Description: The expansion of coniferous trees into sagebrush ecosystems is a major driver of habitat loss and fragmentation, resulting in negative impacts to wildlife. Greater sage-grouse ( Centrocercus urophasianus ) respond directly to conifer expansion through decreased breeding activity, nesting, and overall survival; thus, small amounts of conifer expansion can have significant impacts on sage-grouse habitat and populations. To this end, conservation partners have collaborated across private and public lands to reduce the threat of conifer expansion through targeted removal of conifer trees. Here, we demonstrate the use of the Marxan framework to incorporate important ecosystem attributes in the prioritization of conifer removal within the Oregon range of sage-grouse. We prioritized conifer removal relative to three separate goals: (1) enhancement of existing sage-grouse breeding, nesting, and early brood-rearing habitats; (2) facilitation of sage-grouse movement between breeding and brood-rearing habitats; and (3) improvement of connectivity among sage-grouse priority areas for conservation (PACs). Optimization models successfully identified areas with low conifer canopy cover, high resilience and resistance to wildfire and annual grass invasion, and high bird abundance to enhance sage-grouse habitat. The inclusion of mesic resources resulted in further prioritization of areas that were closer to such resources, but also identified potential pathways that connected breeding habitats to the late brood-rearing habitats associated with mesic areas. Examining areas outside of PACs resulted in the selection of potential corridors to facilitate connectivity; although areas with low conifer cover were selected similarly to the other optimization models, areas with high cover were also chosen to be able to enhance connectivity. Areas identified by optimization models were largely consistent with and overlapped ongoing conifer removal efforts in the Warner Mountains of south-central Oregon. Land ownership of preferential areas selected by models varied with priority goals and followed general ownership patterns of the region, with public lands managed by the Bureau of Land Management and private lands being selected the most. The increased availability of landscape-level datasets and assessment tools in sagebrush ecosystems can reduce the time and cost of both planning and implementation of habitat projects involving conifer removal. Most importantly, incorporating these new datasets and tools can supplement expert-based knowledge to maximize benefits to sagebrush and sage-grouse conservation.

Description: Single particle mass spectral data, collected in Paris, France during the MEGAPOLI winter campaign, have been used to predict hygroscopic growth at the single particle level. The mass fractions of black carbon, organic aerosol, ammonium, nitrate and sulphate present in each particle were estimated using a combination of single particle mass spectrometer and bulk aerosol chemical composition measurements. The Zdanovskii-Stokes-Robinson (ZSR) approach was then applied to predict hygroscopic growth factors based on these mass fraction estimates. Smaller particles with high black carbon mass fractions and low inorganic ion mass fractions exhibited the lowest predicted growth factors, while larger particles with high inorganic ion mass fractions exhibited the highest growth factors. Growth factors were calculated for subsaturated relative humidity (90%) to enable comparison with hygroscopic tandem differential mobility analyser (HTDMA) measurements. Mean predicted and measured hygroscopic growth factors for 110, 165 and 265 nm particles were found to agree within 6%. Single particle-based ZSR hygroscopicity estimates offer an advantage over bulk aerosol composition-based hygroscopicity estimates by providing additional chemical mixing state information. External mixing can be determined for particles of a given diameter through examination of the predicted hygroscopic growth factor distributions. 110 nm and 265 nm particles were found to be predominantly internally mixed using this approach, however external mixing of 165 nm particles was observed periodically when thinly coated and thickly coated BC particles were simultaneously detected. Single particle-resolved chemical information will be useful for modelling efforts aimed at constraining cloud condensation nuclei activity and hygroscopic growth.