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Integrated distribution models (IDMs), in which datasets with different properties are analysed together, are becoming widely used to model species distributions and abundance in space and time. To date, the IDM literature has focused on technical and statistical issues, such as the precision of parameter estimates and mitigation of biases arising from unstructured data sources. However, IDMs have an unrealised potential to estimate ecological properties that could not be properly derived from the source datasets if analysed separately. We present a model that estimates community alpha diversity metrics by integrating one species‐level dataset of presence–absence records with a co‐located dataset of group‐level counts (i.e. lacking information about species identity). We illustrate the ability of community IDMs to capture the true alpha diversity through simulation studies and apply the model to data from the UK Pollinator Monitoring Scheme, to describe spatial variation in the diversity of solitary bees, bumblebees and hoverflies. The simulation and case studies showed that the proposed IDM produced more precise estimates of the community diversity than the single models, and the analysis of the real dataset further showed that the alpha diversity estimates from the IDM were averages of the single models. Our findings also revealed that IDMs had a higher prediction accuracy for all the insect groups in most cases, with this performance linked to the information provided by a data source into the IDM. [ABSTRACT FROM AUTHOR]

Humanity benefits immensely from nature, including through cultural ecosystem services. Geotagged crowdsourced data provide an opportunity to characterize these services at large scales. Flickr data, for example, have been widely used as an indicator of recreational value, while Wikipedia data are increasingly being used as a measure of public interest, potentially capturing often overlooked and less-tangible aspects of socio-cultural values (such as educational, inspirational, and spiritual values). So far, few studies have explored how various geotagged crowdsourced data complement each other, or how correlated these may be, particularly at national scales. To address this knowledge gap, we compare Flickr and Wikipedia datasets in their ability to help characterize the sociocultural value of designated areas in England and assess how this value relates to species richness. Our results show that there was at least one Flickr photo in 35% of all designated areas in England, and at least one Wikipedia page in 60% of them. The Wikipedia and Flickr data were shown not to be independent of each other and were significantly correlated. Species richness was positively and significantly associated with the presence of at least one geotagged Wikipedia page; more biodiverse designated areas, however, were not any more likely to have at least one Flickr photo within them. Our results highlight the potential for new, emerging datasets to capture and communicate the socio-cultural value of nature, building on the strengths of more established crowdsourced data. [ABSTRACT FROM AUTHOR]

This article is an editorial on the topic of biodiversity informatics, which is the use of computer technology to manage, analyze, and interpret biological data. The field of biodiversity informatics focuses on areas such as taxonomy and genomics, ecological modeling, data management and sharing, and citizen science. The article discusses the challenges and opportunities in biodiversity informatics in South Africa, including data sharing, digitization, and data management practices. It also addresses the role of biodiversity informatics in addressing issues such as invasive species, climate change, habitat fragmentation, and community engagement. The article concludes by highlighting the anticipated growth of biodiversity informatics and the key developments that will support effective biodiversity management and conservation. [Extracted from the article]

Biodiversity targets are a key tool, used at a global and national policy level, to align biodiversity goals, promote conservation action, and recover nature. Yet most biodiversity targets are not met. In England, the government has committed to legally‐binding targets to halt and recover the decline in species abundance by 2030 and 2042. We present evidence from recent population trends of 670 terrestrial animal species (for which abundance time series are available) as a species abundance indicator, together with a synthesis of case studies on species recovery, to assess the degree to which these targets are achievable. The case studies demonstrate that recovery is possible through a range of approaches. The indicator demonstrates that theoretically targets can be achieved by addressing severe declines in a relatively small number of species, as well as creating smaller benefits for many species through landscape‐scale interventions. The fact that multiple pathways exist to achieve the species abundance targets in England presents choices but also raises the possibility that targets might be reached with perverse consequences. We demonstrate that evidence on achievability is a necessary but not sufficient condition for determining what is required to deliver conservation outcomes and restore biodiversity. [ABSTRACT FROM AUTHOR]