Approaches for advancing scientific understanding of macrosystems

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

Macrosystems ecology: Understanding ecological patterns and processes at continental scales

Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisciplines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents

Approaches to advance scientific understanding of macrosystems ecology

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological pat- terns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require valida- tion, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

QTLs for Biomass and Developmental Traits in Switchgrass (Panicum virgatum)

Genetic and genomic resources have recently been developed for the bioenergy crop switchgrass (Panicum virgatum). Despite these advances, little research has been focused on identifying genetic loci involved in natural variation of important bioenergy traits, including biomass. Quantitative trait locus (QTL) mapping is typically used to discover loci that contribute to trait variation. Once identified, QTLs can be used to improve agronomically important traits through marker-assisted selection. In this study, we conducted QTL mapping in Austin, TX, USA, with a full-sib mapping population derived from a cross between tetraploid clones of two major switchgrass cultivars (Alamo-A4 and Kanlow-K5). We observed significant among-genotype variation for the vast majority of growth, morphological, and phenological traits measured on the mapping population. Overall, we discovered 27 significant QTLs across 23 traits. QTLs for biomass production colocalized on linkage group 9b across years, as well as with a major biomass QTL discovered in another recent switchgrass QTL study. The experiment was conducted under a rainout shelter, which allowed us to examine the effects of differential irrigation on trait values. We found very minimal effects of the reduced watering treatment on traits, with no significant effect on biomass production. Overall, the results of our study set the stage for future crop improvement through marker-assisted selection breeding