Moose calf detection probabilities: quantification and evaluation of a ground-based survey technique

Abstract

Survey data improve population management, yet those data often have associated bias. We quantified one source of bias in moose survey data (observer detection probability, p), by using repeated ground‐observations of calves‐at‐heel of radio‐collared moose in Colorado, USA. Detection probabilities, which varied both spatially and temporally, were estimated using an occupancy‐modelling framework. We provide an efficient offset for modelled calf‐at‐heel occupancy (ψ) estimates that accommodates summer calf mortality. Detection probabilities were most efficiently modelled with seasonal variation, with the lowest probability of detecting calves‐at‐heel occurring during parturition (i.e. May) and later autumn periods (after August). Our most efficiently modelled detection probability estimate for summer was 0.80 (SE = 0.05). During the four years of this study, ψ estimates ranged from 0.54–0.84 (SE = 0.08–0.11). Accounting for 91.7% monthly calf survival corrected ψ estimates downward (ψ = 0.42–0.65). Our results suggest that repeated ground‐based observations of individual cow moose, during summer months, can be can a cost‐effective strategy for estimating a productivity parameter for moose. Ground survey results can be further improved by accounting for calf mortality.

Effects of willow nutrition and morphology on calving success of moose

“…That said, these data can still provide valuable information when used to evaluate calving success (i.e., the probability of female moose having a calf‐at‐heel). The general trends in (Figure 3) align closely with Bergman et al (2020 b ) who evaluated 4 years of data and did not differentiate between populations. Of note, when compared to previously reported estimates of , the decrease in 2017 can largely be ascribed to a single population (North Park) rather than a decrease in across both populations.…”

“…We estimated the proportion of female moose with a calf for each year using multiple repeated observations of calf presence using an occupancy model as described by Bergman et al (2020 b ). An occupancy model framework uses a flexible model structure and enables estimation of occupancy () while accounting for imperfect detection ().…”

“…American black bears ( Ursus americanus ), mountain lions ( Puma concolor ), and coyotes ( Canus latrans ) were present in both sites, whereas wolves ( Canis lupus ) and grizzly bears ( Ursus arctos ) were absent. Black bears and mountain lions infrequently predated upon moose, resulting in minimal predation pressure (Bergman et al 2020 b ).…”

Robust Algorithms for Drone-Assisted Monitoring of Big Animals in Harsh Conditions of Siberian Winter Forests: Recovery of European elk (Alces alces) in Salair Mountains

“…Animal surveys contribute to the rational conservation of biodiversity. A proper analysis of statistics on migration, fertility and mortality can reveal cases of poaching and assess its real scale [ 3 , 4 , 6 , 10 , 11 , 14 ]. A competent approach provides basic data for informed managerial decisions on the matters of animal population as an integral part of national wealth [ 15 , 16 , 17 , 18 , 19 ].…”

“…Animal survey is an important control factor that helps to balance socio-economic and natural interests. The existing methods are based on direct counting or indirect evidence, e.g., footprints, feces, etc., as their results often prove unreliable [ 10 , 14 , 17 , 20 , 21 ]. Based on old databases, these methods are expensive and time-consuming [ 22 ].…”