TY - JOUR
T1 - nlstimedist: An R package for the biologically meaningful quantification of unimodal phenology distributions
AU - Steer, Nicola C.
AU - Ramsay, Paul M.
AU - Franco, Miguel
PY - 2019/9/3
Y1 - 2019/9/3
N2 - Phenological investigation can provide valuable insights into the ecological effects of climate change. Appropriate modelling of the time distribution of phenological events is key to determining the nature of any changes, as well as the driving mechanisms behind those changes.
Here, we present the nlstimedist r package, a distribution function and modelling framework that describes the temporal dynamics of unimodal phenological events. The distribution function is derived from first principles and generates three biologically interpretable parameters.
Using seed germination at different temperatures as an example, we show how the influence of environmental factors on a phenological process can be determined from the quantitative model parameters.
The value of this model is its ability to represent various unimodal temporal processes statistically. The three intuitively meaningful parameters of the model can make useful comparisons between different time periods, geographical locations or species' populations, in turn allowing exploration of possible causes.
AB - Phenological investigation can provide valuable insights into the ecological effects of climate change. Appropriate modelling of the time distribution of phenological events is key to determining the nature of any changes, as well as the driving mechanisms behind those changes.
Here, we present the nlstimedist r package, a distribution function and modelling framework that describes the temporal dynamics of unimodal phenological events. The distribution function is derived from first principles and generates three biologically interpretable parameters.
Using seed germination at different temperatures as an example, we show how the influence of environmental factors on a phenological process can be determined from the quantitative model parameters.
The value of this model is its ability to represent various unimodal temporal processes statistically. The three intuitively meaningful parameters of the model can make useful comparisons between different time periods, geographical locations or species' populations, in turn allowing exploration of possible causes.
UR - https://pearl.plymouth.ac.uk/context/bms-research/article/1978/viewcontent/Steer_et_al_2019_Methods_in_Ecology_and_Evolution.pdf
U2 - 10.1111/2041-210x.13293
DO - 10.1111/2041-210x.13293
M3 - Article
SN - 2041-210X
VL - 10
SP - 1934
EP - 1940
JO - Methods in Ecology and Evolution
JF - Methods in Ecology and Evolution
IS - 11
ER -