Making better use of non-invasive data in carnivore monitoring

Where do wolverines roam in Norway? How many brown bears live in the Himalayas?  An essential part of wildlife conservation and management is knowledge about the population dynamics and distribution of wild species.

“Wildlife monitoring is a vital tool for setting conservation goals and priorities and evaluating conservation or management decisions,” PhD candidate Mahdieh Tourani says.

“Wildlife monitoring is in essence recording presence of species and individuals to make inferences about population size and distributions. This makes it possible to assess a population’s status and make decisions on whether action is needed to control invasive species or recover endangered ones.”

However, acquiring reliable estimate is difficult because many species are elusive and rare, and spread over vast areas.

New methods for monitoring

The development of non-invasive approaches for monitoring wildlife populations has made it feasible to obtain ecological parameters across landscapes and populations, rather than a few locations or individuals.

“Today, the two most popular and widely used non-invasive monitoring methods are camera trapping and genetic sampling,” Tourani explains.  

Easier to cover larger and remote areas

One of the advantages with non-invasive methods is that they do not require capturing and handling of the animals. Non-invasive methods are particularly useful in the study of wild populations, where avoidance of or habituation to human presence could be detrimental.

In addition, non-invasive methods make it more feasible to cover entire landscapes and detect a larger proportion of the study population. These survey methods are particularly useful to study species for which direct observation is often infeasible, either because the species actively avoid human and inhabit remote areas, or because they naturally occur in low densities

Improving methods

However, despite the technological advances of monitoring methods, complementary analytical capabilities have lagged behind.

Tourani explains that only recently are scientists getting close to exploiting the potentials of non-invasively obtained data.

“My PhD chapters include issues   mostly faced by applied ecologists,” Tourani explains. “Studying wild populations in their natural habitat is associated with incomplete data . We need models that allow us to use all the information available, data that come from multiple monitoring methods, or opportunistically from dead animals.”

Her work includes  simulations of real-world scenarios, model fitting and case studies. Studies include a range of species from wolverine and medium-sized carnivores in Scandinavia to the Himalayan brown bear. 

Separate observation from ecology

The objective of her research was to apply modern hierarchical analytical models to several sets of carnivore monitoring data to address a series of conceptually and methodologically connected problems.

Hierarchical modelling offers ecologists a multi-level approach to disentangle observation and ecological processes.

“All the hierarchical models I have worked with account for imperfect detection, which is a key aspect,” she says.

Increasing detection probability

Tourani has quantified the detectability of mesocarnivores by camera traps and sheds light on the behavioral responses of focal species to detection devices and to olfactory lures as an important aspect of detectability.

“Using a multifaceted perspective on detectability in camera trap studies, we linked different aspects of detectability with species biology, to give investigators a more structured approach to selecting and testing measures intended to boost detection probability,” she says.

Himalayan brown bear

Tourani has incorporated multiple data sources with varying levels of information in data-sparse situations and introduced a multiple observation process model in the spatial capture-recapture framework to estimate population parameters such as density and abundance.

“When working with this model I used multi-method monitoring data of a Himalayan brown bear population in Pakistan,” she comments.  

Large-scale home range patterns

How an animal uses its home range is of perennial interest to wildlife ecologists.

“In that respect, I have examined the effect of heterogeneity in the environment and sex-specific patterns in wolverine home range size in Norway,” Tourani says.

She did this using solely non-invasively collected DNA data and spatial capture-recapture models.

The study area also had an unprecedented spatial extent (266,000 km2).

Tourani continues “Besides detecting evidence of the effect of landscape features such as latitude on home range size of wolverine population in Norway, we showed male wolverines had on average larger home ranges than females, and there was larger variation in home range sizes amongst females than males”.

Real-world ecology

Tourani did her PhD as part of the project WildMap - "Putting wildlife population dynamics on the map through spatially explicit estimation and forecasting".

“My work shows how hierarchical models help us use non-invasively collected data to yield answers to a range of questions in applied ecology.”

“Tackling the associated challenges increases our ability to draw inferences that more closely describe the complexity of real-world ecological systems,” she concludes.

Mahdieh Tourani will defend her PhD thesis "Leveraging non-invasive monitoring of carnivores using hierarchical models", on 25 September 2020. The defense can be followed online, read more about that here.

Published 21. September 2020 - 23:41 - Updated 23. September 2020 - 9:17