Abstract
High resolution monitoring is fundamental to understand and predict the
dynamics of ecological communities in an era of global change and
biodiversity declines. While real-time and fully automated monitoring of
the abiotic components of ecosystems has been possible for some time,
monitoring the biotic components at different organizational scales,
e.g. from individual behaviours and traits to the abundance and
distribution of species, is far more challenging. Recent technological
advancements offer potential solutions to achieve this through: (i)
increasingly affordable high throughput recording hardware, which can
collect rich multidimensional data, and (ii) increasingly accessible
artificial intelligence approaches, which are able to extract ecological
knowledge from large datasets. However, automating the monitoring of
facets of ecological populations and communities via such technologies
is still in its infancy, being primarily achieved at low spatiotemporal
resolutions within specific stages of the monitoring workflow. Here, we
review existing technologies for data recording and processing that
enable automated monitoring of ecological communities. We then present
novel frameworks that combine such technologies, forming fully automated
pipelines to detect, track, classify, and count multiple species, and
even record behavioural and morphological traits, at resolutions which
have previously been impossible to achieve. Based on these rapidly
developing technologies, we illustrate a solution to one of the greatest
challenges in ecology and conservation: the ability to rapidly generate
high resolution, multidimensional, and critically, standardized data
across complex ecologies.