Properly designed biofuel feedstock systems can be considerably more sustainable than their grain-based counterparts, avoiding competition with food production and potentially delivering ecosystem services not currently provided by existing systems. Realizing this potential is not necessarily straightforward, however. Feedstocks grown on "marginal" lands (i.e., land that is less fertile and more water stressed and prone to erosion) will be exposed to multiple stressors simultaneously. To achieve reliable and sustainably high yields, bioenergy feedstocks must have the capacity to adapt and maintain productivity even in such challenging environments. In particular, feedstocks need an enhanced capacity to use water and nutrients efficiently, acquire nitrogen and phosphorus from nutrient-depleted soils, and withstand pests and disease. These components interact in ways that cannot always be predicted from individual factors, yet it is the net effect of all interactions that lends sustainability attributes. Providing climate mitigation and improved air, soil, and water quality requires knowledge of all the organisms and environmental factors that contribute to the sustainability of highly productive ecosystems.
Recent advances in the systems biology of both plants and microbes have the potential to contribute significantly to the understanding of these interacting pieces and therefore to the design of sustainable biofuel systems. Linking these advances to those in ecosystem science provides an unprecedented opportunity to substantially advance both the fundamental knowledge of systems biology in general and the more specific ability to design sustainable biofuel systems.
Plant productivity, defined as plants' ability to fix carbon dioxide into biomass, is an essential characteristic of sustainable biofuel systems. In most agricultural ecosystems, plant productivity is limited by a deficiency in resources such as light, water, and nutrients. In particular, plant traits enabling the efficient use of water, nitrogen, and phosphorus are likely to become increasingly important as climate change brings about shifting and potentially volatile precipitation and temperature patterns. Resource-efficient, sustainable agroecosystems are capable of converting valuable inputs such as water and nutrients into valuable outputs with minimal waste.
To sustainably produce biofuel crops for marginal areas, new breeding strategies are needed for maximizing biomass yields under low-input conditions. In addition to the substantial genetic variation that exists within and between plant species for resource use efficiency traits, a growing body of evidence indicates that the microbial consortia within and surrounding plant roots have a significant influence on the acquisition and utilization of these valuable resources. Genomics approaches can be used to harness these attributes for developing more resource efficient crops by providing a basis for trait-based selection of superior genotypes for breeding programs, particularly in perennial grasses and trees that have substantially longer breeding cycles. Advances in DNA sequencing technology will facilitate development of novel strategies such as genome-wide association studies (GWAS) to accelerate breeding of superior genotypes.
Microorganisms have a dramatic impact on plant biology, playing a critical role in overall plant fitness, including nitrogen fixation and the scavenging of phosphorus and other critical nutrients from soil. Rather than studying plants as isolated entities, investigating their breeding and agronomic management as part of an integral association with the surrounding microbiota will benefit both the sustainable productivity of bioenergy crops and the ecosystem services associated with large-scale bioenergy cropping systems. This research effort will require an understanding of the genomic and molecular interactions in feedstock plants' immediate microbiome, as well as the biogeochemical processes mediated by microbial communities in surrounding agricultural soils. With the advent of high-throughput sequencing, the feasibility of relating co-occurrence of feedstock cultivars and associated microbiota enables the identification of species and genotype specificity between plant and microbe and reveals the molecular underpinnings of biotic interactions and the community. Enhancing understanding of the genetic rules governing community composition and development could facilitate selection of optimal genotypes for long-term deployment in managed settings.
Bioenergy ecosystems capture and sequester carbon, mitigate greenhouse gas fluxes, regulate water and nutrient flows to aquatic and other parts of the landscape, and provide habitat for organisms that benefit both crop and natural communities. All these attributes and processes will be affected by the establishment of biofuel crops on lands that now host ecosystems with different plant communities and that are managed with different levels of intensity. This change will result in the delivery of a different set of ecosystem services than before conversion. The net contribution of biofuel crops to environmental sustainability depends on many interacting factors, almost all of which are influenced by how the crop and its associated microbiome interact. These interactions will differ by crop, location, and management; therefore, a fundamental understanding of their effects at the ecosystem scale is necessary to enable predictions of aggregate effects at landscape and regional scales.
Predicting the impact of different bioenergy cropping systems on belowground carbon capture and stabilization, as well as on biogenic production of greenhouse gases, will require an improved understanding of both complex plant-soil-environment interactions at multiple scales and microbial sources of greenhouse gases, including genomic and environmental factors that regulate these phenomena. Subtle variations in plant traits such as root architecture and chemistry, exudation rates, and mycorrhizal associations have the potential to affect these processes. Research is needed to better understand the mechanisms and processes controlling the types and rates of carbon inputs to and outputs from the belowground systems of bioenergy crops; research also must account for variable effects associated with different bioenergy crops, soil types, edaphic conditions, management practices, and climatic regions.
The biological processes underpinning sustainable agricultural systems are inherently complex and have important emergent properties across spatial and temporal scales. Multiscale modeling, which integrates mechanistic models describing system performance at discrete biological scales to evaluate whole system behavior, is an irreplaceable tool for understanding the behavior of complex biological systems and for enabling evaluation of system behavior in a range of contexts, including future climate and management scenarios.
The growing availability of large datasets at both genomic and ecosystem scales and the increasing accessibility and power of computational resources present unprecedented opportunities to develop mechanistic multiscale models that integrate system behavior from genomes to landscapes and subsurface to troposphere. However, developing meaningful models requires more mechanistic information about plant and microbial biology—the organisms, populations, communities, and interactions among and between organisms. This is especially true of the root-rhizosphere phenome, which is key to plant soil interactions, resource efficiency, and thus the sustainability of biofuel agroecosystems.
Emerging research challenges and opportunities in sustainability that can be addressed through the Genomic Science program include:
Gaining a fundamental understanding of the molecular and physiological plant processes underlying plant resilience and adaptation to change, as well as the plant-microbe interactions that influence these traits, will enable better optimization of bioenergy crops to marginal landscapes and better predictions of bioenergy crop production across agricultural regions.