Marbled Murrelet nest site selection at three fine spatial scales

We implemented a unique tree-climbing effort to examine nesting-habitat selection of Marbled Murrelets (Brachyramphus marmoratus) in managed forest stands of Washington and Oregon during 1996-1999. Researchers climbed over 3000 trees to search for old and active murrelet nests during the breeding season (May-Sept.) in a random sample of stands known to be occupied by murrelets. Within these stands, characteristics of murrelet nest sites and non-nest sites were measured at three fine spatial scales: nest limb or platform, nest tree, and nest-site or forest patch (0.5 ha). We report results of a Bayesian hierarchical logistic regression model using three covariates at each of the three fine spatial scales. All three branch/platform scale covariates positively predicted nest occupancy with higher probabilities of nesting occurring at branches/platforms with higher horizontal cover, larger platform diameters, and higher moss cover. Tree scale characteristics associated with higher probabilities of nesting included higher platform counts and higher moss depth. Effect of tree diameter on probability of nesting was unclear. At the patch scale, lower probability of nesting occurred for stands with higher densities of trees with platforms. This unexpected relationship may be due in part to decreasing likelihood of observing a nest on a given platform when there are more platforms in a patch. Variation in tree size and percent canopy cover at the patch scale showed no clear association with nest selection at the patch scale. The prevalence of nests in Dwarf Mistletoe-infected hemlock trees may have partially obfuscated the effect of tree diameter on probability of encountering a nest in portions of our study area. Fine scale conservation efforts for Marbled Murrelets may include recruiting or retaining trees with larger numbers of platforms, large branches with high percentages of moss cover and horizontal cover, and younger trees with platforms created by Dwarf Mistletoe deformities

DataS2

Douglas-fir dat

DataS3

Camera trap dat

DataS1

Plant community dat

Black-backed Woodpecker occupancy is extensive in green conifer forests of the southern Cascade Mountains, Oregon

Black-backed Woodpeckers (Picoides arcticus) are widely considered a burned forest specialist across much of their range. Several recent studies have examined their occurrence in "green" coniferous forests that have not been recently burned, but Black-backed Woodpecker occupancy and factors influencing occupancy in these forest types remain largely unexamined. We worked on the east slope of the southern Oregon Cascade Mountains and used playback call surveys with repeated visits to 90 transects in 2014 and 2015 to estimate occupancy probabilities by forest type while controlling for detection probability. We detected Black-backed Woodpeckers on 86% of survey transects in green forests composed primarily of mixed conifer, lodgepole pine (Pinus contorta), or ponderosa pine (P. ponderosa). We examined associations between occupancy probability and structural covariates in unburned forests, and found that occupancy did not vary with annual precipitation, large snag density, or snag basal area. Modeled mean occupancy across all transects was 0.87 (95% CI: 0.78-0.93). Detection probability varied during each survey season, with transect-level detection probability reaching a maximum of 0.79 (95% CI: 0.70-0.85) in mid-June. Given high occupancy of green forests by Black-backed Woodpecker in our study area, we suggest that additional study of vital rates in green forests is critical for supporting conservation and management decisions for this species

Number of individuals captured for each of 21 small mammal species captured >1 time in 50 clearcut treatment stands with retention and nine rotation-aged forests, northwest Oregon and southwest Washington, USA, 2017–2019.

(DOCX)</p

Code used to fit community occupancy model in JAGS to small mammal detection data and create Fig 4.

Results of goodness-of-fit test and plot of percent confidence in species detection. (DOCX)</p