Towards a multisensor station for automated biodiversity monitoring

Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts temperature, transformations land-use, or energy budget systems. While latter processes easily quantifiable, documentation loss biodiversity community structure is more difficult. Changes organismal abundance diversity barely documented. Censuses species usually fragmentary inferred often spatially, temporally ecologically unsatisfactory simple lists for individual study sites. Thus, detrimental global their drivers remain unrevealed. A major impediment to monitoring lack human taxonomic expertise that implicitly required large-scale fine-grained assessments. Another amount personnel associated costs needed cover scales, inaccessibility remote but nonetheless affected areas. To overcome these limitations we propose a network Automated Multisensor stations Monitoring Diversity (AMMODs) pave way new generation assessment centers. This combines cutting-edge technologies with informatics expert systems conserve knowledge. Each AMMOD station autonomous samplers insects, pollen spores, audio recorders vocalizing animals, sensors volatile organic compounds emitted plants (pVOCs) camera traps mammals invertebrates. AMMODs largely self-containing have ability pre-process data (e.g. noise filtering) prior transmission receiver storage, integration analyses. Installation on sites difficult access require sophisticated challenging system design optimum balance between power requirements, bandwidth transmission, service, operation under all environmental conditions years. An important prerequisite automated identification databases DNA barcodes, animal sounds, pVOCs, images used as training identification. thus become key component advance field research policy delivering at an unprecedented spatial temporal resolution.