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Periodic travelling waves in cyclic populations: Field studies and reaction-diffusion models

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Periodic travelling waves have been reported in a number of recent spatio-temporal field studies of populations undergoing multi-year cycles. Mathematical modelling has a major role to play in understanding these results and informing future empirical studies. We review the relevant field data and summarize the statistical methods used to detect periodic waves. We then discuss the mathematical theory of periodic travelling waves in oscillatory reaction-diffusion equations. We describe the notion of a wave family, and various ecologically relevant scenarios in which periodic travelling waves occur. We also discuss wave stability, including recent computational developments. Although we focus on oscillatory reaction-diffusion equations, a brief discussion of other types of model in which periodic travelling waves have been demonstrated is also included. We end by proposing 10 research challenges in this area, five mathematical and five empirical.
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Propagating fronts in the complex Ginzburg-Landau equation generate fixed-width bands
of plane waves
Matthew J. Smith*
Microsoft Research, 7 J.J. Thompson Avenue, Cambridge CB3 0FB, United Kingdom
Jonathan A. Sherratt
Department of Mathematics and Maxwell Institute for Mathematical Sciences,
Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom
Received 30 April 2009; revised manuscript received 1 September 2009; published 20 October 2009
Fronts propagating into an unstable background state are an important class of solutions to the cubic
complex Ginzburg-Landau equation. Applications of such solutions include the Taylor-Couette system in the
presence of through flow and chemical systems such as the Belousov-Zhabotinskii reaction. Plane waves are
the typical behavior behind such fronts. However, when the relevant plane-wave solution is unstable, it occurs
only as a spatiotemporal transient before breaking up into turbulence. Previous studies have suggested that the
band of plane waves immediately behind the front will grow continually through time. We show that this is in
fact a transient phenomenon and that in the longer term there is a fixed-width band of plane waves. Moreover,
we show that the phenomenon occurs for a wide range of parameter values on both sides of the Benjamin-
Feir-Newell and absolute instability curves. We present a method for accurately calculating the parameter
dependence of the width of the plane-wave band facilitating future experimental verification in real systems.
DOI: 10.1103/PhysRevE.80.046209 PACS numbers: 05.45.a, 02.70.c, 47.54.r
I. INTRODUCTION
The cubic complex Ginzburg-Landau equation CGLEis
one of the most studied nonlinear equations in physics 1.It
is a generic model for weakly nonlinear spatially extended
oscillatory media arising as the amplitude equation near a
supercritical Hopf bifurcation 2. An important problem in
such systems is front propagation into an unstable state and
the CGLE has been fundamental to the study of this problem
in contexts including the Taylor-Couette system in the pres-
ence of through flow 3,4and chemical systems such as the
Belousov-Zhabotinskii reaction 5. Here we report on, and
explain, a previously unrecognized phenomenon associated
with such front propagation: a fixed-width band of plane
waves behind the front Fig. 1. This phenomenon occurs for
a wide range of parameters and we describe a method that
predicts the width of the band making this a natural target for
future experimental study.
The CGLE in one space dimension is given by
tA=A+1+ib
x
2A1+ic兲兩A2A,1
where the complex field Ais a function of space xand time
t, and band c0 are real parameters. This equation has
a family of propagating front solutions connecting the un-
stable state A=0 to a plane wave. The latter is a fundamental
class of solutions of the CGLE with the general form
A=1−Q2eiQxi
t, where
=b+cQ2cand −1 Q1.
Straightforward substitution reveals a one-parameter family
of plane waves for all values of band c. The wave number
Qvselected behind a propagating front is uniquely deter-
mined by the speed of the front vwhich is 21+b24兴兲
via v=bcQ+b+c/Q4,6. Our specific focus is on the
dynamics that results from the corresponding plane wave
Avbeing unstable. In such cases the plane-wave solution is
either not observed or eventually undergoes a transition to
more complex dynamics such as a pattern of localized de-
fects or spatiotemporal chaos Fig. 1.
In a previous study 7we described and explained the
phenomenon of fixed-width bands of plane waves in a sys-
tem of reaction-diffusion equations of so-called “Lambda-
Omega” type. These are simply CGLE 1with the linear
dispersion term b=0. Superficially, our results appeared to be
qualitatively different from those of Nozaki and Bekki 6
and of subsequent authors reviewed in 4兴兲 for the full
CGLE. These previous studies demonstrated the existence of
a region of plane waves immediately behind the propagating
front, whose width grows through time at a constant rate.
However, when we performed longer term simulations of the
full CGLE 1, we found this behavior to be a transient: the
size of the region of plane-wave solutions eventually reaches
a limit and remains at the limiting width for all subsequent
times. Figure 1illustrates three typical examples of the oc-
currence of plane-wave bands. In each case we apply a small
initial perturbation localized near the left-hand boundary to
the trivial state A=0. This induces a front to propagate across
the domain. Behind the front there is a region of plane
waves, whose width increases at early times, at a rate that
can be calculated via the theory of linear spreading speeds
4,6. However, in each case the long term behavior is a
constant width plane-wave band.
In this paper we provide a detailed account of the occur-
rence and nature of the fixed-width band of plane waves in
the CGLE. We first highlight some numerical errors in the
study of Nozaki and Bekki 6which led them to incorrect
conclusions about the nature of the dynamics behind the
*http://research.microsoft.com/~mattsmi;
matthew.smith@microsoft.com
jas@ma.hw.ac.uk; http://www.ma.hw.ac.uk/~jas
PHYSICAL REVIEW E 80, 046209 2009
1539-3755/2009/804/0462096©2009 The American Physical Society046209-1
propagating front. Next we give a brief overview of the
methods we used to predict the width of the plane-wave
band. We then report our predictions for the parameter de-
pendence of the width, which we confirm with simulations.
Finally, we discuss likely physical systems that could be used
to test our predictions.
II. CORRECTION TO THE STUDY
OF NOZAKI AND BEKKI [6]
The first study that we are aware of on propagating fronts
in the CGLE is that of Nozaki and Bekki 6. These authors
discuss fronts connecting the unstable background state to
both stable and unstable plane waves. We began our own
work by attempting to reproduce the numerical simulations
in 6. Despite 6being very well cited, we found that the
simulations contained previously unrecognized major quali-
tative errors due to problems with numerical truncation. This
is most easily explained for Fig. 2 of 6, in which the au-
thors show a propagating front, behind which there is a re-
gion of low amplitude plane waves, followed by plane waves
of higher amplitude; both plane waves are stable. Moreover,
the front shown in Fig. 2 of 6undergoes a relatively abrupt
change in speed part way through the simulation. The initial
condition used in 6is A
˜
=sech0.05x
˜
; here we use tildes
to denote Nozaki and Bekki’s variables, which differ from
those in Eq. 1via scalings. Our own simulations of this
case show a uniformly propagating front followed by a
single plane wave Fig. 2a. It seems that Nozaki and Bekki
performed their computations in single precision. Thus,
in reality they used initial conditions of the form
A
˜
=sech0.05x
˜
if sech0.05x
˜
10−5 and A
˜
=0 otherwise the
exact threshold would depend on details of their numerical
implementation. In Fig. 2bwe show the results of a simu-
lation done at high precision but using this truncated initial
condition, which reproduces Fig. 2of Nozaki and Bekki.
Figure 2cshows the results for A
˜
x
˜
,0=0 apart from a
perturbation localized to the left-hand boundary. In parts a
and c, a single stable wave train is selected behind the
invasion front. However, the truncated initial conditions lead
to a propagating front that is initially “pushed” before tran-
sitioning to a “pulled” front. These different propagating
front speeds lead to two different plane-wave solutions being
selected. The interface between these plane-wave bands
gradually moves with the lower amplitude wave train replac-
ing that of higher amplitude 19.
There is a similar problem in Fig. 3 of 6, which uses
parameter values giving an unstable plane wave behind the
front. In this case, the authors do not state their initial con-
ditions explicitly, but the tacit implication is that again
FIG. 1. Numerical simulations of pulled propagating fronts in CGLE 1for different band cvalues. The line plots show Afor the last
time output of the surface plot below. The surface plots show the spatiotemporal dynamics of Awith darker shading indicating smaller A
and black corresponding to A=0. The dotted lines mark the beginning and end of the plane-wave band as detected using the method
described in the main text. The figure shows that while different parameters can result in contrasting spatiotemporal dynamics behind the
plane-wave band, the constant width of the band is a consistent phenomenon. Simulations are initialized with A=0 other than a small
perturbation in x1. The boundary conditions are Ax=0. Our numerical method is semi-implicit finite difference with grid spacing of 0.2
and a time step of 10−3.
MATTHEW J. SMITH AND JONATHAN A. SHERRATT PHYSICAL REVIEW E 80, 046209 2009
046209-2
A
˜
x
˜
,0=sech0.05x
˜
. Again, we were able to reproduce their
results by using the “truncated” version of this initial condi-
tion we omit details for brevity. The rather complicated
dynamics in Fig. 3aof Nozaki and Bekki is partly due to
the truncated initial conditions generating different unstable
plane waves in different parts of the domain. When Nozaki
and Bekki were working, more than 25 years ago, computa-
tional precision was much more limited than today; never-
theless, care is still needed to avoid numerical artifacts when
using initial conditions generating “pushed fronts.” In Fig. 1
and throughout the remainder of this paper, we consider ini-
tial conditions that generate a “pulled front,” which has
asymptotic linear spreading speed v
=21+b24; we write
Qv
=Qand Av
=Afor brevity. However, we have also
found the same phenomena in pushed fronts, for which the
propagation speed is faster and the corresponding plane-
wave solution is different.
Since Nozaki and Bekki’s study there have been a number
of real physical experiments that have reported the phenom-
enon of plane waves behind invasion fronts 4. To our
knowledge, however, none have studied the phenomenon in
sufficient detail as to test our prediction that the growth of a
plane-wave band is transient when the wave selected by the
propagating front is unstable.
III. CALCULATING THE WIDTH
OF THE PLANE-WAVE BAND
Our calculation of the width of the plane-wave band is
based on methods we have used in previous studies of the
dynamics behind propagating fronts in the case of b=0 7,8.
We provide only a general overview here, concentrating on
the elements that are different from our previous work, and
refer the reader to our previous publications for detailed de-
scriptions of the methodology.
The key issue underlying our calculation is the absolute
stability of the plane wave Ain a frame of reference moving
with velocity V. If the plane wave is absolutely unstable in a
frame with Vv
, then perturbations to the plane wave can
outrun the front and the plane wave will not be seen. Con-
versely, if the plane wave is stable then there will be an
uninterrupted expanse of plane waves rather than a band.
However, if the plane wave is convectively unstable in the
frame of reference moving with the front speed v
then all
unstable modes will propagate away from the front as they
grow leading to the band in which the plane waves are vis-
ible even though they are unstable. The left-hand edge of the
band occurs when the perturbations present in the plane
FIG. 2. Numerical solutions of the complex Ginzburg-Landau
equation as formulated in Nozaki and Bekki 6with parameters as
in their Fig. 2. The equation is
t
˜
A
˜
=2A
˜
+2.2+i
x
˜
2A
˜
1+i兲兩A
˜
2A
˜
,
which can be converted to Eq. 1by simple rescalings. Shading
corresponds to the value of A
˜
, with darker shading indicating
smaller A
˜
and black corresponding to A
˜
=0. The initial conditions
are as follows: aA
˜
x
˜
,0=sech0.05x
˜
;bA
˜
=sech0.05x
˜
if
sech0.05x
˜
10−5 and A
˜
=0 otherwise; cA
˜
x
˜
,0=0 except for a
small perturbation near x
˜
=0. The boundary conditions are
x
˜
A
˜
=0.
Our numerical method is semi-implicit finite difference with grid
spacing of 0.2 and a time step of 10−3.
0 1 2 3 4 5
−5
−4
−3
−2
−1
0
1
2
3
4
5
(b)
c
b
(20) (10)
(5)
(3.3
)
(2.5
)
(50)
(500)
(250)
(100)
(50)
0 5 10 15 20 25
−15
−10
−5
0
5
(a)
c
b
W=0
0<W<
W=
FIG. 3. aWave train bands behind pulled propagating fronts in
Eq. 1are predicted to occur in b,cparameter space where
0W⬍⬁. The gray broken line is the boundary at which the
selected plane wave is absolutely unstable in the moving frame
of reference with V=v
. This line crosses the b=0 axis at
c=18.727 51. The thick solid line is the boundary at which the
selected plane wave is stable. In bthe thin black solid lines show
contours for the bandwidth coefficient W, with the coefficient val-
ues labeled at the edge of the plot, and we overlay the Benjamin-
Feir-Newell curve thin black broken line, the absolute instability
curve thick black broken line, and the absolute stability boundary
when V=0for the plane wave selected by a pulled propagating
front thick gray line. There is a region of multiple Wvalues in the
bottom left of blocated between the two W=50 contours with
b−2.5.
PROPAGATING FRONTS IN THE COMPLEX GINZBURG-PHYSICAL REVIEW E 80, 046209 2009
046209-3
wave immediately behind the front become sufficiently large
that they dominate the plane wave itself, which we assume to
occur when the perturbations become amplified by a scaling
factor F. For any given frame velocity V, the distance behind
the front at which this amplification first occurs can easily be
calculated: it depends on both the maximum growth rate of
perturbations in that frame of reference and the speed
Vv
at which the perturbation travels away from the front.
The actual width of the plane-wave band is given by the V
which minimizes this distance. In 7we show that this is
V=Vband, which solves
v
VbandImkmaxVband兲兴 =RemaxVband兲兴,2
where max is the growth rate of the most unstable
linear mode and kmax is the corresponding spatial
frequency. The bandwidth itself is −logF/ImkmaxVband兲兴,
so that all of the parameter dependence resides in
Wb,c=1/ImkmaxVband兲兴兩, which we refer to as the
“bandwidth coefficient.” In general, there can be multiple
solutions of Eq. 2and it is then the smallest Wthat will
determine the width of the plane-wave band.
There are three standard approaches to calculating abso-
lute stability and, hence, max and kmax:inumerical con-
tinuation of saddle points of kiVk in the complex k
plane 9;iicalculating the sign of the linear spreading
speed 4;iiicalculating branch points in the absolute spec-
trum 10,11. We adopt the last approach for which 11
gives a detailed methodological description. For a linear
mode with temporal eigenvalue and spatial frequency k,
the dispersion relation D,k;V=0 is a quartic polynomial
in k. We denote the four roots by k1, ... ,k4with
Im k1Im k2Im k3Im k4. “Branch points” are the six
values of for which ki=ki+1 for some iand they are rel-
evant to absolute stability if their index i=2, which corre-
sponds to the “pinching condition” of 12. Therefore, we
solve Eq. 2for Vband via numerical continuation of known
solutions to
D,k;V=
kD,k;V=0 3
monitoring the indices of the repeated roots. Our numerical
codes, which use the software packages MATLAB 13and
AUTO 14, are available from the first author on request.
Note that our approach to calculating absolute stability con-
cerns infinite domains, which is the relevant scenario for the
plane-wave bandwidth. On bounded domains, plane-wave
solutions of the CGLE can exhibit remnant instabilities in
which perturbations grow while being repeatedly reflected
from the boundaries 11,15, but such an instability is not
relevant here.
We used MATLAB 13to solve Eq. 3for given values of
b,c, and Vgiving six values of and their associated values
of k. We used these values as starting points in numerical
continuation of Eq. 3in AUTO 14for varying parameter
values. We first performed continuations in Vlooking for
values that satisfied Eq. 2. This then gave us Vband and,
thus, max,kmax, and Wfor given values of band c. We next
performed continuations in either bor c, while maintaining
equality 2, to allow us to monitor the variation in Wand to
label combinations of band cassociated with specific values
of W. Finally, we used these labeled solutions as starting
points for numerical continuations tracking contours of con-
stant Win b-cparameter space.
We tested our predictions of Wwith numerical simula-
tions of Eq. 1. We used a standard semi-implicit finite dif-
ference method to solve the equations in MATLAB 13兴兲. Nu-
merical tests with this method showed that our simulations
were accurate to about 0.1%. We used an automated method
implemented in MATLAB 13兴兲 for detecting the width of the
plane-wave band in simulations. We defined the observed
bandwidth as the region immediately behind the invasion
front at which
A/
x110−3. This condition gives a ro-
bust measure of bandwidth although the size of the threshold
means that the resulting values are slightly smaller than but
directly correlated withestimates suggested by visual in-
spection of space-time plots such as those shown in Fig. 1.
We estimated the derivative numerically after applying a
smoothing algorithm followed by a polynomial fit over a
moving window of 9 grid points. By implementing this
method we could then compare actual measures of band-
width in numerical simulations with our predicted values of
Wfrom numerical continuation. We used standard linear re-
gression to compare the predictions with the simulations. We
allowed for nonzero intercepts in the regression lines because
our method for measuring the width of the plane-wave band
in simulations excludes some regions on either side.
Note that our defined threshold of
A/
x110−3 is
larger than in our previous study of the b=0 case 7, where
we used
A/
x510−7. We chose the new threshold be-
cause it resulted in a closer correspondence between the au-
tomated measurement and the size of the plane-wave band as
visible by eye as illustrated in Fig. 1. One consequence of
the new threshold is that, as expected from our theory, it
causes a change in the slope and intercept of the fitted linear
relationship between observed bandwidth and W; hence,
these differ from those given in 7. Repeating the analyses
in 7with the larger threshold results in estimates of the
slope and intercept of the linear regression that are similar to
those found here. This is consistent with our theory, which
predicts that for a given thresholdthe observed bandwidth
and Wshould be linearly related, with slope independent of
the parameter values band c.
IV. RESULTS
Our results indicate that a plane-wave band behind propa-
gating fronts will occur for a wide range of parameter values
in the CGLE Fig. 3a. As expected, one boundary to the
parameter region in which a plane-wave band occurs is the
contour at which the wave train band behind the propagating
front becomes stable. Another boundary is the point at which
the plane-wave band is absolutely unstable in all moving
frame reference velocities, V. Along this curve, Vband=v
and
W=0.
Our analysis of Win b,cparameter space revealed the
expected pattern of high bandwidth coefficients close to the
plane-wave stability boundary with lower values further
away Fig. 3b. It also revealed that the bandwidth varies
nonmonotonically with parameters see also Fig. 4. We also
MATTHEW J. SMITH AND JONATHAN A. SHERRATT PHYSICAL REVIEW E 80, 046209 2009
046209-4
plot in Fig. 3bthe Benjamin-Feir-Newell curve beyond
which all plane-wave solutions are unstable, the absolute
instability curve beyond which all plane-wave solutions are
absolutely unstable when V=0, and the absolute stability
boundary for the plane wave selected by a pulled propagat-
ing front when V=0. This highlights that these curves pro-
vide no real information about the bandwidth.
In Fig. 4we compare the width of the plane-wave band
observed in numerical simulations with Wfor two slices in
the b-cparameter plane. The fit is extremely good. The fig-
ure also shows the nonmonotonic dependence of Won pa-
rameters.
We also discovered a region of multiple Wvalues in the
b-cparameter plane Fig. 5awhich allowed us to test and
confirm our prediction that it should be the smallest value of
WFig. 5bthat determines the size of the plane-wave
band. Although we did not find any other regions of multiple
Wvalues during our investigation, we do not know whether
other such regions occur elsewhere in parameter space.
V. DISCUSSION
We have identified a phenomenon in the one-dimensional
CGLE: fixed-width bands of plane waves behind propagating
fronts. We have calculated the bandwidth as a function of
parameters obtaining very good agreement with simulations.
The constancy of the bandwidth over time and the ability to
predict its value precisely make it a natural target for experi-
ments. The widespread applicability of the CGLE means that
there are a number of candidate systems that could be used.
One such is convection in binary miscible fluids. At rela-
tively high Rayleigh numbers, localized perturbations in
temperatureto the quiescent homogeneous conductive state
can generate propagating fronts behind which are plane
waves 16. To our knowledge, only stable plane waves have
been reported, but the relevant amplitude equation is the cu-
bicCGLE 17and, thus, our results suggest that plane-
wave bands, followed by spatiotemporal chaos, would be
found as control parameters are varied. Another possibility is
the Taylor-Couette system with through flow 3for which
the cubicCGLE is again the relevant amplitude equation.
3456789
100
140
180
220
W
Observed band width
(a) c=3
−4 −2 0 2 4
3
4
5
6
7
8
9
b
W
(c) c=3
0 20 40 60
0
400
800
1200
1600
2000
W
(b) b=−4
0 1 2 3 4 5
0
10
20
30
40
50
60
70
c
(d) b=−4
FIG. 4. Comparison of the bandwidth coefficient Wwith nu-
merical simulations of Eq. 1. The initial and boundary conditions
for the simulations are as in Fig. 1except that the domain lengths
and run times were set so that the region of plane-wave solutions
behind the propagating front had reached its limiting width.
The crosses and error bars show the mean and standard deviation
of the observed plane-wave bandwidth for 100 solution times
spaced one time unit apart. We also performed simulations with
b,c=−4 , 4.5and 4,5, which generated no plane-wave band,
as predicted. aand bshow the relationship between Wand
estimated plane-wave bandwidth from simulations. We superimpose
the best-fit linear regression lines, which have slopes of 31.15 and
31.88, intercepts of −21.04 and −22.86, and correlation coefficients
of 0.9921 and 0.9983, for aand b, respectively. In cand dwe
have rescaled the measured plane-wave bandwidth using the linear
regressions in aand b. We chose equally spaced values of bor c
for our simulations with the exception of one additional value at
c=0.2 in band d, which we add to include a point close to the
maximum in W. A close-up of the region to the top left of dis
given in Fig. 5b. The lines in cand dare Wvalues that were
derived using the numerical continuation methods described in the
main text. We measured the observed plane-wave bandwidth using
the methods described in the main text.
0 0.1 0.2 0.3 0.4 0.5 0.6
−5
−4
−3
−2
−1
(
a
)
W=0
0<W<
single W
0<W<
multiple W
0<W<
single W
c
b
0.1 0.15 0.2 0.25 0.3
50
60
70
80
90
c
W
(b) b=−4
FIG. 5. aWave train bands behind pulled propagating fronts in
Eq. 1are predicted to occur in b,cparameter space where
0W⬍⬁. However, there are multiple Wvalues in the region
marked “multiple W.” In such situations we predict that it is the
smallest Wvalue that determines the width of the plane-wave band.
We include the contour at which Wbecomes zero to facilitate com-
parison with Fig. 3.bNumerical simulations confirm our predic-
tion that, in the case of multiple Wvalues, it is the smallest W
value that determines the width of the plane-wave band. This is a
close-up view of the region of multiple Wvalues shown in Fig. 4d
but with additional simulation results. See the legend of Fig. 4d
for definitions. We used the same regression line as in Fig. 4dto
rescale the measured bandwidth.
PROPAGATING FRONTS IN THE COMPLEX GINZBURG-PHYSICAL REVIEW E 80, 046209 2009
046209-5
Localized perturbations can be generated by a sudden change
in the inlet boundary location and lead to plane waves behind
a propagating front. Previously, this has been used to locate
the convective instability boundary, but its wider application
would provide a natural test of our results. Potential non-
physical test systems include oscillatory chemical reactions
5and oscillatory microbial interactions 18, both of which
have been studied using the cubicCGLE. In all of these
various cases, the relevant CGLE coefficients have already
been derived, so that our results can be applied directly to
predict the dependence of the width of the plane-wave band
on the system parameters.
ACKNOWLEDGMENTS
We thank Jens Rademacher CWI, Amsterdamfor many
valuable discussions, Eric Hellmich, Robin Freeman, and Ri-
chard Mann all Microsoft Researchfor technical assistance,
and Des Johnston Heriot-Wattfor comments on the paper.
J.A.S. was supported in part by the Leverhulme Trust.
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MATTHEW J. SMITH AND JONATHAN A. SHERRATT PHYSICAL REVIEW E 80, 046209 2009
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... For instance, in population dynamics, plausible excitable predator-prey models have been proposed [11] but we are not aware of reliable observations of natural systems described by such models. On the other hand, oscillatory behaviour in predator-prey systems is textbook material [12,13] and there are plentiful observational data on traveling waves in cyclic populations [14]. ...
... where β = 0.43, ν = 0.053, γ = 0.1 and w = 0.055 unless stated otherwise, and the Rosenzweig-MacArthur (MA) model [13][14][15] ...
... It is not captured by lambda-omega approach The simple class of two-component reaction-diffusion systems introduced by Kopell and Howard [17] and called "lambda-omega systems", and closely related to the complex Ginzburg-Landau equation, allows exact solutions in the form of periodic waves. It has offered qualitative insight in many nonlinear wave phenomena, including periodic waves in cyclic populations [14]. However, it does not seem to be helpful in our present case. ...
Preprint
We identify a new type of pattern formation in spatially distributed active systems. We simulate one-dimensional two-component systems with predator-prey local interaction and pursuit-evasion taxis between the components. In a sufficiently large domain, spatially uniform oscillations in such systems are unstable with respect to small perturbations. This instability, through a transient regime appearing as spontanous focal sources, leads to establishment of periodic traveling waves. The traveling waves regime is established even if boundary conditions do not favor such solutions. The stable wavelength are within a range bounded both from above and from below, and this range does not coincide with instability bands of the spatially uniform oscillations.
... Advection is not affected by population density, but migration may be faster or slower with a higher population density. In (7), advection speed is 0 , and migration speed 1 and the per capita growth rate function is ( ) =̃( 2 − 1)( 2 + ). Zeng et al. 8 studied the existence of isolated periodic traveling wave solutions of Equation (7) for = 1 and̃= = 1. ...
... They proved that Equation (10) has at most one isolated periodic traveling wave solution for the cases: (i) < 0, = 1, = 2, (ii) < 0, = 2, = 1, (iii) = 1, = 3 for all , (iv) = 2, = 2 for all , and (v) = 3, = 1 for all using Corollary 2 of Li and Zhang 12 . Inspired by the works of Zeng et al., 8 Zhang et al., 9 Wang et al., 3 and Zhang and Xia, 11 we are interested to discuss the existence of an isolated periodic traveling wave solution of Equation (7). Let ...
... If one wants to determine the monotonicity of the ratio of Abelian integrals, then there are several techniques: (i) use Picard Fuchs equations as shown in Cushman and Sanders 26 and Sanders and Cushman, 27 (ii) use Green's formula as illustrated in Chow et al., 28 and (iii) estimation of ′ (ℎ) directly utilizing certain tools as described in Liu and Xiao, 25 Neishtadt, 29 and Dumortier et al. 30 In this paper, we shall make use of Theorems A and B to prove the existence of limit cycles using the monotonicity of Abelian integrals. This paper deals with the isolated periodic traveling wave solutions of nonlinear partial differential equation (7). In general, traveling waves are very important in mathematical biology and many other fields. ...
Article
In this paper, we discuss the existence and uniqueness of isolated periodic traveling wave solutions of a family of nonlinear reaction–convection–diffusion equations using the monotonicity of the ratio of Abelian integrals. A numerical study is also presented.
... At their inception, these mathematical simulations were one dimensional, partial differential equations that greatly simplified natural systems in order to infer the drivers of population waves (1). Building on these models, mathematicians have been able to extend these theories to include multispecies systems, two-dimensional spatial domains, and leptokurtic distributions which more appropriately align these theoretical models with biological systems (19,24,25). Multispecies models of predatorprey systems specifically have advanced our understanding of predator's role in mediating periodic traveling waves through dispersal capacity and reproductive rates (8,15,26). ...
... Here we provide empirical evidence, from a perspective based in individual movement and reproduction, of the underlying life history mechanisms driving the lynx-snowshoe hare wave in North America (17,24,31). Moving forward we hope to see further research into the dynamics governing population increases following a cyclic low, wherein we would expect to see the inverse of the trends observed here, with higher survival in the east followed by a spatially asynchronous increase in reproduction. ...
Article
Full-text available
Cyclical population dynamics are a common phenomenon in populations worldwide, yet the spatial organization of these cycles remains poorly understood. In this study, we investigated the spatial form and timing of a population collapse from 2018 to 2022 in Canada lynx ( Lynx canadensis ) across the northwest boreal forest. We analyzed survival, reproduction, and dispersal data from 143 individual global positioning system (GPS) collared lynx from populations across five study sites spanning interior Alaska to determine whether lynx displayed characteristics of a population wave following a concurrent wave in snowshoe hare ( Lepus americanus ) abundance. Reproductive rates declined across the study sites; however, site-level reproduction declined first in our easternmost study sites, supporting the idea of a population wave. Despite a clear increase in percent of dispersing lynx, there was no evidence of directional bias in dispersal following a hare population wave. Analysis did show increasingly poor survival for lynx dispersing to the east compared to combined resident and westward dispersal. This pattern is consistent with a survival-mediated population wave in lynx as the driver of the theorized population wave. The combination of these factors supports the idea of a hierarchical response to snowshoe hare population declines with a drop in lynx reproduction followed by increased dispersal, and finally reduced survival. All of this evidence is consistent with the expected characteristics of a population undergoing a traveling wave and supports the hypothesis that lynx presence may facilitate and mirror the underlying wave patterns in snowshoe hare.
... Moreover, already the simplest choice for v 1 (x), namely a constant value, generates a traveling pattern (see Supplementary Information Section III.C for further details). We note that stripe-like and travelling patterns also emerge from other PDEs well established in the physics literature, such as reaction-diffusion systems [51] and variants of the nonreciprocal Cahn-Hilliard model studied recently [12,30]. ...
Preprint
Full-text available
Field theories for complex systems traditionally focus on collective behaviors emerging from simple, reciprocal pairwise interaction rules. However, many natural and artificial systems exhibit behaviors driven by microscopic decision-making processes that introduce both nonreciprocity and many-body interactions, challenging these conventional approaches. We develop a theoretical framework to incorporate decision-making into field theories using the shepherding control problem as a paradigmatic example, where agents (herders) must coordinate to confine another group of agents (targets) within a prescribed region. By introducing continuous approximations of two key decision-making elements - target selection and trajectory planning - we derive field equations that capture the essential features of distributed control. Our theory reveals that different decision-making strategies emerge at the continuum level, from random to highly selective choices, and from undirected to goal-oriented motion, driving transitions between homogeneous and confined configurations. The resulting nonreciprocal field theory not only describes the shepherding problem but provides a general framework for incorporating decision-making into continuum theories of collective behavior, with implications for applications ranging from robotic swarms to crowd management systems.
... Future research could delve deeper into the dynamics of periodic travelling waves in reaction-diffusion systems, building on the foundational work of Ermentrout et al., who investigated these phenomena in the context of a subcritical Hopf-bifurcation [63]. Spatiotemporal field studies of interacting populations experiencing multi-year cycles have already demonstrated the occurrence of such waves [64], underscoring their ecological relevance. Future studies could focus on the stability of these waves and other ecologically significant scenarios where this wave structure plays a critical role. ...
Article
The spatiotemporal complexity of a system of interacting species, influenced by hunting cooperation and the additive Allee effect, has garnered significant attention within the ecological framework. This study investigates whether interactions among species can stabilize the dynamics of environmental communities and promote coexistence, employing a cross-diffusion-driven species interaction model. The local and global bifurcation behaviour of the proposed system and the stability of all potential equilibrium points in the absence of diffusion have been comprehensively examined. Numerical simulations have been conducted to validate the analytical findings and assess the applicability of the cross-diffusive model. In a two-dimensional plane, the evolution of diffusion-driven pattern generation, known as black-eye replication, around the coexistence equilibrium point has been presented. Furthermore, it has been demonstrated that species interactions within the context of cross-diffusion can exacerbate the instability dynamics of ecological populations by generating spatial patterns. The results underscore the crucial role of cross-diffusion-driven instability in maintaining ecosystem diversity and structure.
... [10][11][12][13] Exhibited as spatially periodic structures, fronts, backs, and pulses, traveling waves are of a frequent occurrence in plasma physics, 14,15 optics and electronics, [16][17][18][19] hydrodynamics, 20-23 chemistry, [24][25][26] neurophysiology, [27][28][29] as well as on the edge of ecology, population biology, and epidemiology. [30][31][32] Such diversity causes interest of specialists in nonlinear dynamics and complex systems focused on revealing the interdisciplinary, fundamental properties of traveling waves and controlling their characteristics and stability. ...
Article
Full-text available
Using methods of numerical simulation, we demonstrate the constructive role of memristive coupling in the context of the traveling wave formation and robustness in an ensemble of excitable oscillators described by the FitzHugh–Nagumo neuron model. First, the revealed aspects of the memristive coupling action are shown in an example of the deterministic model where the memristive properties of the coupling elements provide for achieving traveling waves at lower coupling strength as compared to non-adaptive diffusive coupling. In the presence of noise, the positive role of memristive coupling is manifested as significant, increasing a noise intensity critical value corresponding to the noise-induced destruction of traveling waves as compared to classical diffusive interaction. In addition, we point out the second constructive factor, the Lévy noise, whose properties provide for inducing traveling waves.
... This is the most likely reason for the low density of lemmings in this part of the reserve. Irregular and rare outbreaks of abundance of this species here are explained by the effect of "periodic travelling waves" described for some vole species of the Northern Europe (Sherratt & Smith, 2008). In this case, the high number of animals leaved territories with high density, and goes to the territories with low density relatively quick. ...
Article
We consider a diffusive Rosenzweig–MacArthur predator–prey model in the situation when the prey diffuses at a rate much smaller than that of the predator. In a certain parameter regime, the existence of fronts in the system is known: the underlying dynamical system in a singular limit is reduced to a scalar Fisher–KPP (Kolmogorov–Petrovski–Piskunov) equation and the fronts supported by the full system are small perturbations of the Fisher–KPP fronts. The existence proof is based on the application of the Geometric Singular Perturbation Theory with respect to two small parameters. This paper is focused on the stability of the fronts. We show that, for some parameter regime, the fronts are spectrally and asymptotically stable using energy estimates, exponential dichotomies, the Evans function calculation, and a technique that involves constructing unstable augmented bundles. The energy estimates provide bounds on the unstable spectrum which depend on the small parameters of the system; the bounds are inversely proportional to these parameters. We further improve these estimates by showing that the eigenvalue problem is a small perturbation of some limiting (as the modulus of the eigenvalue parameter goes to infinity) system and that the limiting system has exponential dichotomies. Persistence of the exponential dichotomies then leads to bounds uniform in the small parameters. The main novelty of this approach is related to the fact that the limit of the eigenvalue problem is not autonomous. We then use the concept of the unstable augmented bundles and by treating these as multiscale topological structures with respect to the same two small parameters consequently as in the existence proof, we show that the stability of the fronts is also governed by the scalar Fisher–KPP equation. Furthermore, we perform numerical computations of the Evans function to explicitly identify regions in the parameter space where the fronts are spectrally stable.
Article
For over sixty years, understanding the causes of multiannual cycles in animal populations has been a central issue in ecology. This book brings together ten of the leaders in this field to examine the major hypotheses and recent evidence in the field, and to establish that trophic interactions are an important factor in driving at least some of the major regular oscillations in animal populations that have long puzzled ecologists.
Chapter
This is an updated version of the best selling first edition, Ecological Census Techniques, with updating, some new chapters and authors. Almost all ecological and conservation work involves carrying out a census or survey. This practically focussed book describes how to plan a census, the practical details and shows with worked examples how to analyse the results. The first three chapters describe planning, sampling and the basic theory necessary for carrying out a census. In the subsequent chapters international experts describe the appropriate methods for counting plants, insects, fish, amphibians, reptiles, mammals and birds. As many censuses also relate the results to environmental variability, there is a chapter explaining the main methods. Finally, there is a list of the most common mistakes encountered when carrying out a census.
Chapter
The spruce needleminer, Epinotia tedella (Cl.) (Lepidoptera: Tortricidae), is a small and abundant moth associated with Norway spruce (Picea abies Karst.). Larvae mine spruce needles, usually those more than 1 year old, and each requires about 35 needles to meet its food demands. In central Europe, the spruce needleminer is regarded as a temporary, serious pest when densities reach several thousand per square meter. However, it seldom causes significant damage in Scandinavian countries. An exception was the heavy infestation in southern Denmark in 1960-61. The spruce needleminer has one generation per year. Adults emerge in June and deposit eggs singly on spruce needles. Larvae mine the needles from July through October and then descend on silken threads in November to hibernate in the forest litter as prepupal larvae in cocoons. Pupation occurs in early May and lasts 3-4 weeks. Like many other forest defoliators, spruce needleminers are associated with a diverse fauna of parasitic Hymenoptera (parasitoids) (Münster-Swendsen 1979). Eggs are attacked by a minute wasp (Trichogramma sp.) that kills the embryo and emerges as an adult a few weeks later. Because spruce needleminer eggs have all hatched by this time, the parasitoids must oviposit in the eggs of other insect species. In other words, this parasitoid is not host-specific and therefore not expected to show a numerical response to spruce needleminer population changes. Newly hatched moth larvae immediately bore into needles and, because of this, are fairly well protected against weather and predators. However, specialized parasitic wasps (parasitoids) are able to deposit their eggs inside a larva by penetrating the needle with their ovipositor. Two species, Apanteles tedellae (Nix.) and Pimplopterus dubius (Hgn.), dominate the parasitoid guild and sometimes attack a large percentage of the larvae (Münster -Swendsen 1985). Parasitized larvae continue to feed and, in November, descend to the forest floor to overwinter with unparasitized individuals. In late April, however, the parasitoids take over and kill their hosts. Besides mortality from endoparasitoids, up to 2% of the larvae die within the mine due to an ectoparasitoid and a predatory cecidomyid larva.
Chapter
My motivation in editing this book has been to present as compelling and credible a story as possible. Although I am personally convinced of the soundness of our argument, that food web architecture plays a key role in the cyclic dynamics of many animal populations, I am not sure that others will be so convinced. In this final chapter, therefore, I exercise my prerogative as editor to have the last word, a final attempt to convince the skeptics and to answer the critics.Perhaps the most compelling case comes from the Mikael Münster-Swendsen monumental study of a needleminer infesting Danish spruce forests (chapter 2). Mikael is the only person I know of who has, almost single-handedly, and with considerable precision, measured all the variables suspected of affecting the dynamics of a particular population over an extended period of time (19 years) and in several different localities (seven isolated spruce stands). Others have longer time series from more places, but none has been so complete in terms of the number of variables measured. This exhaustive study enabled him to build a model of the complete needleminer life system, and use this model to home in on the factors responsible for the cyclical dynamics. However, the story would not have been complete without multivariate time series analysis, which led to the discovery of parasitoids as the cause of the key feedback process, density-related reduction in fecundity. The lesson from Münster-Swendsen's work is clear: If we want to understand population dynamics, we need long time series for all the variables likely to affect the dynamics of the subject population(s). In other words, we need to consistently monitor ecological systems over long periods of time and in many different locations. If there is a weakness in his study, it is the absence of the final definitive experiment. Such an experiment would be relatively easy and cheap to do (relative to those described in other chapters), because isolated spruce stands are common in Denmark and parasitoids emerge from the soil a week or two after the needleminer. Thus, parasitoids could easily be excluded by spraying the ground with an insecticide after needleminer emergence.