Edaphic controls of soil organic carbon in tropical agricultural landscapes

Predicting soil organic carbon (SOC) is problematic in tropical soils because mechanisms of SOC (de)stabilization are not resolved. We aimed to identify such storage mechanisms in a tropical soil landscape constrained by 100 years of similar soil inputs and agricultural disturbance under the production of sugarcane, a C-4 grass and bioenergy feedstock. We measured soil physicochemical parameters, SOC concentration, and SOC dynamics by soil horizon to one meter to identify soil parameters that can predict SOC outcomes. Applying correlative analyses, linear mixed model (LMM) regression, model selection by AICc, and hierarchical clustering we found that slow moving SOC was related to many soil parameters, while the fastest moving SOC was only related to soil surface charge. Our models explained 78-79%, 51-57%, 7-8% of variance in SOC concentration, slow pool decay, and fast pool decay, respectively. Top SOC predictors were roots, the ratio of organo-complexed iron (Fe) to aluminum (Al), water stable aggregates (WSagg), and cation exchange capacity (CEC). Using hierarchical clustering we also assessed SOC predictors across gradients of depth and rainfall with strong reductions in Roots, SOC, and slow pool decay associated with increasing depth, while increased rainfall was associated with increased Clay and WSagg and reduced CEC in surface soils. Increased negative surface charge, water stable aggregation, organo-Fe complexation, and root inputs were key SOC protection mechanisms despite high soil disturbance. Further development of these relationships is expected to improve understanding of SOC storage mechanisms and outcomes in similar tropical agricultural soils globally

Maximizing Soil Carbon Sequestration: Assessing Procedural Barriers to Carbon Management in Cultivated Tropical Perennial Grass Systems

The natural capacity of the terrestrial landscape to capture and store carbon from the atmosphere can be used in cultivated systems to maximize the climate change mitigation potential of agricultural regions. A combination of inherent soil carbon storage potential, conservation management, and rhizosphere inputs should be considered when making landscape‐level decisions about agriculture if climate change mitigation is an important goal. However, the ability to accurately predict soil organic carbon accumulation following management change in the tropics is currently limited by the commonly available tools developed in more temperate systems, a gap that must be addressed locally in order to facilitate these types of landscape‐level decisions. Here, we use a case study in Hawaii to demonstrate multiple approaches to measuring and simulating soil carbon changes after the implementation of zero‐tillage cultivation of perennial grasses following more than a century of intensive sugarcane cultivation. We identify advancements needed to overcome the barriers to potential monitoring and projection protocols for soil carbon storage at our site and other similar sites

Carbon budgets of potential tropical perennial grass cropping scenarios for bioenergy feedstock production

BACKGROUND: The environmental costs of fossil fuel consumption are globally recognized, opening many pathways for the development of regional portfolio solutions for sustainable replacement fuel and energy options. The purpose of this study was to create a baseline carbon (C) budget of a conventionally managed sugarcane (Saccharum officinarum) production system on Maui, Hawaii, and compare it to three different future energy cropping scenarios: (1) conventional sugarcane with a 50% deficit irrigation (sugarcane 50%), (2) ratoon harvested napiergrass (Pennisetum purpureum Schumach.) with 100% irrigation (napier 100%), and (3) ratoon harvested napiergrass with a 50% deficit irrigation (napier 50%). RESULTS: The differences among cropping scenarios for the fossil fuel-based emissions associated with agricultural inputs and field operations were small compared to the differences associated with pre-harvest burn emissions and soil C stock under ratoon harvest and zero-tillage management. Burn emissions were nearly 2000 kg Ceq ha−1 year−1 in the conventional sugarcane; whereas soil C gains were approximately 4500 kg Ceq ha−1 year−1 in the surface layer of the soil profile for napiergrass. Further, gains in deep soil profile C were nearly three times greater than in the surface layer. Therefore, net global warming potential was greatest for conventional sugarcane and least for napier 50% when deep profile soil C was included. Per unit of biomass yield, the most greenhouse gas (GHG) intensive scenario was sugarcane 50% with a GHG Index (GHGI, positive values imply a climate impact, so a more negative value is preferable for climate change mitigation) of 0.11 and the least intensive was napiergrass 50% when a deep soil profile was included (GHGI = − 0.77). CONCLUSION: Future scenarios for energy or fuel production on former sugarcane land across the Pacific Basin or other volcanic islands should concentrate on ratoon-harvested crops that maintain yields under zero-tillage management for long intervals between kill harvest and reduce costs of field operations and agricultural input requirements. For napiergrass on Maui and elsewhere, deficit irrigation maximized climate change mitigation of the system and reduced water use should be part of planning a sustainable, diversified agricultural landscape

Crop Modeling Application to Improve Irrigation Efficiency in Year-Round Vegetable Production in the Texas Winter Garden Region

Given a rising demand for quality assurance, rather than solely yield, supplemental irrigation plays an important role to ensure the viability and profitability of vegetable crops from unpredictable changes in weather. However, under drought conditions, agricultural irrigation is often given low priority for water allocation. This reduced water availability for agriculture calls for techniques with greater irrigation efficiency, that do not compromise crop quality and yield, and that provide economic benefit for producers. This study developed vegetable growing models for eight different vegetable crops (bush bean, green bean, cabbage, peppermint, spearmint, yellow straight neck squash, zucchini, and bell pepper) based on data from several years of field research. The ALMANAC model accurately simulated yields and water use efficiency (WUE) of all eight vegetables. The developed vegetable models were used to evaluate the effects of various irrigation regimes on vegetable growth and production in several locations in the Winter Garden Region of Texas, under variable weather conditions. Based on our simulation results from 960 scenarios, optimal irrigation amounts that produce high yield as well as reasonable economic profit to producers were determined for each vegetable crop. Overall, yields for all vegetables increased as irrigation amounts increased. However, irrigation amounts did not have a sustainable impact on vegetable yield at high irrigation treatments, and the WUEs of most vegetables were not significantly different among various irrigation regimes. When vegetable yields were compared with water cost, the rate decreased as irrigation amounts increased. Thus, producers will not receive economic benefits when vegetable irrigation water demand is too high

Improving Modeling of Quinoa Growth under Saline Conditions Using the Enhanced Agricultural Policy Environmental eXtender Model

Cultivation of highly salt-tolerant plants (i.e., halophytes), may provide a viable alternative to increase productivity compared to conventional salt-sensitive crops, increasing the economic potential of salt-affected lands that comprise ~20% of irrigated lands worldwide. In this study the Agricultural Policy/Environmental eXtender (APEX) model was adapted to simulate growth of the halophyte quinoa, along with salt dynamics in the plant-soil-water system. Model modifications included salt uptake and salt stress functions formulated using greenhouse data. Data from a field site were used to further parameterize and calibrate the model. Initial simulation results were promising, but differences between simulated and observed soil salinity and plant salt values during the growing season in the calibration suggest that additional improvements to salt uptake and soil salinity algorithms are needed. To demonstrate utility of the modified APEX model, six scenarios were run to estimate quinoa biomass production and soil salinity with different irrigation managements and salinities. Simulated annual biomass was sensitive to soil moisture, and root zone salinity increased in all scenarios. Further experiments are needed to improve understanding of crop salt uptake dynamics and stress sensitivities so that future model updates and simulations better represent salt dynamics in plants and soils in agricultural settings

Drought-Induced Nitrogen and Phosphorus Carryover Nutrients in Corn/Soybean Rotations in the Upper Mississippi River Basin

Droughts reduce crop yields, which translates to reduced nutrient uptake or removal from the soil. Under such conditions, residual plant nutrients such as nitrogen (N) and phosphorus (P) can be carried over for subsequent crops. We applied the Agricultural Policy Environmental eXtender (APEX) model to simulate continuous corn (Zea mays L.)/soybean (Glycine max [L.] Merr.) rotations on 3703 farm fields within the Upper Mississippi River Basin (UMRB) over a 47-year timescale: 1960 to 2006. We used the Standardized Precipitation Index (PSI) to identify the drought years between 1960 to 2006, following which we evaluated potential drought-induced carryover N and P nutrients in corn/soybean rotations relative to near normal and very to extremely wet years. Overall, drought reduced N uptake, total N losses, N mineralization and N fixation, the main driver of the soybean carryover N. Given the high cost of fertilizers and concerns over nutrient loss impacts on offsite water quality, farmers are compelled to account for every plant nutrient that is already in the soil. Information from this study could be applied to develop optimal N and P recommendations after droughts, while identification of region-wide potential reductions in N and P applications has implications for conservation efforts aimed at minimizing environmental loading and associated water quality concerns

Drought-Induced Nitrogen and Phosphorus Carryover Nutrients in Corn/Soybean Rotations in the Upper Mississippi River Basin

Droughts reduce crop yields, which translates to reduced nutrient uptake or removal from the soil. Under such conditions, residual plant nutrients such as nitrogen (N) and phosphorus (P) can be carried over for subsequent crops. We applied the Agricultural Policy Environmental eXtender (APEX) model to simulate continuous corn (Zea mays L.)/soybean (Glycine max [L.] Merr.) rotations on 3703 farm fields within the Upper Mississippi River Basin (UMRB) over a 47-year timescale: 1960 to 2006. We used the Standardized Precipitation Index (PSI) to identify the drought years between 1960 to 2006, following which we evaluated potential drought-induced carryover N and P nutrients in corn/soybean rotations relative to near normal and very to extremely wet years. Overall, drought reduced N uptake, total N losses, N mineralization and N fixation, the main driver of the soybean carryover N. Given the high cost of fertilizers and concerns over nutrient loss impacts on offsite water quality, farmers are compelled to account for every plant nutrient that is already in the soil. Information from this study could be applied to develop optimal N and P recommendations after droughts, while identification of region-wide potential reductions in N and P applications has implications for conservation efforts aimed at minimizing environmental loading and associated water quality concerns

Modeling the Distribution of Wild Cotton Gossypium aridum in Mexico Using Flowering Growing Degree Days and Annual Available Soil Water

Climate change is expected to alter species distribution and habitat composition, with wild species being particularly vulnerable. Gossypium aridum, a wild cotton species in Mexico, has shown a decrease in habitat extent and population; however, the data are not precise. The objectives of this study are: (1) to develop a distribution model of G. aridum in Mexico, (2) to identify areas with environmental conditions similar to where the species currently maintains populations, and (3) to determine which variable, flowering growing degree days (FGDD) or annual available soil water (AASW, mm year−1), has greater influence on the distribution of the species. Geographic information system (GIS) software was used with datasets from two databases in Mexico that were partitioned for site characterization, model construction, calibration, validation, and sensitivity analysis. The range of 330–860 FGDD and 4–110 mm year−1 AASW best described the species habitat, according to results of seven precision and accuracy statistical tests. The model identified geographic regions throughout the country with similar conditions as the locations where the species has been observed, including some where no collections have not yet been registered in Mexican databases. FGDD, rather than AASW, showed greater influence on the distribution of the species. The generated information can be used to guide collection expeditions for G. aridum and to study climatic impact on species distribution. The approach using FGDD and AASW can be used in the modeling of wild cotton species that are valuable natural resources for crop improvement

Modeling the Distribution of Wild Cotton <i>Gossypium aridum</i> in Mexico Using Flowering Growing Degree Days and Annual Available Soil Water

Climate change is expected to alter species distribution and habitat composition, with wild species being particularly vulnerable. Gossypium aridum, a wild cotton species in Mexico, has shown a decrease in habitat extent and population; however, the data are not precise. The objectives of this study are: (1) to develop a distribution model of G. aridum in Mexico, (2) to identify areas with environmental conditions similar to where the species currently maintains populations, and (3) to determine which variable, flowering growing degree days (FGDD) or annual available soil water (AASW, mm year−1), has greater influence on the distribution of the species. Geographic information system (GIS) software was used with datasets from two databases in Mexico that were partitioned for site characterization, model construction, calibration, validation, and sensitivity analysis. The range of 330–860 FGDD and 4–110 mm year−1 AASW best described the species habitat, according to results of seven precision and accuracy statistical tests. The model identified geographic regions throughout the country with similar conditions as the locations where the species has been observed, including some where no collections have not yet been registered in Mexican databases. FGDD, rather than AASW, showed greater influence on the distribution of the species. The generated information can be used to guide collection expeditions for G. aridum and to study climatic impact on species distribution. The approach using FGDD and AASW can be used in the modeling of wild cotton species that are valuable natural resources for crop improvement