Evaluating the social and ecological effectiveness of partially protected marine areas

Marine protected areas (MPAs) are a primary tool for the stewardship, conservation, and restoration of marine ecosystems, yet 69% of global MPAs are only partially protected (i.e., are open to some form of fishing). Although fully protected areas have well-documented outcomes, including increased fish diversity and biomass, the effectiveness of partially protected areas is contested. Partially protected areas may provide benefits in some contexts and may be warranted for social reasons, yet social outcomes often depend on MPAs achieving their ecological goals to distinguish them from open areas and justify the cost of protection. We assessed the social perceptions and ecological effectiveness of 18 partially protected areas and 19 fully protected areas compared with 19 open areas along 7000 km of coast of southern Australia. We used mixed methods, gathering data via semistructured interviews, site surveys, and Reef Life (underwater visual census) surveys. We analyzed qualitative data in accordance with grounded theory and quantitative data with multivariate and univariate linear mixed-effects models. We found no social or ecological benefits for partially protected areas relative to open areas in our study. Partially protected areas had no more fish, invertebrates, or algae than open areas; were poorly understood by coastal users; were not more attractive than open areas; and were not perceived to have better marine life than open areas. These findings provide an important counterpoint to some large-scale meta-analyses that conclude partially protected areas can be ecologically effective but that draw this conclusion based on narrower measures. We argue that partially protected areas act as red herrings in marine conservation because they create an illusion of protection and consume scarce conservation resources yet provide little or no social or ecological gain over open areas. Fully protected areas, by contrast, have more fish species and biomass and are well understood, supported, and valued by the public. They are perceived to have better marine life and be improving over time in keeping with actual ecological results. Conservation outcomes can be improved by upgrading partially protected areas to higher levels of protection including conversion to fully protected areas.     

Modeling scale up of anthropogenic impacts from individual pollinator behavior to pollination systems

Understanding how anthropogenic disturbances affect plant–pollinator systems has important implications for the conservation of biodiversity and ecosystem functioning. Previous laboratory studies show that pesticides and pathogens, which have been implicated in the rapid global decline of pollinators over recent years, can impair behavioral processes needed for pollinators to adaptively exploit floral resources and effectively transfer pollen among plants. However, the potential for these sublethal stressor effects on pollinator–plant interactions at the individual level to scale up into changes to the dynamics of wild plant and pollinator populations at the system level remains unclear. We developed an empirically parameterized agent-based model of a bumblebee pollination system called SimBee to test for effects of stressor-induced decreases in the memory capacity and information processing speed of individual foragers on bee abundance (scenario 1), plant diversity (scenario 2), and bee–plant system stability (scenario 3) over 20 virtual seasons. Modeling of a simple pollination network of a bumblebee and four co-flowering bee-pollinated plant species indicated that bee decline and plant species extinction events could occur when only 25% of the forager population showed cognitive impairment. Higher percentages of impairment caused 50% bee loss in just five virtual seasons and system-wide extinction events in less than 20 virtual seasons under some conditions. Plant species extinctions occurred regardless of bee population size, indicating that stressor-induced changes to pollinator behavior alone could drive species loss from plant communities. These findings indicate that sublethal stressor effects on pollinator behavioral mechanisms, although seemingly insignificant at the level of individuals, have the cumulative potential in principle to degrade plant–pollinator species interactions at the system level. Our work highlights the importance of an agent-based modeling approach for the identification and mitigation of anthropogenic impacts on plant–pollinator systems.     

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.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

Digital data sources and methods for conservation culturomics

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.     

Sulfamethoxazole removal from polluted water by immobilized photocatalysis

The photocatalytic activity of TiO₂ deposits (Degussa P25 and Millennium PC500) has been studied using sulfamethoxazole (SMX) as a model water pollutant and a UV fluorescent lamp as a light source (365 nm). Both catalysts have shown very similar properties in the photocatalytic degradation of SMX. Special attention has been given to the effect of the irradiation time, pH, and pollutant concentration. No mass-transfer limitations are observed. The degradation of SMX is accelerated at low concentration, and the photocatalytic degradation kinetics obey the Langmuir–Hinshelwood model, allowing the adsorption and apparent rate constants to be determined for both catalysts.     

Removal of acid yellow 36 using Box–Behnken designed photoelectro-Fenton: a study on removal mechanisms

Photoelectro-Fenton was applied for the removal of acid yellow 36 (AY36) from synthetic aqueous solution using iron electrodes. A Box–Behnken design was used for optimization of the effects of pH, H₂O₂ concentration, current density, and reaction time. Individual effects of these variables were more important than their interaction effects. The derived model was in good agreement with the experimental results. Total organic carbon was determined in solution and sludge in order to clarify the removal mechanism. Increase of H₂O₂ concentration and current density led to domination of oxidation and coagulation mechanisms, respectively. The effects of scavenging and inhibiting agents were also investigated: (1) presence of alcohols can reduce the efficiency through competition with dye for reaction with hydroxyl radicals; (2) anions (NO₃^?, HCO₃^?, and H₂PO₄^?) scavenged hydroxyl radicals and reduced decolorization of AY36.     

Analysis of dust distribution in silo during axial filling using computational fluid dynamics: Assessment on dust explosion likelihood

In this study, the dust distribution in a silo during axial filling was modelled using a commercial computational fluid dynamics (CFD) code. The work focused on the dust concentration distribution in the silo, for evaluating the likelihood of a dust explosion in the silo. The simulation was conducted using a combination of renormalized (RNG) k-epsilon and discrete phase models, with standard pressure interpolation and a second order upwind scheme. The predicted dust concentration distribution showed a good agreement with experimental data adopted from the literature. It was found that the dust concentration distribution was influenced by mean velocity and turbulence flow. The simulation results suggest that the cornstarch concentration inside the silo was always above the lower explosion limit (LEL), hence requiring a mitigating action or a control system to reduce the explosion risk.     

Bypassing the flush,creating new resources: analysing alternative sanitation futures in London

The flush toilet is an illogical form of sanitation from the point of view of water conservation, nutrient recovery and water pollution. Places such as London, with one of the oldest flushing toilet and sewer systems in the world, bears witness to the limits of its universal applicability through dwindling freshwater resources and polluted waterways. It is therefore important to develop new forms of sanitation infrastructure. An actor–network theory coevolution framework is used to explore and gain insights into the coevolution pathways for new types and paradigms of sanitation in London, where waterborne sanitation is currently prevalent. This approach shows that while flushing toilets are currently stable network configurations, there are coevolution pathways that would shift the system towards dry sanitation. The quantity of freshwater resources available for toilet flushing was the main actant cited for the development of these coevolution pathways.     

Inadvertent environmentalism and the action–value opportunity: reflections from studies at both ends of the generational spectrum

A recent turn towards a more contextually sensitive apprehension of the challenge of making everyday life less resource hungry has been partly underwritten by widespread evidence that the environmental values people commonly profess to hold do not often translate into correspondingly low impact actions. Yet sometimes the contexts of everyday life can also conspire to make people limit their consumption without ever explicitly connecting this to the environmental agenda. This paper considers this phenomenon with reference to UK studies from both ends of the generational spectrum. The first questioned how older people keep warm at home during winter and the second examined how young people get rid of no longer wanted possessions. Both found that, though the respondents involved were acting in certain ways that may be deemed comparatively low impact, they were hitherto relatively indifferent to the idea of characterising these actions as such. We outline three ways in which sustainability advocates might respond to the existence of such “inadvertent environmentalists” and consider how they might inspire studies that generate fresh intervention ideas instead of lingering on the dispiriting recognition that people do not often feel able to act for the environment.