Shrub and vegetation cover predict resource selection use by endangered species of desert lizard

blunt nosed leopard lizard wikimedia commons
blunt nosed leopard lizard wikimedia commons

Location, location, location. A research team from York University has published research using field data that describes habitat use and animal movements for an endangered species of desert lizard and foundation shrub species.

The study was published March 17 in the journal Nature.

Christopher Lortie
Christopher Lortie

Biology Professor Christopher Lortie and graduate students Jenna Braun, Taylor Noble, Mario Zuliani, Nargol Ghazian and Malory Owen, together with colleagues at The Bureau of Land Management, The Nature Conservancy and University of California, Santa Barbara, developed a set of resource selection functions to examine habitat use patterns to better inform management and protection of large protected desert habitats.

Lortie states that “these tools can be simple and show where a species is most likely to live within an ecosystem, or relatively more complex identifying key drivers within a landscape that best predict where to find a species. These statistics are not unlike many of the tools used in real estate models, and we developed several online tools to this effect to support stakeholders in exploring these ideas.”

Here is a link to one of the apps developed to provide interactivity with key factors used in the models:

Using the endangered species Gambelia sila (G. sila) and a foundation plant species, researchers used analysis of telemetry, vegetation surveys and remotely sensed data to identify key drivers of selected versus available locations for this lizard in Carrizo Plain National Monument, U.S. This is novel because data from very different scales were integrated and validated in a single set of integrated models.

Blunt-nosed leopard lizard (G. sila)

Lortie proposes that “space is always limiting in natural systems, and we must balance the needs of the many with the needs of the few to ensure that we protect biodiversity and support socioeconomic resilience regionally.”

Braun worked tirelessly for months to compile and connect the data from telemetry sensors, vegetation surveys on the ground and data from satellites to stitch together the big picture for this protected area.

Many endangered species likely have limited access to potential resources and habitats locally and regionally. This is significant because the capacity for endangered species to choose to use habitat can be constrained by availability and relative location. Furthermore, not all species have the capacity to disperse and move long distances biologically or ecological because of barriers in place naturally or from anthropogenic sources.

Tools like resource selection function models and occupancy models can be critical tools that inform strategic restoration. Time, space and resources are always limiting for conservation, and enabling the best decision given the hand we have been dealt in each context is a necessity. This is where strategic investment, triage and habitat ranking come in to play.

In this specific study, the probability of selection by a population of endangered animals given the resource types that were available to them was modeled. Increasing shrub cover, lower and relatively more flat sites, increasing normalized difference vegetation index and solar radiation all significantly predicted likelihood of observed selection within the area sampled.

This thinking can be applied to many other systems and for many other species, and the analytics to do so are rapidly evolving and becoming more accessible, said Lortie. The real estate paradigm that key environmental infrastructure within a neighbourhood or region, such as foundation plant species including shrubs or local differences in the physical attributes, can inform potential investment in some locations over others for this endangered species is critical.

We need to know what other animals prefer too before we can protect and invest wisely, said Lortie.