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Analyzing the effects on cell growth inhibition and/or cell death has been an important component of biological research. The MTS assay and LDH-based cytotoxicity assays are two of the most commonly used methods for this purpose. However, data here showed that MTS cell proliferation assay could not distinguish the effects of cell death or cell growth inhibition. In addition, the original LDH-based cytotoxicity protocol grossly underestimated the proportion of dead cells in conditions with growth inhibition. To overcome the limitation, we present here a simple modified LDH-based cytotoxicity protocol by adding additional condition-specific controls. This modified protocol thus can provide more accurate measurement of killing effects in addition to the measurement of overall effects, especially in conditions with growth inhibition. In summary, we present here a simple, modified cytotoxicity assay, which can determine the overall effects, percentage of cell killing and growth inhibition in one 96-well based assay. This is a viable option for primary screening for many laboratories, and could be adapted for high throughput screening.

Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn-the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as 'risk from turbines is highest in habitats between hoary bat summering and wintering grounds'. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.

The ability of animals to sync the timing and location of molting (the replacement of hair, skin, exoskeletons or feathers) with peaks in resource availability has important implications for their ecology and evolution. In migratory birds, the timing and location of pre-migratory feather molting, a period when feathers are shed and replaced with newer, more aerodynamic feathers, can vary within and between species. While hypotheses to explain the evolution of intraspecific variation in the timing and location of molt have been proposed, little is known about the genetic basis of this trait or the specific environmental drivers that may result in natural selection for distinct molting phenotypes. Here we take advantage of intraspecific variation in the timing and location of molt in the iconic songbird, the Painted Bunting ( Passerina ciris ) to investigate the genetic and ecological drivers of distinct molting phenotypes. Specifically, we use genome-wide genetic sequencing in combination with stable isotope analysis to determine population genetic structure and molting phenotype across thirteen breeding sites. We then use genome-wide association analysis (GWAS) to identify a suite of genes associated with molting and pair this with gene-environment association analysis (GEA) to investigate potential environmental drivers of genetic variation in this trait. Associations between genetic variation in molt-linked genes and the environment are further tested via targeted SNP genotyping in 25 additional breeding populations across the range. Together, our integrative analysis suggests that molting is in part regulated by genes linked to feather development and structure ( GLI2 and CSPG4 ) and that genetic variation in these genes is associated with seasonal variation in precipitation and aridity. Overall, this work provides important insights into the genetic basis and potential selective forces behind phenotypic variation in what is arguably one of the most important fitness-linked traits in a migratory bird.

Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near‐term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either a uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decrease when the reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near‐term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the near‐term population dynamics of finite populations of plant species. Among fast and slow pace and either a uniform or increasing reproductive intensity or short or long reproductive stage duration, slow, semelparous species are at the greatest risk of extinction. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near‐term extinction risk.

Determining patterns of migratory connectivity for highly-mobile, wide-ranging species, such as sea turtles, is challenging. Here, we combined satellite telemetry and stable isotope analysis to estimate foraging locations for 749 individual loggerheads nesting along the east central Florida (USA) coast, the largest rookery for the Northwest Atlantic population. We aggregated individual results by year, identified seven foraging hotspots and tracked these summaries to describe the dynamics of inter-annual contributions of these geographic areas to this rookery over a nine-year period. Using reproductive information for a subset of turtles (n = 513), we estimated hatchling yields associated with each hotspots. We found considerable inter-annual variability in the relative contribution of foraging areas to the nesting adults. Also reproductive success differed among foraging hotspots; females using southern foraging areas laid nests that produced more offspring in all but one year of the study. These analyses identified two high priority areas for future research and conservation efforts: the continental shelf adjacent to east central Florida and the Great Bahama Bank, which support higher numbers of foraging females that provide higher rates of hatchling production. The implementation of the continuous-surface approach to determine geographic origins of unknown migrants is applicable to other migratory species.

Elucidating geographic locations from where migratory birds are recruited into adult breeding populations is a fundamental but largely elusive goal in conservation biology. This is especially true for species that breed in remote northern areas where field-based demographic assessments are logistically challenging. Here we used hydrogen isotopes (deltaD) to determine natal origins of migrating hatch-year lesser scaup (Aythya affinis) harvested by hunters in the United States from all North American flyways during the hunting seasons of 1999-2000 (n = 412) and 2000-2001 (n = 455). We combined geospatial, observational, and analytical data sources, including known scaup breeding range, deltaD values of feathers from juveniles at natal sites, models of deltaD for growing-season precipitation, and scaup band-recovery data to generate probabilistic natal origin landscapes for individual scaup. We then used Monte Carlo integration to model assignment uncertainty from among individual deltaD variance estimates from birds of known molt origin and also from band-return data summarized at the flyway level. We compared the distribution of scaup natal origin with the distribution of breeding population counts obtained from systematic long-term surveys. Our analysis revealed that the proportion of young scaup produced in the northern (above 60 degrees N) versus the southern boreal and Prairie-Parkland region was inversely related to the proportions of breeding adults using these regions, suggesting that despite having a higher relative abundance of breeding adults, the northern boreal region was less productive for scaup recruitment into the harvest than more southern biomes. Our approach for evaluating population declines of migratory birds (particularly game birds) synthesizes all available distributional data and exploits the advantages of intrinsic isotopic markers that link individuals to geography.

Species distributions depend on fine‐scale ecological processes and population growth trajectories and are influenced by climate and weather changes. However, the characterization of inter‐population dynamics underlying the geographic distributions of migratory organisms remains challenging. We adopted a stable isotope approach to investigate the dynamic population geography of a terrestrial migratory bird across multiple generations. We found that the age‐specific geographic source of Mountain Plovers sampled during winter shifted over four years across a latitudinal gradient. Moreover, our results show that differential effects of climate on the probability of occurrence at the wintering ground could be a driver of population turnover in a migratory species adapted to extreme environmental stochasticity (i.e., drought occurrence). We propose a framework for the identification of spatial and temporal climate and weather components and respective effects on population composition and recruitment into migratory wintering populations. Our approach is useful to reveal population compositional shifts through hydrogen stable isotope analysis while accounting for cumulative drought effects.

Climate change is transforming forest structure and function by altering the timing, frequency, intensity, and spatial extent of episodic disturbances. Wildland fire regimes in western U.S. coniferous forests are now characterized by longer fire seasons and greater frequency, with further changes expected. Identifying the impacts of altered fire regimes on forest resources may enable land managers to plan mitigation strategies or prepare for novel or altered communities. We created a stochastic, density‐dependent, matrix projection model for a whitebark pine (Pinus albicaulis) metapopulation to estimate the impacts of increasing fire frequency on metapopulation persistence. Whitebark pine is a widely distributed foundation species of management concern found in upper subalpine and tree line forests of the Northern Rocky Mountains. We parameterized the model using empirically based demographic data from the Greater Yellowstone Ecosystem (GYE) and validated the model by comparing observed whitebark pine densities to those projected by the model when parameterized with historical demographic rates and fire frequencies. We reparameterized the model with current demographic rates including mortality from insect outbreaks and exotic disease. We compared odds of functional extirpation among six scenarios comprising three altered fire frequencies (fires suppressed, historical fire return interval of 268 yr, and decreasing fire return intervals from current to 97 yr) and two seed dispersal probabilities. Historical parameterization with high dispersal probability projected median whitebark pine densities (40.95 trees/ha, first and third quartiles: 21.89, 67.25), which were similar to empirically estimated densities (40.62 trees/ha, first and third quartiles: 12.04, 114.15). Odds of functional extirpation with increasing fire frequency were 8.26 and 139.91 times higher than historical fire frequency and fire suppression, respectively. In decreasing fire return interval scenarios, odds of functional extirpation were 1.76 times higher in low than high dispersal probability scenarios. These findings suggest that fire suppression may be required to maintain whitebark pine metapopulations in the GYE and that maintaining stand networks connected by high rates of seed dispersal could increase metapopulation resiliency.

Animal‐borne trackers are commonly used to study bird movements, including in long‐distance migrants such as shorebirds. Selecting a tracker and attachment method can be daunting, and methodological advancements often have been made by trial and error and conveyed by word of mouth. We synthesized tracking outcomes across 2745 dorsally mounted trackers on 37 shorebird species around the world. We evaluated how attachment method, power source, data retrieval method, relative tracker mass, and biological traits affected success, where success was defined as whether or not each tag deployment reached its expected tracking duration (i.e. all aspects succeeded for the intended duration of the study: attachment, tracking, data acquisition, and bird survival). We conducted separate analyses for tag deployments with remote data retrieval (‘remote‐upload tag deployments') and those that archived data and had to be recovered (‘archival tag deployments'). Among remote‐upload tag deployments, those that were a lighter mass relative to the bird, were beyond their first year of production, transmitted data via satellite, or were attached with a leg‐loop harness were most often successful at reaching their expected tracking duration. Archival tag deployments were most successful when applied at breeding areas, or when applied to males in any season. Remote‐upload tag deployments with solar power, satellite data retrieval, or leg‐loop harnesses continued tracking for longer than those with battery power, other types of data retrieval, or glue attachments. However, the majority of tag deployments failed to reach their expected tracking duration (71% of remote‐upload, 83% of archival), which could have been due to tracker failure, attachment failure, or bird mortality. Our findings highlight that many tag deployments may fail to meet the goals of a study if tracking duration is crucial. Using our results, we provide guidelines for selecting a tracker and attachment to improve success at meeting study goals.

Clark's nutcrackers (Nucifraga columbiana) are obligate seed dispersers for whitebark pine (Pinus albicaulis), but they frequently use other conifer seed resources because of annual variability in cone production or geographic variation in whitebark pine availability. Whitebark pine is declining from several threats including white pine blister rust, leading to potential population declines in the nutcracker and the pine. We hypothesize that where there are few additional seed resources, whitebark pine becomes the key and limiting resource supporting nutcracker populations. We investigated how nutcrackers use coniferous forest community types within Yellowstone National Park to determine potential seed resources and the importance of whitebark pine. We established sites representing five forest community types, including whitebark pine, lodgepole pine (P. contorta), Engelmann spruce (Picea engelmannii), limber pine (P. flexilis), and Douglas‐fir (Pseudotsuga menziesii). Each transect annually generated nutcracker point counts, conifer cone production indices, community composition data, and seed resource use observations. We compared hierarchical distance sampling models, estimating nutcracker density and its relationship to forest community type, seed harvesting time‐period, year, study site, and cone seed energy. We found cone production varied across years indicating annual variability in energy availability. Nutcracker density was best predicted by forest community type and survey time‐period and was highest in whitebark pine stands during the mid‐harvesting season. Nutcracker density was comparatively low for all other forest community types. This finding underscores the importance of whitebark pine as a key seed resource for Clark's nutcracker in Yellowstone National Park. The decline of whitebark pine potentially leads to a downward spiral in nutcrackers and whitebark pine, arguing for continued monitoring of nutcrackers and implementation of restoration treatments for whitebark pine. The coevolved mutualism between whitebark pine (Pinus albicaulis) and Clark's nutcracker (Nucifraga columbiana) is well documented, but our understanding of nutcracker use of additional conifer seed resources is lacking. Data collected over 3 years in Yellowstone National Park suggest that whitebark pine was the only seed resource that nutcrackers visited regularly and that bird density was highest during mid‐September when whitebark pine seeds ripen. In areas without additional seed resources to sustain populations of nutcrackers, we hypothesize that Clark's nutcracker populations may be more directly linked to whitebark pine seed production.