Species are the fundamental units of biology, ecology and conservation, and progress in these fields is therefore hampered by widespread taxonomic bias and uncertainty. Numerous operational techniques based on molecular or phenotypic data have been designed to overcome this problem, yet existing procedures remain subjective or inconsistent, particularly when applying the biological species concept. We address this issue by developing quantitative methods for a classic technique in systematic zoology, namely the use of divergence between undisputed sympatric species as a yardstick for assessing the taxonomic status of allopatric forms. We calculated mean levels of differentiation in multiple phenotypic characters – including biometrics, plumage and voice – for 58 sympatric or parapatric species‐pairs from 29 avian families. We then used estimates of mean divergence to develop criteria for species delimitation based on data‐driven thresholds. Preliminary tests show that these criteria result in relatively few changes to avian taxonomy in Europe, yet are capable of extensive reassignment of species limits in poorly known tropical regions. While we recognize that species limits are in many cases inherently arbitrary, we argue that our system can be applied to the global avifauna to deliver taxonomic decisions with a high level of objectivity, consistency and transparency.

There is growing awareness that ‘nature-based solutions' (NbS) can help to protect us from climate change impacts while slowing further warming, supporting biodiversity and securing ecosystem services. However, the potential of NbS to provide the intended benefits has not been rigorously assessed. There are concerns over their reliability and cost-effectiveness compared to engineered alternatives, and their resilience to climate change. Trade-offs can arise if climate mitigation policy encourages NbS with low biodiversity value, such as afforestation with non-native monocultures. This can result in maladaptation, especially in a rapidly changing world where biodiversity-based resilience and multi-functional landscapes are key. Here, we highlight the rise of NbS in climate policy—focusing on their potential for climate change adaptation as well as mitigation—and discuss barriers to their evidence-based implementation. We outline the major financial and governance challenges to implementing NbS at scale, highlighting avenues for further research. As climate policy turns increasingly towards greenhouse gas removal approaches such as afforestation, we stress the urgent need for natural and social scientists to engage with policy makers. They must ensure that NbS can achieve their potential to tackle both the climate and biodiversity crisis while also contributing to sustainable development. This will require systemic change in the way we conduct research and run our institutions. This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions’.

No abstract

No abstract

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.