Fire and grazing in a mesic tallgrass prairie: impacts on plant species and functional traits

Fire is a globally distributed disturbance that impacts terrestrial ecosystems and has been proposed to be a global “herbivore.” Fire, like herbivory, is a top-down driver that converts organic materials into inorganic products, alters community structure, and acts as an evolutionary agent. Though grazing and fire may have some comparable effects in grasslands, they do not have similar impacts on species composition and community structure. However, the concept of fire as a global herbivore implies that fire and herbivory may have similar effects on plant functional traits. Using 22 years of data from a mesic, native tallgrass prairie with a long evolutionary history of fire and grazing, we tested if trait composition between grazed and burned grassland communities would converge, and if the degree of convergence depended on fire frequency. Additionally, we tested if eliminating fire from frequently burned grasslands would result in a state similar to unburned grasslands, and if adding fire into a previously unburned grassland would cause composition to become more similar to that of frequently burned grasslands. We found that grazing and burning once every four years showed the most convergence in traits, suggesting that these communities operate under similar deterministic assembly rules and that fire and herbivory are similar disturbances to grasslands at the trait-group level of organization. Three years after reversal of the fire treatment we found that fire reversal had different effects depending on treatment. The formerly unburned community that was then burned annually became more similar to the annually burned community in trait composition suggesting that function may be rapidly restored if fire is reintroduced. Conversely, after fire was removed from the annually burned community trait composition developed along a unique trajectory indicating hysteresis, or a time lag for structure and function to return following a change in this disturbance regime. We conclude that functional traits and species-based metrics should be considered when determining and evaluating goals for fire management in mesic grassland ecosystems

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

• Leaf dark respiration (Rdark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark and associated leaf traits. • Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in Rdark. • Area-based Rdark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8–28°C). By contrast, Rdark at a standard T (25°C, Rdark25) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher Rdark25 at a given photosynthetic capacity (Vcmax25) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark25 values at any given Vcmax25 or [N] were higher in herbs than in woody plants. • The results highlight variation in Rdark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs)

Ecosystem Functioning in the Real World

Ecosystem functions are components of an ecosystem that change over time. We rely on many of these functions, such as carbon or water cycling, for survival. For over twenty years, ecologists have been vigorously testing the effects of biodiversity loss on ecosystem functioning. These experiments have nearly all been done either in growth chambers or carefully cultivated field communities. As ecologists frequently acknowledge, it remains to be determined how accurately the results of these studies portray the effects of biodiversity on ecosystem functioning in nature. Ecosystem functioning research has also emphasized biodiversity as the key variable, while other community properties and processes have gone largely ignored. I studied carbon cycling in Arctic tundra plants by focusing on the ecophysiology of respiration rates rather than biodiversity. I also conducted a biodiversity and ecosystem functioning experiment using natural, unmanipulated communities. Finally, I used the data from both of these experiments to quantify intraspecific variation in functional traits, a crucial tool in studies of ecosystem functions. I found that respiration rates in the unique constant daylight environment in the Arctic are much higher than would be expected from studies in temperate environments. In the biodiversity and ecosystem functioning experiment, I was unable to find any measurable effect of biodiversity on biomass production, marking a stark contrast from previous results in controlled experiments. I also found extensive intraspecific variation in many common functional traits, highlighting the importance of including these measurements in similar studies.Ph.D

Beyond species: functional diversity and the maintenance of ecological processes and services

Summary 1. The goal of conservation and restoration activities is to maintain biological diversity and the ecosystem services that this diversity provides. These activities traditionally focus on the measures of species diversity that include only information on the presence and abundance of species. Yet how diversity influences ecosystem function depends on the traits and niches filled by species. 2. Biological diversity can be quantified in ways that account for functional and phenotypic differences. A number of such measures of functional diversity (FD) have been created, quantifying the distribution of traits in a community or the relative magnitude of species similarities and differences. We review FD measures and why they are intuitively useful for understanding ecological patterns and are important for management. 3. In order for FD to be meaningful and worth measuring, it must be correlated with ecosystem function, and it should provide information above and beyond what species richness or diversity can explain. We review these two propositions, examining whether the strength of the correlation between FD and species richness varies across differing environmental gradients and whether FD offers greater explanatory power of ecosystem function than species richness. 4. Previous research shows that the relationship between FD and richness is complex and context dependent. Different functional traits can show individual responses to different gradients, meaning that important changes in diversity can occur with minimal change in richness. Further, FD can explain variation in ecosystem function even when richness does not. 5. Synthesis and applications. FD measures those aspects of diversity that potentially affect community assembly and function. Given this explanatory power, FD should be incorporated into conservation and restoration decision-making, especially for those efforts attempting to reconstruct or preserve healthy, functioning ecosystems

Beyond species: functional diversity and the maintenance of ecological processes and services

Summary 1. The goal of conservation and restoration activities is to maintain biological diversity and the ecosystem services that this diversity provides. These activities traditionally focus on the measures of species diversity that include only information on the presence and abundance of species. Yet how diversity influences ecosystem function depends on the traits and niches filled by species. 2. Biological diversity can be quantified in ways that account for functional and phenotypic differences. A number of such measures of functional diversity (FD) have been created, quantifying the distribution of traits in a community or the relative magnitude of species similarities and differences. We review FD measures and why they are intuitively useful for understanding ecological patterns and are important for management. 3. In order for FD to be meaningful and worth measuring, it must be correlated with ecosystem function, and it should provide information above and beyond what species richness or diversity can explain. We review these two propositions, examining whether the strength of the correlation between FD and species richness varies across differing environmental gradients and whether FD offers greater explanatory power of ecosystem function than species richness. 4. Previous research shows that the relationship between FD and richness is complex and context dependent. Different functional traits can show individual responses to different gradients, meaning that important changes in diversity can occur with minimal change in richness. Further, FD can explain variation in ecosystem function even when richness does not. 5. Synthesis and applications. FD measures those aspects of diversity that potentially affect community assembly and function. Given this explanatory power, FD should be incorporated into conservation and restoration decision-making, especially for those efforts attempting to reconstruct or preserve healthy, functioning ecosystems

Appendix A. Supporting information for model comparisons.

Supporting information for model comparisons

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute’s “Brain-CODE” is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care