Population Ecology Young Scientist Award: Award Lecture
Mathematical models for effective management of populations subject to uncertainty
Hiroyuki Yokomizo (Center for Environmental Risk Research, National Institute for Environmental Studies)
We need to mitigate various anthropogenic threats to species as efficiently as possible because both time and budgets available for management are limited. However, finding optimal solutions is complicated by the uncertainty caused by both stochasticity and imperfect knowledge of targeted populations. One important question is how much we should reduce those uncertainties by monitoring, which also incurs a cost. Different degrees of uncertainty need to be modeled differently. First, I derive optimal conservation and monitoring effort levels under uncertainty on population size of an endangered population. Second, I demonstrate the importance of knowing the relationships between density of invasive plants and its cost of impact for effective weed managements. Third, I propose a mathematical model to spatially allocate conservation efforts based on imperfect knowledge of the rate of change in population size for conservation of Japanese endangered vascular plants. Mathematical models enable us to derive rational and objective management strategies. We can show assumptions clearly in the models, which may contribute to consensus building in decision-making. I show how mathematical models can give us useful insights and provide tools for effective management of populations.