Edmund Hart

The Tao of open science for ecology

The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes “open science.” Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life-cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that ...

Reconstructing Local Population Dynamics in Noisy Metapopulations—The Role of Random Catastrophes and Allee Effects

Reconstructing the dynamics of populations is complicated by the different types of stochasticity experienced by populations, in particular if some forms of stochasticity introduce bias in parameter estimation in addition to error. Identification of systematic biases is critical when determining whether the intrinsic dynamics of populations are stable or unstable and whether or not populations exhibit an Allee effect, i.e., a minimum size below which deterministic extinction should follow. Using a simulation model that allows for Allee effects and a range of intrinsic dynamics, we investigated how three types of stochasticity—demographic, environmental, and random catastrophes— affect our ability to reconstruct the intrinsic dynamics of populations. Demographic stochasticity aside, which is only problematic in small populations, we find that environmental stochasticity—positive and negative environmental fluctuations—caused increased error in parameter estimation, but bias was rarely problematic, except at the highest levels of noise. Random catastrophes, events causing large-scale mortality and likely to be more common than usually recognized, caused immediate bias in parameter estimates, in particular when Allee effects were large. In the latter case, population stability was predicted when endogenous dynamics were actually unstable and the minimum viable population size was overestimated in populations with small or non-existent Allee effects. Catastrophes also generally increased extinction risk, in particular when endogenous Allee effects were large. We propose a method for identifying data points likely resulting from catastrophic events when such events have not been recorded. Using social spider colonies (Anelosimus spp.) as models for populations, we show that after known or suspected catastrophes are accounted for, reconstructed growth parameters are consistent with intrinsic dynamical instability and substantial Allee effects. Our results are applicable to metapopulation or time series data and are relevant for predicting extinction in conservation applications or the management of invasive species.

Testing a ‘genes‐to‐ecosystems’ approach to understanding aquatic–terrestrial linkages

A ‘genes‐to‐ecosystems’ approach has been proposed as a novel avenue for integrating the consequences of intraspecific genetic variation with the underlying genetic architecture of a species to shed light on the relationships among hierarchies of ecological organization (genes → individuals → communities → ecosystems). However, attempts to identify genes with major effect on the structure of communities and/or ecosystem processes have been limited and a comprehensive test of this approach has yet to emerge. Here, we present an interdisciplinary field study that integrated a common garden containing different genotypes of a dominant, riparian tree, Populus trichocarpa, and aquatic mesocosms to determine how intraspecific variation in leaf litter alters both terrestrial and aquatic communities and ecosystem functioning. Moreover, we incorporate data from extensive trait screening and genome‐wide association studies estimating the heritability and genes associated with litter characteristics. We found that tree genotypes varied considerably in the quality and production of leaf litter, which contributed to variation in phytoplankton abundances, as well as nutrient dynamics and light availability in aquatic mesocosms. These ‘after‐life’ effects of litter from different genotypes were comparable to the responses of terrestrial communities associated with the living foliage. We found that multiple litter traits corresponding with aquatic community and ecosystem responses differed in their heritability. Moreover, the underlying genetic architecture of these traits was complex, and many genes contributed only a small proportion to phenotypic variation. Our results provide further evidence that genetic variation is a key component of aquatic–terrestrial linkages, but challenge the ability to predict community or ecosystem responses based on the actions of one or a few genes.

Differential response to frequency-dependent interactions: an experimental test using genotypes of an invasive grass

Positive feedbacks have been suggested as a means for non-indigenous species to successfully invade novel environments. Frequency-dependent feedbacks refer to a species performance being dependent on its local abundance in the population; however, frequency dependence is often described as a monolithic trait of a species rather than examining the variation in response for individual genotypes and fitness traits. Here, we investigate frequency-dependent outcomes for individual genotypes and fitness-related traits for the invasive grass Phalaris arundinacea. We tested for competition-mediated frequency dependence by establishing hexagonal arrays with the center target plant surrounded by either same, different or no genotype neighbors to determine how changing the small-scale frequency neighborhood-influenced invasion success. We used a Bayesian ANOVA approach which allowed us to easily accommodate our non-normal dataset and found that same neighbor plots had greater biomass production than different neighbor plots. Target plants also had greater stem height and aboveground biomass when surrounded by same genotype neighbors. A greenhouse experiment did not support the hypothesis that increased mycorrhizal associations were the cause of positive frequency dependence. We devised a frequency-dependent metric to quantify the extent of fitness-related differences for individual genotypes and found that individual genotypes showed a range of both positive and negative responses to different frequency treatments; however, only positive responses were statistically significant. The small-scale genotypic neighborhood had no effect for the fitness-related traits of leaf number, belowground biomass and total biomass. We demonstrate that individual invasive genotypes respond differently to changing frequency neighborhoods and that growth responses do not respond with the same direction and magnitude. A range of frequency-dependent responses may allow genotypes to invade a wide range of environments.

Ten Simple Rules for Digital Data Storage

Data is the central currency of science, but the nature of scientific data has changed dramatically with the rapid pace of technology. This change has led to the development of a wide variety of data formats, dataset sizes, data complexity, data use cases, and data sharing practices. Improvements in high throughput DNA sequencing, sustained institutional support for large sensor networks, and sky surveys with large-format digital cameras have created massive quantities of data. At the same time, the combination of increasingly diverse research teams and data aggregation in portals (e.g. for biodiversity data, GBIF or iDigBio) necessitates increased coordination among data collectors and institutions. As a consequence, “data” can now mean anything from petabytes of information stored in professionally-maintained databases, through spreadsheets on a single computer, to hand-written tables in lab notebooks on shelves. All remain important, but data curation practices must continue to keep pace with the changes brought about by new forms and practices of data collection and storage.

Climate change triggers morphological and life-history evolution in response to predators

Although climate change is expected to reorganize entire communities, this restructuring might reflect either direct ecological or evolutionary responses to abiotic conditions or indirect effects mediated through altered species interactions. We tested the hypothesis that changes in trophic interaction strength due to altered predator abundance have a cascading evolutionary response in a prey species (Daphnia pulex). Using a multiyear / multigenerational field experiment, we manipulated 12 open aquatic mesocosms to simulate hydrological conditions under climate change. After a three-year press manipulation, we collected Daphnia pulex from each pond and raised them in a common garden. Using quantitative genetic methods, we measured a series of quantitative traits every other day on 108 individuals for eight weeks. There was a significant decrease in tail spine length and population growth rate in groups exposed to the most extreme future climate scenarios. Structural equation models demonstrated that trait changes were best explained as an indirect effect of climate change treatments mediated through changes in predator abundance. Our results suggest climate change can trigger a cascade of ecological and evolutionary forces by reducing predator density, which in turn acts as a selective force leading to evolutionary change in prey morphology and life history.