Research | Ecological Inference for Conservation

Research

Animal movement, demographic inference and conservation decisions under uncertainty.

Many ecological processes that matter for conservation are only partly observable. Animals move through changing landscapes and seascapes; survival and reproduction are imperfectly measured; exposure and vulnerability often have to be inferred from noisy data.

Our work develops quantitative approaches for these problems. We use movement, sensor, demographic and monitoring data to estimate hidden ecological states, connect them to population processes, and ask how uncertainty should affect monitoring and management.

Black-tailed godwit research landscape — Photo: Jan van de Kam

Theme

Conservation demography and annual-cycle limitation

We estimate demographic processes that cannot be observed directly, such as survival, recruitment, reproductive status and life-history stages that shape population trajectories.

Key questions

Which demographic processes limit population recovery or change?
How do breeding, migration and non-breeding conditions connect across the annual cycle?
How do imperfect observations and hidden states affect conservation inference?

Example systems/projects

Black-tailed godwits
Bar-tailed godwits
Brent geese

Methods

Integrated population models
Capture-recapture models
Multi-event and multistate models
Population projection
Uncertainty-aware demographic inference

Godwit chick survival Brent goose migration and demography Bar-tailed godwit demography Related publications

Theme

Movement ecology and behavioural inference

We use tracking and biologging data to infer behavioural modes, movement decisions, resource use and exposure to environmental conditions.

Key questions

What are animals doing when behaviour is not directly observed?
How do individual state, weather, resources and social information shape movement decisions?
Where and when do animals encounter pressures or opportunities?

Example systems/projects

Migratory shorebirds
Geese
Gulls
Spoonbills

Methods

Animal tracking
Hidden-state models
Behavioural classification
Movement-path analysis
Resource-use inference

UvA-BiTS and dashboards Seabird behaviour and offshore wind Bar-tailed godwit demography Brent goose migration and demography Related publications

Theme

Animal-borne monitoring and sentinel indicators

We explore how animal-borne data can reveal environmental exposure, behavioural change and vulnerability in ways that complement conventional monitoring.

Key questions

Which sentinel signals can be inferred reliably from tracking and sensor data?
When do movement or behaviour data indicate exposure to environmental pressures?
How can tracking-data infrastructure turn animal-borne data into interpretable ecological indicators?

Example systems/projects

Waakvogels
UvA-BiTS tracking infrastructure
Gulls, geese, storks and other tracked birds

Methods

Indicator development
Automated tracking analysis
Behavioural discovery
Dashboard development
Event-led calibration

Waakvogels UvA-BiTS and dashboards Seabird behaviour and offshore wind Related publications

Theme

Developing direction: ecological inference for conservation decisions

We are developing ways to connect demographic models, movement-based indicators and uncertainty-aware forecasts more directly to conservation and monitoring decisions.

Key questions

Which ecological uncertainty matters most for conservation interpretation?
How can demographic and movement models help frame possible management actions?
What information is needed before conservation action, monitoring investment or preparedness planning can be improved?

Example systems/projects

Black-tailed godwit conservation landscapes
Waakvogels monitoring and dashboard outputs
Biodiversity monitoring and preparedness collaborations

Methods

Problem framing with stakeholders
Uncertainty-aware forecasting
Monitoring design
Scenario exploration
Management-relevant model outputs

Godwit chick survival Waakvogels Vector-borne disease Related publications