Regional avian species declines estimated from volunteer-collected long-term data using List Length Analysis

Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length,'' can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes

Banking Fees in the Czech Republic and Slovakia

Import 05/08/2014Cílem práce je zhodnotit významnost bankovních poplatků pro vybrané banky České republiky a Slovenska v letech 2007-2012 a posoudit výši poplatků českých a slovenských klientů v roce 2014. V teoretické části je obecně vymezen bankovní systém. V další kapitole je popsán bankovní systém ČR. Závěrečná kapitola je věnována analýze bankovních poplatků. V práci je použita metoda deskripce a komparace. Z výsledků analýzy vyplývá, že elektronické bankovnictví je pro klienta levnější alternativou běžného využívání bankovních služeb. Pro klienta v ČR jsou výrazně levnější malé banky. Ze srovnání nákladovosti bankovních služeb českých a slovenský bank vyplývá, že nejdražší bankou je Slovenská spořitelna, nejlevnější bankou je česká UniCredit Bank. Dle podílu čistých výnosů z poplatků na provozních výnosech banky jsou poplatky nejvýznamnější pro Českou spořitelnu, nejmenší váhu mají pro českou ČSOB.In this thesis, the importance of banking fees for banks in the Czech Republic and Slovakia in 2007-2012 is examined. The thesis is also focused on the amount of banking fees for the customers of the Czech and Slovak banks in 2014. The theoretical chapter defines a banking system in general. The following chapter describes the Czech banking system. The final chapter contains banking fees analysis. In the thesis, the descriptive method and the comparison method are used. The findings show us that services of the small banks are less expensive than that of the large banks in the Czech Republic. Slovenská spořitelna is the most expensive bank from the large Czech and Slovak banks. Czech UniCredit Bank is bank with the lowest fees. The results of the analysis also show that the internet banking is the cheapest alternative for the customers. Fee income is most important for Česká spořitelna; it is the bank with the highest share of net fee income on the operating income. The Czech ČSOB was identified as the bank with the lowest share of net fee income.156 - Katedra národohospodářskávelmi dobř

Integrating Multiple Data Types to Connect Ecological Theory and Data Among Levels

Ecological theories often encompass multiple levels of biological organization, such as genes, individuals, populations, and communities. Despite substantial progress toward ecological theory spanning multiple levels, ecological data rarely are connected in this way. This is unfortunate because different types of ecological data often emerge from the same underlying processes and, therefore, are naturally connected among levels. Here, we describe an approach to integrate data collected at multiple levels (e.g., individuals, populations) in a single statistical analysis. The resulting integrated models make full use of existing data and might strengthen links between statistical ecology and ecological models and theories that span multiple levels of organization. Integrated models are increasingly feasible due to recent advances in computational statistics, which allow fast calculations of multiple likelihoods that depend on complex mechanistic models. We discuss recently developed integrated models and outline a simple application using data on freshwater fishes in south-eastern Australia. Available data on freshwater fishes include population survey data, mark-recapture data, and individual growth trajectories. We use these data to estimate age-specific survival and reproduction from size-structured data, accounting for imperfect detection of individuals. Given that such parameter estimates would be infeasible without an integrated model, we argue that integrated models will strengthen ecological theory by connecting theoretical and mathematical models directly to empirical data. Although integrated models remain conceptually and computationally challenging, integrating ecological data among levels is likely to be an important step toward unifying ecology among levels

Eliciting group judgements about replicability: a technical implementation of the IDEA Protocol

In recent years there has been increased interest in replicating prior research. One of the biggest challenges to assessing replicability is the cost in resources and time that it takes to repeat studies. Thus there is an impetus to develop rapid elicitation protocols that can, in a practical manner, estimate the likelihood that research findings will successfully replicate. We employ a novel implementation of the IDEA (‘Investigate’, ‘Discuss’, ‘Estimate’ and ‘Aggregate) protocol, realised through the repliCATS platform. The repliCATS platform is designed to scalably elicit expert opinion about replicability of social and behavioural science research. The IDEA protocol provides a structured methodology for eliciting judgements and reasoning from groups. This paper describes the repliCATS platform as a multi-user cloud-based software platform featuring (1) a technical implementation of the IDEA protocol for eliciting expert opinion on research replicability, (2) capture of consent and demographic data, (3) on-line training on replication concepts, and (4) exporting of completed judgements. The platform has, to date, evaluated 3432 social and behavioural science research claims from 637 participants

Predicting species and community responses to global change using structured expert judgement : an Australian mountain ecosystems case study

Conservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which has already undergone recent changes in climate and experienced more frequent large-scale bushfires. In lieu of empirical data, we used a structured expert elicitation method (the IDEA protocol) to estimate the abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands are predicted to increase in extent. Predicted species-level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species are predicted to decline or not change in abundance or elevation range; more species with water-centric life-cycles are expected to decline in abundance than other species. While long-term ecological data will always be the gold-standard in informing the future of biodiversity, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management in the face of rapid change and paucity of data

Modeling biodiversity benchmarks in variable environments

Effective environmental assessment and management requires quantifiable bio-diversity targets. Biodiversity benchmarks define these targets by focusing on specific biodiver-sity metrics, such as species richness. However, setting fixed targets can be challenging becausemany biodiversity metrics are highly variable, both spatially and temporally. We present a mul-tivariate, hierarchical Bayesian method to estimate biodiversity benchmarks based on the spe-cies richness and cover of native terrestrial vegetation growth forms. This approach usesexisting data to quantify the empirical distributions of species richness and cover withingrowth forms, and we use the upper quantiles of these distributions to estimate contemporary,“best-on-offer”biodiversity benchmarks. Importantly, we allow benchmarks to differ amongvegetation types, regions, and seasons, and with changes in recent rainfall. We apply ourmethod to data collected over 30 yr at~35,000 floristic plots in southeastern Australia. Ourestimated benchmarks were broadly consistent with existing expert-elicited benchmarks, avail-able for a small subset of vegetation types. However, in comparison with expert-elicited bench-marks, our data-driven approach is transparent, repeatable, and updatable; accommodatesimportant spatial and temporal variation; aligns modeled benchmarks directly with field dataand the concept of best-on-offer benchmarks; and, where many benchmarks are required, islikely to be more efficient. Our approach is general and could be used broadly to estimate bio-diversity targets from existing data in highly variable environments, which is especially relevantgiven rapid changes in global environmental conditions.This research was supported by the Australian Research Council Centre of Excellence for Environmental Decisions (CE11001000104) and the New South Wales Office of Environment and Heritag

Active adaptive conservation of threatened species in the face of uncertainty

Adaptive management has a long history in the natural resource management literature, but despite this, few practitioners have developed adaptive strategies to conserve threatened species. Active adaptive management provides a framework for valuing learning by measuring the degree to which it improves long-run management outcomes. The challenge of an active adaptive approach is to find the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge. We develop and analyze a framework for active adaptive management of a threatened species. Our case study concerns a novel facial tumor disease affecting the Australian threatened species Sarcophilus harrisii: the Tasmanian devil. We use stochastic dynamic programming with Bayesian updating to identify the management strategy that maximizes the Tasmanian devil population growth rate, taking into account improvements to management through learning to better understand disease latency and the relative effectiveness of three competing management options. Exactly which management action we choose each year is driven by the credibility of competing hypotheses about disease latency and by the population growth rate predicted by each hypothesis under the competing management actions. We discover that the optimal combination of management actions depends on the number of sites available and the time remaining to implement management. Our approach to active adaptive management provides a framework to identify the optimal amount of effort to invest in learning to achieve long-run conservation objectives

Threatened plant translocation in Australia: A review

Translocation of plants has become a common approach in conservation biology in the past two decades, but it is not clear how successful it is in achieving long-term conservation outcomes. We combined a literature review with extensive consultations with translocation practitioners to compile data on translocations of threatened Australian plants. We documented 1001 translocations involving 376 taxa, concentrated in regions and habitats with high numbers of threatened species. Only 109 translocation attempts encompassing 71 taxa are documented in peer-reviewed literature. Over 85% of translocations have occurred since 2000 and half since 2010, with an especially rapid increase in development mitigation translocations, which account for 30% of all translocations documented. Many translocations involved extremely small numbers of propagules, with 45% using 250. Of the 724 translocations with sufficient data to assess performance, 42% have <10 plants surviving, and 13% have at least 50 plants surviving and some second-generation recruitment into the population. Translocation performance, measured by number of plants surviving and second-generation recruitment, was highly variable between plant lifeforms, habitats and propagule type. However, species was more variable than all of these, suggesting that some species are more conducive to translocation than others. Use of at least 500 founder individuals increased the chances of creating a viable population. Four decades after the first conservation translocations, our evaluation highlights the need to consider translocation in the broad context of conservation actions for species recovery and the need for long-term commitment to monitoring, site maintenance and documentation.This research was funded by the National Environmental Science Program through the Threatened Species Recovery Hu

Functional trait changes in the floras of 11 cities across the globe in response to urbanization

Urbanization causes major environmental changes globally, which can potentially homogenize biota across cities through the loss and gain of particular types of species. We examine whether urban environments consistently select for plants with particular traits and the implications of such changes on the functional composition of urban floras. We classified plant recorded in 11 cities around the globe as species that have either colonized (arrived and naturalized), persisted or been lost (local extirpation) following urbanization. We analyzed how 10 traits previously linked with plant responses to environmental conditions explained membership of these three groups, by comparing colonisers with persistent and extirpated plants through individual city-level Bayesian models. Then, we used meta-analysis to assess consistency of traits across urban areas. Finally, we explored several possible scenarios of functional change using these results. On average, urban colonizers had heavier seeds, unspecialised nutrient requirements, were taller and were annual species more often, especially when compared to locally extirpated plants. Common trends of functional change in urban plant communities include shifts towards taller and heavier-seeded plants, and an increased prevalence of the short-lived species, and plants without mutualistic nutritional strategies. Our results suggest that plant traits influence the species that succeed in urban environments worldwide. Different species use different ecological strategies to live in urban environments, as suggested by the importance of several traits that may appear as trait constellations. Plant height and seed mass were the only traits associated with both colonizer and extirpated plant status in urban environments. Based on our data, predicting colonization in urban environments may be easier than identifying extirpation-prone plants; albeit some regional variation, colonization seems strongly driven by environmental conditions common to most cities (e.g. altered disturbance regimes), whereas extirpation may depend more on processes that vary across cities.JAC, MAM and PAV were supported by the ARC Centre of Excellence for Environmental Decisions. AKH and MJM would like to acknowledge funding from the Baker Foundation and JAC from the ARC (DE120102221)