bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Дек. 19, 2023
Abstract
The
functional
response
describes
feeding
rates
of
consumers
as
a
function
resource
density.
While
models
for
on
single
species
are
well
studied
and
supported
by
large
body
empirical
research,
multiple
ubiquitous
in
nature.
However,
laboratory
experiments
designed
parameterizing
multi-species
responses
(MSFR)
extremely
rare,
mainly
due
to
logistical
challenges
the
non-trivial
nature
their
statistical
analysis.
Here,
we
describe
how
these
can
be
fitted
data
Bayesian
framework.
Specifically,
address
problem
prey
depletion
during
experiments,
which
accounted
through
dynamical
modeling.
In
comprehensive
simulation
study,
test
effects
experimental
design,
sample
size
noise
level
identifiability
four
distinct
MSFR
models.
Additionally,
demonstrate
method’s
versatility
applying
it
list
datasets.
We
identify
designs
trials
that
produce
most
accurate
parameter
estimates
two-
three-prey
scenarios.
Although
introduces
systematic
bias
estimates,
model
selection
performs
surprisingly
MSFRs,
almost
always
identifying
correct
even
small
This
flexible
framework
allows
simultaneous
analysis
from
both
single-
multi-prey
scenarios,
either
with
or
without
depletion.
will
help
elucidate
mechanisms
such
selectivity,
switching
implications
food
web
stability
biodiversity.
Our
approach
equips
researchers
appropriate
tools
improve
understanding
interactions
complex
ecosystems.
Proceedings of the National Academy of Sciences,
Год журнала:
2023,
Номер
120(11)
Опубликована: Март 7, 2023
Darwinian
evolution
(DE)—biology’s
powerful
process
of
adaptation—is
remarkably
different
from
other
known
dynamical
processes.
It
is
antithermodynamic,
driving
away
equilibrium;
it
has
persisted
for
3.5
billion
years;
and
its
target,
fitness,
can
seem
like
“Just
So”
stories.
For
insights,
we
make
a
computational
model.
In
the
Evolution
Machine
(DEM)
model,
resource-driven
duplication
competition
operate
inside
cycle
search/compete/choose.
We
find
following:
1)
DE
requires
multiorganism
coexistence
long-term
persistence
ability
to
cross
fitness
valleys.
2)
driven
by
resource
dynamics,
booms
busts,
not
just
mutational
change.
And,
3)
ratcheting
mechanistic
separation
between
variation
selection
steps,
perhaps
explaining
biology’s
use
separate
polymers,
DNA
proteins.
Abstract
When
life
arose
from
prebiotic
molecules
3.5
billion
years
ago,
what
came
first?
Informational
(RNA,
DNA),
functional
ones
(proteins),
or
something
else?
We
argue
here
for
a
different
logic:
rather
than
seeking
molecule
type
,
we
seek
dynamical
process.
Biology
required
an
ability
to
evolve
before
it
could
choose
and
optimise
materials.
hypothesise
that
the
evolution
process
was
rooted
in
peptide
folding
Modelling
shows
how
short
random
peptides
can
collapse
water
catalyse
elongation
of
others,
powering
both
increased
stability
emergent
autocatalysis
through
disorder-to-order
Functional Ecology,
Год журнала:
2021,
Номер
37(1), С. 26 - 43
Опубликована: Окт. 22, 2021
Abstract
Species
traits
and
environmental
conditions
determine
the
occurrence
strength
of
trophic
interactions.
If
we
understand
relationship
between
these
factors
interactions,
can
make
more
accurate
predictions
build
better
trophic‐interaction
models.
We
compare
by
considering
their
effect
on
different
parts
(steps)
a
interaction,
such
as
steps
search
pursuit
.
By
linking
to
relevant
steps,
use
relationships
Currently,
this
is
done
ad
hoc,
defining
based
species
interest.
This
makes
it
difficult
across
gain
an
overarching
understanding
how
environment
drive
present
comprehensive
approach
for
explicit
choice
interaction
or
conditions,
which
readily
integrated
into
existing
The
core
framework
that
modular;
eight
occur
in
all
interactions
them
modular,
general
dynamic
model.
When
applying
framework,
one
explicitly
selects
only
most
uses
those
specific
To
our
modular
revisit
expand
functional
numerical
response
functions,
dividing
steps:
(1)
search,
(2)
prey
detection,
(3)
attack
decision,
(4)
pursuit,
(5)
subjugation,
(6)
ingestion,
(7)
digestion
(8)
nutrient
allocation.
Together
form
dynamical
model
where
be
parameterized
multiple
factors.
then
concretize
outlining
community
modelled
selecting
key
modules
parameterizing
exemplify
terrestrial
arthropods
using
empirical
data
body
size
temperature
responses.
With
at
dynamics,
allows
quantification
comparisons
importance
traits,
abiotic
ecosystems
types,
provides
powerful
tool
trait‐based
prediction
food‐web
structure
dynamics.
A
free
Plain
Language
Summary
found
within
Supporting
Information
article.
Methods in Ecology and Evolution,
Год журнала:
2022,
Номер
13(11), С. 2516 - 2530
Опубликована: Сен. 13, 2022
Abstract
Mathematical
models
serve
many
purposes
in
biology.
Each
and
every
model
is
a
necessary
simplification
of
reality,
and,
as
simplifications,
these
are
also
wrong
by
definition.
And
yet
there
ways
to
be
wrong,
some
much
greater
concern
than
others.
For
example,
paradoxical
model‐based
prediction
may
simply
puzzling
whereas
unphysical
variables
(e.g.
negative
amounts
time
or
temperatures
below
absolute
zero)
nonbiological
abundances
feeding
rates)
should
avoided
altogether.
Here
I
analyse
discrete‐time
annual‐plant
population
dynamics
three
phenomenological
for
density‐dependent
fecundity.
These
generally
interchanged
solely
on
the
basis
their
statistical
fit
data.
On
other
hand,
highlight
which
hampers
our
ability
capture
known
aspects
then
demonstrate
how
specify
more
flexible,
biologically
appropriate
illustrate
this
model's
behaviour
interpretation
single‐species
multi‐species
contexts.
By
constructing
generative
dynamics,
can
why
emergent
phenomena,
such
density
dependence,
emerge.
Although
my
focus
applied
annual
plants,
biological
implications
extend
modelling
any
species
with
discrete
life
cycle
nonoverlapping
generations.
More
broadly,
exploration
here
showcases
that
criteria
we
could,
arguably
should,
ground‐truth
mathematical
across
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Май 17, 2024
Abstract
Ecologists
differ
in
the
degree
to
which
they
consider
linear
Type
I
functional
response
be
an
unrealistic
versus
sufficient
representation
of
predator
feeding
rates.
Empiricists
tend
it
unsuitably
non-mechanistic
and
theoreticians
necessarily
simple.
Holling’s
original
rectilinear
model
is
dismissed
by
satisfying
neither
desire,
with
most
compromising
on
smoothly
saturating
II
for
searching
handling
are
assumed
mutually
exclusive
activities.
We
derive
a
“multiple-prey-at-a-time”
generalization
that
includes
III
reflect
predators
can
continue
search
when
arbitrary
number
already-captured
prey.
The
multi-prey
clarifies
empirical
relevance
models
conditions
under
linearity
mechanistically-reasoned
description
rates,
even
times
long.
find
support
presence
35%
2,591
compiled
datasets,
evidence
larger
predator-prey
body-mass
ratios
permit
while
greater
numbers
Incorporating
into
Rosenzweig-MacArthur
population-dynamics
reveals
non-exclusivity
lead
coexistence
states
dynamics
not
anticipated
theory
built
traditional
models.
In
particular,
bistable
fixed-point
limit-cycle
long-term
crawl-by
transients
between
them
where
abundance
top-heavy
food
webs
linear.
conclude
should
considered
empirically
but
also
more
bounded
conclusions
drawn
presuming
appropriate.
Methods in Ecology and Evolution,
Год журнала:
2024,
Номер
15(9), С. 1704 - 1719
Опубликована: Июнь 23, 2024
Abstract
The
functional
response
describes
feeding
rates
of
consumers
as
a
function
resource
density.
While
models
for
on
single
species
are
well
studied
and
supported
by
large
body
empirical
research,
multiple
ubiquitous
in
nature.
However,
laboratory
experiments
designed
parameterizing
multi‐species
responses
(MSFR)
extremely
rare,
mainly
due
to
logistical
challenges
the
non‐trivial
nature
their
statistical
analysis.
Here,
we
describe
how
these
can
be
fitted
data
Bayesian
framework.
Specifically,
address
problem
prey
depletion
during
experiments,
which
accounted
through
dynamical
modelling.
In
comprehensive
simulation
study,
test
effects
experimental
design,
sample
size
noise
level
identifiability
four
distinct
MSFR
models.
Additionally,
demonstrate
method's
versatility
applying
it
list
datasets.
We
identify
designs
trials
that
produce
most
accurate
parameter
estimates
two‐
three‐prey
scenarios.
Although
introduces
systematic
bias
estimates,
model
selection
performs
surprisingly
MSFRs,
almost
always
identifying
correct
even
small
This
flexible
framework
allows
simultaneous
analysis
from
both
single‐
multi‐prey
scenarios,
either
with
or
without
depletion.
will
help
elucidate
mechanisms
such
selectivity,
switching
implications
food
web
stability
biodiversity.
Our
approach
equips
researchers
appropriate
tools
improve
understanding
interactions
complex
ecosystems.
Frontiers in Ecology and Evolution,
Год журнала:
2022,
Номер
10
Опубликована: Авг. 9, 2022
This
article
reviews
the
nature
of
functional
responses
that
have
commonly
been
used
to
represent
feeding
relationships
in
ecological
literature.
It
compares
these
with
range
response
forms
are
likely
characterize
species
natural
communities.
The
latter
set
involves
many
more
variables.
history
models,
and
examines
previous
work
has
allowed
a
predator
single
type
prey
depend
on
additional
variables
beyond
abundance
type.
While
number
complex
discussed
over
years,
affecting
rates
still
typically
omitted
from
models
food
webs.
influences
trophic
levels
above
or
below
particularly
be
ignored,
although
data
suggested
they
can
large
effects
response.
adaptive
behavior
time-scale
measurement
also
too
often
ignored.
Some
known
unknown
consequences
omissions
discussed.
Prey
handling
processes
are
considered
a
dominant
mechanism
leading
to
short-term
positive
indirect
effects
between
prey
that
share
predator.
However,
growing
body
of
research
indicates
predators
not
necessarily
limited
by
such
in
the
wild.
Density-dependent
changes
predator
foraging
behavior
can
also
generate
but
they
rarely
included
as
explicit
functions
densities
functional
response
models.
With
aim
untangling
proximate
mechanisms
species
interactions
natural
communities
and
improving
our
ability
quantify
interaction
strength,
we
extended
multi-prey
version
Holling
disk
equation
including
density-dependent
behavior.
Our
model,
based
on
traits
behavior,
was
inspired
vertebrate
community
arctic
tundra,
where
main
(the
fox)
is
an
active
forager
feeding
primarily
cyclic
small
rodent
(lemming)
eggs
various
tundra-nesting
bird
species.
Short-term
lemmings
birds
have
been
documented
over
circumpolar
Arctic
underlying
remain
poorly
understood.
We
used
unique
data
set,
containing
high-frequency
GPS
tracking,
accelerometer,
behavioral,
experimental
parameterize
15-year
time
series
nesting
success
evaluate
strength
found
(1)
play
minor
role
system
(2)
fox
daily
activity
budget
distance
traveled
partly
explain
predation
release
observed
during
lemming
peaks.
These
adjustments
with
respect
density
thus
appear
commonly
reported
among
tundra
prey.
components
little
studied
deserve
more
attention
improve
interactions.