A field ecologist's adventures in the virtual world: using simulations to design data collection for complex models

Area of Science:

• Ecology
• Ecological modeling
• Environmental science

Background:

• Field data collection is often costly and time-consuming, posing challenges for ecological research requiring sufficient data for statistical analysis.
• Existing methods like pilot studies and power analysis for sampling design are difficult to apply to complex projects with multi-scale, multi-type data.
• There is a need for realistic approaches to guide data collection design in complex ecological research.

Purpose of the Study:

• To develop and demonstrate a flexible simulation approach for designing ecological data collection under realistic fieldwork constraints.
• To inform researchers about the data requirements and time needed for fieldwork.
• To assess the impact of various constraint scenarios on data collection and downstream analysis.

Main Methods:

• Developed a flexible simulation approach incorporating deterministic (field trip length, travel, measurement times) and stochastic (species detection/occupancy rates, weather) constraints.
• Simulated data collection and analysis for a case study involving fitting plant height data to a nonlinear growth model.
• Tested how different constraint scenarios affected model fit, including parameter bias, uncertainty, and capture rate.

Main Results:

• Species prevalence significantly influenced data sets and model performance more than deterministic factors like travel times.
• Ignoring species detection and occupancy rates led to a 40% underestimation of the required field time for adequate data collection.
• The simulation approach effectively informed data needs and collection duration under realistic fieldwork conditions.

Conclusions:

• Flexible simulations are valuable tools for refining fieldwork design, estimating costs, and incorporating uncertainty into ecological project planning.
• Integrating data collection, analysis, and decision-making in a virtual setting can aid field ecologists in research design.
• Simulation-based approaches enhance the realism and efficiency of planning ecological data collection efforts.