@article{Green2020,
abstract = {Integrated Pest Management (IPM) is a holistic approach to combat pests (including herbivores, pathogens, and weeds) using a combination of preventive and curative actions, and only applying synthetic pesticides when there is an urgent need. Just as the recent recognition that an evolutionary perspective is useful in medicine to understand and predict interactions between hosts, diseases, and medical treatments, we argue that it is crucial to integrate an evolutionary framework in IPM to develop efficient and reliable crop protection strategies that do not lead to resistance development in herbivores, pathogens, and weeds. Such a framework would not only delay resistance evolution in pests, but also optimize each element of the management and increase the synergies between them. Here, we outline key areas within IPM that would especially benefit from a thorough evolutionary understanding. In addition, we discuss the difficulties and advantages of enhancing communication among research communities rooted in different biological disciplines and between researchers and society. Furthermore, we present suggestions that could advance implementation of evolutionary principles in IPM and thus contribute to the development of sustainable agriculture that is resilient to current and emerging pests.},
author = {Green, Kristina Karlsson and Stenberg, Johan A and Lankinen, {\AA}sa},
doi = {10.1111/eva.13067},
file = {:home/brad/Dropbox/papers/GreenEtAL2020.pdf:pdf},
issn = {17524571},
journal = {Evolutionary Applications},
keywords = {biological control,crop wild relatives,economic injury level,evolutionary application,evolutionary integrated pest management,pesticide resistance,plant resistance,plant tolerance},
number = {8},
pages = {1791--1805},
title = {{Making sense of Integrated Pest Management (IPM) in the light of evolution}},
volume = {13},
year = {2020}
}
@article{Busi2013,
abstract = {The interaction between environment and genetic traits under selection is the basis of evolution. In this study, we have investigated the genetic basis of herbicide resistance in a highly characterized initially herbicide-susceptible Lolium rigidum population recurrently selected with low (below recommended label) doses of the herbicide diclofop-methyl. We report the variability in herbicide resistance levels observed in F1 families and the segregation of resistance observed in F2 and back-cross (BC) families. The selected herbicide resistance phenotypic trait(s) appear to be under complex polygenic control. The estimation of the effective minimum number of genes (NE), depending on the herbicide dose used, reveals at least three resistance genes had been enriched. A joint scaling test indicates that an additive-dominance model best explains gene interactions in parental, F1, F2 and BC families. The Mendelian study of six F2 and two BC segregating families confirmed involvement of more than one resistance gene. Cross-pollinated L. rigidum under selection at low herbicide dose can rapidly evolve polygenic broad-spectrum herbicide resistance by quantitative accumulation of additive genes of small effect. This can be minimized by using herbicides at the recommended dose which causes high mortality acting outside the normal range of phenotypic variation for herbicide susceptibility. Journal compilation {\textcopyright} 2013 Blackwell Publishing Ltd62 February 2013 10.1111/j.1752-4571.2012.00282.x Original Article Original Articles {\textcopyright} 2012 Blackwell Publishing Ltd. This is an open access article under the terms of the Creative Commons Attribution Non Commercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.},
author = {Busi, Roberto and Neve, Paul and Powles, Stephen},
doi = {10.1111/j.1752-4571.2012.00282.x},
file = {:home/brad/Dropbox/papers/BusiEtAl2012.pdf:pdf},
issn = {17524563},
journal = {Evolutionary Applications},
keywords = {Additive genes,Evolution,Inheritance,Mendelian segregation,Polygenic resistance},
number = {2},
pages = {231--242},
title = {{Evolved polygenic herbicide resistance in Lolium rigidum by low-dose herbicide selection within standing genetic variation}},
volume = {6},
year = {2013}
}
@incollection{Via1986,
address = {Washington, DC},
author = {Via, Sara},
booktitle = {Pesticide resistance: strategies and tactics for management},
chapter = {3},
pages = {222--235},
publisher = {National Academy Press},
title = {{Quantitative genetic models and the evolution of pesticide resistance}},
year = {1986}
}
@article{Raymond2001,
author = {Raymond, Michel and Berticat, Claire and Weill, Mylene and Pasteur, Nicole and Chevillon, Christine},
file = {:home/brad/Dropbox/papers/RaymondEtAl2001.pdf:pdf},
issn = {00138703},
journal = {Genetica},
number = {3},
pages = {239--248},
title = {{Insecticide resistance in the mosquito Culex pipiens: What have we learned about adaptation?}},
volume = {103},
year = {2001}
}
@article{Carriere2016,
abstract = {The primary strategy for delaying the evolution of pest resistance to transgenic crops that produce insecticidal proteins from Bacillus thuringiensis (Bt) entails refuges of plants that do not produce Bt toxins and thus allow survival of susceptible pests. Recent advances include using refuges together with Bt crop 'pyramids' that make two or more Bt toxins effective against the same pest, and planting seed mixtures yielding random distributions of pyramided Bt and non-Bt corn plants within fields. We conclude that conditions often deviate from those favoring the success of pyramids and seed mixtures, particularly against pests with low inherent susceptibility to Bt toxins. For these problematic pests, promising approaches include using larger refuges and integrating Bt crops with other pest management tactics.},
author = {Carri{\`{e}}re, Yves and Fabrick, Jeffrey A. and Tabashnik, Bruce E.},
doi = {10.1016/j.tibtech.2015.12.011},
file = {:home/brad/Dropbox/papers/CarriereEtAl2016.pdf:pdf},
issn = {18793096},
journal = {Trends in Biotechnology},
keywords = {Cross-resistance,Genetically engineered,Redundant killing,Resistance management,Sustainability,Transgenic},
number = {4},
pages = {291--302},
pmid = {26774592},
publisher = {Elsevier Ltd},
title = {{Can Pyramids and Seed Mixtures Delay Resistance to Bt Crops?}},
url = {http://dx.doi.org/10.1016/j.tibtech.2015.12.011},
volume = {34},
year = {2016}
}
@article{Ives2002,
abstract = {Widespread use of transgenic crops that express an insecticidal endotoxin from Bacillus thuringiensis increases the risk of evolution of resistance by the European corn borer and other insect pests. To delay resistance evolution, the high-dose/refuge strategy is being implemented for Bt maize and Bt cotton. We develop a general modelling framework to understand the invasion and spread of alleles conferring resistance. We show that at least three processes are involved in explaining the effectiveness of the high-dose/refuge strategy: the intensity of selection, assortative (non-random) mating due to spatial subdivision, and variation in male mating success also due to spatial subdivision. Understanding these processes leads to a greater range of possible resistance management tactics. For example, efforts to encourage adults to leave their natal fields may have the unwanted effect of speeding rather than slowing resistance evolution. Furthermore, when Bt maize causes high mortality to susceptible target pests, spraying insecticides in refuges to reduce pest populations may not greatly disrupt resistance management.},
author = {Ives, Anthony R. and Andow, D. A.},
doi = {10.1046/j.1461-0248.2002.00392.x},
file = {:home/brad/Dropbox/papers/Ives_Andow2002.pdf:pdf},
issn = {1461023X},
journal = {Ecology Letters},
keywords = {Bacillus thuringiensis,Bt corn,Directional selection,European corn borer,High-dose/refuge strategy,Ostrinia nubilalis,Resistance evolution,Resistance management},
number = {6},
pages = {792--801},
title = {{Evolution of resistance to Bt crops: Directional selection in structured environments}},
volume = {5},
year = {2002}
}
@article{Liang2018,
abstract = {The development of pesticide resistance significantly affects the out comes of pest control. A quantitative depiction of the effects of pesticide resistance development on integrated pest management (IPM) strategies and pest control outcomes is challenging. To address this problem, a discrete host-parasitoid model with pesticide resistance development and IPM strategies is proposed and analyzed. The threshold condition of pest eradication which reveals the relationship between the development of pest resistance and the rate of natural enemy releases is provided and analyzed, and the optimal rate for releasing natural enemies was obtained based on this threshold condition. Furthermore, in order to reduce adverse effects of the pesticide on natural enemies, the model has been extended to consider the spraying of pesticide and releases of natural enemies at different times. The effects of the dynamic complexity and different resistance development equations on the main results are also discussed.},
author = {Liang, Juhua and Tang, Sanyi and Cheke, Robert A.},
doi = {10.1080/17513758.2018.1556351},
file = {:home/brad/Dropbox/papers/LiangEtAl2018.pdf:pdf},
issn = {17513766},
journal = {Journal of Biological Dynamics},
keywords = {Biological control,Dynamic threshold,Host-parasitoid model,IPM,Resistance},
number = {1},
pages = {1059--1078},
pmid = {31305220},
publisher = {Taylor & Francis},
title = {{A discrete host-parasitoid model with development of pesticide resistance and ipm strategies}},
url = {https://doi.org/17513758.2018.1556351},
volume = {12},
year = {2018}
}
@techreport{Directorate2008,
address = {York, UK},
author = {Directorate, Pesticides Safety},
institution = {Pesticides Safety Directorate},
title = {{Plant protection products regulation: agronomic implications of proposals in the EU}},
year = {2008}
}
@article{South2018,
abstract = {Background: Insecticide resistance threatens effective vector control, especially for mosquitoes and malaria. To manage resistance, recommended insecticide use strategies include mixtures, sequences and rotations. New insecticides are being developed and there is an opportunity to develop use strategies that limit the evolution of further resistance in the short term. A 2013 review of modelling and empirical studies of resistance points to the advantages of mixtures. However, there is limited recent, accessible modelling work addressing the evolution of resistance under different operational strategies. There is an opportunity to improve the level of mechanistic understanding within the operational community of how insecticide resistance can be expected to evolve in response to different strategies. This paper provides a concise, accessible description of a flexible model of the evolution of insecticide resistance. The model is used to develop a mechanistic picture of the evolution of insecticide resistance and how it is likely to respond to potential insecticide use strategies. The aim is to reach an audience unlikely to read a more detailed modelling paper. The model itself, as described here, represents two independent genes coding for resistance to two insecticides. This allows the representation of the use of insecticides in isolation, sequence and mixtures. Results: The model is used to demonstrate the evolution of resistance under different scenarios and how this fits with intuitive reasoning about selection pressure. Using an insecticide in a mixture, relative to alone, always prompts slower evolution of resistance to that insecticide. However, when resistance to both insecticides is considered, resistance thresholds may be reached later for a sequence relative to a mixture. Increasing the ability of insecticides to kill susceptible mosquitoes (effectiveness), has the most influence on favouring a mixture over a sequence because one highly effective insecticide provides more protection to another in a mixture. Conclusions: The model offers an accessible description of the process of insecticide resistance evolution and how it is likely to respond to insecticide use. A simple online user-interface allowing further exploration is also provided. These tools can contribute to an improved discussion about operational decisions in insecticide resistance management.},
author = {South, Andy and Hastings, Ian M},
doi = {10.1186/s12936-018-2203-y},
file = {:home/brad/Dropbox/papers/South_Hastings2018.pdf:pdf},
issn = {14752875},
journal = {Malaria Journal},
keywords = {Infectious diseases,Insecticide resistance,Malaria,Mosquitoes,Population genetics,Public health,Vector-borne diseases},
number = {1},
pages = {1--20},
pmid = {29448925},
publisher = {BioMed Central},
title = {{Insecticide resistance evolution with mixtures and sequences: A model-based explanation}},
url = {https://doi.org/10.1186/s12936-018-2203-y},
volume = {17},
year = {2018}
}
@article{Firko1990,
author = {Firko, Michael J and Hayes, Jane Leslie},
file = {:home/brad/Dropbox/papers/Firko_Hayes1990.pdf:pdf},
journal = {Journal of Economic Entomology},
number = {3},
pages = {657--654},
title = {{Quantitative genetic tools for insecticide resistance risk assessment: estimating the heritability of resistance}},
volume = {83},
year = {1990}
}
@article{Curtis1985,
abstract = {Simple one- and multi-generation models are used to show the essential features of the dynamics of selection for resistance to one insecticide or two unrelated insecticides in insect populations, part of which are unexposed to either compound. The use of a mixture appears advantageous provided that resistance is not fully dominant, but, if it is, linkage disequilibrium builds up rapidly and nullifies the advantage of the mixture. {\textcopyright} 1985, Cambridge University Press. All rights reserved.},
author = {Curtis, C. F.},
doi = {10.1017/S0007485300014346},
file = {:home/brad/Dropbox/papers/Curtis1985.pdf:pdf},
isbn = {0007485300014},
issn = {14752670},
journal = {Bulletin of Entomological Research},
number = {2},
pages = {259--266},
title = {{Theoretical models of the use of insecticide mixtures for the management of resistance}},
volume = {75},
year = {1985}
}
@article{Liang2013,
abstract = {After a pest develops resistance to a pesticide, switching between different unrelated pesticides is a common management option, but this raises the following questions: (1) What is the optimal frequency of pesticide use? (2) How do the frequencies of pesticide applications affect the evolution of pesticide resistance? (3) How can the time when the pest population reaches the economic injury level (EIL) be estimated and (4) how can the most efficient frequency of pesticide applications be determined? To address these questions, we have developed a novel pest population growth model incorporating the evolution of pesticide resistance and pulse spraying of pesticides. Moreover, three pesticide switching methods, threshold condition-guided, density-guided and EIL-guided, are modelled, to determine the best choice under different conditions with the overall aim of eradicating the pest or maintaining its population density below the EIL. Furthermore, the pest control outcomes based on those three pesticide switching methods are discussed. Our results suggest that either the density-guided or EIL-guided method is the optimal pesticide switching strategy, depending on the frequency (or period) of pesticide applications. {\textcopyright} 2013 Elsevier Inc.},
author = {Liang, Juhua and Tang, Sanyi and Nieto, Juan J and Cheke, Robert A},
doi = {10.1016/j.mbs.2013.07.008},
file = {:home/brad/Dropbox/papers/LiangEtAl2013.pdf:pdf},
issn = {00255564},
journal = {Mathematical Biosciences},
keywords = {Dynamic threshold,Evolution,Pesticide application frequency,Pesticide switches,Pulse spraying},
number = {2},
pages = {249--257},
pmid = {23891583},
publisher = {Elsevier Inc.},
title = {{Analytical methods for detecting pesticide switches with evolution of pesticide resistance}},
url = {http://dx.doi.org/10.1016/j.mbs.2013.07.008},
volume = {245},
year = {2013}
}
@incollection{Perez-Lucas2019,
address = {London},
author = {P{\'{e}}rez-Lucas, Gabriel and Vela, Nuria and {El Aatik}, Abderrazak and Navarro, S},
booktitle = {Pesticides-use and misuse and their impact in the environment},
chapter = {3},
editor = {Larramendy, M L and Soloneski, S},
file = {:home/brad/Dropbox/papers/Larramendy_Soloneski2019.pdf:pdf},
pages = {45--72},
publisher = {BoD--Books on Demand},
title = {{Environmental risk of groundwater pollution by pesticide leaching through the soil profile}},
year = {2019}
}
@article{Ffrench-Constant2004,
abstract = {The past ten years have seen the elucidation of the molecular basis of insect resistance to many chemical insecticides. Target genes, mostly in the nervous system, have been identified and cloned from Drosophila melanogaster and resistance-associated mutations have been examined in a range of pest insects. More recently, with the advent of annotated insect genomes, resistance mediated by complex multi-gene enzyme systems such as esterases, cytochrome P450s and glutathione-S-transferases has also been elucidated. In this article, we review the impact of Drosophila genetics on the field of insect resistance and focus on the current and future impact of genomics. These studies enable us to address three fundamental questions in the evolution of resistance. How many genes are involved? How many mutations are there within these genes? How often do these mutations arise in natural populations?},
author = {Ffrench-Constant, Richard H and Daborn, Phillip J and {Le Goff}, Gaelle},
doi = {10.1016/j.tig.2004.01.003},
file = {:home/brad/Dropbox/papers/ffrench-Constant2004.pdf:pdf},
issn = {01689525},
journal = {Trends in Genetics},
number = {3},
pages = {163--170},
pmid = {15036810},
title = {{The genetics and genomics of insecticide resistance}},
volume = {20},
year = {2004}
}
@article{Ffrench-Constant2013,
abstract = {The past 60 years have seen a revolution in our understanding of the molecular genetics of insecticide resistance. While at first the field was split by arguments about the relative importance of mono- vs. polygenic resistance and field- vs. laboratory-based selection, the application of molecular cloning to insecticide targets and to the metabolic enzymes that degrade insecticides before they reach those targets has brought out an exponential growth in our understanding of the mutations involved. Molecular analysis has confirmed the relative importance of single major genes in target-site resistance and has also revealed some interesting surprises about the multi-gene families, such as cytochrome P450s, involved in metabolic resistance. Identification of the mutations involved in resistance has also led to parallel advances in our understanding of the enzymes and receptors involved, often with implications for the role of these receptors in humans. This Review seeks to provide an historical perspective on the impact of molecular biology on our understanding of resistance and to begin to look forward to the likely impact of rapid advances in both sequencing and genome-wide association analysis. {\textcopyright} 2013 by the Genetics Society of America.},
author = {Ffrench-Constant, Richard H.},
doi = {10.1534/genetics.112.141895},
file = {:home/brad/Dropbox/papers/ffrench-Constant2013.pdf:pdf},
issn = {00166731},
journal = {Genetics},
number = {4},
pages = {807--815},
title = {{The molecular genetics of insecticide resistance}},
volume = {194},
year = {2013}
}
@article{Classen2014,
abstract = {Wild animals substantially support crop production by providing ecosystem services, such as pollination and natural pest control. However, the strengths of synergies between ecosystem services and their dependencies on land-use management are largely unknown. Here, we took an experimental approach to test the impact of land-use intensification on both individual and combined pollination and pest control services in coffee production systems at Mount Kilimanjaro. We established a full-factorial pollinator and vertebrate exclosure experiment along a land-use gradient from traditional homegardens (agroforestry systems), shaded coffee plantations to sun coffee plantations (total sample size = 180 coffee bushes). The exclusion of vertebrates led to a reduction in fruit set of ca 9%. Pollinators did not affect fruit set, but significantly increased fruit weight of coffee by an average of 7.4%. We found no significant decline of these ecosystem services along the land-use gradient. Pest control and pollination service were thus complementary, contributing to coffee production by affecting the quantity and quality of a major tropical cash crop across different coffee production systems at Mount Kilimanjaro. {\textcopyright} 2014 The Author(s) Published by the Royal Society. All rights reserved.},
author = {Classen, Alice and Peters, Marcell K and Ferger, Stefan W and Helbig-Bonitz, Maria and Schmack, Julia M and Maassen, Genevieve and Schleuning, Matthias and Kalko, Elisabeth K V and Bohning-Gaese, Katrin and Steffan-Dewenter, Ingolf},
doi = {10.1098/rspb.2013.3148},
file = {:home/brad/Dropbox/papers/ClassenEtAl2014.pdf:pdf},
issn = {14712954},
journal = {Proceedings of the Royal Society B: Biological Sciences},
keywords = {Agroforestry,Biological pest control,Coffea arabica,Land-use change,Mount kilimanjaro,Pollination},
number = {1779},
pmid = {24500173},
title = {{Complementary ecosystem services provided by pest predators and pollinators increase quantity and quality of coffee yields}},
volume = {281},
year = {2014}
}
@article{Porter2010,
author = {Porter, John R and Challinor, Andrew and Ewert, Frank and Falloon, Pete and Fischer, Tony and Gregory, Peter and {Van Ittersum}, M K and Olesen, J E and Moore, K J and Rosenzweig, C and Smith, P},
journal = {Science},
number = {5975},
pages = {172--173},
title = {{Food security: focus on agriculture}},
volume = {328},
year = {2010}
}
@article{Lykogianni2021,
abstract = {Sustainable agriculture aims to meet the food needs of the growing world population while ensuring minimal impact on the environment and humans as well as productivity. Although pesticides represent the backbone of the agri-food sector in its endeavor to secure food production their application is perceived by many as an obstacle towards the achievement of sustainability; the main concerns are linked with their adverse effects on human health and the environment. Τhis review aims to present the status of chemical plant protection and provide insights into the use of pesticides within the context of sustainable agriculture. It mainly focuses on the strengthened legislation frameworks, which especially in the European Union and the United States of America ensure the placement in the market of pesticides with acceptable toxicological and environmental profiles without compromising crop production. Furthermore, the implementation of Integrated Pest Management principles plays a key role in the sustainable use of pesticides. The stringent regulatory requirements have resulted in the dramatic increase of the associated effort and costs in pesticide research and development (R&D) of improved products. Nevertheless, the investment of leading agrochemical companies in the R&D of new pesticides remains high. All the above set the ground for the sustainable use of pesticides in crop production while their successful application remains a challenge.},
author = {Lykogianni, Maira and Bempelou, Eleftheria and Karamaouna, Filitsa and Aliferis, Konstantinos A},
doi = {10.1016/j.scitotenv.2021.148625},
file = {:home/brad/Dropbox/papers/LykogianniEtAl2021.pdf:pdf},
issn = {18791026},
journal = {Science of the Total Environment},
keywords = {Integrated pest management,Plant protection products,Sustainable agriculture,pesticides' authorization},
pages = {148625},
pmid = {34247073},
publisher = {Elsevier B.V.},
title = {{Do pesticides promote or hinder sustainability in agriculture? The challenge of sustainable use of pesticides in modern agriculture}},
url = {https://doi.org/10.1016/j.scitotenv.2021.148625},
volume = {795},
year = {2021}
}
@article{Mani1985,
abstract = {A two-locus model is used to analyze the effectiveness of a mixture of insecticides in delaying resistance, compared to the use of the insecticides singly. The effects of factors such as recombination, effective dominance, initial value of allele frequencies and initial value of linkage disequilibrium are considered. It is shown that the use of mixtures is always more effective in delaying the onset of resistance, often by many orders of magnitude. It is shown that there exists a threshold value of recombination fraction, above which the evolution of resistance is extremely slow. Resistance evolves very rapidly for values of recombination fraction below the threshold. Finally, the relevance of these results on resistance management is discussed.},
author = {Mani, G S},
doi = {10.1093/genetics/109.4.761},
file = {:home/brad/Dropbox/papers/Mani1985.pdf:pdf},
issn = {00166731},
journal = {Genetics},
number = {4},
pages = {761--783},
pmid = {3988040},
title = {{Evolution of resistance in the presence of two insecticides.}},
volume = {109},
year = {1985}
}
@article{Bourguet2013,
abstract = {The evolution of resistance to pesticides and drugs by pests and pathogens is a textbook example of adaptation to environmental changes and a major issue in both public health and agronomy. Surprisingly, there is little consensus on how to combine selection pressures (i.e., molecules used in the treatment of pests or pathogens) over space and time to delay or prevent this evolutionary process. By reviewing theoretical models and experimental studies, we show that higher levels of heterogeneity of selection are associated with longer-term sustainability of pest or pathogen control. The combination of molecules usually outcompetes other resistance management strategies, such as Responsive alternation, Periodic application, or Mosaic, because it ensures 'multiple intragenerational killing'. A strategic deployment over space and/or time of several combinations can ensure 'multiple intergenerational killing', further delaying the evolution of resistance. {\textcopyright} 2012 Elsevier Ltd.},
author = {Bourguet, Denis and Delmotte, Francois and Franck, Pierre and Guillemaud, Thomas and Reboud, Xavier and Vacher, Corinne and Bordeaux, Univ and Walker, Anne Sophie},
doi = {10.1016/j.tree.2012.09.001},
file = {:home/brad/Dropbox/papers/REXConsortium2013.pdf:pdf},
issn = {01695347},
journal = {Trends in Ecology and Evolution},
number = {2},
pages = {110--118},
pmid = {23040463},
publisher = {Elsevier Ltd},
title = {{Heterogeneity of selection and the evolution of resistance}},
url = {http://dx.doi.org/10.1016/j.tree.2012.09.001},
volume = {28},
year = {2013}
}
@techreport{Chen2018,
address = {Wellesley, MA, USA},
author = {Chen, Jason},
pages = {Report Code CHM029G},
title = {{Biopesticides: Global Markets to 2022}},
year = {2018}
}
@incollection{Matten2012,
abstract = {This article aims to break new ground in academia by bridging the existing knowledge and practice gap on governance during conflict. It seeks to understand the governance dynamics during conflict in the non-government-controlled parts of Syria. It pays particular attention to civil society and state building processes. In doing so, the study spans historical and geographical width. Historically, to understand the roots of the conflict, it assesses the state-civil society-market dynamics of governance in Syria prior to 2011. Nevertheless, its focus is on contemporary Syria between March, 2011 and May, 2014. Geographically, its particular attention and in-depth analysis is on three areas in the non-government-controlled parts: Al-Raqqa (the city), Deir Ez-zor (Al-Mayadeen and the city) and Aleppo (the city).},
archivePrefix = {arXiv},
arxivId = {arXiv:1011.1669v3},
author = {Matten, Sharlene R and Frederick, Robert J and Reynolds, Alan H},
booktitle = {Regulation of Agricultural Biotechnology: The United States and Canada},
chapter = {11},
doi = {10.1007/978-94-007-2156-2_11},
editor = {Wozniak, C A and McHughen, A},
eprint = {arXiv:1011.1669v3},
file = {:home/brad/Dropbox/papers/Wozniak_McHughen2012.pdf:pdf},
isbn = {9772081415},
issn = {17549469},
keywords = {Biafra,Cultural theory,DS92.S9,Ethnic conflict,Fulani,Hausa,Hierarchy,Ibo,Individualism,Journal article,Nigeria,Public Administration,Syria,Syria--History--21st century,Syria--Politics and government,Yoruba,civi war onset,civil war,corporate,economic development,exclusion,global governance,good governance,governance,governance theories,government,icle,indian,lack of accountability,leadership philosophy,poor governance,rebel mobilization,self-governance,syria,the bhagavad-gita,unescap},
pages = {175--267},
pmid = {25246403},
title = {{United States Environmental Protection Agency insect resistance management programs for plant-incorporated protectants and use of simulation modeling}},
url = {https://www.researchgate.net/publication/269107473_What_is_governance/link/548173090cf22525dcb61443/download%0Ahttp://www.econ.upf.edu/$\sim$reynal/Civil wars_12December2010.pdf%0Ahttps://think-asia.org/handle/11540/8282%0Ahttps://www.jstor.org/stable/41857625},
year = {2012}
}
@book{Elnahal2022,
abstract = {Microbial control agents serve as alternatives to synthetic pesticides for the management of insect pests and plant pathogens. Naturally occurring microorganisms such as bacteria, fungi, and protozoa may be beneficial, pathogenic, or neutral to host plants. This review focuses on the potential role of useful microorganisms as biofertilizers or biopesticides in sustaining and enhancing crop production, and protection. It is necessary to highlight the advantages of the beneficial microorganisms to encourage farmers to use biological control agents and biofertilizers and reduce the excessive use of toxic chemical pesticides and fertilizers. Here, we review the importance of using microorganisms in the agriculture sector for their potential role in fulfilling the nutritional requirements of plants, food safety, and sustainable crop production. Microorganisms can interact with the crop plants to improve their resistance to pathogen attack, plant growth, and development. Their metabolites have been recognized based on their precious excellent plant growth promotion, efficient biocontrol capabilities, successful mass production, appropriate formulation and availability for commercial application. Bio-complexes, including biofertilizers and biopesticides, promote growth and provide protection to plants against various biotic and abiotic stress through the production of plant growth regulators and siderophores, enhancement of nutrient uptake, increasing yield, and production of antagonistic compounds such as antibiotics, hydrolytic enzymes, hydrogen cyanide, and volatile organic compounds. This review sheds the light on the potential of employing microbial agents in agriculture as biofertilizers, biopesticides, nano-biofertilizers and nano-biopesticides to enhance plant productivity and sustainable agriculture. Graphical abstract: [Figure not available: see fulltext.]},
author = {Elnahal, Ahmed SM and El-Saadony, Mohamed T and Saad, Ahmed M and Desoky, El Sayed M and El-Tahan, Amira M and Rady, Mostafa M and AbuQamar, Synan F and El-Tarabily, Khaled A},
booktitle = {European Journal of Plant Pathology},
doi = {10.1007/s10658-021-02393-7},
file = {:home/brad/Dropbox/papers/ElnahalEtAl2022.pdf:pdf},
isbn = {1065802102},
issn = {15738469},
keywords = {Biological control,Microbial inoculants,Plant growth-promoting rhizobacteria,Sustainable agriculture},
number = {4},
pages = {759--792},
publisher = {Springer Netherlands},
title = {{The use of microbial inoculants for biological control, plant growth promotion, and sustainable agriculture: A review}},
url = {https://doi.org/10.1007/s10658-021-02393-7},
volume = {162},
year = {2022}
}
@article{Lundin2013,
abstract = {Pollination is a key ecosystem service which most often has been studied in isolation although effects of pollination on seed set might depend on, and interact with, other services important for crop production. We tested three competing hypotheses on how insect pollination and pest control might jointly affect seed set: independent, compensatory or synergistic effects. For this, we performed a cage experiment with two levels of insect pollination and simulated pest control in red clover (Trifolium pratense L.) grown for seed. There was a synergistic interaction between the two services: the gain in seed set obtained when simultaneously increasing pollination and pest control outweighed the sum of seed set gains obtained when increasing each service separately. This study shows that interactions can alter the benefits obtained from service-providing organisms, and this needs to be considered to properly manage multiple ecosystem services. {\textcopyright} 2012 The Author(s) Published by the Royal Society. All rights reserved.},
author = {Lundin, Ola and Smith, Henrik G and Rundl{\"{o}}f, Maj and Bommarco, Riccardo},
doi = {10.1098/rspb.2012.2243},
file = {:home/brad/Dropbox/papers/LundinEtAl2012.pdf:pdf},
issn = {14712954},
journal = {Proceedings of the Royal Society B: Biological Sciences},
keywords = {Apion,Bombus,Herbivore,Pollen limitation,Seed predator},
number = {1753},
pages = {1--6},
pmid = {23269852},
title = {{When ecosystem services interact: Crop pollination benefits depend on the level of pest control}},
volume = {280},
year = {2013}
}
@article{Tabashnik2014,
abstract = {Evolution of pest resistance to pesticides is an urgent global problem with resistance recorded in at least 954 species of pests, including 546 arthropods, 218 weeds, and 190 plant pathogens. To facilitate understanding and management of resistance, we provide definitions of 50 key terms related to resistance. We confirm the broad, long-standing definition of resistance, which is a genetically based decrease in susceptibility to a pesticide, and the definition of "field-evolved resistance," which is a genetically based decrease in susceptibility to a pesticide in a population caused by exposure to the pesticide in the field. The impact of field-evolved resistance on pest control can vary from none to severe. We define "practical resistance" as field-evolved resistance that reduces pesticide efficacy and has practical consequences for pest control. Recognizing that resistance is not "all or none" and that intermediate levels of resistance can have a continuum of effects on pest control, we describe five categories of field-evolved resistance and use them to classify 13 cases of field-evolved resistance to five Bacillus thuringiensis (Bt) toxins in transgenic corn and cotton based on monitoring data from five continents for nine major pest species. We urge researchers to publish and analyze their resistance monitoring data in conjunction with data on management practices to accelerate progress in determining which actions will be most useful in response to specific data on the magnitude, distribution, and impact of resistance. {\textcopyright} 2014 Entomological Society of America. {\textcopyright} 2014 Entomological Society of America.},
author = {Tabashnik, Bruce E and Mota-Sanchez, David and Whalon, Mark E and Hollingworth, Robert M and Carri{\`{e}}re, Yves},
doi = {10.1603/EC13458},
file = {:home/brad/Dropbox/papers/TabashnikEtAl2014.pdf:pdf},
issn = {00220493},
journal = {Journal of Economic Entomology},
keywords = {Bacillus thuringiensis,Evolution,Genetically engineered crop,Peld-evolved resistance},
number = {2},
pages = {496--507},
pmid = {24772527},
title = {{Defining terms for proactive management of resistance to Bt crops and pesticides}},
volume = {107},
year = {2014}
}
@article{Sudo2018,
abstract = {Although theoretical studies have shown that the mixture strategy, which uses multiple toxins simultaneously, can effectively delay the evolution of insecticide resistance, whether it is the optimal management strategy under different insect life histories and insecticide types remains unknown. To test the robustness of this management strategy over different life histories, we developed a series of simulation models that cover almost all the diploid insect types and have the same basic structure describing pest population dynamics and resistance evolution with discrete time steps. For each of two insecticidal toxins, independent one-locus two-allele autosomal inheritance of resistance was assumed. The simulations demonstrated the optimality of the mixture strategy either when insecticide efficacy was incomplete or when some part of the population disperses between patches before mating. The rotation strategy, which uses one insecticide on one pest generation and a different one on the next, did not differ from sequential usage in the time to resistance, except when dominance was low. It was the optimal strategy when insecticide efficacy was high and premating selection and dispersal occur.},
author = {Sudo, Masaaki and Takahashi, Daisuke and Andow, David A and Suzuki, Yoshito and Yamanaka, Takehiko},
doi = {10.1111/eva.12550},
file = {:home/brad/Dropbox/papers/SudoEtAl2018.pdf:pdf},
issn = {17524571},
journal = {Evolutionary Applications},
keywords = {high-dose/refuge,interpatch dispersal,pesticide rotation,population-based model,pyramiding,selection pressure},
number = {2},
pages = {271--283},
title = {{Optimal management strategy of insecticide resistance under various insect life histories: Heterogeneous timing of selection and interpatch dispersal}},
volume = {11},
year = {2018}
}
@article{Haridas2018,
abstract = {Widespread use of pesticides has resulted in the evolution of resistance in many insect pests worldwide limiting their use in pest control. Effective pest and resistance management practices require understanding of the genetics of resistance and of the life history of the pest. Most models for pesticide resistance assume that resistance is monogenic, conferred by a single gene. However, resistance could evolve as a polygenic quantitative trait resulting from the action of several genes, especially when pesticide dose is low. Further, fitness of the pest could be density-dependent and might depend upon abiotic factors such as temperature. It is not known how these factors affect the evolution of polygenic resistance or pest population dynamics when resistance evolves. We use the western corn rootworm, Diabrotica virgifera virgifera, as a case study and use data on density-dependent survival, heritability and survival rates on the transgenic Cry3Bb1 toxin and corresponding LC50 values, to model polygenic resistance to Cry3Bb1. We found that LC50 increased rapidly even at doses that produced a mortality of less than 99.9%. However, survival reached 100% only when mortality was as high as 99.9%. Fast response to high selection pressure produced cyclical larval densities while lower selection pressures produced equilibrium densities. Interestingly we found that a relatively low density observed in a population may not be evidence for a low survival to the pesticide. As a consequence we found that larger refuges might not necessarily help in reducing pest densities especially when pesticide mortality is low. This effect, arising from the tradeoff between response to selection and density dependence, calls for careful assessment of the evolution of resistance based on change in survival as well as on pest densities. When selection pressure is low a lower initial density resulted in a larger response to selection. Finally, we showed that populations with shorter developmental times developed resistance faster initially irrespective of selection pressure. However, when selection pressure is low survival eventually became higher in populations with longer developmental times. Since developmental time depends on degree days spatio-temporal variation in temperature could be an important factor in polygenic resistance evolution.},
author = {Haridas, C. V. and Tenhumberg, Brigitte},
doi = {10.1016/j.jtbi.2018.07.034},
file = {:home/brad/Dropbox/papers/Haridas_Tenhumberg2018.pdf:pdf},
issn = {10958541},
journal = {Journal of Theoretical Biology},
keywords = {Breeder's equation,Density-dependence,Developmental time,Diabrotica virgifera virgifera,Low-dose,Pesticide,Polygenic resistance,Resistance management,Selection gradient,Transgenic},
pages = {224--232},
pmid = {30075171},
publisher = {Elsevier Ltd},
title = {{Modeling effects of ecological factors on evolution of polygenic pesticide resistance}},
url = {https://doi.org/10.1016/j.jtbi.2018.07.034},
volume = {456},
year = {2018}
}
@article{Saikai2021,
abstract = {BACKGROUND: Farmers around the world have used Bt maize for more than two decades, delaying resistance using a high-dose/refuge strategy. Nevertheless, field-evolved resistance to Bacillus thuringiensis (Bt) toxins has been documented. This paper describes a spatially explicit population genetics model of resistance to Bt toxins by the insect Ostrinia nubilalis and an agent-based model of farmer adoption of Bt maize incorporating social networks. The model was used to evaluate multiple resistance mitigation policies, including combinations of increased refuges for all farms, localized bans on Bt maize where resistance develops, area-wide sprays of insecticides on fields with resistance and taxes on Bt maize seed for all farms. Evaluation metrics included resistance allele frequency, pest population density, farmer adoption of Bt maize and economic surplus. RESULTS: The most effective mitigation policies for maintaining a low resistance allele frequency were 50% refuge and localized bans. Area-wide sprays were the most effective for maintaining low pest populations. Based on economic surplus, refuge requirements were the recommended policy for mitigating resistance to high-dose Bt maize. Social networks further enhanced the benefits of refuges relative to other mitigation policies but accelerated the emergence of resistance. CONCLUSION: These results support using refuges as the foundation of resistance mitigation for high-dose Bt maize, just as for resistance management. Other mitigation policies examined were more effective but more costly. Social factors had substantial effects on the recommended management and mitigation of insect resistance, suggesting that agent-based models can make useful contributions for policy analysis.},
author = {Saikai, Yuji and Hurley, Terrance M. and Mitchell, Paul D.},
doi = {10.1002/ps.6016},
file = {:home/brad/Dropbox/papers/SaikaiEtAl202.pdf:pdf},
issn = {15264998},
journal = {Pest Management Science},
keywords = {European corn borer,population genetics model,resistance mitigation policies,social networks,technology adoption},
number = {1},
pages = {273--284},
pmid = {32696499},
title = {{An agent-based model of insect resistance management and mitigation for Bt maize: a social science perspective}},
volume = {77},
year = {2021}
}
@article{Hawkins2019,
abstract = {Durable crop protection is an essential component of current and future food security. However, the effectiveness of pesticides is threatened by the evolution of resistant pathogens, weeds and insect pests. Pesticides are mostly novel synthetic compounds, and yet target species are often able to evolve resistance soon after a new compound is introduced. Therefore, pesticide resistance provides an interesting case of rapid evolution under strong selective pressures, which can be used to address fundamental questions concerning the evolutionary origins of adaptations to novel conditions. We ask: (i) whether this adaptive potential originates mainly from de novo mutations or from standing variation; (ii) which pre-existing traits could form the basis of resistance adaptations; and (iii) whether recurrence of resistance mechanisms among species results from interbreeding and horizontal gene transfer or from independent parallel evolution. We compare and contrast the three major pesticide groups: insecticides, herbicides and fungicides. Whilst resistance to these three agrochemical classes is to some extent united by the common evolutionary forces at play, there are also important differences. Fungicide resistance appears to evolve, in most cases, by de novo point mutations in the target-site encoding genes; herbicide resistance often evolves through selection of polygenic metabolic resistance from standing variation; and insecticide resistance evolves through a combination of standing variation and de novo mutations in the target site or major metabolic resistance genes. This has practical implications for resistance risk assessment and management, and lessons learnt from pesticide resistance should be applied in the deployment of novel, non-chemical pest-control methods.},
author = {Hawkins, Nichola J. and Bass, Chris and Dixon, Andrea and Neve, Paul},
doi = {10.1111/brv.12440},
file = {:home/brad/Dropbox/papers/HawkinsEtAl2019.pdf:pdf},
issn = {1469185X},
journal = {Biological Reviews},
keywords = {adaptive introgression,de novo mutation,evolution,fungicide,herbicide,insecticide,pesticide resistance,pleiotropic co-option,selective sweeps,standing variation},
number = {1},
pages = {135--155},
title = {{The evolutionary origins of pesticide resistance}},
volume = {94},
year = {2019}
}
@article{Gould2018,
abstract = {Resistance to insecticides and herbicides has cost billions of U.S. dollars in the agricultural sector and could result in millions of lives lost to insect-vectored diseases. We mostly continue to use pesticides as if resistance is a temporary issue that will be addressed by commercialization of new pesticides with novel modes of action. However, current evidence suggests that insect and weed evolution may outstrip our ability to replace outmoded chemicals and other control mechanisms. To avoid this outcome, we must address the mix of ecological, genetic, economic, and sociopolitical factors that prevent implementation of sustainable pest management practices. We offer an ambitious proposition.},
author = {Gould, Fred and Brown, Zachary S. and Kuzma, Jennifer},
doi = {10.1126/science.aar3780},
file = {:home/brad/Dropbox/papers/GouldEtAl2016.pdf:pdf},
issn = {10959203},
journal = {Science},
number = {6390},
pages = {728--732},
pmid = {29773742},
title = {{Wicked evolution: Can we address the sociobiological dilemma of pesticide resistance?}},
volume = {360},
year = {2018}
}
@article{Bradshaw2016,
abstract = {Insects have presented human society with some of its greatest development challenges by spreading diseases, consuming crops and damaging infrastructure. Despite the massive human and financial toll of invasive insects, cost estimates of their impacts remain sporadic, spatially incomplete and of questionable quality. Here we compile a comprehensive database of economic costs of invasive insects. Taking all reported goods and service estimates, invasive insects cost a minimum of US$70.0 billion per year globally, while associated health costs exceed US$6.9 billion per year. Total costs rise as the number of estimate increases, although many of the worst costs have already been estimated (especially those related to human health). A lack of dedicated studies, especially for reproducible goods and service estimates, implies gross underestimation of global costs. Global warming as a consequence of climate change, rising human population densities and intensifying international trade will allow these costly insects to spread into new areas, but substantial savings could be achieved by increasing surveillance, containment and public awareness.},
author = {Bradshaw, Corey J A and Leroy, Boris and Bellard, C{\'{e}}line and Roiz, David and Albert, C{\'{e}}line and Fournier, Alice and Barbet-Massin, Morgane and Salles, Jean Michel and Simard, Fr{\'{e}}d{\'{e}}ric and Courchamp, Franck},
doi = {10.1038/ncomms12986},
file = {:home/brad/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Bradshaw et al. - 2016 - Massive yet grossly underestimated global costs of invasive insects.pdf:pdf},
issn = {20411723},
journal = {Nature Communications},
pages = {12986},
pmid = {27698460},
title = {{Massive yet grossly underestimated global costs of invasive insects}},
volume = {7},
year = {2016}
}
@article{Duthie2018,
abstract = {Management strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty. We present the R package GMSE, which generalises MSE using a game-theoretic approach, applying genetic algorithms to simulate adaptive decision-making management scenarios between stakeholders with competing objectives under complex social-ecological interactions and uncertainty. GMSE models can be agent-based and spatially explicit, incorporating a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem; additionally, user-defined sub-models can also be incorporated as functions into the broader GMSE framework. We show how GMSE simulates a social-ecological system using the example of an adaptively managed waterfowl population on an agricultural landscape; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield. The R package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub.},
author = {Duthie, A Bradley and Cusack, Jeremy J and Jones, Isabel L and Nilsen, Erlend B and Pozo, Rocio A and Rakotonarivo, O. Sarobidy and Moorter, Bram Van and Bunnefeld, Nils},
doi = {10.1101/221432},
file = {:home/brad/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Duthie et al. - 2018 - GMSE an R package for generalised management strategy evaluation.pdf:pdf},
journal = {Methods in Ecology and Evolution},
keywords = {adaptive management,conservation conflict,ecological modelling,game theory,management},
pages = {2396--2401},
title = {{GMSE: an R package for generalised management strategy evaluation}},
url = {https://www.biorxiv.org/content/early/2017/11/17/221432},
volume = {9},
year = {2018}
}
@article{Hamblin2013,
abstract = {* Genetic algorithms are a heuristic global optimisation technique mimicking the action of natural selection to solve hard optimisation problems, which has enjoyed growing usage in evolution and ecology. However, there is little standardisation in how genetic algorithms are implemented in these fields and even less practical advice for those hoping to implement genetic algorithms for their own models. This article aims to demystify genetic algorithms and provide assistance to researchers; basic programming knowledge is important for working with genetic algorithms, but none is required to read this article. * I review the basics of genetic algorithm methodology and provide suggestions on problems that may or may not benefit from genetic algorithm methods. The genetic operators (selection, replacement, mutation, crossover) and their rate parameters (mutation rate, etc.) are a source of potential confusion and to ease their selection, I present recommendations informed by historical usage and best practices, concluding with potential pitfalls. * Good reasons for employing genetic algorithms include: solving optimisation problems beyond the reach of analytical techniques, relaxing model assumptions, evolving behaviour in individual-based models, and simulating co-evolutionary processes. However, genetic algorithms are not always the correct technique to use. Simpler methods may sometimes outperform genetic algorithms, and certain problem features may cause trouble. * Genetic algorithms strike a balance between exploration of the search space and exploitation of good solutions, driven by the choice of genetic operators and rate parameters. I outline a basic set of parameter values and operator choices for genetic algorithm models as a starting point and provide advice on how to modify them to explore the exploitation/exploration trade-off. Finally, I provide general advice on analysis and reporting of these models. * There are a number of potential issues that can surprise unwary users, such as rate parameter values that lead to pathological outcomes; I suggest ways to detect and correct these problems. Also, contrary to popular usage, genetic algorithms can find solutions to game theory problems but cannot guarantee their stability. Finally, while genetic algorithms offer great power and flexibility by drawing inspiration from evolutionary processes, they are (usually) not a faithful model of genetics or evolution.},
author = {Hamblin, Steven},
doi = {10.1111/2041-210X.12000},
file = {:home/brad/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Hamblin - 2013 - On the practical usage of genetic algorithms in ecology and evolution.pdf:pdf},
isbn = {2041-210X},
issn = {2041210X},
journal = {Methods in Ecology and Evolution},
keywords = {Evolutionary computation,Genetic algorithm,Metaheuristics,Optimisation techniques},
number = {2},
pages = {184--194},
title = {{On the practical usage of genetic algorithms in ecology and evolution}},
volume = {4},
year = {2013}
}
@Book{Luke2013, author = { Sean Luke }, title =
{ Essentials of Metaheuristics},
edition = { second }, year =
{ 2013 },
publisher = { Lulu }, note = { Available for free at http://cs.gmu.edu/$\sim$sean/book/metaheuristics/ }}
@techreport{Directorate2008,
address = {York, UK},
author = {Directorate, Pesticides Safety},
institution = {Pesticides Safety Directorate},
title = {{Plant protection products regulation: agronomic implications of proposals in the EU}},
year = {2008}
}
@article{Mangan2023,
abstract = {Microbial biopesticides containing living parasites are valuable emerging crop protection technologies against insect pests, but they are vulnerable to resistance evolution. Fortunately, the fitness of alleles that provide resistance, including to parasites used in biopesticides, frequently depends on parasite identity and environmental conditions. This context-specificity suggests a sustainable approach to biopesticide resistance management through landscape diversification. To mitigate resistance risks, we advocate increasing the range of biopesticides available to farmers, whilst simultaneously encouraging other aspects of landscape-wide crop heterogeneity that can generate variable selection on resistance alleles. This approach requires agricultural stakeholders to prioritize diversity as well as efficiency, both within agricultural landscapes and the biocontrol marketplace.},
author = {Mangan, Rosie and Bussi{\`{e}}re, Luc F. and Polanczyk, Ricardo Ant{\^{o}}nio and Tinsley, Matthew C.},
doi = {10.1016/j.tree.2023.01.012},
file = {:home/brad/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Mangan et al. - 2023 - Increasing ecological heterogeneity can constrain biopesticide resistance evolution.pdf:pdf},
issn = {01695347},
journal = {Trends in Ecology and Evolution},
keywords = {agroecology,crop protection,genotype-by-environment interactions,integrated pest management,landscape diversity,sustainable agriculture},
mendeley-groups = {resevol},
number = {7},
pages = {605--614},
publisher = {Elsevier Ltd},
title = {{Increasing ecological heterogeneity can constrain biopesticide resistance evolution}},
url = {https://doi.org/10.1016/j.tree.2023.01.012},
volume = {38},
year = {2023}
}
@article{Daly2022,
abstract = {Agent-based models (ABMs) are an increasingly popular choice for simulating large systems of interacting components, and have been applied across a wide variety of natural and environmental systems. However, ABMs can be incredibly disparate and often opaque in their formulation, implementation, and analysis. This can impede critical assessment and re-implementation, and jeopardize the reproducibility and conclusions of ABM studies. In this review, we survey recent work towards standardization in ABM methodology in several aspects: model description and documentation, model implementation, and model analysis and inference. Based on a critical review of the literature, focused on ABMs of environmental and natural systems, we describe a recurrent trade-off between flexibility and standardization in ABM methodology. We find that standard protocols for model documentation are beginning to establish, although their uptake by the ABM community is inhibited by their sometimes excessive level of detail. We highlight how implementation options now exist at all points along a spectrum from ad hoc, ‘from scratch' implementations, to specific software offering ‘off-the-shelf' ABM implementations. We outline how the main focal points of ABM analysis (behavioural and inferential analysis) are facing similar issues with similar approaches. While this active development of ABM analysis techniques brings additional methods to our analysis toolbox, it does not contribute to the development of a standardized framework, since the performance and design of these methods tends to be highly problem-specific. We therefore recommend that agent-based modellers should consider multiple approaches simultaneously when analysing their model. Well-documented software packages, and critical comparative reviews of such, will be important facilitators in these advances. ABMs can additionally make better use of developments in other fields working with high-dimensional problems, such as Bayesian statistics and machine learning.},
author = {Daly, Aisling J. and {De Visscher}, Lander and Baetens, Jan M. and {De Baets}, Bernard},
doi = {10.1016/j.envsoft.2022.105514},
file = {:home/brad/Dropbox/papers/DalyEtAl2022.pdf:pdf},
issn = {13648152},
journal = {Environmental Modelling and Software},
keywords = {Agent-based models,Calibration,Inference,Model analysis,Simulation},
mendeley-groups = {resevol},
pages = {105514},
publisher = {Elsevier Ltd},
title = {{Quo vadis, agent-based modelling tools?}},
url = {https://doi.org/10.1016/j.envsoft.2022.105514},
volume = {157},
year = {2022}
}
@article{Newman2023,
abstract = {Topographic data are increasingly important to environmental models as fine-scale resolution, wide coverage data sets become available. Scale is an important consideration for predictive model quality. Recent advances in multiscale terrain analysis led to scaling techniques that allow the scale at which a topographic parameter is represented to vary spatially. This research compared predictive soil model performance across feature sets generated with different scaling strategies; including multiple heterogeneous strategies, common feature selection algorithms applied to homogeneously scaled data, and unscaled data. Model performance was assessed for accuracy and uncertainty. The results showed that unscaled data performed worse in all circumstances compared to multiscale feature sets. Overall, heterogeneous and homogeneous feature sets did not differ substantially in accuracy, prediction uncertainty, or error. However, one scaling strategy exploited the flexibility of heterogeneous scaling to consistently perform better than other feature sets for most soil properties in terms of accuracy, and consistently ranked among the least uncertain and least error prone (up to a 0.080 increase in accuracy with a corresponding 0.017 decrease in prediction uncertainty and 0.011 decrease in error relative to the second best method, in the case of the proportion of clay modelled at 5–15 cm depth). This was achieved by decoupling the definition of process scales from analytical parameterization, allowing the optimization to occur within broadly defined process scales. This research demonstrates how to exploit heterogeneous scaling of topographic attributes to improve model performance.},
author = {Newman, D. R. and Saurette, D. D. and Cockburn, J. M.H. and Dragut, Lucian and Lindsay, J. B.},
doi = {10.1016/j.envsoft.2022.105612},
file = {:home/brad/Dropbox/papers/NewmanEtAl2023.pdf:pdf},
issn = {13648152},
journal = {Environmental Modelling and Software},
keywords = {Data mining,Digital soil mapping,Geomorphometry,Machine learning,Multiscale},
mendeley-groups = {resevol},
pages = {105612},
publisher = {Elsevier Ltd},
title = {{Assessing spatially heterogeneous scale representation with applied digital soil mapping}},
url = {https://doi.org/10.1016/j.envsoft.2022.105612},
volume = {160},
year = {2023}
}
@article{Millington2021,
abstract = {Increasing global demand for agricultural commodities has driven local land use/cover change (LUCC) and agricultural production across Brazil during the 21st century. Modelling tools are needed to help understand the range of possible outcomes due to these ‘telecoupled' global-to-local relationships, given future political, economic and environmental uncertainties. Here, we present CRAFTY-Brazil, a LUCC model representing production of multiple agricultural commodities that accounts for spatially explicit (e.g., land access) and temporally contingent (e.g., agricultural debt) processes of importance across our nearly four million km2 Brazilian study area. We calibrate the model calibration for 2001–2018, and run tests and scenarios about commodity demand, agricultural yields, climate change, and policy decisions for 2019–2035. Results indicate greater confidence in modelled time-series than spatial allocation. We discuss how our approach might be best understood to be agency-based, rather than agent-based, and highlight questions more and less appropriate for this approach.},
author = {Millington, James D.A. and Katerinchuk, Valeri and da Silva, Ramon Felipe Bicudo and Victoria, Daniel de Castro and Batistella, Mateus},
doi = {10.1016/j.envsoft.2021.105024},
file = {:home/brad/Dropbox/papers/MillingtonEtAl2021.pdf:pdf},
issn = {13648152},
journal = {Environmental Modelling and Software},
keywords = {Agent-based,Brazil,CRAFTY,Land use/cover,Simulation,Telecoupling},
mendeley-groups = {resevol},
pages = {105024},
publisher = {Elsevier Ltd},
title = {{Modelling drivers of Brazilian agricultural change in a telecoupled world}},
url = {https://doi.org/10.1016/j.envsoft.2021.105024},
volume = {139},
year = {2021}
}
@article{Zhang2020,
abstract = {Google Earth Engine (GEE) is an ideal platform for large-scale geospatial agricultural and environmental modeling based on its diverse geospatial datasets, easy-to-use application programming interface (API), rich reusable library, and high-performance computational capacity. However, using GEE to prepare geospatial data requires not only the skills of programming languages like JavaScript and Python, but also the knowledge of GEE APIs and data catalog. This paper presents the AgKit4EE toolkit to facilitate the use of the Cropland Data Layer (CDL) product over the GEE platform. This toolkit contains a variety of frequently used functions for use of CDL including crop sequence modeling, crop frequency modeling, confidence layer modeling, and land use change analysis. The experimental results suggest that the proposed software can significantly reduce the workload for modelers who conduct geospatial agricultural and environmental modeling with CDL data as well as developers who build the GEE-enabled geospatial cyberinfrastructure for agricultural land use modeling of the conterminous United States. AgKit4EE is an open source and it is free to use, modify, and distribute. The latest release of AgKit4EE can be imported to any modeling workflow developed using GEE Code Editor (https://code.earthengine.google.com/?accept_repo=users/czhang11/agkit4ee). The source code, examples, documentation, user community, and wiki pages are available on GitHub (https://github.com/czhang11/agkit4ee).},
author = {Zhang, Chen and Di, Liping and Yang, Zhengwei and Lin, Li and Hao, Pengyu},
doi = {10.1016/j.envsoft.2020.104694},
file = {:home/brad/Dropbox/papers/ZhangEtAl2020.pdf:pdf},
issn = {13648152},
journal = {Environmental Modelling and Software},
keywords = {Crop mapping,Cropland Data Layer,Geospatial cyberinfrastructure,Google Earth Engine,Land use modeling},
mendeley-groups = {resevol},
pages = {104694},
publisher = {Elsevier Ltd},
title = {{AgKit4EE: A toolkit for agricultural land use modeling of the conterminous United States based on Google Earth Engine}},
url = {https://doi.org/10.1016/j.envsoft.2020.104694},
volume = {129},
year = {2020}
}
