Details

Autor(en) / Beteiligte

• Kindsvater, Holly K.
• Dulvy, Nicholas K.
• Horswill, Cat
• Juan-Jordá, Maria-José
• Mangel, Marc
• Matthiopoulos, Jason

Titel

Overcoming the Data Crisis in Biodiversity Conservation

Ist Teil von

• Trends in ecology & evolution (Amsterdam), 2018-09, Vol.33 (9), p.676-688

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2018

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species’ status with unparalleled quantitative rigor. Diagnosing the conservation status of many species is hampered by insufficient data. Modern computer-intensive fitting methods make it possible to merge mechanistic models and population data on well-studied indicator species, extending the inferences we can make about their data-limited relatives. Historically, assessments have used data from one population or species to create ad hoc proxy values for the life-history traits of relatives, but with modern Bayesian models we can share information in a standardized, coherent way. Advances in understanding community ecology and life-history evolution can be incorporated into these models as priors, extending statistical power even when data are sparse. These advances offer new possibilities for the rigorous assessment and protection of populations and species that previously have suffered from policy gaps created by insufficient data.