Kasey Rahn
UM News Service
MISSOULA – The University of Montana’s Avian Science Center collects, synthesizes and communicates knowledge about birds and their ecosystems for the conservation of natural resources. This mission often translates to analyzing the approaches used to collect information about birds, improving the scientific data that are the backbone of conservation management decisions.
In a new study, Avian Science Center doctoral student Kaitlyn Reintsma tested a relatively unknown nest density estimator for songbirds using Brewer’s sparrow nesting data, and she determined it is just as accurate as traditional methods. Her co-authors include Victoria Dreitz, the UM Avian Science Center director, and former Avian Science Center researcher Alan Harrington, currently a graduate student at Oregon State University.
“This study provides evidence that the nest density estimator developed by Guillaume Péron and his collaborators in a 2014 study is a potentially useful tool for a wider range of taxa than solely the species it was created for,” Reintsma said. “Use of this model could improve insight into vital measurements important for wildlife conservation.”
Reintsma is a doctoral student studying fish and wildlife biology in the W.A. Franke College of Forestry and Conservation at UM. She originally began the study as part of her undergraduate research required by the Davidson Honors College, as well as the honors option of UM’s Bachelor of Science in Wildlife Biology. This blossomed into publication-worthy research under the guidance of Dreitz, her undergraduate research adviser and now-Ph.D. adviser.
Birds are sensitive to environmental changes, so they’re frequently used to understand human impacts on the environment and establish ecosystem-level conservation policies, Reintsma and her co-authors say. As humans increasingly put pressure on the natural world, it becomes important to understand what demographic factors drive changes in wildlife population sizes. For birds, that often comes down to breeding productivity – how many baby birds are successfully launched into the world.
Breeding productivity is most often inferred exclusively from nest success rates, or the proportion of nests with at least one offspring fledging successfully. But clutch size and nest density – how many nests there are in a given area – also play important roles.
The easiest way for scientists to calculate nest density would be to find all of the nests in a given area and divide by the size of the area, but finding all of the nests is easier said than done. It’s often not feasible to locate every nest in a given area because the nests are not always easily detected on the day the area is surveyed, and even if they are, they are likely to be missed by scientists during nest searching. For example, nests could already have failed or fledged before the day scientists collect data, or researchers might not detect an active nest concealed by tall grass.
Distance sampling is the most widely accepted sampling method used to account for imperfect detection in nest density estimation. Distance sampling models usually require observers to record nests from a pre-determined transect line and then estimate detection probability based on the distance from the observer to the nest. They cannot include data from nests found in any other way than a structured survey or account for nests unavailable for detection at the time of the survey.
Péron and his co-authors developed an alternative method in 2014, published in Ecology (http://bit.ly/37Oiivr). Unlike standard distance sampling methods, the time-to-event nest density estimator mathematically accounts for nest availability and is more flexible in the data that can be included. The validation of this new method was limited to its original study species, the blue-winged teal.
Reintsma and her co-authors evaluated the general applicability of the time-to-event estimator in the Passeriformes order, which includes songbirds and more than half of all bird species. They compared estimates of nest detection rates and nest density from the time-to-event estimator to distance sampling methods for 42 Brewer’s sparrow nests monitored in 2015. They found the time-to-event estimator produced similar but more precise density estimates than distance sampling methods.
“Wildlife biologists are always striving to identify and validate efficient new tools to understand and protect wildlife populations,” Reintsma said. “This study is just one example of that sentiment.”
The study, “Validation of a novel time-to-event nest density estimator on passerines: An example using Brewer’s sparrows (Spizella breweri)” was published in the journal PLOS ONE in December. The article is online at https://doi.org/10.1371/journal.pone.0227092.
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