Interrelation Between the Dynamic Capabilities of Knowledge Management, Learning, Adaptation, with Innovation in Medium and Large Companies in an Emerging Economy in Times of Pandemic

The general idea of this article is to analyse the interrelation between the dynamic capabilities of knowledge management, learning, adaptation, with innovation in medium and large companies in an emerging Latin American economy. This is because innovation is a key strategy for dealing with crises such as the one caused by the COVID-19 pandemic. A Likert scale survey of 106 executives from the same number of firms in the pharmaceuticals, information and communication technologies and processed food sectors was applied to obtain data. The general findings show that there is a significant inter-relationship between the different dynamic capabilities of the firms above described. However, when analyzing the interrelationship between the dynamic capability of innovation with the other three capabilities, the strongest interrelationship is with adaptive capability. These findings, positively draw attention, given that a literature review on the subject indicates that in emerging economies the companies developing these capabilities are unusual. These encouraging findings suggest that companies in these economies have the capacity to effectively address the issues posed by the COVID-19 epidemic. © 2023 IMI

Ecological factors influence balancing selection on leaf chemical profiles of a wildflower

Balancing selection is frequently invoked as a mechanism that maintains variation within and across populations. However, there are few examples of balancing selection operating on loci underpinning complex traits, which frequently display high levels of variation. We investigated mechanisms that may maintain variation in a focal polymorphism - leaf chemical profiles of a perennial wildflower (Boechera stricta, Brassicaceae) - explicitly interrogating multiple ecological and genetic processes including spatial variation in selection, antagonistic pleiotropy and frequency-dependent selection. A suite of common garden and greenhouse experiments showed that the alleles underlying variation in chemical profile have contrasting fitness effects across environments, implicating two ecological drivers of selection on chemical profile: herbivory and drought. Phenotype-environment associations and molecular genetic analyses revealed additional evidence of past selection by these drivers. Together, these data are consistent with balancing selection on chemical profile, probably caused by pleiotropic effects of secondary chemical biosynthesis genes on herbivore defence and drought response

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

Timing of activity can reveal an organism’s efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non-migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad-scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds. Methods Data were compiled from previously collected GPS movement datasets. We include days with 8+ h of data, and exclude migrations > 500 km long. For colonial nesting pelagic birds, we compare only days with known foraging trips. Dataset here includes the six temporal variables used in our study, measured at the hourly and daily scale. Usage Notes Mallon et al. 2020. Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales. Journal of Avian Biology The dryad repository contents include the following data: 1. Final dataset used in analysis: mallon2020_trait_data.csv 2. Original hourly data measures of several temporal variables: mallon2020_hr_data.csv 3. Original daily data measures of several temporal variables: mallon2020_day_data.csv 4. Final morphological data used in analysis: mallon2020_morpho_data.csv Data columns of note: active.hr = if individual is active or inactive, based on threshold defined in Mallon et al. 2020 mspeed = mean speed during active hours n.hrs = number of location hours per day dsunrise.min = first activity, relative to sunrise dsunset.max = last activity, relative to sunset midday.speed = hourly speed nearest to solar noon prop.diel = proportion of active hours between sunrise and sunset n.periods.activity = number of movement bouts activity.dur = mean duration of movement bouts r2n = maximum net squared displacement from the beginning of the day (m) mean.r2n = mean net squared displacement from the beginning of the day (m) median.r2n = median net squared displacement from the beginning of the day (m