Incorporating species population dynamics into static prioritization: Targeting species undergoing rapid change. Issue 2 (12th November 2018) - Fukumori, Kayoko; Ishida, Shinya; Shimoda, Michiko; Takenaka, Akio; Akasaka, Munemitsu; Nishihiro, Jun; Takamura, Noriko; Kadoya, Taku
Abstract: Conservation planning has generally used models with a static spatial distribution of species to predict the likely occurrence of species. However, static data do not usually capture rapid changes in the abundance of endangered species or cryptic life stages such as the dormancy stage of eggs and seeds. Little is known about how neglecting dynamic population processes, such as recovery processes, can affect the outcomes of spatial prioritization in conservation planning. In this study, we investigated the distribution of 62 aquatic plant species, including 23 threatened species, in 415 agricultural ponds for 37 years to examine the importance of including recovery processes in conservation planning. Using long‐term historical presence–absence data and seedbank longevity data for aquatic macrophytes, we estimated rates of population disappearance and recovery for each species in each pond over the next 100 years. Average rates of recovery exceeded 0, 0.2, and 0.4 in 85.4%, 40.3%, and 4.8% of aquatic plant species, respectively. Simulation results suggested that the extinction risk for a species greatly decreased when recovery processes were considered. We found that including recovery processes in target species populations increased the performance of spatial prioritization by protecting more species in a smaller number of protected ponds. Spatial ranking of ponds for species conservation differed substantially among scenarios that included and excluded population recovery processes, suggesting that conservation priorities based on complementarity analysis are sensitive to underlying assumptions. Synthesis and applications . Our dynamic approach, which considers recovery processes of species, contributes to more effective conservation planning by reducing bias in the prediction of species' state, given that cryptic life stages are ubiquitous among many plants and some animals. Time‐series presence/absence data on target species are quite useful for the approach and are often archived by participatory monitoring. Thus, the opportunities for applying our method are broad, especially for conservation prioritization and decision‐making at the local scale. Abstract : Our dynamic approach, which considers recovery processes of species, contributes to more effective conservation planning by reducing bias in the prediction of species' state, given that cryptic life stages are ubiquitous among many plants and some animals. Time‐series presence/absence data on target species are quite useful for the approach and are often archived by participatory monitoring. Thus, the opportunities for applying our method are broad, especially for conservation prioritization and decision‐making at the local scale.