scaled up to counteract the widespread degradation of the world’s forests, although restoration costs can often limit their application. Thus, there is a pressing need to identify cost-effective approaches that catalyze landscape-scale ecological recovery. Here, we highlight seven assisted restoration innovations with demonstrated local-scale results that, once upscaled, hold promise to rapidly regenerate forests. We comprehensively assessed how each approach facilitated forest, woodland, and/or mangrove recovery across 143 studies. Our results reveal techniques with a marked ability to catalyze vegetation recovery compared to “business-as-usual” approaches. However, the context-dependent cost-benefit ratio and feasibility of applying particular approaches requires careful consideration. Our assessment emphasizes that we already have many of the tools necessary to drive the terrestrial restoration movement forward. It is time to implement and assess their efficacy at scale

Ectopic Expression of Vaccinia Virus E3 and K3 Cannot Rescue Ectromelia Virus Replication in Rabbit RK13 Cells

Citation: Hand, E. S., Haller, S. L., Peng, C., Rothenburg, S., & Hersperger, A. R. (2015). Ectopic Expression of Vaccinia Virus E3 and K3 Cannot Rescue Ectromelia Virus Replication in Rabbit RK13 Cells. Plos One, 10(3), 15. doi:10.1371/journal.pone.0119189As a group, poxviruses have been shown to infect a wide variety of animal species. However, there is individual variability in the range of species able to be productively infected. In this study, we observed that ectromelia virus (ECTV) does not replicate efficiently in cultured rabbit RK13 cells. Conversely, vaccinia virus (VACV) replicates well in these cells. Upon infection of RK13 cells, the replication cycle of ECTV is abortive in nature, resulting in a greatly reduced ability to spread among cells in culture. We observed ample levels of early gene expression but reduced detection of virus factories and severely blunted production of enveloped virus at the cell surface. This work focused on two important host range genes, named E3L and K3L, in VACV. Both VACV and ECTV express a functional protein product from the E3L gene, but only VACV contains an intact K3L gene. To better understand the discrepancy in replication capacity of these viruses, we examined the ability of ECTV to replicate in wild-type RK13 cells compared to cells that constitutively express E3 and K3 from VACV. The role these proteins play in the ability of VACV to replicate in RK13 cells was also analyzed to determine their individual contribution to viral replication and PKR activation. Since E3L and K3L are two relevant host range genes, we hypothesized that expression of one or both of them may have a positive impact on the ability of ECTV to replicate in RK13 cells. Using various methods to assess virus growth, we did not detect any significant differences with respect to the replication of ECTV between wild-type RK13 compared to versions of this cell line that stably expressed VACV E3 alone or in combination with K3. Therefore, there remain unanswered questions related to the factors that limit the host range of ECTV

Three Economist’s Tools for Antitrust Analysis: A Non-Technical Introduction

The importance of economics to the analysis and enforcement of competition policy and law has increased tremendously in the developed market economies in the past forty years. In younger and developing market economies, competition law itself has a history of twenty to twenty-five years at most – sometimes much less – and economic tools that have proven useful to competition law enforcement in developed market economies in focusing investigations and in assisting decision makers in distinguishing central from secondary issues are inevitably less well understood. This paper presents a non-technical introduction to three economic tools that have become widespread in competition law enforcement in general and in the analysis of proposed mergers in particular: critical loss analysis, upward pricing pressure, and the vertical arithmetic

Heterogeneous Merger Impacts on Competitive Outcomes

Mergers realize heterogeneous competitive effects on profits, production, and prices. To date, it is unclear whether differential merger outcomes are caused mostly by firms’ technology or product market attributes. Furthermore, empirical merger studies conventionally assume that, conditional on regressors, the impact of mergers on outcomes is the same for every firm. We allow the merger responses to vary across firms, even after controlling for regressors, and apply a random-coefficient or heterogeneous treatment effect model (in the context of Angrist and Krueger (1999), Heckman, Urzua, and Vytlacil (2006), and Cerulli (2012)). Based on a comprehensive dataset on the static random access memory industry, we find that firms’ postmerger output further increases (and postmerger price further declines) if merging firms are more efficient, operate in more elastic product markets, are more innovative, and acquire knowledge in technological areas that are relatively unexplored to themselves. A further interesting insight is that product market characteristics cause stronger postmerger outcome heterogeneities than do technology market characteristics. We also find that the postmerger effects accounting for heterogeneities differ greatly from those that consider homogeneous postmerger outcome effects. Our estimation results provide evidence that ignoring heterogeneous outcome effects can result in heterogeneity bias, just as ignoring premerger heterogeneities can lead to selectivity bias