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Unprecedented conservation efforts for sagebrush (Artemisia spp.) ecosystems across the western United States have been catalyzed by risks from escalated wildfire activity that reduces habitat for sagebrush-obligate species such as Greater Sage-Grouse (Centrocercus urophasianus). However, post-fire restoration is challenged by spatial variation in ecosystem processes influencing resilience to disturbance and resistance to non-native invasive species, and spatial and temporal lags between slower sagebrush recovery processes and faster demographic responses of sage-grouse to loss of important habitat. Decision-support frameworks that account for these factors can help users strategically apply restoration efforts by predicting short and long-term ecological benefits of actions. Here, we developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit sage-grouse populations through time. Specifically, we estimated sagebrush recovery following wildfire and risk of non-native annual grass invasion under four scenarios: passive recovery, grazing exclusion, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration scenario and measured changes in habitat. Application of this framework coupled with strategic planting designs aimed at developing patches of nesting habitat may help increase operational resilience for fire-impacted sagebrush ecosystems.

Resource managers and scientists across western U.S. agencies seek methodologies for identifying environmental attributes important to both wildlife conservation and broad-scale land stewardship. The Greater Sage-Grouse (Centrocercus urophasianus; hereafter, sage-grouse) exemplifies a species in need of this broad-scale approach given widespread population declines that have resulted from loss and degradation of habitat from natural and anthropogenic disturbances. These include agricultural land conversion, conifer expansion, energy development, and wildfire coupled with ecological conversion by invasive plants such as cheatgrass (Bromus tectorum). Development of habitat assessments and conservation actions for sage-grouse benefit from studies that link demographic responses to habitat selection patterns. To address this, we examined nest survival of sage-grouse in relation to fine-scale habitat patterns (i.e., field-based habitat measurements) that influenced nest site selection, using data from nests of telemetered females at 17 sites over 6 years in Nevada and northeastern California, USA. Importantly, sites spanned mesic and xeric average precipitation conditions that contributed substantially to vegetation community structure across cold desert ecosystems of the North American Great Basin. Vegetative cover immediately surrounding sage-grouse nests was important for both nest site selection and nest survival, but responses varied between mesic and xeric sites. For example, while taller perennial grasses were selected at xeric sites, we found no evidence of selection for perennial grass at mesic sites, indicating a functional response to availability of habitat features between hydrographic regions. Furthermore, perennial grass height and forb height both had positive effects on nest survival at xeric sites, but we found varying effects at mesic sites. We emphasize that precipitation conditions driving ecosystem productivity vary regionally among sagebrush communities, shaping vegetation structure and suitable habitat conditions for nesting sage-grouse.

Human enterprise has led to large‐scale changes in landscapes and altered wildlife population distribution and abundance, necessitating efficient and effective conservation strategies for impacted species. Greater sage‐grouse (Centrocercus urophasianus; hereafter sage‐grouse) are a widespread sagebrush (Artemisia spp.) obligate species that has experienced population declines since the mid‐1900s resulting from habitat loss and expansion of anthropogenic features into sagebrush ecosystems. Habitat loss is especially evident in North Dakota, USA, on the northeastern fringe of sage‐grouse’ distribution, where a remnant population remains despite recent development of energy‐related infrastructure. Resource managers in this region have determined a need to augment sage‐grouse populations using translocation techniques that can be important management tools for countering species decline from range contraction. Although translocations are a common tool for wildlife management, very little research has evaluated habitat following translocation, to track individual behaviors such as habitat selection and fidelity to the release site, which can help inform habitat requirements to guide selection of future release sites. We provide an example where locations from previously released radio‐marked sage‐grouse are used in a resource selection function framework to evaluate habitat selection following translocation and identify areas of seasonal habitat to inform habitat management and potential restoration needs. We also evaluated possible changes in seasonal habitat since the late 1980s using spatial data provided by the Rangeland Analysis Platform coupled with resource selection modeling results. Our results serve as critical baseline information for habitat used by translocated individuals across life stages in this study area, and will inform future evaluations of population performance and potential for long‐term recovery., Decades of human enterprise have impacted populations of greater sage‐grouse (Centrocercus urophasianus) in the western United States. Although translocation is a viable management option to restore populations in areas where habitat has recovered, quantitative planning tools are needed to promote success of restoration efforts. We developed seasonal resource selection models for translocated sage‐grouse and evaluated habitat changes since the late 1980s to help guide future translocation decisions that will benefit population recovery.

Globally accelerating frequency and extent of wildfire threatens the persistence of specialist wildlife species through direct loss of habitat and indirect facilitation of exotic invasive species. Habitat specialists may be especially prone to rapidly changing environmental conditions because their ability to adapt lags behind the rate of habitat alteration. As a result, these populations may become increasingly susceptible to ecological traps by returning to suboptimal breeding habitats that were dramatically altered by disturbance. We demonstrate a multistage modeling approach that integrates habitat selection and survival during the key nesting life‐stage of a bird species of high conservation concern, the greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse). We applied these spatially explicit models to a spatiotemporally robust dataset of sage‐grouse nest locations and fates across wildfire‐altered sagebrush ecosystems of the Great Basin ecoregion, western United States. Female sage‐grouse exhibited intricate habitat selection patterns that varied across regional gradients of ecological productivity among sagebrush communities, but often selected nest sites that disproportionately resulted in nest failure. For example, 23% of nests occurred in wildfire‐affected habitats characterized by reduced sagebrush cover and greater composition of invasive annual grasses. We found survival of nests was negatively associated with wildfire‐affected areas, but positively associated with higher elevations with increased ruggedness and overall shrub cover. Strong site fidelity likely drove sage‐grouse to continue nesting in habitats degraded by wildfire. Hence, increasing frequency and extent of wildfire may contribute disproportionately to reduced reproductive success by creating ecological traps that act as population sinks. Identifying such habitat mismatches between selection and survival facilitates deeper understanding of the mechanisms driving reduced geographic niche space and population decline at broad spatiotemporal scales, while guiding management actions to areas that would be most beneficial to the species., Wildfire frequency and severity has increased within Great Basin sagebrush ecosystems. Non‐native annual grasses invade burned areas, providing new fuels and promoting additional fire through a positive feedback cycle. Greater sage‐grouse can become “trapped” in the wildfire‐invasive grass feedback loop, due to strong breeding and nest site fidelity to areas where sagebrush cover and subsequent nest success becomes reduced following wildfire. Landscape modeling of nest site selection and nest survival suggests that long‐term losses in sagebrush and permanent transitions to annual grassland facilitate maladaptive breeding habitat selection and ecological niche loss.

According to the ideal-free distribution (IFD), individuals within a population are free to select habitats that maximize their chances of success. Assuming knowledge of habitat quality, the IFD predicts that average fitness will be approximately equal among individuals and between habitats, while density varies, implying that habitat selection will be density dependent. Populations are often assumed to follow an IFD, although this assumption is rarely tested with empirical data, and may be incorrect when territoriality indicates habitat selection tactics that deviate from the IFD (e.g. ideal-despotic distribution or ideal-preemptive distribution). When territoriality influences habitat selection, species' density will not directly reflect components of fitness such as reproductive success or survival. In such cases, assuming an IFD can lead to false conclusions about habitat quality. We tested theoretical models of density-dependent habitat selection on a species known to exhibit territorial behaviour in order to determine whether commonly applied habitat models are appropriate under these circumstances. We combined long-term radiotelemetry and census data from grey wolves Canis lupus in the Upper Peninsula of Michigan, USA to relate spatiotemporal variability in wolf density to underlying classifications of habitat within a hierarchical state-space modelling framework. We then iteratively applied isodar analysis to evaluate which distribution of habitat selection best described this recolonizing wolf population. The wolf population in our study expanded by >1,000% during our study (~50 to >600 individuals), and density-dependent habitat selection was most consistent with the ideal-preemptive distribution, as opposed to the ideal-free or ideal-despotic alternatives. Population density of terrestrial carnivores may not be positively correlated with the fitness value of their habitats, and density-dependent habitat selection patterns may help to explain complex predator-prey dynamics and cascading indirect effects. Source-sink population dynamics appear likely when species exhibit rapid growth and occupy interspersed habitats of contrasting quality. These conditions are likely and have implications for large carnivores in many systems, such as areas in North America and Europe where large predator species are currently recolonizing their former ranges.

Background Drastic increases in wildfire size and frequency threaten western North American sagebrush (Artemisia L. spp.) ecosystems. At relatively large spatial scales, wildfire facilitates type conversion of sagebrush-dominated plant communities to monocultures of invasive annual grasses (e.g., Bromus tectorum L.). Annual grasses provide fine fuels that promote fire spread, contributing to a positive grass–fire feedback cycle that affects most sagebrush ecosystems, with expected habitat loss for resident wildlife populations. Greater sage-grouse (Centrocercus urophasianus Bonaparte, 1827) are sagebrush obligate species that are indicators of sagebrush ecosystem function because they rely on different components of sagebrush ecosystems to meet seasonal life history needs. Because wildfire cannot be predicted, chronic impacts of wildfire on sage-grouse populations have been largely limited to correlative studies. Thus, evidence from well-designed experiments is needed to understand the specific mechanisms by which wildfire is detrimental to sage-grouse population dynamics. Results Following a significant wildfire event in the southwest periphery of sage-grouse range, we implemented a before-after-control-impact study with long-term paired (BACIP) datasets of male sage-grouse surveyed from traditional breeding grounds (leks) within and outside the wildfire boundary. We estimated sage-grouse population rate of change in apparent abundance ($$ \hat{\uplambda} $$ λ ̂ ) at burned and unburned areas before and after wildfire and derived BACIP ratios, which provide controlled evidence of wildfire impact. We found that $$ \hat{\uplambda} $$ λ ̂ at leks within the wildfire boundary decreased approximately 16% relative to leks at control sites. Furthermore, we estimated a 98.5% probability that the observed change in $$ \hat{\uplambda} $$ λ ̂ could be attributed to the wildfire. Conclusions We demonstrated adverse wildfire impacts on sage-grouse population growth using an experimental BACIP design, which disentangled the effect of wildfire disturbance from natural population fluctuations. Our results underscore the importance of active and comprehensive management actions immediately following wildfire (i.e., seeding coupled with planting sagebrush), that might offset short-term impacts of wildfire by timing rapid recovery of sagebrush to meet short-term species’ habitat requirements. Burned leks likely have substantial immediate impacts that may extend beyond wildfire boundaries, especially if critical source habitats are removed. Such impacts could fragment habitat and disrupt connectivity, thereby affecting larger populations and possibly contributing to more widespread declines in sage-grouse populations.

Gene expression across tissues is regulated by an unknown number of determinants, including prevalence of transcription factors (TFs) and their binding sites along with other aspects of cellular state. Recent studies have emphasized the importance of both genetic and epigenetic states, at least two of which have substantial literature support as causal determinants of tissue specificity: TF binding sites, and chromatin accessibility at those sites. In order to investigate the extent and relative contributions of these potential determinants, we constructed three genome-scale datasets for both root and shoot tissues of the same Arabidopsis thaliana plants: TSS-seq data to identify Transcription Start Sites, OC-seq data to identify regions of Open Chromatin, and RNA-seq data to assess gene expression levels. For those genes that are differentially expressed between root and shoot, we constructed a machine learning model incorporating chromatin accessibility with TF binding information upstream of TSS locations, with the goal of predicting the tissue in which each of these genes would be upregulated. The resulting model was highly accurate when both chromatin structure and sequence were considered (over 90% auROC and auPRC), allowing one to predict the tissue in which a given gene will express. By considering model contributions that most strongly influence the predicted tissue of expression, our analysis suggests that patterns of TF binding sites within ~500 nt TSS-proximal regions are predominant explainers of tissue of expression in a large majority of cases. Thus, in plants, cis-regulatory control of tissue specific gene expression appears unlikely to be limited to or even predominantly located in enhancer-like distal accessible chromatin regions. This study highlights the exciting future possibility of a native TF site-based design process for the tissue-specific targeting of plant gene promoters.

Expanding human enterprise across remote environments impacts numerous wildlife species. Anthropogenic resources provide subsidies for generalist predators that can lead to cascading effects on prey species at lower trophic levels. A fundamental challenge for applied ecologists is to disentangle natural and anthropogenic influences on species occurrence, and subsequently develop spatially explicit models to help inform management and conservation decisions. Using Bayesian hierarchical occupancy models, we mapped the broad‐scale occurrence of common ravens Corvus corax as a function of natural and anthropogenic landscape covariates using >15,000 point count surveys performed during 2007–2016 within the Great Basin region, USA. Raven abundance and distribution is substantially increasing across the American west due to unintended anthropogenic resource subsidies. Importantly, ravens prey on eggs and chicks of numerous species including greater sage‐grouse Centrocercus urophasianus, an indicator species whose decline is at the centre of national conservation strategies and land‐use policies. Anthropogenic factors that contributed to greater raven occurrence were: increased road density, presence of transmission lines, agricultural activity, and presence of roadside rest areas. Natural landscape characteristics included lower elevations with greener vegetation (Normalized Difference Vegetation Index), greater stream and habitat edge densities, and lower percentages of big sagebrush Artemisia tridentata spp. Interactions between anthropogenic sources of nesting substrate and food subsidies suggested that raven occurrence increased multiplicatively when these resource subsidies co‐occurred. Overall, the average probability of raven occurrence estimated within sagebrush ecosystems of the study area was c. 0.83. Synthesis and applications. We demonstrate how anthropogenic factors can be disentangled from natural effects when making spatially explicit predictions of subsidized predators occurring across expansive landscapes. This approach can guide management decisions where subsidized predators overlap sensitive prey habitats. For example, we identify areas where elevated raven occurrence coincides with breeding sage‐grouse concentration areas and appears to be largely driven by anthropogenic factors. Management applications could focus on reducing raven access to anthropogenic subsidies in these areas, while prioritizing habitat improvements for sage‐grouse elsewhere. Our approach is applicable to other species where widespread survey data are available.

Ewing’s sarcoma treatment failures are associated with high mortality indicating a need for new therapeutic approaches. We used a k-mer counting approach to identify cancer-specific mRNA transcripts in 3 Ewing’s Family Tumor (EFT) cell lines not found in the normal human transcriptome. Phosphorodiamidate morpholino oligomers targeting six EFT-specific transcripts were evaluated for cytotoxicity in TC-32 and CHLA-10 EFT lines and in HEK293 renal epithelial control cells. Average morpholino efficacy (EC50) was 0.66 ± 0.13 in TC-32, 0.25 ± 0.14 in CHLA-10 and 3.07 ± 5.02 µM in HEK293 control cells (ANOVA p < 0.01). Synergy was observed for a cocktail of 12 morpholinos at low dose (0.3 µM) in TC-32 cells, but not in CHLA-10 cells. Paired synergy was also observed in both EFT cell lines when the PHGDH pre-mRNA transcript was targeted in combination with XAGE1B or CYP4F22 transcripts. Antagonism was observed when CCND1 was targeted with XAGE1B or CYP4F22, or when IGFBP-2 was targeted with CCND1 or RBM11. This transcriptome profiling approach is highly effective for cancer drug discovery, as it identified new EWS-specific target genes (e.g. CYP4F22, RBM11 and IGBP-2), and predicted effective antisense agents (EC50 < 1 µM) that demonstrate both synergy and antagonism in combination therapy.

Understanding landscape patterns in mortality risk is crucial for promoting recovery of threatened and endangered species. Humans affect mortality risk in large carnivores such as wolves (Canis lupus), but spatiotemporally varying density dependence can significantly influence the landscape of survival. This potentially occurs when density varies spatially and risk is unevenly distributed. We quantified spatiotemporal sources of variation in survival rates of gray wolves (C. lupus) during a 21-year period of population recovery in the Upper Peninsula of Michigan, USA. We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time-dependent covariates, thus exploring a shifting mosaic of survival. Extended CPH models and time-dependent covariates revealed influences of seasonality, density dependence and experience, as well as individual-level factors and landscape predictors of risk. We used results to predict the shifting landscape of risk at the beginning, middle, and end of the wolf recovery time series. Survival rates varied spatially and declined over time. Long-term change was density-dependent, with landscape predictors such as agricultural land cover and edge densities contributing negatively to survival. Survival also varied seasonally and depended on individual experience, sex, and resident versus transient status. The shifting landscape of survival suggested that increasing density contributed to greater potential for human conflict and wolf mortality risk. Long-term spatial variation in key population vital rates is largely unquantified in many threatened, endangered, and recovering species. Variation in risk may indicate potential for source-sink population dynamics, especially where individuals preemptively occupy suitable territories, which forces new individuals into riskier habitat types as density increases. We encourage managers to explore relationships between adult survival and localized changes in population density. Density-dependent risk maps can identify increasing conflict areas or potential habitat sinks which may persist due to high recruitment in adjacent habitats.

Human enterprise has modified ecosystem processes through direct and indirect alteration of native predators' distribution and abundance. For example, human activities subsidize food, water, and shelter availability to generalist predators whose subsequent increased abundance impacts lower trophic-level prey species. The common raven (Corvus corax; hereafter, raven) is an avian scavenger and predator, native to the northern hemisphere, that can become invasive when subsidized. Raven populations are increasing at unprecedented rates in many regions globally. Information regarding scale of impact and potential ecological thresholds is needed to guide conservation actions aimed at reducing adverse effects on sensitive prey. We conducted a multi-part analysis to investigate broad-scale variation in raven densities and impacts on nesting greater sage-grouse (Centrocercus urophasianus), an indicator species for sagebrush ecosystems in western North America. We estimated raven densities using >16,000 point surveys over 10 years within the Great Basin, USA, and examined associations with anthropogenic and environmental covariates. Average density was 0.54 ravens km−2 (95% CI: 0.42–0.70), with higher densities at lower relative elevations comprising increased agriculture and development. We then used a reduced dataset to estimate the effect of raven density on sage-grouse nest survival (nests = 737). We identified negative impacts to nesting sage-grouse, especially where raven density exceeded ~0.40 km−2, a potential ecological threshold. We mapped regions where elevated raven densities were predicted to depress sage-grouse population growth in the absence of compensatory demographic responses from other sage-grouse life-history stages, and found ~64% of sage-grouse breeding areas were adversely impacted by high raven density.

In today's competitive market, demand volume and even the underlying demand distribution can change quickly for a newsvendor seller. We refer to sudden changes in demand distribution as demand shocks. When a newsvendor seller has limited demand distribution information and also experiences underlying demand shocks, the majority of existing methods for newsvendor problems may not work well since they either require demand distribution information or assume stationary demand distribution. We present a new, robust, and effective machine learning algorithm for newsvendor problems with demand shocks but without any demand distribution information. The algorithm needs only an approximate estimate of the lower and upper bounds of demand range; no other knowledge such as demand mean, variance, or distribution type is necessary. We establish the theoretical bounds that determine this machine learning algorithm's performance in handling demand shocks. Computational experiments show that this algorithm outperforms the traditional approaches in a variety of situations including large and frequent shocks of the demand mean. The method can also be used as a meta-algorithm by incorporating other traditional approaches as experts. Working together, the original algorithm and the extended meta-algorithm can help manufacturers and retailers better adapt their production and inventory control decisions in dynamic environments where demand information is limited and demand shocks are frequent

Hybrid zones are a valuable tool for studying the process of speciation and for identifying the genomic regions undergoing divergence and the ecological (extrinsic) and non-ecological (intrinsic) factors involved. Here, we explored the genomic and geographic landscape of divergence in a hybrid zone betweenPapilio glaucusandPapilio canadensis. Using a genome scan of 28,417 ddRAD SNPs, we identified genomic regions under possible selection and examined their distribution in the context of previously identified candidate genes for ecological adaptations. We showed that differentiation was genome-wide, including multiple candidate genes for ecological adaptations, particularly those involved in seasonal adaptation and host plant detoxification. The Z-chromosome and four autosomes showed a disproportionate amount of differentiation, suggesting genes on these chromosomes play a potential role in reproductive isolation. Cline analyses of significantly differentiated genomic SNPs, and of species diagnostic genetic markers, showed a high degree of geographic coincidence (81%) and concordance (80%) and were associated with the geographic distribution of a climate-mediated developmental threshold (length of the growing season). A relatively large proportion (1.3%) of the outliers for divergent selection were not associated with candidate genes for ecological adaptations and may reflect the presence of previously unrecognized intrinsic barriers between these species. These results suggest that exogenous (climate-mediated) and endogenous (unknown) clines may have become coupled and act together to reinforce reproductive isolation. This approach of assessing divergence across both the genomic and geographic landscape can provide insight about the interplay between the genetic architecture of reproductive isolation and endogenous and exogenous selection.

Understanding landscape patterns in mortality risk is crucial for promoting recovery of threatened and endangered species. Humans affect mortality risk in large carnivores such as wolves (Canis lupus), but spatiotemporally varying density dependence can significantly influence the landscape of survival. This potentially occurs when density varies spatially and risk is unevenly distributed. We quantified spatiotemporal sources of variation in survival rates of gray wolves (C. lupus) during a 21‐year period of population recovery in the Upper Peninsula of Michigan, USA. We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time‐dependent covariates, thus exploring a shifting mosaic of survival. Extended CPH models and time‐dependent covariates revealed influences of seasonality, density dependence and experience, as well as individual‐level factors and landscape predictors of risk. We used results to predict the shifting landscape of risk at the beginning, middle, and end of the wolf recovery time series. Survival rates varied spatially and declined over time. Long‐term change was density‐dependent, with landscape predictors such as agricultural land cover and edge densities contributing negatively to survival. Survival also varied seasonally and depended on individual experience, sex, and resident versus transient status. The shifting landscape of survival suggested that increasing density contributed to greater potential for human conflict and wolf mortality risk. Long‐term spatial variation in key population vital rates is largely unquantified in many threatened, endangered, and recovering species. Variation in risk may indicate potential for source‐sink population dynamics, especially where individuals preemptively occupy suitable territories, which forces new individuals into riskier habitat types as density increases. We encourage managers to explore relationships between adult survival and localized changes in population density. Density‐dependent risk maps can identify increasing conflict areas or potential habitat sinks which may persist due to high recruitment in adjacent habitats.

Summary The developmental programme of grape berries within a cluster is coordinated to synchronize their ripening. Altered transcriptional events and metabolite accumulation are responsible for the differential progress of ripening., Transcriptional studies in relation to fruit ripening generally aim to identify the transcriptional states associated with physiological ripening stages and the transcriptional changes between stages within the ripening programme. In non-climacteric fruits such as grape, all ripening-related genes involved in this programme have not been identified, mainly due to the lack of mutants for comparative transcriptomic studies. A feature in grape cluster ripening (Vitis vinifera cv. Pinot noir), where all berries do not initiate the ripening at the same time, was exploited to study their shifted ripening programmes in parallel. Berries that showed marked ripening state differences in a véraison-stage cluster (ripening onset) ultimately reached similar ripeness states toward maturity, indicating the flexibility of the ripening programme. The expression variance between these véraison-stage berry classes, where 11% of the genes were found to be differentially expressed, was reduced significantly toward maturity, resulting in the synchronization of their transcriptional states. Defined quantitative expression changes (transcriptional distances) not only existed between the véraison transitional stages, but also between the véraison to maturity stages, regardless of the berry class. It was observed that lagging berries complete their transcriptional programme in a shorter time through altered gene expressions and ripening-related hormone dynamics, and enhance the rate of physiological ripening progression. Finally, the reduction in expression variance of genes can identify new genes directly associated with ripening and also assess the relevance of gene activity to the phase of the ripening programme.

Local adaptation of populations could preclude or slow range expansions in response to changing climate, particularly when dispersal is limited. To investigate the differential responses of populations to changing climatic conditions, we exposed poleward peripheral and central populations of two Lepidoptera to reciprocal, common-garden climatic conditions and compared their whole-transcriptome expression. We found evidence of simple population differentiation in both species, and in the species with previously identified population structure and phenotypic local adaptation, we found several hundred genes that responded in a synchronized and localized fashion. These genes were primarily involved in energy metabolism and oxidative stress, and expression levels were most divergent between populations in the same environment in which we previously detected divergence for metabolism. We found no localized genes in the species with less population structure and for which no local adaptation was previously detected. These results challenge the assumption that species are functionally similar across their ranges and poleward peripheral populations are preadapted to warmer conditions. Rather, some taxa deserve population-level consideration when predicting the effects of climate change because they respond in genetically based, distinctive ways to changing conditions.

Prebreeding habitat selection in birds can often be explained in part by habitat characteristics. However, females may also select habitats on the basis of fidelity to areas of previous reproductive success or use by conspecifics. The relative influences of sociobehavioural attributes versus habitat characteristics in habitat selection has been primarily investigated in songbirds, while less is known about how these factors affect habitat selection processes in migratory waterfowl. Animal resource selection models often exhibit much unexplained variation; spatial patterns driven by social and behavioural characteristics may account for some of this. We radiomarked female lesser scaup, Aythya affinis, in the southwestern extent of their breeding range to explore hypotheses regarding relative roles of habitat quality, site fidelity and conspecific density in prebreeding habitat selection. We used linear mixed-effects models to relate intensity of use within female home ranges to habitat features, distance to areas of reproductive success during the previous breeding season and conspecific density. Home range habitats included shallow water (≤118 cm), moderate to high densities of flooded emergent vegetation/open water edge and open water areas with submerged aquatic vegetation. Compared with habitat features, conspecific female density and proximity to successful nesting habitats from the previous breeding season had greater influences on habitat use within home ranges. Fidelity and conspecific attraction are behavioural characteristics in some waterfowl species that may exert a greater influence than habitat features in influencing prebreeding space use and habitat selection within home ranges, particularly where quality habitat is abundant. These processes may be of critical importance to a better understanding of habitat selection in breeding birds.

As important vectors of human disease, phlebotomine sand flies are of global significance to human health, transmitting several emerging and re-emerging infectious diseases. The most devastating of the sand fly transmitted infections are the leishmaniases, causing significant mortality and morbidity in both the Old and New World. Here we present the first global transcriptome analysis of the Old World vector of cutaneous leishmaniasis, Phlebotomus papatasi (Scopoli) and compare this transcriptome to that of the New World vector of visceral leishmaniasis, Lutzomyia longipalpis. A normalized cDNA library was constructed using pooled mRNA from Phlebotomus papatasi larvae, pupae, adult males and females fed sugar, blood, or blood infected with Leishmania major. A total of 47 615 generated sequences was cleaned and assembled into 17 120 unique transcripts. Of the assembled sequences, 50% (8837 sequences) were classified using Gene Ontology (GO) terms. This collection of transcripts is comprehensive, as demonstrated by the high number of different GO categories. An in-depth analysis revealed 245 sequences with putative homology to proteins involved in blood and sugar digestion, immune response and peritrophic matrix formation. Twelve of the novel genes, including one trypsin, two peptidoglycan recognition proteins (PGRP) and nine chymotrypsins, have a higher expression level during larval stages. Two novel chymotrypsins and one novel PGRP are abundantly expressed upon blood feeding. This study will greatly improve the available genomic resources for P. papatasi and will provide essential information for annotation of the full genome.

We present theoretical results for large-file distribution on general networks of known topology (known link bandwidths and router locations). We show that the problem of distributing a file in minimum time is NP-hard in this model, and we give an O(logn) approximation algorithm, where n is the number of workstations that require the file. We also characterize our method as optimal amongst the class of "no-link-sharing" algorithms.

Elk (Cervus elaphus) range expansion and reintroduction is a topic of national interest in wildlife management. Eastern states are facilitating the recolonization of elk to historic ranges. Success of these herds depends on habitat evaluations, site-specific considerations of human tolerance to elk and interactions between elk and existing wildlife. Interest in elk restoration has increased for multiple stakeholders in Michigan (USA), where prospering elk suggest there is potential for range expansion. Habitat quality at the landscape scale for elk in Michigan depends primarily on available forage, suitable cover, habitat diversity, and road densities so we quantified these factors in the Upper Peninsula and northern Lower Peninsula of Michigan using a habitat suitability index model framework. We focused our analysis on target areas of interest and compared habitat suitability values occurring at those locations to values occurring within the current elk range (Pigeon River County State Forest area, or Pigeon River). We used elk habitat utilization information associated with the Pigeon River to validate and adjust our habitat suitability model. We also included a model that assigned less weight to the road density parameter, to account for uncertainty regarding the influence of roads on elk. Results from our habitat models suggested that patches of moderately suitable habitat exist outside the Pigeon River range in Michigan. Target areas differed in quality and quantity of habitat when compared to existing elk range, but habitat suitability values overlapped considerably among locations. Large patches of moderately suitable habitat also occurred outside of target areas. Results suggest that Michigan has potential to support an expanded elk range; however, additional site-specific considerations (land ownership, winter snowpack, deer-elk interaction, wolf density) likely need to be accounted for at potential restoration and expansion sites.