Aino S, Yodo T, Yoshioka M (2015) Changes in the composition of stock origin and standard length of ayu Plecoglossus altivelis altivelis during the Tomozuri angling season in the Nagara River, central Japan. Fish Sci 81(1):37–42. https://doi.org/10.1007/s12562-014-0822-y
CAS
Article
Google Scholar
Aït-Sahalia Y, Matthys F (2019) Robust consumption and portfolio policies when asset prices can jump. J Econ Theory 179:1–56. https://doi.org/10.1016/j.jet.2018.09.006
Article
Google Scholar
Azimzadeh P, Bayraktar E, Labahn G (2018) Convergence of implicit schemes for Hamilton–Jacobi–Bellman quasi-variational inequalities. SIAM J Control Optim 56(6):3994–4016. https://doi.org/10.1137/18M1171965
Article
Google Scholar
Barles G, Rouy E (1998) A strong comparison result for the Bellman equation arising in stochastic exit time control problems and its applications. Commun Partial Differ Equ 23(11–12):1995–2033. https://doi.org/10.1080/03605309808821409
Article
Google Scholar
Barles G, Souganidis PE (1991) Convergence of approximation schemes for fully nonlinear second order equations. Asymptot Anal 4(3):271–283. https://doi.org/10.3233/ASY-1991-4305
Article
Google Scholar
Braumann CA (2007) Harvesting in a random environment: Ito or Stratonovich calculus? J Theor Biol 244(3):424–432. https://doi.org/10.1016/j.jtbi.2006.08.029
Article
PubMed
Google Scholar
Brigo D, Jeanblanc M, Vrins F (2019) SDEs with uniform distributions: Peacocks, Conic martingales and mean reverting uniform diffusions. Stoch Process Appl 99:99. https://doi.org/10.1016/j.spa.2019.11.003
Article
Google Scholar
Company R, Egorova VN, Jódar L, Soleymani F (2016) A mixed derivative terms removing method in multi-asset option pricing problems. Appl Math Lett 60:108–114. https://doi.org/10.1016/j.aml.2016.04.011
Article
Google Scholar
Crandall MG, Ishii H, Lions PL (1992) User’s guide to viscosity solutions of second order partial differential equations. Bull Am Math Soc 27(1):1–67. https://doi.org/10.1090/S0273-0979-1992-00266-5
Article
Google Scholar
Debrabant K, Jakobsen E (2013) Semi-Lagrangian schemes for linear and fully non-linear diffusion equations. Math Comput 82(283):1433–1462. https://doi.org/10.1090/S0025-5718-2012-02632-
Article
Google Scholar
Denisov SI, Bystrik YS (2019) Statistics of bounded processes driven by Poisson white noise. Phys A 515:38–46. https://doi.org/10.1016/j.physa.2018.09.158
Article
Google Scholar
Desrosiers C, Leflaive J, Eulin A, Ten-Hage L (2013) Bioindicators in marine waters: benthic diatoms as a tool to assess water quality from eutrophic to oligotrophic coastal ecosystems. Ecol Ind 32:25–34. https://doi.org/10.1016/j.ecolind.2013.02.021
CAS
Article
Google Scholar
Duan C, Liu C, Wang C, Yue X (2019) Numerical complete solution for random genetic drift by energetic variational approach. ESAIM Math Model Numer Anal 53(2):615–634. https://doi.org/10.1051/m2an/2018058
Article
Google Scholar
Ekström E, Tysk J (2010) The Black–Scholes equation in stochastic volatility models. J Math Anal Appl 368(2):498–507. https://doi.org/10.1016/j.jmaa.2010.04.014
Article
Google Scholar
Ensminger I, Hagen C, Braune W (2000) Strategies providing success in a variable habitat: I. Relationships of environmental factors and dominance of Cladophora glomerata. Plant Cell Environ 23(10):1119–1128. https://doi.org/10.1046/j.1365-3040.2000.00596.x
Article
Google Scholar
Feng X, Jensen M (2017) Convergent semi-Lagrangian methods for the Monge–Ampère equation on unstructured grids. SIAM J Numer Anal 55(2):691–712. https://doi.org/10.1137/16M1061709
Article
Google Scholar
Fleming WH, Soner HM (2006) Controlled Markov processes and viscosity solutions. Springer, New York
Google Scholar
Floris C (2019) First-passage time study of a stochastic growth model. Nonlinear Dyn 98(2):861–872. https://doi.org/10.1007/s11071-019-05189-x
Article
Google Scholar
Fouque JP, Ning N (2018) Uncertain volatility models with stochastic bounds. SIAM J Financ Math 9(4):1175–1207. https://doi.org/10.1137/17M1116908
Article
Google Scholar
Friedrichs KO (1944) The identity of weak and strong extensions of differential operators. Trans Am Math Soc 55(1):132–151. https://doi.org/10.2307/199014
Article
Google Scholar
Gladyshev MI, Gubelit YI (2019) Green tides: new consequences of the eutrophication of natural waters (invited review). Contemp Probl Ecol 12(2):109–125. https://doi.org/10.1134/S1995425519020057
Article
Google Scholar
Grigoriu M (2002) Stochastic calculus: applications in science and engineering. Birkhäuser, Boston
Book
Google Scholar
Guiver C, Mueller M, Hodgson D, Townley S (2016) Robust set-point regulation for ecological models with multiple management goals. J Math Biol 72(6):1467–1529. https://doi.org/10.1007/s00285-015-0919-7
Article
PubMed
Google Scholar
Han B, Wong HY (2019) Optimal investment and consumption problems under correlation ambiguity. IMA J Manag Math. https://doi.org/10.1093/imaman/dpz002
Article
Google Scholar
Ismail A, Pham H (2019) Robust Markowitz mean–variance portfolio selection under ambiguous covariance matrix. Math Finance 29(1):174–207. https://doi.org/10.1111/mafi.12169
Article
Google Scholar
Ji H, Shao J, Xi F (2020) Stability of regime-switching jump diffusion processes. J Math Anal Appl 484(1):123727. https://doi.org/10.1016/j.jmaa.2019.123727
Article
Google Scholar
Koleva MN, Vulkov LG (2019) A new mixed derivative terms removing numerical method for option pricing in the Heston model. In: AIP conference proceedings, vol 2172(1). AIP Publishing LLC, p 070012
Lions JL, Magenes E (1972) Non-homogeneous boundary value problems and applications, vol 1. Springer, Berlin
Book
Google Scholar
Manoussi V, Xepapadeas A, Emmerling J (2018) Climate engineering under deep uncertainty. J Econ Dyn Control 94:207–224. https://doi.org/10.1016/j.jedc.2018.06.003
Article
Google Scholar
Matsumoto M, Nishimura T (1998) Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Trans Model Comput Simul (TOMACS) 8(1):3–30. https://doi.org/10.1145/272991.272995
Article
Google Scholar
Mertz L, Pironneau O (2019) Numerical analysis of degenerate Kolmogorov equations of constrained stochastic Hamiltonian systems. Comput Math Appl 78(8):2719–2733. https://doi.org/10.1016/j.camwa.2019.04.013
Article
Google Scholar
Miyagawa Y, Onoda Y, Ohtsuki K, Nakamura K (2019) A simple method for assessment of colonization risk of a large filamentous algae Cladophora glomerata at dam downstream reaches using bed material size distribution data. Annu J Hydraul Eng 75(2):I_505–I_510 (in Japanese with English Abstract)
Google Scholar
Neufeld A, Nutz M (2017) Nonlinear Lévy processes and their characteristics. Trans Am Math Soc 369(1):69–95. https://doi.org/10.1090/tran/6656
Article
Google Scholar
Oberman AM (2006) Convergent difference schemes for degenerate elliptic and parabolic equations: Hamilton–Jacobi equations and free boundary problems. SIAM J Numer Anal 44(2):879–895. https://doi.org/10.1137/S0036142903435235
Article
Google Scholar
Okada H, Watanabe Y (2007) Distribution of Cladophora glomerata in the riffle with reference to the stability of streambed substrata. Landsc Ecol Eng 3(1):15–20. https://doi.org/10.1007/s11355-006-0017-5
Article
Google Scholar
Øksendal B (2003) Stochastic differential equations. Springer, Berlin
Book
Google Scholar
Øksendal B, Sulem A (2019) Applied stochastic control of jump diffusions. Springer Nature, Cham
Book
Google Scholar
Pirrotta A (2007) Multiplicative cases from additive cases: extension of Kolmogorov–Feller equation to parametric Poisson white noise processes. Probab Eng Mech 22(2):127–135. https://doi.org/10.1016/j.probengmech.2006.08.005
Article
Google Scholar
Peckham SD, Waymire EC, De Leenheer P (2018) Critical thresholds for eventual extinction in randomly disturbed population growth models. J Math Biol 77(2):495–525. https://doi.org/10.1007/s00285-018-1217-y
Article
PubMed
Google Scholar
Peng S (2019) Nonlinear expectations and stochastic calculus under uncertainty: with robust CLT and G-Brownian motion. Springer, Berlin
Book
Google Scholar
Pérez P, Ruiz-Herrera A, San Luis AM (2019) Management guidelines in disturbance-prone populations: the importance of the intervention time. J Theor Biol. https://doi.org/10.1016/j.jtbi.2019.110075
Article
PubMed
Google Scholar
Pesce M, Critto A, Torresan S, Giubilato E, Pizzol L, Marcomini A (2019) Assessing uncertainty of hydrological and ecological parameters originating from the application of an ensemble of ten global-regional climate model projections in a coastal ecosystem of the lagoon of Venice, Italy. Ecol Eng 133:121–136. https://doi.org/10.1016/j.ecoleng.2019.04.011
Article
Google Scholar
Picarelli A, Reisinger C (2020) Probabilistic error analysis for some approximation schemes to optimal control problems. Syst Control Lett 137:104619. https://doi.org/10.1016/j.sysconle.2019.104619
Article
Google Scholar
Platen E, Bruti-Liberati N (2010) Numerical solution of stochastic differential equations with jumps in finance. Springer, Berlin
Book
Google Scholar
Pooley DM, Forsyth PA, Vetzal KR (2003) Numerical convergence properties of option pricing PDEs with uncertain volatility. IMA J Numer Anal 23(2):241–267. https://doi.org/10.1093/imanum/23.2.24
Article
Google Scholar
Reaver NGF, Kaplan DA, Mattson RA, Carter E, Sucsy PV, Frazer TK (2019) Hydrodynamic controls on primary producer communities in spring-fed rivers. Geophys Res Lett 46(9):4715–4725. https://doi.org/10.1029/2019GL082571
Article
Google Scholar
Reisinger C, Arto JR (2017) Boundary treatment and multigrid preconditioning for semi-Lagrangian schemes applied to Hamilton–Jacobi–Bellman equations. J Sci Comput 72(1):198–230
Article
Google Scholar
Salmaso F, Quadroni S, Compare S, Gentili G, Crosa G (2019) Benthic diatoms as bioindicators of environmental alterations in different watercourses of northern Italy. Environ Monit Assess. https://doi.org/10.1007/s10661-019-7290-x
Article
PubMed
Google Scholar
Schneider SC, Sample JE, Moe JS, Petrin Z, Meissner T, Hering D (2018) Unravelling the effect of flow regime on macroinvertebrates and benthic algae in regulated versus unregulated streams. Ecohydrology 11(7):e1996. https://doi.org/10.1002/eco.1996
Article
Google Scholar
Schlomann BH (2018) Stationary moments, diffusion limits, and extinction times for logistic growth with random catastrophes. J Theor Biol 454:154–163. https://doi.org/10.1016/j.jtbi.2018.06.007
Article
PubMed
PubMed Central
Google Scholar
Segatto PL, Battin TJ, Bertuzzo E (2020) Modeling the coupled dynamics of stream metabolism and microbial biomass. Limnol Oceanogr. https://doi.org/10.1002/lno.11407
Article
Google Scholar
Soleymani F, Akgül A (2019) European option valuation under the Bates PIDE in finance: a numerical implementation of the Gaussian scheme. Discrete Continu Dyn Syst S. https://doi.org/10.3934/dcdss.2020052
Article
Google Scholar
Stancheva R, Fetscher AE, Sheath RG (2012) A novel quantification method for stream-inhabiting, non-diatom benthic algae, and its application in bioassessment. Hydrobiologia 684(1):225–239. https://doi.org/10.1007/s10750-011-0986-8
CAS
Article
Google Scholar
Takahashi I, Azuma K, Fujita S, Kinoshita I (2002) Habitat shift of ayu Plecoglossus altivelis altivelisin early stages from waters adjacent to the bank to the center of flow in the Shimanto estuary. Fish Sci 68:554–559. https://doi.org/10.1046/j.1444-2906.2002.00461.x
CAS
Article
Google Scholar
Tran TD, Hofrichter J, Jost J (2013) An introduction to the mathematical structure of the Wright–Fisher model of population genetics. Theory Biosci 132(2):73–82. https://doi.org/10.1007/s12064-012-0170-3
Article
PubMed
Google Scholar
Tran TD, Hofrichter J, Jost J (2019) A general solution of the Wright–Fisher model of random genetic drift. Differ Equ Dyn Syst 27(4):467–492. https://doi.org/10.1007/s12591-016-0289-7
Article
Google Scholar
Uchida A (2002) The contents of the digestive tract of ayu in the middle reach of the Yahagi River. Yahagi River Res 6:5–20 (in Japanese)
Google Scholar
Vadillo F (2019) Comparing stochastic Lotka–Volterra predator-prey models. Appl Math Comput 360:181–189. https://doi.org/10.1016/j.amc.2019.05.002
Article
Google Scholar
Wang H (2001) Some control problems with random intervention times. Adv Appl Probab 33(2):404–422. https://doi.org/10.1017/S0001867800010867
Article
Google Scholar
Wang SL, Jin XL, Huang ZL, Cai GQ (2015) Break-out of dynamic balance of nonlinear ecosystems using first passage failure theory. Nonlinear Dyn 80(3):1403–1411. https://doi.org/10.1007/s11071-015-1951-2
Article
Google Scholar
Wang CJ, Lin QF, Yao YG, Yang KL, Tian MY, Wang Y (2019) Dynamics of a stochastic system driven by cross-correlated sine-Wiener bounded noises. Nonlinear Dyn 95(3):1941–1956. https://doi.org/10.1007/s11071-018-4669-0
Article
Google Scholar
Xu S, Chen M, Liu C, Zhang R, Yue X (2019a) Behavior of different numerical schemes for random genetic drift. BIT Numer Math 59(3):797–821. https://doi.org/10.1007/s10543-019-00749-4
Article
Google Scholar
Xu S, Chen X, Liu C, Yue X (2019b) Numerical method for multi-alleles genetic drift problem. SIAM J Numer Anal 57(4):1770–1788. https://doi.org/10.1137/18M1211581
Article
Google Scholar
Yin GG, Zhu C (2009) Hybrid switching diffusions: properties and applications. Springer, New York
Google Scholar
Yoshioka H, Yaegashi Y (2018) Robust stochastic control modeling of dam discharge to suppress overgrowth of downstream harmful algae. Appl Stoch Models Bus Ind 34(3):338–354. https://doi.org/10.1002/asmb.2301
Article
Google Scholar
Yoshioka H, Tsujimura M (2019) A model problem of stochastic optimal control subject to ambiguous jump intensity. Discussion Paper. Presented at ROC2019, London, June 21–29, 2019. https://www.realoptions.org/openconf2019/data/papers/370.pdf
Yoshioka H, Yaegashi Y, Yoshioka Y, Tsugihashi K (2019) Optimal harvesting policy of an inland fishery resource under incomplete information. Appl Stoch Models Bus Ind 35(4):939–962. https://doi.org/10.1002/asmb.2428
Article
Google Scholar
Yoshioka H, Yoshioka Y (2020) A non-standard two-species stochastic competing system and a related degenerate parabolic equation, preprint available on bioRxiv. BIORXIV/2020/001347
Zhu C, Yin G, Baran NA (2015) Feynman-Kac formulas for regime-switching jump diffusions and their applications. Stoch Int J Probab Stoch Process 87(6):1000–1032. https://doi.org/10.1080/17442508.2015.1019884
Article
Google Scholar