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.     

Society for environmental geochemistry and health twelth European meeting contaminated land call for papers

Society for environmental geochemistry and health twelth European meeting contaminated land call for papers     

A method for facilitating the use of algae growing on tree trunks as bioindicators of air quality

The abundance of epiphytic green algae has been observed to correlate strongly with air quality in several studies. In contrast to lichens, the abundance of green algae is difficult to measure accurately by visual observation. A new method based on photography and digital image processing was developed to estimate the chlorophyll content of algae growing on the bark of pine. Calibration data for the method was collected from polluted areas by spectrophotometric analysis of chlorophyll density.     

Identifying taxonomic and functional surrogates for spring biodiversity conservation

Surrogate approaches are widely used to estimate overall taxonomic diversity for conservation planning. Surrogate taxa are frequently selected based on rarity or charisma, whereas selection through statistical modeling has been applied rarely. We used boosted‐regression‐tree models (BRT) fitted to biological data from 165 springs to identify bryophyte and invertebrate surrogates for taxonomic and functional diversity of boreal springs. We focused on these 2 groups because they are well known and abundant in most boreal springs. The best indicators of taxonomic versus functional diversity differed. The bryophyte Bryum weigelii and the chironomid larva Paratrichocladius skirwithensis best indicated taxonomic diversity, whereas the isopod Asellus aquaticus and the chironomid Macropelopia spp. were the best surrogates of functional diversity. In a scoring algorithm for priority‐site selection, taxonomic surrogates performed only slightly better than random selection for all spring‐dwelling taxa, but they were very effective in representing spring specialists, providing a distinct improvement over random solutions. However, the surrogates for taxonomic diversity represented functional diversity poorly and vice versa. When combined with cross‐taxon complementarity analyses, surrogate selection based on statistical modeling provides a promising approach for identifying groundwater‐dependent ecosystems of special conservation value, a key requirement of the EU Water Framework Directive.     

Occupationally Oriented Medical Rehabilitation and Hairdressers’ Work Techniques–A one-and-a-half-year follow-up

This study examined changes in work techniques and musculoskeletal symptoms after occupationally oriented medical rehabilitation arranged for 21 hairdressers who were experiencing neck-shoulder or back pain but were still able to work. OWAS (Ovako Working Posture Analysing System) analyses of working postures and questionnaire data were obtained at the beginning of the courses and one and a half years later. The participants worked with their back bent and twisted or their arms at or over shoulder level more seldom (p < .0001) at the end of the follow-up than at the beginning of the rehabilitation. Subjective work-related physical and mental strain had decreased by 45.4% (p < .001) and 27.1% (p < .05), respectively, and subjective neck and back pain by 40.0% (p < .0 1 ) and 45.3% (p < .01). respectively. This’study suggests that occupationally oriented medical rehabilitation can have significant and long-lasting effects on the rehabilitee’s work techniques and subjective well-being.     

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.     

The “Seili-index” for the Prediction of Chlorophyll-α Levels in the Archipelago Sea of the northern Baltic Sea,southwest Finland

Environmental Modeling & Assessment - To build a forecasting tool for the state of eutrophication in the Archipelago Sea, we fitted a Generalized Additive Mixed Model (GAMM) to marine...     

A conceptual model of the social–ecological system of nature-based solutions in urban environments

This article provides a perspective on nature-based solutions. First, the argument is developed that nature-based solutions integrate social and ecological systems. Then, theoretical considerations relating to relational values, multifunctionality, transdisciplinarity, and polycentric governance are briefly outlined. Finally, a conceptual model of the social–ecological system of nature-based solutions is synthesised and presented. This conceptual model comprehensively defines the social and ecological external and internal systems that make up nature-based solutions, and identifies theoretical considerations that need to be addressed at different stages of their planning and implementation The model bridges the normative gaps of existing nature-based solution frameworks and could be used for consistent, comprehensive, and transferable comparisons internationally. The theoretical considerations addressed in this article inform practitioners, policymakers, and researchers about the essential components of nature-based solutions. The conceptual model can facilitate the identification of social and ecological interconnections within nature-based solutions and the range of stakeholders and disciplines involved.     

Predicting the decomposition of Scots pine, Norway spruce, and birch stems in Finland.

Models were developed for predicting the decomposition of dead wood for the main tree species in Finland, based on data collected from long-term thinning experiments in southern and central Finland. The decomposition rates were strongly related to the number of years after tree death. In contrast to previous studies, which have used the first-order exponential model, we found that the decomposition rate was not constant. Therefore, the Gompertz and Chapman-Richard's functions were fitted to the data. The slow initial decomposition period was mainly due to the fact that most dead trees remained standing as snags after their death. The initial period was followed by a period of rapid decomposition and, finally, by a period of moderately slow decomposition. Birch stems decomposed more rapidly than Scots pine and Norway spruce stems. Decomposition rates of Norway spruce stems were somewhat lower than those of Scots pine. Because the carbon concentration of decaying boles was relatively stable (about 50%) the rate of carbon loss follows that of mass loss. Models were also developed for the probability that a dead tree remains standing as a snag. During the first years after death, the probability was high. Thereafter, it decreased rapidly, the decrease being faster for birch stems than for Scots pine and Norway spruce stems. Almost all stems had fallen down within 40 years after their death. In Scots pine and Norway spruce, most snags remained hard and belonged to decay class 1. In birch, a higher proportion of snags belonged to the more advanced decay classes. The models provide a framework for predicting dead wood dynamics in managed as well as dense unthinned stands. The models can be incorporated into forest management planning systems, thereby facilitating estimates of carbon dynamics.