Comparing telemetry and fecal dna sampling methods to quantify survival and dispersal of juvenile pygmy rabbits

Abstract

Age-specific life-history data are needed to understand animal ecology and inform conservation strategies. We compared telemetry and noninvasive genetic sampling (NGS) as methods for monitoring survival and dispersal of juvenile pygmy rabbits (Brachylagus idahoensis) reintroduced to central Washington, USA. During summer 2012, we released 104 juvenile rabbits, 85 of which were fitted with glue-on radiotransmitters and located 2-4 times/week while transmitters were retained ( x ¼ 15 days). We tracked and recovered 63 transmitters, while signals were lost from 22. Most rabbits remained near the release site, with 9 dispersing > 1 km, and only 2 moving >3 km. During winter, we surveyed nearly 9 km 2 around the release site and collected 117 fecal samples for genetic analysis. Forty-two individuals were identified, 38 from the summer releases (37% survival) and 4 born in the wild from parents released in 2011. Using NGS, we identified rabbits 1) released without transmitters, 2) with undetected transmitter signals, 3) presumed dead, and 4) produced in the wild. Short-term dispersal behavior was best gathered with telemetry, but information was limited, and we were unable to estimate survival probabilities because of the short duration of transmitter retention. The information on dispersal, survival, and reproduction provided by NGS allowed us to evaluate longer term reintroduction success, but was limited by the area we were able to search. We compare the results, costs, benefits, and limitations of each method for addressing specific monitoring objectives.

Costs and Precision of Fecal DNA Mark–Recapture versus Traditional Mark–Resight

“…Previous studies have demonstrated the ability of fecal DNA capture–recapture to provide abundance and density estimates when applied to wild ungulate populations (Brinkman et al 2011, Goode et al 2014, Lounsberry et al 2015, Woodruff et al 2016, Furnas et al 2018). However, few studies have evaluated the cost‐effectiveness (i.e., cost per level of precision) of this method when compared with traditional methods of estimating abundance (Janecka et al 2011, Poole et al 2011, DeMay et al 2015). We had the opportunity to compare both methods and their associated costs and precision.…”

Consequences for conservation: population density and genetic effects on reproduction of an endangered lagomorph

“…Due to the recent mixing of multiple populations, loci were not expected to be in Hardy–Weinberg or linkage equilibrium across the entire recovery population, but separate analyses of two source populations indicated that loci were in equilibrium (DeMay et al. ). We assigned parentage using a strict exclusion approach using Cervus 3.0 (Marshall et al.…”

“…We generated microsatellite genotypes in duplicate from each tissue sample at 19 microsatellite loci, including a sex identification locus, following the methods of DeMay et al (2015). Due to the recent mixing of multiple populations, loci were not expected to be in Hardy-Weinberg or linkage equilibrium across the entire recovery population, but separate analyses of two source populations indicated that loci were in equilibrium (DeMay et al 2015). We assigned parentage using a strict exclusion approach using Cervus 3.0 (Marshall et al 1998, Kalinowski et al 2007).…”

Contrasting dispersal inference methods for the greater white-toothed shrew

“…Our results have important implications for conservation, where the evaluation of long‐term reintroduction success, the estimation of immigration rates, and distances in fragmented habitats are paramount to the management of threatened species. Direct methods, such as mark‐recapture and telemetry (Demay et al ), show some limitations to infer dispersal (e.g., transmitter retention times, signal detection, confirmation of mortality), whereas genetic‐based approaches not only perform better but also allow individuals to be detected throughout their life so that long‐term study questions about survival, reproduction, movement, and genetic diversity can be investigated. Our data further indicate the species studied and spatial scale considered will dictate which method is best suited to estimate dispersal.…”

“…These data contribute to policy on ecosystem resilience, conservation strategies, and environmental management in a time where many habitats are fragmented, or under threat of destruction, and where climate change will force species to move with their climate niche if they are unable to adapt (Simberloff , Kokko and Lopez‐Sepulcre , Nathan et al ). Beyond general patterns at the species level, details of dispersal polymorphism within a species (e.g., rare, long‐distance dispersal events or differences in the dispersal ability of the sexes) are also relevant to evolutionary or conservation biology (Aars and Ims , Nathan ) where evaluating the long‐term success of reintroduction is critical for the management of threatened species (Demay et al ).…”