Evaluating the outcomes of genetic rescue attempts

Augmenting gene flow is a powerful tool for the conservation of small, isolated populations. However, genetic rescue attempts have largely been limited to populations at the brink of extinction, in part due to concerns over negative outcomes (e.g., outbreeding depression). Increasing habitat fragmentation may necessitate more proactive genetic management. Broader application of augmented gene flow will, in turn, require rigorous evaluation to increase confidence and identify pitfalls in this approach. To date, there has been no assessment of best monitoring practices for genetic rescue attempts. We used genomically explicit, individual-based simulations to examine the effectiveness of common approaches (i.e., tests for increases in fitness, migrant ancestry, heterozygosity, and abundance) for determining whether genetic rescue or outbreeding depression occurred. Statistical power to detect the effects of gene flow on fitness was high (≥0.8) when effect sizes were large, a finding consistent with those from previous studies on severely inbred populations. However, smaller effects of gene flow on fitness can appreciably affect persistence probability but current evaluation approaches fail to provide results from which reliable inferences can be drawn. The power of the metrics we examined to evaluate genetic rescue attempts depended on the time since gene flow and whether gene flow was beneficial or deleterious. Encouragingly, the use of multiple metrics provided nonredundant information and improved inference reliability, highlighting the importance of intensive monitoring efforts. Further development of best practices for evaluating genetic rescue attempts will be crucial for a responsible transition to increased use of translocations to decrease extinction risk.     

Decision making to address complexity in systems and organizations

Environment Systems and Decisions -     

Environmental and endogenous control of selective tidal-stream transport behavior during blue crab <Emphasis Type="Italic">Callinectes sapidus</Emphasis> spawning migrations

Selective tidal-stream transport (STST) is used by many estuarine organisms. Spawning blue crabs use a form of STST, ebb-tide transport (ETT), to migrate to high-salinity areas of the lower estuary and coastal ocean for larval release. In tidal estuaries, ETT is driven by a circatidal rhythm in vertical swimming with episodic ascents into the water column during ebb tide. This study examined vertical swimming behavior of migrating female blue crabs tethered in habitats they could encounter during migration. A combined bio-physical field study in the summer of 2009 simultaneously measured physical parameters of the water column and vertical swimming behavior of tethered ovigerous crabs using pressure-recording dataloggers. Tethering sites were in the tidal Beaufort Inlet drainage and the non-tidal Albemarle-Pamlico Estuarine System, North Carolina, USA. Crabs tethered in tidal areas swam primarily during ebb tides, both day and night. Swimming frequency increased as embryonic development progressed and ebb-tide swimming continued after larval release. Swimming frequency varied among habitats with the highest swimming frequency in the known migratory corridor. Swimming did not occur in the non-tidal habitat. Differences in swimming frequency among sites are hypothesized to be responses to environmental cues, including flow regime. Some habitats serve as migratory corridors while others serve as foraging stopovers. These areas are likely defined by a combination of environmental cues including flow regime.     

Decision framework for evaluating the macroeconomic risks and policy impacts of cyber attacks

Increased reliance on the Internet for critical infrastructure and the global nature of supply chains provides an opportunity for adversaries to leverage dependencies and gain access to vital infrastructure. Traditional approaches to assessing risk in the cyber domain, including estimation of impacts, fall short due to uncertainty in how interconnected systems react to cyber attack. This paper describes a method to represent the pathways of disruption propagation, evaluate the macroeconomic impact of cyber threats and aid in selecting among various cybersecurity policies. Based on state of the art agent-based modeling, multicriteria decision analysis, and macroeconomic modeling tools, this framework provides dynamic macroeconomic, demographic and fiscal insights regarding shocks caused by cyber attacks to the regional economy over time. The interlinkage of these models will provide a robust and adaptive system that allows policy makers to evaluate complex issues such as cybersecurity threats and their impacts on the geopolitical, social, environmental, and macroeconomic landscape.     

A meta‐analytic evaluation of diversity training outcomes

The purpose of this meta‐analysis was to use theory and research on diversity, attitudes, and training to examine potential differential effects on affective‐based, cognitive‐based, and skill‐based outcomes, to examine potential moderators of those effects with a focus on affective‐based outcomes, and finally, to provide quantitative estimates of these posited relationships. Results from 65 studies (N = 8465) revealed sizable effects on affective‐based, cognitive‐based, and skill‐based outcomes as well as interesting boundary conditions for these effects on affective‐based outcomes. This study provides practical value to human resources managers and trainers wishing to implement diversity training within organizations as well as interesting theoretical advances for researchers. Practitioners have quantitative evidence that diversity training changes affective‐based, cognitive‐based, and skill‐based trainee outcomes. This study also supports and addresses future research needs. Copyright © 2012 John Wiley & Sons, Ltd.     

Application of SWAT with and without Variable Source Area Hydrology to a Large Watershed

In this study, two different versions of the Soil and Water Assessment Tool (SWAT) model were used to simulate the hydrology and biogeochemical response of the Cannonsville Reservoir watershed, in New York. The first version distributes overland flow in ways that are consistent with variable source area (VSA) hydrology driven by saturation excess runoff, whereas the second version is the standard version of SWAT. These two models were each calibrated for streamflow (Flow), particulate phosphorus (PP), total dissolved phosphorus (TDP), and sediment (Sed) against measured data from the 1,200 km² Cannonsville watershed. The standard version of the model yielded an r² between the measured and simulated data of 0.85, 0.73, 0.70, and 0.72 for Flow, Sed, TDP, and PP, respectively. The VSA version yielded an r² of 0.84, 0.69, 0.72, and 0.53 for Flow, Sed, TDP, and PP, respectively. The two models were then used to determine the maximum upper bound on the reduction in phosphorus loading by removing all of the corn in the watershed. The average reductions between the two models were 65 and 37% for PP and TDP, respectively. The VSA version was also used to estimate the effect of moving corn land in the watershed from the wettest, most runoff prone areas to the driest, least runoff prone areas, which cannot be done directly with the standard SWAT model.     

SWATmodel: A Multi‐Operating System,Multi‐Platform SWAT Model Package in R

The Soil and Water Assessment Tool (SWAT) model (Arnold et al., 1998) is a popular watershed management tool. Currently, the SWAT model, actively supported by the U.S. Department of Agriculture and Texas A&M, operates only on Microsoft^® Windows, which hinders modelers that use other operating systems (OS). This technical note introduces the Comprehensive R Archive Network (CRAN) distributed “SWATmodel” package which allows SWAT 2005 and 2012 to be widely distributed and run as a linear model‐like function on multiple OS and processor platforms. This allows researchers anywhere in the world using virtually any OS to run SWAT. In addition to simplifying the use of SWAT across computational platforms, the SWATmodel package allows SWAT modelers to utilize the analytical capabilities, statistical libraries, modeling tools, and programming flexibility inherent to R. The software allows watershed modelers to develop a simple hydrological watershed model conceptualization of the SWAT model and to obtain a first approximation of the minimum expected results a more complicated model should deliver. As a proof of concept, we test the SWAT model by initializing and calibrating 314 U.S. Geological Survey stream gages in the Chesapeake Bay watershed and present the results.