Meghan L. Avolio

Understanding preferences for tree attributes: the relative effects of socio-economic and local environmental factors.

Urban plant biodiversity is influenced by both the physical environment and attitudes and preferences of urban residents for specific plant types. Urban residents are assumed to be disconnected from their immediate environment, and cultural and societal factors have been emphasized over environmental factors in studies of landscaping choices. However, we postulate that local climatic and environmental factors can also affect preferences for plant attributes. Therefore, spatial and temporal patterns in urban tree biodiversity may be driven not only by the direct effect of environmental variables on plant function, but also by the effect of environmental variables on attitudes toward trees and associated choices about which types of trees to plant. Here, we tested the relative effects of socio-economic and local environmental factors on preferences toward tree attributes in five counties in southern California in and surrounding Los Angeles, based on 1,029 household surveys. We found that local environmental factors have as strong an effect on preferences for tree attributes as socio-economic factors. Specifically, people located in hotter climates (average maximum temperature 25.1 °C) were more likely to value shade trees than those located in cooler regions (23.1 °C). Additionally, people located in desert areas were less likely to consider trees to be important in their city compared with people located in naturally forested areas. Overall, our research demonstrates the inherent connections between local environmental factors and perceptions of nature, even in large modern cities. Accounting for these factors can contribute to the growing interest in understanding patterns of urban biodiversity.

Toward a better integration of biological data from precipitation manipulation experiments into Earth system models

The biological responses to precipitation within the terrestrial components of Earth system models, or land surface models (LSMs), are mechanistically simple and poorly constrained, leaving projections of terrestrial ecosystem functioning and feedbacks to climate change uncertain. A number of field experiments have been conducted or are underway to test how changing precipitation will affect terrestrial ecosystems. Results from these experiments have the potential to vastly improve modeled processes. However, the transformation of experimental results into model improvements still represents a grand challenge. Here we review the current state of precipitation manipulation experiments and the precipitation responses of biological processes in LSMs to explore how these experiments can help improve model realism. First, we discuss contemporary precipitation projections and then review the structure and function of current-generation LSMs. We then examine different experimental designs and discuss basic variables that, if measured, would increase a field experiments usefulness in a modeling context. Next, we compare biological processes commonly measured in the field with their model analogs and find that, in many cases, the way these processes are measured in the field is not compatible with the way they are represented in LSMs, an effect that hinders model development. We then discuss the challenge of scaling from the plot to the globe. Finally, we provide a series of recommendations aimed to improve the connectivity between experiments and LSMs and conclude that studies designed from the perspective of researchers in both communities will provide the greatest benefit to the broader global change community.

Assessing Fine-Scale Genotypic Structure of a Dominant Species in Native Grasslands

Abstract Genotypic diversity of dominant species has been shown to have important consequences for community and ecosystem processes at a fine spatial scale. We examined the fine-scale (i.e., plant neighborhood scale, <1 m2) genotypic structure of Andropogon gerardii, a dominant species in the tallgrass prairie, which is a productive and endangered grassland ecosystem, employing the commonly used amplified fragment length polymorphism (AFLP) technique. In this paper we used two methods to assess the fine-scale genetic spatial structure of a dominant perennial grass, (1) we determined how many tillers to sample in a 1 m2 area and (2) we developed AFLP markers that would differentiate between genotypes. By determining appropriate sampling and molecular techniques, our findings can be applied to questions addressing how genetic diversity of dominant species affect ecosystem processes in the tallgrass prairie.

A framework for quantifying the magnitude and variability of community responses to global change drivers

A major challenge in global change ecology is to predict the trajectory and magnitude of community change in response to global change drivers (GCDs). Here, we present a new framework that not only increases the predictive power of individual studies, but also allows for synthesis across GCD studies and ecosystems. First, we suggest that by quantifying community dissimilarity of replicates both among and within treatments, we can infer both the magnitude and predictability of community change, respectively. Second, we demonstrate the utility of integrating rank abundance curves with measures of community dissimilarity to understand the species-level dynamics driving community changes and propose a series of testable hypotheses linking changes in rank abundance curves with shifts in community dissimilarity. Finally, we review six case studies that demonstrate how our new conceptual framework can be applied. Overall, we present a new framework for holistically predicting community responses to GCDs that has broad applicability in this era of unprecedented global change and novel environmental conditions.

Tree diversity in southern California's urban forest: the interacting roles of social and environmental variables

Socio-economic and environmental drivers are important determinants urban plant richness patterns. The scale at which these patterns are observed in different regions, however, has not been explored. In arid regions, where forests are not native, the majority of the urban forest is planted, and trees are presumably chosen for specific attributes. Here, we investigate the role of spatial scales and the relative importance of environmental versus socio-economic drivers in determining the community structure of southern California’s urban forest. Second, we assess the usefulness of ecosystem service-based traits for understanding patterns of urban biodiversity, compared with species composition data. Third, we test whether resident preferences for specific tree attributes are important for understanding patterns of species composition and diversity. We studied tree communities in 37 neighborhoods in three southern California counties (Los Angeles, Orange, and Riverside). The urban forest in southern California is very diverse with 114 species. Using multiple regression analyses we found socio-economic drivers were generally more important than environmental and the strength of the relationship between urban forest community structure and socio-economic drivers depended on whether we were analyzing within or across counties. There was greater tree richness in wealthier neighborhoods compared with less affluent neighborhoods across all counties and Orange County, but not in Los Angeles or Riverside counties alone. We also found a greater proportion of residential shade trees in hotter neighborhoods than in cooler neighborhoods, which corresponds with survey results of residents’ preferences for tree attributes. Ultimately our study demonstrates that the species richness and functional traits of urban tree communities are influenced by managers’ and residents’ preferences and perceptions of urban tree traits.

Mechanisms of selection: Phenotypic differences among genotypes explain patterns of selection in a dominant species

Predicted changes in precipitation means and variability are expected to alter genotype composition of plant populations; however, it remains unclear whether selection will be for trait differences among genotypes or phenotypic plasticity. This is especially true for more variable precipitation patterns that simultaneously alter soil moisture means and variability. In a previous study we found that a decade of more variable growing-season precipitation patterns changed the genotypic composition of a dominant C4 grass population (Andropogon gerardii) in native tallgrass prairie located in northeastern Kansas. Here, we assessed potential mechanisms underlying the changes observed in population structure of this species by studying how changes in both the size and variability of watering events affected ecophysiological, growth, biomass-allocation, and fitness traits of five common genotypes of A. gerardii in a greenhouse experiment. Three of these genotypes had greater abundances or were only present in fie...

Measuring genetic diversity in ecological studies

There is an increasing interest in how genetic diversity may correlate with and influence community and ecosystem properties. Genetic diversity can be defined in multiple ways, and currently lacking in ecology is a consensus on how to measure genetic diversity. Here, we examine two broad classes of genetic diversity: genotype-based and genome-based measures. Genotype-based measures, such as genotypic richness, are more commonly used in ecological studies, and often it is assumed that as genotypic diversity increases, genomic diversity (the number of genetic polymorphisms and/or genomic dissimilarity among individuals) also increases. However, this assumption is rarely assessed. We tested this assumption by investigating correlations between genotype- and genome-based measures of diversity using two plant population genetic datasets: one observational with data collected at Konza Prairie, KS, and the other based on simulated populations with five levels of genotypic richness, a typical design of genetic diversity experiments. We found conflicting results for both datasets; we found a mismatch between genotypic and genomic diversity measures for the field data, but not the simulated data. Last, we tested the consequences of this mismatch and found that correlations between genetic diversity and community/ecosystem properties depended on metric used. Ultimately, we argue that genome-based measures should be included in future studies alongside genotypic-based measures because they capture a greater spectrum of genetic differences among individuals.

Regulation of genes involved in nitrogen utilization on different C/N ratios and nitrogen sources in the model ectomycorrhizal fungus Hebeloma cylindrosporum

Nitrogen (N) utilization by ectomycorrhizal fungi is an essential aspect of their ecosystem function. N deposition changes both the N pools and the carbon/nitrogen (C/N) ratio of the substrates where ectomycorrhizal fungi are found, and it is important to understand how these changes affect the N forms used by ectomycorrhizal fungi. To overcome the difficulties of studying ectomycorrhizal fungi in situ, we investigated all known N genes in the model fungus, Hebeloma cylindrosporum in a culture study. In addition to studying the regulation of all known N utilization genes, we aimed to understand whether there are gene clusters that undergo similar regulation. Lastly we studied how C/N ratio, N transporter type, and N source affected relative gene expression levels. We grew the D2 strain of H. cylindrosporum on a range of inorganic and organic N sources under low, medium, and high C/N ratios. We found three gene clusters that were regulated in a similar pattern. Lastly, we found C/N ratio, N source and N transporter type all affected gene expression levels. Relative expression levels were highest on the high C/N ratio, BSA and diLeucine N sources, and inorganic N transporters were always expressed at higher levels than organic N transporters. These results suggest that inorganic N sources may always the default preference for H. cylindrosporum, regardless of both the N sources and the C/N ratio of the substrate.

Ecological homogenization of residential macrosystems

Similarities in planning, development and culture within urban areas may lead to the convergence of ecological processes on continental scales. Transdisciplinary, multi-scale research is now needed to understand and predict the impact of human-dominated landscapes on ecosystem structure and function.

Asynchrony among local communities stabilises ecosystem function of metacommunities

Abstract Temporal stability of ecosystem functioning increases the predictability and reliability of ecosystem services, and understanding the drivers of stability across spatial scales is important for land management and policy decisions. We used species‐level abundance data from 62 plant communities across five continents to assess mechanisms of temporal stability across spatial scales. We assessed how asynchrony (i.e. different units responding dissimilarly through time) of species and local communities stabilised metacommunity ecosystem function. Asynchrony of species increased stability of local communities, and asynchrony among local communities enhanced metacommunity stability by a wide range of magnitudes (1–315%); this range was positively correlated with the size of the metacommunity. Additionally, asynchronous responses among local communities were linked with species’ populations fluctuating asynchronously across space, perhaps stemming from physical and/or competitive differences among local communities. Accordingly, we suggest spatial heterogeneity should be a major focus for maintaining the stability of ecosystem services at larger spatial scales.