Ecological neighborhoods as a framework for umbrella species selection

Umbrella species are typically chosen because they are expected to confer protection for other species assumed to have similar ecological requirements. Despite its popularity and substantial history, the value of the umbrella species concept has come into question because umbrella species chosen using heuristic methods, such as body or home range size, are not acting as adequate proxies for the metrics of interest: species richness or population abundance in a multi-species community for which protection is sought. How species associate with habitat across ecological scales has important implications for understanding population size and species richness, and therefore may be a better proxy for choosing an umbrella species. We determined the spatial scales of ecological neighborhoods important for predicting abundance of 8 potential umbrella species breeding in Nebraska using Bayesian latent indicator scale selection in N-mixture models accounting for imperfect detection. We compare the conservation value measured as collective avian abundance under different umbrella species selected following commonly used criteria and selected based on identifying spatial land cover characteristics within ecological neighborhoods that maximize collective abundance. Using traditional criteria to select an umbrella species resulted in sub-maximal expected collective abundance in 86% of cases compared to selecting an umbrella species based on land cover characteristics that maximized collective abundance directly. We conclude that directly assessing the expected quantitative outcomes, rather than ecological proxies, is likely the most efficient method to maximize the potential for conservation success under the umbrella species concept

Estimating the Use of Public Lands: Integrated Modeling of Open Populations with Convolution Likelihood Ecological Abundance Regression

We present an integrated open population model where the population dynamics are defined by a differential equation, and the related statistical model utilizes a Poisson binomial convolution likelihood. Key advantages of the proposed approach over existing open population models include the flexibility to predict related, but unobserved quantities such as total immigration or emigration over a specified time period, and more computationally efficient posterior simulation by elimination of the need to explicitly simulate latent immigration and emigration. The viability of the proposed method is shown in an in-depth analysis of outdoor recreation participation on public lands, where the surveyed populations changed rapidly and demographic population closure cannot be assumed even within a single day

A Bayesian method for assessing multi-scale species-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multiscale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships

A Bayesian method for assessing multi-scale species-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multiscale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships

Biodiversity Scale-Dependence and Opposing Multi-level Correlations Underlie Differences among Taxonomic, Phylogenetic and Functional Diversity

Aim: Biodiversity is a multidimensional property of biological communities that represents different information depending on how it is measured, but how dimensions relate to one another and under what conditions is not well understood. We explore how taxonomic, phylogenetic, and functional diversity can differ in scale-of-effect dependence and habitat-biodiversity relationships, and subsequently how spatial differences among biodiversity dimensions may arise. Location: Nebraska, United States. Taxon: Birds. Methods: Across 2016 and 2017, we conducted 2,641 point counts at 781 sites. We modeled the occupancy of 141 species using Bayesian Bernoulli-Bernoulli hierarchical logistic regressions. We calculated species richness (SR), phylogenetic diversity (PD), and functional diversity (FD) for each site and year based on predicted occupancy, accounting for imperfect detection. Using Bayesian latent indicator scale selection and multivariate modeling, we quantified the spatial scales-of-effect that best explained the relationships between environmental characteristics and SR, PD, and FD. Additionally, we decomposed the residual between-site and within-site biodiversity correlations using our repeated measures design. Results: Although relationships between specific land cover types and SR, PD, and FD were qualitatively similar, the spatial scales at which these variables were important in explaining biodiversity differed among dimensions. Between-site residual biodiversity correlations were negative, yet within-site biodiversity residual correlations were positive. Main conclusions: Our results demonstrate how spatial differences among biodiversity dimensions may arise from biodiversity-specific scale-dependent habitat relationships, low shared environmental correlations, and opposing residual correlations between dimensions, suggesting that single-scale and single-dimension analyses are not entirely appropriate for quantifying habitat-biodiversity relationships. After accounting for shared habitat relationships, we found positive within-site residual correlations between SR, PD, and FD, suggesting that habitat change over time influenced all biodiversity dimensions similarly. However, negative between-site residual correlation among biodiversity dimensions may indicate trade-offs in achieving maximum biodiversity across multiple biodiversity dimensions at any given location

Genetic Correlates of Individual Differences in Sleep Behavior of Free-Living Great Tits (Parus major)

Within populations, free-living birds display considerable variation in observable sleep behaviors, reflecting dynamic interactions between individuals and their environment. Genes are expected to contribute to repeatable between-individual differences in sleep behaviors, which may be associated with individual fitness. We identified and genotyped polymorphisms in nine candidate genes for sleep, and measured five repeatable sleep behaviors in free-living great tits (Parus major), partly replicating a previous study in blue tits (Cyanistes caeruleus). Microsatellites in the CLOCK and NPAS2 clock genes exhibited an association with sleep duration relative to night length, and morning latency to exit the nest box, respectively. Furthermore, microsatellites in the NPSR1 and PCSK2 genes associated with relative sleep duration and proportion of time spent awake at night, respectively. Given the detection rate of associations in the same models run with random markers instead of candidate genes, we expected two associations to arise by chance. The detection of four associations between candidate genes and sleep, however, suggests that clock genes, a clock-related gene, or a gene involved in the melanocortin system, could play key roles in maintaining phenotypic variation in sleep behavior in avian populations. Knowledge of the genetic architecture underlying sleep behavior in the wild is important because it will enable ecologists to assess the evolution of sleep in response to selection

Media Portrayal of Regions in the Czech Republic

Import 05/08/2014Sdělovací prostředky spolu s informacemi, které poskytují, se významnou měrou podílejí na utváření image regionů a také spoluurčují jejich postavení na mentálních mapách. Cílem této diplomové práce je kvantitativní a kvalitativní analýza a interpretace zpravodajských příspěvků o krajích České republiky, které byly publikovány ve zpravodajských relacích nejsledovanějších televizních stanic u nás – České televize, televize Nova a televize Prima. Teoretická část této práce je zaměřená na samotné sdělovací prostředky a regionální členění České republiky. Profily krajů poskytují srovnání krajů České republiky z hlediska geografické polohy, demografického vývoje, situace na trhu práce a ekonomické úrovně. Analytická část je zaměřená na kvantitativní a kvalitativní analýzu a interpretaci zpravodajských příspěvků o jednotlivých krajích. Podle výsledků analýzy byl z kvantitativního hlediska zaznamenán převažující podíl počtu zpráv, které se váží k hlavnímu městu Praze. Z výsledků kvalitativní analýzy je zřejmé, že tematická struktura zpravodajských příspěvků o krajích České republiky je poměrně jednostranně orientovaná na zprávy bulvárního charakteru.The media along with the information that provide significantly contribute to shaping the image of the regions and also factors determining their position on the mental maps. The objective of this thesis is a quantitative and qualitative analysis and interpretation of news reports about the regions of the Czech Republic published in national TV coverage the most watched television stations in the country – Česká televize, TV Nova and TV Prima. The theoretical part of this thesis is focused on the media and the regional division of the Czech Republic. Profiles of the regions provide comparisons between regions in terms of geographic location, demographic trends, situation on the labor market and economic level. The analytical part is focused on quantitative and qualitative analysis and interpretation of news reports about regions of the Czech Republic. According to the results of analysis from a quantitative point of view was recorded predominant proportion of the number of contributions that are associated with the capital city Prague. From results of qualitative analysis is evident that the thematic structure of news reports about the regions of the Czech Republic is relatively unilaterally oriented on reports tabloid character.118 - Katedra regionální a environmentální ekonomikyvýborn

Public Access for Pheasant Hunters: Understanding an Emerging Need

Ring‐necked pheasant (Phasianus colchicus; i.e., pheasant) hunting participation is declining across North America, reflecting a larger downward trend in American hunting participation and threatening benefits to grassland conservation and rural economies. To stabilize and expand the pheasant hunting population, we must first identify factors that influence pheasant hunter participation. We used an extensive in‐person hunter survey to test the hypothesis that hunter demographics interact with social‐ecological traits of hunting locations to affect hunter decisions, outcomes, and perceptions. We built a series of Bayesian mixed effects models to parse variation in demographics, perceptions, and hunt outcomes of pheasant hunters interviewed at public access hunting sites across 3 regions in Nebraska, USA, that varied in pheasant abundance and proximity to urban population centers. Among pheasant hunters in Nebraska, access to private lands was negatively related to the human population density of a pheasant hunter’s home ZIP code and the distance a hunter had traveled to reach a hunting location. Pheasant hunters interviewed closer to metropolitan areas tended to be more urban and travel shorter distances, and their parties were more likely to include youth but less likely to include dogs. Hunter satisfaction was positively associated with seeing and harvesting pheasants and hunting with youth. Whereas youth participation and the number of pheasants seen varied by study region, hunter satisfaction did not differ across regions, suggesting that hunters may calibrate their expectations and build their parties based on where they plan to hunt. The variation in hunter demographics across hunting locations and disconnects between social and ecological correlates of hunter satisfaction suggests that diverse pheasant hunting constituencies will be best served by diverse pheasant hunting opportunities

Translating statistical species-habitat models to interactive decision support tools

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audience

Hunters and Their Perceptions of Public Access: A View from Afield

Declining hunter participation threatens cultural traditions and public support for conservation, warranting examination of the forces behind the downward trajectory. Access to lands for hunting, an often-cited reason for non participation, may play a critical role in the retention and recruitment of hunters. Meeting the access needs of a diverse hunting constituency requires understanding how hunters use and perceive access opportunities, particularly public-access sites. Given that perceptions of access are entirely place based and degrade with time, traditional postseason survey methods may fail to adequately quantify the value of public access to the hunting constituency. To overcome the potential limitations of postseason surveys, we conducted on-site assessments of hunter perceptions of habitat quality, game abundance, ease of access, and crowding as well as whether the experience met the hunters’ expectations and their likelihood to return to hunt. Over 3 y, we interviewed 3,248 parties of which 71.5% were hunting. Most parties (65.9%) reported having no private access within the region of Nebraska where they were interviewed. Parties (67.6%) were largely limited to two or fewer hunters, most of whom were adult males (84.3%) who were, on average, 41.2 y old. The perception of public-access sites was generally positive, but 43.1% of parties indicated that game abundance was below average despite 59.2% of parties seeing game and 37.3% harvesting at least one animal. Similar to other explorations of hunter satisfaction, we found game abundance, and in particular harvest success, had the most consistent relationship with hunter perception of public access. By surveying multiple types of hunters across sites that encompass a range of social and ecological conditions, we gained a broader understanding of how hunters perceive public access in real time, which will help to inform future management decisions to foster and improve public-access programs