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1. Global dataset of soil organic carbon in tidal marshes

Author

Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, Worthington, Thomas A., Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, and Worthington, Thomas A.

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023
Full Text
View/download PDF

2. Global dataset of soil organic carbon in tidal marshes

Author

Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, Worthington, Thomas A., Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, and Worthington, Thomas A.

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023
Full Text
View/download PDF

3. Global dataset of soil organic carbon in tidal marshes

Author

Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E.N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias, Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, Worthington, Thomas A., Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E.N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias, Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, and Worthington, Thomas A.

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023

4. Global dataset of soil organic carbon in tidal marshes

Author

Maxwell, Tania L., Rovai, André S., Adame, Maria F., Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Lewis, Carolyn J. E., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna E. L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei S., Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana C., Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias, Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia V., Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, Worthington, Thomas A., Maxwell, Tania L., Rovai, André S., Adame, Maria F., Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Lewis, Carolyn J. E., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna E. L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei S., Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana C., Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias, Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia V., Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, and Worthington, Thomas A.

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023

5. Global dataset of soil organic carbon in tidal marshes

Author

Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, Worthington, Thomas A., Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, and Worthington, Thomas A.

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023
Full Text
View/download PDF

6. Global dataset of soil organic carbon in tidal marshes

Author

Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, Worthington, Thomas A., Maxwell, Tania L., Rovai, André S., Adame, Maria Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael E., Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace M., Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Ewers Lewis, Carolyn J., Giani, Luise, Gispert, Maria, Gontharet, Swanne, González-Pérez, José A., González-Alcaraz, M. Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. Patrick, Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva-Maria, Pollmann, Thomas, Raw, Jacqueline L., Recio, María, Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian, Santos, Rui, Serrano, Oscar, Siewert, Matthias B., Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Antisari, Livia Vittori, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, and Worthington, Thomas A.

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023
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7. Global dataset of soil organic carbon in tidal marshes

Author

U.S. Army Engineer Research and Development Center, Fundação para a Ciência e a Tecnologia (Portugal), Agencia Estatal de Investigación (España), Ministerio de Ciencia e Innovación (España), European Commission, Mancomunidad de los Canales del Taibilla, Fundación Técnica Industrial, Ministry of Business, Innovation, and Employment (New Zealand), Department of Science and Innovation (South Africa), Nelson Mandela Metropolitan University, German Research Foundation, Scottish Government, Natural Environment Research Council (UK), Welsh Government, Xunta de Galicia, Velux Foundation, Maxwell, Tania L. [0000-0002-8413-9186], Adame, María Fernanda [0000-0001-9620-9252], Boscutti, Francesco [0000-0002-4969-2752], Böttcher, Michael Ernst [0000-0002-8877-0303], Burden, Annette [0000-0002-7694-1638], Worthington, Thomas [0000-0002-8138-9075], González-Pérez, José Antonio [0000-0001-7607-1444], Guerra, Roberta [0000-0002-7151-6616], Jones, Alice R. [0000-0002-6157-2024], Kohfeld, Karen E. [0000-0001-7241-1624], Krause-Jensen, Dorte [0000-0001-9792-256X], Lavery, Paul S. [0000-0001-5162-273X], Lovelock, Catherine E. [0000-0002-2219-6855], Megonigal, J. P. [0000-0002-2018-7883], Neto, João M. [0000-0002-9033-3671], Nogueira, Juliana [0000-0003-4858-8774], Pagès, Jordi F. [0000-0001-9346-8312], Pollmann, Thomas [0000-0001-9099-1618], Law, Jacqueline L. [0000-0002-5270-032X], Recio, M. [0000-0002-6186-6049], Ruiz-Fernández, Ana Carolina [0000-0002-2515-1249], Sanders, Christian J. [0000-0003-0090-0896], Siewert, Matthias [0000-0003-2890-8873], Smeaton, Craig [0000-0003-4535-2555], Trasar-Cepeda, Carmen [0000-0001-9019-5590], Livia, Vittori Antisari [0000-0001-6970-6931], Raymond D. [0000-0002-7391-5530], Zubrzycki, Sebastian [0000-0002-6398-9173], Maxwell, Tania L., Rovai, André S., Adame, María Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael Ernst, Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace, Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Worthington, Thomas, Lewis, Carolyn J. Ewers, Giani, Luise, Gispert, M., Gontharet, Swanne, González-Pérez, José Antonio, González-Alcaraz, María Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. P., Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva M., Pollmann, Thomas, Law, Jacqueline L., Recio, M., Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian J., Santos, Rui, Serrano, Oscar, Siewert, Matthias, Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Livia, Vittori Antisari, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, Spalding, Mark, U.S. Army Engineer Research and Development Center, Fundação para a Ciência e a Tecnologia (Portugal), Agencia Estatal de Investigación (España), Ministerio de Ciencia e Innovación (España), European Commission, Mancomunidad de los Canales del Taibilla, Fundación Técnica Industrial, Ministry of Business, Innovation, and Employment (New Zealand), Department of Science and Innovation (South Africa), Nelson Mandela Metropolitan University, German Research Foundation, Scottish Government, Natural Environment Research Council (UK), Welsh Government, Xunta de Galicia, Velux Foundation, Maxwell, Tania L. [0000-0002-8413-9186], Adame, María Fernanda [0000-0001-9620-9252], Boscutti, Francesco [0000-0002-4969-2752], Böttcher, Michael Ernst [0000-0002-8877-0303], Burden, Annette [0000-0002-7694-1638], Worthington, Thomas [0000-0002-8138-9075], González-Pérez, José Antonio [0000-0001-7607-1444], Guerra, Roberta [0000-0002-7151-6616], Jones, Alice R. [0000-0002-6157-2024], Kohfeld, Karen E. [0000-0001-7241-1624], Krause-Jensen, Dorte [0000-0001-9792-256X], Lavery, Paul S. [0000-0001-5162-273X], Lovelock, Catherine E. [0000-0002-2219-6855], Megonigal, J. P. [0000-0002-2018-7883], Neto, João M. [0000-0002-9033-3671], Nogueira, Juliana [0000-0003-4858-8774], Pagès, Jordi F. [0000-0001-9346-8312], Pollmann, Thomas [0000-0001-9099-1618], Law, Jacqueline L. [0000-0002-5270-032X], Recio, M. [0000-0002-6186-6049], Ruiz-Fernández, Ana Carolina [0000-0002-2515-1249], Sanders, Christian J. [0000-0003-0090-0896], Siewert, Matthias [0000-0003-2890-8873], Smeaton, Craig [0000-0003-4535-2555], Trasar-Cepeda, Carmen [0000-0001-9019-5590], Livia, Vittori Antisari [0000-0001-6970-6931], Raymond D. [0000-0002-7391-5530], Zubrzycki, Sebastian [0000-0002-6398-9173], Maxwell, Tania L., Rovai, André S., Adame, María Fernanda, Adams, Janine B., Álvarez-Rogel, José, Austin, William E. N., Beasy, Kim, Boscutti, Francesco, Böttcher, Michael Ernst, Bouma, Tjeerd J., Bulmer, Richard H., Burden, Annette, Burke, Shannon A., Camacho, Saritta, Chaudhary, Doongar R., Chmura, Gail L., Copertino, Margareth, Cott, Grace, Craft, Christopher, Day, John, de los Santos, Carmen B., Denis, Lionel, Ding, Weixin, Ellison, Joanna C., Worthington, Thomas, Lewis, Carolyn J. Ewers, Giani, Luise, Gispert, M., Gontharet, Swanne, González-Pérez, José Antonio, González-Alcaraz, María Nazaret, Gorham, Connor, Graversen, Anna Elizabeth L., Grey, Anthony, Guerra, Roberta, He, Qiang, Holmquist, James R., Jones, Alice R., Juanes, José A., Kelleher, Brian P., Kohfeld, Karen E., Krause-Jensen, Dorte, Lafratta, Anna, Lavery, Paul S., Laws, Edward A., Leiva-Dueñas, Carmen, Loh, Pei Sun, Lovelock, Catherine E., Lundquist, Carolyn J., Macreadie, Peter I., Mazarrasa, Inés, Megonigal, J. P., Neto, Joao M., Nogueira, Juliana, Osland, Michael J., Pagès, Jordi F., Perera, Nipuni, Pfeiffer, Eva M., Pollmann, Thomas, Law, Jacqueline L., Recio, M., Ruiz-Fernández, Ana Carolina, Russell, Sophie K., Rybczyk, John M., Sammul, Marek, Sanders, Christian J., Santos, Rui, Serrano, Oscar, Siewert, Matthias, Smeaton, Craig, Song, Zhaoliang, Trasar-Cepeda, Carmen, Twilley, Robert R., Van de Broek, Marijn, Vitti, Stefano, Livia, Vittori Antisari, Voltz, Baptiste, Wails, Christy N., Ward, Raymond D., Ward, Melissa, Wolfe, Jaxine, Yang, Renmin, Zubrzycki, Sebastian, Landis, Emily, Smart, Lindsey, and Spalding, Mark

Abstract

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Published
2023

8. Combining manure with mineral N fertilizer maintains maize yields: Evidence from four long-term experiments in Kenya

Author

Laub, Moritz, Corbeels, Marc, Ndungu, Samuel Mathu, Mucheru-Muna, Monicah Wanjiku, Mugendi, Daniel, Necpalova, Magdalena, Van de Broek, Marijn, Waswa, Wycliffe, Vanlauwe, Bernard, Six, Johan, Laub, Moritz, Corbeels, Marc, Ndungu, Samuel Mathu, Mucheru-Muna, Monicah Wanjiku, Mugendi, Daniel, Necpalova, Magdalena, Van de Broek, Marijn, Waswa, Wycliffe, Vanlauwe, Bernard, and Six, Johan

Abstract

Context: Crop productivity in sub-Saharan Africa cannot be substantially improved without simultaneously addressing short-term crop nutrient demand and long-term soil fertility. Integrated soil fertility management tackles both by the combined application of mineral fertilizers and organic resource inputs but few studies examined its' long-term effectiveness. Objective: To address this knowledge gap, this study analysed maize yield trends in four long-term (31–37 cropping seasons) field experiments in Kenya with contrasting soil textures and under different climates. Methods: All sites had two maize cropping seasons per year, received a base P and K fertilization and tested combinations of organic resource addition (1.2 and 4 t C ha-1 yr-1 ranging from farmyard manure, to high-quality Tithonia diversifolia and Calliandra calothyrsus material to low-quality saw dust), combined with (+N) and without (-N) mineral N fertilizer (120 kg N ha-1 season-1). General maize yield trends across sites and site specific trends were analyzed. Results: Across sites, the no-input control experienced significant average maize yield reductions of 50 kg ha-1 yr-1 over the study period. In contrast, the treatment with farmyard manure +N maintained yields at both 1.2 and 4 t C ha-1 yr-1. High initial yields following additions of Tithonia and Calliandra, reduced over time. Assessment by site showed site specificity of maize yields and yield trends. For example, the two climatically favorable sites in western Kenya experienced yield gains with high quality organic resources at 4 t C ha-1 yr-1, leading to yields of up to 8 t ha-1 per season, while sites in central Kenya experienced yield losses, leading to 3.5 t ha-1 per season. Yield site specificity for ± mineral N treatments was stonger than for organic resource treatments, e.g. the clayey site in central Kenya in the end showed no yield differences between ± N, except for the 1.2 t C ha-1 yr-1 farmyard manure treatment. Yet, farmyard ma

Published
2023

9. Managing soil organic carbon in tropical agroecosystems: evidence from four long-term experiments in Kenya

Author

Laub, Moritz, Corbeels, Marc, Couedel, Antoine, Ndungu, Samuel Mathu, Mucheru-Muna, Monicah Wanjiku, Mugendi, Daniel, Necpalova, Magdalena, Waswa, Wycliffe, Van de Broek, Marijn, Vanlauwe, Bernard, Six, Johan, Laub, Moritz, Corbeels, Marc, Couedel, Antoine, Ndungu, Samuel Mathu, Mucheru-Muna, Monicah Wanjiku, Mugendi, Daniel, Necpalova, Magdalena, Waswa, Wycliffe, Van de Broek, Marijn, Vanlauwe, Bernard, and Six, Johan

Abstract

In sub-Saharan Africa, maize is one of the most important staple crops, but long-term maize cropping with low external inputs has been associated with the loss of soil fertility. While adding high-quality organic resources combined with mineral fertilizer has been proposed to counteract this fertility loss, the long-term effectiveness and interactions with site properties still require more understanding. This study used repeated measurements over time to assess the effect of different quantities and qualities of organic resource addition combined with mineral nitrogen (N) on the change of soil organic carbon (SOC) contents over time (and SOC stocks in the year 2021) in four ongoing long-term experiments in Kenya. These experiments were established with identical treatments in moist to dry climates, on coarse to clayey soil textures, and have been conducted for at least 16 years. They received organic resources in quantities equivalent to 1.2 and 4 t C ha−1 yr−1 in the form of Tithonia diversifolia (high quality, fast turnover), Calliandra calothyrsus (high quality, intermediate turnover), Zea mays stover (low quality, fast turnover), sawdust (low quality, slow turnover) and local farmyard manure (variable quality, intermediate turnover). Furthermore, the addition of 240 kg N ha−1 yr−1 as mineral N fertilizer or no fertilizer was the split-plot treatment. At all four sites, a loss of SOC was predominantly observed, likely because the sites had been converted to cropland only a few decades before the start of the experiments. Across sites, the average decline of SOC content over 19 years in the 0 to 15 cm topsoil layer ranged from 42 % to 13 % of the initial SOC content for the control and the farmyard manure treatments at 4 t C ha−1 yr−1, respectively. Adding Calliandra or Tithonia at 4 t C ha−1 yr−1 limited the loss of SOC contents to about 24 % of initial SOC, while the addition of sawdust, maize stover (in three of the four sites) and sole mineral N addition show

Published
2023

10. Soil multifunctionality : Synergies and trade-offs across European climatic zones and land uses

Author

Zwetsloot, Marie J., van Leeuwen, Jeroen, Hemerik, Lia, Martens, Henk, Simó Josa, Iolanda, Van de Broek, Marijn, Debeljak, Marko, Rutgers, Michiel, Sandén, Taru, Wall, David P., Jones, Arwyn, Creamer, Rachel E., Zwetsloot, Marie J., van Leeuwen, Jeroen, Hemerik, Lia, Martens, Henk, Simó Josa, Iolanda, Van de Broek, Marijn, Debeljak, Marko, Rutgers, Michiel, Sandén, Taru, Wall, David P., Jones, Arwyn, and Creamer, Rachel E.

Abstract

With increasing societal demands for food security and environmental sustainability on land, the question arises: to what extent do synergies and trade-offs exist between soil functions and how can they be measured across Europe? To address this challenge, we followed the functional land management approach and assessed five soil functions: primary productivity, water regulation and purification, climate regulation, soil biodiversity and nutrient cycling. Soil, management and climate data were collected from 94 sites covering 13 countries, five climatic zones and two land-use types (arable and grassland). This dataset was analysed using the Soil Navigator, a multicriteria decision support system developed to assess the supply of the five soil functions simultaneously. Most sites scored high for two to three soil functions, demonstrating that managing for multifunctionality in soil is possible but that local constraints and trade-offs do exist. Nutrient cycling, biodiversity and climate regulation were less frequently delivered at high capacity than the other two soil functions. Using correlation and co-occurrence analyses, we also found that synergies and trade-offs between soil functions vary among climatic zones and land-use types. This study provides a new framework for monitoring soil quality at the European scale where both the supply of soil functions and their interactions are considered. Highlights: Managing and monitoring soil multifunctionality across Europe is possible. Synergies and trade-offs between soil functions exist, making it difficult to maximize the supply of all five soil functions simultaneously. Synergies and trade-offs between soil functions vary by climatic zone and land-use type. Climate regulation, biodiversity and nutrient cycling are less frequently delivered at high capacity.

Published
2021

11. The soil organic carbon stabilization potential of old and new wheat cultivars: a ¹³CO₂-labeling study

Author

Van de Broek, Marijn; https://orcid.org/0000-0002-6993-7825, Ghiasi, Shiva, Decock, Charlotte, Hund, Andreas; https://orcid.org/0000-0002-2309-1625, Abiven, Samuel, Friedli, Cordula, Werner, Roland A; https://orcid.org/0000-0002-4117-1346, Six, Johan, Van de Broek, Marijn; https://orcid.org/0000-0002-6993-7825, Ghiasi, Shiva, Decock, Charlotte, Hund, Andreas; https://orcid.org/0000-0002-2309-1625, Abiven, Samuel, Friedli, Cordula, Werner, Roland A; https://orcid.org/0000-0002-4117-1346, and Six, Johan

Abstract

Over the past decades, average global wheat yields have increased by about 250 %, mainly due to the cultivation of high-yielding wheat cultivars. This selection process not only affected aboveground parts of plants, but in some cases also reduced root biomass, with potentially large consequences for the amount of organic carbon (OC) transferred to the soil. To study the effect of wheat breeding for high-yielding cultivars on subsoil OC dynamics, two old and two new wheat cultivars from the Swiss wheat breeding program were grown for one growing season in 1.5 m deep lysimeters and pulse labeled with ¹³CO₂ to quantify the amount of assimilated carbon that was transferred belowground and can potentially be stabilized in the soil. The results show that although the old wheat cultivars with higher root biomass transferred more assimilated carbon belowground compared to more recent cultivars, no significant differences in net rhizodeposition were found between the different cultivars. As a consequence, the long-term effect of wheat cultivar selection on soil organic carbon (SOC) stocks will depend on the amount of root biomass that is stabilized in the soil. Our results suggest that the process of wheat selection for high-yielding cultivars resulted in lower amounts of belowground carbon translocation, with potentially important effects on SOC stocks. Further research is necessary to quantify the long-term importance of this effect.

Published
2020

12. Land use impacts on soil erosion and rejuvenation in Southern Brazil

Author

UCL - SST/ELI/ELIC - Earth & Climate, UCL - SST/ELI/ELIE - Environmental Sciences, Vanacker, Veerle, Ameijeiras Mariño, Yolanda, Schoonejans, Jerome, Cornelis, Jean-Thomas, Minella, Jean, Lamouline, Florence, Vermeire, Marie-Liesse, Campforts, Benjamin, Robinet, Jeremy, Van de Broek, Marijn, Delmelle, Pierre, Opfergelt, Sophie, UCL - SST/ELI/ELIC - Earth & Climate, UCL - SST/ELI/ELIE - Environmental Sciences, Vanacker, Veerle, Ameijeiras Mariño, Yolanda, Schoonejans, Jerome, Cornelis, Jean-Thomas, Minella, Jean, Lamouline, Florence, Vermeire, Marie-Liesse, Campforts, Benjamin, Robinet, Jeremy, Van de Broek, Marijn, Delmelle, Pierre, and Opfergelt, Sophie

Abstract

Topography is one of the key factors controlling soil erosion and redistribution of pedogenic material along slope. Land cover change can have an accelerating or retarding impact on topographically-controlled soil erosion rates, depending on the type and intensity of land use and management. In this study, we investigated the combined effect of hillslope gradient and land cover change on soil redistribution and rejuvenation in a subtropical region where Atlantic rain forest was converted to agricultural land. We used a two by two design, and evaluated the effect of hillslope gradient (steep vs. gentle) and land cover (forest vs. cropland) on the spatial pattern of soil weathering degree along slope. In four soil toposequences, soil weathering indices (Total Reserve in Bases, Chemical Index of Alteration, clay content, iron oxide content) and mineralogical assemblages were used to express the soil physico-chemical and mineralogical properties of the soil profiles. Our data showed that the spatial differentiation in chemical weathering degree along slope is strongly dependent on the hillslope gradient, with no to very limited differentiation in chemical weathering degree along the two gentle slopes and a clear differentiation along the steep slopes. Besides, there is an interaction effect between hillslope gradient and land cover. Forest conversion to cropland enhances erosion-driven soil redistribution with a marked effect on soil rejuvenation along steep slopes but no clear effect along gentle slopes. The comparative study based on four toposequences highlights that accelerated soil erosion after conversion of forests to cropland further enhanced lateral soil fluxes and redistribution of topsoil material along steep slopes, and led to soil rejuvenation and exposure of less weathered soil material at the eroding sites.

Published
2019

13. Assessing the Climate Regulation Potential of Agricultural Soils Using a Decision Support Tool Adapted to Stakeholders' Needs and Possibilities

Author

Van de Broek, Marijn, Henriksen, Christian Bugge, Ghaley, Bhim Bahadur, Lugato, Emanuele, Kuzmanovski, Vladimir, Trajanov, Aneta, Debeljak, Marko, Sandén, Taru, Spiegel, Heide, Decock, Charlotte, Creamer, Rachel, Six, Johan, Van de Broek, Marijn, Henriksen, Christian Bugge, Ghaley, Bhim Bahadur, Lugato, Emanuele, Kuzmanovski, Vladimir, Trajanov, Aneta, Debeljak, Marko, Sandén, Taru, Spiegel, Heide, Decock, Charlotte, Creamer, Rachel, and Six, Johan

Abstract

Soils perform many functions that are vital to societies, among which their capability to regulate global climate has received much attention over the past decades. An assessment of the extent to which soils perform a specific function is not only important to appropriately value their current capacity, but also to make well-informed decisions about how and where to change soil management to align the delivered soil functions with societal demands. To obtain an overview of the capacity of soils to perform different functions, accurate and easy-to-use models are necessary. A problem with most currently-available models is that data requirements often exceed data availability, while generally a high level of expert knowledge is necessary to apply these models. Therefore, we developed a qualitative model to assess how agricultural soils function with respect to climate regulation. The model is driven by inputs about agricultural management practices, soil properties and environmental conditions. To reduce data requirements on stakeholders, the 17 input variables are classified into either (1) three classes: low, medium and high or (2) the presence or absence of a management practice. These inputs are combined using a decision tree with internal integration rules to obtain an estimate of the magnitude of N2O emissions and carbon sequestration. These two variables are subsequently combined into an estimate of the capacity of a soil to perform the climate regulation function. The model was tested using data from long-term field experiments across Europe. This showed that the model is generally able to adequately assess this soil function across a range of environments under different management practices. In a next step, this model will be combined with models to assess other soil functions (soil biodiversity, primary productivity, nutrient cycling and water regulation and purification). This will allow the assessment of trade-offs between these soil functio

Published
2019

14. A Field-Scale Decision Support System for Assessment and Management of Soil Functions

Author

Debeljak, Marko, Trajanov, Aneta, Kuzmanovski, Vladimir, Schröder, Jaap, Sandén, Taru, Spiegel, Heide, Wall, David P., Van de Broek, Marijn, Rutgers, Michiel, Bampa, Francesca, Creamer, Rachel E., Henriksen, Christian B., Debeljak, Marko, Trajanov, Aneta, Kuzmanovski, Vladimir, Schröder, Jaap, Sandén, Taru, Spiegel, Heide, Wall, David P., Van de Broek, Marijn, Rutgers, Michiel, Bampa, Francesca, Creamer, Rachel E., and Henriksen, Christian B.

Abstract

Agricultural decision support systems (DSSs) are mostly focused on increasing the supply of individual soil functions such as, e.g., primary productivity or nutrient cycling, while neglecting other important soil functions, such as, e.g., water purification and regulation, climate regulation and carbon sequestration, soil biodiversity, and habitat provision. Making right management decisions for long-term sustainability is therefore challenging, and farmers and farm advisors would greatly benefit from an evidence-based DSS targeted for assessing and improving the supply of several soil functions simultaneously. To address this need, we designed the Soil Navigator DSS by applying a qualitative approach to multi-criteria decision modeling using Decision Expert (DEX) integrative methodology. Multi-criteria decision models for the five main soil functions were developed, calibrated, and validated using knowledge of involved domain experts and knowledge extracted from existing datasets by data mining. Subsequently, the five DEX models were integrated into a DSS to assess the soil functions simultaneously and to provide management advices for improving the performance of prioritized soil functions. To enable communication between the users and the DSS, we developed a user-friendly computer-based graphical user interface, which enables users to provide the required data regarding their field to the DSS and to get textual and graphical results about the performance of each of the five soil functions in a qualitative way. The final output from the DSS is a list of soil mitigation measures that the end-users could easily apply in the field in order to achieve the desired soil function performance. The Soil Navigator DSS has a great potential to complement the Farm Sustainability Tools for Nutrients included in the Common Agricultural Policy 2021–2027 proposal adopted by the European Commission. The Soil Navigator has also a potential to be spatially upgraded to assist deci

Published
2019

15. Assessing the climate regulation potential of Agricultural soils using a decision support tool adapted to stakeholders' needs and possibilities

Author

Van de Broek, Marijn, Henriksen, Christian Bugge, Ghaley, Bhim Bahadur, Lugato, Emanuele, Kuzmanovski, Vladimir, Trajanov, Aneta, Debeljak, Marko, Sandén, Taru, Spiegel, Heide, Decock, Charlotte, Creamer, Rachel, Six, Johan, Van de Broek, Marijn, Henriksen, Christian Bugge, Ghaley, Bhim Bahadur, Lugato, Emanuele, Kuzmanovski, Vladimir, Trajanov, Aneta, Debeljak, Marko, Sandén, Taru, Spiegel, Heide, Decock, Charlotte, Creamer, Rachel, and Six, Johan

Abstract

Soils perform many functions that are vital to societies, among which their capability to regulate global climate has received much attention over the past decades. An assessment of the extent to which soils perform a specific function is not only important to appropriately value their current capacity, but also to make well-informed decisions about how and where to change soil management to align the delivered soil functions with societal demands. To obtain an overview of the capacity of soils to perform different functions, accurate and easy-to-use models are necessary. A problem with most currently-available models is that data requirements often exceed data availability, while generally a high level of expert knowledge is necessary to apply these models. Therefore, we developed a qualitative model to assess how agricultural soils function with respect to climate regulation. The model is driven by inputs about agricultural management practices, soil properties and environmental conditions. To reduce data requirements on stakeholders, the 17 input variables are classified into either (1) three classes: low, medium and high or (2) the presence or absence of a management practice. These inputs are combined using a decision tree with internal integration rules to obtain an estimate of the magnitude of N2O emissions and carbon sequestration. These two variables are subsequently combined into an estimate of the capacity of a soil to perform the climate regulation function. The model was tested using data from long-term field experiments across Europe. This showed that the model is generally able to adequately assess this soil function across a range of environments under different management practices. In a next step, this model will be combined with models to assess other soil functions (soil biodiversity, primary productivity, nutrient cycling and water regulation and purification). This will allow the assessment of trade-offs between these soil functions for agricul

Published
2019

16. A Field-Scale Decision Support System for Assessment and Management of Soil Functions

Author

Debeljak, Marko, Trajanov, Aneta, Kuzmanovski, Vladimir, Schroder, J.J., Sandén, Taru, Spiegel, Heide, Wall, David, van de Broek, Marijn, Rutgers, Michiel, Bampa, Francesca, Creamer, Rachel, Henriksen, Christian Bugge, Debeljak, Marko, Trajanov, Aneta, Kuzmanovski, Vladimir, Schroder, J.J., Sandén, Taru, Spiegel, Heide, Wall, David, van de Broek, Marijn, Rutgers, Michiel, Bampa, Francesca, Creamer, Rachel, and Henriksen, Christian Bugge

Abstract

Agricultural decision support systems (DSS) are mostly focused on increasing the supply of individual soil functions such as e.g. primary productivity or nutrient cycling, while neglecting other important soil functions, such as e.g. water purification and regulation, climate regulation and carbon sequestration, soil biodiversity and habitat provision. Making right management decisions for long-term sustainability is therefore challenging, and farmers and farm advisors would greatly benefit from an evidence-based DSS targeted for assessing and improving the supply of several soil functions simultaneously. To address this, need we designed the Soil Navigator DSS by applying a qualitative approach to multi criteria decision modelling using Decision Expert (DEX) integrative methodology. Multi-criteria decision models for the five main soil functions were developed, calibrated and validated using knowledge of involved domain experts and knowledge extracted from existing datasets by data mining. Subsequently, the five DEX models were integrated into a DSS to assess the soil functions simultaneously, and to provide management advises for improving the performance of prioritized soil functions. To enable communication between the users and the DSS, we developed a user-friendly computer-based graphical user interface, which enables users to provide the required data regarding their field to the DSS and to get textual and graphical results about the performance of each of the five soil functions in a qualitative way. The final output from the DSS is a list of soil mitigation measures that the end-users could easily apply in the field in order to achieve the desired soil function performance. The Soil Navigator DSS has a great potential to complement the Farm Sustainability Tools for Nutrients included in the Common Agricultural Policy 2021-2027 proposal adopted by the European Commission. The Soil Navigator has also a potential to be spatially upgraded to assist decisions on

Published
2019

17. A Field-Scale Decision Support System for Assessment and Management of Soil Functions

Author

Debeljak, Marko, Trajanov, Aneta, Kuzmanovski, Vladimir, Schröder, Jaap, Sandén, Taru, Spiegel, Heide, Wall, David P., Van de Broek, Marijn, Rutgers, Michiel, Bampa, Francesca, Creamer, Rachel E., Henriksen, Christian B., Debeljak, Marko, Trajanov, Aneta, Kuzmanovski, Vladimir, Schröder, Jaap, Sandén, Taru, Spiegel, Heide, Wall, David P., Van de Broek, Marijn, Rutgers, Michiel, Bampa, Francesca, Creamer, Rachel E., and Henriksen, Christian B.

Abstract

Agricultural decision support systems (DSSs) are mostly focused on increasing the supply of individual soil functions such as, e.g., primary productivity or nutrient cycling, while neglecting other important soil functions, such as, e.g., water purification and regulation, climate regulation and carbon sequestration, soil biodiversity, and habitat provision. Making right management decisions for long-term sustainability is therefore challenging, and farmers and farm advisors would greatly benefit from an evidence-based DSS targeted for assessing and improving the supply of several soil functions simultaneously. To address this need, we designed the Soil Navigator DSS by applying a qualitative approach to multi-criteria decision modeling using Decision Expert (DEX) integrative methodology. Multi-criteria decision models for the five main soil functions were developed, calibrated, and validated using knowledge of involved domain experts and knowledge extracted from existing datasets by data mining. Subsequently, the five DEX models were integrated into a DSS to assess the soil functions simultaneously and to provide management advices for improving the performance of prioritized soil functions. To enable communication between the users and the DSS, we developed a user-friendly computer-based graphical user interface, which enables users to provide the required data regarding their field to the DSS and to get textual and graphical results about the performance of each of the five soil functions in a qualitative way. The final output from the DSS is a list of soil mitigation measures that the end-users could easily apply in the field in order to achieve the desired soil function performance. The Soil Navigator DSS has a great potential to complement the Farm Sustainability Tools for Nutrients included in the Common Agricultural Policy 2021–2027 proposal adopted by the European Commission. The Soil Navigator has also a potential to be spatially upgraded to assist deci

Published
2019

18. Assessing the Climate Regulation Potential of Agricultural Soils Using a Decision Support Tool Adapted to Stakeholders' Needs and Possibilities

Author

Van de Broek, Marijn, Henriksen, Christian Bugge, Ghaley, Bhim Bahadur, Lugato, Emanuele, Kuzmanovski, Vladimir, Trajanov, Aneta, Debeljak, Marko, Sandén, Taru, Spiegel, Heide, Decock, Charlotte, Creamer, Rachel, Six, Johan, Van de Broek, Marijn, Henriksen, Christian Bugge, Ghaley, Bhim Bahadur, Lugato, Emanuele, Kuzmanovski, Vladimir, Trajanov, Aneta, Debeljak, Marko, Sandén, Taru, Spiegel, Heide, Decock, Charlotte, Creamer, Rachel, and Six, Johan

Abstract

Soils perform many functions that are vital to societies, among which their capability to regulate global climate has received much attention over the past decades. An assessment of the extent to which soils perform a specific function is not only important to appropriately value their current capacity, but also to make well-informed decisions about how and where to change soil management to align the delivered soil functions with societal demands. To obtain an overview of the capacity of soils to perform different functions, accurate and easy-to-use models are necessary. A problem with most currently-available models is that data requirements often exceed data availability, while generally a high level of expert knowledge is necessary to apply these models. Therefore, we developed a qualitative model to assess how agricultural soils function with respect to climate regulation. The model is driven by inputs about agricultural management practices, soil properties and environmental conditions. To reduce data requirements on stakeholders, the 17 input variables are classified into either (1) three classes: low, medium and high or (2) the presence or absence of a management practice. These inputs are combined using a decision tree with internal integration rules to obtain an estimate of the magnitude of N2O emissions and carbon sequestration. These two variables are subsequently combined into an estimate of the capacity of a soil to perform the climate regulation function. The model was tested using data from long-term field experiments across Europe. This showed that the model is generally able to adequately assess this soil function across a range of environments under different management practices. In a next step, this model will be combined with models to assess other soil functions (soil biodiversity, primary productivity, nutrient cycling and water regulation and purification). This will allow the assessment of trade-offs between these soil functio

Published
2019

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