Biology subjects

Ernest, S. K. M.

Publications and source records attributed to Ernest, S. K. M..

4 recordsLinked to original sources

bioRxiv2018

Developing a modern data workflow for living data

Data management and publication are core components of the research process. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. \"Evolving data\" present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a evolving data workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to: 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow uses two tools from software development, version control and continuous integration, to create a modern data management system that automates the pipeline.

ecology↗

bioRxiv2018

Developing an automated iterative near-term forecasting system for an ecological study

O_LIMost forecasts for the future state of ecological systems are conducted once and never updated or assessed. As a result, many available ecological forecasts are not based on the most up-to-date data, and the scientific progress of ecological forecasting models is slowed by a lack of feedback on how well the forecasts perform.\nC_LIO_LIIterative near-term ecological forecasting involves repeated daily to annual scale forecasts of an ecological system as new data becomes available and regular assessment of the resulting forecasts. We demonstrate how automated iterative near-term forecasting systems for ecology can be constructed by building one to conduct monthly forecasts of rodent abundances at the Portal Project, a long-term study with over 40 years of monthly data. This system automates most aspects of the six stages of converting raw data into new forecasts: data collection, data sharing, data manipulation, modeling and forecasting, archiving, and presentation of the forecasts.\nC_LIO_LIThe forecasting system uses R code for working with data, fitting models, making forecasts, and archiving and presenting these forecasts. The resulting pipeline is automated using continuous integration (a software development tool) to run the entire pipeline once a week. The cyberinfrastructure is designed for long-term maintainability and to allow the easy addition of new models. Constructing this forecasting system required a team with expertise ranging from field site experience to software development.\nC_LIO_LIAutomated near-term iterative forecasting systems will allow the science of ecological forecasting to advance more rapidly and provide the most up-to-date forecasts possible for conservation and management. These forecasting systems will also accelerate basic science by allowing new models of natural systems to be quickly implemented and compared to existing models. Using existing technology, and teams with diverse skill sets, it is possible for ecologists to build automated forecasting systems and use them to advance our understanding of natural systems.\nC_LI

ecology↗

bioRxiv2017

Body Size Shifts Influence Effects Of Increasing Temperatures On Ectotherm Metabolism

INTRODUCTION INTRODUCTION METHODS RESULTS DATA ACCESSIBILITY BIOSKETCH REFERENCES Environmental temperature influences organisms in many ways; temperature increases or decreases rates of physiological processes (Brown et al., 2012), determines timing of reproduction (Olive, 1995), and even directly affects mortality (Pauly, 1980). Because of the far-reaching influence of temperature, projected increases in global temperatures due to climate change are expected to substantially alter diverse species characteristics. Increased temperatures have already been implicated in shifts in species geographic distributions (e.g., Buckley et al., 2010), and in the phenology of species life history and development (e.g., Wolkovich ...

ecology↗

bioRxiv2016

Bees Without Flowers: Before Peak Bloom, Diverse Native Bees Visit Insect-produced Honeydew Sugars

Bee foragers respond to complex visual, olfactory, and extrasensory cues to optimize searches for floral rewards. Their abilities to detect and distinguish floral colors, shapes, volatiles, and ultraviolet signals, and even gauge nectar availability from changes in floral humidity or electric fields are well studied. Bee foraging behaviors in the absence of floral cues, however, are rarely considered. We observed forty-four species of wild bees visiting inconspicuous, non-flowering shrubs during early spring in a protected, Mediterranean habitat. We determined experimentally that these bees were accessing sugary honeydew secretions from scale insects without the aid of standard cues. While honeydew use is known among some social Hymenoptera, its use across a diverse community of mostly solitary bees is a novel observation. The widespread ability of native bees to locate and use unadvertised, non-floral sugars suggests unappreciated sensory mechanisms and/or the existence of a social foraging network among solitary bees that may influence how native bee communities cope with increasing environmental change.

ecology↗