Modelling ectotherms’ populations considering physiological age structure and spatial motion: A novel approach

Ahmed, 2019, Analysing the impact of trap shape and movement behaviour of ground-dwelling arthropods on trap efficiency, Method Ecol. Evol., 10, 1246, 10.1111/2041-210X.13207 Ainseba, 2000, On a population dynamics control problem with age dependence and spatial structure, J. Mathemat. Anal. Appl., 248, 455, 10.1006/jmaa.2000.6921 Ainseba, 2001, Age-dependent population dynamics with diffusion, Abst. Appl. Anal., 0, 357, 10.1155/S108533750100063X Aylaj, 2021, On the interaction between soft and hard sciences: the role of mathematical sciences, Vietnam J. Mathemat., 49, 3, 10.1007/s10013-019-00381-3 Bellagamba, 1987, Stochastic models in fruit-fly population dynamics, 91 Berg, 1998, The infinite island model with sex-differentiated gene flow, Heredity, 81, 63, 10.1046/j.1365-2540.1998.00358.x Bono Rossello, 2019, A novel Observer-based Architecture for water management in large-scale (Hazelnut) orchards, IFAC Pap. Online, 52, 62, 10.1016/j.ifacol.2019.12.498 Briere, 1999, A novel rate model of temperature-dependent development for arthropods, Environ. Entomol., 28, 22, 10.1093/ee/28.1.22 Brunetti, 2020, A mathematical model for Xylella fastidiosa epidemics in the mediterranean regions. Promoting good agronomic practices for their effective control., Ecol. Modell., 432, 109204, 10.1016/j.ecolmodel.2020.109204 Buffoni, 2020, Numerical methods for the solution of PDE describing the stochastic development of an age-structured population, Computer science and mathematical methods in plant protection Buffoni, 2007, Structured population dynamics: continuous size and discontinuous stage structures, J. Math. Biol., 54, 555, 10.1007/s00285-006-0058-2 Cardé, 2008, Navigational strategies used by insects to find distant, wind-borne sources of odor, J. Chem. Ecol., 34, 854, 10.1007/s10886-008-9484-5 Cavaletto, 2021, Ambrosia beetle response to ethanol concentration and host tree species, J. Appl. Entomol., 12895 Clymans, 2020, Marking drosophila suzukii (diptera: drosophilidae) with fluorescent dusts, Insects, 11, 152, 10.3390/insects11030152 Cohen, 1981, A generalized diffusion model for growth and dispersal in a population, J. Math. Biol., 12, 237, 10.1007/BF00276132 Cook, 2007, The use of push-pull strategies in integrated pest management, Annu. Rev. Entomol., 52, 375, 10.1146/annurev.ento.52.110405.091407 Currier, 2018, Multisensory control of orientation in tethered flying drosophila, Curr. Biol., 28, 3533, 10.1016/j.cub.2018.09.020 Damos, 2016, Using multivariate cross correlations, granger causality and graphical models to quantify spatiotemporal synchronization and causality between pest populations, BMC Ecol., 16, 33, 10.1186/s12898-016-0087-7 Dangles, 2019, Ecosystem services provided by insects for achieving sustainable development goals, Ecosys. Ser., 35, 109, 10.1016/j.ecoser.2018.12.002 Demir, 2020, Walking drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters, eLife, 9, 1, 10.7554/eLife.57524 Di Blasio, 1977, Age-dependent population dynamics, atti della accademia nazionale dei lincei. classi di scienze fisiche, Mathemat. Naturali., 8, 175 Di Blasio, 1978, An initial-boundary value problem for age-dependent population diffusion, STAM J. Appl. Mathemat., 35, 593 El-Sayed, 2006, Potential of mass trapping for long-term pest management and eradication of invasive species, J. Econ. Entomol., 99, 1550, 10.1093/jee/99.5.1550 Emiljanowicz, 2014, Development, reproductive output and population growth of the fruit fly pest drosophila suzukii (diptera: drosophilidae) on artificial diet, J. Econ. Entomol., 107, 1392, 10.1603/EC13504 Feng, 2009, Seasonal migration of helicoverpa armigera (lepidoptera: noctuidae) over the bohai sea, J. Econ. Entomol., 102, 95, 10.1603/029.102.0114 Gatehouse, 1997, Behavior and ecological genetics of wind-borne migration by insects, Annu. Rev. Entomol., 42, 475, 10.1146/annurev.ento.42.1.475 Gilioli, 2016, A modelling framework for pest population dynamics and management: an application to the grape berry moth, Ecol. Modell., 320, 348, 10.1016/j.ecolmodel.2015.10.018 Gil-Tapetado, 2018, Distribution and dispersal of the invasive Asian chestnut gall wasp, dryocosmus kuriphilus (hymenoptera: cynipidae), across the heterogeneous landscape of the Iberian Peninsula, Eur. J. Entomol., 115, 575, 10.14411/eje.2018.055 Grassi, 2015, Development and efficacy of droskidrink, a food bait for trapping Drosophila suzukii, IOBC/WPRS Bullet., 109, 197 Grimm, 2020, Three questions to ask before using model outputs for decision support, Nat. Commun., 11, 4959, 10.1038/s41467-020-17785-2 Gutierrez, 2012, Prospective analysis of the invasive potential of the European grapevine moth Lobesia botrana (Den. & Schiff.) in California, Agricult. Forest Entomol., 14, 225, 10.1111/j.1461-9563.2011.00566.x Gutierrez, 2016, Analysis of the invasiveness of spotted wing drosophila (drosophila suzukii) in North America, Europe, and the Mediterranean Basin, Biol. Invas., 18, 3647, 10.1007/s10530-016-1255-6 Gutierrez, 2020, Climate warming effects on grape and grapevine moth (Lobesia botrana) in the Palearctic region, Agricult. Forest Entomol. Hanski, 2003, Metapopulation theory for fragmented landscapes, Theor. Popul. Biol., 64, 119, 10.1016/S0040-5809(03)00022-4 Hanski, 1994, A practical model of metapopulation dynamics, J. Animal Ecol., 63, 151, 10.2307/5591 Hanski, 1998, Metapopulation dynamics, Nature, 396, 41, 10.1038/23876 hyeon Byeon, 2018, Review of CLIMEX and MaxEnt for studying species distribution in South Korea, J. Asia-Pac. Biodiv., 11, 325 Jeger, 2004, Epidemiology of insect-transmitted plant viruses: modelling disease dynamics and control interventions, Physiol. Entomol., 29, 291, 10.1111/j.0307-6962.2004.00394.x Jung, 2016, Insect distribution in response to climate change based on a model: review of function and use of CLIMEX, Entomol. Res., 46, 223, 10.1111/1748-5967.12171 Kareiva, 1983, Local movement in herbivorous insects: applying a passive diffusion model to mark-recapture field experiments, Oecologia, 57, 322, 10.1007/BF00377175 Keyfitz, 1997, The McKendrick partial differential equation and its uses in epidemiology and population study, Mathemat. Comput. Modell., 26, 1, 10.1016/S0895-7177(97)00165-9 Knight, 2019, Radio-tracking reveals how wind and temperature influence the pace of daytime insect migration, Biol. Lett., 15, 20190327, 10.1098/rsbl.2019.0327 Kpienbaareh, 2011, Examining the potential of open source remote sensing for building effective decision support systems for precision agriculture in resource-poor settings, GeoJournal Kuparinen, 2006, Mechanistic models for wind dispersal, Trends Plant Sci., 11, 296, 10.1016/j.tplants.2006.04.006 Leduc, 2019, The ClimEx project: a 50-member ensemble of climate change projections at 12-km resolution over europe and northeastern north america with the canadian regional climate model (CRCM5), J. Appl. Meteorol. Climatol., 58, 663, 10.1175/JAMC-D-18-0021.1 Leitch, 2020, The long-distance flight behavior of drosophila suggests a general model for wind-assisted, Disper. Insect., 118 Leslie, 1945, On the use of matrices in certain population mathematics, Biometrika, 33, 183, 10.1093/biomet/33.3.183 Leslie, 1948, Some further notes on the use of matrices in population mathematics, Biometrika, 35, 213, 10.2307/2332342 Li, 2019, Spatial patterns and determinants of the diversity of hemipteran insects in the qinghai-tibetan plateau, Front. Ecol. Evol., 7, 1, 10.3389/fevo.2019.00165 Lippi, 2021, A yolo-based pest detection system for precision agriculture, 342 Ludwig, 1978, Qualitative analysis of insect outbreak systems: The spruce budworm and forest, J. Animal Ecol., 47, 315, 10.2307/3939 Ludwig, 1980, Harvesting strategies for a randomly fluctuating population, ICES J. Marine Sci., 39, 168, 10.1093/icesjms/39.2.168 Mathers, 2019, Sex-specific changes in the aphid DNA methylation landscape, Mol. Ecol., 28, 4228, 10.1111/mec.15216 McKendrick, 1926, Applications of Mathematics to Medical Problems, vol.44, 98 Merow, 2013, A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter, Ecography, 36, 1058, 10.1111/j.1600-0587.2013.07872.x Metha, 2020, Ecology and phenology of migration in insects, 23 Navarro-Llopis, 2008, Evaluation of traps and lures for mass trapping of Mediterranean fruit fly in citrus groves, J. Econ. Entomol., 101, 126, 10.1093/jee/101.1.126 Nguyen, 2018, Edge-biased distributions of insects., A Rev. Agron. Sustain. Develop., 38, 11, 10.1007/s13593-018-0488-4 Orlandini, 2018, 453 Otero, 2006, A Stochastic Population Dynamics Model for Aedes Aegypti,: Formulation and Application to a City with Temperate Climate, Bull. Math. Biol., 68, 1945, 10.1007/s11538-006-9067-y Ovaskainen, 2018, Frontiers in metapopulation biology: The legacy of Ilkka Hanski, Annu. Rev. Ecol. Evol. Sys., 49, 231, 10.1146/annurev-ecolsys-110617-062519 Phillips, 2004, A maximum entropy approach to species distribution modeling, proceedings, twenty-first international conference on machine learning, ICML, 2004, 655 Phillips, 2006, Modelling and analysis of the atmospheric nitrogen deposition in North Carolina, Int. J. Global Environ. Iss., 6, 231, 10.1504/IJGENVI.2006.010156 Polatto, 2014, Influence of abiotic factors and floral resource availability on daily foraging activity of bees, J. Insect. Behavior, 27, 593, 10.1007/s10905-014-9452-6 Potamitis, 2017, Automated remote insect surveillance at a global scale and the internet of things, Robotics, 6, 19, 10.3390/robotics6030019 Preisler, 1993, Modelling spatial patterns of trees attacked by bark-beetles, Appl. Stat., 42, 501, 10.2307/2986328 Preti, 2021, Insect pest monitoring with camera-equipped traps: strengths and limitations, J. Pest Sci., 94, 203, 10.1007/s10340-020-01309-4 Rassati, 2020, Fungal pathogen and ethanol affect host selection and colonization success in ambrosia beetles, Agricult. Forest Entomol., 22, 1, 10.1111/afe.12351 Rispe, 1999, Extreme life-cycle and sex ratio variation among sexually produced clones of the aphid rhopalosiphum padi (Homoptera: Aphididae), Oikos, 86, 254, 10.2307/3546443 Rossi Stacconi, 2019, Augmentative releases of Trichopria drosophilae for the suppression of early season Drosophila suzukii populations, BioControl, 64, 9, 10.1007/s10526-018-09914-0 Rossini, 2019, Use of ROOT to build a software optimized for parameter estimation and simulations with distributed delay model, Ecol. Inf., 50, 184, 10.1016/j.ecoinf.2019.02.002 Rossini, 2019, A novel modelling approach to describe an insect life cycle vis-à-vis plant protection: description and application in the case study of Tuta absoluta, Ecol. Modell., 409, 108778, 10.1016/j.ecolmodel.2019.108778 Rossini, 2020, EntoSim, a ROOT-based simulator to forecast insects’ life cycle: description and application in the case of, Lobesia Botrana. Crop Protect., 129 Rossini, 2020, Distributed delay model and von foerster's equation: different points of view to describe insects’ life cycles with chronological age and physiological time, Ecol. Inf., 59, 101117, 10.1016/j.ecoinf.2020.101117 Rossini, 2020, Reformulation of the distributed delay model to describe insect pest populations using count variables, Ecol. Modell., 436, 109286, 10.1016/j.ecolmodel.2020.109286 Rossini, 2020, A modelling approach to describe the Anthonomus eugenii (Coleoptera: Curculionidae) life cycle in plant protection: a priori and a posteriori analysis, Flor. Entomol., 103, 259, 10.1653/024.103.0217 Rossini, 2020, A novel version of the Von Foerster equation to describe poikilothermic organisms including physiological age and reproduction rate, Ricer. Di. Matemat., 6 Rossini, 2020, Modelling drosophila suzukii adult male populations: a physiologically based approach with validation, Insects, 11, 751, 10.3390/insects11110751 Rossini, 2021, Life tables and a physiologically based model application to Corcyra cephalonica (Stainton) populations, J. Stor. Prod. Res., 91, 101781, 10.1016/j.jspr.2021.101781 Rossini, 2021, 13066 Rossini, 2021, EntoSim, an insects life cycle simulator enclosing multiple models in a Docker container, Environ. Eng. Manage. J., 20, 1703, 10.30638/eemj.2021.159 Rossini, 2021, A general ODE-based model to describe the physiological age structure of ectotherms: description and application to drosophila suzukii, Ecol. Modell., 456, 109673, 10.1016/j.ecolmodel.2021.109673 Roux, 2011, Spatial patterns and eco-epidemiological systems - part I: multi-scale spatial modelling of the occurrence of Chagas disease insect vectors, Geospat. Health, 6, 41, 10.4081/gh.2011.156 Ryan, 2016, Thermal tolerances of the spotted-wing drosophila drosophila suzukii (Diptera: Drosophilidae), J. Econ. Entomol., 109, 746, 10.1093/jee/tow006 Salom, 1991, Flight behavior of scolytid beetle in response to semiochemicals at different wind speeds, J. Chem. Ecol., 17, 647, 10.1007/BF00982133 Scotter, 1971, An insect dispersal parameter, Ecology, 52, 174, 10.2307/1934751 Sharov, 1996, Modelling forest insect dynamics, 6 Sultson, 2021, Orographic factors as a predictor of the spread of the siberian silk Moth outbreak in the mountainous southern taiga forests of Siberia, Land, 10, 115, 10.3390/land10020115 Tait, 2018, Large-scale spatial dynamics of Drosophila suzukii in Trentino, Italy, J. Pest Sci., 91, 1213, 10.1007/s10340-018-0985-x Takeuchi, 2019, Estimation of dispersal distance of the soybean pod borer leguminivora glycinivorella (Lepidoptera: Tortricidae) by mark-recapture experiments, Appl. Entomol. Zoolog., 54, 285, 10.1007/s13355-019-00625-1 Thistlewood, 2018, Spatial analysis of seasonal dynamics and overwintering of Drosophila suzukii (Diptera: Drosophilidae) in the Okanagan-Columbia Basin 2010-2014, Environ. Entomol., 47, 221, 10.1093/ee/nvx178 Tochen, 2014, Temperature-related development and population parameters for Drosophila suzukii (Diptera: Drosophilidae) on cherry and blueberry, Environ. Entomol., 43, 501, 10.1603/EN13200 Vale, 1983, The effects of odours, wind direction and wind speed on the distribution of Glossina (Diptera: Glossinidae) and other insects near stationary targets, Bull. Entomol. Res., 73, 53, 10.1017/S0007485300013791 Vinatier, 2011, Factors and mechanisms explaining spatial heterogeneity: a review of methods for insect populations, Method Ecol. Evol., 2, 11, 10.1111/j.2041-210X.2010.00059.x Virla, 2003, Estudios bioecológicos sobre la chicharrita del maíz “Dalbulus maidis” (Insecta - Cicadellidae) en Tucumán (Argentina), Boletín de sanidad vegetal. Plagas, 29, 17 Volterra, 1926, 2 Von Foerster, 2010, Some remarks on changing populations, 382 Wang, 2002, Modeling the bathtub shape hazard rate function in terms of reliability, Reliability engineering & system safety, 75, 397, 10.1016/S0951-8320(01)00124-7 Whelan, 2000, The null hypothesis of precision agriculture management, Precision Agricult., 2, 265, 10.1023/A:1011838806489 Wong, 2018, Drosophila suzukii flight performance reduced by starvation but not affected by humidity, J. Pest Sci., 91, 1269, 10.1007/s10340-018-1013-x Young, 2005, 116