Aim The aim of this study is to answer the questions: (1) do small organisms disperse farther than large, or vice versa; and (2) does the observed pattern differ for passive and active dispersers? These questions are central to several themes in biogeography (including microbial biogeography), macroecology, metacommunity ecology and conservation biology.Location The meta-analysis was conducted using published data collected worldwide. MethodsWe collected and analysed 795 data values in the peer-reviewed literature for direct observations of both maximal dispersal distance and mass of the dispersing organisms (e.g. seeds, not trees). Analysed taxa ranged in size from bacteria to whales. We applied macroecology analyses based on null models (using Monte Carlo randomizations) to test patterns relative to specific hypotheses. ResultsCollected dispersal distance and mass data spanned 9 and 21 orders of magnitude, respectively. Active dispersers dispersed significantly farther ( P < 0.001) and were significantly greater in mass ( P < 0.001) than passive dispersers. Overall, size matters: larger active dispersers attained greater maximum observed dispersal distances than smaller active dispersers. In contrast, passive-disperser distances were random with respect to propagule mass, but not uniformly random, in part due to sparse data available for tiny propagules. ConclusionsSize is important to maximal dispersal distance for active dispersers, but not for passive dispersers. Claims that microbes disperse widely cannot be tested by current data based on direct observations of dispersal: indirect approaches will need to be applied. Distance-mass relationships should contribute to a resolution of neutral and niche-based metacommunity theories by helping scale expectations for dispersal limitation. Also, distance-mass relationships should inform analyses of latitudinal species richness and conservation biology topics such as fragmentation, umbrella species and taxonomic homogenization.

Mesoscale model simulations have been performed of the second episode of gravity waves observed in great detail in previous studies on 11-12 July 1981 during the Cooperative Convective Precipitation Experiment. The dominant wave simulated by the model was mechanically forced by the strong updraft associated with a mountainplains solenoid (MPS). As this updraft impinged upon a stratified shear layer above the deep, well-mixed boundary layer that developed due to strong sensible heating over the Absaroka Mountains, the gravity wave was created. This wave rapidly weakened as it propagated eastward. However, explosive convection developed directly over the remnant gravity wave as an eastward-propagating density current produced by a rainband generated within the MPS leeside convergence zone merged with a westward-propagating density current in eastern Montana. The greatly strengthened cool pool resulting from this new convection then generated a bore wave that appeared to be continuous with the movement of the incipient gravity wave as it propagated across Montana and the Dakotas. The nonlinear balance equation and Rossby number were computed to explore the role of geostrophic adjustment in the forecast gravity wave generation, as suggested in previous studies of this wave event. These fields did indicate flow imbalance, but this was merely the manifestation of the MPS-forced gravity wave. Thus, the imbalance indicator fields provided no lead time for predicting wave occurrence. Several sensitivity tests were performed to study the role of diabatic processes and topography in the initiation of the flow imbalance and the propagating gravity waves. When diabatic effects owing to precipitation were prevented, a strong gravity wave still was generated in the upper troposphere within the region of imbalance over the mountains. However, it did not have a significant impact because moist convection was necessary to maintain wave energy in the absence of an efficient wave duct. No gravity waves were present in either a simulation that disallowed surface sensible heating, or the ''flat terrain'' simulation, because the requisite MPS forcing could not occur. This study highlights difficulties encountered in attempting to model the generation of observed gravity waves over complex terrain in the presence of strong diabatic effects. The complex interactions that occurred between the sensible heating over complex terrain, the incipient gravity wave, and convection highlight the need for much more detailed observations between wave generation regions over mountains and the plains downstream of such regions.

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Agricultural industrialization and the subsequent reliance on pesticides has resulted in numerous unintended consequences, such as impacts upon the environment and by extension human health. Eco‐efficiency is a strategy for sustainably increasing production, while simultaneously decreasing these externalities on ecological systems. Eco‐efficiency is defined as the ratio of production to environmental impacts. It has been widely adopted to improve chemical production, but we investigate the challenges of applying eco‐efficiency to pesticide use. Eco‐efficiency strategies include technological innovation, investment in research and development, improvement of business processes, and accounting for market forces. These components are often part of integrated pest management (IPM) systems that include alternatives to pesticides, but its implementation is often thwarted by commercial realities and technical challenges. We propose the creation and adoption of an eco‐efficiency index for pesticide use so that the broad benefits of eco‐efficient strategies such as IPM can be more readily quantified. We propose an index based upon the ratio of crop yield to a risk quotient (RQ) calculated from pesticide toxicity. Eco‐efficiency is an operational basis for optimizing pest management for sustainability. It naturally favors adoption of IPM and should be considered by regulators, researchers, and practitioners involved in pest management. © 2019 Society of Chemical Industry

Social epidemics or behaviorally based non-communicable diseases are becoming an increasingly important problem in developed countries including the United States. It is the aim of our paper to propose a previously understudied aspect of the spread of social epidemics, the role of information in both causing and mitigating social epidemics. In this paper, we ask, can information be harmful, contagious, and a causal factor in social epidemics? In the spread of biological epidemics, the causal agents are biological pathogens such as bacteria or viruses. We propose that in the spread of social epidemics, one of the causal agents is harmful information, which is increasing exponentially in the age of the internet. We ground our idea in the concept of the meme and define the concept of an infopathogen as harmful information that can spread or intensify a social epidemic. Second, we ask, what are the best tools to understand the role of information in the spread of social epidemics? The epidemiological triad that includes a host, agents (and vectors), and the environment is extended into a quad by including information agents. The quad includes the role of information technologies as vectors and the impact of the social environment. The “life cycles” of pathogens in biological epidemics and infopathogens in social epidemics are compared, along with mitigations suggested by the epidemiological quad. Challenges to the theory of infopathogens, including the complexities associated with the spread of memes and the role of behavior in the spread of epidemics are discussed. Implications of the theory including the classification of harmfulness, the freedom of speech, and the treatment of infected individuals are also considered. We believe the application of the epidemiological quad provides insights into social epidemics and potential mitigations. Finally, we stress that infopathogens are only part of social epidemic development; susceptible hosts, a favorable environment, and availability of physical agents are all also required.