Language matters for biodiversity.

Language is central to the way people learn about the natural world. A salient concern of the biodiversity conservation arena has been to understand how language can be employed by scientists to communicate knowledge to nonexpert audiences and build ecological literacy. The use of analogy and narrative by scientists are prominent techniques. In this article, we consider how these two modes of language-based reasoning extend into ordinary conversational language use by the public, specifically when articulating everyday understanding and experiences of biodiversity. Drawing on a process of public engagement in a UK woodland environment, a typological framework based on principles of analogical and narrative reasoning is developed to characterize the precise character of processes of everyday biodiversity sense making. The implications of the framework are discussed in the context of future biodiversity research, particularly its participatory and educational dimensions.

Nature, smells, and human wellbeing.

The link between nature and human wellbeing is well established. However, few studies go beyond considering the visual and auditory underpinnings of this relationship, even though engaging with nature is a multisensory experience. While research linking smell to wellbeing exists, it focuses predominantly on smells as a source of nuisance/offence. Smells clearly have a prominent influence, but a significant knowledge gap remains in the nexus of nature, smell, and wellbeing. Here, we examine how smells experienced in woodlands contribute to wellbeing across four seasons. We show that smells are associated with multiple wellbeing domains, both positively and negatively. They are linked to memories, and specific ecological characteristics and processes over space/time. By making the link between the spatiotemporal variability in biodiversity and wellbeing explicit, we unearth a new line of enquiry. Overall, the multisensory experience must be considered by researchers, practitioners, policy-makers and planners looking to improve wellbeing through nature.

The features and processes underpinning high-quality data generation in participatory research and engagement activities.

Participatory approaches are widely used by researchers to gather data and insight about how the environment is perceived, valued and used. The participatory activities may be creating information as part of curiosity-driven blue-skies research or to inform policy/practise decision-making.The quality and usability of data derived from participatory approaches are heavily influenced by how activities are conducted. We share a set of features and processes that underpin the generation of high-quality data, based on our collective experience of developing and undertaking participatory activities with an environmental and conservation focus.We propose four general features: (a) Depth and breadth of engagement; (b) robustness of the approach; (c) allowing space for surprises; (d) usability across contexts. We also provide a practical toolbox of processes, and associated facilitation techniques, which can be employed to maximise participant engagement and generate quality data.The features and processes are a practical guide for project leaders/teams to consider in the context of their work, rather than a set of inflexible rules. They should be relevant regardless of the participatory methods used, or the research, policy or practice setting being addressed.

Do ecosystem service frameworks represent people's values?

Since the Millennium Ecosystem Assessment was published, a plethora of ecosystem service frameworks have been developed to conceptualise the links between the natural environment and society. The intended geographic scales of application, the policy/practice context, and the scientific disciplines involved have driven variations in how the frameworks are constructed. However, the frameworks are homogenous in that they have been created predominately based on expert opinions and views of how ecosystem services are structured. Here, we use the Common International Classification of Ecosystem Services (CICES) to examine the extent to which frameworks capture people's values for British woodlands. Our findings reveal several disparities between how experts and the public conceptualise ecosystem services. The considerable refinement and specificity provided by CICES does not align with public values (e.g. some provisioning, and regulation and maintenance, services), which tend to be more generalised. We also demonstrate differences in values explained by social characteristics (e.g. ethnicity) that need to be accounted for in decision-making processes. Moving forwards, we need to consider how society views the services derived from nature and reflect this in frameworks to ensure ecosystem service approaches are effective, transparent and widely supported.

Species identification by conservation practitioners using online images: accuracy and agreement between experts.

Emerging technologies have led to an increase in species observations being recorded via digital images. Such visual records are easily shared, and are often uploaded to online communities when help is required to identify or validate species. Although this is common practice, little is known about the accuracy of species identification from such images. Using online images of newts that are native and non-native to the UK, this study asked holders of great crested newt (Triturus cristatus) licences (issued by UK authorities to permit surveying for this species) to sort these images into groups, and to assign species names to those groups. All of these experts identified the native species, but agreement among these participants was low, with some being cautious in committing to definitive identifications. Individuals' accuracy was also independent of both their experience and self-assessed ability. Furthermore, mean accuracy was not uniform across species (69-96%). These findings demonstrate the difficulty of accurate identification of newts from a single image, and that expert judgements are variable, even within the same knowledgeable community. We suggest that identification decisions should be made on multiple images and verified by more than one expert, which could improve the reliability of species data.