Non-local Dispersal Models for a Population under Climate Change (Joy) Ying Zhou, Mark Kot Department of Applied Mathematics University of Washington 1.

Slides:



Advertisements
Similar presentations
Cavitation and Bubble Dynamics Ch.4 Dynamics of Oscillating Bubbles.
Advertisements

Population Ecology & Demography; Leslie Matrices and Population Projection Methods Introduction to linking demography, population growth and extinction.
R 0 and other reproduction numbers for households models MRC Centre for Outbreak analysis and modelling, Department of Infectious Disease Epidemiology.
Modeling the Re-invasion of Sea Otters along the Coast of California M.J. Krkosek J.S. Lauzon.
Distillation Modeling and Dynamics Distillation Part 2.
Heat flow in chains driven by noise Hans Fogedby Aarhus University and Niels Bohr Institute (collaboration with Alberto Imparato, Aarhus)
A Simulation-Based Approach to the Evolution of the G-matrix Adam G. Jones (Texas A&M Univ.) Stevan J. Arnold (Oregon State Univ.) Reinhard Bürger (Univ.
Community Ecology BCB321 Mark J Gibbons, Room 4.102, BCB Department, UWC Tel: Image acknowledgements –
Halo calculations in ATF DR Dou Wang (IHEP), Philip Bambade (LAL), Kaoru Yokoya (KEK), Theo Demma (LAL), Jie Gao (IHEP) FJPPL-FKPPL Workshop on ATF2 Accelerator.
The Tools of Demography and Population Dynamics
Examining the interaction of density dependence and stochastic dispersal over several life history scenarios Heather Berkley Bruce Kendall David Siegel.
Governing equation for concentration as a function of x and t for a pulse input for an “open” reactor.
Inherent Uncertainties in Nearshore Fisheries: The Biocomplexity of Flow, Fish and Fishing Dave Siegel 1, Satoshi Mitarai 1, Crow White 1, Heather Berkley.
Predation – what is it? One animal kills another for food ( + - interaction ) One animal kills another for food ( + - interaction ) Parasitism / Parasitoidism.
Ch. 6 The Normal Distribution
Mahanalobis Distance Dr. A.K.M. Saiful Islam Source:
Inherent Uncertainties in Nearshore Fisheries: The Biocomplexity of Flow, Fish and Fishing Dave Siegel 1, Satoshi Mitarai 1, Crow White 1, Heather Berkley.
Outline 1.Density dependent population dynamics: logistic equation 2.Cyclic and chaotic populations 3.Life history strategies 4.K vs r selection (MacArthur)
Spatial and Temporal Patterns in Modeling Marine Fisheries Heather Berkley.
Fishing in a stirred ocean: sustainable harvest can increase spatial variation in fish populations Heather Berkley Bruce Kendall David Siegel.
Examining the interaction of density dependence and stochastic dispersal over several life history scenarios Heather Berkley Bruce Kendall David Siegel.
CONNECTIVITY MATRIX (6 REALIZATIONS) Passive larvae Active larvae Retention increases, heterogeneity decreases.
Introductio n The guiding of relativistic laser pulse in performed hollow plasma channels Xin Wang and Wei Yu Shanghai Institute of Optics and Fine Mechanics,
Hallo! Carol Horvitz Professor of Biology University of Miami, Florida, USA plant population biology, spatial and temporal variation in demography applications.
Projection exercises Stable age distribution and population growth rate Reproductive value of different ages Not all matrices yield a stable age distribution.
11 Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. BIOL 3240 Plant and Animal Ecology – Population Dynamics.
Black hole production in preheating Teruaki Suyama (Kyoto University) Takahiro Tanaka (Kyoto University) Bruce Bassett (ICG, University of Portsmouth)
Forming and Feeding Super-massive Black Holes in the Young Universe Wolfgang J. Duschl Institut für Theoretische Astrophysik Universität Heidelberg.
FDA- A scalable evolutionary algorithm for the optimization of ADFs By Hossein Momeni.
Smoothed Particle Hydrodynamics (SPH) Fluid dynamics The fluid is represented by a particle system Some particle properties are determined by taking an.
Modeling Colonization of BC Rivers by Feral Atlantic Salmon 2008 PIMS Mathematical Biology Summer Workshop.
Ecology 8310 Population (and Community) Ecology. Context.
Brookhaven Science Associates U.S. Department of Energy MUTAC Review April , 2004, LBNL Target Simulation Roman Samulyak, in collaboration with.
1 Optimal control for integrodifferencequa tions Andrew Whittle University of Tennessee Department of Mathematics Andrew Whittle University of Tennessee.
Cognitive ability affects connectivity in metapopulation: A simulation approach Séverine Vuilleumier The University of Queensland.
Pulse confinement in optical fibers with random dispersion Misha Chertkov (LANL) Ildar Gabitov (LANL) Jamey Moser (Brown U.)
Integral projection models
Harvesting and viability
Xianwu Ling Russell Keanini Harish Cherukuri Department of Mechanical Engineering University of North Carolina at Charlotte Presented at the 2003 IPES.
Numeric Summaries and Descriptive Statistics. populations vs. samples we want to describe both samples and populations the latter is a matter of inference…
Source-Sink Dynamics. Remember, all landscapes are heterogeneous at some scale Consequently, patch quality is heterogeneous All else being equal, individuals.
Advanced Stellar Populations Advanced Stellar Populations Raul Jimenez
1 Radio-mode Feedback Alex Wagner Geoff Bicknell (with previous contributions by Ralph Sutherland & Curtis Saxton)
Population Dynamics Focus on births (B) & deaths (D) B = bN t, where b = per capita rate (births per individual per time) D = dN t  N = bN t – dN t =
Yanjmaa Jutmaan  Department of Applied mathematics Some mathematical models related to physics and biology.
Population ecology Gauguin. 15 populations (various patch sizes) Time since fire: 0 to >30 years 9 years ( ) >80 individuals per population each.
Acoustic wave propagation in the solar subphotosphere S. Shelyag, R. Erdélyi, M.J. Thompson Solar Physics and upper Atmosphere Research Group, Department.
Continuous Probability Distribution By: Dr. Wan Azlinda Binti Wan Mohamed.
The Landscape Ecology of Invasive Spread Question: How is spatial pattern expected to affect invasive spread? Premise: Habitat loss and fragmentation leads.
Arthur Straube PATTERNS IN CHAOTICALLY MIXING FLUID FLOWS Department of Physics, University of Potsdam, Germany COLLABORATION: A. Pikovsky, M. Abel URL:
Pushing the space charge limit in the CERN LHC injectors H. Bartosik for the CERN space charge team with contributions from S. Gilardoni, A. Huschauer,
Sam Young University of Sussex arXiv: , SY, Christian Byrnes Texas Symposium, 16 th December 2015 CONDITIONS FOR THE FORMATION OF PRIMORDIAL BLACK.
Intraspecific population growth CHARPTER 11 Can a population continue to grow indefinitely in the real world?
Improved fauna habitat quality assessment for decision making in the Pilbara Bioregion Amy Whitehead NERP Environmental Decisions.
Seed dispersal and seedling recruitment in Miro (Podocarpus ferrugineus, Podocarpaceae) & Puriri (Vitex lucens, Verbenaceae) Andrew Pegman PhD Candidate.
Performance of small populations
Charles J. Krebs, Jeffery R. Werner, and Rudy Boonstra
Longitudinal Effects in Space Charge Dominated Cooled Bunched Beams
PROBABILITY DISTRIBUTION Dr.Fatima Alkhalidi
Lecture 12: Population dynamics
Population A group of individuals of the same species that interact with each other in the same place at the same time Metapopulation A population of populations,
Space-charge Effects for a KV-Beam Jeffrey Eldred
CHAPTER 5 Fundamentals of Statistics
What would be the typical temperature in Atlanta?
Kenji Fukushima (RIKEN BNL Research Center)
CENTRAL MOMENTS, SKEWNESS AND KURTOSIS
Physics 319 Classical Mechanics
2. Crosschecking computer codes for AWAKE
Instability and Transport driven by ITG mode
Another Paradigm Shift (Hanski and Simberloff 1997)
Presentation transcript:

Non-local Dispersal Models for a Population under Climate Change (Joy) Ying Zhou, Mark Kot Department of Applied Mathematics University of Washington 1

Cartoon of a Range Shift 2

3 Global mean: 0.42km/yr

Cartoon of a Range Shift 4 Population Dynamics Matter

Talk Outline 5 Population Models on Range Shifts under: Constant-speed climate change Accelerated climate change

Organisms of Interest Well-defined life stages (growth, dispersal) Growth and dispersal occur in separate time periods Non-overlapping generations Larvae Adult Egg mass Flower Seed Seedling Cocoon

Integrodifference equation 7 Integrodifference eqn (IDE) kernel Assuming no Allee effects

How To Mathematize Climate Warming? 8

Climatically Suitable Habitat Habitat shifts 9 Combination of two classical problems Zhou and Kot 2011 Theoretical Ecology

Two Classic IDE Models 10

Two Classic IDE Models 11

What Population Dynamics Will We Observe? A Steady Range Shift For Small c 12 Zhou and Kot 2011 Theoretical Ecology

Extinction When c Large 13 Zhou and Kot 2011 Theoretical Ecology

Critical Speed “c*” Viability of a population Ability to establish itself at a low density Instability of the trivial equilibrium Dominant eigenvalue of an integral operator exceeding 1 14

Eigenvalue Problem Net reproductive rate Analytic method for “separable” kernels Numerical method “Nystrom’s method” Delves and Wash 1974

Larger Net Reproductive Rate Helps 16 Zhou and Kot 2011 Theoretical Ecology

More Dispersal, But Not Over-dispersal 17 Dispersal radius radius Zhou and Kot 2011 Theoretical Ecology

18 Lockwood et al. 2002

Clark 1998 Mean deviation 19 Schultz 1998

Result for a typical leptokurtic kernel The “Tail” of The Dispersal Kernel Result for a typical leptokurtic kernel Result for a typical platykurtic kernel 20 Zhou and Kot 2011 Theoretical Ecology

Population projection matrix Matrix of dispersal kernels Vector of population density in each stage

Climatically Suitable Habitat Habitat shifts Heterogeneous Habitat Suitability 22 Habitat quality function Latore et al. 1999

Consider linearized equation For normally distributed habitat quality a Gaussian dispersal kernel

and a special initial condition (Gaussian initial profile), then we have an ansatz : peak of the pulse : amplitude of the pulse Latore et al. 1999

25

26 “climate deficit”

27 Declining population if

Accelerated Climate Change Same ansatz

The mean of the Gaussian ansatz

30 The “climate deficit”

Time Speed T

32 vs. For large t Comparison of climate deficit

33

34

Summary An integrodifference equation model with shifting boundaries Critical speed Acceleration may hurt a lot (more than average) 35

Thank you! Questions? 36