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1. Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage

Author

Rieke, Elizabeth L., Cappellazzi, Shannon B., Cope, Michael, Liptzin, Daniel, Mac Bean, G., Greub, Kelsey L. H., Norris, Charlotte E., Tracy, Paul W., Aberle, Ezra, Ashworth, Amanda, Banuelos Tavarez, Oscar, Bary, Andy, I, Baumhardt, R. L., Borbon Gracia, Alberto, Brainard, Daniel C., Brennan, Jameson R., Briones Reyes, Dolores, Bruhjell, Darren, Carlyle, Cameron N., Crawford, James J. W., Creech, Cody F., Culman, Steve W., Deen, Bill, Dell, Curtis J., Derner, Justin D., Ducey, Thomas F., Duiker, Sjoerd W., Dyck, Miles F., Ellert, Benjamin H., Espinosa Solorio, Avelino, Fonte, Steven J., Fonteyne, Simon, Fortuna, Ann-Marie, Foster, Jamie L., Fultz, Lisa M., Gamble, Audrey, V, Geddes, Charles M., Griffin-LaHue, Deirdre, Grove, John H., Hamilton, Stephen K., Hao, Xiying, Hayden, Zachary D., Honsdorf, Nora, Howe, Julie A., Ippolito, James A., Johnson, Gregg A., Kautz, Mark A., Kitchen, Newell R., Kumar, Sandeep, Kurtz, Kirsten S. M., Larney, Francis J., Lewis, Katie L., Liebman, Matt, Lopez Ramirez, Antonio, Machado, Stephen, Maharjan, Bijesh, Martinez Gamino, Miguel Angel, May, William E., McClaran, Mitchel P., McDaniel, Marshall D., Millar, Neville, Mitchell, Jeffrey P., Moore, Amber D., Moore, Philip A., Mora Gutierrez, Manuel, Nelson, Kelly A., Omondi, Emmanuel C., Osborne, Shannon L., Osorio Alcala, Leodegario, Owens, Philip, Pena-Yewtukhiw, Eugenia M., Poffenbarger, Hanna J., Ponce Lira, Brenda, Reeve, Jennifer R., Reinbott, Timothy M., Reiter, Mark S., Ritchey, Edwin L., Roozeboom, Kraig L., Rui, Yichao, Sadeghpour, Amir, Sainju, Upendra M., Sanford, Gregg R., Schillinger, William F., Schindelbeck, Robert R., Schipanski, Meagan E., Schlegel, Alan J., Scow, Kate M., Sherrod, Lucretia A., Shober, Amy L., Sidhu, Sudeep S., Solis Moya, Ernesto, St Luce, Mervin, Strock, Jeffrey S., Suyker, Andrew E., Sykes, Virginia R., Tao, Haiying, Trujillo Campos, Alberto, Van Eerd, Laura L., Verhulst, Nele, Vyn, Tony J., Wang, Yutao, Watts, Dexter B., William, Bryan B., Wright, David L., Zhang, Tiequan, Morgan, Cristine L. S., Honeycutt, C. Wayne, Rieke, Elizabeth L., Cappellazzi, Shannon B., Cope, Michael, Liptzin, Daniel, Mac Bean, G., Greub, Kelsey L. H., Norris, Charlotte E., Tracy, Paul W., Aberle, Ezra, Ashworth, Amanda, Banuelos Tavarez, Oscar, Bary, Andy, I, Baumhardt, R. L., Borbon Gracia, Alberto, Brainard, Daniel C., Brennan, Jameson R., Briones Reyes, Dolores, Bruhjell, Darren, Carlyle, Cameron N., Crawford, James J. W., Creech, Cody F., Culman, Steve W., Deen, Bill, Dell, Curtis J., Derner, Justin D., Ducey, Thomas F., Duiker, Sjoerd W., Dyck, Miles F., Ellert, Benjamin H., Espinosa Solorio, Avelino, Fonte, Steven J., Fonteyne, Simon, Fortuna, Ann-Marie, Foster, Jamie L., Fultz, Lisa M., Gamble, Audrey, V, Geddes, Charles M., Griffin-LaHue, Deirdre, Grove, John H., Hamilton, Stephen K., Hao, Xiying, Hayden, Zachary D., Honsdorf, Nora, Howe, Julie A., Ippolito, James A., Johnson, Gregg A., Kautz, Mark A., Kitchen, Newell R., Kumar, Sandeep, Kurtz, Kirsten S. M., Larney, Francis J., Lewis, Katie L., Liebman, Matt, Lopez Ramirez, Antonio, Machado, Stephen, Maharjan, Bijesh, Martinez Gamino, Miguel Angel, May, William E., McClaran, Mitchel P., McDaniel, Marshall D., Millar, Neville, Mitchell, Jeffrey P., Moore, Amber D., Moore, Philip A., Mora Gutierrez, Manuel, Nelson, Kelly A., Omondi, Emmanuel C., Osborne, Shannon L., Osorio Alcala, Leodegario, Owens, Philip, Pena-Yewtukhiw, Eugenia M., Poffenbarger, Hanna J., Ponce Lira, Brenda, Reeve, Jennifer R., Reinbott, Timothy M., Reiter, Mark S., Ritchey, Edwin L., Roozeboom, Kraig L., Rui, Yichao, Sadeghpour, Amir, Sainju, Upendra M., Sanford, Gregg R., Schillinger, William F., Schindelbeck, Robert R., Schipanski, Meagan E., Schlegel, Alan J., Scow, Kate M., Sherrod, Lucretia A., Shober, Amy L., Sidhu, Sudeep S., Solis Moya, Ernesto, St Luce, Mervin, Strock, Jeffrey S., Suyker, Andrew E., Sykes, Virginia R., Tao, Haiying, Trujillo Campos, Alberto, Van Eerd, Laura L., Verhulst, Nele, Vyn, Tony J., Wang, Yutao, Watts, Dexter B., William, Bryan B., Wright, David L., Zhang, Tiequan, Morgan, Cristine L. S., and Honeycutt, C. Wayne

Abstract

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity.

Published
2022
Full Text
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2. Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage

Author

Rieke, Elizabeth L., Cappellazzi, Shannon B., Cope, Michael, Liptzin, Daniel, Mac Bean, G., Greub, Kelsey L. H., Norris, Charlotte E., Tracy, Paul W., Aberle, Ezra, Ashworth, Amanda, Banuelos Tavarez, Oscar, Bary, Andy, I, Baumhardt, R. L., Borbon Gracia, Alberto, Brainard, Daniel C., Brennan, Jameson R., Briones Reyes, Dolores, Bruhjell, Darren, Carlyle, Cameron N., Crawford, James J. W., Creech, Cody F., Culman, Steve W., Deen, Bill, Dell, Curtis J., Derner, Justin D., Ducey, Thomas F., Duiker, Sjoerd W., Dyck, Miles F., Ellert, Benjamin H., Espinosa Solorio, Avelino, Fonte, Steven J., Fonteyne, Simon, Fortuna, Ann-Marie, Foster, Jamie L., Fultz, Lisa M., Gamble, Audrey, V, Geddes, Charles M., Griffin-LaHue, Deirdre, Grove, John H., Hamilton, Stephen K., Hao, Xiying, Hayden, Zachary D., Honsdorf, Nora, Howe, Julie A., Ippolito, James A., Johnson, Gregg A., Kautz, Mark A., Kitchen, Newell R., Kumar, Sandeep, Kurtz, Kirsten S. M., Larney, Francis J., Lewis, Katie L., Liebman, Matt, Lopez Ramirez, Antonio, Machado, Stephen, Maharjan, Bijesh, Martinez Gamino, Miguel Angel, May, William E., McClaran, Mitchel P., McDaniel, Marshall D., Millar, Neville, Mitchell, Jeffrey P., Moore, Amber D., Moore, Philip A., Mora Gutierrez, Manuel, Nelson, Kelly A., Omondi, Emmanuel C., Osborne, Shannon L., Osorio Alcala, Leodegario, Owens, Philip, Pena-Yewtukhiw, Eugenia M., Poffenbarger, Hanna J., Ponce Lira, Brenda, Reeve, Jennifer R., Reinbott, Timothy M., Reiter, Mark S., Ritchey, Edwin L., Roozeboom, Kraig L., Rui, Yichao, Sadeghpour, Amir, Sainju, Upendra M., Sanford, Gregg R., Schillinger, William F., Schindelbeck, Robert R., Schipanski, Meagan E., Schlegel, Alan J., Scow, Kate M., Sherrod, Lucretia A., Shober, Amy L., Sidhu, Sudeep S., Solis Moya, Ernesto, St Luce, Mervin, Strock, Jeffrey S., Suyker, Andrew E., Sykes, Virginia R., Tao, Haiying, Trujillo Campos, Alberto, Van Eerd, Laura L., Verhulst, Nele, Vyn, Tony J., Wang, Yutao, Watts, Dexter B., William, Bryan B., Wright, David L., Zhang, Tiequan, Morgan, Cristine L. S., Honeycutt, C. Wayne, Rieke, Elizabeth L., Cappellazzi, Shannon B., Cope, Michael, Liptzin, Daniel, Mac Bean, G., Greub, Kelsey L. H., Norris, Charlotte E., Tracy, Paul W., Aberle, Ezra, Ashworth, Amanda, Banuelos Tavarez, Oscar, Bary, Andy, I, Baumhardt, R. L., Borbon Gracia, Alberto, Brainard, Daniel C., Brennan, Jameson R., Briones Reyes, Dolores, Bruhjell, Darren, Carlyle, Cameron N., Crawford, James J. W., Creech, Cody F., Culman, Steve W., Deen, Bill, Dell, Curtis J., Derner, Justin D., Ducey, Thomas F., Duiker, Sjoerd W., Dyck, Miles F., Ellert, Benjamin H., Espinosa Solorio, Avelino, Fonte, Steven J., Fonteyne, Simon, Fortuna, Ann-Marie, Foster, Jamie L., Fultz, Lisa M., Gamble, Audrey, V, Geddes, Charles M., Griffin-LaHue, Deirdre, Grove, John H., Hamilton, Stephen K., Hao, Xiying, Hayden, Zachary D., Honsdorf, Nora, Howe, Julie A., Ippolito, James A., Johnson, Gregg A., Kautz, Mark A., Kitchen, Newell R., Kumar, Sandeep, Kurtz, Kirsten S. M., Larney, Francis J., Lewis, Katie L., Liebman, Matt, Lopez Ramirez, Antonio, Machado, Stephen, Maharjan, Bijesh, Martinez Gamino, Miguel Angel, May, William E., McClaran, Mitchel P., McDaniel, Marshall D., Millar, Neville, Mitchell, Jeffrey P., Moore, Amber D., Moore, Philip A., Mora Gutierrez, Manuel, Nelson, Kelly A., Omondi, Emmanuel C., Osborne, Shannon L., Osorio Alcala, Leodegario, Owens, Philip, Pena-Yewtukhiw, Eugenia M., Poffenbarger, Hanna J., Ponce Lira, Brenda, Reeve, Jennifer R., Reinbott, Timothy M., Reiter, Mark S., Ritchey, Edwin L., Roozeboom, Kraig L., Rui, Yichao, Sadeghpour, Amir, Sainju, Upendra M., Sanford, Gregg R., Schillinger, William F., Schindelbeck, Robert R., Schipanski, Meagan E., Schlegel, Alan J., Scow, Kate M., Sherrod, Lucretia A., Shober, Amy L., Sidhu, Sudeep S., Solis Moya, Ernesto, St Luce, Mervin, Strock, Jeffrey S., Suyker, Andrew E., Sykes, Virginia R., Tao, Haiying, Trujillo Campos, Alberto, Van Eerd, Laura L., Verhulst, Nele, Vyn, Tony J., Wang, Yutao, Watts, Dexter B., William, Bryan B., Wright, David L., Zhang, Tiequan, Morgan, Cristine L. S., and Honeycutt, C. Wayne

Abstract

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity.

Published
2022

3. Soybean response to nitrogen application across the United States: A synthesis-analysis

Author

Mourtzinis, Spyridon, Kaur, Gurpreet, Orlowski, John M., Shapiro, Charles A., Lee, Chad D., Wortmann, Charles, Holshouser, David L., Nafziger, Emerson D., Kandel, Hans, Neikamp, Jason, Ross, William J., Lofton, Josh, Vonk, Joshua, Roozeboom, Kraig L., Thelen, Kurt D., Lindsey, Laura E., Staton, Michael, Naeve, Seth L., Casteel, Shaun N., Wiebold, William J., Conley, Shawn P., Mourtzinis, Spyridon, Kaur, Gurpreet, Orlowski, John M., Shapiro, Charles A., Lee, Chad D., Wortmann, Charles, Holshouser, David L., Nafziger, Emerson D., Kandel, Hans, Neikamp, Jason, Ross, William J., Lofton, Josh, Vonk, Joshua, Roozeboom, Kraig L., Thelen, Kurt D., Lindsey, Laura E., Staton, Michael, Naeve, Seth L., Casteel, Shaun N., Wiebold, William J., and Conley, Shawn P.

Abstract

The effects of supplemental nitrogen (N) on soybean [Glycine max (L.) Merr.] seed yield have been the focus of much research over the past four decades. However, most experiments were region-specific and focused on the effect of a single N-related management choice, thus resulting in a limited inference space. Here, we composited data from individual experiments conducted across the US that examined the effect of N fertilization on soybean yield. The combined database included 207 environments (experiment x year combinations) for a total of 5991 N-treated soybean yields. We used hierarchical modeling and conditional inference tree analysis on the combined dataset to establish the relationship and contribution of several N management choices on soybean yield. The N treatment variables were: N-application (single or split), N-method (soil incorporated, foliar, etc.), N-timing (pre-plant, at a reproductive stage, etc.), and N-rate (from a 0 N control to as much as 560 kg ha−1). Of the total yield variability, 68% was associated with the effect of environment, whereas only a small fraction of that variability (< 1%) was attributable to each N variable. Averaged over all experiments, a single N application and the split N application were 60 and 110 kg ha−1 greater yielding than the zero N control treatment, respectively. A split N application with more than one method (e.g., soil incorporated and foliar) resulted in 120 kg ha−1 greater yield than zero N plots. Split N application between planting and reproductive stages (Rn) resulted in greater yield than zero N and single application during a Rn; however, the effect was not significantly different than N application at other growth stages. Increasing the N rate increased the environment average soybean yield; however, 93% of the environment-specific N-rate responses were not significant which suggested a minimal effect of N across the examined region. A large yield variability was observed among e

Published
2018
Full Text
View/download PDF

4. Soybean response to nitrogen application across the United States: A synthesis-analysis

Author

School of Plant and Environmental Sciences, Virginia Agricultural Experiment Station, Mourtzinis, Spyridon, Kaur, Gurpreet, Orlowski, John M., Shapiro, Charles A., Lee, Chad D., Wortmann, Charles, Holshouser, David L., Nafziger, Emerson D., Kandel, Hans, Neikamp, Jason, Ross, William J., Lofton, Josh, Vonk, Joshua, Roozeboom, Kraig L., Thelen, Kurt D., Lindsey, Laura E., Staton, Michael, Naeve, Seth L., Casteel, Shaun N., Wiebold, William J., Conley, Shawn P., School of Plant and Environmental Sciences, Virginia Agricultural Experiment Station, Mourtzinis, Spyridon, Kaur, Gurpreet, Orlowski, John M., Shapiro, Charles A., Lee, Chad D., Wortmann, Charles, Holshouser, David L., Nafziger, Emerson D., Kandel, Hans, Neikamp, Jason, Ross, William J., Lofton, Josh, Vonk, Joshua, Roozeboom, Kraig L., Thelen, Kurt D., Lindsey, Laura E., Staton, Michael, Naeve, Seth L., Casteel, Shaun N., Wiebold, William J., and Conley, Shawn P.

Abstract

The effects of supplemental nitrogen (N) on soybean [Glycine max (L.) Merr.] seed yield have been the focus of much research over the past four decades. However, most experiments were region-specific and focused on the effect of a single N-related management choice, thus resulting in a limited inference space. Here, we composited data from individual experiments conducted across the US that examined the effect of N fertilization on soybean yield. The combined database included 207 environments (experiment x year combinations) for a total of 5991 N-treated soybean yields. We used hierarchical modeling and conditional inference tree analysis on the combined dataset to establish the relationship and contribution of several N management choices on soybean yield. The N treatment variables were: N-application (single or split), N-method (soil incorporated, foliar, etc.), N-timing (pre-plant, at a reproductive stage, etc.), and N-rate (from a 0 N control to as much as 560 kg ha−1). Of the total yield variability, 68% was associated with the effect of environment, whereas only a small fraction of that variability (< 1%) was attributable to each N variable. Averaged over all experiments, a single N application and the split N application were 60 and 110 kg ha−1 greater yielding than the zero N control treatment, respectively. A split N application with more than one method (e.g., soil incorporated and foliar) resulted in 120 kg ha−1 greater yield than zero N plots. Split N application between planting and reproductive stages (Rn) resulted in greater yield than zero N and single application during a Rn; however, the effect was not significantly different than N application at other growth stages. Increasing the N rate increased the environment average soybean yield; however, 93% of the environment-specific N-rate responses were not significant which suggested a minimal effect of N across the examined region. A large yield variability was observed among e

Published
2018

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