Plot-level photography is an attractive time-saving alternative to field measurements for vegetation monitoring. However, widespread adoption of this technique relies on efficient workflows for post-processing images and the accuracy of the resulting products. Here, we estimated relative vegetation cover using both traditional field sampling methods (point frame) and semi-automated classification of photographs (plot-level photography) across thirty 1 m² plots near Utqiaġvik, Alaska, from 2012 to 2021. Geographic object-based image analysis (GEOBIA) was applied to generate objects based on the three spectral bands (red, green, and blue) of the images. Five machine learning algorithms were then applied to classify the objects into vegetation groups, and random forest performed best (60.5% overall accuracy). Objects were reliably classified into the following classes: bryophytes, forbs, graminoids, litter, shadows, and standing dead. Deciduous shrubs and lichens were not reliably classified. Multinomial regression models were used to gauge if the cover estimates from plot-level photography could accurately predict the cover estimates from the point frame across space or time. Plot-level photography yielded useful estimates of vegetation cover for graminoids. However, the predictive performance varied both by vegetation class and whether it was being used to predict cover in new locations or change over time in previously sampled plots. These results suggest that plot-level photography may maximize the efficient use of time, funding, and available technology to monitor vegetation cover in the Arctic, but the accuracy of current semi-automated image analysis is not sufficient to detect small changes in cover.

Coastal sand dunes are dynamic ecosystems with elevated levels of disturbance and are highly susceptible to plant invasions. One invasive plant that is of concern to the Great Lakes system is Gypsophila paniculata L. (perennial baby’s breath). The presence of G. paniculata negatively impacts native species and has the potential to alter ecosystem dynamics. Our research goals were to (1) estimate the genetic structure of invasive G. paniculata along the Michigan dune system and (2) identify landscape features that influence gene flow in this area. We analyzed 12 populations at 14 nuclear and two chloroplast microsatellite loci. We found strong genetic structure among populations (global F_ST = 0.228), and pairwise comparisons among all populations yielded significant F_ST values. Results from clustering analysis via STRUCTURE and discriminant analysis of principal components (DAPC) suggest two main genetic clusters that are separated by the Leelanau Peninsula, and this is supported by the distribution of chloroplast haplotypes. Land cover and topography better explained pairwise genetic distances than geographic distance alone, suggesting that these factors influence the genetic distribution of populations within the dunes system. Together, these data aid in our understanding of how invasive populations move through the dune landscape, providing valuable information for managing the spread of this species.

In the West Gulf Coastal Plains (WGCP) northern bobwhite (Colinus virginianus) are declining faster than range-wide averages and such declines have been linked to the consequences of land management. Management for the endangered red-cockaded woodpecker (Picoides borealis) has benefitted northern bobwhite by restoring mature pine-grassland ecosystems in some areas of the region. However, at Felsenthal National Wildlife Refuge, Crossett, Arkansas, USA, the bobwhite population was not increasing despite the availability of seemingly suitable habitat from management for the endangered species. To understand factors that may be affecting bobwhite survival on Felsenthal National Wildlife Refuge we conducted a telemetry study and assessed summer survival, brood survival, and nest success from 1 April– 11 August in 2013 and 1 April– 15 August in 2014. We also calculated home-range sizes and measured microhabitat characteristics around nests. Summer survival rates were 71% (SE = 0.17) and 47% (SE = 0.14); while nest success was 47% (SE = 0.02) and 100% for 2013 and 2014, respectively. Between years, both 95% and 50% kernel home-ranges were not different (pooled, 63.92±6.07 ha and 14.94±1.75 ha); however minimum convex polygon home-range sizes were (113.8 ± 20.1 ha in 2013; and 393.1 ± 49.0 ha in 2014, P < 0.001). Only numerical differences in microhabitat vegetation characteristics of nest sites and non- nest sites were observed. We suggest management for red-cockaded woodpeckers supports bobwhite populations but only as a buffer against more severe declines. Since bobwhites are declining range-wide, we believe areas federally managed for red-cockaded woodpeckers will become increasingly more important for sustaining regional bobwhite population levels.