Warming, crops, and insect pests: Crop responses to climate warming suggest that yields will decrease as growing-season temperatures increase. Deutsch et al. show that this effect may be exacerbated by insect pests (see the Perspective by Riegler). Insects already consume 5 to 20% of major grain crops. The authors' models show that for the three most important grain crops—wheat, rice, and maize—yield lost to insects will increase by 10 to 25% per degree Celsius of warming, hitting hardest in the temperate zone. These findings provide an estimate of further potential climate impacts on global food supply and a benchmark for future regional and field-specific studies of crop-pest-climate interactions. Science , this issue p. 916 ; see also p. 846

Livestock industries are vulnerable to disease threats, which can cost billions of dollars and have substantial negative social ramifications. Losses are mitigated through increased use of disease-related biosecurity practices, making increased biosecurity an industry goal. Currently, there is no industry-wide standard for sharing information about disease incidence or on-site biosecurity strategies, resulting in uncertainty regarding disease prevalence and biosecurity strategies employed by industry stakeholders. Using an experimental simulation game, with primarily student participants, we examined willingness to invest in biosecurity when confronted with disease outbreak scenarios. We varied the scenarios by changing the information provided about 1) disease incidence and 2) biosecurity strategy or response by production facilities to the threat of disease. Here we show that willingness to invest in biosecurity increases with increased information about disease incidence, but decreases with increased information about biosecurity practices used by nearby facilities. Thus, the type or context of the uncertainty confronting the decision maker may be a major factor influencing behavior. Our findings suggest that policies and practices that encourage greater sharing of disease incidence information should have the greatest benefit for protecting herd health.

Disease in U.S. animal livestock industries annually costs over a billion dollars. Adoption and compliance with biosecurity practices is necessary to successfully reduce the risk of disease introduction or spread. Yet, a variety of human behaviors, such as the urge to minimize time costs, may induce non-compliance with biosecurity practices. Utilizing a “serious gaming” approach, we examine how information about infection risk impacts compliance with biosecurity practices. We sought to understand how simulated environments affected compliance behavior with treatments that varied using three factors: (1) the risk of acquiring an infection, (2) the delivery method of the infection risk message (numerical, linguistic and graphical), and (3) the certainty of the infection risk information. Here we show that compliance is influenced by message delivery methodology, with numeric, linguistic, and graphical messages showing increasing efficacy, respectively. Moreover, increased situational uncertainty and increased risk were correlated with increases in compliance behavior. These results provide insight toward developing messages that are more effective and provide tools that will allow managers of livestock facilities and policy makers to nudge behavior toward more disease resilient systems via greater compliance with biosecurity practices.

We developed an agent-based susceptible / infective model which simulates disease incursions in the hog production chain networks of three U.S. states. Agent parameters, contact network data, and epidemiological spread patterns are output a er each model run. Key network metrics are then calculated, some of which pertain to overall network structure, and others to each node's positionality within the network. We run statistical tests to evaluate the extent to which each network metric predicts epidemiological vulnerability, finding significant correlations in some cases, but no individual metric that serves as a reliable risk indicator. To investigate the complex interactions between network structure and node positionality, we use a genetic programming (GP) algorithm to search for mathematical equations describing combinations of individual metrics-which we call "meta-metrics"-that may better predict vulnerability. We find that the GP solutions-the best of which combine both global and node-level metrics-are far better indicators of disease risk than any individual metric, with meta-metrics explaining up to % of the variability in agent vulnerability across all three study areas. We suggest that this methodology could be applied to aid livestock epidemiologists in the targeting of biosecurity interventions, and also that the meta-metric approach may be useful to study a wide range of complex network phenomena.

The Russian wheat aphid, Diuraphis noxia (Kurdjumov) is a serious pest of small grains, such as wheat and barley. High population growth rates and a broad gramineae host range have allowed this aphid to successfully establish and become pestiferous across much of North America since its invasion in the mid-1980s. Resistant wheat cultivars were developed and provided control of D. noxia until 2003, when a new biotype (designated RWA2, as contrasted with the original biotype’s designation, RWA1) emerged and rapidly spread through dryland winter wheat-growing regions. RWA2 displaced RWA1 more quickly than expected, based on RWA2’s advantage in RWA1-resistant wheat cultivars. Previous research suggested that RWA2 may out-compete RWA1 in cooler temperatures. Thus, we sought to determine if RWA2 had a competitive advantage over RWA1 during the overwintering period. We placed a known distribution of RWA1 and RWA2 aphids in the field for the winter at three sites across a latitudinal gradient (from northern Colorado to Texas) to test for a competitive advantage between these biotypes. We found overwhelming support for an overwintering competitive advantage by RWA2 over RWA1, with evidence suggesting a 10-fold advantage even at our Texas site (i.e., the site with the mildest winter). This substantial overwintering advantage helps explain the quick dispersion and displacement of RWA1 by RWA2.

As the Covid-19 pandemic continues worldwide, it has become increasingly clear that effective communication of disease transmission risks associated with protective behaviors is essential, and that communication tactics are not ubiquitously and homogenously understood. Analogous to Covid-19, communicable diseases in the hog industry result in millions of animal deaths and in the United States costs hundreds of millions of dollars annually. Protective behaviors such as preventative biosecurity practices are implemented to reduce these costs. Yet even with the knowledge of the importance of biosecurity, these practices are not employed consistently. The efficacy of biosecurity practices relies on consistent implementation and is influenced by a variety of behavioral factors under the umbrella of human decision-making. Using an experimental game, we collected data to quantify how different messages that described the likelihood of a disease incursion would influence willingness to follow biosecurity practices. Here we show that graphical messages combined with linguistic phrases demarking infection risk levels are more effective for ensuring compliance with biosecurity practices, as contrasted with either simple linguistic phrases or graphical messages with numeric demarcation of risk levels. All three of these delivery methods appear to be more effective than using a simple numeric value to describe probability of infection. Situationally, we saw greater than a 3-fold increase in compliance by shifting message strategy without changing the infection risk, highlighting the importance of situational awareness and context when designing messages.