Study design and parameter estimability for spatial and temporal ecological models

Parameter Estimation in a PDE Model for the Spatial Spread of Cocoa Black Pod Disease

In this paper, we develop an epidemiological model with both environmental (primary infection from the environmental spores reservoir) and direct transmission (secondary infection from an infected host to a susceptible pod). This model simulates the spatiotemporal evolution of cocoa black pod disease caused by Phytophthora megakarya. Since reliable parameter estimation is a central issue for modeling realistic biological systems, we used a mechanistic-statistical approach to estimate model parameters from real observations of a specific cocoa plot. In addition, to refine numerical simulations of the pathosystem, data describing the shade intensity all over the plot were exploited and led to increased model predictions accuracy and also highlighted a higher number of infected pods located in areas of the plot with higher shading intensity. Recommendations in terms of promoting cocoa farming in systems with low shading intensity may be evident if these results are confirmed. Our results also highlight the importance of the environmental spore reservoir in black pod disease dynamics.

Study design and parameter estimability for spatial and temporal ecological models

The statistical tools available to ecologists are becoming increasingly sophisticated, allowing more complex, mechanistic models to be fit to ecological data. Such models have the potential to provide new insights into the processes underlying ecological patterns, but the inferences made are limited by the information in the data. Statistical nonestimability of model parameters due to insufficient information in the data is a problem too‐often ignored by ecologists employing complex models. Here, we show how a new statistical computing method called data cloning can be used to inform study design by assessing the estimability of parameters under different spatial and temporal scales of sampling. A case study of parasite transmission from farmed to wild salmon highlights that assessing the estimability of ecologically relevant parameters should be a key step when designing studies in which fitting complex mechanistic models is the end goal.