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Introducing perennial biomass crops into agricultural landscapes to address water quality challenges and provide other environmental services: Integrating perennial bioenergy crops into agricultural landscapes
The world is faced with a difficult multiple challenge of meeting nutritional, energy, and other basic needs, under a limited land and water budget, of between 9 and 10 billion people in the next three decades, mitigating impacts of climate change, and making agricultural production resilient. More productivity is expected from agricultural lands, but intensification of production could further impact the integrity of our finite surface water and groundwater resources. Integrating perennial bioenergy crops in agricultural lands could provide biomass for biofuel and potential improvements on the sustainability of commodity crop production. This article provides an overview of ways in which research has shown that perennial bioenergy grasses and short rotation woody crops can be incorporated into agricultural production systems with reduced indirect land use change, while increasing water quality benefits. Current challenges and opportunities as well as future directions are also highlighted.
Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China
Here, we discuss that rice is one of the main crops grown in southern China. Global climate change has significantly altered the local water availability and temperature regime for rice production. In this study, we explored the influence of climate change on suitable rice cropping areas, rice cropping systems and crop water requirements (CWRs) during the growing season for historical (from 1951 to 2010) and future (from 2011 to 2100) time periods. The results indicated that the land areas suitable for rice cropping systems shifted northward and westward from 1951 to 2100 but with different amplitudes.
Large Area Crop Inventory Experiment (LACIE). An overview of the Large Area Crop Inventory Experiment and the outlook for a satellite crop inventory
The author has identified the following significant results. The most important LACIE finding was that the technology worked very well in estimating wheat production in important geographic locations. Based on working through the many successes and shortcomings of LACIE, it can be stated with confidence that: (1) the current technology can successfully monitor what production in regions having similar characteristics to those of the U.S.S.R. wheat areas and the U.S. hard red winter wheat areas; (2) with additional applied research, significant improvements in capabilities to monitor wheat in these and other important production regions can be expected in the near future; (3) the remote sensing and weather effects modeling technology approached used by LACIE is generally applicable to other major crops and crop-producing regions of the world; and (4) with suitable effort, this technology can now advance rapidly and could be widespread use in the late 1980's.
Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States
Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.
Small soil C cycle responses to three years of cover crops in maize cropping systems
Cover crops are touted for their ability to improve many ecosystem functions in annual cropping systems. In addition to water and nutrient retention, cover crops may influence C cycling by increasing total C inputs to the agroecosystem, stimulating microbial populations, altering main crop residue decomposition rate, or changing litter chemistry over time. We assessed whether annual (rye) or perennial (bluegrass) cover crops in maize cropping systems influenced maize residue decomposition (litterbags) or microbial communities (shotgun metagenomics) in soil and litter, and whether these cover crops had an effect on microbially active pools of C: particulate organic matter (POM) C and N, or potentially mineralizable C (PMC) after three years of cover crops. Neither cover crop affected litterbag decay rates or microbial composition relative to no cover crop controls. However, both cover crop types increased PMC indicating that microbially-available C was boosted by cover crops. Total POM and POM-N were higher with bluegrass cover crops. These modest effects of cover crops on dynamic soil C pools suggest the generally positive long-term effects of cover crops on soil protection and nutrient retention are related to incremental shifts in quantity, timing and quality of C inputs.
Identifying representative crop rotation patterns and grassland loss in the US Western Corn Belt
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A meta-analysis of global cropland soil carbon changes due to cover cropping
Including cover crops within agricultural rotations may increase soil organic carbon (SOC). However, contradictory findings generated by on-site experiments make it necessary to perform a comprehensive assessment of interactions between cover crops, environmental and management factors, and changes in SOC. In this study, we collected data from studies that compared agricultural production with and without cover crops, and then analyzed those data using meta-analysis and regression. Our results showed that including cover crops into rotations significantly increased SOC, with an overall mean change of 15.5% (95% confidence interval of 13.8% to 17.3%). Whereas medium-textured soils had highest SOC stocks with (mean = 39 Mg ha-1) and without (mean = 37 Mg ha-1) cover crops, fine-textured soils showed the greatest increase in SOC after the inclusion of cover crops (mean change of 39.5%). Coarse-textured (11.4%) and medium-textured soils (10.3%) had comparatively smaller changes in SOC. Cover crop mixtures resulted in greater increases in SOC compared to mono-species cover crops, and using legumes resulted in greater SOC increases than grasses and broadleaf species. Cover cropping was associated with significant SOC increases in shallow soils (= 30 cm), but not in subsurface soils (> 30 cm). The regression analysis revealed that SOC changes from cover cropping were correlated with improvements in soil quality, specifically decreased runoff and erosion and increased mineralizable carbon, mineralizable nitrogen, and soil nitrogen. Soil carbon change was also affected by annual temperature, number of years after start of cover crop usage, latitude, and initial SOC concentrations. Finally, the mean rate of carbon sequestration from cover cropping across all studies was 0.56 Mg ha-1 yr-1. If 15% of current global cropland were to adopt cover crops, this value would translate to 0.17 Pg of carbon sequestered per year or ~1-2% of current fossil fuels emissions. Altogether, these results indicated that inclusion of cover crops into agricultural rotations can enhance soil carbon concentrations, improve many soil quality parameters, and serve as a potential sink for atmosphere CO2.
Bioenergy crop models: Descriptions, data requirements and future challenges
Field studies that address the production of lignocellulosic biomass as a potential source of renewable energy are making available critical information for the development, validation, and use of bioenergy crop models. A literature survey revealed that 14 models have been developed and validated for herbaceous and woody bioenergy crops, and for Crassulacean acid metabolism (CAM) crops adapted to arid lands. These models simulate field-scale production of biomass for switchgrass (ALMANAC, EPIC, and Agro-BGC), miscanthus (MISCANFOR, MISCANMOD, and WIMOVAC), sugarcane (APSIM, AUSCANE, and CANEGRO), and poplar and willow (SECRETS and 3PG). Two models are adaptations of dynamic global vegetation models and simulate biomass yields of miscanthus and sugarcane as plant function types at regional scales (Agro-IBIS and LPJmL). A model of biomass production in CAM plants has been developed (EPI), but lacks the sophistication of the other models. Except for CAM plants, all the models include representations of leaf area dynamics, radiation interception and utilization, biomass production, and partitioning of biomass to roots and shoots. A few of the models are capable of simulating soil water, nutrient, and carbon cycle processes, making them especially useful for assessing environmental consequences (e.g., erosion and nutrient losses) associated with the field-scale deployment of bioenergy crops. Similar to other process-based models, simulations are challenged by computing and data management issues and an integrated framework for model testing and inter-comparison is needed. Considerable work remains concerning the development of models for unconventional bioenergy crops like CAM plants, generation and distribution of high-quality field data for model development and validation, and development of an integrated framework for efficient execution of large-scale simulations for use in planning regional to global sustainable bioenergy production systems.
Atmospheric inversion of surface carbon flux with consideration of the spatial distribution of US crop production and consumption
In order to improve quantification of the spatial distribution of carbon sinks and sources in the conterminous US, we conduct a nested global atmospheric inversion with detailed spatial information on crop production and consumption. County-level cropland net primary productivity, harvested biomass, soil carbon change, and human and livestock consumption data over the conterminous US are used for this purpose. Time-dependent Bayesian synthesis inversions are conducted based on CO₂ observations at 210 stations to infer CO₂ fluxes globally at monthly time steps with a nested focus on 30 regions in North America. Prior land surface carbon fluxes are first generated using a biospheric model, and the inversions are constrained using prior fluxes with and without adjustments for crop production and consumption over the 2002–2007 period. After these adjustments, the inverted regional carbon sink in the US Midwest increases from 0.25 ± 0.03 to 0.42 ± 0.13 Pg C yr⁻¹, whereas the large sink in the US southeast forest region is weakened from 0.41 ± 0.12 to 0.29 ± 0.12 Pg C yr⁻¹. These adjustments also reduce the inverted sink in the west region from 0.066 ± 0.04 to 0.040 ± 0.02 Pg C yr⁻¹ because of high crop consumption and respiration by humans and livestock. The general pattern of sink increases in crop production areas and sink decreases (or source increases) in crop consumption areas highlights the importance of considering the lateral carbon transfer in crop products in atmospheric inverse modeling, which provides a reliable atmospheric perspective of the overall carbon balance at the continental scale but is unreliable for separating fluxes from different ecosystems.
Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios
Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.
Cover crop root contributions to soil carbon in a no‐till corn bioenergy cropping system
Abstract Crop residues are potential biofuel feedstocks, but residue removal may reduce soil carbon (C). The inclusion of a cover crop in a corn bioenergy system could provide additional biomass, mitigating the negative effects of residue removal by adding to stable soil C pools. In a no‐till continuous corn bioenergy system in the northern US Corn Belt, we used 13 CO 2 pulse labeling to trace plant C from a winter rye ( Secale cereale ) cover crop into different soil C pools for 2 years following rye cover crop termination. Corn stover left as residue (30% of total stover) contributed 66, corn roots 57, rye shoots 61, rye roots 50, and rye rhizodeposits 25 g C m −2 to soil. Five months following cover crop termination, belowground cover crop inputs were three times more likely to remain in soil C pools than were aboveground inputs, and much of the root‐derived C was in mineral‐associated soil fractions. After 2 years, both above‐ and belowground inputs had declined substantially, indicating that the majority of both root and shoot inputs are eventually mineralized. Our results underscore the importance of cover crop roots vs. shoots and the importance of cover crop rhizodeposition (33% of total belowground cover crop C inputs) as a source of soil C. However, the eventual loss of most cover crop C from these soils indicates that cover crops will likely need to be included every year in rotations to accumulate soil C.
Data from: Cover crop root contributions to soil carbon in a no-till corn bioenergy cropping system
Crop residues are potential biofuel feedstocks, but residue removal may reduce soil carbon (C). The inclusion of a cover crop in a corn bioenergy system could provide additional biomass, mitigating the negative effects of residue removal by adding to stable soil C pools. In a no-till continuous corn bioenergy system in the northern US Corn Belt, we used 13CO2 pulse labeling to trace plant C from a winter rye (Secale cereale) cover crop into different soil C pools for 2 years following rye cover crop termination. Corn stover left as residue (30% of total stover) contributed 66, corn roots 57, rye shoots 61, rye roots 50, and rye rhizodeposits 25 g C m−2 to soil. Five months following cover crop termination, belowground cover crop inputs were three times more likely to remain in soil C pools than were aboveground inputs, and much of the root-derived C was in mineral-associated soil fractions. After 2 years, both above- and belowground inputs had declined substantially, indicating that the majority of both root and shoot inputs are eventually mineralized. Our results underscore the importance of cover crop roots vs. shoots and the importance of cover crop rhizodeposition (33% of total belowground cover crop C inputs) as a source of soil C. However, the eventual loss of most cover crop C from these soils indicates that cover crops will likely need to be included every year in rotations to accumulate soil C.
Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China
Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.
Data for Attributing Differences of Solar-Induced Chlorophyll Fluorescence (SIF)-Gross Primary Production (GPP) Relationships between Two C4 Crops, Corn and Miscanthus
Information to characterize the solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationship in C4 cropping systems remains limited. The annual C4 crop corn and perennial C4 crop miscanthus differ in phenology, canopy structure and leaf physiology. Investigating the SIF-GPP relationships in these species could deepen our understanding of SIF-GPP relationships within C4 crops. Using in situ canopy SIF and GPP measurements for both species along with leaf-level measurements, we found considerable differences in the SIF-GPP relationships between corn and miscanthus, with a stronger SIF-GPP relationship and higher slope of SIF-GPP observed in corn compared to miscanthus. These differences were mainly caused by leaf physiology. For miscanthus, high non-photochemical quenching (NPQ) under high light, temperature and water vapor deficit (VPD) conditions caused a large decline of fluorescence yield (ΦF), which further led to a SIF midday depression and weakened the SIF-GPP relationship. The larger slope in corn than miscanthus was mainly due to its higher GPP in mid-summer, largely attributed to the higher leaf photosynthesis and less NPQ. Our results demonstrated variation of the SIF-GPP relationship within C4 crops and highlighted the importance of leaf physiology in determining canopy SIF behaviors and SIF-GPP relationships.
Data for Immediate Impacts of Soybean Cover Crop on Bacterial Community Composition and Diversity in Soil Under Long-Term Saccharum Monoculture
Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.
The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2)
Abstract Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human‐earth systems interactions in ESMs.
Optimizing pollinator conservation and crop yield among perennial bioenergy crops
In order to both combat the decline of biodiversity and produce food, fuel, and fiber for a growing human population, current agricultural landscapes must transition into diversified, multifunctional systems. Perennial cellulosic biofuel crops have potential to meet both of these challenges, acting as multifunctional systems that can enhance biodiversity. What is not well understood, and what we test here, are the tradeoffs among different perennial crops in their performance as biofuels and in biodiversity conservation. Working in an established bioenergy experiment with four native, perennial, cellulosic biofuel crop varieties - ranging from monoculture to diverse restoration planting - we tested the effect of biofuel crop management on flower communities, pollinator communities, and crop yield. The greatest abundance and diversity of pollinators and flowers were in treatments that were successional (unmanaged), followed by restored prairie (seeded mix of native grasses and forbs), switchgrass, and a mix of native grasses. However, biofuel crop yield was approximately the inverse, with native grasses having the highest yield, followed by switchgrass and prairie, then successional treatments. Restored prairie was the optimal biofuel crop when both pollinator conservation and crop yield are valued similarly. We add to mounting evidence that policy is needed to create sustainable markets that value the multifunctionality of perennial biofuel systems in order to achieve greater ecosystem services from agricultural landscapes.