Laboratory experiments are an attractive option for testing theoretical predictions not amenable to field-based investigations. The lesson from our work is to not underestimate the time, effort, and repeated failure required to establish a novel laboratory experimental system; and to be ready to pivot to a ‘safe’ option when continued failure may compromise a project.
We established laboratory systems to test theoretical predictions regarding the effects of habitat network structure on population outcomes. Previous empirical work in this space used protist systems, mostly with ‘migration’ supplied by pipetting between habitat patches (jars). Our systems increased the scale of organism, using Daphnia sp. as the model organism, and allowed self-directed movement by connecting habitat patches with aquarium tubing.
Early attempts were beset by high mortality and extinctions. Literally months were required to balance feeding rate and water replacement, enabling habitat networks that supported populations over months. Successful experiments then tested the effects of network structure on equilibrium population outcomes and the effects of disrupting connectivity of established populations.
However, attempts to introduce directional bias to movement between habitat patches were unsuccessful. Movement bias is common in systems like rivers, or habitat networks subject to strong prevailing winds. Despite promising pilot results, attempts to introduce directional flow were unsuccessful at full experimental scale. Similarly, using a light gradient with the phototactic Daphnia appeared promising but could not be scaled up.
At that stage, we pivoted to model-based simulations to assess the effect of movement bias and rate. However, to inform the efforts of future laboratory researchers, we parameterised the models using data from the successful experiments and used a reasonable number of replicates that one might see in a well-resourced laboratory. Simulation-based power analyses identified potentially observable effects in a laboratory setting.
By remaining flexible and planning for contingency the laboratory program was robust to the many failures along the way and the broader project was robust to the ultimate failure of some laboratory tests. Planning for contingencies, learning from failure, and documenting the trials and tribulations inherent in establishing this type of system can help future researchers to go further, faster.