Scientific Collaborations: How Do We Measure the Return on Relationships?

Emerging infectious diseases (EIDs), the majority of which are zoonotic, represent a tremendous challenge for public health and biosurveillance infrastructure across the globe. Due to the complexity of zoonotic pathogens, it is essential that research and response to EIDs be a transdisciplinary effort. And while crisis and circumstance may be the initial catalyst for responding to an outbreak, we provide examples of how transdisciplinary scientific collectives, which are organized and solidified in advance of crises, can transform the way the world responds to outbreaks and in some cases could even prevent one from occurring (1). Current methods for assessing whether a cooperative engagement between countries is producing measurable and sustainable value is based on the ideas of return on investment and do not consider the inherent importance of relationships. In this article, we apply the idea of return on relationships (ROR) and propose a method for measuring ROR, using a system dynamics modeling framework commonly used in epidemiology. Tracking the numerous and diverse scientific collaborations that emerged from a training workshop for biosurveillance of bats held in Singapore in 2014, we apply a methodology for visualizing and measuring the relationship networks and outcomes that result. Additionally, the collaborative, multidisciplinary network that coalesced in response to the Hantavirus outbreak in New Mexico is 1993 is discussed as an example of the long-term benefits of ROR.

Scale-dependent responses of plant biodiversity to nitrogen enrichment.

Experimental studies demonstrating that nitrogen (N) enrichment reduces plant diversity within individual plots have led to the conclusion that anthropogenic N enrichment is a threat to global biodiversity. These conclusions overlook the influence of spatial scale, however, as N enrichment may alter beta diversity (i.e., how similar plots are in their species composition), which would likely alter the degree to which N-induced changes in diversity within localities translate to changes in diversity at larger scales that are relevant to policy and management. Currently, it is unclear how N enrichment affects biodiversity at scales larger than a small plot. We synthesized data from 18 N-enrichment experiments across North America to examine the effects of N enrichment on plant species diversity at three spatial scales: small (within plots), intermediate (among plots), and large (within and among plots). We found that N enrichment reduced plant diversity within plots by an average of 25% (ranging from a reduction of 61% to an increase of 5%) and frequently enhanced beta diversity. The extent to which N enrichment altered beta diversity, however, varied substantially among sites (from a 22% increase to an 18% reduction) and was contingent on site productivity. Specifically, N enrichment enhanced beta diversity at low-productivity sites but reduced beta diversity at high-productivity sites. N-induced changes in beta diversity generally reduced the extent of species loss at larger scales to an average of 22% (ranging from a reduction of 54% to an increase of 18%). Our results demonstrate that N enrichment often reduces biodiversity at both local and regional scales, but that a focus on the effects of N enrichment on biodiversity at small spatial scales may often overestimate (and sometimes underestimate) declines in regional biodiversity by failing to recognize the effects of N on beta diversity.