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Consumer interest in food products, including fresh vegetables, with health promoting properties is rising. In fresh vegetables, these properties include vitamins, minerals, dietary fiber, and secondary compounds, which collectively impart a large portion of the dietary, nutritional or health value associated with vegetable intake. Many, including farmers, aim to increase the health-promoting properties of fresh vegetables on the whole but they face at least three obstacles. First, describing crop composition in terms of its nutrition-based impact on human health is complex and there are few, if any, accepted processes and associated metrics for assessing and managing vegetable composition on-farm, at the origin of supply. Second, data suggest that primary and secondary metabolism can be 'in conflict' when establishing the abundance versus composition of a crop. Third, fresh vegetable farmers are rarely compensated for the phytochemical composition of their product. The development and implementation of a fresh vegetable 'nutritional yield' index could be instrumental in overcoming these obstacles. Nutritional yield is a function of crop biomass and tissue levels of health-related metabolites, including bioavailable antioxidant potential. Data from a multi-factor study of leaf lettuce primary and secondary metabolism and the literature suggest that antioxidant yield is sensitive to genetic and environmental production factors, and that changes in crop production and valuation will be required for fresh vegetable production systems to become more focused and purposeful instruments of public health.

Plants exhibit plasticity in response to their current environment and, in some cases, to that of the previous generation (i.e. maternal effects). However, few studies have evaluated both within- and between-generation plasticities and the extent to which they interact to influence fitness, especially in natural environments. The plasticity of adult traits to two generations of natural differences in light was determined for Campanulastrum americanum, a forest-edge herb that expresses annual and biennial life histories. Plasticity was found to an individual's light environment (within generation) and the maternal light environment (between generations). Responses to ambient light for size traits and timing of flowering were probably passive, whereas apparently adaptive responses were found for light acquisition traits. Maternal light influenced the expression of most adult traits but had the strongest effect when plants were germinated in natural environments. The transgenerational effects of light were consistent with adaptive plasticity for several traits. Plastic within-generation changes in flowering time may also result in adaptive between-generation effects by altering the offspring life history schedule. Finally, the results underscore the importance of conducting studies of within- and between-generation plasticity in natural populations, where the environmental context is relevant to that in which the traits evolved.

The Nigerian government is committed to sustaining rice production to meet national demand. Nevertheless, political tension and climate-induced stressors remain crucial constraints in achieving policy targets. This study examines whether climate change and political instability significantly threaten rice production in Nigeria. First, we employed nonparametric methods to estimate the country's rainfall and temperature trends between 1980Q1 and 2015Q4. Second, we employed the autoregressive distributed lag (ARDL) technique to examine the effects of climate change and political instability on rice production. The results show that while temperature has an increasing pattern, rainfall exhibits no significant trend. The findings from the ARDL estimate reveal that rice production responds negatively to temperature changes but is less sensitive to changes in rainfall. In addition, political instability adversely affects rice production in Nigeria. We argue that Nigeria's slow growth in rice production can be traced back to the impact of climate change and political tension in rice farming areas. As a result, reducing the overall degree of conflict to ensure political stability is critical to boosting the country's self-sufficiency in rice production. We also recommend that farmers be supported and trained to adopt improved rice varieties less prone to extreme climate events while supporting them with irrigation facilities to facilitate rice production.

• Premise of the study: Climate change is associated with phenological shifts in an increasing number of organisms worldwide. However, accurate estimates of these shifts are dependent on long‐term data sets that include phenological observations from before annual average temperatures began to rise.• Methods: We compared the first flowering times of native prairie plants between 2007 and 2010 with historical data recorded by O. A. Stevens from 1910 to 1961. By merging climate variable data from the same time period, it also was possible to correlate first flowering dates with associated climate variables.• Key results: Over the past 100 years, spring temperatures in the Red River Valley near Fargo, North Dakota, USA, have increased, and growing seasons have lengthened significantly. Seventy‐five percent of the 178 species observed by Stevens had flowering times that were sensitive to at least one variable related to temperature or precipitation. Over the past 4 yr, 5% to 17% of the species observed have significantly shifted their first flowering time either earlier or later relative to the previous century.• Conclusions: The results of this study indicate that as spring temperatures in the northern Great Plains have increased and the growing season has lengthened, some spring flowering species have advanced their first flowering time, some fall species have delayed their first flowering, and some species have not changed. Given the importance of flowering timing for reproductive success, the changing climate in the Great Plains is expected to have long‐term ecological and evolutionary consequences for native plant species.

Abstract Industrial hemp, (Cannabis sativa L.), one of the earliest crops spun for fiber, is now used for a variety of commercial products including paper, textiles, clothing, biodegradable plastics, biofuel, food, animal feed etc., all of which are derived from hemp fiber or seeds. Being wind pollinated, dioecious and staminate hemp plants produce large amounts of pollen that are attractive to bees. Hemp flowering in northern Colorado, where this study was conducted, occurs between the end of July and the end of September. This time period coincides with a dearth of pollinator-friendly crop plants in the region, making hemp flowers a potentially valuable source of pollen for foraging bees. Here we present the diversity and abundance of bees collected in the fields of flowering hemp. A total of 23 different genera of bees were collected of which the European honeybee, Apis mellifera at 38% of the total abundance was the most dominant followed by Melissodes bimaculata at 25% and Peponapis pruinosa at 16%. These three genera made up nearly 80% of the total abundance. While hemp does not produce any nectar, the pollen rich nature of the flowers can make hemp an ecologically valuable crop. As cultivation of hemp continues to expand, we expect insect pests on hemp to also become prevalent. Our results documenting bee diversity in flowering hemp provides the impetus for the development of integrated pest management plans that protect pollinators while controlling pests.

This study highlights how Chinese economic development detrimentally impacted water quality in recent decades and how this has been improved by enormous investment in environmental remediation funded by the Chinese government. To our knowledge, this study is the first to describe the variability of surface water quality in inland waters in China, the affecting drivers behind the changes, and how the government-financed conservation actions have impacted water quality. Water quality was found to be poorest in the North and the Northeast China Plain where there is greater coverage of developed land (cities + cropland), a higher gross domestic product (GDP), and higher population density. There are significant positive relationships between the concentration of the annual mean chemical oxygen demand (COD) and the percentage of developed land use (cities + cropland), GDP, and population density in the individual watersheds (p < 0.001). During the past decade, following Chinese government-financed investments in environmental restoration and reforestation, the water quality of Chinese inland waters has improved markedly, which is particularly evident from the significant and exponentially decreasing GDP-normalized COD and ammonium (NH4+-N) concentrations. It is evident that the increasing GDP in China over the past decade did not occur at the continued expense of its inland water ecosystems. This offers hope for the future, also for other industrializing countries, that with appropriate environmental investments a high GDP can be reached and maintained, while simultaneously preserving inland aquatic ecosystems, particularly through management of sewage discharge.

As climate change moves insect systems into uncharted territory, more knowledge about insect dynamics and the factors that drive them could enable us to better manage and conserve insect communities. Climate change may also require us to revisit insect management goals and strategies and lead to a new kind of scientific engagement in management decision-making. Here we make five key points about the role of insect science in aiding and crafting management decisions, and we illustrate those points with the monarch butterfly and the Karner blue butterfly, two species undergoing considerable change and facing new management dilemmas. Insect biology has a strong history of engagement in applied problems, and as the impacts of climate change increase, a reimagined ethic of entomology in service of broader society may emerge. We hope to motivate insect biologists to contribute time and effort toward solving the challenges of climate change.

AbstractThe change in the phenology of plants or animals reflects the response of living systems to climate change. Numerous studies have reported a consistent earlier spring phenophases in many parts of middle and high latitudes reflecting increasing temperatures with the exception of China. A systematic analysis of Chinese phenological response could complement the assessment of climate change impact for the whole Northern Hemisphere. Here, we analyze 1263 phenological time series (1960–2011, with 20+ years data) of 112 species extracted from 48 studies across 145 sites in China. Taxonomic groups include trees, shrubs, herbs, birds, amphibians and insects. Results demonstrate that 90.8% of the spring/summer phenophases time series show earlier trends and 69.0% of the autumn phenophases records show later trends. For spring/summer phenophases, the mean advance across all the taxonomic groups was 2.75 days decade−1 ranging between 2.11 and 6.11 days decade−1 for insects and amphibians, respectively. Herbs and amphibians show significantly stronger advancement than trees, shrubs and insect. The response of phenophases of different taxonomic groups in autumn is more complex: trees, shrubs, herbs and insects show a delay between 1.93 and 4.84 days decade−1, while other groups reveal an advancement ranging from 1.10 to 2.11 days decade−1. For woody plants (including trees and shrubs), the stronger shifts toward earlier spring/summer were detected from the data series starting from more recent decades (1980s–2000s). The geographic factors (latitude, longitude and altitude) could only explain 9% and 3% of the overall variance in spring/summer and autumn phenological trends, respectively. The rate of change in spring/summer phenophase of woody plants (1960s–2000s) generally matches measured local warming across 49 sites in China (R = −0.33, P < 0.05).

The interaction of severe weather, overhead lines and surrounding trees is the leading cause of outages to electric distribution networks in forested areas. In this paper, we show how utility-specific infrastructure and land cover data, aggregated around overhead lines, can improve outage predictions for Eversource Energy (formerly Connecticut Light and Power), the largest electric utility in Connecticut. Eighty-nine storms from different seasons (cold weather, warm weather, transition months) in the period 2005–2014, representing varying types (thunderstorms, blizzards, nor’easters, hurricanes) and outage severity, were simulated using the Weather Research and Forecasting (WRF) atmospheric model. WRF simulations were joined with utility outage data to calibrate four types of models: a decision tree (DT), random forest (RF), boosted gradient tree (BT) and an ensemble (ENS) decision tree regression that combined predictions from DT, RF and BT. The study shows that the ENS model forced with weather, infrastructure and land cover data was superior to the other models we evaluated, especially in terms of predicting the spatial distribution of outages. This framework could be used for predicting outages to other types of critical infrastructure networks with benefits for emergency-preparedness functions in terms of equipment staging and resource allocation.