Advances in crop insect modelling methods—Towards a whole system approach
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Tobias Landmann | Sunday Ekesi | Christian Borgemeister | L. V. Nedorezov | Ritter A. Guimapi | Lisa Biber-Freudenberger | Bruce Anani | Tino Johansson | Henri E. Z. Tonnang | Henri E. Z. Tonnang | Bisseleua D. B. Herve | Daisy Salifu | Sevgan Subramanian | Valentine B. Ngowi | Francois M. M. Kakmeni | Hippolyte Affognon | Saliou Niassy | Frank T. Ndjomatchoua | Sansao A. Pedro | Chrysantus M. Tanga | Paulin Nana | Komi K. M. Fiaboe | Samira F. Mohamed | Nguya K. Maniania | S. A. Pedro | Henri E. Z. Tonnang | F. M. Kakmeni | C. Borgemeister | T. Landmann | Lisa Biber-Freudenberger | T. Johansson | H. Tonnang | P. Nana | F. T. Ndjomatchoua | K. Fiaboe | H. Affognon | S. Ekesi | C. Tanga | D. Salifu | S. Niassy | S. Subramanian | R. Guimapi | N. K. Maniania | Bisseleua D. B. Hervé | V. Ngowi | Bruce Y. Anani | Samira Mohamed | Bruce Anani | Tino Johansson | Valentine B. Ngowi | L. Biber-Freudenberger
[1] J. Luyten,et al. Simulation of Biological Processes , 2018, Agricultural Systems modeting and Simulation.
[2] Henri E. Z. Tonnang,et al. Spatial and temporal spread of maize stem borer Busseola fusca (Fuller) (Lepidoptera: Noctuidae) damage in smallholder farms , 2016 .
[3] H. Groote,et al. Assessing the long-term welfare effects of the biological control of cereal stemborer pests in East and Southern Africa: Evidence from Kenya, Mozambique and Zambia , 2016 .
[4] David W. Archer,et al. Exploring agricultural production systems and their fundamental components with system dynamics modelling , 2016 .
[5] George Okeyo,et al. Modeling the risk of invasion and spread of Tuta absoluta in Africa , 2016 .
[6] Henri E. Z. Tonnang,et al. Future Risks of Pest Species under Changing Climatic Conditions , 2016, PloS one.
[7] H. Affognon,et al. Impact assessment of Integrated Pest Management (IPM) strategy for suppression of mango-infesting fruit flies in Kenya , 2016 .
[8] Henri E. Z. Tonnang,et al. Correction: Identification and Risk Assessment for Worldwide Invasion and Spread of Tuta absoluta with a Focus on Sub-Saharan Africa: Implications for Phytosanitary Measures and Management , 2015, PloS one.
[9] Itamar M. Lensky,et al. Modeling insect population fluctuations with satellite land surface temperature , 2015 .
[10] Henri E. Z. Tonnang,et al. Identification and Risk Assessment for Worldwide Invasion and Spread of Tuta absoluta with a Focus on Sub-Saharan Africa: Implications for Phytosanitary Measures and Management , 2015, PloS one.
[11] G. Ragaglini,et al. Large‐scale simulation of temperature‐dependent phenology in wintering populations of Bactrocera oleae (Rossi) , 2015 .
[12] Henri E. Z. Tonnang,et al. Predicting the Impact of Temperature Change on the Future Distribution of Maize Stem Borers and Their Natural Enemies along East African Mountain Gradients Using Phenology Models , 2015, PloS one.
[13] Roderick M. Rejesus,et al. Economic Impacts of Integrated Pest Management (IPM) Farmer Field Schools (FFS): Evidence from Onion Farmers in the Philippines , 2015 .
[14] Johan Ehrlén,et al. Predicting changes in the distribution and abundance of species under environmental change , 2015, Ecology letters.
[15] Brian D. Fath,et al. Sustainable systems promote wholeness-extending transformations: The contributions of systems thinking , 2014 .
[16] J. Kroschel,et al. Effect of temperature on the life history parameters of noctuid lepidopteran stem borers, busseola fusca and sesamia calamistis , 2014 .
[17] David B. Lobell,et al. Robust features of future climate change impacts on sorghum yields in West Africa , 2014 .
[18] Mahesh Kumar,et al. Predicting the impact of climate change on regional and seasonal abundance of the mealybug Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) using temperature-driven phenology model linked to GIS , 2014 .
[19] Sizah Mwalusepo,et al. Stability Analysis of Competing Insect Species for a Single Resource , 2014, J. Appl. Math..
[20] James W. Jones,et al. Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment , 2014 .
[21] Brendan A. Wintle,et al. Predicting species distributions for conservation decisions , 2013, Ecology letters.
[22] Trevor Hastie,et al. Inference from presence-only data; the ongoing controversy. , 2013, Ecography.
[23] Florian Altermatt,et al. Predicting novel trophic interactions in a non-native world. , 2013, Ecology letters.
[24] Leon C. Hinz,et al. Using Maxent to model the historic distributions of stonefly species in Illinois streams: The effects of regularization and threshold selections , 2013 .
[25] H. Juárez,et al. Insect Life Cycle Modelling (ILCYM) software - a new tool for regional and global insect pest risk assessments under current and future climate change scenarios. , 2013 .
[26] Reinhard Simon,et al. Predicting climate-change-caused changes in global temperature on potato tuber moth Phthorimaea operculella (Zeller) distribution and abundance using phenology modeling and GIS mapping , 2013 .
[27] Simone Orlandini,et al. The effects of climate variability and the color of weather time series on agricultural diseases and pests, and on decisions for their management , 2013 .
[28] Davide Fumagalli,et al. Comparison of modelling approaches to simulate the phenology of the European corn borer under future climate scenarios , 2012 .
[29] A. Dankyi,et al. The Effects of Integrated Pest Management Techniques Farmer Field Schools on Groundnut Productivity: Evidence from Ghana , 2012 .
[30] R. Didham,et al. Landscape moderation of biodiversity patterns and processes ‐ eight hypotheses , 2012, Biological reviews of the Cambridge Philosophical Society.
[31] Dong Ren,et al. Crop diseases and pests monitoring based on remote sensing: A survey , 2012, World Automation Congress 2012.
[32] Y. Clough,et al. A minor pest reduces yield losses by a major pest: plant‐mediated herbivore interactions in Indonesian cacao , 2012 .
[33] Gerald Forkuor,et al. Comparison of SRTM and ASTER Derived Digital Elevation Models over Two Regions in Ghana - Implications for Hydrological and Environmental Modeling , 2012 .
[34] R. Halvorsen,et al. Species distribution modelling—Effect of design and sample size of pseudo-absence observations , 2011 .
[35] Yann Clough,et al. Multifunctional shade‐tree management in tropical agroforestry landscapes – a review , 2011 .
[36] L. V. Nedorezov,et al. Host–parasitoid population density prediction using artificial neural networks: diamondback moth and its natural enemies , 2010 .
[37] Anne G. Hoen,et al. Field and climate-based model for predicting the density of host-seeking nymphal Ixodes scapularis, an important vector of tick-borne disease agents in the eastern United States , 2010 .
[38] Tong‐Xian Liu,et al. Functional Synchronization of Biological Rhythms in a Tritrophic System , 2010, PloS one.
[39] D. Kriticos,et al. Pest Risk Maps for Invasive Alien Species: A Roadmap for Improvement , 2010 .
[40] J. Kean,et al. Progress in risk assessment for classical biological control , 2010 .
[41] K. Anderson,et al. Modeling herbivore competition mediated by inducible changes in plant quality. , 2009 .
[42] S. Khandker,et al. Handbook on Impact Evaluation: Quantitative Methods and Practices , 2009 .
[43] J. Luck,et al. A concept model to estimate the potential distribution of the Asiatic citrus psyllid (Diaphorina citri Kuwayama) in Australia under climate change—A means for assessing biosecurity risk , 2009 .
[44] Peng Lin,et al. A prediction model for population occurrence of paddy stem borer (Scirpophaga incertulas), based on Back Propagation Artificial Neural Network and Principal Components Analysis , 2009 .
[45] S. Ekesi,et al. Effect of Metarhizium anisopliae inoculation on the mating behavior of three species of African Tephritid fruit flies, Ceratitis capitata, Ceratitis cosyra and Ceratitis fasciventris , 2009 .
[46] M. Kearney,et al. Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges. , 2009, Ecology letters.
[47] M De Meyer,et al. Ecological niche and potential geographic distribution of the invasive fruit fly Bactrocera invadens (Diptera, Tephritidae) , 2009, Bulletin of Entomological Research.
[48] Michael J. Watts,et al. Estimating the risk of insect species invasion: Kohonen self-organising maps versus k-means clustering. , 2009 .
[49] J. Elith,et al. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .
[50] G. Alagarswamy,et al. Spatial variation of crop yield response to climate change in East Africa , 2009 .
[51] L. V. Nedorezov,et al. Assessing the impact of biological control of Plutella xylostella through the application of Lotka-Volterra model , 2009 .
[52] Yafit Cohen,et al. Effect of elevation on spatio‐temporal patterns of olive fly (Bactrocera oleae) populations in northern Greece , 2008 .
[53] L. V. Nedorezov,et al. Assessing the importance of self-regulating mechanisms in diamondback moth population dynamics: application of discrete mathematical models. , 2008, Journal of theoretical biology.
[54] Javier G. P. Gamarra,et al. Spatial scaling of mountain pine beetle infestations. , 2008, The Journal of animal ecology.
[55] Jurgen Kurths,et al. Synchronization in complex networks , 2008, 0805.2976.
[56] J. Vandermeer,et al. Spatial pattern and ecological process in the coffee agroforestry system. , 2008, Ecology.
[57] Wenjun Zhang,et al. Neural network modeling of survival dynamics of holometabolous insects: A case study , 2008 .
[58] Ian Kaplan,et al. Interspecific interactions in phytophagous insects revisited: a quantitative assessment of competition theory. , 2007, Ecology letters.
[59] Eliot R. Smith,et al. Agent-Based Modeling: A New Approach for Theory Building in Social Psychology , 2007, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.
[60] F. Baret,et al. Quantification of plant stress using remote sensing observations and crop models: the case of nitrogen management. , 2006, Journal of experimental botany.
[61] G. J. Moraes,et al. Identification of priority areas in South America for exploration of natural enemies for classical biological control of Tetranychus evansi (Acari: Tetranychidae) in Africa , 2006 .
[62] S. Hartley,et al. Quantifying uncertainty in the potential distribution of an invasive species: climate and the Argentine ant. , 2006, Ecology letters.
[63] J. Logan,et al. Temperature-dependent phenology and predation in arthropod systems , 2006 .
[64] M. Hoddle,et al. Use of life table statistics and degree-day values to predict the invasion success of Gonatocerus ashmeadi (Hymenoptera: Mymaridae), an egg parasitoid of Homalodisca coagulata (Hemiptera: Cicadellidae), in California , 2006 .
[65] Suzana Dragicevic,et al. A fuzzy-constrained cellular automata model of forest insect infestations , 2006 .
[66] Uta Berger,et al. Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology , 2005, Science.
[67] W. Thuiller,et al. Predicting species distribution: offering more than simple habitat models. , 2005, Ecology letters.
[68] Jarkko Kari,et al. Theory of cellular automata: A survey , 2005, Theor. Comput. Sci..
[69] Iram Gleria,et al. The Lotka-Volterra canonical format , 2005 .
[70] Aziz Elbehri,et al. Estimating the Impact of Transgenic Bt Cotton on West and Central Africa: A General Equilibrium Approach , 2004 .
[71] W. Cramer,et al. The performance of models relating species geographical distributions to climate is independent of trophic level , 2004 .
[72] Y. Phillis,et al. Evaluating strategies for sustainable development: fuzzy logic reasoning and sensitivity analysis , 2004 .
[73] Michael Jackson,et al. Systems Thinking: Creative Holism for Managers , 2003 .
[74] R. Sutherst,et al. Prediction of species geographical ranges , 2003 .
[75] W. Choi,et al. A matrix model for predicting seasonal fluctuations in field populations of Paronychiurus kimi (Collembola: Onychiruidae) , 2003 .
[76] H. Groote,et al. Economic impact of biological control of water hyacinth in Southern Benin , 2003 .
[77] H. Groote,et al. Socio-economic impact of biological control of mango mealybug in Benin , 2002 .
[78] S. Ellner,et al. Fitting population dynamic models to time-series data by gradient matching , 2002 .
[79] E. Bonabeau. Agent-based modeling: Methods and techniques for simulating human systems , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[80] M. Thomas,et al. Natural enemy diversity and pest control: patterns of pest emergence with agricultural intensification. , 2002 .
[81] P. Stott,et al. Origins and estimates of uncertainty in predictions of twenty-first century temperature rise , 2002, Nature.
[82] Kimberly A. With,et al. THRESHOLD EFFECTS OF LANDSCAPE STRUCTURE ON BIOLOGICAL CONTROL IN AGROECOSYSTEMS , 2002 .
[83] S. Ekesi,et al. Mortality in Three African Tephritid Fruit Fly Puparia and Adults Caused by the Entomopathogenic Fungi, Metarhizium anisopliae and Beauveria bassiana , 2002 .
[84] N. Magan,et al. Fungi as Biocontrol Agents: Progress, Problems and Potential , 2001 .
[85] Friedrich Recknagel,et al. Applications of machine learning to ecological modelling , 2001 .
[86] Jim M Cushing,et al. Chaos and population control of insect outbreaks , 2001 .
[87] Young-Seuk Park,et al. Use of an Artificial Neural Network to Predict Population Dynamics of the Forest–Pest Pine Needle Gall Midge (Diptera: Cecidomyiida) , 2000 .
[88] Bai-Lian Li,et al. Fractal geometry applications in description and analysis of patch patterns and patch dynamics , 2000 .
[89] Mywish K. Maredia,et al. Ex Post Evaluation of Economic Impacts of Agricultural Research Programs: a Tour of Good Practice , 2000 .
[90] D. J. Bailey,et al. Saprotrophic invasion by the soil‐borne fungal plant pathogen Rhizoctonia solani and percolation thresholds , 2000 .
[91] A. Janvry,et al. Technological change in agriculture and poverty reduction , 1999 .
[92] David R. B. Stockwell,et al. The GARP modelling system: problems and solutions to automated spatial prediction , 1999, Int. J. Geogr. Inf. Sci..
[93] J. Pierre,et al. A Novel Rate Model of Temperature-Dependent Development for Arthropods , 1999 .
[94] Paul S. Addison,et al. Fractals and Chaos: An Illustrated Course , 1997 .
[95] R. Moss,et al. The regional impacts of climate change : an assessment of vulnerability , 1997 .
[96] Robert Lee Schooley,et al. Patchy Landscapes and Animal Movements: Do Beetles Percolate? , 1997 .
[97] Wayne M. Getz,et al. Modelling the biological control of insect pests: a review of host-parasitoid models , 1996 .
[98] James F. Oehmke,et al. Science under scarcity: Principles and practice for agricultural research evaluation and priority setting , 1996 .
[99] B. Beattie. Science Under Scarcity: Principles and Practice for Agricultural Research Evaluation and Priority Setting , 1995 .
[100] A. Gutierrez,et al. Modelling the interaction of cotton and the cotton boll weevil. II, Bollweevil (Anthonomus grandis) in Brazil , 1991 .
[101] N. D. Stone,et al. MODELLING THE INTERACTION OF COTTON AND THE COTTON BOLL WEEVIL. I. A COMPARISON OF GROWTH AND DEVELOPMENT OF COTTON VARIETIES , 1991 .
[102] R. Bawden. Systems thinking and practice in agriculture , 1991 .
[103] P. Neuenschwander,et al. Analysis of Biological Control of Cassava Pests in Africa. II. Cassava Mealybug Phenacoccus manihoti , 1988 .
[104] R. Norgaard. The Biological Control of Cassava Mealybug in Africa , 1988 .
[105] R. W. Sutherst,et al. A computerised system for matching climates in ecology , 1985 .
[106] Lee G. Cooper,et al. Parameter Estimation for a Multiplicative Competitive Interaction Model—Least Squares Approach , 1974 .
[107] L. Lefkovitch. The study of population growth in organisms grouped by stages , 1965 .
[108] P. H. Leslie. On the use of matrices in certain population mathematics. , 1945, Biometrika.
[109] C. Eisenhart,et al. Tables for Testing Randomness of Grouping in a Sequence of Alternatives , 1943 .
[110] Mahesh Kumar,et al. A temperature-based phenology model for predicting development, survival and population growth potential of the mealybug, Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) , 2014 .
[111] M. Njeri. ECONOMIC EVALUATION OF INTEGRATED PEST MANAGEMENT TECHNOLOGY FOR CONTROL OF MANGO FRUIT FLIES IN EMBU COUNTY, KENYA , 2014 .
[112] Maureen Nandwa Kuboka,et al. Effect of Temperature on the Efficacy of Metarhizium Anisopliae (Metchnikoff) Sorokin In the Control of Western Flower Thrips in French Beans , 2013 .
[113] Mahabub Hossain,et al. The Impact of Integrated Pest Management Information Dissemination Methods on Insecticide Use and Efficiency: Evidence from Rice Producers , 2009 .
[114] Mark New,et al. Ensemble forecasting of species distributions. , 2007, Trends in ecology & evolution.
[115] I. Jonckheerea,et al. A fractal dimension-based modelling approach for studying the effect of leaf distribution on LAI retrieval in forest canopies , 2006 .
[116] J. Goudriaan,et al. ON APPROACHES AND APPLICATIONS OF THE WAGENINGEN CROP MODELS , 2003 .
[117] A. Shelton,et al. Economic, ecological, food safety, and social consequences of the deployment of bt transgenic plants. , 2002, Annual review of entomology.
[118] H. Herren,et al. Economics of biological control of cassava mealybug in Africa , 2000 .
[119] T. Carter. Assessing Climate Change Adaptations: The IPCC Guidelines , 1996 .
[120] G. Grimmett. What Is Percolation , 1989 .
[121] E. G. Lewis. On the Generation and Growth of a Population , 1977 .
[122] P. S. Messenger. Use of Life Tables in a Bioclimatic Study of an Experimental Aphid‐Braconid Wasp Host‐Parasite System , 1964 .