Land cover along hiking trails in a nature tourism destination: the Azores as a case study

Environment, Development and Sustainability - Tourists have become increasingly interested in certain aspects of their destination, including landscape and biodiversity elements, thereby promoting...     

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.     

Motivations for the use and consumption of wildlife products

The dominant approach to combating the illegal wildlife trade has traditionally been to restrict the supply of wildlife products. Yet conservationists increasingly recognize the importance of implementing demand-side interventions that target the end consumers in the trade chain. Their aim is to curb the consumption of wildlife or shift consumption to more sustainable alternatives. However, there are still considerable knowledge gaps in understanding of the diversity of consumer motivations in the context of illegal wildlife trade, which includes hundreds of thousands of species, different uses, and diverse contexts. Based on consultation with multiple experts from a diversity of backgrounds, nationalities, and focal taxa, we developed a typology of common motivations held by wildlife consumers that can be used to inform conservation interventions. We identified 5 main motivational categories for wildlife use: experiential, social, functional, financial, and spiritual, each containing subcategories. This framework is intended to facilitate the segmentation of consumers based on psychographics and allow the tailoring of interventions—whether behavior change campaigns, enforcement efforts, or incentive programs—to the specific context in which they will be used. Underlining the importance of consumer research and collaborating with local actors is an important step toward promoting a more systematic approach to the design of demand reduction interventions.     

Ecotoxicological evaluation of fungicides used in viticulture in non-target organisms

Environmental Science and Pollution Research - The effect of fungicides, commonly used in vine cultures, on the health of terrestrial and aquatic ecosystems has been poorly studied. The objective...     

Characterizing efforts to reduce consumer demand for wildlife products

The unsustainable trade in wildlife is a key threat to Earth's biodiversity. Efforts to mitigate this threat have traditionally focused on regulation and enforcement, and there is a growing interest in campaigns to reduce consumer demand for wildlife products. We aimed to characterize these behavior-change campaigns and the evidence of their impacts. We searched peer-reviewed and grey literature repositories and over 200 institutional websites to retrieve information on demand-reduction campaigns. We found 236 campaigns, mainly in the grey literature. Since the 1970s, the number of campaigns increased, although for over 15% a start date could not be found. Asia was the primary focus, although at the national level the United States was where most campaigns took place. Campaigns most often focused on a single species of mammal; other vertebrates groups, with the exception of sharks, received limited attention. Many campaigns focused on broad themes, such as the wildlife trade in general or seafood. Thirty-seven percent of campaigns reported some information on their inputs, 98% on strategies, 70% on outputs, 37% on outcomes (i.e., changes in the target audience), and 9% on impacts (i.e., biological changes or threat reduction). Information on outcomes and impacts was largely anecdotal or based on research designs that are at a high risk of bias, such as pre- and postcampaign comparisons. It was unclear whether demand-reduction campaigns had direct behavioral or biological impacts. The lack of robust impact evaluation made it difficult to draw insights to inform future efforts, a crucial part of effectively addressing complex issues, such as the wildlife trade. If demand-reduction campaigns are to become a cornerstone of the efforts to mitigate the unsustainable trade in wildlife, conservationists need to adopt more rigorous impact evaluation and a more collaborative approach that fosters the sharing of data and insights.     

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.     

Characterization of bedload intermittency near the threshold of motion using a Lagrangian sediment transport model

At the smallest scales of sediment transport in rivers, the coherent structures of the turbulent boundary layer constitute the fundamental mechanisms of bedload transport, locally increasing the instantaneous hydrodynamic forces acting on sediment particles, and mobilizing them downstream. Near the critical threshold for initiating sediment motion, the interactions of the particles with these unsteady coherent structures and with other sediment grains, produce localized transport events with brief episodes of collective motion occurring due to the near-bed velocity fluctuations. Simulations of these flows pose a significant challenge for numerical models aimed at capturing the physical processes and complex non-linear interactions that generate highly intermittent and self-similar bedload transport fluxes. In this investigation we carry out direct numerical simulations of the flow in a rectangular flat-bed channel, at a Reynolds number equal to Re = 3632, coupled with the discrete element method to simulate the dynamics of spherical particles near the bed. We perform two-way coupled Lagrangian simulations of 48,510 sediment particles, with 4851 fixed particles to account for bed roughness. Our simulations consider a total of eight different values of the non-dimensional Shields parameter to study the evolution of transport statistics. From the trajectory and velocity of each sediment particle, we compute the changes in the probability distribution functions of velocities, bed activity, and jump lengths as the Shields number increases. For the lower shear stresses, the intermittency of the global bedload transport flux is described by computing the singularity or multifr actal spectrum of transport, which also characterizes the widespread range of transport event magnitudes. These findings can help to identify the mechanisms of sediment transport at the particle scale. The statistical analysis can also be used as an ingredient to develop larger, upscaled models for predicting mean transport rates, considering the variability of entrainment and deposition that characterizes the transport near the threshold of motion.     

Changing the Course of Rivers in an Asian City: Linking Landscapes to Human Benefits through Iterative Modeling and Design

Concerns over water scarcity, climate change, and environmental health risks have prompted some Asian cities to invest in river rehabilitation, but deciding on the end goals of rehabilitation is a complex undertaking. We propose a multidisciplinary framework linking riparian landscape change to human well‐being, providing information relevant to decision makers, in a format that facilitates stakeholder involvement. We illustrate this through a case study of the densely settled, environmentally degraded, and flood prone Ciliwung River flowing through metropolitan Jakarta, Indonesia. Our methodology attempts to respond to this complexity through an iterative approach, strongly based on conceptualization and mathematical modeling. Nested hydrologic, hydrodynamic, and water quality models provide outputs at catchment‐, corridor‐, and localized site‐scales. Advanced 3‐D landscape modeling is used for procedural design and precise visualization of proposed changes and their impacts, as predicted by the mathematical models. Finally, participatory planning and design methods allow us to obtain critical stakeholder feedback in shaping a socially acceptable approach. Our framework aims at demonstrating that a change in paradigm in river rehabilitation is possible, and providing future scenarios that balance concerns over flooding, water quality, and ecology, with the realities of a rapidly growing megacity.