Physiological control of diving behaviour in the Weddell seal Leptonychotes weddelli: a model based on cardiorespiratory control theory
Department of Zoology, University of Toronto, Toronto, Ontario, Canada M5S 3G5
e-mail: rstephsn{at}zoo.utoronto.ca
Accepted 10 March 2005
![]() |
Summary |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Key words: diving, Weddell seal, cardiorespiratory control, model, behaviour
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Several attempts have been made to understand the adaptive advantages that
are realized by engaging in bouts of short dives vs other possible
strategies, such as maximizing time underwater in each dive
(Castellini et al., 1988;
Fedak and Thompson, 1993
;
Kooyman et al., 1980
). For
example, following the pioneering study by Dunstone and O'Connor
(1979
), several investigators
have exploited the basic principles of optimal foraging theory
(Houston and Carbone, 1992
;
Kramer, 1988
) to show that on
average the diving tactics used by various species may improve the efficacy or
efficiency of foraging, at least in terms of time and/or energy budgets.
Despite their heuristic value, the validity of optimal diving models is
currently open to debate because there remains considerable uncertainty about
the physiological mechanisms involved in the proximate control of diving
activities, which means that there is also uncertainty about the appropriate
constraints to include in the models.
The most obvious and important constraints arise from the fact that
submerged mammals cannot breathe and there is a limit to breath-hold duration.
This issue was addressed experimentally by Kooyman and others, and developed
into the 'aerobic dive limit' (ADL) concept (Kooyman et al.,
1983,
1980
), defined as the maximum
length of time that an animal can dive without significant elevation of
post-dive plasma lactate concentrations. The ADL has also often been
calculated in terms of the estimated O2 storage capacity of the
animal and its rate of O2 consumption during dives
(Kooyman and Ponganis, 1998
),
and a behaviour-based estimate of the ADL has also been attempted
(Burns, 1999
) using the
correlation between post-dive surface interval and post-dive plasma lactate
concentration (Kooyman et al.,
1980
). In most studies the majority of dives in the majority of
species are observed to be of durations less than the ADL, and it is now
widely accepted that routine foraging dives are a sustainable aerobic activity
- a conclusion that represents an important and enduring contribution of the
ADL hypothesis. The ADL concept (and models based upon it) assumes that oxygen
supply is a limiting factor, but there is no explicit model that explains what
actually triggers the initiation and termination of dives, especially those
shorter than the ADL. It seems likely that numerous physiological,
psychological and environmental factors govern the voluntary diving behaviours
of marine mammals. The goal of this study was to determine whether the
respiratory control system could, at least in principle, be an important
component of this complex behavioural control system.
The ADL concept was never intended to be a model for the physiological
regulation of diving behaviour, but in the absence of a better alternative it
has often been used, at least implicitly, in that context. As a consequence,
oxygen has been assigned a key role in most attempts to understand the
physiological mechanisms underlying diving behaviour
(Borg et al., 2004;
Burns, 1999
;
Butler and Jones, 1997
;
Castellini et al., 1988
;
Fedak and Thompson, 1993
;
Kooyman and Ponganis, 1998
;
Kooyman et al., 1980
).
However, from the perspective of respiratory control this ADL-based approach
is inadequate and should be elaborated, for several reasons. First of all, in
mammals the peripheral chemoreceptors (principally the carotid body
chemoreceptors) respond to partial pressure of oxygen in the arterial blood
rather than O2 content and there is a non-linear relation between
partial pressure and content (i.e. the sigmoid blood oxygen dissociation
curve). The aortic bodies may detect O2 content of arterial blood
(Lahiri et al., 1983
), but
there is no evidence that they have an important role in respiratory control
in diving species (Daly et al.,
1977
; Jones and Purves,
1970
). Secondly, the partial pressures of carbon dioxide in the
arterial blood and brain tissue play a dominant role in the regulation of
breathing in mammals (Phillipson et al.,
1981
). It can be argued that depletion of O2 and
accumulation of CO2 are coupled during breath-hold dives, so that
elevation of the partial pressure of CO2 may indirectly indicate
depletion of the O2 store. However, this neglects the fact that
partial pressures of O2 and CO2 both stimulate
respiration, and these stimuli interact non-additively. A potential role for
CO2 in the regulation of dive and surface times has been suggested
before (Boutilier et al., 1993
,
2001
;
Butler and Stephenson, 1988
;
Halsey et al., 2003
;
Parkos and Wahrenbrock, 1987
;
Pasche, 1976b
;
Stephenson et al., 1986
;
Wilson et al., 2003
), but
there has not yet been a serious attempt to include this variable in a formal
physiological model.
Finally, and perhaps most importantly, the ADL concept neglects the dynamic
aspects of cardiorespiratory control. The chemoreflex control system is a
negative feedback loop with significant circulatory delay between the
effectors (internal and external gas exchange surfaces) and the sensory
receptors. A controller of this type may induce changes in respiratory drive
that are temporally out of phase with the changes in O2 store
(Cherniack and Longobardo,
1986; Khoo, 2000
).
Furthermore, neural feedforward inputs add to the chemoreflex inputs to modify
respiratory drive (Shea,
1996
). Hence to be fully explanatory, rather than merely
descriptive, the ADL concept must be expanded to include information about
changes in partial pressures of both O2 and CO2,
chemoreflex characteristics (thresholds and sensitivities of both central and
peripheral chemoreceptors), how they vary over time, and how they combine with
non-chemoreflex inputs to affect overall respiratory drive.
It is often assumed that asphyxia develops with time under water and the
diving animal remains submerged until a strong drive to breathe or some other
stimulus triggers it to return to the surface
(Castellini and Castellini,
2004; Davis et al.,
2004
; Milsom,
2000
). As a dive progresses, the gradually increasing respiratory
drive is assumed to be counteracted by inhibitory inputs arising perhaps from
sensory receptors in the upper respiratory tract or from central neural
origin. The present study was designed to evaluate an alternative hypothesis
(Woodin and Stephenson, 1998
);
that apnoea is initiated and maintained during dives by disfacilitation of
breathing, not active inhibition, and that under routine conditions a diving
mammal is stimulated to return to the water surface by any positive value of
net respiratory drive. That is, it is postulated that the threshold level of
chemical respiratory drive that triggers an aquatic mammal to begin a dive and
to return to the water surface is equivalent to zero net chemoreflex drive.
The plausibility of this hypothesis was examined using a mathematical model of
the cardiorespiratory control system, with parameter values derived from the
literature for an average adult Weddell seal Leptonychotes weddelli.
This species was chosen because it is a marine mammal species for which there
is a reasonably complete set of parameter values available, it usually dives
for durations less than the ADL and was the species upon which Kooyman based
his original formulation of the ADL concept.
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The specific version of the model used in the present study is shown schematically in Fig. 1. It consists of six body compartments (alveolar lung, myocardium, brain, locomotor muscle, postural muscle and viscera) interconnected by the blood circulation. The locomotor and postural muscle compartments were treated as a combined compartment (i.e. assigned identical parameter values) in the present study. Parameter values used in computer simulations of diving in Weddell seals are given in Table 1. In all equations, volumes were expressed in litres, mass in kg, time in min, and partial pressures in mmHg (1 mm Hg=0.133 kPa). Abbreviations are summarized in Tables 1 and 2.
|
|
|
The underlying assumption in this analysis is that respiratory drives represent a stimulus causing the animal to `decide' to begin and end a dive.
Gas exchange
Mass balance equations were used to calculate exchange of gases between
blood and atmosphere in the lung, and blood and tissues in the other model
compartments. It was assumed that `arterial' (i.e. pulmonary capillary)
partial pressures of oxygen (PaO2 and carbon
dioxide (PaCO2) and the respective alveolar
partial pressures (PAO2 and
PACO2), were equivalent. It was also
assumed that the partial pressures of gases in venous blood leaving the brain,
heart, muscle and viscera compartments were equal to those in the respective
tissues. O2 was assumed to be obtained only from blood haemoglobin
(i.e. dissolved O2 was neglected) in all tissue compartments except
muscle, which also included myoglobin saturation and desaturation. Blood and
tissue CO2 capacitances were assumed to be equal, so that
CO2 was added to tissue and blood in equal proportion by mass in
all tissue compartments. Hence, the change in quantity of CO2 and
O2 in one iteration (dt=t-t0,
where t is the current iteration and t0 the
previous one) is the sum of changes due to blood flow and metabolism:
![]() | (1a) |
![]() | (1b) |
where CO2i,
O2i are the changes in
quantities of CO2 and O2 in compartment `i',
CaCO2 (t-ti),
CaO2 (t-ti) are the
concentrations of CO2 and O2 in arterial blood entering
compartment `i' after the relevant circulation lag time
(t-ti), and
iCO2
(t),
iO2 (t)
represent aerobic metabolic rate of compartment `i' in the current iteration
(t), measured as rates of CO2 production and O2
consumption, respectively:
![]() | (2a) |
![]() | (2b) |
where Mi is the mass of compartment `i'. This assumes that mass is numerically equivalent to tissue water volume.
It was assumed that tissue respiratory quotient
(RQ=CO2/
O2)
was equal to 1.0 in the brain compartment, where the tissues metabolize mainly
glucose, and 0.85 in the other compartments.
In the lung compartment, change in quantities of CO2 and
O2 in one iteration is the sum of changes due to blood flow
(cardiac output ) and alveolar
ventilation (
A):
![]() | (3a) |
![]() | (3b) |
where CO2A,
O2A are the changes in
quantities of CO2 and O2 in the alveoli, and
C
CO2
(t-tv),
C
O2
(t-tv) are mixed venous concentrations of
CO2 and O2 entering the lung after venous lag time
(t-tv).
![]() | (4a) |
![]() | (4b) |
![]() | (5a) |
![]() | (5b) |
where PA is alveolar partial pressure,
FA is alveolar fractional concentration,
VA is average alveolar volume, PB is
barometric pressure and PH2O is saturated water
vapour pressure at 37°C (47 mmHg). Lung volume (VL)
could differ between surface respiration and apnoea onset. The respiratory
exchange ratio (RER) was calculated as:
![]() | (6) |
Blood circulation
Three main functional categories were quantified: blood flow, circulatory
transfer functions and blood gases.
Blood flow
Cardiac output () was calculated as
the sum of blood flows through each of the model tissue compartments (except
lung) and the arterio-venous shunt
(
a-
).
a-
was an adjustable parameter that could differ between dive and surface
intervals. It was assumed that changes in
were associated with relatively large
changes in heart rate (fH, beats min1)
and relatively smaller changes in cardiac stroke volume
(VS, litres), and the following relations were used,
calculated from data in Davis and Kanatous
(1999
):
![]() | (7a) |
![]() | (7b) |
Maximum cardiac output
(max) was varied in this
model by adjusting maximum heart rate.
Brain blood flow (B) was
assumed to be dependent on fractional oxygen saturation of arterial blood
(SaO2) and PaCO2
in blood entering the brain (Fortune et
al., 1992
):
![]() | (8) |
where Brest,
PaCO2rest and
SaO2rest are parameters representing standard
`resting' values, and Gq is a factor representing the relative cerebral
vascular sensitivity to CO2
(Fortune et al., 1992
).
Myocardial, skeletal muscle and viscera compartment blood flows were
subject to `local regulation', modeled as follows:
![]() | (9) |
where i is blood flow
through compartment `i',
iO2 is oxygen
consumption of compartment `i', CaO2
(t-ti) is oxygen content of the arterial blood entering
the compartment after the appropriate circulatory lag time
(t-ti) and
is a `target' blood
oxygen extraction coefficient:
![]() | (10) |
where CvO2(t) is oxygen concentration of compartmental venous blood. Thus, compartmental blood flow was assumed to be dependent on metabolic rate of the tissue and arterial blood oxygen delivery.
For the myocardium, the target blood oxygen extraction coefficient was
fixed at a value
that yielded published coronary blood flow under resting conditions
(Zapol et al., 1979
).
Myocardial metabolic rate was assumed to change in direct proportion to
cardiac output. This mechanism therefore ensured an adequate supply of oxygen
to the heart muscle whenever blood oxygen content and heart work varied.
For the skeletal muscle and viscera compartments, tissue metabolic rates
were set as adjustable parameter values during dives and surface intervals. In
addition to the `local regulation' of blood flow described above, these
compartments were also subject to `systemic regulation' of blood flow, modeled
by coupling target blood oxygen extraction coefficient
to net respiratory drive
(
). The extent of this
cardiorespiratory coupling was independently adjustable for both dive and
surface intervals in each compartment, and the gain of the coupling mechanism
was normalized to standard resting lung ventilation
(
rest):
if >
rest,
![]() | (11a) |
if <
rest,
![]() | (11b) |
where is
a standard resting blood oxygen extraction coefficient, and
and
are
user-defined limits for the target oxygen extraction coefficient in each
compartment. Within these limits, the `relative coupling gain'
(
) caused compartmental target blood
oxygen extraction coefficient
to vary in proportion to
the relative change in lung ventilation:
if >
rest,
![]() | (12a) |
if <
rest,
![]() | (12b) |
where max and
min are maximum lung
ventilation (a value determined in real animals by factors such as mechanical
limitations on lung ventilation) and minimum ventilation (apnoea),
respectively. In practice, the intensity of the `systemic' cardiovascular
response was adjusted by changing the degree of cardiorespiratory coupling
via the
and
values (Eqn
11). In this study, all tissues were assumed to remain within the ADL (i.e.
net anaerobic metabolism was excluded). Therefore in the viscera, which have
no appreciable O2 store,
never
exceeded 0.8 (Davis and Kanatous,
1999
). In skeletal muscle, however, nearly zero blood flow
(
m) could be achieved
during apnoea by setting
to a very
high value (a value of 10 was used in this study). To satisfy the ADL
constraint, if myoglobin oxygen saturation
(SmO2) decreased to a minimum value (0.01),
became 0.8 and muscle blood flow therefore became dependent on muscle
metabolic rate
(
mO2) and
arterial blood oxygen content
[CaO2(t-ta)] for the
remainder of the dive (Eqn 9).
Elevations in compartmental blood flows during surface intervals were
constrained by maximum cardiac output and under limiting conditions, the
competing drives for blood flow in the different compartments were resolved by
imposing an arbitrary priority order:
B=
h>
m
>
v. Thus, cerebral and
coronary oxygen delivery was always adequate, and skeletal muscle recovery was
given priority over viscera to facilitate myoglobin reoxygenation. When
present, the arterio-venous blood shunt
(
n-v) functioned as a fixed
parameter and therefore assumed top priority, and because of this the maximum
shunt flow was never set so high as to limit cerebral and coronary blood
flows.
Circulatory transfer function
The arterial and venous transfer functions were each modeled as the sum of
two components, a circulatory lag time and a mixing function
(Lange et al., 1966).
Circulatory lag times were assumed to be proportional to cardiac output and
blood volume, and the latter was divided into arterial blood
(Vba) and venous blood (Vbv) in the
volume ratio 3:7. The arterial lag time represents the average time taken for
blood to flow from the lung to the muscles and viscera
[(t-ta)], and was calculated as:
![]() | (13a) |
It was assumed that circulatory lag time to the peripheral chemoreceptors
and brain (t-tc) was 70% of arterial lag time
(t-ta), and that the heart is half way between lung and
brain (i.e. circulatory lag time to the myocardium (t-th)
was 50% of chemoreceptor lag time (t-tc). Venous
circulatory lag time (t-tv) was calculated similarly:
![]() | (13b) |
The mixing function was modeled as a simple first order system with time
constant (mix):
![]() | (14) |
where Vmix is the effective volume of the mixed subcompartments of the arterial (Vamix) and venous (Vvmix) systems (Fig. 1).
A step change in cardiac output cannot be modeled with a step change in
circulation lag (i.e. in the referenced row of the spreadsheet) because in a
real circulatory system a change in cardiac output is followed by a transition
period lasting the duration of the new `instantaneous steady-state'
circulatory lag time. During this transition period the `waveform' of blood
gases at any given point in the circulation appears compressed or expanded
when cardiac output increases or decreases, respectively. When cardiac output
changes continuously, as it does during a diving bout, the circulatory delay
is continuously in `transitional' mode. To account for this, the appropriate
lag time [expressed as the number of spreadsheet rows, R(t)]
was calculated for each iteration as follows:
![]() | (15) |
where R(t0) is the number of rows representing the actual circulation lag time in the previous iteration, R(t)* is the number of rows equal to the calculated instantaneous steady-state circulation lag time [of duration (t-ti*)] in the current iteration and dt is the duration of each iteration (min).
Blood gases
Contents and partial pressures of blood gases were related by oxygen and
carbon dioxide equilibrium curves. Bohr and Haldane effects were omitted.
Temperature of the blood and tissues was assumed to be constant at 37°C.
For oxygen, the Hill equation was used:
![]() | (16a) |
![]() | (16b) |
where P50 is the PO2 at 0.5 fractional saturation, n is the Hill cooperativity coefficient, and SO2 is fractional saturation. The same relations hold for myoglobin, where n=1.
SO2 was related to O2
concentration (CO2) by:
![]() | (17) |
where CHb is the concentration of haemoglobin and ßHb is the haemoglobin O2 binding coefficient.
For carbon dioxide, a linear version of the carbon dioxide equilibrium
curve was derived from data for human blood
(Miyamura and Honda, 1978) and
it was assumed to be the same for Weddell seal blood and tissue fluids:
![]() | (18a) |
![]() | (18b) |
System controller
The ventilatory controller was based on Duffin's modification of the
`Oxford model' of respiratory control
(Cunningham et al., 1986;
Duffin et al., 2000
),
consisting of additive drives from central and peripheral chemoreceptors
(feedback), and a central neural `behavioural' drive (feedforward) that is
independent of chemical stimuli. All respiratory drives were expressed in 1
min1.
This model assumes that central and peripheral chemoreceptors have a
chemoreceptor threshold (Tc and Tp,
respectively) for PCO2, below which
chemoreceptors are functionally silent
(Duffin et al., 2000).
Chemoreceptor drives were assumed to increase as a linear function of
PCO2 above the respective chemoreceptor
thresholds (Tc and Tp). The slopes of
these relationships represent the central and peripheral chemosensitivities
(Sc and Sp, respectively). Chemical respiratory
drive (
chem) was computed
as the sum of central and peripheral chemoreceptor drives
(
c and
p, respectively), and
affected ventilation only when above a threshold (chemical drive threshold,
Tchem). When chemical respiratory drive
(
chem) fell below chemical
drive threshold (Tchem), ventilation was determined solely
by the behavioural drive
(
n):
![]() | (19a) |
if chem >
Tchem,
![]() | (19b) |
if chem
Tchem,
![]() | (19c) |
The chemoreflex threshold (T1) is the partial pressure
of CO2 at which chemical respiratory drive
(chem) is equal to chemical
drive threshold (Tchem). In this study,
n was set at user-defined
values during surface intervals and fell to zero during dives. The chemoreflex
threshold (T1) and chemical drive threshold
(Tchem) therefore both function as an `apnoeic threshold'
whenever behavioural drive
(
n) is zero.
Central chemoreceptors were assumed to be (indirectly) sensitive to the
partial pressure of carbon dioxide in the brain tissue compartment
[PBCO2(t); see Lahiri and Forster
(2003) for a justification of
this assumption] and peripheral chemoreceptors were assumed to be sensitive to
PaO2 and PaCO2
in arterial blood flowing through the chemoreceptors [i.e. at time
(t-tc) after leaving the lung]:
if PBCO2(t) >
Tc,
![]() | (20a) |
if PaCO2(t-tc) >
Tp,
![]() | (20b) |
Central chemosensitivity (Sc) was a fixed parameter
(Table 1), but peripheral
chemosensitivity (Sp) was a variable
(Table 2), varying as an
inverse hyperbolic function of PaO2
(Duffin et al., 2000;
Mohan and Duffin, 1997
):
![]() | (21) |
Reliable values for some respiratory control parameters
(n, Tc,
Tp, Sc, Sp, K, A) are
available only for adult male human beings. The corresponding values for an
adult Weddell seal were estimated as follows.
n, Sc and
Sp were estimated by defining a standard resting level of
ventilation for both human and seal, and expressing
n, Sc and K,
respectively, as multiples of standard ventilations. The value of A in Eqn 21
was assumed to be 15 mmHg, the same as the assumed lower critical
PaO2 for cerebral viability in seals
(Elsner et al., 1970
).
It was assumed that there is a constant respiratory dead space volume in
series with the alveolar compartment of the lung. Alveolar ventilation
(A) was derived from total
ventilation (
) as follows:
![]() | (22) |
![]() | (23) |
Protocol
Standard model parameter values were derived from the literature or
estimated as described above for an average adult male Weddell seal
(Table 1). The primary
objective was to determine whether the model could simulate variations in
respiratory drive in a way that is consistent with the hypotheses outlined in
the Introduction. These hypotheses predict that net respiratory drive will
oscillate with amplitude large enough to induce apnoea. Furthermore, the
durations of the simulated apnoeic and eupnoeic intervals must correspond to
the range of durations reported for dive and surface intervals in freely
behaving seals.
The basic approach used in each simulation was to set model parameters to
desired `resting' values and, with the model forced to remain at the surface,
the system was allowed to reach a steady-state condition. The model was then
switched to enable dive cycles so that parameter values automatically assumed
`surface' values when ventilating, and `diving' values when apnoeic. Briefly,
beginning at the water surface, if chemical respiratory drive
(chem) fell below chemical
drive threshold (Tchem), a dive was initiated and model
parameters assumed `diving' values. When chemical respiratory drive
subsequently increased above the chemical drive threshold, the dive was
terminated and the model switched back to `surface' parameter values. These
studies were conducted with maximum dive depth set to 1 m to avoid any
confounding effects of depth. This paper therefore describes simulations of a
seal floating at the water surface and the effect of swimming to depth is to
be examined in a subsequent study. To avoid any transients associated with the
transition from steady state rest to diving mode, all analyses refer to dive
cycles occurring in the interval 65-135 min after the onset of simulated
diving behaviour.
An extensive series of simulations was conducted in which parameter values
were systematically varied, alone and in combination, in order to determine
the relative influence of each on respiratory stability. Only the most
relevant tests are reported: (i) the effects of changes in behavioural
respiratory drive, n
(hyperventilation), (ii) the effects of variations in chemoreflex
characteristics (Tc, Tp, Sc
and Sp), (iii) the effects of cerebral blood flow, (iv)
the effects of variation in the arterial and venous circulatory transfer
functions, (v) the role of oxygen and (vi) the role of the spleen.
Hyperventilation
To examine the effect of hyperventilation the model was initially designed
to include a timer function that enabled the user to specify a minimum
ventilatory interval (ts,min) between dives. This allowed
an analysis of combinations of intensity
(n) and duration
(ts) of hyperventilation. The duration of apnoea (i.e. a
shallow `dive', td) was measured as a function of
ts at each of several values of
n. It was found in these
tests that hyperventilation is necessary for apnoea, so a `standard' value for
the behavioural respiratory drive
(
n=180 1 min-1)
was used during the surface intervals in the subsequent simulations unless
noted otherwise.
Chemoreflex parameters
When ts,min is used as in the above preliminary
simulations, the duration of surface intervals is an independent variable.
This was considered to be an unsatisfactory approach in the absence of any
well-defined physiological analogue to the arbitrary mathematical `timer'
(ts,min). Further tests were therefore conducted to
determine whether surface and dive durations could both be modeled as
dependent variables using conventional respiratory control mechanisms.
Specifically, on the basis of factors that are known to influence respiratory
stability during sleep-wake cycles (e.g.
Khoo, 2000), it was
hypothesized that differences between dive and surface parameter values of the
chemoreflex thresholds and/or chemosensitivities might provide a mechanism for
modulation of ts. The surface and diving values for
thresholds and sensitivities (slopes) of both peripheral and central
chemoreflexes were adjusted individually and in combination over a limited
range around the nominal resting levels. The role of the peripheral
chemoreceptors was tested by systematic changes in peripheral chemoreceptor
threshold (Tp) in combination with variation in the
peripheral chemoreceptor hypoxic asymptote (A). In these and all subsequent
simulations, the ts,min function was inactivated (i.e.
kept constant at zero) so that dive duration (td) and
surface intervals (ts) could both be assessed as dependent
variables. On the basis of these tests a `standard' set of chemoreflex
parameter values was defined and used in all subsequent simulations unless
noted otherwise.
Cerebral blood flow
Cerebral blood flow (B)
was manipulated by adjusting the model parameter values for cerebrovascular
CO2 gain (Gq in Eqn 8) and the minimum cerebral blood flow
(
Bmin), separately and in
combination.
Circulatory transfer functions
The effects on simulated surface intervals (ts) and
dive durations (td) of variation in arterial and venous
transfer functions were examined by systematic adjustment of the two
components, circulatory lag time and time constant of the mixing function.
The circulatory lag time was dependent on blood volume and cardiac output
(Eqn 13). In these tests, blood volume was held constant and cardiac output
() was varied either during dives
(
d) or during surface
intervals (
s). Mean
d was manipulated in two
ways; by altering arterio-venous shunt flow
(
a-
)
during simulated dives or by altering the degree of cardiorespiratory coupling
via changes in
during
dives. Mean
s was
manipulated by combined changes in maximum cardiac output
(
max) and arterio-venous
blood shunt
(
a-
)
during surface intervals.
The time constants of arterial and venous mixing were adjusted by systematic changes in the effective volumes of the mixed circulatory sub-compartments (Vamix and Vvmix). Values of Vamix and Vvmix were varied separately and in combination over the range 2-50% of arterial and venous blood volumes, respectively, and the effects of this on simulated dive and surface durations were noted. On the basis of these tests, `standard' values for the effective volumes of the mixed circulatory sub-compartments (Vamix and Vvmix) were defined and used in all subsequent simulations (Table 1).
The role of oxygen
The oxygen concentration of inhaled air was adjusted over the range 10% to
100% O2 (FIO2=0.1-1.0).
This was then repeated after elimination of oxygen-sensitive mechanisms in the
model. First of all, peripheral chemoreceptor threshold
(Tp) was increased sufficiently to abolish peripheral
chemoreflex drive (p),
thereby simulating acute carotid body denervation (CBD). Secondly, the
cerebrovascular O2-sensitivity was deleted from Eqn 8 so that
cerebral blood flow was solely dependent on arterial
PCO2. Finally, alveolar volume at the start of
a dive was set to zero to eliminate any effect of O2 storage in the
lung compartment. With all of the above manipulations applied concurrently the
`local regulation' component of tissue compartment blood flow (Eqn 9) remained
as the only mechanism by which altered
FIO2 could have an effect on
simulated diving behaviour in this model.
Oxygen store (VO2store) was calculated for
the first iteration of a dive, and used in conjunction with the rate of oxygen
consumption during dives
(O2d) to
estimate the aerobic dive limit in the convention manner: ADL=
VO2store/
O2d.
O2 content of the lung was calculated as the product of fractional
alveolar oxygen concentration and alveolar volume
(FAO2*VA),
O2 contents of arterial and venous blood were taken as the average
concentration over the number of spreadsheet rows corresponding to the current
arterial and venous circulatory lag times multiplied by the respective
arterial and venous blood volumes, and muscle O2 content was
calculated as the product of muscle O2 carrying capacity and
myoglobin fractional oxygen saturation.
The role of the spleen
All of the above simulations were carried out using blood volume
(Vb) and haemoglobin concentration (CHb) values
corresponding to a seal with spleen contracted. To examine the functional
significance of splenic contraction in the present model, standard diving
parameters (Table 1) were
entered with corrections to simulate an absence of splenic contraction:
Vb=76 1, CHb=0.15 kg 11. The
roles of Vb and CHb were examined separately and
in combination.
Cardio-respiratory responses
Diving behaviour, lung ventilation, cardiac output, heart rate, regional
blood flows, contents and partial pressures of O2 and
CO2 in blood and tissue compartments and the chemoreflex drives
were all calculated as dependent variables of the model. The dynamic responses
of these variables were plotted and their interactions examined.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Hyperventilation
As mentioned above, the model parameters shown in
Table 1 gave rise to a
dynamically stable control loop, and the model therefore did not develop
spontaneous oscillatory behaviour. Hence, hyperventilation induced by an
elevated feedforward `behavioural' respiratory drive
(n) was needed to force
chemical respiratory drive
(
chem) below chemical drive
threshold (Tchem) and thereby initiate and sustain cycles
of apnoea (simulated dives) and ventilation (simulated surface intervals).
With the timer mechanism deactivated (ts,min=0),
surface intervals (ts) decreased from 2 min at moderate
behavioural respiratory drive
(n=60 l min-1)
to 1.3 min at high behavioural respiratory drive
(
n=200 l min-1).
Similarly, dive duration (td) was short and only slightly
affected by intensity of hyperventilation, rising from 1.5 min at
n=60 l min-1 to
3.1 min at
n=200 l
min-1.
The ts,min function was then used to examine the effect
of increased duration of hyperventilation on subsequent dive duration. Dive
duration (td) was found to be influenced by both duration
(ts,min) and intensity
(n) of hyperventilation.
For surface intervals less than 3 min, no amount of hyperventilation (up to
max) could induce long
duration dives. At any given
n there was a critical
ts,min that marked an abrupt increase in
td, and this critical ts,min decreased
with increasing
n.
Chemoreflex characteristics
Central chemoreceptor threshold (Tc) was found to be
the only factor that could, when manipulated on its own, induce long-period
dive cycles. Specifically, long duration simulated dives occurred when the
central chemoreceptor threshold was lower during surface intervals than during
dives (Tc). There was a critical
Tc (3.4 mmHg) that marked a transition
between short-period and long-period dive cycles
(Fig. 2).
|
When adjusted individually, the central and peripheral chemosensitivities
(Sc and Sp, respectively), and peripheral
chemoreceptor threshold (Tp), had negligible effects on
simulated dive and surface intervals. Furthermore, combinations of changes in
peripheral chemoreceptor threshold (Tp), and central and
peripheral chemosensitivities (Sc and Sp)
without concurrent changes in central chemoreceptor threshold
(Tc) had little effect on simulated dive and surface
intervals. However the peripheral chemoreflex was not completely without
influence because the Tc mechanism was found to be
influenced by peripheral chemoreceptor threshold (Tp)
(Fig. 2). Specifically, the
effect of
Tc on simulated diving behaviour was
attenuated when Tp was lower than the nominal resting
value (i.e. when the peripheral chemoreceptors were more active).
Variation of the peripheral hypoxic asymptote (A) in the range 15-30 mmHg
O2 had only a small negative linear effect on dive and surface
intervals. For example, at the standard Tc and
Tp (see below), ts decreased by 2.1 s
and td decreased by 7.9 s per mmHg increase in A. Using
these preliminary data as a guide, `standard' chemoreflex parameter values
were defined and used in all subsequent simulations, except where noted
otherwise. Thus, the resting values (see
Table 1) for
Tp, Sp, A and Sc were used
for both dives and surface intervals, and the resting Tc
was used during dives together with a Tc of
5.1 mmHg during surface intervals. These chemoreflex parameter values
substituted for the ts,min function and allowed both
ts and td to be treated as dependent
variables in all subsequent simulations.
Cerebral blood flow
When cerebral blood flow
(B) was constrained to
remain constant at resting levels, simulated dive and surface intervals were
short (1.4 min and 3.4 min, respectively). When this constraint was relaxed,
cerebral blood flow tended to rise during apnoea and fall during
hyperventilation. Cerebrovascular CO2 chemosensitivity (Gq)
affected the rate of change in cerebral blood flow, while minimum cerebral
blood flow (
Bmin) imposed a
limit on the maximum possible decline during hyperventilation-induced
hypocapnia. There were found to be thresholds in both parameters marking
abrupt changes between long and short simulated dive and surface intervals.
Long-period dive cycles occurred only if Gq exceeded a threshold of
0.035
Brest
mmHg1, together with
Bmin < 45% of
Brest.
Circulatory transfer function
Deletion of the arterial mixed sub-compartment from the model had
relatively minor effects on simulated dive and surface intervals. In contrast,
the venous mixed sub-compartment was found to be a necessary feature of the
model, because without it blood gases and chemoreflex drives displayed
unrealistic step transients associated with the large and rapid changes in
ventilation and cardiac output over the course of a dive cycle. Nevertheless,
the quantitative effects of variations in the time constants of the venous
mixing function on simulated dive and surface intervals were small. Increases
in Vamix and Vvmix both caused surface
intervals to increase by 0.05 min l1 and dive durations to
increase by 0.2 min l1. Vamix and
Vvmix had additive effects.
Systematic variation of mean cardiac output over the surface interval
(s) (with mean diving
cardiac output,
d, held
constant) had substantial effects on simulated dive (td)
and surface (ts) intervals
(Fig. 3). There was a threshold
value of
s, below which
dive cycles were always short (ts
3.5 min and
td
5 min) and independent of
s. Above the threshold,
ts and td increased to an asymptote
with further increases in
s. In addition,
Fig. 3 shows that the effect of
suprathreshold
s was
dependent on the intensity of hyperventilation
(
n). As
n increased, the
s threshold increased,
asymptotic td increased slightly, and asymptotic
ts decreased substantially.
|
Systematic variation of mean cardiac output during dives
(d) with
s held constant had
non-linear effects on both simulated dive and surface intervals. Manipulation
of
d by varying the
arterio-venous shunt flow
(
a-v) caused damped
oscillations (period approximately 6 min) in diving blood gas levels that gave
rise to concomitant oscillations in chemical respiratory drive
(
chem). This in turn led to
fluctuating relations between ts and
td vs
d
(Fig. 4). In contrast, when
d was varied by changes in
cardiorespiratory coupling (i.e
see Eqn 11)
the rapid oscillations in blood gases were absent, and dive and surface
intervals were both linearly related to
indicating
inverse hyperbolic relations (see Eqn 9) between simulated dive and surface
intervals vs
d
(Fig. 4). Arterio-venous blood
shunt flow during dives caused a general increase in simulated dive and
surface intervals at all but the lowest
d
(Fig. 4).
|
The role of oxygen
With standard `control' parameter values, simulated dive and surface
intervals were reduced in hypoxia
(FIO2<0.21). For example, simulated dive and
surface intervals were reduced by 55% and 52%, respectively, when fractional
inspired oxygen concentration (FIO2)
was decreased from 0.21 to 0.1. When
FIO2 was less than 0.1, dives were
aborted due to PaO2 falling below the lower critical level
for cerebral viability (assumed to be 15 mmHg). At
FIO2 in the range 0.1 to 0.15,
simulated diving was unsteady, with long-term periodic modulation of simulated
dive and surface intervals over two or more dive cycles. Simulation of
hyperoxia (FIO2>0.21) had only
slight effects on simulated dive and surface intervals. For example, dive
duration increased by 7% when FIO2
increased from 0.21 to 1.0
Elimination of peripheral chemoreflex drive by increasing peripheral chemoreceptor threshold (Tp) to 47.6 mmHg modified the above responses to hypoxia and hyperoxia. Under these conditions, which were intended to mimic acute carotid body chemoreceptor denervation (CBD), there was an overall increase in both dive and surface intervals, as predicted from Fig. 2, and the hypoxia-induced decreases in simulated dive and surface intervals were strongly attenuated, but not abolished. Dive cycles continued to exhibit long-term (multiple dive cycle) periodicity during hypoxia (FIO2=0.10.15) in the absence of peripheral chemoreflex input.
Elimination of the cerebrovascular sensitivity to arterial blood oxygen saturation (see Eqn 8) resulted in stable dive cycles at all FIO2 above 0.1, and reductions in simulated dive and surface intervals, an effect that progressively disappeared in hyperoxia. Furthermore, cerebrovascular insensitivity to O2 partially reversed the effects of CBD alone, in that the CBD-induced overall increases in simulated dive and surface intervals were greatly reduced when cerebral blood flow was simultaneously rendered insensitive to arterial oxygen.
Finally, setting alveolar volume (VA) at the start of
the dive to zero had the effect of causing decreases in simulated dive and
surface intervals at all FIO2, an
effect that was also apparent when alveolar collapse was imposed concurrently
with CBD and cerebrovascular O2 insensitivity, leaving `local'
control of peripheral blood flow as the only functional
O2-sensitive mechanism remaining in the model. Under the latter
conditions, dive cycles were stable but the effects of
FIO2 on simulated dive and surface
intervals were otherwise virtually identical to control. This indirect effect
of O2 on dive duration (td) is illustrated in
Fig. 4, where hypoxia per
se can be seen to have little effect on the td vs
d relation.
Under standard control conditions, with FIO2 at 0.21, VO2store was calculated to be 43.7 1 at the onset of a simulated dive and, assuming that all of the O2 is available for metabolism, calculated ADL was 24.6 min.
The role of the spleen
Splenic contraction was found to have a marked effect on simulated diving
behaviour in this model, an effect that interacted with the cardiovascular
diving response. Fig. 4 shows
that splenic contraction altered the relations between simulated dive and
surface intervals vs diving cardiac output
(d). Splenic contraction
caused increases in both simulated dive and surface intervals, and this effect
was greater at lower
d.
Simulations were compared at constant
d (20.8 1 min-1)
with all four combinations of blood volume (Vb=96 and 76 1) and blood
haemoglobin concentration (CHb=0.26 and 0.15 kg
11). There were direct correlations of simulated dive and
surface intervals to both Vb and CHb, such that
simulated dive and surface intervals were each directly proportional to total
blood haemoglobin content (VbxCHb).
Analysis of the integrated responses of blood and tissue gas tensions
determined that the effect of haemoglobin concentration was mediated by
variation in the rate of change of brain tissue
PCO2 during the surface interval due to changes
in cardiac output. The latter occurred as a consequence of
CHb-related variation in O2 delivery to the
tissue compartments and hence in the drive for peripheral blood flow. The
effect of blood volume was mediated by altered rates of change in brain tissue
PCO2 due to Vb-induced variation in
cardiovascular lag times and mixing time constants during both simulated dives
and surface intervals.
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
This model proposes that diving behaviour may entrain to oscillations in respiratory drive, the period, duty cycle and amplitude of which are susceptible to modification via numerous factors. The model requires that respiratory drive be perturbed by hyperventilation, which causes an otherwise stable chemoreflex loop to oscillate; an example of induced respiratory instability. The temporal characteristics of the oscillating model system were found to be dependent on several key assumptions that will require empirical verification. These include differences between `diving' and `surface' values of the behavioural respiratory drive and central chemoreceptor threshold, and appropriate values for cerebrovascular chemosensitivity and cardiorespiratory coupling.
The model simulations demonstrated that active inhibition of breathing is
not necessary to sustain apnoea during shallow dives up to the ADL in this
species. However, the model does not preclude active inhibition of breathing,
and indeed such inhibition will be required during the ascent phase of deeper
dives. This model proposes that positive chemical respiratory drive triggers
the decision to return to the water surface, and seals at depth must obviously
delay respiration until the ascent phase is completed. This issue is to be
addressed in more detail in a subsequent paper. Furthermore, it is highly
likely that various other factors (emotional, volitional, physiological, etc)
may modify diving behaviour (Fedak and
Thompson, 1993) leading to delays in the termination of some
individual dives, and active inhibition would be necessary under those
circumstances. Nevertheless, the present study is consistent with the
suggestion that in the absence of such extrinsic stimuli the animals will tend
to remain at the surface as long as chemoreflex drive is positive, and they
will usually remain submerged as long as the chemoreflex drive remains below
the apnoeic threshold. In other words, diving behaviour is modeled as
repetitive central apnoea with hyperventilatory surface intervals. Model
simulations indicate that adjustment of the levels of hyperventilation and
tachycardia at the water surface, and bradycardia during dives, provide
powerful mechanisms by which a diving seal can adjust the dynamic
characteristics of the cardiorespiratory system in the short term. Regulation
of blood volume via splenic contraction represents an additional
potential mechanism for longer-term regulation in Weddell seals. It is
suggested on the basis of these results that diving behaviour and respiratory
control are `tuned' in such a way that the seals essentially ride an
adjustable wave of respiratory drive
(Woodin and Stephenson, 1998
).
This study therefore builds upon the ADL concept by using a more detailed
model of the cardiorespiratory control system, enabling quantitative
evaluation of the roles of a variety of physiological factors in the control
of individual dives.
Using various combinations of physiologically realistic parameter values,
simulated surface intervals (ts) varied from 1.33 to 10.66
min and simulated dive times (td) varied from 1.46 to
27.41 min. This corresponds well to the observed ranges of surface intervals
and dive durations in unrestrained adult Weddell seals. For example, in the
classic study by Kooyman and colleagues
(Kooyman et al., 1980),
time-depth recorders were deployed on 22 free-ranging seals. Over 97% of 4601
dives were less than 26 min in duration, and over half were less than 10 min.
Fewer data are available for surface times of freely diving Weddell seals, but
most reported observations are less than 10 min
(Burns, 1999
). The aerobic dive
limit (ADL), measured or calculated in various ways, generally falls within
the range 18-25 min for adult Weddell seals, and this was also the case in the
present model. The model simulations suggest that several physiological
factors may influence surface intervals and dive durations and the final
behavioural pattern is determined by quantitative variations in the
combination of these factors. The following discussion summarizes and
integrates the key components of the model.
Dynamic modeling approach
The design of the model is based on previously published attempts to
understand the physiological basis of periodic breathing, Cheyne-Stokes
breathing and sleep apnoea in human beings
(Cherniack and Longobardo,
1986; Khoo, 2000
;
Khoo et al., 1991
,
1982
; Longobardo et al.,
1966
,
1982
). However, application of
this approach to the control of diving required several modifications to
accommodate the profound cardiovascular responses that sometimes occur during
diving behaviour. The model described here also differs substantially from
that described by Davis and colleagues
(Davis and Kanatous, 1999
;
Davis et al., 2004
), as do the
objectives of the two studies. Specifically, the present model includes an
external gas exchanger (lung), it emphasizes cardio-respiratory control
mechanisms, and it treats the system as operating in an explicitly non-steady
state during diving behaviour. In addition to blood and tissue gas contents,
respiratory and cardiovascular convection are dependent variables in the
present model. Diving behaviour, or more specifically the `decisions' to begin
a dive and to begin the ascent to the water surface at the end of a dive, are
hypothesized to be dictated by respiratory drives, and as such are also
dependent variables of the present model.
When the model was held in `surface mode', all dependent variables
eventually settled to a steady state, indicating that with the parameter
values given in Table 1, the
Weddell seal model system exhibits dynamic stability. Various factors can lead
to the development of spontaneous instability
(Khoo, 2000), and this was
observed under certain conditions in the present model of the Weddell seal.
For example, small decreases in resting cardiac output were sufficient to
elicit spontaneous periodic breathing and intermittent apnoea. However a
discussion of these results is beyond the scope of the present paper. The
steady-state values for dependent variables are given in
Table 2 and are in reasonable
agreement with published data, although it is not clear whether true
steady-state conditions have ever actually been studied in seals because even
seals hauled out on ice often display intermittent or periodic breathing, and
full equilibration of CO2 in the model viscera and skeletal muscle
compartments required over an hour of constant resting ventilation and blood
flow. Nevertheless it was necessary to define starting conditions for the
simulations and it was felt that steady resting conditions were most
appropriate because they were reproducible and facilitated a smooth transition
to `diving' mode.
Hyperventilation
It is hypothesized that diving apnoea is initiated and maintained by
disfacilitation of respiration, which requires that the chemical drive to
breathe falls below the apnoeic threshold for intervals up to the ADL (i.e.
20-25 min). Chemical respiratory drive can only be reduced by
hyperventilation, which causes decreases in
PCO2 of the brain and arterial blood and
increases in PO2 of the arterial blood.
Hyperventilation at a level sufficient to induce apnoea was therefore a
necessary component of the model.
Kooyman et al. (1971)
observed a resting ventilation of approximately 20 1 min-1, and
this was adopted as the standard resting value against which chemoreflex
parameters were scaled in this study. The model settled to a steady-state
ventilation of 35 1 min-1, somewhat higher than the standard value
but still within the range of resting values observed in seals breathing at an
artificial ice hole. Kooyman et al.
(1971
) also reported a maximum
single observation of post-dive ventilation of approximately 225 1
min-1 and in the present study, the maximum possible level of
ventilation (
max) was
assumed to be slightly higher than this, at 12 times the standard resting
level (i.e. 240 1 min-1). Most diving animals that have been
studied have been found to hyperventilate between serial dives, including the
Weddell seal. In the present study most simulations assumed a submaximal value
of behavioural respiratory drive
(
n=180 1 min-1),
which is in the upper part of the range of values most commonly observed by
Kooyman et al. (1971
).
In addition to hyperventilation per se, the model predicted that
it was also necessary to ensure that the surface interval lasted long enough
to enable the venous blood to achieve relatively hypocapnic and hyperoxic
blood gas levels. Only then was it possible to sustain long dive times without
active inhibition of breathing. In initial tests, the role of hyperventilation
was investigated using a feedforward drive
(n) to determine the
`intensity' of hyperventilation and a `timer' function
(ts,min) to set the minimum duration of hyperventilation
between dives. These studies uncovered a complex interaction between intensity
and duration, shown in subsequent simulations to be also influenced by cardiac
output (see below). Basically, for any given level of behavioural respiratory
drive (
n) there was a
critical surface duration below which subsequent dives were short and above
which subsequent dives were long. The critical surface time varied in a
non-linear inverse relation to
n.
The cause of the abrupt transition between long and short dive durations
can be explained with reference to Fig.
5, which depicts some results of a typical model simulation.
During apnoea the chemical drive to breathe
(chem) varied in an
unexpected way over time, rising to an early broad `peak' and then decreasing
slightly before gradually rising again late in the dive. The short duration
dives were cases where the early rise in brain tissue
PCO2 was sufficient to cause central
chemoreflex drive (
c, and
hence
chem) to exceed the
chemical drive threshold (Tchem) so that the dives were
terminated after approximately 2-8 min. In contrast, the long duration dives
(14-24 min) represented cases where the early rise in
c was insufficient to
trigger ventilation so that the onset of breathing was delayed until brain
tissue and arterial blood PCO2 rose to the
point where the combination of central
(
c) and peripheral
(
p) chemoreflex drives
equaled the chemical drive threshold (Tchem).
|
The blood and tissue gas curves shown in
Fig. 5 provide insight into the
interdependence of the various components of the cardiorespiratory system. In
particular, model simulations highlight the importance of the temporal (phase)
relations between variables for the pattern of respiratory drive. For example,
the rise in brain tissue (and hence central chemoreceptor)
PCO2 that occurred early in a simulated dive
was induced by the rise in arterial blood PCO2
[at (t-tc) circulatory time lag] following the cessation
of pulmonary gas exchange at the start of apnoea
(Fig. 5D). When breathing
stopped, alveolar PCO2 rapidly increased until
it came to equilibrium with mixed venous PCO2.
Thus, mixed venous PCO2 at the start of apnoea
had an important indirect influence on the size of the initial rise in brain
tissue PCO2 (and hence
chem) during early apnoea,
highlighting the important influence that venous
PCO2 is predicted to have on dive duration in
this model. The subsequent (paradoxical) gradual decrease in chemical
respiratory drive (
chem)
following the initial peak during the early part of the dive is brought about
by two related factors: (i) a delayed effect of hyperventilation from the
previous surface interval making its way through the venous system and causing
arterial blood to exhibit a delayed undershoot in
PCO2, and (ii) the washout of CO2
from the brain tissue as the blood and brain tissue gradually equilibrate in
this closed (apnoeic) system. Finally, the initially slow, but accelerating
rise in peripheral chemoreflex drive
(
p), closely followed by a
rise in central chemoreflex drive
(
c) reflects the delayed
effect of ongoing tissue respiration during apnoea working its way through the
circulation to the peripheral and central chemoreceptors. It is the latter
combination of
c and
p that eventually
terminates the long dives.
In preliminary tests without the ts,min function it was
found that only short period dive cycles could be induced because the resonant
frequency of the system was predominantly determined by the lung to
chemoreceptor delay time (t-tc), as expected from similar
observations in models of human Cheyne-Stokes respiration
(Khoo et al., 1991;
Longobardo et al., 1966
). This
prompted a search for a plausible mechanism for extending surface times. The
importance of the venous blood gases at dive onset has already been mentioned,
and preliminary studies in which a central venous chemoreceptor was included
in the model successfully simulated long-period dive cycles. However, this
approach was abandoned because there is no evidence for such a mechanism in
mammals (Daly et al., 1977
;
Lahiri et al., 1983
), and
attention was turned instead to conventional chemoreflex mechanisms that have
been shown to be implicated in human respiratory instability
(Khoo, 2000
;
Smith et al., 2003
).
Chemoreflex mechanisms
There are few data available on the central and peripheral chemoreflex
thresholds and chemosensitivities of seals. These parameters are difficult to
measure accurately and reliable estimates exist only for human subjects where
carefully controlled studies have been conducted. The main difficulty concerns
knowing the PCO2 and
PO2 at the chemoreceptor sites and this is
particularly problematic in animals such as seals where respiration is often
intermittent, setting up large oscillations in blood gas tensions with
substantial phase lags as demonstrated in this model analysis (see
Fig. 5). In the present study
it was assumed that chemoreceptor thresholds of the Weddell seal are 10%
greater than the mean human value because studies involving inhalation of
hypercapnic gases have shown fairly consistent right shifts in the responses
of diving mammals compared with human beings and other terrestrial species
(Craig and Pasche, 1980;
Milsom et al., 1996
;
Parkos and Wahrenbrock, 1987
;
Pasche, 1976a
). Note that this
is a small deviation since it remains within the normal range of human central
chemoreceptor threshold values, which are quite variable between individuals.
The evidence for reduced CO2 chemosensitivity (i.e. the slope of
the response) in seals in weak (Skinner
and Milsom, 2004
), and normal human values were adopted, assuming
that chemosensitivity can be scaled relative to standard ventilation. However,
there is (slightly) stronger evidence for a blunted hypoxic ventilatory
response in seals, and this was incorporated into the present model by setting
the hypoxic asymptote (A, see Eqn 21) to 15 mmHg, equal to the assumed
critical PO2 for CNS viability
(Parkos and Wahrenbrock, 1987
;
Pasche, 1976b
). Simulations in
which A was raised to 30 mmHg (the normal value for human subjects) had only a
small effect on surface intervals and dive durations, a first clue as to the
relatively small (but not negligible) role played by O2 and the
peripheral chemoreflexes in this model, discussed in more detail below.
It was found that a small decrease (4 to 8 mmHg) in central
chemoreceptor threshold (Tc) during surface
hyperventilation served to prolong surface time long enough for venous
hypocapnia to develop, enabling long-period dive cycles to occur. Short-term
and long-term transitions in chemoreflex thresholds have been measured, mainly
in human subjects, in a number of situations. These include slow changes over
circadian (24 h) timescales (Stephenson et
al., 2000
), changes over several minutes in response to acute
hypoxia (Duffin and Mahamed,
2003
; Mohan and Duffin,
1997
), and rapid changes over several seconds during transitions
between sleep and wakefulness (Phillipson
and Bowes, 1986
). A decrease in the central chemoreceptor
threshold is a left shift in the central chemoreflex response curve and
therefore represents an increase in the responsiveness of the respiratory
system to brain PCO2 (via changes in
brain pH; Lahiri and Forster,
2003
) during surface hyperventilation. The underlying mechanisms
are unknown but may involve excitatory neuromodulation or inhibitory
disfacilitation at the chemoreceptors or at some other part of the chemoreflex
neural pathway. Note that the standard
Tc used in
this study (5.1 mmHg) involved the threshold falling to only 5% below
the mean value for normal human subjects, which remains within the normal
range of human subject variability. Thus, the changes in
Tc required by this model are not unreasonably large.
Nevertheless, a hyperventilation-associated decrease in central chemoreceptor
threshold has not been demonstrated (or even looked for) in seals or any other
diving species, and represents an important untested prediction of the
model.
It has been suggested that a central `timer' mechanism for determining
surface interval duration, simulated in the present model by the
ts,min function, might exist in the form of descending
influences on respiratory drive originating in a central neural pattern
generator (CPG; Milsom et al.,
1997). It was found, however, in the simulations involving
ts,min that some ts,min durations gave
rise to relatively unstable dive cycles, with long-term modulation of surface
intervals and dive durations over several cycles. The two mechanisms used in
this study to regulate the duration of surface intervals
(ts,min and
Tc) are not
necessarily mutually exclusive and it is possible to envisage a `conditional'
CPG whose timing signal is fine-tuned by chemical feedback in order to
suppress long-term instabilities (Milsom
et al., 1997
). The latter scenario could work, for example, if the
CPG exerted its effect via the
Tc
mechanism, with the CPG determining the magnitude of
Tc at any given time. This of course is pure
speculation at present and represents an intriguing topic for further
experimental research.
Simulated carotid body chemoreceptor denervation caused increases in
surface intervals and dive durations, indicating that the peripheral
chemoreceptors are not necessary for simulation of long-period dive cycles in
this model. This is in sharp contrast to the central role that the peripheral
chemoreflex plays in the development of human periodic breathing and sleep
apnoea (Smith et al., 2003).
This suggests that despite the superficial similarities in the breathing
patterns in diving (and sleeping) seals and human sleep apnoea patients that
originally prompted the work described here
(Stephenson et al., 1986
;
Woodin and Stephenson, 1998
),
there are some important fundamental mechanistic differences. Nevertheless,
when present, the peripheral chemoreceptors served to modulate surface
intervals and dive durations through a direct contribution to total chemical
drive (
chem) at the end of
dives. This can be understood with reference to
Fig. 5, which shows that
peripheral chemoreflex drive
(
p) remained below
threshold until late in the dive when the arterial blood gases began to change
relatively rapidly, leading to a rapid surge in
p. This was the main factor
that caused total chemical respiratory drive
(
chem) to rise relatively
suddenly above the apnoeic threshold to terminate the dive. Increased
responsiveness of the peripheral chemoreceptors therefore had the effect of
initiating the surge in
p a
little earlier, thereby reducing dive times, and vice versa
(Fig. 2).
Cerebral blood flow
As discussed above, the early broad `peak' in chemical respiratory drive
(chem) during dives
(Fig. 5B) was found to be
strongly related to brain tissue PCO2, and the
central chemoreceptor threshold (Tc) was found to be the
most influential chemoreflex characteristic affecting durations of apnoea and
ventilation. These results point to a prominent role for the central
chemoreceptors in the regulation of dive and surface intervals, a suggestion
that was reinforced by the finding that surface intervals and dive durations
were strongly dependent on regulation of cerebral blood flow
(
B). Cerebral blood flow
has an important role in the regulation of central chemoreflex drive
(
c) because brain tissue
PCO2 is determined by balancing the rates of
brain CO2 `delivery' (via metabolism and arterial blood)
and CO2 removal (via brain venous drainage and chemical
buffering). Long-period dive cycles were abolished when constant cerebral
blood flow was assumed, demonstrating the importance of appropriate
adjustments of cerebral blood flow over the dive cycle in this model. This is
supported by the finding that cerebral blood flow oscillated over dive cycles
in freely diving rats (Ollenberger and
West, 1998b
). The model predicts that two factors are crucial;
sensitivity of the brain vasculature to arterial
PCO2 (Gq, see Eqn 8), also supported by data in
diving rats and apnoeic humans
(Ollenberger and West, 1998a
;
Przbylowski et al., 2003
), and
the maximum degree of cerebral vasoconstriction that can occur in response to
hypocapnia (
Bmin). In this
model, regulation of cerebral blood flow during the surface interval was of
greater importance than that during dives because it played a prominent role
in determining the rate of washout of brain CO2, and therefore in
the time taken for central chemoreflex drive
(
c) to fall below threshold
to initiate a dive. High cerebral blood flow during the surface interval led
to rapid washout of brain CO2 and a short surface interval. This in
turn led to relatively high venous blood PCO2
at dive onset and therefore short dive durations, as explained earlier.
Conversely, low cerebral blood flow during the surface interval led to slow
washout of brain CO2, long surface interval and therefore long
subsequent dive. High cerebrovascular chemosensitivity (Gq) allowed cerebral
blood flow to fall rapidly at the start of the surface interval, but when
Bmin was very low (<30%
of
Brest), washout of brain
CO2 was too slow and the surface interval was long enough for
excessive venous hypocapnia to develop. This resulted in a subsequent dive in
which oxygen stores were fully consumed before CO2 built up
sufficiently to initiate ventilation, and the simulated animal `died'. Hence,
the appropriate value of Gq was 0.05
Brest
mmHg1 CO2, which is in the upper part of the
normal range observed in human subjects, and a
Bmin of 40% of
Brest was adopted. These
assumptions require experimental verification.
Cardiovascular responses
The circulatory transfer function describes the delay and distortion of the
blood gas `waveform' as the blood flows between tissue and alveolar gas
exchangers (venous transfer function) and between the lung and chemoreceptors
and tissues (arterial transfer function). There are absolute lag times,
representing the time taken for blood to flow between effectors, that are
dependent on blood volume and cardiac output, and there are arterial and
venous mixing processes that `smear' the blood gas waveform, and depend on the
effective mixing volume and cardiac output. In humans, the arterial effective
mixed blood volume (Vamix) is approximately 10-15% of
arterial blood volume (calculated from data published by
Lange et al., 1966). To my
knowledge, comparable data are not available for pinnipeds. However there is
anatomical and functional evidence for an expanded and compliant proximal
aorta (Windkessel) in seals (Drabek,
1975
; Molyneux and Bryden,
1978
; Rhode et al.,
1986
; Shadwick and Gosline,
1995
), which might be predicted to increase
Vamix. It was therefore assumed that
Vamix was 15% of arterial blood volume (i.e. at the upper
end of the normal human range) in the present simulations. Relative effective
mixed volume for the venous system (Vvmix) was arbitrarily
assumed to be double that of the arterial system (i.e. 30% of
Vbv). Variations of both parameters led to only minor
effects on surface intervals and dive durations, indicating that errors in
these values will not significantly affect the overall conclusions of the
study.
Cardiac output (), which influences
both components (mixing and lag) of the transfer function as well as the rates
of gas exchange in the tissue compartments and lung, had an important role in
the regulation of surface intervals and dive durations in these computer
simulations. There was a strong interaction between the effects of cardiac
output and the intensity of hyperventilation during the surface interval, on
the durations of surface intervals and dives
(Fig. 3). In general, higher
hyperventilation enabled longer dives, but only when accompanied by high
cardiac output. When mean surface cardiac output
(
s) was less than 90%
max, variations in
hyperventilation (
n)
affected surface intervals and dive durations only when
n was mild to moderate
intensity (i.e. less than 75
max). With
s near maximum (i.e.
90-110% of nominal
max),
variations in
n had greater
effects on surface intervals and dive durations. Thus the diving efficiency,
expressed as the dive-pause ratio
(td/ts), increased with increasing
hyperventilation at maximal
s, but not when
s was less than 90% of
maximum. This model assumed a constant behavioural respiratory drive
(
n) during surface
intervals, which is probably an oversimplification. It seems likely that the
drive to hyperventilate may vary over time at the surface, incrementing,
decrementing or perhaps exhibiting a biphasic or more complex pattern. Weddell
seals have been reported to show a decrementing pattern of ventilation between
dives (Kooyman et al., 1971
).
However the present simulations suggest that the observed decrease in
ventilation over time at the surface is to some extent due to the falling
chemoreflex drive (Fig. 5) and
it is unclear whether
n
also varied over time in Kooyman's studies. Further research is needed to
clarify this issue, and to understand how ventilation,
n and
s are fully integrated
during surface intervals in freely behaving animals.
The preceding discussion concerning the role of surface cardiac output
(s) in the regulation of
surface intervals and dive durations was based on simulations in which the
`intensity' of the diving response was always `maximal' (i.e. minimal blood
flow in muscle and viscera with correspondingly low cardiac output and heart
rate). In simulations with fixed levels of hyperventilation and cardiac output
during surface intervals
(
n=75% of
max and
s=100% of
max), surface intervals and
dive durations were both inversely related to mean diving cardiac output
(
d). However, the effect
was non-linear and variation in
d (via changes in
the gain of cardiorespiratory coupling) had a significant influence on diving
behaviour only when diving cardiac output was less than approximately 25% of
resting levels. This provides a tentative explanation for the finding that
pharmacological blockade of diving responses had little effect on short dives
in captive harbour seals (Elliott et al.,
2002
), where bradycardia was not very intense even under control
conditions.
The situation was a little more complicated when an arteriovenous blood
shunt (a-v) was used to
adjust mean diving cardiac output. Under these conditions, the accumulation of
venous CO2 was influenced by arterial admixture during the dive and
this had two main effects: it caused oscillations in blood gas tensions during
dives (carried over from the preceding surface interval), and it delayed the
time taken to raise chemical respiratory drive
(
chem) to the apnoeic
threshold, which in turn led to increased dive durations. Furthermore, the
longer dive led to greater production of CO2 and greater depletion
of O2 in the tissues so that more time was required during the
subsequent surface interval to drive chemical respiratory drive back below the
apnoeic threshold. Diving cardiac output (as indicated by heart rate) has been
observed to vary between and within voluntary dives
(Butler and Jones, 1997
;
Kooyman and Campbell, 1972
)
but the fine control of peripheral blood flow has not been measured and it is
not known whether an arterio-venous shunt or tissue perfusion, or a
combination of both, contribute to the variation in
d during voluntary dives.
Radioactive microsphere tracer studies in Weddell seals, spotted seals and
grey seals found evidence for an increase in peripheral arterio-venous blood
shunting during forced submergence (Blix et
al., 1983
; Zapol et al.,
1979
) but the relevance of this to voluntary dives is unclear.
The role of oxygen
Overall, the model simulations point to an important role for the central
chemoreceptors in the development of long-period cycles of intermittent
ventilation, which implies that CO2 is a dominant influence in this
model. So what is the role, if any, of O2? Oxygen is involved in
several aspects of the present model. First of all, the ADL (i.e.
O2 store) places an absolute limit on dive durations. Anaerobic
metabolism represents a biochemical alternative that would have implications
for respiratory control and may extend the behavioural options of the diving
animal (Fedak and Thompson,
1993). Future modeling studies that include anaerobiosis would
therefore be instructive. In addition to its role as a limiting factor, oxygen
has several direct roles in the regulation of respiration and circulation.
Peripheral chemosensitivity is potentiated by arterial hypoxia, and the
present study suggests that increased peripheral chemoreflex drive is
inversely related to dive durations (Fig.
2). However, the finding that elimination of peripheral
chemoreflexes (simulated carotid body denervation) did not prevent the
simulation of long-period dive cycles, indicates that the peripheral
chemoreflex is not an essential factor in the regulation of diving behaviour
in this model.
The effects of atmospheric hypoxia on simulated diving behaviour are in
broad agreement with direct observations of diving seals, where dives were
shortened and considerably less frequent when inspired oxygen concentration
(FIO2) was decreased, and only
slightly affected by hyperoxia (Parkos and
Wahrenbrock, 1987; Pasche,
1976b
). However, although diving was suppressed, it was not
completely abolished at 10% inspired O2, as the model has
predicted. Two factors missing from the model simulations may explain this
discrepancy; acute hypoxia may induce a hypometabolic response
(Frappell et al., 1992
)
resulting in an elevated ADL, although recent data do not support such a
scenario in elephant seals (Kohin et al.,
1999
), or anaerobiosis may be important over the course of an
experimental exposure to extreme hypoxia. Unfortunately, anaerobic metabolites
have not been measured during hypoxic diving in seals.
Elimination of peripheral chemoreflex drive (simulated carotid body denervation, CBD) had the effect of modifying the simulated behavioural responses to hypoxia and hyperoxia. Durations of dives and surface intervals were increased, relative to control, at all except the highest FIO2, and the hypoxia-induced decrease in dive duration was suppressed (but not abolished). Elimination of the O2-sensitive component of the mechanism regulating cerebral blood flow caused small decreases (relative to control) in simulated surface intervals and dive durations under hypoxia, and it significantly reduced the effect of concurrent CBD. Thus, in this model O2 has effects on dive durations via two antagonistic mechanisms; peripheral chemoreceptors (carotid bodies) tend to decrease dive durations and cerebrovascular oxygen sensors tend to increase dive durations. Simulated lung collapse at dive onset eliminates the alveolar stores of O2 and CO2 and this had an overall effect of decreasing dive durations at most FIO2. This effect was independent of CBD and cerebrovascular O2-sensitivity and did not alter the overall effect of FIO2.
Thus, elimination from the model of all of the above
O2-sensitive mechanisms had surprisingly little impact on the
responses to hypoxia, leading to the conclusion that the primary effect of
hypoxia on dive duration was mediated by variations in viscera compartment
blood flow, the only remaining avenue by which O2 could exert an
effect on the system in this model. In these simulations the muscle blood flow
was essentially insensitive to O2 because the `full' diving
response had been invoked by setting the `target' oxygen extraction
coefficient
to
10, as explained in the Materials and methods.
The role of the spleen
Several investigations have concluded that Weddell seals and other
pinnipeds raise the oxygen carrying capacity of the blood during diving
activities by contraction of the spleen
(Hurford et al., 1996;
Kooyman et al., 1980
;
Qvist et al., 1986
). An
obvious advantage of this is the consequent increase in ADL, but the present
study has found that there are also indirect effects that may play a
significant role in the regulation of dive and surface times. Specifically,
changes in blood haemoglobin concentration (CHb) and/or
blood volume (Vb) led indirectly to variation in the rate of change
in brain tissue PCO2 during surface intervals
and/or dives. The splenic expansion of blood volume affected brain tissue
PCO2 mainly through increases in circulatory
lag times, analogous to the effects of changes in cardiac output. Indeed, this
model analysis (Fig. 4)
revealed that Weddell seals are able to greatly extend their dive times as a
result of the co-evolution of an intense diving response (bradycardia and
vasoconstriction) and splenic contraction. The combined effects of these two
adaptations were far greater than the sum of the individual effects. For
example, in the absence of splenic contraction, the diving response alone
resulted in simulated dive duration increasing by 53%, from 4.5 min to 6.9
min, while splenic contraction in the absence of a diving response caused a
similar increase in simulated dive duration
(Fig. 4). However, when both
factors were combined, simulated dive duration was increased by 440%, from 4.5
min to 19.7 min. The effects of the haemoglobin concentration component of
splenic contraction on simulated diving behaviour were also mediated by
changes in circulatory lag time, but in this case via the `local
regulation' of peripheral blood flow. In this model, increased haemoglobin
concentration enabled O2 delivery to be achieved at lower blood
flow, which decreased diving cardiac output and, therefore, increased
circulation lag times and simulated dive duration. Qvist et al.
(1986
) observed that when
dives were separated by relatively long surface intervals, haemoglobin
concentration varied across the dive cycle, rising to a maximum during longer
dives and falling toward resting values during longer surface intervals,
implying that spleen volume is under dynamic control. For simplicity, the
present study assumed constant blood volume and haemoglobin concentration in
any given dive bout, as was observed by Castellini et al.
(1988
).
The above discussion concludes that the mechanism used in this model for
the regulation of peripheral blood flow (Eqn 9) represents the main way in
which O2 exerted an effect on diving behaviour. This approach to
modeling the regulation of peripheral blood flow was adopted to ensure that
the ADL is not exceeded in any peripheral tissue compartment by matching blood
flows to metabolic rates and arterial O2 content. The model also
features coupling between local and systemic cardiovascular control mechanisms
on the one hand, and cardiovascular and respiratory mechanisms on the other
(Eqns 11 and 12). In defence of this approach, there is strong experimental
evidence that tissue perfusion is regulated by a combination of autoregulatory
(local) mechanisms and autonomic and/or endocrine (systemic) mechanisms in
mammals (Marshall, 1999).
Furthermore, central mechanisms that integrate cardiovascular and respiratory
reflexes normally ensure that these two systems are coupled
(Daly, 1986
).
It must be acknowledged, however, that the cardiovascular control system is
far more complex than this simple model implies. While O2 has been
shown to play an important role in the regulation of capillary blood flow
(Marshall, 1999;
Mohrman and Regal, 1988
), many
other mechanisms are also involved that may modify the regional and global
distribution of tissue blood flow
(Marshall, 1999
;
Thomas and Segal, 2004
). For
example, there is evidence for some degree of independence of respiratory and
circulatory `drives' (e.g. variability of heart rate during dives
(Kooyman and Campbell, 1972
;
Qvist et al., 1986
) that could
not be modeled in the present study. Nevertheless, as a first approximation
the present scheme captures the essential characteristics of the system, and
has yielded insights that would not have emerged had a simpler approach been
adopted, such as the assumption of constant tissue blood flow. A more
sophisticated model of cardiovascular control may yield further insights in
future studies.
So how well does the model simulate the behaviour and physiology of freely
diving Weddell seals? The elegant field studies conducted by Kooyman and
colleagues (Castellini et al.,
1988,
1992
;
Kooyman and Campbell, 1972
;
Kooyman et al., 1983
,
1971
,
1973
,
1980
;
Ponganis et al., 1993
) and
Qvist et al. (1986
) provide
data for comparison. Overall, they indicate that the dependent variables
calculated by the model are remarkably consistent with those measured
experimentally, although there are some noteworthy deviations.
Hyperventilation and tachycardia during the surface intervals between serial
dives are essential parameters in the model
(Fig. 5A), without which the
`disfacilitation' hypothesis would fail. Both were observed in freely diving
seals (Kooyman and Campbell,
1972
; Kooyman et al.,
1971
; Qvist et al.,
1986
). Fig. 5D
indicates that the model predicts low alveolar and arterial
PCO2 during the surface interval as a
consequence of hyperventilation, and while only a few measurements were taken,
both end-tidal PCO2 and arterial blood
PCO2 were as low as 30 mmHg (Kooyman et al.,
1971
,
1980
;
Qvist et al., 1986
). These
experimental observations are slightly higher than the model predictions,
probably because the levels of hyperventilation and tachycardia chosen for the
model simulations are near the maximum values observed experimentally. The
model predicts that arterial PCO2 remains close
to the resting value (the actual level is determined by the venous
PCO2 at the end of the surface interval and
early in the dive) until relatively late in a dive, when it rises
progressively. This was observed during both long and short dives in the field
(Kooyman et al., 1973
;
Qvist et al., 1986
), prompting
the authors to suggest that this implies a difference in metabolic rate in
long and short dives. The present simulations suggest that this explanation
may not be correct because the same result is obtained when simulated dive
times are adjusted (at constant metabolic rates) by changes in factors such as
hyperventilation, surface tachycardia, diving bradycardia, and the relative
distribution of blood flow between tissues and arterio-venous anastomoses. The
highest arterial blood PCO2 is predicted by the
model to occur at some time (depending upon the position of the blood sampling
catheter) just after the onset of the surface interval, and this also was
observed experimentally (Qvist et al.,
1986
).
The model also replicated observed changes in
PO2 with reasonable success. High alveolar and
arterial PO2 (>120 mmHg) were recorded after
approximately 3 min of post-dive recovery, immediately before a dive and
during approximately the first minute of a dive (Kooyman et al.,
1973,
1980
;
Qvist et al., 1986
). This was
simulated by the model, although again, for the reasons given above, the peak
PO2 calculated by the model
(Fig. 5E) was slightly higher
than observed values. Arterial blood PO2
decreased to as low as 18.2 mmHg at 1 min before the end of a 27 min dive
(Qvist et al., 1986
), just
above the lower critical value (15 mmHg) assumed in this study. Low values
were observed in long and short dives, and this is also apparent in the model
simulations. Furthermore, arterial blood oxygen content was found to remain
constant for approximately half of the dive duration
(Qvist et al., 1986
), a
finding also replicated in the present model simulations
(Fig. 5F).
It has been suggested on the basis of direct measurements of end-tidal
PCO2 and PO2 in
the grey seal and harbor porpoise that the duration of the surface interval is
mainly determined by the dynamics of CO2 elimination
(Boutilier et al., 2001). A
progressive rise in respiratory exchange ratio (RER) was observed in diving
grey seals (Reed et al.,
1994
), and this was also simulated in the present model. The rise
in RER is dependent on the level of hyperventilation and reflects the
difference in the slopes of the O2 and CO2 blood
equilibrium curves. The slope of the O2 equilibrium curve decreases
as haemoglobin becomes saturated, whereas the slope of the CO2
equilibrium curve was assumed to be constant in this model. The latter
assumption probably led to a small overestimation of predicted RER toward the
end of the surface interval in the present study. Furthermore, `U-shaped'
changes in end tidal PCO2 and
PO2 were observed in grey seals
(Reed et al., 1994
) and
attributed by the authors to a limitation in oxygen consumption from lung or
blood during dives (see also Butler and
Jones, 1997
). The present model supports their conclusion that the
above result is not an experimental artifact
(Fig. 5D,E) but suggests that
the U-shaped curves may reflect a phase lag in venous blood gas tensions,
rather than a limited O2 uptake, highlighting again the importance
of the dynamic aspect of cardiorespiratory control.
In conclusion, this study presents a model for the proximate control of diving behaviour in the Weddell seal. It remains to be seen whether the model can be generalized to other species of diving mammals and birds. The model expands on the aerobic dive limit concept and is based on fundamental principles of cardiorespiratory control. The majority of parameter values were derived from direct measurements in Weddell seals as published by Kooyman and others, and unknown parameters were estimated conservatively from human data. The latter mainly concerned chemoreflex characteristics and represent an area in need of further investigation in pinnipeds and other diving animals. The study supports the plausibility of the basic hypotheses set out in the Introduction: that the control of diving can be modeled in terms of respiratory control and that the apnoeic threshold can trigger the initiation and termination of dives without the need to resort to active inhibition of breathing. This analysis suggests that CO2 is an important factor regulating diving behaviour, with O2 relegated to secondary modulatory roles. The model also underscores the importance of the dynamic aspects of the cardiorespiratory system during dive cycles, with phase relationships between lung, arterial and venous blood, brain and other tissues playing a key role in the overall integrated behaviour of the system and of the animal.
While this model emphasizes a role for the respiratory control system in the regulation of diving behaviour, it must be stressed that this does not imply that the respiratory control system is the only factor involved. It is envisaged that the present model represents one part of a hierarchical behavioural control system that also includes input from factors such as volitional, appetitive, emotional, arousal and circadian drives. It is suggested that the cardiorespiratory control system is a core component of the overall control system, assuming primary control of diving behaviour under routine conditions when other inputs are weak or absent, and responding to and modulating the effect of other inputs when they are present. The model also suggests that in most dives the animals are not necessarily fighting against a powerful drive to breathe, and that once the urge to breathe does reappear, the animal will be stimulated to 'decide' to return to the surface, unless some other priority intervenes (such as predator avoidance or imminent capture of prey etc). Hence, it is proposed that there is a reciprocal interaction between behaviour and cardiorespiratory control, with diving behaviour responding to cardiorespiratory inputs and the cardiorespiratory system responding to overriding behavioural drives. This model is intended to facilitate further research by providing a conceptual framework for the investigation of how diving animals control their behaviour, and by providing a tool for the development of testable quantitative predictions. Computer simulations have confirmed the plausibility of the model, but they cannot confirm or refute its validity without experimental investigation. To this end, the model was constructed in spreadsheet format so that it will be useful to as many researchers as possible. A copy of the spreadsheet is freely available from the author upon request.
![]() |
Acknowledgments |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Blix, A. S., Elsner, R. and Kjekshus, J. K. (1983). Cardiac output and its distribution through capillaries and A-V shunts in diving seals. Acta Physiol. Scand. 118,109 -116.[Medline]
Borg, K. A., Milsom, W. K. and Jones, D. R. (2004). The effect of O2 and CO2 on the dive behavior and heart rate of lesser scaup ducks (Aythya affinis): quantification of the critical PaO2 that initiates a diving bradycardia. Resp. Physiol. Neurobiol. 144,263 -279.[CrossRef]
Boutilier, R. G., Nikinmaa, M. and Tufts, B. L. (1993). Relationship between blood buffering properties, erythrocyte pH and water content, in grey seals (Halichoerus grypus). Acta Physiol. Scand. 147,241 -247.[Medline]
Boutilier, R. G., Reed, J. Z. and Fedak, M. A. (2001). Unsteady-state gas exchange and storage in diving marine mammals: the harbor porpoise and gray seal. Am. J. Physiol. 281,R490 -R494.
Burns, J. M. (1999). The development of diving behavior in juvenile Weddell seals: pushing the physiological limits in order to survive. Can. J. Zool. 77,737 -747.[CrossRef]
Butler, P. J. and Jones, D. R. (1997).
Physiology of diving of birds and mammals. Physiol.
Rev. 77,837
-899.
Butler, P. J. and Stephenson, R. (1988). Chemoreceptor control of heart rate and behaviour during diving in the tufted duck (Aythya fuligula). J. Physiol. 397, 63-80.[Abstract]
Castellini, M. A. and Castellini, J. M. (2004). Defining the limits of diving biochemistry in marine mammals. Comp. Biochem. Physiol. 139B,509 -518.
Castellini, M. A., Davis, R. W. and Kooyman, G. L. (1988). Blood chemistry regulation during repetitive diving in Weddell seals. Physiol. Zool. 61,379 -386.
Castellini, M. A., Kooyman, G. L. and Ponganis, P. J. (1992). Metabolic rates of freely diving Weddell seals: correlations with oxygen stores, swim velocity and diving duration. J. Exp. Biol. 165,181 -194.[Abstract]
Cherniack, N. S. and Longobardo, G. S. (1986). Abnormalities in respiratory rhythm. In Handbook of Physiology, vol. Section 3: The Respiratory System. Volume II. Control of Breathing, Part 2 (ed. N. S. Cherniack and J. G. Widdicombe), pp. 729-749. Bethesda: American Physiological Society.
Chonan, T., El Hefnawy, A. M., Simonetti, O. P. and Cherniack, N. S. (1988). Rate of elimination of excess CO2 in humans. Resp. Physiol. 73,379 -394.[CrossRef][Medline]
Craig, A. B. and Pasche, A. (1980). Respiratory physiology of freely diving harbor seals (Phoca vitulina). Physiol. Zool. 53,419 -432.
Cunningham, D. J. C., Robbins, P. A. and Wolff, C. B. (1986). Integration of respiratory responses to changes in alveolar partial pressures of CO2 and O2 and in arterial pH. In Handbook of Physiology, vol. Section 3: The Respiratory System. Volume II. Control of Breathing, Part 2 (ed. N. S. Cherniack and J. G. Widdicombe), pp.475 -528. Bethesda: American Physiological Society.
Daly, M. d. B. (1986). Interactions between respiration and circulation. In Handbook of Physiology, vol. Section 3: The Respiratory System. Volume II. Control of Breathing, Part 2 (ed. N. S. Cherniack and J. G. Widdicombe), pp.529 -594. Bethesda: American Physiological Society.
Daly, M. d. B., Elsner, R. and Angell-James, J. E. (1977). Cardiorespiratory control by carotid chemoreceptors during experimental dives in the seal. Am. J. Physiol. 232,H508 -H516.[Medline]
Davis, R. W. and Kanatous, S. B. (1999).
Convective oxygen transport and tissue oxygen consumption in Weddell seals
during aerobic dives. J. Exp. Biol.
202,1091
-1113.
Davis, R. W., Polasek, L., Watson, R., Fuson, A., Williams, T. M. and Kanatous, S. B. (2004). The diving paradox: new insights into the role of the dive response in air-breathing vertebrates. Comp. Biochem. Physiol. 138A,263 -268.
Drabek, C. M. (1975). Some anatomical aspects of the cardiovascular system of Antarctic seals and their possible functional significance in diving. J. Morphol. 145,85 -105.[CrossRef][Medline]
Duffin, J. and Mahamed, S. (2003). Adaptation in the respiratory control system. Can. J. Physiol. Pharmacol. 81,765 -773.[CrossRef][Medline]
Duffin, J., Mohan, R. M., Vasiliou, P., Stephenson, R. and Mahamed, S. (2000). A model of the chemoreflex control of breathing in humans: model parameters measurement. Resp. Physiol. 120,13 -26.[CrossRef][Medline]
Dunstone, N. and O'Connor, R. J. (1979). Optimal foraging in an amphibious mammal. I. The aqualung effect. Anim. Behav. 27,1182 -1194.[CrossRef]
Elliott, N. M., Andrews, R. D. and Jones, D. R.
(2002). Pharmacological blockade of the dive response: effects on
heart rate and diving behaviour in the harbour seal (Phoca vitulina).
J. Exp. Biol. 205,3757
-3765.
Elsner, R., Shurley, J. T., Hammond, D. D. and Brooks, R. E. (1970). Cerebral tolerace to hypoxemia in asphyxiated Weddell seals. Resp. Physiol. 9,287 -297.[CrossRef][Medline]
Fedak, M. A. and Thompson, D. (1993). Behavioural and physiological options in diving seals. Symp. Zool. Soc. Lond. 66,333 -348.
Fortune, J. B., Bock, D., Kupinski, A. M., Stratton, H. H., Shah, D. M. and Feustel, P. J. (1992). Human cerebrovascular responses to oxygen and carbon dioxide as determined by internal carotid artery duplex scanning. J. Trauma 32,618 -628.[Medline]
Frappell, P., Lanthier, C., Baudinette, R. V. and Mortola, J. P. (1992). Metabolism and ventilation in acute hypoxia: a comparative analysis in small mammalian species. Am. J. Physiol. 262,R1040 -R1046.[Medline]
Halsey, L., Reed, J. Z., Woakes, A. J. and Butler, P. J. (2003). The influence of oxygen and carbon dioxide on diving behaviour of tufted ducks, Aythya fuligula. Physiol. Biochem. Zool. 76,436 -446.[CrossRef][Medline]
Houston, A. I. and Carbone, C. (1992). The optimal allocation of time during the diving cycle. Behav. Ecol. 3,255 -265.
Hurford, W. E., Hochachka, P. W., Schneider, R. C., Guyton, G.
P., Stanek, K. S., Zapol, D. G., Liggins, G. C. and Zapol, W. M.
(1996). Splenic contraction, catecholamine release, and blood
volume redistribution during diving in the Weddell seal. J. Appl.
Physiol. 80,298
-306.
Jones, D. R. and Purves, M. J. (1970). The carotid body in the duck and the consequences of its denervation upon the cardiac responses to immersion. J. Physiol. 211,279 -294.[Medline]
Khoo, M. C. K. (2000). Determinants of ventilatory instability and variability. Resp. Physiol. 122,167 -182.[CrossRef][Medline]
Khoo, M. C. K., Gottschalk, A. and Pack, A. I.
(1991). Sleep-induced periodic breathing and apnea: a theoretical
study. J. Appl. Physiol.
70,2014
-2024.
Khoo, M. C. K., Kronauer, R. E., Strohl, K. P. and Slutsky, A.
S. (1982). Factors inducing periodic breathing in humans: a
general model. J. Appl. Physiol.
53,644
-659.
Kohin, S., Williams, T. M. and Ortiz, C. L. (1999). Effects of hypoxia and hypercapnia on aerobic metabolic processes in northern elephant seals. Resp. Physiol. 117, 59-72.[CrossRef][Medline]
Kooyman, G. L. and Campbell, W. B. (1972). Heart rates in freely diving Weddell seals, Leptonychotes weddelli. Comp. Biochem. Physiol. 43A, 31-36.[CrossRef]
Kooyman, G. L., Castellini, M. A., Davis, R. W. and Maue, R. A. (1983). Aerobic diving limits of immature Weddell seals. J. Comp. Physiol. 151,171 -174.
Kooyman, G. L., Kerem, D. H., Campbell, W. B. and Wright, J. J. (1971). Pulmonary function in freely diving Weddell seals, Leptonychotes weddelli. Resp. Physiol. 12,271 -282.[CrossRef][Medline]
Kooyman, G. L., Kerem, D. H., Campbell, W. B. and Wright, J. J. (1973). Pulmonary gas exchange in freely diving Weddell seals, Leptonychotes weddelli. Resp. Physiol. 17,283 -290.[CrossRef][Medline]
Kooyman, G. L. and Ponganis, P. J. (1998). The physiological basis of diving to depth: birds and mammals. Annu. Rev. Physiol. 60,19 -32.[CrossRef][Medline]
Kooyman, G. L., Wahrenbrock, E. A., Castellini, M. A., Davis, R. W. and Sinnett, E. E. (1980). Aerobic and anaerobic metabolism during voluntary diving in Weddell seals: evidence of preferred pathways from blood chemistry and behavior. J. Comp. Physiol. 138,335 -346.
Kramer, D. L. (1988). The behavioral ecology of air breathing by aquatic animals. Can. J. Zool. 66, 89-94.
Lahiri, S. and Forster, R. E. I. (2003). CO2/H+ sensing: periperal and central chemoreception. Int. J. Biochem. Cell Biol. 35,1413 -1435.[CrossRef][Medline]
Lahiri, S., Smatresk, N. and Mulligan, E. (1983). Responses of peripheral chemoreceptors to natural stimuli. In Physiology of the Peripheral Arterial Chemoreceptors (ed. H. Acker and R. O'Regan), pp.221 -256. Amsterdam: Elsevier.
Lange, R. L., Horgan, J. D., Botticelli, J. T., Tsagaris, T.,
Carlisle, R. P. and Kuida, H. (1966). Pulmonary to arterial
circulatory transfer function: importance in respiratory control.
J. Appl. Physiol. 21,1281
-1291.
Longobardo, G. S., Cherniack, N. S. and Fishman, A. P.
(1966). Cheyne-Stokes breathing produced by a model of the human
respiratory system. J. Appl. Physiol.
21,1839
-1846.
Longobardo, G., Evangelisti, C. J. and Cherniack, N. S. (2002). Effects of neural drives on breathing in the awake state in humans. Resp. Physiol. 129,317 -333.[CrossRef][Medline]
Longobardo, G. S., Gothe, B., Goldman, M. D. and Cherniack, N. S. (1982). Sleep apnea considered as a control system instability. Resp. Physiol. 50,311 -333.[CrossRef][Medline]
Marshall, J. M. (1999). The integrated response to hypoxia: from circulation to cells. Exp. Physiol. 84,449 -470.[CrossRef][Medline]
Milsom, W. K. (2000). Breathless - by choice. Biologist 47,239 -242.[Medline]
Milsom, W. K., Castellini, M. A., Harris, M. B., Castellini, J., Jones, D. R., Berger, R., Bahrma, S., Rea, L. and Costa, D. P. (1996). Effects of hypoxia and hypercapnia on patterns of sleep-associated apnea in elephant seal pups. Am. J. Physiol. 271,R1017 -R1024.[Medline]
Milsom, W. K., Harris, M. B. and Reid, S. G. (1997). Do descending influences alternate to produce episodic breathing? Resp. Physiol. 110,307 -317.[CrossRef][Medline]
Miyamura, M. and Honda, Y. (1978). CO2 dissociation curves of oxygenated whole blood obtained at rest and in exercise. Eur. J. Appl. Physiol. 39, 37-45.[CrossRef]
Mohan, R. and Duffin, J. (1997). The effect of hypoxia on the ventilatory response to carbon dioxide in man. Resp. Physiol. 108,101 -115.[CrossRef][Medline]
Mohrman, D. E. and Regal, R. R. (1988). Relation of blood flow to VO2, PO2, and PCO2 in dog gastrocnemius muscle. Am. J. Physiol. 255,H1004 -H1010.[Medline]
Molyneux, G. S. and Bryden, M. M. (1978). Arteriovenous anastamoses in the skin of seals. I. The Weddell seal Leptonychotes weddelli and the elephant seal Mirounga leonina (Pinnipedia: Phocidae). Anat. Rec. 191,239 -252.[CrossRef][Medline]
Ollenberger, G. P. and West, N. H. (1998a). Contribution of hypercapnia and trigeminal stimulation to cerebrovascular dilation during simulated diving. Am. J. Physiol. 274,R921 -R930.[Medline]
Ollenberger, G. P. and West, N. H. (1998b).
Distribution of regional cerebral blood flow in voluntarily diving rats.
J. Exp. Biol. 201,549
-558.
Parkos, C. A. and Wahrenbrock, E. A. (1987). Acute effects of hypercapnia and hypoxia on minute ventilation in unrestrained Weddell seals. Resp. Physiol. 67,197 -207.[CrossRef][Medline]
Pasche, A. (1976a). The effect of hypercapnia on respiratory characteristics and diving behaviour of freely diving seals. Resp. Physiol. 26,183 -194.[CrossRef][Medline]
Pasche, A. (1976b). Hypoxia in freely diving hooded seal, Cystophora cristata. Comp. Biochem. Physiol. 55A,319 -322.[CrossRef]
Phillipson, E. A. and Bowes, G. (1986). Control of breathing during sleep. In Handbook of Physiology, Section 3: The Respiratory System, vol. Volume II: Control of Breathing, Part 2 (ed. N. S. Cherniack and J. G. Widdicombe), pp.649 -689. Baltimore, MD: American Physiological Society.
Phillipson, E. A., Duffin, J. and Cooper, J. D.
(1981). Critical dependence of respiratory rhythmicity on
metabolic CO2 load. J. Appl. Physiol.
50, 45-54.
Ponganis, P. J., Kooyman, G. L. and Castellini, M. A. (1993). Determinants of the aerobic dive limit of Weddell seal: analysis of diving metabolic rates, postdive end tidal PO2s, and blood and muscle oxygen stores. Physiol. Zool. 66,732 -749.
Przbylowski, T., Bangash, M.-F., Reichmuth, K., Morgan, B. J.,
Skatrud, J. B. and Dempsey, J. A. (2003). Mechanisms
of the cerebrovascular response to apnoea in humans. J.
Physiol. 548,323
-332.
Qvist, J., Hill, R. D., Schneider, R. C., Falke, K. J., Liggins,
G. C., Guppy, M., Elliot, R. L., Hochachka, P. W. and Zapol, W. M.
(1986). Hemoglobin concentrations and blood gas tensions of
free-diving Weddell seals. J. Appl. Physiol.
61,1560
-1569.
Reed, J. Z., Chambers, C., Fedak, M. A. and Butler, P. J.
(1994). Gas exchange of captive freely diving grey seals
(Halichoerus grypus). J. Exp. Biol.
191, 1-18.
Rhode, E. A., Elsner, R., Peterson, T. M., Campbell, W. B. and Spangler, W. (1986). Pressure-volume characteristics of aortas of harbor and Weddell seals. Am. J. Physiol. 251,R174 -R180.[Medline]
Shadwick, R. E. and Gosline, J. M. (1995). Arterial Windkessels in marine mammals. Symp. Soc. Exp. Biol. 49,243 -252.[Medline]
Shea, S. A. (1996). Behavioural and arousal-related influences on breathing in humans. Exp. Physiol. 81,1 -26.[Abstract]
Skinner, L. A. and Milsom, W. K. (2004). Respiratory chemosensitivity during wake and sleep in harbour seal pups (Phoca vitulina richardsii). Physiol. Biochem. Zool. 77,847 -863.[CrossRef][Medline]
Smith, C. A., Nakayama, H. and Dempsey, J. A. (2003). The essential role of carotid body chemoreceptors in sleep apnea. Can. J. Physiol. Pharmacol. 81,774 -779.[CrossRef][Medline]
Stephenson, R. (2004). A theoretical study of the effect of circadian rhythms on sleep-induced periodic breathing and apnoea. Resp. Physiol. Neurobiol. 139,303 -319.[CrossRef]
Stephenson, R., Butler, P. J. and Woakes, A. J. (1986). Diving behaviour and heart rate in tufted ducks (Aythya fuligula). J. Exp. Biol. 126,341 -359.[Abstract]
Stephenson, R., Mohan, R. M., Duffin, J. and Jarsky, T. M. (2000). Circadian rhythms in the chemoreflex control of breathing. Am. J. Physiol. 278,R282 -R286.
Thomas, G. D. and Segal, S. S. (2004). Neural
control of muscle blood flow during exercise. J. Appl.
Physiol. 97,731
-738.
Wilson, R. P., Simeone, A., Luna-Jorquera, G., Steinfurth, A.,
Jackson, S. and Fahlman, A. (2003). Patterns of respiration
in diving penguins: is the last gasp an inspired tactic? J. Exp.
Biol. 206,1751
-1763.
Woodin, M. A. and Stephenson, R. (1998). Circadian rhythms in diving behavior and ventilatory response to asphyxia in canvasback ducks. Am. J. Physiol. 274,R686 -R693.[Medline]
Zapol, W. M., Liggins, G. C., Schneider, R. C., Qvist, J.,
Snider, M. T., Creasy, R. K. and Hochachka, P. W.
(1979). Regional blood flow during simulated diving in the
conscious Weddell seal. J. Appl. Physiol.
47,968
-973.