The scope and severity of white-nose syndrome on hibernating bats in North America

Assessing the scope and severity of threats is necessary for evaluating impacts on populations to inform conservation planning. Quantitative threat assessment often requires monitoring programs that provide reliable data over relevant spatial and temporal scales, yet such programs can be difficult to justify until there is an apparent stressor. Leveraging efforts of wildlife management agencies to record winter counts of hibernating bats, we collated data for 5 species from over 200 sites across 27 U.S. states and 2 Canadian provinces from 1995 to 2018 to determine the impact of white-nose syndrome (WNS), a deadly disease of hibernating bats. We estimated declines of winter counts of bat colonies at sites where the invasive fungus that causes WNS (Pseudogymnoascus destructans) had been detected to assess the threat impact of WNS. Three species undergoing species status assessment by the U.S. Fish and Wildlife Service (Myotis septentrionalis, Myotis lucifugus, and Perimyotis subflavus) declined by more than 90%, which warrants classifying the severity of the WNS threat as extreme based on criteria used by NatureServe. The scope of the WNS threat as defined by NatureServe criteria was large (36% of Myotis lucifugus range) to pervasive (79% of Myotis septentrionalis range) for these species. Declines for 2 other species (Myotis sodalis and Eptesicus fuscus) were less severe but still qualified as moderate to serious based on NatureServe criteria. Data-sharing across jurisdictions provided a comprehensive evaluation of scope and severity of the threat of WNS and indicated regional differences that can inform response efforts at international, national, and state or provincial jurisdictions. We assessed the threat impact of an emerging infectious disease by uniting monitoring efforts across jurisdictional boundaries and demonstrated the importance of coordinated monitoring programs, such as the North American Bat Monitoring Program (NABat), for data-driven conservation assessments and planning.     

浅水湖泊孢粉和植物残体对水生植被的表现率

研究浅水湖泊中植物残体对水生植物的表现率,用于重建近代水生植被历史,可为治理湖泊富营养化,恢复湖泊生态环境提供依据。研究选址为英国北部的一个小湖泊,通过水生植物调查及表层沉积物中植物残体和孢粉分析,及地理信息系统方法定量研究植物残体对水生植物的表现率。结果表明：沉积物中植物残体精确地反映了植物优势种的存在;植物和植物残体的关系是很复杂的,有些植物在残体中表现率明显超高,而有些表现率偏低; 应把叶子和其它非繁殖植株部分作为恢复近代多年生植物历史依据;植物残体传输性较差,主要集中在植物母体附近;利用植物残体与孢粉分析相结合的方法能更准确地重建植被历史。     

Cytotoxic activity of spark‐decomposed sulfur hexafluoride and analysis of cytotoxic contributions of individual spark decomposition products†

Sulfur hexafluoride decomposed by electrical sparks has been found to by cytotoxic to hamster cells when tested in an in vitro cell survival assay, while SF₆ shows no cytotoxic activity. Chemical analysis of spark‐decomposed SF₆ has identified and quantified the following compounds: SOF₂, SO₂F₂, SF₄, SOF₄, SiF₄, SO₂ and HF. Each of these gases, at concentration ranges expected in spark‐decomposed SF₆, were tested for cytotoxic activity toward hamster cells. Of the gases showing cytotoxic activity, SO₂F₂ and SOF₄ were similar in activity, as were SOF₂ and SF₄, while the behavior of SiF₄ was different from the rest. None of these individual gases, at concentrations expected in spark‐decomposed SF₆, has sufficient cytotoxic activity to account for the cytotoxic effect of spark‐decomposed SF₆ observed in our assay system. A four‐component mixture of some of the gases enumerated above (at concentrations overestimating their abundance in spark‐decomposed SF₆) was much less cytotoxic than the spark‐decomposed SF₆ gas. A mathematical simulation of the cytotoxic activity of a mixture of gases at concentrations found in spark‐decomposed SF₆ was made, assuming independent cytotoxic effects from each component. The simulated cytotoxic effect thus computed was less than that seen in spark‐decomposed SF₆. Since individual components or mixtures of the major decomposition products do not account for the observed biological activity of spark‐decomposed SF₆, this suggests there may be one or more components, present in the spark‐decomposed gas at very low concentrations, which may have a very strong cytotoxic activity.     

Correlation between the seasonal distribution of harbour porpoises and their prey in the Sound,Baltic Sea

Low densities of harbour porpoises in winter (November–March) and high densities in summer (April–October) were found in the Sound, connecting the Baltic Sea and Kattegat. Due to their high energy requirements, it is hypothesized that the density of harbour porpoises is related to local prey abundance. This was tested by examining the stomach content of 53 harbour porpoises collected between 1987 and 2010 in the Sound (high season, 34 porpoises; low season, 19 porpoises). A total of 1,442 individual fish specimens from thirteen species were identified. Twelve of these were present in the high–porpoise density season and seven in the low-density season. The distribution of occurrence and the distribution of number of fish species were different between seasons, indicating a shift in prey intake between seasons. Furthermore, during the high-density season, the mean and total prey weight per stomach as well as the prey species diversity was higher. However, no difference was found in the number of prey species between the two seasons, indicating a higher quality of prey in the high-density season. Atlantic cod was found to be the main prey species in terms of weight in the high-density season while Atlantic herring and Atlantic cod were equally important during the low-density season. Prey availability and predictability are suggested as the main drivers for harbour porpoise distribution, and this could be caused by the formation of frontal zones in spring in the northern part of the Sound, leading to prey concentrations in predictable areas.     

Adsorptive separation of phosphate oxyanion from aqueous solution using an inorganic adsorbent

Phosphate removal from aqueous solution was explored using granular ferric hydroxide (GFH) as an inorganic adsorbent. Adsorption, desorption and kinetic studies were conducted on laboratory scale to evaluate the performance of GFH as an adsorbent for low concentrations of phosphate solution. The effect of pH on adsorption was investigated, and phosphate uptake was shown to decrease with an increase in solution pH, with maximum removal seen to occur at pH 3. The experimental data best fit the Temkin isotherm at both pH 3 and 4. Uptake of phosphate by GFH follows second-order kinetics, with the small particle range (76–200 μm) removing phosphate from the solution more rapidly than the larger particle range (710–850 μm). The kinetic results suggest that intra-particle diffusion is an important factor in phosphate adsorption onto GFH. Thermodynamic parameters (ΔG°, ΔH°, ΔS°) were evaluated, and the results indicated that the adsorption process was endothermic and spontaneous. This study demonstrates that GFH has potential to be used as a cost-effective adsorbent for phosphate removal from aqueous solution.     

Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour

In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.