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3. CropPol : A dynamic, open and global database on crop pollination

Author

Allen-Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts-Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra-Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., de Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A. M., Stanley, Dara A., Zaragoza-Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A. N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., da Silva, Fabiana Oliveira, Willcox, Bryony, Ramos, Davi L., da Silva e Silva, Felipe D., Lázaro, Amparo, Alomar, David, González-Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P. D., Jodar, Diego N. Nabaes, Stewart, Rebecca I. A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H., Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L. W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Chan, D. Susan Willis, Chacoff, Natacha, Andersson, Georg K. S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J. J. A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H., Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A., Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero-Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan-Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega-Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M., Woyciechowski, Michał, Nunes-Silva, Patrícia, de Oliveira, Rosana Halinski, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., García, Fermín José Chamorro, Parra, Guiomar Nates, Pigozo, Camila Magalhães, and Bartomeus, Ignasi

Published
2022

5. Untangling the plant reproductive success of changing community composition and pollinator foraging choices.

Author

Allen‐Perkins, Alfonso, Artamendi, Maddi, Montoya, Daniel, Rubio, Encarnación, and Magrach, Ainhoa

Subjects
*PLANT competition, *BIOLOGICAL fitness, *POLLINATORS, *PLANT species diversity, *FLOWERING of plants, *FLORAL morphology
Abstract

Pollinator choices when selecting flowers for nectar or pollen collection are crucial in determining the effectiveness of pollination services provided to plants. From the plant's perspective, this effectiveness is a phenomenon shaped by factors at both the species‐ (e.g. pollinator density and flower morphology) and community‐level, including pollinator diversity and plant competition for pollinators. At the species level, individual pollinator effectiveness is influenced by foraging choices, plant identity, and the resulting pollen flow within and between plant species. In natural ecosystems, these species coexist within a complex community, where various interactions can modify foraging choices and alter pollen flows, giving rise to community‐level effectiveness, a less explored aspect of pollinator effectiveness. This study investigates the drivers of individual pollinator foraging choices across two study areas and two flowering seasons. It also assesses the community‐level effectiveness of pollination services received by different plant species, considering indirect interactions between plants through shared pollinators and evaluating their impact on plant reproductive success. Our results show that the determinants of pollinator foraging choices are consistent across different habitats, with floral constancy and flower abundance playing pivotal roles across all species and sites. Foraging choices can shift throughout the flowering season as plant and pollinator composition changes, significantly impacting pollination effectiveness. The overlap in pollination service use by individuals of the same plant species decreases their fruit set, whereas sharing pollinator services with individuals of other plant species increases fruit set. Our results support significant, positive biodiversity–ecosystem functioning associations driven by both plant and pollinator species richness, suggesting that the overlap in pollination service use by different plant species fosters facilitative interactions rather than competition. This is likely influenced by more stable pollination supplies under high plant species diversity conditions and the existence of mechanisms to mitigate the negative impacts of heterospecific pollen deposition. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Multilayer diffusion networks as a tool to assess the structure and functioning of fine grain sub‐specific plant–pollinator networks.

Author

Allen‐Perkins, Alfonso, Hurtado, María, García‐Callejas, David, Godoy, Oscar, and Bartomeus, Ignasi

Subjects
*BIOTIC communities, *POLLEN, *PLANT species, *MODULAR construction, *MODULAR forms
Abstract

Interaction networks are a widely used tool to understand the dynamics of plant–pollinator ecological communities. However, while most mutualistic networks have been defined at the species level, ecological processes such as pollination take place at different scales, including the individual or patch levels. Yet, current approaches studying fine‐grain sub‐specific plant–pollinator networks only account for interactions among nodes belonging to a single plant species due to the conceptual and mathematical limitations of modeling simultaneously several plant species each composed of several nodes. Here, we introduce a multilayer diffusion network framework that allows modeling simple diffusion processes between nodes pertaining to the same or different layers (i.e. species). It is designed to depict from the network structure the potential conspecific and heterospecific pollen flows among plant individuals or patches. This potential pollen flow is modeled as a transport‐like system, in which pollen grain movements are represented as random‐walkers that diffuse on an ensemble of bipartite layers of conspecific plants and their shared pollinators. We exemplify this physical conceptualization using a dataset of nine fine‐grain sub‐specific plant–pollinator networks from a Mediterranean grassland of annual plants, where plant nodes represent groups of conspecifics within patches of 1 m2. The diffusion networks show pollinators effectively connecting sets of patches of the same and different plant species, forming a modular structure. Interestingly, different properties of the network structure, such as the conspecific pollen arrival probability and the number of conspecific subgraphs in which plants are embedded, are critical for the seed production of different plant species. We provide a simple but robust set of metrics to calculate potential pollen flow and scale down network ecology to functioning properties at the individual or patch level, where most ecological processes take place, hence moving forward the description and interpretation of species‐rich communities across scales. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Pollination supply models from a local to global scale

Author

Giménez-García, Angel, primary, Allen-Perkins, Alfonso, additional, Bartomeus, Ignasi, additional, Balbi, Stefano, additional, Knapp, Jessica L., additional, Hevia, Violeta, additional, Woodcock, Ben Alex, additional, Smagghe, Guy, additional, Miñarro, Marcos, additional, Eeraerts, Maxime, additional, Colville, Jonathan F., additional, Hipólito, Juliana, additional, Cavigliasso, Pablo, additional, Nates-Parra, Guiomar, additional, Herrera, José M., additional, Cusser, Sarah, additional, Simmons, Benno I., additional, Wolters, Volkmar, additional, Jha, Shalene, additional, Freitas, Breno M., additional, Horgan, Finbarr G., additional, Artz, Derek R., additional, Sidhu, C. Sheena, additional, Otieno, Mark, additional, Boreux, Virginie, additional, Biddinger, David J., additional, Klein, Alexandra-Maria, additional, Joshi, Neelendra K., additional, Stewart, Rebecca I. A., additional, Albrecht, Matthias, additional, Nicholson, Charlie C., additional, O'Reilly, Alison D., additional, Crowder, David William, additional, Burns, Katherine L. W., additional, Nabaes Jodar, Diego Nicolás, additional, Garibaldi, Lucas Alejandro, additional, Sutter, Louis, additional, Dupont, Yoko L., additional, Dalsgaard, Bo, additional, da Encarnação Coutinho, Jeferson Gabriel, additional, Lázaro, Amparo, additional, Andersson, Georg K. S., additional, Raine, Nigel E., additional, Krishnan, Smitha, additional, Dainese, Matteo, additional, van der Werf, Wopke, additional, Smith, Henrik G., additional, and Magrach, Ainhoa, additional

Published
2023
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8. Pollination supply models from a local to global scale

Author

Giménez-García, Angel, Allen-Perkins, Alfonso, Bartomeus, Ignasi, Balbi, Stefano, Knapp, Jessica L., Hevia, Violeta, Woodcock, Ben Alex, Smagghe, Guy, Miñarro, Marcos, Eeraerts, Maxime, Colville, Jonathan F., Hipólito, Juliana, Cavigliasso, Pablo, Nates-Parra, Guiomar, Herrera, José M., Cusser, Sarah, Simmons, Benno I., Wolters, Volkmar, Jha, Shalene, Freitas, Breno M., Horgan, Finbarr G., Artz, Derek R., Sidhu, C. Sheena, Otieno, Mark, Boreux, Virginie, Biddinger, David J., Klein, Alexandra-Maria, Joshi, Neelendra K., Stewart, Rebecca I.A., Albrecht, Matthias, Nicholson, Charlie C., O'Reilly, Alison D., Crowder, David William, Burns, Katherine L.W., Nabaes Jodar, Diego Nicolás, Garibaldi, Lucas Alejandro, Sutter, Louis, Dupont, Yoko L., Dalsgaard, Bo, da Encarnação Coutinho, Jeferson Gabriel, Lázaro, Amparo, Andersson, Georg K.S., Raine, Nigel E., Krishnan, Smitha, Dainese, Matteo, van der Werf, Wopke, Smith, Henrik G., Magrach, Ainhoa, Giménez-García, Angel, Allen-Perkins, Alfonso, Bartomeus, Ignasi, Balbi, Stefano, Knapp, Jessica L., Hevia, Violeta, Woodcock, Ben Alex, Smagghe, Guy, Miñarro, Marcos, Eeraerts, Maxime, Colville, Jonathan F., Hipólito, Juliana, Cavigliasso, Pablo, Nates-Parra, Guiomar, Herrera, José M., Cusser, Sarah, Simmons, Benno I., Wolters, Volkmar, Jha, Shalene, Freitas, Breno M., Horgan, Finbarr G., Artz, Derek R., Sidhu, C. Sheena, Otieno, Mark, Boreux, Virginie, Biddinger, David J., Klein, Alexandra-Maria, Joshi, Neelendra K., Stewart, Rebecca I.A., Albrecht, Matthias, Nicholson, Charlie C., O'Reilly, Alison D., Crowder, David William, Burns, Katherine L.W., Nabaes Jodar, Diego Nicolás, Garibaldi, Lucas Alejandro, Sutter, Louis, Dupont, Yoko L., Dalsgaard, Bo, da Encarnação Coutinho, Jeferson Gabriel, Lázaro, Amparo, Andersson, Georg K.S., Raine, Nigel E., Krishnan, Smitha, Dainese, Matteo, van der Werf, Wopke, Smith, Henrik G., and Magrach, Ainhoa

Abstract

Ecological intensification has been embraced with great interest by the academic sector but is still rarely taken up by farmers because monitoring the state of different ecological functions is not straightforward. Modelling tools can represent a more accessible alternative of measuring ecological functions, which could help promote their use amongst farmers and other decision-makers. In the case of crop pollination, modelling has traditionally followed either a mechanistic or a data-driven approach. Mechanistic models simulate the habitat preferences and foraging behaviour of pollinators, while data-driven models associate georeferenced variables with real observations. Here, we test these two approaches to predict pollination supply and validate these predictions using data from a newly released global dataset on pollinator visitation rates to different crops. We use one of the most extensively used models for the mechanistic approach, while for the data-driven approach, we select from among a comprehensive set of state-of-the-art machine-learning models. Moreover, we explore a mixed approach, where data-derived inputs, rather than expert assessment, inform the mechanistic model. We find that, at a global scale, machine-learning models work best, offering a rank correlation coefficient between predictions and observations of pollinator visitation rates of 0.56. In turn, the mechanistic model works moderately well at a global scale for wild bees other than bumblebees. Biomes characterized by temperate or Mediterranean forests show a better agreement between mechanistic model predictions and observations, probably due to more comprehensive ecological knowledge and therefore better parameterization of input variables for these biomes. This study highlights the challenges of transferring input variables across multiple biomes, as expected given the different composition of species in different biomes. Our results provide clear guidance on which pollination supply mode

Published
2023

9. Pollination supply models from a local to global scale

Author

Agencia Estatal de Investigación (España), Eusko Jaurlaritza, Comunidad de Madrid, European Commission, Universidad Politécnica de Madrid, Research Foundation - Flanders, Ministerio de Economía y Competitividad (España), Ministerio de Universidades (España), Fundação para a Ciência e a Tecnologia (Portugal), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil), Department of Agriculture (US), German Research Foundation, Irish Research Council, Swedish Research Council, Giménez-García, Ángel, Allen-Perkins, Alfonso, Bartomeus, Ignasi, Balbi, Stefano, Knapp, Jessica L., Hevia, Violeta, Woodcock, Ben Alex, Smagghe, Guy, Miñarro, Marcos, Eeraerts, Maxime, Colville, Jonathan F., Hipólito, Juliana, Cavigliasso, Pablo, Nates-Parra, Guiomar, Herrera, José M., Cusser, Sarah, Simmons, Benno I., Wolters, Volkmar, Jha, Shalene, Freitas, Breno M., Horgan, Finbarr G., Artz, Derek R., Sidhu, C. Sheena, Otieno, Mark, Boreux, Virginie, Biddinger, David J., Klein, Alexandra Maria, Joshi, Neelendra K., Stewart, Rebecca I.A., Albrecht, Matthias, Nicholson, Charlie C., O'Reilly, Alison D., Crowder, David William, Burns, Katherine L.W., Nabaes Jodar, Diego Nicolás, Garibaldi, Lucas Alejandro, Sutter, Louis, Dupont, Yoko L., Dalsgaard, Bo, Da Encarnação Coutinho, Jeferson Gabriel, Lázaro, Amparo, Andersson, Georg K. S., Raine, Nigel E., Krishnan, Smitha, Dainese, Matteo, Van Der Werf, Wopke, Smith, Henrik G., Magrach, Ainhoa, Agencia Estatal de Investigación (España), Eusko Jaurlaritza, Comunidad de Madrid, European Commission, Universidad Politécnica de Madrid, Research Foundation - Flanders, Ministerio de Economía y Competitividad (España), Ministerio de Universidades (España), Fundação para a Ciência e a Tecnologia (Portugal), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil), Department of Agriculture (US), German Research Foundation, Irish Research Council, Swedish Research Council, Giménez-García, Ángel, Allen-Perkins, Alfonso, Bartomeus, Ignasi, Balbi, Stefano, Knapp, Jessica L., Hevia, Violeta, Woodcock, Ben Alex, Smagghe, Guy, Miñarro, Marcos, Eeraerts, Maxime, Colville, Jonathan F., Hipólito, Juliana, Cavigliasso, Pablo, Nates-Parra, Guiomar, Herrera, José M., Cusser, Sarah, Simmons, Benno I., Wolters, Volkmar, Jha, Shalene, Freitas, Breno M., Horgan, Finbarr G., Artz, Derek R., Sidhu, C. Sheena, Otieno, Mark, Boreux, Virginie, Biddinger, David J., Klein, Alexandra Maria, Joshi, Neelendra K., Stewart, Rebecca I.A., Albrecht, Matthias, Nicholson, Charlie C., O'Reilly, Alison D., Crowder, David William, Burns, Katherine L.W., Nabaes Jodar, Diego Nicolás, Garibaldi, Lucas Alejandro, Sutter, Louis, Dupont, Yoko L., Dalsgaard, Bo, Da Encarnação Coutinho, Jeferson Gabriel, Lázaro, Amparo, Andersson, Georg K. S., Raine, Nigel E., Krishnan, Smitha, Dainese, Matteo, Van Der Werf, Wopke, Smith, Henrik G., and Magrach, Ainhoa

Abstract

Ecological intensification has been embraced with great interest by the academic sector but is still rarely taken up by farmers because monitoring the state of different ecological functions is not straightforward. Modelling tools can represent a more accessible alternative of measuring ecological functions, which could help promote their use amongst farmers and other decision-makers. In the case of crop pollination, modelling has traditionally followed either a mechanistic or a data-driven approach. Mechanistic models simulate the habitat preferences and foraging behaviour of pollinators, while data-driven models associate georeferenced variables with real observations. Here, we test these two approaches to predict pollination supply and validate these predictions using data from a newly released global dataset on pollinator visitation rates to different crops. We use one of the most extensively used models for the mechanistic approach, while for the data-driven approach, we select from among a comprehensive set of state-of-The-Art machine-learning models. Moreover, we explore a mixed approach, where data-derived inputs, rather than expert assessment, inform the mechanistic model. We find that, at a global scale, machine-learning models work best, offering a rank correlation coefficient between predictions and observations of pollinator visitation rates of 0.56. In turn, the mechanistic model works moderately well at a global scale for wild bees other than bumblebees. Biomes characterized by temperate or Mediterranean forests show a better agreement between mechanistic model predictions and observations, probably due to more comprehensive ecological knowledge and therefore better parameterization of input variables for these biomes. This study highlights the challenges of transferring input variables across multiple biomes, as expected given the different composition of species in different biomes. Our results provide clear guidance on which pollination supply mode

Published
2023

12. Structural asymmetry in biotic interactions as a tool to understand and predict ecological persistence.

Author

Allen‐Perkins, Alfonso, García‐Callejas, David, Bartomeus, Ignasi, and Godoy, Oscar

Subjects
*NUMBERS of species, *ECOSYSTEMS, *EMPIRICAL research, *NUMBER systems, *POPULATION dynamics
Abstract

A universal feature of ecological systems is that species do not interact with others with the same sign and strength. Yet, the consequences of this asymmetry in biotic interactions for the short‐ and long‐term persistence of individual species and entire communities remains unclear. Here, we develop a set of metrics to evaluate how asymmetric interactions among species translate to asymmetries in their individual vulnerability to extinction under changing environmental conditions. These metrics, which solve previous limitations of how to independently quantify the size from the shape of the so‐called feasibility domain, provide rigorous advances to understand simultaneously why some species and communities present more opportunities to persist than others. We further demonstrate that our shape‐related metrics are useful to predict short‐term changes in species' relative abundances during 7 years in a Mediterranean grassland. Our approach is designed to be applied to any ecological system regardless of the number of species and type of interactions. With it, we show that is possible to obtain both mechanistic and predictive information on ecological persistence for individual species and entire communities, paving the way for a stronger integration of theoretical and empirical research. [ABSTRACT FROM AUTHOR]

Published
2023
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14. Non‐random interactions within and across guilds shape the potential to coexist in multi‐trophic ecological communities.

Author

García‐Callejas, David, Godoy, Oscar, Buche, Lisa, Hurtado, María, Lanuza, Jose B., Allen‐Perkins, Alfonso, and Bartomeus, Ignasi

Subjects
BIOTIC communities, COEXISTENCE of species, COMMUNITIES, GUILDS
Abstract

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic guilds. However, we lack empirical evaluations of how the structure, strength and sign of biotic interactions drive the potential to coexist in diverse multi‐trophic communities. Here, we model community feasibility domains, a theoretically informed measure of multi‐species coexistence probability, from grassland communities comprising more than 45 species on average from three trophic guilds (plants, pollinators and herbivores). Contrary to our hypothesis, increasing community complexity, measured either as the number of guilds or community richness, did not decrease community feasibility. Rather, we observed that high degrees of species self‐regulation and niche partitioning allow for maintaining larger levels of community feasibility and higher species persistence in more diverse communities. Our results show that biotic interactions within and across guilds are not random in nature and both structures significantly contribute to maintaining multi‐trophic diversity. [ABSTRACT FROM AUTHOR]

Published
2023
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15. CropPol:A dynamic, open and global database on crop pollination

Author

Allen‐Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts‐Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra‐Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A. M., Stanley, Dara A., Zaragoza‐Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A. N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., Oliveira da Silva, Fabiana, Willcox, Bryony, Ramos, Davi L., D. da Silva e Silva, Felipe, Lázaro, Amparo, Alomar, David, González‐Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P. D., Nabaes Jodar, Diego N., Stewart, Rebecca I. A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H., Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L. W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Willis Chan, D. Susan, Chacoff, Natacha, Andersson, Georg K. S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J. J. A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H., Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A., Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero‐Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan‐Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega‐Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M., Woyciechowski, Michał, Nunes‐Silva, Patrícia, Halinski de Oliveira, Rosana, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., Chamorro García, Fermín José, Nates Parra, Guiomar, Magalhães Pigozo, Camila, Bartomeus, Ignasi, Allen‐Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts‐Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra‐Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A. M., Stanley, Dara A., Zaragoza‐Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A. N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., Oliveira da Silva, Fabiana, Willcox, Bryony, Ramos, Davi L., D. da Silva e Silva, Felipe, Lázaro, Amparo, Alomar, David, González‐Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P. D., Nabaes Jodar, Diego N., Stewart, Rebecca I. A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H., Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L. W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Willis Chan, D. Susan, Chacoff, Natacha, Andersson, Georg K. S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J. J. A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H., Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A., Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero‐Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan‐Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega‐Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M., Woyciechowski, Michał, Nunes‐Silva, Patrícia, Halinski de Oliveira, Rosana, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., Chamorro García, Fermín José, Nates Parra, Guiomar, Magalhães Pigozo, Camila, and Bartomeus, Ignasi

Abstract

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e., berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001–2005 (21 studies), 2006–2010 (40), 2011–2015 (88), and 2016–2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this da

Published
2022

16. CropPol:A dynamic, open and global database on crop pollination

Author

Allen-Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts-Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra-Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., de Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A. M., Stanley, Dara A., Zaragoza-Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A.N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., Oliveira da Silva, Fabiana, Willcox, Bryony, Ramos, Davi L., da Silva e Silva, Felipe D., Lázaro, Amparo, Alomar, David, González-Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P. D., Nabaes Jodar, Diego N., Stewart, Rebecca I. A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H, Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L.W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Willis Chan, D. Susan, Chacoff, Natacha, Andersson, Georg K. S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J. J. A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H, Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A, Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero-Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan-Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega-Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M, Woyciechowski, Michał, Nunes-Silva, Patrícia, Halinski de Oliveira, Rosana, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., Chamorro García, Fermín José, Nates Parra, Guiomar, Magalhães Pigozo, Camila, Bartomeus, Ignasi, Allen-Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts-Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra-Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., de Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A. M., Stanley, Dara A., Zaragoza-Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A.N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., Oliveira da Silva, Fabiana, Willcox, Bryony, Ramos, Davi L., da Silva e Silva, Felipe D., Lázaro, Amparo, Alomar, David, González-Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P. D., Nabaes Jodar, Diego N., Stewart, Rebecca I. A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H, Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L.W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Willis Chan, D. Susan, Chacoff, Natacha, Andersson, Georg K. S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J. J. A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H, Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A, Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero-Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan-Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega-Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M, Woyciechowski, Michał, Nunes-Silva, Patrícia, Halinski de Oliveira, Rosana, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., Chamorro García, Fermín José, Nates Parra, Guiomar, Magalhães Pigozo, Camila, and Bartomeus, Ignasi

Abstract

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e., berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001–2005 (21 studies), 2006–2010 (40), 2011–2015 (88), and 2016–2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this

Published
2022

17. CropPol: a dynamic, open and global database on crop pollination

Author

Allen‐Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts‐Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra‐Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A.M., Stanley, Dara A., Zaragoza‐Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A.N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., Silva, Fabiana Oliveira, Willcox, Bryony, Ramos, Davi L., Silva e Silva, Felipe D., Lázaro, Amparo, Alomar, David, González‐Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P.D., Nabaes Jodar, Diego N., Stewart, Rebecca I.A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H., Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L.W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Chan, D. Susan Willis, Chacoff, Natacha, Andersson, Georg K.S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J.J.A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H., Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A., Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero‐Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan‐Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega‐Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M., Woyciechowski, Michał, Nunes‐Silva, Patrícia, Oliveira, Rosana Halinski, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., García, Fermín José Chamorro, Parra, Guiomar Nates, Pigozo, Camila Magalhães, Bartomeus, Ignasi, Allen‐Perkins, Alfonso, Magrach, Ainhoa, Dainese, Matteo, Garibaldi, Lucas A., Kleijn, David, Rader, Romina, Reilly, James R., Winfree, Rachael, Lundin, Ola, McGrady, Carley M., Brittain, Claire, Biddinger, David J., Artz, Derek R., Elle, Elizabeth, Hoffman, George, Ellis, James D., Daniels, Jaret, Gibbs, Jason, Campbell, Joshua W., Brokaw, Julia, Wilson, Julianna K., Mason, Keith, Ward, Kimiora L., Gundersen, Knute B., Bobiwash, Kyle, Gut, Larry, Rowe, Logan M., Boyle, Natalie K., Williams, Neal M., Joshi, Neelendra K., Rothwell, Nikki, Gillespie, Robert L., Isaacs, Rufus, Fleischer, Shelby J., Peterson, Stephen S., Rao, Sujaya, Pitts‐Singer, Theresa L., Fijen, Thijs, Boreux, Virginie, Rundlöf, Maj, Viana, Blandina Felipe, Klein, Alexandra‐Maria, Smith, Henrik G., Bommarco, Riccardo, Carvalheiro, Luísa G., Ricketts, Taylor H., Ghazoul, Jaboury, Krishnan, Smitha, Benjamin, Faye E., Loureiro, João, Castro, Sílvia, Raine, Nigel E., Groot, Gerard Arjen, Horgan, Finbarr G., Hipólito, Juliana, Smagghe, Guy, Meeus, Ivan, Eeraerts, Maxime, Potts, Simon G., Kremen, Claire, García, Daniel, Miñarro, Marcos, Crowder, David W., Pisanty, Gideon, Mandelik, Yael, Vereecken, Nicolas J., Leclercq, Nicolas, Weekers, Timothy, Lindstrom, Sandra A.M., Stanley, Dara A., Zaragoza‐Trello, Carlos, Nicholson, Charlie C., Scheper, Jeroen, Rad, Carlos, Marks, Evan A.N., Mota, Lucie, Danforth, Bryan, Park, Mia, Bezerra, Antônio Diego M., Freitas, Breno M., Mallinger, Rachel E., Silva, Fabiana Oliveira, Willcox, Bryony, Ramos, Davi L., Silva e Silva, Felipe D., Lázaro, Amparo, Alomar, David, González‐Estévez, Miguel A., Taki, Hisatomo, Cariveau, Daniel P., Garratt, Michael P.D., Nabaes Jodar, Diego N., Stewart, Rebecca I.A., Ariza, Daniel, Pisman, Matti, Lichtenberg, Elinor M., Schüepp, Christof, Herzog, Felix, Entling, Martin H., Dupont, Yoko L., Michener, Charles D., Daily, Gretchen C., Ehrlich, Paul R., Burns, Katherine L.W., Vilà, Montserrat, Robson, Andrew, Howlett, Brad, Blechschmidt, Leah, Jauker, Frank, Schwarzbach, Franziska, Nesper, Maike, Diekötter, Tim, Wolters, Volkmar, Castro, Helena, Gaspar, Hugo, Nault, Brian A., Badenhausser, Isabelle, Petersen, Jessica D., Tscharntke, Teja, Bretagnolle, Vincent, Chan, D. Susan Willis, Chacoff, Natacha, Andersson, Georg K.S., Jha, Shalene, Colville, Jonathan F., Veldtman, Ruan, Coutinho, Jeferson, Bianchi, Felix J.J.A., Sutter, Louis, Albrecht, Matthias, Jeanneret, Philippe, Zou, Yi, Averill, Anne L., Saez, Agustin, Sciligo, Amber R., Vergara, Carlos H., Bloom, Elias H., Oeller, Elisabeth, Badano, Ernesto I., Loeb, Gregory M., Grab, Heather, Ekroos, Johan, Gagic, Vesna, Cunningham, Saul A., Åström, Jens, Cavigliasso, Pablo, Trillo, Alejandro, Classen, Alice, Mauchline, Alice L., Montero‐Castaño, Ana, Wilby, Andrew, Woodcock, Ben A., Sidhu, C. Sheena, Steffan‐Dewenter, Ingolf, Vogiatzakis, Ioannis N., Herrera, José M., Otieno, Mark, Gikungu, Mary W., Cusser, Sarah J., Nauss, Thomas, Nilsson, Lovisa, Knapp, Jessica, Ortega‐Marcos, Jorge J., González, José A., Osborne, Juliet L., Blanche, Rosalind, Shaw, Rosalind F., Hevia, Violeta, Stout, Jane, Arthur, Anthony D., Blochtein, Betina, Szentgyorgyi, Hajnalka, Li, Jin, Mayfield, Margaret M., Woyciechowski, Michał, Nunes‐Silva, Patrícia, Oliveira, Rosana Halinski, Henry, Steve, Simmons, Benno I., Dalsgaard, Bo, Hansen, Katrine, Sritongchuay, Tuanjit, O'Reilly, Alison D., García, Fermín José Chamorro, Parra, Guiomar Nates, Pigozo, Camila Magalhães, and Bartomeus, Ignasi

Abstract

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e. berry weight, number of fruits and kg per hectare, among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), Northern America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-05 (21 studies), 2006-10 (40), 2011-15 (88), and 2016-20 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should

Published
2022

19. Increasing crop richness and reducing field sizes provide higher yields to pollinator‐dependent crops.

Author

Magrach, Ainhoa, Giménez‐García, Angel, Allen‐Perkins, Alfonso, Garibaldi, Lucas A., and Bartomeus, Ignasi

Subjects
CROP yields, BIODIVERSITY conservation, CROPS, ECONOMIC impact, LANDSCAPE changes, TRADITIONAL farming
Abstract

Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2023
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20. Efficient approach to time-dependent super-diffusive Lévy random walks on finite 2D-tori using circulant analogues.

Author

Serrano, Alfredo Blanco, Allen-Perkins, Alfonso, and Andrade, Roberto Fernandes Silva

Subjects
*LEVY processes, *INVERSE problems, *CIRCULANT matrices, *RANDOM walks, *MARKOV processes, *BROAD jump
Abstract

This work resumes the investigation on discrete-time super-diffusive in Lévy random walks defined on networks by using a inverse problem approach, with a focus on 2D-tori. Imposing that the mean square displacement of the walker should be proportional to t γ , we use a Markov Chain formalism to evaluate a fine tuned time-dependent probability distribution of long-distance jumps the walker should use to meet this dependency. Despite its wide applicability, calculations are time-intensive, with a computing time proportional to the number of nodes in the graph to a power > 3. 4. Here it is shown that, by using the circulant property satisfied by the adjacency matrices of a class of tori, it is possible to significantly speed up the calculations. For the purpose of comparison, the inverse super-diffusion problem is solved for two tori based on finite patches of the two-dimensional square lattice, namely the usual (non-circulant) and the helical (circulant) ones. The results of the latter, based on derived new expressions to compute the mean square displacement valid for circulant tori, are in complete agreement with those derived using general expressions, even if the computing time increases with respect to the number of nodes with a significantly smaller exponent ≳ 2. 1. Numerical simulations in both tori types also reproduce super-diffusion when using the time-dependent probability distributions obtained for the helical one. The results suggest that this time efficient approach can be extended to model super-diffusion on cubic and hyper-cubic lattices. • Markovian formulation for diffusion of discrete Lévy random walkers on circulant tori. • Analytical solutions based on the eigenvalues and eigenvectors of circulant matrices. • Evaluation of power law distribution of long jumps with a time dependent exponent. • Numerically computed exponents lead to exact superdiffusive walks before saturation. • Circulant property enables using large lattice sizes with small computing time. [ABSTRACT FROM AUTHOR]

Published
2022
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