Quantifying species recovery and conservation success to develop an IUCN Green List of Species

Stopping declines in biodiversity is critically important, but it is only a first step toward achieving more ambitious conservation goals. The absence of an objective and practical definition of species recovery that is applicable across taxonomic groups leads to inconsistent targets in recovery plans and frustrates reporting and maximization of conservation impact. We devised a framework for comprehensively assessing species recovery and conservation success. We propose a definition of a fully recovered species that emphasizes viability, ecological functionality, and representation; and use counterfactual approaches to quantify degree of recovery. This allowed us to calculate a set of 4 conservation metrics that demonstrate impacts of conservation efforts to date (conservation legacy); identify dependence of a species on conservation actions (conservation dependence); quantify expected gains resulting from conservation action in the medium term (conservation gain); and specify requirements to achieve maximum plausible recovery over the long term (recovery potential). These metrics can incentivize the establishment and achievement of ambitious conservation targets. We illustrate their use by applying the framework to a vertebrate, an invertebrate, and a woody and an herbaceous plant. Our approach is a preliminary framework for an International Union for Conservation of Nature (IUCN) Green List of Species, which was mandated by a resolution of IUCN members in 2012. Although there are several challenges in applying our proposed framework to a wide range of species, we believe its further development, implementation, and integration with the IUCN Red List of Threatened Species will help catalyze a positive and ambitious vision for conservation that will drive sustained conservation action.     

Parasite transmission in a migratory multiple host system

A transmission model was devised for trichostrongyloid nematodes of saiga antelopes and domestic sheep in Kazakhstan. The framework extends previous models by including seasonal migration of saigas, contact with separate populations of sheep, and climate-driven stochasticity in herbage biomass and in the development, survival and migration onto herbage of free-living larvae. The model was parameterised for the contrasting life histories of Marshallagia, Haemonchus and Nematodirus, three important parasites of saigas and sheep in the region, and was successful at predicting broad qualitative patterns of infection dynamics in sheep and saigas. Parasite transmission between saigas and sheep was predicted to be most important for Marshallagia (from sheep to saigas in the south in winter, and onward transmission to sheep in the north in summer) and Haemonchus (from sheep in the north in summer via saigas to sheep further south in autumn). Model predictions for winter transmission of Marshallagia infection in saigas were consistent with field data, which showed that saigas culled before they have grazed the winter range carry lower burdens of this parasite than older animals. The model provides a mechanistic explanation for its predictions, which will assist hypothesis formation, and further the epidemiological basis of efforts to control parasite transmission between wildlife and livestock in both directions. A similar modelling approach could prove useful in other situations where detailed mechanistic models of parasite transmission are inappropriate in the face of parameter uncertainty and spatio-temporal variation in climate and host density. This is likely to include the majority of wildlife-parasite systems.