Biology subjects

Ernest, S. K. M.

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

10 recordsLinked to original sources

bioRxiv2023

Transferability of ecological forecasting models to novel biotic conditions in a long-term experimental study

Ecological forecasting models play an increasingly important role for managing natural resources and assessing our fundamental knowledge of processes driving ecological dynamics. As global environmental change pushes ecosystems beyond their historical conditions, the utility of these models may depend on their transferability to novel conditions. Because species interactions can alter resource use, timing of reproduction, and other aspects of a species realized niche, changes in biotic conditions, which can arise from community reorganization events in response to environmental change, have the potential to impact model transferability. Using a long-term experiment on desert rodents, we assessed model transferability under novel biotic conditions to better understand the limitations of ecological forecasting. We show that ecological forecasts can be less accurate when the models generating them are transferred to novel biotic conditions, and that the extent of model transferability can depend on the species being forecast. We also demonstrate the importance of incorporating uncertainty in forecast evaluation with transferred models generating less accurate and more uncertain forecasts. These results suggest that how a species perceives its competitive landscape can influence model transferability, and that when uncertainties are properly accounted for, transferred models may still be appropriate for decision making. Assessing the extent of the transferability of forecasting models is a crucial step to increase our understanding of the limitations of ecological forecasts. Open Research StatementData (10.5281/zenodo.8436468) and code (10.5281/zenodo.11053744) used to conduct data analyses are archived in Zenodo and supplementary results (10.6084/m9.figshare.25733691.v1) in Figshare.

ecology↗

bioRxiv2022

Temporal changes in the individual size distribution decouple long-term trends in abundance, biomass, and energy use of North American breeding bird communities

AimA core objective of contemporary biodiversity science is to understand long-term trends in the structure and function of ecological communities. Different currencies of ecological function - specifically, total abundance, total standing biomass, and total metabolic flux - are naturally linked, but may become decoupled if the underlying size structure of a system changes. Here, we seek to establish how changes in community size composition modulate long-term relationships between different currencies of ecological function for North American birds. LocationNorth America, north of Mexico. Time period1988-2018. Major taxa studiedBreeding birds. MethodsWe used species traits and allometric scaling to estimate individual size measurements and basal metabolic rate for birds observed in the North American Breeding Bird Survey. We compared the long-term trajectories for community-wide standing biomass and energy use to the long-term trends driven by changes in individual abundance alone. Finally, we used dissimilarity metrics to evaluate the link between changes in species and size composition and changes in the relationship between abundance- and size-driven dynamics. ResultsFor a substantial minority of communities, shifts in community size composition have decoupled the long-term dynamics of biomass, energy use, and individual abundance. While trends in abundance were dominated by decreases, trends in biomass were evenly divided between decreases and increases, and trends in energy use featured more increases than expected given changes in abundance alone. Communities with decoupled dynamics showed greater increases in community-wide mean body size than other communities, but did not differ from other communities in overall turnover in species or size composition. Main conclusionsSize- and abundance-based currencies of ecological function are linked, but not necessarily equivalent. For North American breeding birds, shifts in species composition favoring larger-bodied species may have partially offset declines in standing biomass driven by losses of individuals over the past 30 years.

ecology↗

bioRxiv2021

Maintenance of community function through compensation breaks down over time in a desert rodent community

Understanding the ecological processes that maintain community function in systems experiencing species loss, and how these processes change over time, is key to understanding the relationship between community structure and function and predicting how communities may respond to perturbations in the Anthropocene. Using a 30-year experiment on desert rodents, we show that the impact of species loss on community-level energy use has changed repeatedly and dramatically over time, due to 1) the addition of new species to the community, and 2) a reduction in functional redundancy among the same set of species. Although strong compensation, initially driven by the dispersal of functionally redundant species to the local community, occurred in this system from 1997-2010, since 2010, compensation has broken down due to decreasing functional overlap within the same set of species. Simultaneously, long-term changes in sitewide community composition due to niche complementarity have decoupled the dynamics of compensation from the overall impact of species loss on community-level energy use. Shifting, context-dependent compensatory dynamics, such as those demonstrated here, highlight the importance of explicitly long-term, metacommunity, and eco-evolutionary perspectives on the link between species-level fluctuations and community function in a changing world.

ecology↗

bioRxiv2021

A general deep learning model for bird detection in high resolution airborne imagery

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it needs large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increase these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.

ecology↗

bioRxiv2021

Empirical abundance distributions are more uneven than expected given their statistical baseline

Exploring and accounting for the emergent properties of ecosystems as complex systems is a promising horizon in the search for general processes to explain common ecological patterns. For example, the ubiquitous hollow-curve form of the species abundance distribution is frequently assumed to reflect ecological processes structuring communities, but can also emerge as a statistical phenomenon from the mathematical definition of an abundance distribution. Although the hollow curve may be a statistical artefact, ecological processes may induce subtle deviations between empirical species abundance distributions and their statistically most probable forms. These deviations may reflect biological processes operating on top of mathematical constraints and provide new avenues for advancing ecological theory. Examining [~]22,000 communities, we found that empirical SADs are highly uneven and dominated by rare species compared to their statistical baselines. Efforts to detect deviations may be less informative in small communities - those with few species or individuals - because these communities have poorly-resolved statistical baselines. The uneven nature of many empirical SADs demonstrates a path forward for leveraging complexity to understand ecological processes governing the distribution of abundance, while the issues posed by small communities illustrate the limitations of using this approach to study ecological patterns in small samples.

ecology↗

bioRxiv2019

Macroevolution of dimensionless life history metrics in tetrapods

Life history traits represent organisms strategies to navigate the fitness trade-offs between survival and reproduction. Eric Charnov developed three dimensionless metrics to quantify fundamental life history trade-offs. Lifetime reproductive effort (LRE), relative reproductive lifespan (RRL), and relative offspring size (ROS), together with body mass, can be used classify life history strategies across the four major classes of tetrapods: amphibians, reptiles, mammals, and birds. First, we investigate how the metrics have evolved in concert with body mass. In most cases, we find evidence for correlated evolution between body mass and the three metrics. Finally, we compare life history strategies across the four classes of tetrapods and find that LRE, RRL, and ROS delineate a space in which the major tetrapod clades occupy mostly unique subspaces. These distinct combinations of life history strategies provide us with a framework to understand the impact of major evolutionary transitions in energetics, physiology, and ecology.

evolutionary biology↗

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↗