10.5061/DRYAD.68SD84VH
Ozgul, Arpat
University of Cambridge
Coulson, Tim
Imperial College London
Reynolds, Alan
University of Leeds
Cameron, Tom C.
University of Leeds
Umeå University
Benton, Tim G.
University of Leeds
Data from: Population responses to perturbations: the importance of
trait-based analysis illustrated through a microcosm experiment
Dryad
dataset
2012
Population: dynamics
Ecology: population
Life history: ecology
Sancassania berlesei
Ecology: statistical
Environmental variability
Modeling: population ecology
2012-01-09T18:00:48Z
2012-01-09T18:00:48Z
en
https://doi.org/10.1086/664999
153031 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Environmental change continually perturbs populations from a stable state,
leading to transient dynamics that can last multiple generations. Several
long-term studies have reported changes in trait distributions along with
demographic response to environmental change. Here we conducted an
experimental study on soil mites and investigated the interaction between
demography and an individual trait over a period of nonstationary
dynamics. By following individual fates and body sizes at each
life-history stage, we investigated how body size and population density
influenced demographic rates. By comparing the ability of two alternative
approaches, a matrix projection model and an integral projection model, we
investigated whether consideration of trait-based demography enhances our
ability to predict transient dynamics. By utilizing a prospective
perturbation analysis, we addressed which stage-specific demographic or
trait-transition rate had the greatest influence on population dynamics.
Both body size and population density had important effects on most rates;
however, these effects differed substantially among life-history stages.
Considering the observed trait-demography relationships resulted in better
predictions of a population’s response to perturbations, which highlights
the role of phenotypic plasticity in transient dynamics. Although the
perturbation analyses provided comparable predictions of stage-specific
elasticities between the matrix and integral projection models, the order
of importance of the life-history stages differed between the two
analyses. In conclusion, we demonstrate how a trait-based demographic
approach provides further insight into transient population dynamics.
Daily sampling of individual mitesday: day of the study (day t) | no:
individual ID for each day | surv: survival to day t+1? | stage:
life-history stage at day t | stage1: life-history stage at day t+1 |
trns: transition to next stage at day t+1? | tsex: transition to female
stage at day t+1? | dens: weighted population density at day t | size:
log(body size) at day t | size1: log(body size) at day t+1 | rep: produced
eggs at day t+1? | rec: number of eggs produced on day t+1 | day2: number
of eggs hatched on day t+2 | day3: number of eggs hatched on day t+3 |
day4: number of eggs hatched on day t+4 | day5: number of eggs hatched on
day t+5 | day6: number of eggs hatched on day t+6 | day7: number of eggs
hatched after day t+6 | eggsurv: proportion of eggs hatched | hrate: daily
hatching rate | eggsize: average log(egg size)ind_data.csvAdditional
experiment measuring egg-to-larva size transitioneggSize: log(egg size) |
larvaSize: log(larva size)egg_data.csvDaily population censusday: day of
the study (day t) | e: number of eggs | l: number of larvae | p: number of
protonymphs | t: number of tritonymphs | f: number of female adults | m:
number of male adults | group: (c)ontrol or (s)ample group? | dens:
weighted population densitypop_census.csv