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ASIP Mentor guide
AI, data and signal processingB21Partner brief8 of 12 in AI

Counting What Lives in a Place

Atria Foundation

Estimate what species live in an area when detection is always imperfect.

Skills
  • Statistical estimation under imperfect detection
  • Species classification from image or audio
  • Sensor deployment
  • Data visualisation
Domains
Environment

Who you work with#

Atria Foundation, described in Brief 12, under its Bio-Diversity pillar. The Foundation runs plantation drives and describes its aim there as promoting harmony across species. It has no way at present of saying what any of that has done to the life in a place.

The situation#

Someone wants to know what species live in a given area — a forest patch, a farm, a stretch of riverbank. That question sits behind conservation planning, environmental clearance, restoration monitoring and corporate biodiversity reporting.

Several methods exist and each sees a different slice:

  • Camera traps catch ground-dwelling mammals well and miss small, arboreal and nocturnal-silent species
  • Acoustic recorders catch birds, bats, frogs and insects that call, and miss everything that does not
  • Environmental DNA detects traces of many species from a water or soil sample, but needs a laboratory, sequencing, and a reference database that is incomplete for Indian species
  • Transect and plot surveys are reliable and expensive in expert time
  • Citizen records such as bird and nature-observation platforms are large and heavily biased toward attractive species near roads

What is going wrong#

Each method gives you a list that reflects the method as much as the place. Combining them is not addition, because each one detects different species with different probability, so you cannot simply pool the lists and call it a survey.

Why it is not fixed yet#

Because it is a genuine open problem in ecology, not an engineering oversight. Estimating how many species are present when your detection is imperfect and varies by method is a live statistical research area. Anyone promising a complete answer is overselling.

Skills and Expertise#

  • Branch — CS and Electronics, with a strong pull for anyone interested in ecology or statistics.
  • Technical skills — Statistical estimation under imperfect detection, combining heterogeneous data sources, species classification from images or audio, sensor deployment, data visualisation.
  • Other skills — Reading ecological literature, stating uncertainty, resisting the urge to claim completeness.