Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

BACKGROUND: Conserving animal populations in places where human activity is increasing is an ongoing challenge in many parts of the world. We investigated how human activity interacted with maternal status and individual variation in behavior to affect reliability of spatially-explicit models intended to guide conservation of critical ungulate calving resources. We studied Rocky Mountain elk (Cervus elaphus) that occupy a region where 2900 natural gas wells have been drilled. METHODOLOGY/PRINCIPAL FINDINGS: We present novel applications of generalized additive modeling to predict maternal status based on movement, and of random-effects resource selection models to provide population and individual-based inference on the effects of maternal status and human activity. We used a 2×2 factorial design (treatment vs. control) that included elk that were either parturient or non-parturient and in areas either with or without industrial development. Generalized additive models predicted maternal status (parturiency) correctly 93% of the time based on movement. Human activity played a larger role than maternal status in shaping resource use; elk showed strong spatiotemporal patterns of selection or avoidance and marked individual variation in developed areas, but no such pattern in undeveloped areas. This difference had direct consequences for landscape-level conservation planning. When relative probability of use was calculated across the study area, there was disparity throughout 72-88% of the landscape in terms of where conservation intervention should be prioritized depending on whether models were based on behavior in developed areas or undeveloped areas. Model validation showed that models based on behavior in developed areas had poor predictive accuracy, whereas the model based on behavior in undeveloped areas had high predictive accuracy. CONCLUSIONS/SIGNIFICANCE: By directly testing for differences between developed and undeveloped areas, and by modeling resource selection in a random-effects framework that provided individual-based inference, we conclude that: 1) amplified selection or avoidance behavior and individual variation, as responses to increasing human activity, complicate conservation planning in multiple-use landscapes, and 2) resource selection behavior in places where human activity is predictable or less dynamic may provide a more reliable basis from which to prioritize conservation action

Total Organic Carbon and the Contribution From Speciated Organics in Cloud Water: Airborne Data Analysis From the CAMP2Ex Field Campaign

This work focuses on total organic carbon (TOC) and contributing species in cloud water over Southeast Asia using a rare airborne dataset collected during NASA’s Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex), in which a wide variety of maritime clouds were studied, including cumulus congestus, altocumulus, altostratus, and cumulus. Knowledge of TOC masses and their contributing species is needed for improved modeling of cloud processing of organics and to understand how aerosols and gases impact and are impacted by clouds. This work relies on 159 samples collected with an axial cyclone cloudwater collector at altitudes of 0.2–6.8 km that had sufficient volume for both TOC and speciated organic composition analysis. Species included monocarboxylic acids (glycolate, acetate, formate, and pyruvate), dicarboxylic acids (glutarate, adipate, succinate, maleate, and oxalate), methanesulfonic acid (MSA), and dimethylamine (DMA). TOC values range between 0.018 and 13.66 ppm C with a mean of 0.902 ppm C. The highest TOC values are observed below 2 km with a general reduction aloft. An exception is samples impacted by biomass burning for which TOC remains enhanced at altitudes as high as 6.5 km (7.048 ppm C). Estimated total organic matter derived from TOC contributes a mean of 30.7 % to total measured mass (inorganics + organics). Speciated organics contribute (on a carbon mass basis) an average of 30.0 % to TOC in the study region and account for an average of 10.3 % to total measured mass. The order of the average contribution of species to TOC, in decreasing contribution of carbon mass, is as follows (±1 standard deviation): acetate (14.7 ± 20.5 %), formate (5.4 ± 9.3 %), oxalate (2.8 ± 4.3 %), DMA (1.7 ± 6.3 %), succinate (1.6 ± 2.4 %), pyruvate (1.3 ± 4.5 %), glycolate (1.3 ± 3.7 %), adipate (1.0 ± 3.6 %), MSA (0.1 ± 0.1 %), glutarate (0.1 ± 0.2 %), and maleate (\u3c 0.1 ± 0.1 %). Approximately 70 % of TOC remains unaccounted for, highlighting the complex nature of organics in the study region; in samples collected in biomass burning plumes, up to 95.6 % of TOC mass is unaccounted for based on the species detected. Consistent with other regions, monocarboxylic acids dominate the speciated organic mass (∼ 75 %) and are about 4 times more abundant than dicarboxylic acids. Samples are categorized into four cases based on backtrajectory history, revealing source-independent similarity between the bulk contributions of monocarboxylic and dicarboxylic acids to TOC (16.03 %–23.66 % and 3.70 %–8.75 %, respectively). Furthermore, acetate, formate, succinate, glutarate, pyruvate, oxalate, and MSA are especially enhanced during biomass burning periods, which is attributed to peat emissions transported from Sumatra and Borneo. Lastly, dust (Ca2+) and sea salt (Na+/Cl−) tracers exhibit strong correlations with speciated organics, supporting how coarse aerosol surfaces interact with these water-soluble organics

Identifying and Prioritizing Greater Sage-Grouse Nesting and Brood-Rearing Habitat for Conservation in Human-Modified Landscapes

BACKGROUND: Balancing animal conservation and human use of the landscape is an ongoing scientific and practical challenge throughout the world. We investigated reproductive success in female greater sage-grouse (Centrocercus urophasianus) relative to seasonal patterns of resource selection, with the larger goal of developing a spatially-explicit framework for managing human activity and sage-grouse conservation at the landscape level. METHODOLOGY/PRINCIPAL FINDINGS: We integrated field-observation, Global Positioning Systems telemetry, and statistical modeling to quantify the spatial pattern of occurrence and risk during nesting and brood-rearing. We linked occurrence and risk models to provide spatially-explicit indices of habitat-performance relationships. As part of the analysis, we offer novel biological information on resource selection during egg-laying, incubation, and night. The spatial pattern of occurrence during all reproductive phases was driven largely by selection or avoidance of terrain features and vegetation, with little variation explained by anthropogenic features. Specifically, sage-grouse consistently avoided rough terrain, selected for moderate shrub cover at the patch level (within 90 m(2)), and selected for mesic habitat in mid and late brood-rearing phases. In contrast, risk of nest and brood failure was structured by proximity to anthropogenic features including natural gas wells and human-created mesic areas, as well as vegetation features such as shrub cover. CONCLUSIONS/SIGNIFICANCE: Risk in this and perhaps other human-modified landscapes is a top-down (i.e., human-mediated) process that would most effectively be minimized by developing a better understanding of specific mechanisms (e.g., predator subsidization) driving observed patterns, and using habitat-performance indices such as those developed herein for spatially-explicit guidance of conservation intervention. Working under the hypothesis that industrial activity structures risk by enhancing predator abundance or effectiveness, we offer specific recommendations for maintaining high-performance habitat and reducing low-performance habitat, particularly relative to the nesting phase, by managing key high-risk anthropogenic features such as industrial infrastructure and water developments

Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Winter Resource Selection by Mule Deer on the Wyoming-Colorado Border Prior to Wind Energy Development

Areas identified as winter range are important seasonal habitats for mule deer (Odocoileus hemionus) because they can moderate overwinter mortality by providing thermal cover and forage. Therefore, identifying seasonally important resources is a conservation priority, especially when sensitive areas are proposed for development. We used data collected from global positioning system (GPS) collars fitted on female mule deer (n=19; one location every 3 h) to identify resources important during winter (23 February 2011-30 April 2011; 1 November 2011-15 January 2012) in a region spanning southern Wyoming and northern Colorado that has been proposed for wind energy development. The study period included portions of two consecutive winters but were pooled for analysis. We used methods to account for GPS biases, fractal analyses to determine perceived spatial scale, and discrete choice models and conditional logistic regression to assess resource selection prior to development (i.e., baseline data). Resource selection by female mule deer revealed similar patterns between active (0600-1800 hours) and nonactive (2100-0300 hours) periods. Deer selected most strongly for proximity to rock outcrops and shrubland and average values of slope. Deer tended to avoid roads and grasslands; all other landscape features had minimal influence on resource selection (hazard ratios near, or overlapping, 1). Using the fixed-effects coefficient estimates, we developed two spatially explicit maps that depicted probability of mule deer occurrence across the landscape. Based on an independent validation sample, each map (active and nonactive) validated well with a greater percentage of locations occurring in the two highest probability of use bins. These maps offer guidance to managing mule deer populations, conserving important seasonal habitats, and mitigating development (e.g., wind energy) in areas identified as important to mule deer.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202

Winter Resource Selection by Mule Deer on the Wyoming–Colorado Border Prior to Wind Energy Development

Areas identified as winter range are important seasonal habitats for mule deer (Odocoileus hemionus) because they can moderate overwinter mortality by providing thermal cover and forage. Therefore, identifying seasonally important resources is a conservation priority, especially when sensitive areas are proposed for development. We used data collected from global positioning system (GPS) collars fitted on female mule deer (n=19; one location every 3 h) to identify resources important during winter (23 February 2011-30 April 2011; 1 November 2011-15 January 2012) in a region spanning southern Wyoming and northern Colorado that has been proposed for wind energy development. The study period included portions of two consecutive winters but were pooled for analysis. We used methods to account for GPS biases, fractal analyses to determine perceived spatial scale, and discrete choice models and conditional logistic regression to assess resource selection prior to development (i.e., baseline data). Resource selection by female mule deer revealed similar patterns between active (0600-1800 hours) and nonactive (2100-0300 hours) periods. Deer selected most strongly for proximity to rock outcrops and shrubland and average values of slope. Deer tended to avoid roads and grasslands; all other landscape features had minimal influence on resource selection (hazard ratios near, or overlapping, 1). Using the fixed-effects coefficient estimates, we developed two spatially explicit maps that depicted probability of mule deer occurrence across the landscape. Based on an independent validation sample, each map (active and nonactive) validated well with a greater percentage of locations occurring in the two highest probability of use bins. These maps offer guidance to managing mule deer populations, conserving important seasonal habitats, and mitigating development (e.g., wind energy) in areas identified as important to mule deer.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202

Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus.

Like many viruses, Hepatitis C Virus (HCV) has a high mutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly useful to estimate in vivo fitness costs, but this approach works best with deep sequencing data from many hosts are. In this study, we applied the frequency-based approach to a large dataset of 195 patients and estimated the fitness costs of mutations at 7957 sites along the HCV genome. We used beta regression and random forest models to better understand how different factors influenced fitness costs. Our results revealed that costs of nonsynonymous mutations were three times higher than those of synonymous mutations, and mutations at nucleotides A or T had higher costs than those at C or G. Genome location had a modest effect, with lower costs for mutations in HVR1 and higher costs for mutations in Core and NS5B. Resistance mutations were, on average, costlier than other mutations. Our results show that in vivo fitness costs of mutations can be site and virus specific, reinforcing the utility of constructing in vivo fitness cost maps of viral genomes

Greater Sage-Grouse and Severe Winter Conditions: Identifying Habitat for Conservation

Developing sustainable rangeland management strategies requires solution-driven research that addresses ecological issues within the context of regionally important socioeconomic concerns. A key sustainability issue in many regions of the world is conserving habitat that buffers animal populations from climatic variability, including seasonal deviation from long-term precipitation or temperature averages, and that can establish an ecological bottleneck by which the landscape-level availability of critical resources becomes limited. We integrated methods to collect landscape-level animal occurrence data during severe winter conditions with estimation and validation of a resource selection function, with the larger goal of developing spatially explicit guidance for rangeland habitat conservation. The investigation involved greater sage-grouse (Centrocercusurophasianus) that occupy a landscape that is undergoing human modification for development of energy resources. We refined spatial predictions by exploring how reductions in the availability of sagebrush (as a consequence of increasing snow depth) may affect patterns of predicted occurrence. Occurrence of sage-grouse reflected landscape-level selection for big sagebrush, taller shrubs, and favorable thermal conditions and avoidance of bare ground and anthropogenic features. Refinement of spatial predictions showed that important severe winter habitat was distributed patchily and was constrained in spatial extent (7-18% of the landscape). The mapping tools we developed offer spatially explicit guidance for planning human activity in ways that are compatible with sustaining habitat that functions disproportionately in population persistence relative to its spatial extent or frequency of use. Increasingly, place-based, quantitative investigations that aim to develop solutions to landscape sustainability issues will be needed to keep pace with human-modification of rangeland and uncertainty associated with global climate change and its effects on animal populations.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202