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3. Prime stars multiplexes

Author

Allen-Perkins, Alfonso and Andrade, Roberto F. S.

Subjects
Physics - Physics and Society
Abstract

This work investigates the class of prime star multiplexes, in which each of its layers $i$, $i=1,2, \ldots M$, consists of a regular cycle graph where any node has $2J_i$ neighbors. In a process that does not affect the cyclic topology, it is assumed that, before the multiplex is assembled, the nodes are labeled differently in each individual layer. As the setup requires that all representations of the same node in the different $M$ layers must be linked by inter-layers connections, the resulting multiplex pattern can be highly complex. This can be better visualized if one assumes that in one layer the nodes are labeled in the sequentially ascending order and that the nodes with the same label are drawn on the top of the other, so that all inter-layer connections are represented by vertical lines. In such cases, the other $M-1$ layers are characterized by long distance shortcuts. As a consequence, in spite of sharing the same internal topological structure, the multiplex ends up with very dissimilar layers. For prime number of nodes, a regular star geometry arises by requiring that the neighbor labels of the $M-1$ layers differ by a constant value $p_i>1$. For $M=2$, we use analytical and numerical approaches to provide a thorough characterization of the multiplex topological properties, of the inter layer dissimilarity, and of the diffusive dynamical processes taking place on them. For the sake of definitiveness, it is considered that each node in the sequentially labeled layer is characterized by $J_1\geq1$. In the other layer, we fix $J_2\equiv1$, while $p>1$ becomes a proxy of layer dissimilarity., Comment: 20 pages, 6 figures

Published
2019
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4. Fractional dynamics on circulant multiplex networks: optimal coupling and long-range navigation for continuous-time random walks

Author

Allen-Perkins, Alfonso and Andrade, Roberto F. S.

Subjects
Physics - Physics and Society, Nonlinear Sciences - Adaptation and Self-Organizing Systems
Abstract

This work analyzes fractional continuous-time random walks on two-layer multiplexes. A node-centric dynamics is used, in which it is assumed a Poisson distribution of a walker to become active, while a jump to one of its neighbors depends on the connection weight. Synthetic multiplexes with well known topology are used to illustrate dynamical features obtained by numerical simulations, while exact analytical expressions are presented for multiplexes assembled by circulant layers with finite number of nodes. Special attention is given to the effect of inter- $D_x$ and intra-layer $D_i$ coefficients on the system's behavior. In opposition to usual discrete time dynamics, the relaxation time has a well defined minimum at an optimal value of $D_x/D_i$. It is found that, even for the enhanced diffusion condition, the walkers mean square displacement increases linearly with time., Comment: 32 pages, 4 figures

Published
2019
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5. Mathematical modeling for sustainable aphid control in agriculture via intercropping

Author

Allen-Perkins, Alfonso and Estrada, Ernesto

Subjects
Quantitative Biology - Populations and Evolution, Physics - Physics and Society
Abstract

Agricultural losses to pest represent an important challenge in a global warming scenario. Intercropping is an alternative farming practice that promotes pest control without the use of chemical pesticides. Here we develop a mathematical model to study epidemic spreading and control in intercropped agricultural fields as a sustainable pest management tool for agriculture. The model combines the movement of aphids transmitting a virus in an agricultural field, the spatial distribution of plants in the intercropped field, and the presence of `trap crops' in an epidemiological Susceptible-Infected-Removed (SIR) model. Using this model we study several intercropping arrangements without and with trap crops and find a new intercropping arrangement that improves significantly pest management in agricultural fields respect to the commonly used intercrop systems., Comment: 29 pages, 15 figures

Published
2019
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6. Markov chain approach to anomalous diffusion on Newman-Watts networks

Author

Allen-Perkins, Alfonso, Serrano, Alfredo Blanco, de Assis, Thiago Albuquerque, Pastor, Juan Manuel, and Andrade, Roberto F. S.

Subjects
Physics - Physics and Society
Abstract

A Markov chain (MC) formalism is used to investigate the mean-square displacement (MSD) of a random walker on Newman-Watts (NW) networks. It leads to a precise analysis of the conditions for the emergence of anomalous sub- or super-diffusive regimes in such random media. Whereas results provided by most numerical approaches used so far base their results on the computation of a large number of independent runs over many equivalent substrates, the MC framework is applied only once to each equivalent sample. Starting from the simple cycle graph with $2k$ nearest neighbor connections, for which exact MSD expressions within the MC formalism can be derived, the randomness and complexity of the substrate is easily controlled by the number $x$ of added links. Results for different values of $k$, $x$, and the number $N$ of nodes make it possible to distinguish actual anomalous regimes from transient behavior and finite size effects. Albeit the high computing cost restricts the size of our networks to $N\leq1500$ nodes, our very precise results justify a new and more comprehensive scaling ansatz for walker dynamics, from which the behavior for very large networks can be derived., Comment: 24 pages, 13 figures

Published
2019
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7. Random spherical graphs

Author

Allen-Perkins, Alfonso

Subjects
Physics - Physics and Society
Abstract

This work addresses a modification of the random geometric graph (RGG) model by considering a set of points uniformly and independently distributed on the surface of a $(d-1)$-sphere with radius $r$ in a $d-$dimensional Euclidean space, instead of on an unit hypercube $[0,1]^d$ . Then, two vertices are connected by a link if their great circle distance is at most $s$. In the case of $d=3$, the topological properties of the random spherical graphs (RSGs) generated by this model are studied as a function of $s$. We obtain analytical expressions for the average degree, degree distribution, connectivity, average path length, diameter and clustering coefficient for RSGs. By setting $r=\sqrt{\pi}/(2\pi)$, we also show the differences between the topological properties of RSGs and those of two-dimensional RGGs and random rectangular graphs (RRGs). Surprisingly, in terms of the average clustering coefficient, RSGs look more similar to the analytical estimation for RGGs than RGGs themselves, when their boundary effects are considered. We support all our findings by computer simulations that corroborate the accuracy of the theoretical models proposed for RSGs., Comment: 28 pages, 14 figures

Published
2018
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8. Superdiffusion on complex networks: the role of shortcuts and long-range interactions

Author

Allen-Perkins, Alfonso, Serrano, Alfredo Blanco, de Assis, Thiago Albuquerque, Pastor, Juan Manuel, and Andrade, Roberto F. S.

Subjects
Physics - Physics and Society
Abstract

This work addresses the superdiffusive motion of a discrete time random walker on ordered discrete substrates and complex networks with the presence of long-range interactions (LRIs). In ordered regular lattices, where LRIs have a clear geometrical meaning, their presence allow for hoppings between more distant sites, yet with a smaller probability. In such cases, it is found that LRIs do not affect the dependency of the mean square displacement (MSD) traveled by the walker: exact analytical results for the the cycle graph within the Markov chain framework shows that MSD follows the same linearly increasing behavior with time when LRIs are absent, independently of the strength of LRI. This contrasts with the superdiffusive scenario in complex networks. When they have very short diameter ($\sim \log N$), the analysis of the time dependency of MSD becomes quite difficult, as it saturates very quickly even when LRIs are absent. The presence of a faster than linearly increasing growth phase can be noticed, but it can hardly be measured with precision. This effect is sidestepped on small-world Newman-Watts (NW) networks, where the network diameter can be controlled by the number of new links (shortcuts) that are added to the cycle graph. The time duration $t_f$ of the superdiffusive regime and the power law exponent can be adequately evaluated by numerical methods. They depend on the number of nodes and shortcuts, as well as the strength of LRIs. Although the later causes a strong reduction in $t_f$ when shortcuts are present, their presence by itself is not sufficient to trigger a superdiffusive behavior., Comment: 30 pages, 13 figures

Published
2018

9. Relaxation time of the global order parameter on multiplex networks: the role of interlayer coupling in Kuramoto oscillators

Author

Allen-Perkins, Alfonso, de Assis, Thiago Albuquerque, Pastor, Juan Manuel, and Andrade, Roberto F. S.

Subjects
Physics - Physics and Society
Abstract

This work considers the timescales associated with the global order parameter and the interlayer synchronization of coupled Kuramoto oscillators on multiplexes. For the two-layer multiplexes with initially high degree of synchronization in each layer, the difference between the average phases in each layer is analyzed from two different perspectives: the spectral analysis and the non-linear Kuramoto model. Both viewpoints confirm that the prior timescales are inversely proportional to the interlayer coupling strength. Thus, increasing the interlayer coupling always shortens the transient regimes of both the global order parameter and the interlayer synchronization. Surprisingly, the analytical results show that the convergence of the global order parameter is faster than the interlayer synchronization, and the latter is generally faster than the global synchronization of the multiplex. The formalism also outlines the effects of frequencies on the difference between the average phases of each layer, and identifies the conditions for an oscillatory behavior. Computer simulations are in fairly good agreement with the analytical findings and reveal that the timescale of the global order parameter is at least half times smaller than timescale of the multiplex., Comment: 26 pages, 9 figures

Published
2017
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10. Two-walks degree assortativity in graphs and networks

Author

Allen-Perkins, Alfonso, Pastor, Juan Manuel, and Estrada, Ernesto

Subjects
Physics - Physics and Society, Computer Science - Social and Information Networks, 05C82, 05C75, 91D30, 92C42
Abstract

Degree ssortativity is the tendency for nodes of high degree (resp.low degree) in a graph to be connected to high degree nodes (resp. to low degree ones). It is sually quantified by the Pearson correlation coefficient of the degree-degree correlation. Here we extend this concept to account for the effect of second neighbours to a given node in a graph. That is, we consider the two-walks degree of a node as the sum of all the degrees of its adjacent nodes. The two-walks degree assortativity of a graph is then the Pearson correlation coefficient of the two-walks degree-degree correlation. We found here analytical expression for this two-walks degree assortativity index as a function of contributing subgraphs. We then study all the 261,000 connected graphs with 9 nodes and observe the existence of assortative-assortative and disassortative-disassortative graphs according to degree and two-walks degree, respectively. More surprinsingly, we observe a class of graphs which are degree disassortative and two-walks degree assortative. We explain the existence of some of these graphs due to the presence of certain topological features, such as a node of low-degree connected to high-degree ones. More importantly, we study a series of 49 real-world networks, where we observe the existence of the disassortative-assortative class in several of them. In particular, all biological networks studied here were in this class. We also conclude that no graphs/networks are possible with assortative-disassortative structure., Comment: 15 pages, 5 figures, 2 tables

Published
2017

12. Inducing Self-Organized Criticality in a network toy model by neighborhood assortativity

Author

Allen-Perkins, Alfonso, Galeano, Javier, and Pastor, Juan Manuel

Subjects
Nonlinear Sciences - Adaptation and Self-Organizing Systems, Physics - Physics and Society
Abstract

Complex networks are a recent type of frameworks used to study complex systems with many interacting elements, such as Self-Organized Criticality (SOC). The network node's tendency to link to other nodes of similar type is characterized by assortative mixing. Real networks exhibit assortative mixing by vertex degree, however typical random network models, such as Erdos-Renyi or Barabasi-Albert, show no assortative arrangements. In this paper we introduce the neighborhood assortativity notion, as the tendency of a node to belong to a community (its neighborhood) showing an average property similar to its own. Imposing neighborhood assortative mixing by degree in a network toy model, SOC dynamics can be found. The long-range correlations resulting from the criticality have been characterized by means of fluctuation analysis and show an anticorrelation in the node's activity. The model contains only one parameter and its statistics plots for different values of the parameter can be collapsed into a single curve. The simplicity of the model allows performing numerical simulations and also to study analytically the statistics for a specific value of the parameter, making use of the Markov chains., Comment: 15 pages, 8 figures, resubmitted to PRE

Published
2016
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13. 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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14. 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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15. 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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16. 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

17. 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

18. 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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22. 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., 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., Aström, 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, 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., 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., 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., Aström, 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

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

23. 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

24. 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

25. 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

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

Author

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

Published
2022
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29. 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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33. 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
2021

46. 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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