Estimating density of a rare and cryptic high-mountain Galliform species, the Buff-throated Partridge Tetraophasis szechenyii

Estimates of abundance or density are essential for wildlife management and conservation. There are few effective density estimates for the Buff-throated Partridge Tetraophasis szechenyii, a rare and elusive high-mountain Galliform species endemic to western China. In this study, we used the temporary emigration N-mixture model to estimate density of this species, with data acquired from playback point count surveys around a sacred area based on indigenous Tibetan culture of protection of wildlife, in Yajiang County, Sichuan, China, during April–June 2009. Within 84 125-m radius points, we recorded 53 partridge groups during three repeats. The best model indicated that detection probability was described by covariates of vegetation cover type, week of visit, time of day, and weather with weak effects, and a partridge group was present during a sampling period with a constant probability. The abundance component was accounted for by vegetation association. Abundance was substantially higher in rhododendron shrubs, fir-larch forests, mixed spruce-larch-birch forests, and especially oak thickets than in pine forests. The model predicted a density of 5.14 groups/km², which is similar to an estimate of 4.7 – 5.3 groups/km² quantified via an intensive spot-mapping effort. The post-hoc estimate of individual density was 14.44 individuals/km², based on the estimated mean group size of 2.81. We suggest that the method we employed is applicable to estimate densities of Buff-throated Partridges in large areas. Given importance of a mosaic habitat for this species, local logging should be regulated. Despite no effect of the conservation area (sacred) on the abundance of Buff-throated Partridges, we suggest regulations linking the sacred mountain conservation area with the official conservation system because of strong local participation facilitated by sacred mountains in land conservation.

Quantifying avian relative abundance and ecosystem service value to identify conservation opportunities in the Midwestern U.S.

Grassland birds are highly imperiled because of historical habitat loss and ongoing conversion of grasslands to agricultural and urban land uses. Therefore, prioritizing and further justifying conservation action in remaining grasslands is critical to protecting what remains. Grassland bird conservation has focused on identifying and protecting large grassland complexes referred to as Grassland Bird Conservation Areas (GBCAs). We identified and classified GBCAs in a region highly impacted by both agricultural and urban land conversion using previously developed methods. Then, we extended the analysis to include estimated relative abundance of five grassland focal species in each GBCA. Models of relative abundance were built using eight years of monitoring data collected by citizen scientists. Finally, we quantified the value of ecosystem services provided by each GBCA. There were nearly 55,000 ha of grassland habitats in the Chicago Metropolitan Region that met GBCA criteria, 33% (18,415 ha) of which were protected. Proportion of abundance in protected versus unprotected areas was similar for Bobolink (Dolichonyx oryzivorus; 46%), Grasshopper Sparrow (Ammodramus savannarum; 52%), and Sedge Wren (Cistothorus platensis; 48%), whereas, Henslow’s Sparrow (Ammodramus henslowii; 75%) had a higher proportion of relative abundance in protected GBCAs and Eastern Meadowlark (Sturnella magna) had lower proportions (37%). GBCAs provisioned just under $900 million annually in ecosystem services, 73% of which is because of flood control. Outputs of this comprehensive approach will inform grassland bird conservation by providing detailed information about the value for birds and people of grassland habitats.

Detectability of migrating raptors and its effect on bias and precision of trend estimates

Annual counts of migrating raptors at fixed observation points are a widespread practice, and changes in numbers counted over time, adjusted for survey effort, are commonly used as indices of trends in population size. Unmodeled year-to-year variation in detectability may introduce bias, reduce precision of trend estimates, and reduce power to detect trends. We conducted dependent double-observer surveys at the annual fall raptor migration count at Lucky Peak, Idaho, in 2009 and 2010 and applied Huggins closed-capture removal models and information-theoretic model selection to determine the relative importance of factors affecting detectability. The most parsimonious model included effects of observer team identity, distance, species, and day of the season. We then simulated 30 years of counts with heterogeneous individual detectability, a population decline (λ = 0.964), and unexplained random variation in the number of available birds. Imperfect detectability did not bias trend estimation, and increased the time required to achieve 80% power by less than 11%. Results suggested that availability is a greater source of variance in annual counts than detectability; thus, efforts to account for availability would improve the monitoring value of migration counts. According to our models, long-term trends in observer efficiency or migratory flight distance may introduce substantial bias to trend estimates. Estimating detectability with a novel count protocol like our double-observer method is just one potential means of controlling such effects. The traditional approach of modeling the effects of covariates and adjusting the index may also be effective if ancillary data is collected consistently.