新型锰氧化菌株Pseudoxanthomonas mexicana S5-3-5X的分离及锰氧化机理研究

锰氧化微生物能催化氧化Mn^II生成锰氧化物（Mn^IV&III）,而生成的锰氧化物可强化水处理体系（如锰砂滤池、湿地）中的微量有机污染物降解及底泥中甲烷的厌氧氧化,因而受到广泛研究.从环境中分离出更多种属和生态位的锰氧化菌是生物强化环境中锰氧化过程的重要基础.依据锰氧化菌株对低浓度营养物的潜在偏好,本研究梯度稀释常用的锰氧化菌培养基（PYG培养基）,配置出5级营养物梯度浓度的培养基.相对于原培养基,从较低浓度的4级培养基中多分离出6个菌属的锰氧化菌株,提高了锰氧化菌株的分离效率.分离出的Pseudoxanthomonas（假黄色单胞菌属）菌属的锰氧化菌株（Pseudoxanthomonas mexicana S5-3_-5X）,属中文文献首次报道.研究发现该菌株能在环境常见条件（pH 6.0~7.8、低营养物浓度（如稀释5~625倍PYG培养基）、50 μmol·L^-1 ~1.6 mmol·L^-1的Mn^II浓度）生长并产生锰氧化活性;可以产生胞外超氧化物和锰氧化蛋白等锰氧化活性物质;基因组具有编码锰氧化模式菌株Pseudomonas putida GB-1的3个Mn^II氧化蛋白的同源基因,并且具有降解一些有机污染物的代谢通路.因此,该菌株具有较好的工程应用潜力.     

Achieving a real-time online monitoring system for conservation culturomics

Environmental monitoring is increasingly shifting toward a set of systems that describe changes in real time. In ecology specifically, a series of challenges have prevented the rollout of real-time monitoring for features such as biodiversity change or ecosystem service provision. Conservation culturomics, a field concerned with interactions between people and nature, is well placed to demonstrate how monitoring might move toward a network of real-time platforms, given its existence exclusively in the digital realm. We examined a set of considerations associated with the development of real-time monitoring platforms for conservation culturomics and introduce a near real-time platform for the Species Awareness Index, a global index of changing biodiversity awareness derived from the rate of change in page views for species on Wikipedia. This platform will update automatically each month, operating in near real time ( https://joemillard.shinyapps.io/Real_time_SAI/ ). There are plans to make the underlying data queryable via an application programing interface independent of the platform. The real-time Species Awareness Index will represent the first real-time and entirely automated conservation culturomic platform and one of the first real-time platforms in the discipline of ecology. Real-time monitoring for culturomics can provide insight into human–nature interactions as they play out in the physical realm and provide a framework for the development of real-time monitoring in ecology. Real-time monitoring metrics can be processed on private virtual machines and hosted on publicly available cloud services. Conservation now needs an online, real-time observatory that can evolve with the structure of the web.     

How to address data privacy concerns when using social media data in conservation science

Social media data are being increasingly used in conservation science to study human–nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.     

Sentiment analysis as a measure of conservation culture in scientific literature

Culturomics is emerging as an important field within science, as a way to measure attitudes and beliefs and their dynamics across time and space via quantitative analysis of digitized data from literature, news, film, social media, and more. Sentiment analysis is a culturomics tool that, within the last decade, has provided a means to quantify the polarity of attitudes expressed within various media. Conservation science is a crisis discipline; therefore, accurate and effective communication are paramount. We investigated how conservation scientists communicate their findings through scientific journal articles. We analyzed 15,001 abstracts from articles published from 1998 to 2017 in 6 conservation-focused journals selected based on indexing in scientific databases. Articles were categorized by year, focal taxa, and the conservation status of the focal species. We calculated mean sentiment score for each abstract (mean adjusted z score) based on 4 lexicons (Jockers-Rinker, National Research Council, Bing, and AFINN). We found a significant positive annual trend in the sentiment scores of articles. We also observed a significant trend toward increasing negativity along the spectrum of conservation status categories (i.e., from least concern to extinct). There were some clear differences in the sentiments with which research on different taxa was reported, however. For example, abstracts mentioning lobe finned fishes tended to have high sentiment scores, which could be related to the rediscovery of the coelacanth driving a positive narrative. Contrastingly, abstracts mentioning elasmobranchs had low scores, possibly reflecting the negative sentiment score associated with the word shark. Sentiment analysis has applications in science, especially as it pertains to conservation psychology, and we suggest a new science-based lexicon be developed specifically for the field of conservation.     

Using Wikipedia to measure public interest in biodiversity and conservation

The recent growth of online big data offers opportunities for rapid and inexpensive measurement of public interest. Conservation culturomics is an emerging research area that uses online data to study human–nature relationships for conservation. Methods for conservation culturomics, though promising, are still being developed and refined. We considered the potential of Wikipedia, the online encyclopedia, as a resource for conservation culturomics and outlined methods for using Wikipedia data in conservation. Wikipedia's large size, widespread use, underlying data structure, and open access to both its content and usage analytics make it well suited to conservation culturomics research. Limitations of Wikipedia data include the lack of location information associated with some metadata and limited information on the motivations of many users. Seven methodological steps to consider when using Wikipedia data in conservation include metadata selection, temporality, taxonomy, language representation, Wikipedia geography, physical and biological geography, and comparative metrics. Each of these methodological decisions can affect measures of online interest. As a case study, we explored these themes by analyzing 757 million Wikipedia page views associated with the Wikipedia pages for 10,099 species of birds across 251 Wikipedia language editions. We found that Wikipedia data have the potential to generate insight for conservation and are particularly useful for quantifying patterns of public interest at large scales.     

Evaluating global interest in biodiversity and conservation

The first target of the Convention for Biological Diversity (Aichi target 1) was to increase public awareness of the values of biodiversity and actions needed to conserve it—a key prerequisite for other conservation targets. Monitoring success in achieving this target at a global scale has been difficult; however, increased digitization of human life in recent decades has made it easier to measure people's interests at an unprecedented scale and allows for a more comprehensive evaluation of Aichi target 1 than previously attempted. We used Google search volume data for over a thousand search terms related to different aspects of biodiversity and conservation to evaluate global interest in biodiversity and its conservation. We also investigated the correlation of interest in biodiversity and conservation across countries to variables related to biodiversity, economy, demography, research, education, internet use, and presence of environmental organizations. From 2013 to 2020, global searches for biodiversity components increased, driven mostly by searches for charismatic fauna (59% of searches were for mammal species). Searches for conservation actions, driven mostly by searches for national parks, decreased since 2019, likely due to the COVID-19 pandemic. Economic inequality was negatively correlated with interest in biodiversity and conservation, whereas purchasing power was indirectly positively correlated with higher levels of education and research. Our results suggest partial success toward achieving Aichi target 1 in that interest in biodiversity increased widely, but not for conservation. We suggest that increased outreach and education efforts aimed at neglected aspects of biodiversity and conservation are still needed. Popular topics in biodiversity and conservation could be leveraged to increase awareness of other topics with attention to local socioeconomic contexts.     

Sentiment analysis of the Twitter response to Netflix's Our Planet documentary

The role of nature documentaries in shaping public attitudes and behavior toward conservation and wildlife issues is unclear. We analyzed the emotional content of over 2 million tweets related to Our Planet, a major nature documentary released on Netflix, with dictionary and rule-based automatic sentiment analysis. We also compared the sentiment associated with species mentioned in Our Planet and a set of control species with similar features but not mentioned in the documentary. Tweets were largely negative in sentiment at the time of release of the series. This effect was primarily linked to the highly skewed distributions of retweets and, in particular, to a single negatively valenced and massively retweeted tweet (>150,000 retweets). Species mentioned in Our Planet were associated with more negative sentiment than the control species, and this effect coincided with a short period following the airing of the series. Our results are consistent with a general negativity bias in cultural transmission and document the difficulty of evoking positive sentiment, on social media and elsewhere, in response to environmental problems.