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A strategy for the next decade to address data deficiency in neglected biodiversity.

Axel HochkirchMichael J SamwaysJustin GerlachMonika BöhmPaul WilliamsPedro CardosoNeil CumberlidgeP J StephensonMary B SeddonViola ClausnitzerPaulo A V BorgesGregory M MuellerPaul Pearce-KellyDomitilla C RaimondoAnja DanielczakKlaas-Douwe B Dijkstra
Published in: Conservation biology : the journal of the Society for Conservation Biology (2020)
Measuring progress toward international biodiversity targets requires robust information on the conservation status of species, which the International Union for Conservation of Nature (IUCN) Red List of Threatened Species provides. However, data and capacity are lacking for most hyperdiverse groups, such as invertebrates, plants, and fungi, particularly in megadiverse or high-endemism regions. Conservation policies and biodiversity strategies aimed at halting biodiversity loss by 2020 need to be adapted to tackle these information shortfalls after 2020. We devised an 8-point strategy to close existing data gaps by reviving explorative field research on the distribution, abundance, and ecology of species; linking taxonomic research more closely with conservation; improving global biodiversity databases by making the submission of spatially explicit data mandatory for scientific publications; developing a global spatial database on threats to biodiversity to facilitate IUCN Red List assessments; automating preassessments by integrating distribution data and spatial threat data; building capacity in taxonomy, ecology, and biodiversity monitoring in countries with high species richness or endemism; creating species monitoring programs for lesser-known taxa; and developing sufficient funding mechanisms to reduce reliance on voluntary efforts. Implementing these strategies in the post-2020 biodiversity framework will help to overcome the lack of capacity and data regarding the conservation status of biodiversity. This will require a collaborative effort among scientists, policy makers, and conservation practitioners.
Keyphrases
  • electronic health record
  • big data
  • public health
  • healthcare
  • quality improvement
  • microbial community
  • artificial intelligence
  • deep learning
  • wastewater treatment
  • adverse drug