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The developmental and behavioral effects of prenatal exposure to cocaine and/or ethanol were examined in rats. Pregnant rats received ethanol (E; 2 g/kg, b.i.d.) orally, cocaine (C; 6 mg/kg/day, IV), or both (C/E) on gestational days 8-20. Controls consisted of pair-fed (PF) and untreated (UNT) groups. Offspring were weighed and examined for developmental markers beginning postnatal day one (PD1). On PD21 pups were individually observed in an open-field following either an injection of cocaine (10 mg/kg, IP), an injection of saline, or no treatment. Drug-treated and PF dams ate less food and gained less weight than the UNT dams. C and E litters had slightly increased mortality rates. Pups from both the C and E groups appeared less sensitive to the locomotor stimulant effect of cocaine. Pups from the E group engaged in significantly less spontaneous stereotypic locomotion than UNT and PF pups, while male pups from the C group exhibited a decrease in spontaneous exploratory behavior. Thus, prenatal exposure to C or E altered spontaneous and/or cocaine-induced behavior in weanling-aged rats, while the C/E combination did not augment either effect.

It is increasingly acknowledged that climate change is influencing terrestrial ecosystems by increased drought and rainfall intensities. Soil microbes are key drivers of many processes in terrestrial systems and rely on water in soil pores to fulfill their life cycles and functions. However, little is known on how drought and rainfall fluctuations, which affect the composition and structure of microbial communities, persist once original moisture conditions have been restored. Here, we study how simulated short-term drying and re-wetting events shape the community composition of soil fungi and prokaryotes. In a mesocosm experiment, soil was exposed to an extreme drought, then re-wetted to optimal moisture (50% WHC, water holding capacity) or to saturation level (100% WHC). Composition, community structure and diversity of microbes were measured by sequencing ITS and 16S rRNA gene amplicons 3 weeks after original moisture content had been restored. Drying and extreme re-wetting decreased richness of microbial communities, but not evenness. Abundance changes were observed in only 8% of prokaryote OTUs, and 25% of fungal OTUs, whereas all other OTUs did not differ between drying and re-wetting treatments. Two specific legacy response groups (LRGs) were observed for both prokaryotes and fungi. OTUs belonging to the first LRG decreased in relative abundance in soil with a history of drought, whereas OTUs that increased in soil with a history of drought formed a second LRG. These microbial responses were spread among different phyla. Drought appeared to be more important for the microbial community composition than the following extreme re-wetting. 16S profiles were correlated with both inorganic N concentration and basal respiration and ITS profiles correlated with fungal biomass. We conclude that a drying and/or an extreme re-wetting history can persist in soil microbial communities via specific response groups composed of members with broad phylogenetic origins, with possible functional consequences on soil processes and plant species. As a large fraction of OTUs responding to drying and re-wetting belonged to the rare biosphere, our results suggest that low abundant microbial species are potentially important for ecosystem responses to extreme weather events.

Abstract The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N−) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

The agriculture and horticulture sector in the Netherlands is one of the most productive in the world. Although the sector is one of the most advanced and intense agricultural production systems worldwide, it faces challenges, such as climate change and environmental and social unsustainability of industrial production. To overcome these challenges, alternative food production initiatives have emerged, especially in large cities such as Amsterdam. Some initiatives involve producing food in the urban environment, supported by new technologies and practices, so-called high-tech urban agriculture (HTUA). These initiatives make cultivation of plants inside and on top of buildings possible and increase green spaces in urban areas. The emerging agricultural technologies are creating new business environments that are shape d by technology developers (e.g., suppliers of horticultural light emitting diodes (LED) and control environment systems) and developers of alternative food production practices (e.g., HTUA start-ups). However, research shows that the uptake of these technological innovations in urban planning processes is problematic. Therefore, this research analyzes the barriers that local government planners and HTUA developers are facing in the embedding of HTUA in urban planning processes, using the city of Amsterdam as a case study. This study draws on actor-network theory (ANT) to analyze the interactions between planners, technologies, technology developers and developers of alternative food production practices. Several concepts of ANT are integrated into a multi-level perspective on sustainability transitions (MLP) to create a new theoretical framework that can explain how interactions between technologies and planning actors transform the incumbent social–technical regime. The configuration of interactions between social and material entities in technology development and adoption processes in Amsterdam is analyzed through the lens of this theoretical framework. The data in this study were gathered by tracing actors and their connections by using ethnographic research methods. In the course of the integration of new technologies into urban planning practices, gaps between technologies, technology developers, and planning actors have been identified. The results of this study show a lacking connection between planning actors and technology developers, although planning actors do interact with developers of alternative food production practices. These interactions are influenced by agency of artefacts such as visualizations of the future projects. The paper concludes that for the utilization of emerging technologies for sustainability transition of cities, the existing gap between technology developers and planning actors needs to be bridged through the integration of technology development visions in urban agendas and planning processes.

• 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.

AbstractThe adoption of a bioenergy crop is affected by various factors, including but not limited to the characteristics of farmers, farm economics, market forces, and physical environment. This study develops a spatially explicit agent‐based model for ascertaining the adoption rate of carinata (Brassica carinata) among the farmers in the Little River Experimental Watershed located in the southern state of Georgia in the United States. Each farmer's adoption behavior is modeled using the profitability difference between traditional crop rotations (with and without carinata at different contract prices), the adoption rate of neighboring farmers, and their land allocation decisions from managing a risky portfolio of enterprises. Carinata production in the winter season once every 3 years has no conflict with the most profitable and popular traditional row crop rotations, such as cotton‐cotton‐cotton and cotton‐cotton‐peanut, to a larger extent. The results show that 28% and 85% of farmers in the watershed will adopt carinata after 33 years at a contract price of $13/bushel (bu) under two different assumptions of low (2.5%) and high (5%) initial neighborhood adoption rates. The proportions of land allocated to carinata to the total farmland under field crops are 38% and 85% after 33 years under the same low and high neighborhood adoption rates, respectively. Our results suggest that fixing the appropriate contract price of carinata will bring additional profits to farmers without any significant foreseeable agronomic risks, thereby increasing the adoption rate of carinata at a regional level.